Second edition - SUCKHOENOITIET.VN · Second edition The mission of the International Diabetes...

Second edition

The mission of the International Diabetes Federation is to

work with our member associations to enhance the lives

of people with diabetes.

Second edition

DIABETES

ATLAS

Diabetes Atlas Second Edition Diabetes Atlas Second Edition

Diabetes Atlas committeeBjørnar Allgot (co-chair)Delice Gan (co-chair)Hilary KingPierre LefèbvreJean-Claude MbanyaMartin SilinkLinda SiminerioRhys WilliamsPaul Zimmet

Editor and project manager: Delice GanProject coordinator: Catherine Regniers

Diabetes Atlas, second edition,and other IDF publications are available from:International Diabetes FederationExecutive Office19 Avenue Emile de MotB-1000 BrusselsBelgiumTel +32-2-5385511Fax [email protected]

Electronic version of Diabetes Atlas: www.idf.org/e-atlas

© International Diabetes Federation, 2003

No part of this publication may be reproduced or transmitted in any form or by any means without the prior written permission of the International Diabetes Federation.

First published, 2000Second edition, 2003

Permission has been obtained to use material from the following organizations:(1) United Nations(2) World Bank(3) World Health Organization

Copyright permission has been obtained from Martin Dunitz to adapt ‘The St Vincent Declaration: experience gained for better outcome of cardiovascular, eye and kidney complications in the future’ in Chapter 8.

ISBN 2-930229-27-6

Design and layout: perplex | Aalst, Belgium

Cover: De Blauwe Peer, Gent, Belgium

Printer: Imprimerie L Vanmelle SA, Gent/Mariakerke, Belgium

Diabetes Atlas Second Edition Diabetes Atlas Second Edition

Acknowledgements

Chapter 1

1.1 R Sicree, J Shaw, P Zimmet

1.2 R Tapp, J Shaw, P Zimmet

Chapter 2

2.1 G Soltèsz, C Patterson, G Dahlquist

2.2 R Singh, J Shaw, P Zimmet

Chapter 3

Introduction P Zimmet

3.1 N Rigby, RJ Leach, WPT James

3.2 CS Cockram, K Hynes

Chapter 4

R Williams

Chapter 5

J-C Mbanya, L Fezeu

Chapter 6

6.1 J Piette

6.2 L Siminerio

6.3 T Songer

Chapter 7

7.1 K Ramaiya, R Sicree, C Patterson

7.2 M Arab, AS Shera, R Sicree, C Patterson

7.3 M Massi-Benedetti, L Etu-Seppälä,

R Sicree, C Patterson

7.4 Y Vovides, B Wentzell, R Sicree,

C Patterson

7.5 A Pérez-Comas, R Sicree, C Patterson

7.6 H Mahtab, MA Sayeed, R Sicree,

C Patterson

7.7 G Bunyan, R Sicree, C Patterson

Chapter 8

8.1 M Massi-Benedetti, J Akwe Akwi,

P Ferolla, MO Federici

8.2 Y Vovides, B Wentzell

8.3 CS Cockram

Chapter 9

C Regniers, D Gan, B Allgot

Chapter 10

P Lefèbvre

Profiles

J Colquhoun, D Lukoseviciene, N Ojha,

G Rafique, M Silink

Appendix 2

A Hornsby

Special thanks to S Murray for coordinating the

work at the International Diabetes Institute.

The International Diabetes Federation (IDF)

would like to express its thanks to the World

Diabetes Foundation for its generous support

in making the Diabetes Atlas, second edition,

possible.

IDF would also like to thank Novo Nordisk A/S

for its generous support.

IDF would like to thank Novartis Pharma AG

for its generous support in making possible

the report on impaired glucose tolerance in

Chapter 1.

IDF would also like to thank Johnson and

Johnson for its generous support in making

possible the report on type 2 diabetes in the

young in Chapter 2.

A publication such as this would not have

been possible without the commitment and

contribution of many people around the

world. IDF would like to thank and gratefully

acknowledges the contributions of the

following authors:

Diabetes Atlas Second Edition

IDF also gratefully acknowledges the help of

the following people in making this publication

possible:

N Abdella, K Ajlouni, C Alexander, AS Alkuwari,

MC Almaraz, A Al-Nuaim, FI Al-Zurba, T Aspray,

V Augustiniene, B Balkau, TK Banerjee,

A Barceló, T Beljic, P Bennett, O Bernard,

C Berne, PR Betts, G Booth, E Briganti,

C Castell, A Chan, S-Y Chen, B Choi, P Chou,

LM Chuang, SS Chung, R Colagiuri, S Colagiuri,

M Comaschi, D Dabelea, M Dagmar, R Dankner,

H Dean, D De Bacquer, B Detournay,

CL de Visser, M Dragan, R Duarte, T Dwyer,

R Dyck, M Elbagir, M Eliasson, M Engelau,

J Eriksson, E Eskelinen, J Feinglass, E Ford,

MC Foss, M M-T Fuh, MM Garcia de Belaunde,

C Giorda, RT Go, A Goday, R Gupta, CH Han,

N Hancu, M Harris, J Harvey, L de Hassine,

GE Holder-Nelson, G Hu, C Invitti, ED Janus,

J Jervell, F Johansen, AJ Karter, S Kiauka,

T Kitagawa, D Koev, M Korecova, CF Kwok,

L Lavery, A Lerario, N Levitt, S Likitmaskul,

B McBride, M McGill, SM Makled, K Midthjell,

J Mohith, Z Naeemullah, P Nilsson,

W Nitiyanant, F Nobels, H-H Parving,

J Perusicova, G Piatt, E Placzkiewicz,

D Ragoobirsingh, A Ramachandran,

U Ramdanee, H Rashidi, W Rathmann,

I Raz, G Rennert, G Roglic, A Rotchford,

E Rudinskiene, M Sadikot, I Satman,

MA Sayeed, A Schranz, D Simon, A Sinha,

J Skrha, E Spichler, E Stern, S Tandhanand,

W Thefeld, R Toomath, J Tuomilehto, G Uwaifo,

K Van Acker, D Webb, S Wild, P Wilson, JP Yeo

IDF gratefully acknowledges the support and

help given by its member associations, task

forces and consultative sections.

Special thanks to L Al Obaidi, S Ash,

V Campanella de Lemes, L Cann, E Ng, N Ohja,

P Onraed, L Rabemananjara and Y Vovides for

their invaluable contribution in the regions.

Contents


5

Contents

Foreword 7Introduction 9Executive Summary 11

1. The Global Burden of Diabetes 15 1.1 Diabetes and Impaired Glucose Tolerance: Prevalence and Projections 17 1.2 Complications of Diabetes 72

2. Diabetes in the Young: a Global Perspective 113 2.1 Global Trends in Childhood Type 1 Diabetes 114 2.2 Type 2 Diabetes in the Young 135

3. The Widening Circle 157 3.1 Obesity 159 3.2 Cardiovascular Disease and Diabetes: Double Jeopardy 167

4. The Economic Impact of Diabetes 175

5. Access to Insulin and Diabetes Supplies 193

6. Diabetes Education 207 6.1 Effectiveness of Self-management Education 208 6.2 Educational Practices: a Global View 216 6.3 Cost-Effectiveness of Diabetes Education 221

7. Meeting the Challenges 225 7.1 Africa 226 7.2 Eastern Mediterranean and Middle East 231 7.3 Europe 237 7.4 North America 244 7.5 South and Central America 250 7.6 South-East Asia 255 7.7 Western Pacific 260

8. Reducing the Burden 267 8.1 The St Vincent Declaration 268 8.2 Declaration of the Americas on Diabetes 276 8.3 Western Pacific Declaration on Diabetes 278 8.4 Declaration of the Eastern Mediterranean and Middle East Region 280

Contents


6

9. Diabetes Associations: from Patients to Partners 283

10. Prevention and Strategic Action 301

Appendices Appendix 1 Methodology 305 Appendix 2 Socio-economic Indicators 316 Appendix 3 IDF Member Associations Address List 329

Glossary 345Acronyms 349World Diabetes Foundation 352Index 354 Index of Countries 357

Foreword


7

Foreword

Several years ago it was proposed by my predecessors that it would be helpful to bring together relevant data about diabetes and diabetes associations around the world. This culminated in the publication of the first edition of the Diabetes

Atlas at the 17th IDF Congress in Mexico. It was beautifully produced and instantly popular. It went to Ministers of Health in IDF member countries, WHO offices, diabetes associations and many others.

The Diabetes Atlas has proved to be an invaluable resource. It was decided that it should go on the IDF website to be updated regularly – but should reappear in hard copy for the 18th IDF Congress in Paris.

Many new sections have been included since the first edition. The epidemiology section has been updated, stressing again the rapid rise in prevalence, as has that on economics. A new section on impaired glucose tolerance (IGT) is included, giving an indication of the further rise in diabetes that is to come. This is the first time worldwide data on IGT have been collected together.

The prevalence of complications is now included – important for planners, health professionals and people with diabetes alike. It is also the first time that such information has been compiled in one publication. It is useful in showing not only the prevalence data but also the gaps in our knowledge in this area.

Another new chapter discusses the relationship between obesity and diabetes as well as the effect of diabetes on cardiovascular disease. The vital topic of access to insulin is also covered – an area of critical importance in many IDF member countries.

Diabetes education has an expanded section, emphasizing its role in the successful management of the disease. There are then very useful chapters on IDF regional activities and diabetes associations. Primary prevention and socio-economic indicators complete the text.

The evidence that we have shows beyond doubt that diabetes is on an epidemic increase and that the toll from this disease will be huge in economic, social and individual terms if action is not taken now.

There is also evidence that prevention of type 2 diabetes is possible. What remains now is for all of us – governments, health organizations, diabetes associations – to take the next step to use the knowledge that we have to curb the rise of diabetes and its complications.

Foreword


8

I personally feel that the second edition is a major step forward and will prove invaluable to governments and diabetes associations as well as individuals.Production of the Diabetes Atlas is a costly undertaking. We should acknowledge the time given by many colleagues in IDF and also our various sponsors, particularly the new charity the World Diabetes Foundation, without whom the second edition of the Diabetes Atlas would not have been possible.

Sir George AlbertiIDF President, 2000 - 2003

Introduction


9

Introduction

Since the publication of the first edition of the Diabetes Atlas in 2000, a number of things have changed. Our appreciation of the extent of the burden of diabetes in the world has been refined, our knowledge of the risks to health as a whole

and to diabetes in particular has increased and our conviction that type 2 diabetes is potentially preventable has been confirmed with solid evidence about the steps we need to make that potential a reality.

WHO and IDF continue their partnership in the fight to improve the wellbeing of people with diabetes and to include in this partnership other organizations with an important part to play in this endeavour.

In terms of the worldwide burden, the WHO Global Burden of Disease estimated that around 177 million people in the world had diabetes in the year 2000. This second edition of the Diabetes Atlas estimates 194 million in the year 2003, and around two-thirds of these people live in developing countries. The projections for the future provide no comfort at all. If current trends prevail, the above figure may well more than double by the year 2025. We also know that already as much as a quarter or even a third of acute sector health expenditures in some communities has to be devoted to diabetes and its long-term complications.

The World Health Report 2002 quantifies the impact of several major risk factors on current mortality and overall burden of disease. It brings into focus the importance of overweight and low levels of physical activity in increasing the risks of developing type 2 diabetes as well as a number of other conditions of enormous public health importance. In that Report it is estimated that 58% of the global burden of diabetes, 21% of ischaemic heart disease and 8-42% of certain cancers are attributable to BMI (body mass index) above 21 kg/m2.

Physical inactivity is related to diabetes risk both directly as a result of its effect on insulin sensitivity but also indirectly via obesity and the World Health Report estimates that 11-24% of people, depending on the region in which they live, are currently physically inactive.

The Report also quantifies the potential for future reduction of the burden of disease. A relatively modest 25% reduction of current and future obesity and physical inactivity could avoid at least one-half and one-third of the burden attributed to these respective risk factors in the year 2020. Several risk factors can be addressed in synergy with policies that promote a healthy diet and encourage physical activity.

Introduction


10

As long as diabetes exists, the need to manage it effectively will always be here. However, by slowing the incidence of new cases, through reducing levels of risk in the population as a whole and in those at high risk, the management of existing diabetes can surely only be improved.

Recently published randomized controlled trials provide clear proof that behavioural changes which lead to weight reduction and/or increased physical activity or the use of some widely available drugs can delay, or at least postpone, the transition from impaired glucose tolerance to type 2 diabetes. Such evidence provides hope that the current inexorable rise in the numbers of people with diabetes may, one day, be slowed or even reversed.

While we work towards this promising future, IDF’s Diabetes Atlas provides one way of tracking this epidemic and, more importantly, galvanizing IDF member associations, governments, industry and other committed organizations to take action. Action is needed now to ensure that people who already have diabetes can lead fuller and more productive lives and that there is some hope of reducing the number of people at risk of developing diabetes and its life-threatening complications.

Derek YachExecutive DirectorNoncommunicable Diseases and Mental Health ClusterWorld Health OrganizationGeneva

Executive Summary


11

Executive Summary

Many new topics have been included in the second edition of the Diabetes

Atlas to reflect the growing need to tackle the diabetes pandemic on all fronts. These topics emphasize the importance of looking not just at the epidemiology of diabetes but also at its risk factors, the management of the disease to prevent or delay complications and primary prevention of diabetes in high risk groups. This edition of the Atlas also shows the immense costs of diabetes, in financial and human terms, to both the individual and society as a whole.

The Diabetes Atlas therefore aims to communicate the global impact of diabetes and to underline the need for intervention now. In spite of the number of studies describing the epidemiology of diabetes, many governments and public health planners still remain largely unaware of the current magnitude, or, more importantly, the future potential for increases in diabetes and its serious complications in their own countries.

The second edition of the Diabetes Atlas extends coverage to 212 countries and territories around the world. It provides current estimates of the prevalence of diabetes and impaired glucose tolerance (IGT) as well as forecasts the estimates for 2025, forewarning of the enormous burden to come. The future predictions of cost are as alarming as the future predictions of prevalence. They suggest that unless effective prevention measures are introduced, expenditure devoted to diabetes and its complications will

dominate the health economies of many countries by the end of the first quarter of the current century.

The decision to include data on IGT was based on two major factors associated with its presence: a high sensitivity for future diabetes incidence and its association with future cardiovascular disease occurrence. IGT is now recognized as being a stage in the transition from normality to diabetes. Thus, individuals with IGT are at high risk of progressing to type 2 diabetes, although such progression is not inevitable. Some 70% of these individuals, however, are expected to develop the disease.

The reports in this edition of the Diabetes Atlas reconfirm that diabetes is now one of the most common non-communicable diseases globally. It is the fourth or fifth leading cause of death in most developed countries and there is substantial evidence that it is epidemic in many developing and newly industrialized nations.

It is estimated that currently some 194 million people worldwide, or 5.1% in the adult population, have diabetes and that this will jump to 333 million, or 6.3%, by 2025.

This situation is exacerbated by the estimated number of people with IGT – currently at 314 million, or 8.2% in the adult population, and expected to increase to 472 million, or 9.0%, by 2025.

It is estimated that currently some 194 million people worldwide, or 5.1% in the adult population, have diabetes and that this will jump to 333 million, or 6.3%, by 2025.

Executive Summary


12

Executive Summary


13

Type 2 diabetes constitutes about 85% to 95% of all diabetes in developed countries, and accounts for an even higher percentage in developing countries. It is now a serious global health problem, which, for most countries, has evolved in association with rapid cultural and social changes, ageing populations, increasing urbanization, dietary changes, reduced physical activity, and other unhealthy lifestyle and behavioural patterns. The change in lifestyle is a worldwide phenomenon, occurring in both developed and emerging nations, where it is most prevalent in urban areas.

The risk of developing type 2 diabetes is clearly linked to an increasing prevalence of obesity. Reports from the World Health Organization (WHO) and the International Obesity Task Force (IOTF) indicate that approximately 58% of diabetes mellitus globally can be attributed to body mass index above 21 kg/m2. However, there are indications that in western countries, around 90% of type 2 diabetes cases are attributable to weight gain.

Whereas previously type 2 diabetes affected only individuals in the older age groups, there are now ever increasing reports of type 2 diabetes in children worldwide, with some as young as eight years of age being affected. There is now growing recognition that type 2 diabetes in children is becoming a global public health issue with potentially serious health outcomes.

The purpose of the report on type 2 diabetes in the young is to call attention to this emergent problem by bringing together for the first time, the available epidemiological data on type 2 diabetes incidence and prevalence in the young from around the world. By the inclusion of such data it is hoped to highlight deficiencies in the knowledge of the disease and also to promote strategies to deal with it.

The studies on type 2 diabetes in children have important implications in that they highlight the risk of complications occurring at a relatively young age, which will place a significant burden on health budgets as well as society as a whole. Early detection and intervention is therefore essential to reduce the risk of future complications.

Governments will be forced to deal with the problem of type 2 diabetes in children in time to come. As such, it would be better to address the problem as a public health issue under the heading of primary care and prevention, rather than dealing with the consequences of an entrenched condition and its complications in a young population.

Although type 1 diabetes usually accounts for only a minority of the total burden of diabetes in a population it is the predominant form of the disease in younger age groups in most developed countries. The incidence of childhood onset diabetes is increasing in many countries in the world with an estimated overall annual increase of around 3%.

It is estimated that on an annual basis some 65,000 children worldwide under the age of 15 years develop type 1 diabetes. Of the estimated total of about 400,000 prevalent cases of type 1 diabetes in childhood, more than a quarter come from the South-East Asian Region, and more than a fifth from the European Region where reliable, up-to-date estimates of incidence were available for the majority of countries. The continued mapping of global trends in incidence of type 1 diabetes in all age groups is important, and in conjunction with other scientific research may provide a logical basis for intervention studies and future primary prevention strategies which must be the ultimate goal.

Executive Summary


12

Executive Summary


13

The new section on diabetic complications, which brings together available studies on the prevalence of the major complications, is a reminder of the urgent need for effective diabetes care. The main relevance of diabetes complications in a public health perspective is the relationship to human suffering and disability, and the huge socio-economic costs through premature morbidity and mortality. Indeed, diabetic complications are those aspects of the disease that are most feared such as blindness and amputation, and account for much of the social and financial burden of diabetes.

In virtually every developed society, diabetes is ranked among the leading causes of blindness, renal failure and lower limb amputation. Through its effects on cardiovascular disease(50-80% of people with diabetes die of cardiovascular disease), it is also now one of the leading causes of death.

Cardiovascular death rates on the whole are either high or appear to be climbing in countries where diabetes is prevalent. The outlook for cardiovascular disease (CVD) is alarming when one considers the number of people with diabetes worldwide and that this is set to more than double by 2025.

The recent decline in cardiovascular disease in the USA, Australasia and western Europe may be compromised significantly by this upsurge in diabetes. In other parts of the world where CVD have been proliferating in recent years, the additional impact of diabetes threatens to have devastating consequences.

The heavy financial burden is shown clearly in the chapter on the economic impact of diabetes in which estimates are made on the direct healthcare expenditure in countries covered by the Diabetes Atlas. The annual direct

healthcare costs of diabetes worldwide, for people in the 20-79 age group, is currently estimated to be at least 153 billion international dollars and may be as much as 286 billion.

If predictions of diabetes prevalence for 2025 are fulfilled, total direct healthcare expenditure on diabetes worldwide for that year will be between 213 billion and 396 billion international dollars. In some countries this will be as much as 40% of their total healthcare budget.

Even while sophisticated medical technology and new medications are being developed in one part of the world, one cannot ignore the fact that there are people dying from the simple lack of access to insulin in another part. Continuous accessibility to insulin is still a major problem in many developing countries especially those in sub-Saharan Africa such that there are reports of premature deaths due to the chronic lack of access to insulin in some of these countries. At the same time, although the medical aspects of diabetes care such as eye exams and blood glucose monitoring have improved in recent years, outcomes for many people with diabetes remain poor. While many factors contribute to poor outcome, this apparent contradiction also reflects the central role that people with diabetes themselves play in determining their health status, and the challenges associated with supporting their efforts to manage their self-care.

The expanded section on diabetes education clearly shows that diabetes education is now considered an integral part of diabetes care. Diabetes self-management education assists people in coping with the mental and physical demands of their illness, given their unique economic, cultural and social circumstances.

If predictions of diabetes prevalence for 2025 are fulfilled, total direct healthcare expenditure on diabetes worldwide for that year will be between 213 billion and 396 billion international dollars. In some countries this will be as much as 40% of their total healthcare budget.

Executive Summary


14

Diabetes self-management education is therefore a multi-faceted process involving much more than helping people with diabetes monitor their blood glucose, or take their medication as prescribed. Diabetes education must be an ongoing process rather than a one-time event because a person’s health status and need for support changes over time. More importantly, self-management education is most likely to be successful when it is part of a comprehensive and coordinated approach to diabetes care.

Education for people with diabetes has therefore become one of the key activities of diabetes associations and regional organizations, as evidenced in the Atlas. In facing the challenges brought about by the diabetes epidemic, diabetes associations and regional organizations have galvanized into action. Declarations on diabetes, spelling out strategic actions, have been signed in five regions – Eastern Mediterranean and Middle East, Europe, North America together with South and Central America, and Western Pacific.

These declarations also reflect the significance of strategic alliances at all levels with organizations such as the World Health Organization (WHO). At the global level, IDF is collaborating with WHO to embark on a major course of action, the ‘Global awareness, advocacy and action in diabetes’ programme. This programme aims to raise awareness about diabetes and its complications amongst the public, health professionals and decision makers, with major emphasis on prevention particularly in low income countries.

By promoting diabetes prevention, IDF will also ensure that those millions who already have diabetes will not face the nightmare of a regression in the quality of care they deserve while, on the contrary, there is a great need in many parts of the world to improve it.

The ultimate goal of a publication such as the Diabetes Atlas would be to stimulate research and concrete action by governments and all those concerned with health and wellbeing to stem the rising tide of diabetes in order to bring about better lives for all.

The Global Burden of DiabetesChapter 1

Diabetes Atlas Second Edition15

The Global Burden of Diabetes Chapter 1

Diabetes is now one of the most common non-communicable diseases

globally. It is the fourth or fifth leading cause of death in most developed countries and there is substantial evidence that it is epidemic in many developing and newly industrialized nations. Complications from diabetes, such as coronary artery and peripheral vascular disease, stroke, diabetic neuropathy, amputations, renal failure and blindness are resulting in increasing disability, reduced life expectancy and enormous health costs for virtually every society. Diabetes is certain to be one of the most challenging health problems in the 21st century.

The number of studies describing the epidemiology of diabetes over the last 20 years has been extraordinary, but many governments and public health planners still remain largely unaware of the current magnitude, or, more importantly, the future potential for increases in diabetes and its serious complications in their own countries.

In addition to diabetes, the condition of impaired glucose tolerance (IGT) also constitutes a major public health problem, both because of its association with diabetes incidence and its own association with an increased risk of the development of cardiovascular disease.

This chapter provides estimates of the prevalence of diabetes mellitus and IGT for 212 countries and territories for the years 2003 and 2025, so that some

1.1 Diabetes and Impaired Glucose Tolerance: Prevalence and Projections

1.2 Complications of Diabetes





concept of the likely future burden should be apparent. In adding to the scope of the first edition of the Diabetes Atlas, data are also provided on the prevalence of many of the complications of diabetes. The data on diabetes, IGT and diabetes complications were compiled at the International Diabetes Institute, Melbourne, Australia.

The data presented here should be cautiously interpreted as general indicators of diabetes frequency, and the estimates will need to be revised as new and better epidemiological information becomes available. When reporting data in this form, various assumptions need to be made that give rise to a number of limitations. Caution should be used when interpreting this report, and the data limitations will be discussed further throughout the text.

Comparisons of country, regional, and even global rates from one report to the next can be misleading and should be performed with extreme caution. Large changes in the prevalence or numbers of people with diabetes from one edition of the Diabetes Atlas to another are usually due to the use of a more recent study rather than a genuine change in the profile of diabetes within that country. Thus, the inclusion of recent, and more reliable research brings us closer to the actual rates of diabetes, but also brings with it dangers in comparing global reports and estimates over time. These limitations need always to be considered, and the reader must realize that the key purpose of a report such as this is to stimulate action in the form of preventive and management programmes, as well as further research.





1.1 Diabetes and Impaired Glucose Tolerance: Prevalence and Projections

The diagnosis of type 2 diabetes usually occurs after the age of 40 years although the age of onset is often a decade earlier in populations with a high diabetes prevalence (10). Type 2 diabetes can remain asymptomatic for many years and the diagnosis is often made from associated complications or incidentally through an abnormal blood or urine glucose test.

Type 2 diabetes is often, but not always, associated with obesity, which itself can cause insulin resistance and lead to elevated blood sugar levels. It is strongly familial, but major susceptibility genes have not yet been identified. In contrast to type 1 diabetes, persons with type 2 diabetes are not dependent on exogenous insulin and are not ketosis-prone, but may require insulin for control of hyperglycaemia if this is not achieved with diet alone or with oral hypoglycaemic agents.

Introduction

Diabetes mellitus and lesser forms of glucose intolerance, particularly impaired glucose tolerance, can now be found in almost every population in the world and epidemiological evidence suggests that, without effective prevention and control programmes, diabetes will likely continue to increase globally (1).

Major categories of glucose intoleranceDiabetes is recognized as a group of heterogeneous disorders with the common elements of hyperglycaemia and glucose intolerance due to insulin deficiency, impaired effectiveness of insulin action, or both (2).

Diabetes mellitus is classified on the basis of aetiology and clinical presentation of the disorder into four types:• type 1 diabetes • type 2 diabetes • gestational diabetes • other specific types

Type 1 diabetesType 1 diabetes results from cellular-mediated autoimmune destruction of pancreatic islet beta cells causing the loss of insulin production (3). It ranks as the most common chronic childhood disease in developed nations (4), but occurs at all ages (5) and the clinical presentation can vary with age (6, 7).

Type 2 diabetesType 2 diabetes is characterized by insulin resistance and relative insulin deficiency, either of which may be present at the time that diabetes becomes clinically manifest (8, 9). The specific reasons for the development of these abnormalities are not yet known.

All diabetes and IGT 2003 2025

Total world population (billions) 6.3 8.0Adult population (billions) (20-79 years) 3.8 5.3Number of people with diabetes (millions) (20-79 years) 194 333World diabetes prevalence (%) (20-79 years) 5.1 6.3Number of people with IGT (millions) (20-79 years) 314 472IGT prevalence (%) (20-79 years) 8.2 9.0

At a glance





Type 2 diabetes constitutes about 85 to 95% of all diabetes in developed countries (1), and accounts for an even higher percentage in developing countries. Type 2 diabetes is now a common and serious global health problem, which, for most countries, has evolved in association with rapid cultural and social changes, ageing populations, increasing urbanization, dietary changes, reduced physical activity and other unhealthy lifestyle and behavioural patterns (1).

Figure 1.1 highlights the large range of type 2 diabetes prevalence even within the same or similar ethnic groups, when living under different conditions. Clearly, many of the differences between these rates reflect underlying behavioural, environmental and social risk factors, such as diet, level of obesity and physical activity.

Within ethnic groups, high rates of type 2 diabetes are usually found in migrant

or urbanized populations that may have experienced a greater degree of lifestyle change. The lowest rates are generally found in rural communities where people are living lifestyles incorporating high levels of physical activity.

The incidence and prevalence of type 2 diabetes is also reported to be increasing in children. Studies from America and Japan have demonstrated an increasing incidence (12, 13). Other ethnic groups with high adult diabetes prevalence such as the Pima Indians (14) are also reporting increasing adolescent prevalences. The importance of this problem and the need for further research are emphasized by the authors of this chapter. A section collating studies on type 2 diabetes in children and adolescents has been included in Chapter 2.

Impaired glucose tolerance (IGT) is an asymptomatic condition defined by elevated (though not diabetic) levels of blood glucose two hours after a 75g oral

Figure 1.1Differences in the prevalence of type 2 diabetes among selected ethnic groups, 2003(adapted from King et al (11))

a. Rates are age-standardized to Segi’s World Population for ages 30 to 64 years

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glucose challenge. Along with impaired fasting glucose (IFG), it is now recognized as being a stage in the transition from normality to diabetes.

Thus, individuals with IGT are at high risk of progressing to type 2 diabetes, although such progression is not inevitable, and probably over 30% of individuals with IGT will return to normal glucose tolerance over a period of several years (15). Not surprisingly, IGT shares many characteristics with type 2 diabetes, being associated with obesity, advancing age, insulin resistance and an insulin secretory defect (16).

In addition to estimating the prevalence of diabetes for the years 2003 and 2025, data on case numbers and national prevalence of IGT are presented for both years in this section. The decision to include data on IGT was based on two major factors associated with its presence: a higher sensitivity for future diabetes incidence (17), and its association with future occurrence of cardiovascular disease (18, 19).

Gestational diabetes The most widely accepted definition of gestational diabetes mellitus (GDM) is “carbohydrate intolerance of varying degrees of severity with onset or first recognition during pregnancy” (20, 21). This definition applies regardless of whether insulin is used for treatment or the condition persists after pregnancy. It does not exclude the possibility that unrecognized glucose intolerance may have antedated the pregnancy.

It is widely believed that differences in reported prevalence of GDM parallel the differences that have been found in the frequency of type 2 diabetes among different populations. Nonetheless GDM is increasing in prevalence in concert with the worldwide rise in type 2 diabetes. Studies currently in progress hold much hope of providing the data from which ‘outcome based’ diagnostic criteria and

appropriate strategies for the detection of GDM can be developed.

Classification criteria and reporting standardsStandardization of methods and reporting in diabetes epidemiology promotes comparison between studies and may permit the pooling of results from different investigations (22, 23). Standardized criteria for detecting and reporting glucose intolerance have evolved greatly since the 1960s (24).

In the late 1970s both the US National Diabetes Data Group (NDDG) and the World Health Organization (WHO) produced new criteria on which to diagnose diabetes mellitus. In 1985, WHO modified their criteria to be more consistent with NDDG values. More recently, the American Diabetes Association (ADA) (25) and WHO (26) have produced new recommendations for the diagnosis of diabetes. The major change recommended is the lowering of the diagnostic value of the fasting plasma glucose concentration to 7.0 mmol/l. For glucose tested in whole blood, the new recommended threshold is 6.1 mmol/l (26).

In many population studies, individuals have been categorized as having diabetes mellitus based on blood glucose values measured after an overnight fast and/or two hours after a 75g oral glucose load. Whilst WHO still recommends the oral glucose tolerance test (OGTT) as being the single best choice, they also state that “if it is not possible to perform the OGTT (eg for logistical or economic reasons), the fasting plasma glucose alone may be used for epidemiological purposes” (26).

It is important to realize that different screening and diagnostic criteria may have been used for different studies in this report. The impact that the recent diagnostic cut-off level changes have on prevalence estimates seems to vary from country to country (27). In this section,





the criteria used will be reported when they are known.

Global estimates of diabetesThe global burden of diabetes has been estimated several times (28-31). In 1994, the International Diabetes Federation Directory (28) contained type 1 and type 2 diabetes estimates supplied by member nations. Using these data the International Diabetes Federation (IDF) estimated that over 100 million people worldwide had diabetes. Also in 1994, McCarty et al (29) used data from population-based epidemiological studies and estimated that the global burden of diabetes was 110 million in 1994 and that it would likely more than double to 239 million by 2010.

WHO (30) also produced a report using epidemiological information and estimated the global burden at 135 million in 1995, with the number reaching 299 million by the year 2025. In 1997, Amos et al (31) estimated the global burden of diabetes to be 124 million people, and projected that this would increase to 221 million people by the year 2010. Despite using different methodologies, and at times showing large differences in country-specific estimates, these reports have arrived at remarkably similar global figures of diabetes.

Methodology

The principal details of the methodology are provided in Appendix 1.1, where details of the rationale and process of obtaining age-specific prevalences for those countries with adequate data are given.

The principal aspects of the determination of prevalence were:

1 Identification of studies through a detailed literature search, and contact with IDF member organizations.

2 Employing the methodology indicated in Appendix 1.1 to create smoothed

curves for prevalence (with respect to age).

3 Applying the prevalence rates to the population distribution of that country, and where no data for countries were available, to those other countries of similar ethnicity and economic circumstances.

4 Assuming an urban:rural prevalence ratio of 2:1 for diabetes (but not IGT), except in those countries classified by WHO (30) as market economies, or former socialist economies. The urban proportion of the population was derived from UN estimates (32). The only other exception to this2:1 urban:rural prevalence ratio was for India (and Nepal, for which data were derived from India), for which the cited data indicated that the urban:rural ratio was nearer to 4:1 for diabetes prevalence (33, 34).

5 The data for diabetes rates include both type 1 and type 2 diabetes, with a separate chapter providing estimates on type 1 diabetes in children and adolescents (see Chapter 2).

6 The prevalence of diabetes throughout the Diabetes Atlas includes both undiagnosed and previously diagnosed diabetes.

This section contains prevalence estimates of diabetes and IGT for the years 2003 and 2025, and although the Tables contain data listed to one decimal point, it should not be inferred that this indicates the degree of precision, but rather to facilitate calculations and the appearance of the tables. In general, no predictions of diabetes or IGT numbers should be taken as having reliability of more than one significant figure.

The consequence of applying current age and gender specific prevalence rates to estimate 2025 prevalences and number of cases is that only changes in the age and urban/rural distribution of the population will affect the estimates. Since it is likely that the age specific prevalence





rates (the prevalence at any given age) will rise due to increasing obesity, the figures are probably underestimates.

Results

The main aim of this section is to estimate the prevalence of diabetes mellitus and IGT for each country for the years 2003 and 2025. Data are provided for 212 countries and territories, which have been allocated mostly on a geographical basis into one of the seven IDF regions: Africa (AFR), Eastern Mediterranean and Middle East (EMME), Europe (EUR), North America (NA), South and Central America (SACA), South-East Asia (SEA) and Western Pacific (WP).

Rates for each country have not been age-standardized, but are presented as the crude rates for the specific country and region according to the number of persons aged 20-79 years for that national and geographical entity.

The data presented are for all diabetes and IGT for adults from 20 to 79 years, and relate only to individuals 20 years of age or older because the majority of people who have type 2 diabetes and IGT are adults. Type 2 diabetes in children and adolescents is acknowledged as a very important and growing problem (see Chapter 2).

Furthermore as the emphasis is on numbers of persons with diabetes and IGT for each country, prevalence rates are markedly affected by the population age distribution so that those countries with older age distributions will inevitably have higher crude prevalences for the 20-79 year age group. It should be noted that column numbers in the Tables may not always exactly be the sum of the components because of rounding effects.

DemographyThe total populations and the population aged from 20-79 years are shown in Figure 1.2. It is clear that the Western

Figure 1.2World population (20-79 age group) by region

Figure 1.3Prevalence of diabetes (20-79 age group) by region

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Pacific Region, which has China as a member, and the South-East Asian Region, which has India as a member, have the greatest numbers in people.





DiabetesPrevalence In 2003, it is estimated that approximately 194 million people worldwide, or 5.1% in the age group 20-79, have diabetes. This estimate is expected to increase to some 333 million, or 6.3% in the adult population, by 2025.

The European Region with 48 million and Western Pacific Region with 43 million currently have the highest number of people with diabetes. However the prevalence rate of 3.1% for the Western Pacific Region is significantly lower than 7.9% in the North American Region and 7.8% in the European Region as seen in Figure 1.3.

By 2025, the region with the greatest number of persons with diabetes is expected to change to the South-East Asian Region with about 82 million as shown in Figure 1.4. The region’s prevalence of 7.5% will however continue to be lower than that of North America, estimated at 9.7%, and Europe at 9.1%.

Age distribution The 40-59 age group currently has the greatest number of persons with diabetes. By 2025, because of the ageing of the world’s population, there will be 146 million aged 40-59 and 147 million aged 60 or older.

Gender distribution The estimates for both 2003 and 2025 showed a female predominance in the number of persons with diabetes. The female numbers were about 10% higher than for males.

Urban/rural distribution In 2003, the number of people with diabetes in urban areas was 78 million, compared to 44 million persons with diabetes in rural areas in countries not considered to be established market economies, or former socialist economies. By 2025, it is expected that this discrepancy will increase to

Figure 1.4Number of people with diabetes (20-79 age group) by region

Figure 1.5Prevalence of impaired glucose tolerance (20-79 age group) by region

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Figure 1.7Estimated prevalence of diabetes and impaired glucose tolerance (20-79 age group) by region

182 million urban and 61 million rural persons with diabetes.

Impaired Glucose TolerancePrevalence In 2003, it is estimated that approximately 314 million people worldwide, or 8.2% in the age group 20 – 79, have IGT. By 2025, the number of people with IGT is projected to increase to 472 million, or 9.0% in the adult population.

The South-East Asian Region currently has the highest number of people with IGT with some 93 million and the highest prevalence rate with 13.2%. While the Western Pacific Region is the next highest in terms of number with about 78 million, its prevalence rate of 5.7% is the lowest compared with the other regions as seen in Figure 1.5.

By 2025, the trend is expected to continue with the South-East Asian Region leading in prevalence with 13.5% and in number with some 146 million people as seen in Figure 1.6. The prevalence of IGT in the European Region will remain the next highest with 10.9%.

As can be seen in Figure 1.7, the prevalence of IGT is more than twice that of diabetes in the African and South-East Asian Regions, whereas in the Eastern Mediterranean and Middle East, and North American Regions the prevalence of IGT is slightly lower than that of diabetes.

Age distribution As with diabetes, the 40-59 age group currently has the greatest number of persons with IGT and this will remain true by 2025.

Gender distribution There was also a female predominance in the number of persons with IGT in the estimates for both 2003 and 2025. The female numbers were about 20% higher than for males.

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Figure 1.6Number of people with impaired glucose tolerance(20-79 age group) by region

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Regional estimates for diabetes and IGT for 2003 and 2025 are shown in Table 1.1, and highlight the large increases in absolute numbers of both conditions over the 22-year period as also shown in Figure 1.8.

Discussion

In order to make national, regional and global predictions for the prevalence of diabetes, a number of assumptions needed to be made, and therefore the results are subject to a number of limitations. In addition to those highlighted in the Methodology section in Appendix 1.1, some of these are that:

• The studies included in this section often used differing screening techniques. The majority of studies used an OGTT to screen for diabetes, however, some studies used a fasting blood glucose test (FBG), some a two-hour blood glucose (2BG), some

a random blood glucose (RBG), and some based their data on self-report (SR). It is difficult to control for this unless, for example, only those studies that used an OGTT were included. This would also have the effect of excluding studies lacking OGTT data, which would have increased the number of countries for which data were extrapolated from another country.

• There were some inconsistencies in the technique used for a particular test (eg for the Argentinian data, diabetes was measured according to a 50g two-hour post-glucose load test, and not a 75g load as recommended by WHO), and persons with previously diagnosed diabetes were excluded from the analysis.

• There were inconsistencies in the diagnostic criteria adopted, resulting from the updating of the diagnostic criteria in 1997 (25). The use of a lower fasting diagnostic criterion for diabetes will tend to result in a higher prevalence of diabetes and lower prevalence of IGT. The diagnostic criteria used for each country are indicated in the data source tables.

• Three of the datasets reported only

previously diagnosed diabetes – New Zealand (35), Canada (36) and Germany (37). In order to account for those with undiagnosed diabetes, the figures from New Zealand were doubled based on Australian data showing that the ratio of known:unknown persons with diabetes is 1:1 (38, 39), as was data from Germany (40) while data from the USA (41) indicated that Canadian figures should be increased by 50%.

• If a country lacked data, it was assumed that their age and sex-specific prevalence rates of diabetes mellitus were the same as those rates in another socio-economically, ethnically and geographically similar country.

Figure 1.8Estimated number of people with diabetes and impaired glucose tolerance (20-79 age group) by region

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2003 2025

Region

Population(20-79)

No. of people with

diabetesDiabetes

prevalence

No. of people

with IGT IGT

prevalence Population

(20-79)

No. of people with

diabetesDiabetes

prevalence

No. of people

with IGT IGT

prevalence

(millions) (millions) (%) (millions) (%) (millions) (millions) (%) (millions) (%)

AFR 295 7.1 2.4 21.4 7.3 541 15.0 2.8 39.4 7.3

EMME 276 19.2 7.0 18.7 6.8 494 39.4 8.0 36.5 7.4

EUR 621 48.4 7.8 63.2 10.2 646 58.6 9.1 70.6 10.9

NA 290 23.0 7.9 20.3 7.0 374 36.2 9.7 29.6 7.9

SACA 252 14.2 5.6 18.5 7.3 364 26.2 7.2 29.5 8.1

SEA 705 39.3 5.6 93.4 13.2 1,081 81.6 7.5 146.3 13.5

WP 1,384 43.0 3.1 78.5 5.7 1,751 75.8 4.3 120.2 6.9

Total 3,823 194 5.1 314 8.2 5,251 333 6.3 472 9.0

Table 1.1Regional estimates for diabetes and impaired glucose tolerance (20-79 age group), 2003 and 2025

With the forces of globalization and industrialization proceeding at an increasing rate, the prevalence of diabetes is predicted to increase dramatically over the next few decades. The resulting burden of complications and premature mortality will continue to present itself as a major and growing public health problem for most countries.

It is hoped that this report will assist in monitoring the trends of diabetes prevalence over time, by adopting the same methodology for future reports. A report such as this should also be an indicator of a country’s and region’s ‘database’ of research. It should stimulate research in those countries lacking data, as well as encourage further and improved research in those countries where available data may not be representative of national rates.

Finally, this report should act as a stimulus for intervention. Perhaps the most essential aspect of research is the action taken as a result of findings. Diabetes requires culturally appropriate intervention in order to reduce the enormous personal suffering and economic burden that grows with this epidemic.





Map 1.1Prevalence estimates of diabetes, 2003

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Map 1.2Prevalence estimates of diabetes, 2025

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Map 1.3Prevalence estimates of impaired glucose tolerance, 2003

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Map 1.4Prevalence estimates of impaired glucose tolerance, 2025

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2003 2025

Country Prevalence (%) Country Prevalence (%)

1 Nauru 30.2 1 Nauru 33.0

2 United Arab Emirates 20.1 2 United Arab Emirates 24.5

3 Bahrain 14.9 3 Singapore, Republic of 19.5

4 Kuwait 12.8 4 Bahrain 18.3

5 Tonga 12.4 5 Kuwait 16.4

6 Singapore, Republic of 12.3 6 Tonga 15.9

7 Oman 11.4 7 Mauritius 14.7

8 Mauritius 10.7 8 Barbados 12.8

9 Germany 10.2 9 Hong Kong 12.8

10 Spain 9.9 10 Suriname 12.3

Table 1.2Estimated top 10: Prevalence of diabetes (20-79 age group), 2003 and 2025

Only countries have been included for which surveys including glucose testing were undertaken for that country

Figure 1.9Estimated top 10 prevalences of diabetes (20-79 age group), 2003

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2003 2025

Country Persons (millions) Country Persons (millions)

1 India 35.5 1 India 73.5

2 China, People’s Republic of 23.8 2 China, People’s Republic of 46.1

3 USA 16.0 3 USA 23.1

4 Russia 9.7 4 Pakistan 11.6

5 Japan 6.7 5 Russia 10.7

6 Germany 6.3 6 Brazil 10.7

7 Pakistan 6.2 7 Mexico 9.0

8 Brazil 5.7 8 Egypt 7.8

9 Mexico 4.4 9 Japan 7.1

10 Egypt 3.9 10 Germany 7.1

Table 1.3Estimated top 10: Number of people with diabetes (20-79 age group), 2003 and 2025

Top ten





2003 2025

Country Prevalence (%) Country Prevalence (%)

1 Nauru 20.4 1 Nauru 21.2

2 Bahrain 17.2 2 United Arab Emirates 20.8

3 United Arab Emirates 17.2 3 Bahrain 20.7

4 Kiribati 17.2 4 Kuwait 19.6

5 Kuwait 16.8 5 Poland 18.5

6 Singapore, Republic of 16.6 6 Kiribati 18.1

7 Poland 16.6 7 Mauritius 17.7

8 Mauritius 16.2 8 Singapore, Republic of 17.5

9 India 14.2 9 Hong Kong 14.6

10 Japan 13.0 10 India 14.5

Table 1.4Estimated top 10: Prevalence of impaired glucose tolerance(20-79 age group), 2003 and 2025

Only countries have been included for which surveys including glucose testing were undertaken for that country

2003 2025

Country Persons (millions) Country Persons (millions)

1 India 85.6 1 India 132.0

2 China, People’s Republic of 33.2 2 China, People’s Republic of 54.3

3 Russia 17.8 3 Indonesia 20.9

4 USA 13.9 4 USA 19.3

5 Indonesia 12.9 5 Russia 18.3

6 Japan 12.6 6 Japan 12.7

7 Brazil 7.5 7 Brazil 11.7

8 Ukraine 6.2 8 Pakistan 10.9

9 Pakistan 5.7 9 Bangladesh 10.1

10 Bangladesh 5.3 10 Nigeria 7.4

Table 1.5Estimated top 10: Number of people with impaired glucose tolerance(20-79 age group), 2003 and 2025

Figure 1.10Estimated top 10 prevalences of impaired glucose tolerance (20-79 age group), 2003

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Top ten





Country Data used Screening method Diagnostic criteria Sample size Age (yrs)

Angolaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Beninb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Botswanac South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+

Burkina Fasob Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Burundia Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Cameroon Cameroon (Mbanya et al, 1997)44 OGTT WHO – 1985 1,767 24-74

Cape Verdeb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Central African Republicb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Chad Sudan (Elbagir et al, 1996)48 2BG WHO – 1985 1,284 25-84

Comorosa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Congo, Democratic Republic of a Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Congo, Republic ofb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Côte d’Ivoireb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Djibouti Sudan (Elbagir et al, 1996)48 2BG WHO – 1985 1,284 25-84

Equatorial Guineab Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Eritreaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Ethiopiaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Gabonb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Gambiab Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Ghana Ghana (Amoah et al, 2002)45 OGTT WHO – 1999 4,733 25+

Guineab Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Guinea-Bissaub Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Kenyaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Lesothoc South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+

Liberiab Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Madagascara Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Malawia Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Malib Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Mauritania Sudan (Elbagir et al, 1996)48 2BG WHO – 1985 1,284 25-84

Mozambiquea Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Namibiac South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+

Nigerb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Nigeriab Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Reunion Mauritius (Dowse et al, 1990)49 OGTT WHO – 1985 4,929 25-74

Rwandaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Sao Tome and Principeb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Senegalb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Seychelles Mauritius (Dowse et al, 1990)49 OGTT WHO – 1985 5,080 25-74

Sierra Leoneb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Somaliaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

South Africac South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+

Swazilandc South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+

Tanzaniaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Togob Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Ugandaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Western Sahara Sudan (Elbagir et al, 1996)48 2BG WHO – 1985 1,284 25-84

Zambiaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Zimbabwea South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+

Table 1.6Data sources: prevalence estimates of diabetes mellitus (DM) and impaired glucose tolerance (IGT) – African Region

a. The prevalence was calculated after the combination of the data of the two studies, notwithstanding the different criteria. IGT figures were calculated from the McLarty data, as the Aspray study only used FBG criteria.

b. The prevalence was calculated as the average of the two studies as their sample sizes differed considerably.c. The prevalence was calculated after the combination of the data of the two studies. IGT figures were based

only on the study of Omar et al.






Angolaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Beninb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Botswanac South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+

Burkina Fasob Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Burundia Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Cameroon Cameroon (Mbanya et al, 1997)44 OGTT WHO – 1985 1,767 24-74

Cape Verdeb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Central African Republicb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Chad Sudan (Elbagir et al, 1996)48 2BG WHO – 1985 1,284 25-84

Comorosa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Congo, Democratic Republic of a Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Congo, Republic ofb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Côte d’Ivoireb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Djibouti Sudan (Elbagir et al, 1996)48 2BG WHO – 1985 1,284 25-84

Equatorial Guineab Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Eritreaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Ethiopiaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Gabonb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Gambiab Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Ghana Ghana (Amoah et al, 2002)45 OGTT WHO – 1999 4,733 25+

Guineab Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Guinea-Bissaub Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Kenyaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Lesothoc South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+

Liberiab Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Madagascara Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Malawia Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Malib Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Mauritania Sudan (Elbagir et al, 1996)48 2BG WHO – 1985 1,284 25-84

Mozambiquea Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Namibiac South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+

Nigerb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Nigeriab Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Reunion Mauritius (Dowse et al, 1990)49 OGTT WHO – 1985 4,929 25-74

Rwandaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Sao Tome and Principeb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Senegalb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Seychelles Mauritius (Dowse et al, 1990)49 OGTT WHO – 1985 5,080 25-74

Sierra Leoneb Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Somaliaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

South Africac South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+

Swazilandc South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+

Tanzaniaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Togob Cameroon (Mbanya et al, 1997)44 and Ghana (Amoah et al, 2002)45 OGTT WHO – 1985, 1999 6,500 24+

Ugandaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Western Sahara Sudan (Elbagir et al, 1996)48 2BG WHO – 1985 1,284 25-84

Zambiaa Tanzania (McLarty et al, 1989 and Aspray et al, 2002)42,43 OGTT/FBG WHO – 1985, 1999 7,781 15+

Zimbabwea South Africa (Omar et al, 1993 and Levitt et al, 1993)46,47 OGTT WHO – 1985 1,208 15+





Population (20-79)

DM prevalence

Number of people with DM (000’s)in the 20-79 age group

Country (000’s) % Rural Urban Male Female 20-39 40-59 60-79 Total

Angola 5,846 2.7 33.1 123.7 84.0 72.8 51.6 69.5 35.8 156.8

Benin 2,911 2.1 23.6 38.9 32.7 29.8 19.0 28.1 15.5 62.5

Botswana 716 3.6 3.2 22.3 8.8 16.7 4.1 13.9 7.5 25.5

Burkina Faso 4,969 2.7 90.4 44.8 67.8 67.4 40.1 55.2 40.0 135.3

Burundi 2,860 1.3 22.0 16.0 19.4 18.6 12.6 15.6 9.8 38.0

Cameroon 7,278 0.8 19.5 38.9 23.9 34.5 9.4 42.3 6.7 58.4

Cape Verde 228 2.3 1.1 4.2 2.2 3.1 2.0 1.7 1.7 5.3

Central African Republic 1,780 2.3 16.3 25.0 21.1 20.2 10.7 17.6 13.0 41.3

Chad 3,674 2.7 60.7 39.9 39.1 61.5 12.2 54.5 33.9 100.6

Comoros 355 2.5 1.9 7.0 4.8 4.1 3.2 3.9 1.8 8.9

Congo, Democratic Republic of 22,436 2.5 136.6 415.4 294.7 257.3 182.3 237.4 132.3 552.0

Congo, Republic of 1,403 2.6 7.6 28.3 18.4 17.6 10.5 15.2 10.3 35.9

Côte d’Ivoire 7,959 2.3 63.9 121.9 107.3 78.6 51.4 83.0 51.5 185.8

Djibouti 300 4.9 1.3 13.5 4.8 9.9 1.3 8.3 5.2 14.8

Equatorial Guinea 226 2.5 1.8 3.8 2.9 2.7 1.5 2.5 1.7 5.6

Eritrea 1,906 1.9 13.6 22.7 19.7 16.6 11.8 15.6 8.8 36.2

Ethiopia 29,562 1.9 214.6 335.8 299.4 250.9 176.6 234.9 138.8 550.4

Gabon 647 2.9 5.0 13.9 9.9 9.0 4.0 8.1 6.8 18.9

Gambia 703 2.2 7.4 8.0 8.3 7.0 4.1 7.2 4.0 15.4

Ghana 9,986 3.3 143.8 190.2 185.0 149.0 93.4 152.8 87.8 334.0

Guinea 3,855 2.0 37.6 41.2 42.8 36.0 23.3 35.5 20.1 78.9

Guinea-Bissau 588 2.0 7.0 4.8 6.3 5.5 3.1 5.2 3.5 11.8

Kenya 14,604 2.5 78.1 281.5 193.6 166.0 133.7 152.3 73.5 359.6

Lesotho 1,040 3.1 17.3 14.8 12.3 19.8 4.2 17.6 10.4 32.1

Liberia 1,573 2.0 10.5 21.3 17.0 14.8 11.6 11.6 8.6 31.8

Madagascar 7,782 2.5 47.3 144.6 104.3 87.5 63.2 85.5 43.2 191.9

Malawi 5,131 1.7 38.0 49.3 46.6 40.6 28.8 35.5 23.0 87.2

Mali 5,231 2.0 54.4 52.5 55.8 51.1 30.7 42.6 33.6 106.9

Mauritania 1,309 3.5 11.4 34.6 18.0 28.0 5.6 26.1 14.3 46.0

Mozambique 8,681 3.1 44.9 221.6 142.4 124.1 86.0 118.8 61.6 266.5

Namibia 831 3.1 10.1 15.4 9.5 16.0 3.9 13.6 8.0 25.5

Niger 4,728 3.1 36.4 110.3 57.7 89.0 20.8 83.9 41.9 146.7

Nigeria 54,248 2.2 439.3 779.4 655.4 563.3 354.5 528.9 335.3 1,218.7

Reuniona 474 13.1 10.0 51.9 29.1 32.8 11.2 29.7 21.0 61.9

Rwanda 3,645 1.1 28.3 13.1 22.7 18.7 15.2 14.7 11.4 41.4

Sao Tome and Principeb 107 2.8 1.0 1.9 1.6 1.4 0.6 1.3 1.0 2.9

Senegal 4,607 2.3 34.9 68.9 54.7 49.0 31.3 46.8 25.6 103.7

Seychellesa,b 49 12.3 1.5 4.5 2.9 3.0 1.0 2.9 2.0 6.0

Sierra Leone 2,268 2.2 21.3 27.6 25.7 23.2 14.0 21.8 13.1 48.9

Somalia 4,086 2.3 24.5 67.5 49.6 42.4 32.2 40.5 19.3 92.0

South Africa 24,741 3.4 272.1 569.1 322.7 518.5 127.1 489.6 224.5 841.2

Swaziland 450 3.0 6.0 7.4 5.2 8.2 2.0 7.4 3.9 13.4

Tanzania 16,616 2.3 98.1 281.0 203.4 175.7 134.9 163.9 80.3 379.1

Togo 2,196 2.1 21.4 23.7 23.9 21.2 13.2 19.4 12.5 45.1

Uganda 10,018 1.5 71.0 83.9 84.9 70.0 56.7 60.7 37.5 154.9

Western Sahara 149 4.9 0.1 7.1 2.9 4.4 0.7 3.6 2.9 7.3

Zambia 4,625 3.0 21.8 118.2 76.1 64.0 49.2 59.1 31.8 140.1

Zimbabwe 5,686 2.6 68.2 80.5 59.0 89.7 24.7 79.7 44.3 148.7

AFR Total * 295,065 2.4 2,380 4,692 3,580 3,491 1,985 3,265 1,821 7,072

Table 1.7Prevalence estimates of diabetes mellitus (DM), 2003 – African Region

* The totals may not be the exact sum of the column due to rounding.

a. Reunion and the Seychelles were deemed as having the same ethnicity distribution as Mauritius.b. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of world population 2003.





Population (20-79)

DM prevalence



Angola 11,873 3.2 48.5 334.5 206.0 176.9 142.3 167.3 73.4 382.9

Benin 5,851 2.4 36.1 107.0 74.4 68.7 43.4 60.8 39.0 143.1

Botswana 1,011 3.5 1.8 33.6 14.6 20.9 7.3 17.6 10.7 35.5

Burkina Faso 10,920 1.9 99.2 105.7 106.3 98.6 69.6 89.4 46.0 204.9

Burundi 5,534 1.8 37.6 60.6 53.1 45.1 36.2 39.0 23.0 98.2

Cameroon 12,625 1.2 28.3 119.5 64.5 83.3 49.9 52.7 45.2 147.8

Cape Verde 412 3.2 1.6 11.4 6.4 6.6 3.0 6.5 3.6 13.0

Central African Republic 2,988 2.4 19.7 51.8 36.5 35.0 22.0 29.0 20.6 71.6

Chad 7,349 2.8 94.7 113.5 82.2 126.1 27.7 116.6 63.9 208.2

Comoros 715 3.5 3.3 21.9 13.9 11.4 7.7 12.6 5.0 25.2

Congo, Democratic Republic of 49,259 3.0 220.5 1,251.8 799.2 673.2 556.3 625.2 290.9 1,472.4

Congo, Republic of 2,823 2.6 10.6 62.9 37.7 35.8 23.3 30.9 19.4 73.5

Côte d’Ivoire 13,673 2.3 76.0 244.3 182.3 138.0 90.5 140.4 89.4 320.3

Djibouti 378 3.5 0.8 12.3 3.6 9.5 2.0 5.2 5.9 13.1

Equatorial Guinea 430 2.7 2.2 9.2 6.0 5.5 3.2 5.0 3.3 11.4

Eritrea 3,628 2.6 22.3 71.5 51.2 42.6 30.4 41.1 22.3 93.8

Ethiopia 52,442 2.4 307.4 952.9 692.5 567.8 457.0 510.8 292.5 1,260.3

Gabon 1,095 2.8 5.2 25.7 16.2 14.7 8.4 12.3 10.2 30.9

Gambia 1,167 2.6 10.0 19.9 15.9 14.1 7.3 13.2 9.4 29.9

Ghana 17,839 4.1 216.6 507.7 408.3 315.9 178.0 345.2 201.0 724.2

Guinea 7,131 2.4 56.5 114.1 93.0 77.5 47.2 77.6 45.8 170.6

Guinea-Bissau 1,036 2.2 9.8 12.6 11.9 10.5 6.4 9.6 6.3 22.3

Kenya 25,033 3.4 107.3 753.5 472.7 388.2 300.0 386.7 174.1 860.8

Lesotho 1,195 2.9 13.0 21.7 14.2 20.5 5.9 15.8 13.0 34.6

Liberia 3,300 2.4 18.0 61.6 43.5 36.0 22.4 42.5 14.7 79.5

Madagascar 15,397 3.3 75.4 431.5 276.5 230.4 161.4 233.2 112.4 507.0

Malawi 8,961 2.2 53.7 142.7 109.3 87.1 74.6 78.3 43.5 196.4

Mali 10,339 2.2 82.2 149.0 124.0 107.2 69.2 99.4 62.6 231.2

Mauritania 2,590 3.9 16.1 85.3 40.5 60.9 11.8 56.6 33.0 101.4

Mozambique 13,773 3.6 49.8 447.1 270.3 226.6 183.7 212.7 100.4 496.9

Namibia 1,463 3.2 12.2 35.1 19.4 28.0 8.4 25.5 13.4 47.4

Niger 10,662 2.6 133.9 148.2 115.4 166.8 39.3 162.8 80.0 282.2

Nigeria 103,872 2.5 615.3 1,987.4 1,411.5 1,191.2 777.5 1,118.4 706.9 2,602.7

Reuniona 640 16.4 11.5 93.1 49.3 55.3 12.8 49.8 42.1 104.7

Rwanda 6,305 1.4 46.3 44.9 50.4 40.8 32.1 38.7 20.4 91.2

Sao Tome and Principeb 146 3.4 1.2 3.8 2.7 2.3 0.8 2.1 2.0 5.0

Senegal 8,798 2.6 52.0 176.1 120.0 108.1 64.6 104.3 59.2 228.1

Seychellesa,b 67 14.9 1.7 8.3 4.9 5.1 1.4 4.7 3.9 10.0

Sierra Leone 4,181 2.3 29.3 68.7 51.5 46.5 29.1 43.2 25.7 98.0

Somalia 9,053 2.9 43.7 220.5 142.5 121.7 92.7 119.3 52.3 264.2

South Africa 26,816 3.9 249.3 805.7 416.8 638.2 130.2 536.3 388.5 1,055.0

Swaziland 589 2.9 5.1 11.8 6.8 10.1 3.3 8.1 5.5 16.9

Tanzania 31,855 3.1 152.2 849.6 544.6 457.2 343.5 460.8 197.6 1,001.8

Togo 4,178 2.3 32.6 65.0 52.3 45.3 28.5 42.7 26.4 97.6

Uganda 22,514 2.0 132.4 327.4 252.9 206.9 175.6 197.7 86.5 459.8

Western Sahara 269 5.2 0.1 13.9 5.8 8.3 1.3 8.6 4.2 14.0

Zambia 8,922 3.6 31.1 286.1 177.0 140.1 121.1 141.3 54.7 317.1

Zimbabwe 10,041 2.8 89.3 194.7 119.5 164.5 56.6 152.6 74.8 284.0

AFR Total * 541,140 2.8 3,364 11,677 7,870 7,171 4,566 6,750 3,724 15,041

Table 1.8Prevalence estimates of diabetes mellitus (DM), 2025 – African Region


a. Reunion and the Seychelles were deemed as having the same ethnicity distribution as Mauritius.b. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of world population growth

from 2003 to 2025.





Population (20-79)

IGT prevalence

Number of people with IGT (000’s)in the 20-79 age group

Country (000’s) % Male Female 20-39 40-59 60-79 Total

Angola 5,846 7.5 190.2 251.0 193.9 152.4 95.0 441.2

Benin 2,911 6.9 99.3 102.7 82.9 77.5 41.5 202.0

Botswana 716 7.0 31.4 18.9 15.3 12.3 22.7 50.3

Burkina Faso 4,969 7.0 156.8 189.3 144.6 113.2 88.3 346.1

Burundi 2,860 7.5 86.2 127.0 94.4 76.5 42.4 213.2

Cameroon 7,278 2.2 104.5 56.4 23.9 86.4 50.6 161.0

Cape Verde 228 6.8 6.2 9.2 7.2 4.2 4.0 15.4

Central African Republic 1,780 7.4 63.0 69.2 47.3 49.2 35.7 132.3

Chad 3,674 2.3 29.9 53.5 21.0 38.5 23.9 83.4

Comoros 355 7.3 11.3 14.7 12.4 8.7 4.9 26.0

Congo, Democratic Republic of 22,436 7.6 729.1 966.7 746.0 572.8 377.0 1,695.8

Congo, Republic of 1,403 7.2 48.7 51.7 39.5 36.5 24.4 100.4

Côte d’Ivoire 7,959 7.2 308.9 262.6 219.2 219.5 132.8 571.5

Djibouti 300 2.6 2.3 5.6 1.5 3.9 2.5 7.9

Equatorial Guinea 226 7.5 8.3 8.6 6.0 6.4 4.4 16.8

Eritrea 1,906 7.6 62.6 82.0 62.7 51.5 30.3 144.6

Ethiopia 29,562 7.6 978.6 1,270.7 966.5 796.1 486.7 2,249.3

Gabon 647 8.1 25.7 26.7 15.5 20.1 16.8 52.5

Gambia 703 7.4 26.0 25.8 18.9 21.5 11.5 51.9

Ghana 9,986 12.0 564.8 636.3 529.4 409.1 262.6 1,201.1

Guinea 3,855 7.0 137.9 133.9 109.0 104.9 57.8 271.7

Guinea-Bissau 588 7.4 21.4 22.0 15.9 16.7 10.8 43.4

Kenya 14,604 7.2 461.0 592.7 514.6 338.9 200.2 1,053.7

Lesotho 1,040 8.5 58.7 30.1 19.7 22.5 46.5 88.8

Liberia 1,573 6.5 52.0 50.6 49.8 30.4 22.4 102.7

Madagascar 7,782 7.5 256.3 331.0 257.2 207.1 122.9 587.3

Malawi 5,131 7.5 166.1 221.0 170.5 131.6 85.0 387.2

Mali 5,231 7.2 183.2 193.8 148.2 129.0 99.9 377.1

Mauritania 1,309 2.3 10.8 18.9 7.5 14.3 7.9 29.7

Mozambique 8,681 7.6 286.0 376.5 284.6 228.3 149.6 662.5

Namibia 831 8.0 43.3 22.9 17.0 15.4 33.7 66.1

Niger 4,728 6.7 160.8 157.1 140.8 117.7 59.4 318.0

Nigeria 54,248 7.1 1,947.9 1,900.5 1,527.5 1,432.8 888.1 3,848.4

Reuniona 474 16.2 29.2 47.6 29.2 31.0 16.6 76.8

Rwanda 3,645 7.2 114.7 149.5 128.5 83.3 52.4 264.2

Sao Tome and Principeb 107 8.1 4.3 4.3 2.6 3.5 2.6 8.7

Senegal 4,607 7.0 160.5 162.2 131.1 124.7 66.9 322.7

Seychellesa,b 49 16.1 3.2 4.7 2.9 3.2 1.7 7.9

Sierra Leone 2,268 7.2 79.8 82.8 63.2 62.5 36.9 162.6

Somalia 4,086 7.4 129.9 171.1 139.6 104.5 56.9 301.0

South Africa 24,741 7.2 1,201.8 573.4 498.6 553.8 722.8 1,775.2

Swaziland 450 7.8 23.4 11.7 9.1 8.9 17.0 35.1

Tanzania 16,616 7.3 525.5 694.8 574.2 413.1 233.1 1,220.3

Togo 2,196 7.1 77.1 78.5 62.1 57.4 36.1 155.6

Uganda 10,018 7.3 319.3 407.9 351.2 233.9 142.1 727.2

Western Sahara 149 2.5 1.3 2.4 0.8 1.6 1.3 3.7

Zambia 4,625 7.4 151.4 189.5 158.8 107.2 74.9 340.9

Zimbabwe 5,686 7.2 285.0 124.2 126.9 99.6 182.6 409.2

AFR Total * 295,065 7.3 10,426 10,984 8,789 7,434 5,186 21,410

Table 1.9Prevalence estimates of impaired glucose tolerance (IGT), 2003 – African Region


a. Reunion and the Seychelles were deemed as having the same ethnicity distribution as Mauritius.b. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of world population 2003.





Table 1.10Prevalence estimates of impaired glucose tolerance (IGT), 2025 – African Region

Population (20-79)

IGT prevalence



Angola 11,873 7.2 374.9 484.9 418.6 279.6 161.6 859.8

Benin 5,851 7.1 204.9 210.0 167.6 151.6 95.7 414.9

Botswana 1,011 7.2 47.0 26.0 22.8 16.7 33.6 73.0

Burkina Faso 10,920 6.7 357.3 373.7 327.9 268.4 134.8 731.0

Burundi 5,534 7.3 175.3 230.5 193.6 131.2 80.9 405.7

Cameroon 12,625 2.2 188.1 93.6 45.2 156.8 79.7 281.7

Cape Verde 412 7.8 15.1 17.1 10.0 14.4 7.9 32.2

Central African Republic 2,988 7.1 102.7 109.6 86.7 73.7 51.8 212.3

Chad 7,349 2.2 58.5 100.6 43.3 75.1 40.7 159.1

Comoros 715 7.7 24.2 30.7 22.5 21.4 11.0 54.9

Congo, Democratic Republic of 49,259 7.2 1,568.1 1,991.9 1,753.6 1,125.6 680.7 3,559.9

Congo, Republic of 2,823 6.9 96.2 99.7 82.6 69.9 43.4 195.9

Côte d’Ivoire 13,673 7.3 522.6 471.2 382.0 371.8 240.0 993.8

Djibouti 378 2.1 2.3 5.7 2.4 2.5 3.0 7.9

Equatorial Guinea 430 7.3 15.5 15.7 11.9 11.7 7.6 31.2

Eritrea 3,628 7.7 122.2 155.8 119.2 96.2 62.5 277.9

Ethiopia 52,442 7.4 1,718.8 2,144.7 1,834.1 1,200.7 828.8 3,863.5

Gabon 1,095 7.5 40.7 41.1 30.0 28.4 23.3 81.7

Gambia 1,167 7.7 44.5 45.2 30.2 34.9 24.5 89.6

Ghana 17,839 12.7 1,070.9 1,188.0 874.2 837.3 547.5 2,258.9

Guinea 7,131 7.3 265.8 252.5 194.7 205.4 118.1 518.3

Guinea-Bissau 1,036 7.2 36.9 37.5 29.1 27.6 17.7 74.4

Kenya 25,033 7.5 827.7 1,041.4 847.0 636.2 385.9 1,869.1

Lesotho 1,195 8.6 66.5 36.7 26.2 19.8 57.1 103.1

Liberia 3,300 6.9 117.5 109.0 88.2 103.3 35.0 226.5

Madagascar 15,397 7.7 518.3 661.4 500.5 419.9 259.3 1,179.6

Malawi 8,961 7.2 292.2 355.9 319.2 198.2 130.6 648.0

Mali 10,339 7.1 368.5 361.3 295.8 268.0 166.0 729.8

Mauritania 2,590 2.3 22.2 38.0 14.6 28.9 16.7 60.2

Mozambique 13,773 7.3 444.6 563.9 484.7 316.8 207.0 1,008.5

Namibia 1,463 7.5 73.3 36.5 30.9 28.2 50.7 109.9

Niger 10,662 6.8 370.9 348.9 315.6 270.0 134.2 719.7

Nigeria 103,872 7.1 3,807.8 3,593.1 2,962.3 2,738.5 1,700.1 7,400.9

Reuniona 640 17.4 44.3 67.2 31.6 47.9 31.9 111.4

Rwanda 6,305 7.3 202.2 260.6 214.1 167.1 81.7 462.9

Sao Tome and Principeb 146 8.9 6.5 6.5 3.1 5.2 4.8 13.0

Senegal 8,798 7.3 318.4 319.9 242.3 254.1 141.8 638.3

Seychellesa,b 67 17.0 4.7 6.7 3.5 4.8 3.1 11.4

Sierra Leone 4,181 7.1 146.5 148.8 118.5 111.6 65.3 295.4

Somalia 9,053 7.3 289.0 375.6 309.6 229.0 126.0 664.6

South Africa 26,816 8.8 1,585.0 766.0 523.5 597.6 1,229.9 2,350.9

Swaziland 589 7.6 29.2 15.6 13.3 9.4 22.1 44.8

Tanzania 31,855 7.5 1,041.2 1,341.5 1,072.5 844.0 466.2 2,382.7

Togo 4,178 7.2 151.1 148.8 117.7 113.3 68.9 299.9

Uganda 22,514 7.1 706.8 896.0 801.7 535.8 265.3 1,602.8

Western Sahara 269 2.6 2.6 4.4 1.4 3.8 1.9 7.0

Zambia 8,922 7.2 289.5 349.5 317.7 208.8 112.6 639.1

Zimbabwe 10,041 6.8 478.0 202.2 228.6 181.4 270.3 680.3

AFR Total * 541,140 7.3 19,257 20,181 16,566 13,543 9,329 39,438


a. Reunion and the Seychelles were deemed as having the same ethnicity distribution as Mauritius.b. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of world population growth

from 2003 to 2025.






Afghanistana Pakistan (Shera et al, 1995, 1999a, 1999b)50,51,52 OGTT WHO – 1985 3,409 25+

Algeriab,c Tunisia (Papoz et al, 1988 and Ghannem et al, 1997)53,54 FBG/SR WHO – 1980 6,570 20+

Armenia Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Bahraind Bahrain (Al-Mahroos et al, 1998)56 OGTT WHO – 1985 2,128 40-69

Egyptb Egypt (Herman et al, 1995 and Arab, 1997)57,58 OGTT/Post-prandial GT WHO – 1985 5,251 20+

Irane Iran (Amini et al, 1997)59 OGTT WHO – 1985 3,910 40+

Iraq Jordan (Ajlouni et al, 1998)60 OGTT WHO – 1985 2,776 25-79

Jordan Jordan (Ajlouni et al, 1998)60 OGTT WHO – 1985 2,776 25-79

Kuwaitd Kuwait (Abdella et al, 1998)61 OGTT WHO – 1985 3,003 20+

Lebanon Lebanon (Salti et al, 1997)62 OGTT WHO – 1985 2,518 30+

Libyac Libya (Kadiki et al, 1999)63 Registration N/A 15,912 20+

Moroccob,c Tunisia (Papoz et al, 1988 and Ghannem et al, 1997)53,54 FBG/SR WHO – 1980 6,570 20+

Occupied Palestinian Territories Jordan (Ajlouni et al, 1998)60 OGTT WHO – 1985 2,776 25-79

Omanf Oman (Al-Lawati et al, 2002)64 OGTT WHO – 1999 5,731 20-79

Pakistana Pakistan (Shera et al, 1995, 1999a, 1999b)50,51,52 OGTT WHO – 1985 3,409 25+

Qatard Bahrain (Al-Mahroos et al, 1998)56 OGTT WHO – 1985 2,128 40-69

Saudi Arabia Saudi Arabia (El-Hazmi et al, 1998)66 OGTT WHO – 1985 15,420 14+

Sudan Sudan (Elbagir et al, 1996)48 2BG WHO – 1985 1,284 25-84

Syria Jordan (Ajlouni et al, 1998)60 OGTT WHO – 1985 2,776 25-79

Tunisiab,c Tunisia (Papoz et al, 1988 and Ghannem et al, 1997)53,54 FBG/SR WHO – 1980 6,570 20+

United Arab Emirates UAE (Malik et al, 2002 )67 OGTT WHO – 1999 6,612 19+

Yemenf Oman (Al-Lawati et al, 2002)64 OGTT WHO – 1999 5,731 20-79

Table 1.11Data sources: prevalence estimates of diabetes mellitus (DM) and impaired glucose tolerance (IGT) – Eastern Mediterranean andMiddle East Region

a. The prevalence was obtained by combining the data from the three studies.b. The prevalences were calculated as the average of the two cited studies as their sample sizes

differed considerably.c. Because of the absence of data for IGT in the studies used for diabetes,

IGT figures were calculated from Jordanian data.d. Because of the absence of data for IGT in the study used for diabetes,

IGT figures were calculated from UAE data.e. Because of the absence of data for IGT in the studies used for diabetes,

IGT figures were calculated from Pakistani data.f. Because of the absence of data for IGT in the studies used for diabetes,

IGT figures were calculated from other Oman data (Asfour et al, 1995)65.

N/A not available






Afghanistana Pakistan (Shera et al, 1995, 1999a, 1999b)50,51,52 OGTT WHO – 1985 3,409 25+

Algeriab,c Tunisia (Papoz et al, 1988 and Ghannem et al, 1997)53,54 FBG/SR WHO – 1980 6,570 20+

Armenia Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Bahraind Bahrain (Al-Mahroos et al, 1998)56 OGTT WHO – 1985 2,128 40-69

Egyptb Egypt (Herman et al, 1995 and Arab, 1997)57,58 OGTT/Post-prandial GT WHO – 1985 5,251 20+

Irane Iran (Amini et al, 1997)59 OGTT WHO – 1985 3,910 40+

Iraq Jordan (Ajlouni et al, 1998)60 OGTT WHO – 1985 2,776 25-79

Jordan Jordan (Ajlouni et al, 1998)60 OGTT WHO – 1985 2,776 25-79

Kuwaitd Kuwait (Abdella et al, 1998)61 OGTT WHO – 1985 3,003 20+

Lebanon Lebanon (Salti et al, 1997)62 OGTT WHO – 1985 2,518 30+

Libyac Libya (Kadiki et al, 1999)63 Registration N/A 15,912 20+

Moroccob,c Tunisia (Papoz et al, 1988 and Ghannem et al, 1997)53,54 FBG/SR WHO – 1980 6,570 20+

Occupied Palestinian Territories Jordan (Ajlouni et al, 1998)60 OGTT WHO – 1985 2,776 25-79

Omanf Oman (Al-Lawati et al, 2002)64 OGTT WHO – 1999 5,731 20-79

Pakistana Pakistan (Shera et al, 1995, 1999a, 1999b)50,51,52 OGTT WHO – 1985 3,409 25+

Qatard Bahrain (Al-Mahroos et al, 1998)56 OGTT WHO – 1985 2,128 40-69

Saudi Arabia Saudi Arabia (El-Hazmi et al, 1998)66 OGTT WHO – 1985 15,420 14+

Sudan Sudan (Elbagir et al, 1996)48 2BG WHO – 1985 1,284 25-84

Syria Jordan (Ajlouni et al, 1998)60 OGTT WHO – 1985 2,776 25-79

Tunisiab,c Tunisia (Papoz et al, 1988 and Ghannem et al, 1997)53,54 FBG/SR WHO – 1980 6,570 20+

United Arab Emirates UAE (Malik et al, 2002 )67 OGTT WHO – 1999 6,612 19+

Yemenf Oman (Al-Lawati et al, 2002)64 OGTT WHO – 1999 5,731 20-79





Population (20-79)

DM prevalence



Afghanistan 11,130 8.2 718.0 199.4 501.5 415.8 231.5 487.1 198.7 917.3

Algeria 17,737 4.1 176.0 551.8 321.0 406.8 205.8 344.9 177.1 727.8

Armenia 2,607 8.1 48.6 162.4 81.6 129.3 20.1 96.9 94.0 211.0

Bahrain 439 14.9 2.4 63.1 42.1 23.4 11.4 44.8 9.3 65.5

Egypt 39,299 9.8 1,326.8 2,542.5 1,729.5 2,139.8 1,007.7 1,931.5 930.1 3,869.3

Iran 38,506 3.6 317.0 1,073.7 705.5 685.1 441.4 652.0 297.2 1,390.6

Iraq 11,962 7.7 114.4 801.2 456.0 459.7 147.3 514.3 254.1 915.6

Jordan 2,648 7.0 26.0 159.0 96.0 89.0 35.2 95.6 54.2 185.0

Kuwait 1,240 12.8 1.8 156.4 107.2 51.0 23.6 94.7 39.9 158.2

Lebanon 2,202 6.4 7.0 133.2 67.0 73.3 8.4 59.6 72.2 140.2

Libya 3,128 3.7 7.1 107.4 47.8 66.7 27.5 71.6 15.5 114.5

Morocco 17,598 4.2 197.7 533.9 312.2 419.3 195.2 351.3 185.0 731.5

Occupied Palestinian Territoriesa 1,525 7.4 15.8 96.7 54.7 57.9 18.7 60.9 32.9 112.5

Oman 1,274 11.4 10.6 134.4 84.9 60.1 42.2 74.6 28.2 145.0

Pakistan 72,760 8.5 3,909.2 2,271.2 3,310.5 2,869.8 1,426.3 3,332.6 1,421.5 6,180.4

Qatar 393 16.0 2.3 60.6 46.8 16.1 10.8 45.5 6.6 62.9

Saudi Arabia 10,544 9.4 70.5 921.7 597.1 395.1 145.3 583.4 263.5 992.2

Sudan 16,584 3.1 232.4 290.0 210.4 311.9 61.7 289.8 170.8 522.3

Syria 8,516 6.2 150.4 377.9 260.2 268.0 94.8 281.9 151.5 528.2

Tunisia 5,966 4.6 52.8 220.8 117.9 155.8 66.7 130.1 76.9 273.6

United Arab Emirates 1,829 20.1 26.4 340.9 272.7 94.6 54.7 247.7 64.9 367.3

Yemen 8,137 7.7 267.4 358.2 290.1 335.4 235.7 265.4 124.5 625.6

EMME Total * 276,025 7.0 7,680 11,556 9,713 9,524 4,512 10,056 4,669 19,237

Table 1.12Prevalence estimates of diabetes mellitus (DM), 2003 – Eastern Mediterranean and Middle East Region


a. Occupied Palestinian Territories assigned urban/rural distribution of Jordan.





Population (20-79)

DM prevalence



Afghanistan 21,973 8.3 1,185.2 634.0 973.3 845.9 449.4 976.6 393.2 1,819.2

Algeria 28,950 5.5 247.5 1,343.5 693.1 897.9 288.5 829.4 473.1 1,591.0

Armenia 2,968 10.7 52.9 263.2 124.9 191.2 21.8 131.6 162.8 316.2

Bahrain 645 18.3 2.7 115.6 67.3 51.1 13.2 56.7 48.4 118.3

Egypt 63,676 12.3 1,879.1 5,923.7 3,440.7 4,362.1 1,669.6 3,709.3 2,423.9 7,802.8

Iran 65,757 4.4 455.6 2,440.3 1,438.5 1,457.5 764.3 1,322.5 809.0 2,895.9

Iraq 23,293 9.1 185.8 1,940.5 1,061.2 1,065.1 284.2 1,197.8 644.2 2,126.3

Jordan 5,054 9.3 45.7 426.0 244.9 226.8 57.1 284.7 129.8 471.7

Kuwait 2,178 16.4 3.0 354.8 219.8 137.9 47.6 139.7 170.4 357.7

Lebanon 3,214 9.1 9.9 282.8 139.5 153.2 10.1 138.2 144.4 292.7

Libya 5,215 4.7 10.8 231.8 94.7 147.9 41.7 166.8 34.0 242.6

Morocco 28,128 5.4 264.7 1,250.4 645.5 869.6 277.1 770.7 467.3 1,515.1

Occupied Palestinian Territoriesa 3,543 8.2 28.2 263.2 147.6 143.7 43.8 159.7 87.9 291.4

Oman 2,710 11.9 10.7 312.7 173.3 150.0 97.1 146.8 79.5 323.4

Pakistan 136,909 8.5 5,700.0 5,906.8 5,890.5 5,716.2 2,754.9 6,078.1 2,773.7 11,606.8

Qatar 537 18.2 2.6 95.0 63.1 34.5 10.3 43.5 43.8 97.6

Saudi Arabia 21,851 9.6 99.8 2,001.5 1,146.4 954.9 355.9 1,017.0 728.5 2,101.3

Sudan 29,070 3.9 334.4 810.7 472.8 672.3 114.3 645.0 385.8 1,145.1

Syria 16,711 8.6 285.6 1,155.9 721.4 720.0 189.2 828.9 423.3 1,441.4

Tunisia 8,442 6.0 69.5 436.2 214.2 291.6 80.1 259.5 166.2 505.8

United Arab Emirates 2,482 24.5 31.4 575.7 409.7 197.3 76.0 230.9 300.2 607.0

Yemen 20,253 8.6 501.7 1,239.3 874.9 866.0 604.4 804.2 332.3 1,740.9

EMME Total * 493,560 8.0 11,407 28,004 19,257 20,153 8,251 19,938 11,222 39,410

Table 1.13Prevalence estimates of diabetes mellitus (DM), 2025 – Eastern Mediterranean and Middle East Region


a. Occupied Palestinian Territories assigned urban/rural distribution of Jordan.





Population (20-79)

IGT prevalence



Afghanistan 11,130 7.6 286.3 554.7 321.6 337.3 182.1 841.1

Algeria 17,737 7.3 649.5 650.3 417.5 625.5 256.8 1,299.8

Armenia 2,607 7.0 58.7 124.4 42.5 78.4 62.3 183.2

Bahrain 439 17.2 40.0 35.7 26.8 38.7 10.1 75.6

Egypt 39,299 4.6 886.3 934.7 676.2 699.8 445.0 1,821.0

Iran 38,506 7.7 999.3 1,956.7 1,086.5 1,238.0 631.4 2,956.0

Iraq 11,962 7.3 435.3 433.0 282.0 422.7 163.7 868.3

Jordan 2,648 6.9 95.8 87.3 67.8 79.9 35.4 183.1

Kuwait 1,240 16.8 118.2 89.9 71.7 103.2 33.1 208.0

Lebanon 2,202 3.5 32.0 45.6 13.2 32.7 31.7 77.6

Libya 3,128 7.3 122.1 106.3 71.0 111.6 45.9 228.5

Morocco 17,598 7.6 644.9 685.4 402.0 655.2 273.1 1,330.3

Occupied Palestinian Territories 1,525 7.2 54.0 55.1 36.3 51.3 21.5 109.1

Oman 1,274 9.7 56.8 66.8 48.8 57.4 17.3 123.5

Pakistan 72,760 7.8 1,980.7 3,727.3 2,035.3 2,303.7 1,369.0 5,708.0

Qatar 393 16.9 42.4 24.0 21.6 38.0 6.8 66.4

Saudi Arabia 10,544 1.0 48.5 57.1 24.1 56.0 25.6 105.7

Sudan 16,584 2.3 143.4 242.8 94.9 183.9 107.5 386.2

Syria 8,516 6.9 292.4 295.0 207.8 268.3 111.4 587.4

Tunisia 5,966 7.8 230.4 234.9 132.3 224.5 108.5 465.3

United Arab Emirates 1,829 17.2 210.2 104.7 90.4 176.7 47.8 314.9

Yemen 8,137 9.5 270.6 501.1 364.5 307.4 99.8 771.7

EMME Total * 276,025 6.8 7,698 11,013 6,535 8,090 4,086 18,711

Table 1.14Prevalence estimates of impaired glucose tolerance (IGT), 2003 – Eastern Mediterranean and Middle East Region






Population (20-79)

IGT prevalence



Afghanistan 21,973 7.6 573.2 1,106.2 628.2 679.4 371.8 1,679.5

Algeria 28,950 9.0 1,307.8 1,287.6 564.3 1,376.5 654.7 2,595.5

Armenia 2,968 8.2 83.6 159.7 39.8 98.9 104.6 243.3

Bahrain 645 20.7 68.4 65.2 32.1 48.7 52.7 133.5

Egypt 63,676 5.1 1,599.0 1,668.6 970.5 1,233.5 1,063.7 3,267.7

Iran 65,757 8.7 2,025.7 3,674.7 1,690.5 2,384.9 1,625.0 5,700.4

Iraq 23,293 8.0 932.2 925.0 511.5 944.5 401.2 1,857.3

Jordan 5,054 8.1 213.0 198.3 105.1 224.5 81.6 411.3

Kuwait 2,178 19.6 219.4 208.1 121.9 164.4 141.2 427.5

Lebanon 3,214 4.6 65.4 83.3 15.1 71.2 62.5 148.8

Libya 5,215 8.7 229.4 225.2 99.6 251.5 103.5 454.6

Morocco 28,128 8.9 1,237.8 1,262.6 547.2 1,302.8 650.5 2,500.5

Occupied Palestinian Territories 3,543 7.4 134.0 129.7 81.5 127.1 55.2 263.8

Oman 2,710 10.1 114.1 158.4 108.4 116.3 47.9 272.5

Pakistan 136,909 8.0 3,714.0 7,218.6 3,847.6 4,316.0 2,769.1 10,932.6

Qatar 537 20.7 64.4 46.5 26.3 36.6 48.0 110.8

Saudi Arabia 21,851 1.0 86.9 134.7 55.4 99.8 66.4 221.6

Sudan 29,070 2.5 277.2 459.7 155.5 363.8 217.6 736.9

Syria 16,711 8.3 693.1 686.1 365.0 723.7 290.5 1,379.2

Tunisia 8,442 9.5 399.4 405.5 152.8 426.9 225.2 804.9

United Arab Emirates 2,482 20.8 312.3 204.2 120.0 167.2 229.2 516.5

Yemen 20,253 9.3 723.7 1,162.2 856.4 791.4 238.2 1,885.9

EMME Total * 493,560 7.4 15,074 21,470 11,095 15,950 9,500 36,545

Table 1.15Prevalence estimates of impaired glucose tolerance (IGT), 2025 – Eastern Mediterranean and Middle East Region







Albaniaa Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Andorra Spain (Castell et al, 1999)69 OGTT WHO – 1985 3,839 30-79

Austriab,c Germany (Rathmann et al, 2003 and Thefeld et al, 1999)70,37 SR/OGTT WHO – 1999 8,477 18-79

Azerbaijan Republic Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Belarusc Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Belgium The Netherlands (Mooy et al, 1995)73 OGTT WHO – 1985 2,540 50-74

Bosnia and Herzegovina Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Bulgaria Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Croatiaa Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Cyprusa Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Czech Republicc Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Denmark Sweden (Eliasson et al, 2002)74 OGTT WHO – 1999 6,952 25-74

Estoniac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Finland Finland (Tuomilehto et al, 1986 and 1991)75,76 OGTT WHO – 1985 3,329 45-79

Francec Italy (Verillo et al, 1985 and Garancini et al, 1995)77,78 OGTT WHO – 1980 3,772 20+

Georgia, Republic of Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Germanyb,c Germany (Rathmann et al, 2003 and Thefeld et al, 1999)70,37 SR/OGTT WHO – 1999 8,477 18-79

Greecea Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Hungaryc Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Icelandd Iceland (Vilbergsson et al, 1997)79 OGTT (50-100g) WHO – 1985 18,887 30-79

Ireland, Republic of c United Kingdom (Unwin et al, 1997 and Yudkin et al, 1993)80,81 OGTT WHO – 1985 2,529 25-75

Israelc,e Israel (Bar-On et al, 1992 and Stern et al, 1999)82,83 OGTT WHO – 1980/1985 6,918 25-64

Italyc Italy (Verillo et al, 1985 and Garancini et al, 1995)77,78 OGTT WHO – 1980 3,772 20+

Kazakhstan Uzbekistan (King et al, 1998)84 2BG WHO – 1994 1,956 35+

Kyrgyzstan Uzbekistan (King et al, 1998)84 2BG WHO – 1994 1,956 35+

Latviac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Lithuaniac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Luxembourg The Netherlands (Mooy et al, 1995)73 OGTT WHO – 1985 2,540 50-74

Macedoniaa Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Malta Malta (Schranz, 1989)85 OGTT WHO – 1985 1,422 35+

Moldova, Republic of c Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Monacoc Italy (Verillo et al, 1985 and Garancini et al, 1995)77,78 OGTT WHO – 1980 3,772 20+

Netherlands The Netherlands (Mooy et al, 1995)73 OGTT WHO – 1985 2,540 50-74

Norway Sweden (Eliasson et al, 2002)74 OGTT WHO – 1999 6,952 25-74

Polandc Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Portugal Spain (Castell et al, 1999)69 OGTT WHO – 1985 3,839 30-79

Romaniac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Russian Federationc Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

San Marinoc Italy (Verillo et al, 1985 and Garancini et al, 1995)77,78 OGTT WHO – 1980 3,772 20+

Serbia and Montenegroa Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Slovakiac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Sloveniac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Spain Spain (Castell et al, 1999)69 OGTT WHO – 1985 3,839 30-79

Sweden Sweden (Eliasson et al, 2002)74 OGTT WHO – 1999 6,952 25-74

Switzerlandc Germany (Rathmann et al, 2003 and Thefeld et al, 1999)70,37 SR/OGTT WHO – 1999 8,477 18-79

Tajikistan Uzbekistan (King et al, 1998)84 2BG WHO – 1994 1,956 35+

Turkey Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Turkmenistan Uzbekistan (King et al, 1998)84 2BG WHO – 1994 1,956 35+

Ukrainec Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

United Kingdomc United Kingdom (Unwin et al, 1997 and Yudkin et al, 1993)80,81 OGTT WHO – 1985 2,529 25-75

Uzbekistan Uzbekistan (King et al, 1998)84 2BG WHO – 1994 1,956 35+

Table 1.16Data sources: prevalence estimates of diabetes mellitus (DM) and impaired glucose tolerance (IGT) – European Region

a. Because of the absence of data for IGT in the study used for diabetes, IGT figures were calculated from Turkish data.

b. IGT prevalences were derived from the data of Rathmann et al.c. The prevalences for the studies based on the German, Italian, Israeli, Polish and the United Kingdom studies

were obtained by combining the data from the two studies respectively.






Albaniaa Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Andorra Spain (Castell et al, 1999)69 OGTT WHO – 1985 3,839 30-79

Austriab,c Germany (Rathmann et al, 2003 and Thefeld et al, 1999)70,37 SR/OGTT WHO – 1999 8,477 18-79

Azerbaijan Republic Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Belarusc Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Belgium The Netherlands (Mooy et al, 1995)73 OGTT WHO – 1985 2,540 50-74

Bosnia and Herzegovina Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Bulgaria Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Croatiaa Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Cyprusa Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Czech Republicc Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Denmark Sweden (Eliasson et al, 2002)74 OGTT WHO – 1999 6,952 25-74

Estoniac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Finland Finland (Tuomilehto et al, 1986 and 1991)75,76 OGTT WHO – 1985 3,329 45-79

Francec Italy (Verillo et al, 1985 and Garancini et al, 1995)77,78 OGTT WHO – 1980 3,772 20+

Georgia, Republic of Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Germanyb,c Germany (Rathmann et al, 2003 and Thefeld et al, 1999)70,37 SR/OGTT WHO – 1999 8,477 18-79

Greecea Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Hungaryc Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Icelandd Iceland (Vilbergsson et al, 1997)79 OGTT (50-100g) WHO – 1985 18,887 30-79

Ireland, Republic of c United Kingdom (Unwin et al, 1997 and Yudkin et al, 1993)80,81 OGTT WHO – 1985 2,529 25-75

Israelc,e Israel (Bar-On et al, 1992 and Stern et al, 1999)82,83 OGTT WHO – 1980/1985 6,918 25-64

Italyc Italy (Verillo et al, 1985 and Garancini et al, 1995)77,78 OGTT WHO – 1980 3,772 20+

Kazakhstan Uzbekistan (King et al, 1998)84 2BG WHO – 1994 1,956 35+

Kyrgyzstan Uzbekistan (King et al, 1998)84 2BG WHO – 1994 1,956 35+

Latviac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Lithuaniac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Luxembourg The Netherlands (Mooy et al, 1995)73 OGTT WHO – 1985 2,540 50-74

Macedoniaa Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Malta Malta (Schranz, 1989)85 OGTT WHO – 1985 1,422 35+

Moldova, Republic of c Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Monacoc Italy (Verillo et al, 1985 and Garancini et al, 1995)77,78 OGTT WHO – 1980 3,772 20+

Netherlands The Netherlands (Mooy et al, 1995)73 OGTT WHO – 1985 2,540 50-74

Norway Sweden (Eliasson et al, 2002)74 OGTT WHO – 1999 6,952 25-74

Polandc Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Portugal Spain (Castell et al, 1999)69 OGTT WHO – 1985 3,839 30-79

Romaniac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Russian Federationc Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

San Marinoc Italy (Verillo et al, 1985 and Garancini et al, 1995)77,78 OGTT WHO – 1980 3,772 20+

Serbia and Montenegroa Greece (Katsilambros et al, 1993)68 SR Known diabetes 9,092 20-79

Slovakiac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Sloveniac Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

Spain Spain (Castell et al, 1999)69 OGTT WHO – 1985 3,839 30-79

Sweden Sweden (Eliasson et al, 2002)74 OGTT WHO – 1999 6,952 25-74

Switzerlandc Germany (Rathmann et al, 2003 and Thefeld et al, 1999)70,37 SR/OGTT WHO – 1999 8,477 18-79

Tajikistan Uzbekistan (King et al, 1998)84 2BG WHO – 1994 1,956 35+

Turkey Turkey (Satman et al, 2002)55 2BG WHO – 1999 24,788 20+

Turkmenistan Uzbekistan (King et al, 1998)84 2BG WHO – 1994 1,956 35+

Ukrainec Poland (Szurkowska et al and Lopatynski et al, 2001)71,72 OGTT WHO – 1985 6,842 35+

United Kingdomc United Kingdom (Unwin et al, 1997 and Yudkin et al, 1993)80,81 OGTT WHO – 1985 2,529 25-75

Uzbekistan Uzbekistan (King et al, 1998)84 2BG WHO – 1994 1,956 35+

d. Because of the absence of data for IGT in the study used for diabetes, IGT figures were calculated from Netherlands data.

e. IGT prevalence for Israel was derived only from the data in Bar-On et al.





Population (20-79)

DM prevalence



Albania 1,966 3.8 34.9 40.1 4.0 27.2 43.7 75.0

Andorraa 50 7.7 1.9 2.0 0.1 1.3 2.5 3.9

Austria 5,991 9.6 258.5 317.5 38.8 172.7 364.5 576.0

Azerbaijan Republic 5,154 6.9 122.1 235.4 143.6 213.9 44.7 159.8 152.9 357.5

Belarus 7,336 6.9 309.1 374.3 63.4 242.3 377.7 683.4

Belgium 7,531 4.2 140.6 174.5 3.1 71.1 240.9 315.1

Bosnia and Herzegovina 3,074 9.6 117.2 178.2 24.5 141.0 129.9 295.4

Bulgaria 5,894 10.0 135.8 455.4 235.7 355.5 37.6 248.1 305.5 591.2

Croatia 3,412 5.8 82.4 116.7 5.3 56.8 137.1 199.1

Cyprus 541 5.1 12.3 15.4 0.9 9.4 17.5 27.7

Czech Republic 7,734 9.5 365.2 369.6 66.8 286.2 381.9 734.9

Denmark 3,863 6.9 120.9 144.0 23.3 87.0 154.6 264.9

Estonia 991 9.7 43.4 52.9 8.6 33.3 54.4 96.3

Finland 3,775 7.2 130.3 143.2 10.3 56.3 207.0 273.5

France 42,546 6.2 1,306.3 1,347.3 175.0 1,045.3 1,433.3 2,653.6

Georgia, Republic of 3,681 9.0 102.8 229.5 129.0 203.4 25.6 134.7 172.1 332.4

Germany 61,895 10.2 2,879.3 3,415.0 374.0 1,752.7 4,167.6 6,294.3

Greece 8,069 6.1 217.0 276.0 12.9 129.0 351.0 493.0

Hungary 7,350 9.7 336.3 375.1 62.6 259.5 389.2 711.4

Iceland 192 2.0 2.1 1.7 0.2 1.2 2.4 3.7

Ireland, Republic of 2,674 3.4 43.6 46.2 6.0 34.4 49.4 89.8

Israel 3,959 7.1 140.9 140.7 36.8 102.7 142.1 281.6

Italy 43,925 6.6 1,400.2 1,479.9 185.7 1,009.4 1,684.9 2,880.1

Kazakhstan 10,235 5.5 147.3 411.6 305.2 253.8 39.1 288.8 231.1 558.9

Kyrgyzstan 2,896 4.3 57.7 67.1 71.4 53.5 9.1 62.1 53.6 124.8

Latvia 1,758 9.9 77.5 96.1 15.1 58.4 100.1 173.6

Lithuania 2,648 9.4 114.7 134.2 24.6 84.8 139.5 248.9

Luxembourg 327 3.8 5.8 6.8 0.1 3.0 9.3 12.5

Macedonia 1,428 4.9 30.9 39.0 2.5 23.2 44.2 69.9

Malta 280 9.2 10.6 15.3 0.3 9.0 16.5 25.8

Moldova, Republic of 2,915 9.3 117.2 124.6 26.6 97.8 117.3 241.8

Monacoa 23 6.1 0.7 0.7 0.1 0.6 0.8 1.4

Netherlands 11,678 3.7 203.4 228.8 5.3 118.3 308.5 432.2

Norway 3,154 6.7 95.5 116.2 19.8 69.6 122.3 211.7

Poland 27,852 9.0 1,238.7 1,267.8 239.0 1,002.5 1,265.0 2,506.5

Portugal 7,471 7.8 278.5 305.9 14.9 170.9 398.7 584.5

Romania 16,392 9.3 760.0 759.2 154.7 519.0 845.6 1,519.2

Russian Federation 105,244 9.2 4,417.7 5,275.9 899.4 3,637.5 5,156.7 9,693.6

San Marinoa 20 6.1 0.6 0.6 0.1 0.5 0.7 1.2

Serbia and Montenegro 7,542 5.6 182.0 240.1 11.8 127.1 283.2 422.1

Slovakia 3,903 8.7 167.5 171.3 35.9 135.6 167.2 338.7

Slovenia 1,511 9.6 72.2 73.1 13.1 53.5 78.6 145.2

Spain 30,329 9.9 1,209.7 1,794.6 838.4 973.2 1,192.6 3,004.3

Sweden 6,290 7.3 206.4 250.5 36.3 140.1 280.5 456.9

Switzerland 5,310 9.5 235.0 270.0 35.3 166.6 303.1 504.9

Tajikistan 3,174 3.7 62.9 53.8 70.3 46.4 9.6 57.5 49.6 116.7

Turkey 42,411 7.0 514.1 2,444.6 1,254.3 1,704.4 370.4 1,440.7 1,147.7 2,958.7

Turkmenistan 2,648 4.0 42.5 62.5 61.7 43.3 9.7 55.7 39.6 105.0

Ukraine 35,625 9.7 1,552.3 1,901.1 302.2 1,154.7 1,996.6 3,453.4

United Kingdom 42,423 3.9 813.7 857.9 89.4 588.9 993.3 1,671.5

Uzbekistan 14,144 4.0 244.0 316.5 333.0 227.5 48.7 287.7 224.1 560.5

EUR Total * 621,235 7.8 1,429 4,276 22,337 26,041 4,462 17,388 26,528 48,378

Table 1.17Prevalence estimates of diabetes mellitus (DM), 2003 – European Region


a. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of developed world population 2003.





Population (20-79)

DM prevalence



Albania 2,559 5.1 61.3 69.9 4.5 43.5 83.2 131.2

Andorraa 52 9.5 2.5 2.5 0.1 1.3 3.5 4.9

Austria 5,887 11.9 338.3 364.5 28.2 187.0 487.5 702.8

Azerbaijan Republic 6,793 9.4 156.8 479.5 259.4 376.9 53.6 285.3 297.3 636.3

Belarus 7,233 10.7 356.5 416.6 58.5 259.3 455.3 773.1

Belgium 7,658 5.2 180.4 214.2 2.6 74.9 317.1 394.6


Bulgaria 4,871 11.6 93.7 471.2 223.1 341.7 28.8 233.3 302.8 564.9

Croatia 3,304 6.7 96.6 123.9 4.6 58.5 157.5 220.5

Cyprus 637 6.3 18.3 21.8 1.0 10.5 28.6 40.1

Czech Republic 7,599 11.7 441.9 445.5 51.9 292.2 543.3 887.4

Denmark 3,988 8.3 148.3 182.2 20.3 83.3 226.8 330.4

Estonia 814 11.0 41.7 47.7 6.4 30.2 52.8 89.4

Finland 3,822 10.0 186.0 198.0 9.3 47.1 327.6 383.9

France 45,141 7.3 1,609.5 1,675.8 156.3 1,058.2 2,070.8 3,285.3

Georgia, Republic of 3,341 10.7 79.0 278.7 142.5 215.2 22.1 143.1 192.5 357.7

Germany 60,030 11.9 3,459.1 3,684.5 293.8 1,852.9 4,997.0 7,143.7

Greece 7,767 7.3 254.3 312.1 9.2 153.4 403.8 566.4

Hungary 6,807 11.2 364.7 397.0 49.4 261.7 450.6 761.7

Iceland 229 2.5 3.2 2.6 0.2 1.4 4.2 5.8


Israel 5,776 8.1 243.4 224.9 48.9 151.2 268.2 468.3

Italy 40,482 7.9 1,583.5 1,614.8 116.4 1,093.1 1,988.8 3,198.3

Kazakhstan 11,358 7.0 153.9 642.6 429.9 366.6 47.7 371.7 377.2 796.5

Kyrgyzstan 4,355 5.8 86.9 164.8 143.6 108.1 16.5 124.0 111.1 251.6

Latvia 1,610 11.1 84.4 93.7 12.7 60.0 105.5 178.2

Lithuania 2,626 10.8 136.0 148.1 21.2 96.8 166.1 284.1

Luxembourg 415 4.4 8.4 9.8 0.2 3.7 14.3 18.1

Macedonia 1,598 6.1 43.6 53.1 2.5 28.7 65.5 96.7

Malta 304 11.6 15.4 19.7 0.3 7.9 26.9 35.1


Monacoa 24 7.2 0.9 0.9 0.1 0.6 1.1 1.7

Netherlands 12,538 5.1 290.9 344.4 4.4 127.8 503.2 635.3

Norway 3,534 8.2 129.3 159.1 18.6 73.0 196.8 288.5

Poland 28,567 11.0 1,545.9 1,606.7 217.8 1,017.5 1,917.3 3,152.6

Portugal 7,456 9.5 344.4 361.8 11.0 210.7 484.5 706.2

Romania 15,860 10.6 834.3 842.7 123.0 645.1 908.8 1,676.9

Russian Federation 98,969 10.9 4,909.1 5,837.5 784.7 3,536.9 6,425.0 10,746.6

San Marinoa 21 7.2 0.7 0.8 0.1 0.5 0.9 1.5


Slovakia 4,127 10.7 219.2 224.1 31.7 153.6 258.1 443.3

Slovenia 1,451 12.0 86.8 86.7 9.5 54.7 109.2 173.5

Spain 29,155 10.1 1,478.9 1,466.0 40.0 874.0 2,030.9 2,944.9

Sweden 6,373 8.6 245.6 302.6 32.9 131.5 383.8 548.2

Switzerland 5,114 12.6 308.0 338.5 24.5 147.2 474.8 646.5

Tajikistan 5,305 5.1 110.1 158.2 158.2 110.1 20.1 139.2 109.0 268.3

Turkey 59,689 9.1 551.7 4,878.5 2,285.4 3,144.8 435.1 2,665.9 2,329.1 5,430.2

Turkmenistan 4,537 5.5 75.6 171.9 142.5 105.0 18.4 127.4 101.6 247.5

Ukraine 31,102 10.8 1,558.4 1,799.5 247.7 1,142.4 1,967.8 3,357.9

United Kingdom 45,322 4.7 1,079.8 1,061.5 79.4 628.2 1,433.7 2,141.4

Uzbekistan 22,883 5.7 422.3 875.0 753.5 543.8 92.7 662.5 542.1 1,297.3

EUR Total * 646,334 9.1 1,730 8,120 27,842 30,796 3,325 19,800 35,512 58,638

Table 1.18Prevalence estimates of diabetes mellitus (DM), 2025 – European Region


a. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of developed world population from 2003 to 2025.





Population (20-79)

IGT prevalence



Albania 1,966 6.5 45.2 81.9 35.7 53.9 37.4 127.1

Andorraa 50 9.9 2.0 2.9 1.3 1.8 1.9 4.9

Austria 5,991 5.8 161.0 184.2 0.7 84.2 260.4 345.3

Azerbaijan Republic 5,154 6.5 108.6 228.4 95.2 137.8 104.1 337.0

Belarus 7,336 17.0 487.1 760.0 287.8 484.5 474.7 1,247.1

Belgium 7,531 6.4 237.8 243.7 54.8 141.6 285.0 481.5


Bulgaria 5,894 8.0 162.3 308.5 78.9 188.7 203.2 470.8

Croatia 3,412 7.9 92.1 177.6 46.2 107.6 115.9 269.7

Cyprus 541 7.4 14.2 26.0 7.9 17.5 14.8 40.2

Czech Republic 7,734 17.0 563.8 754.4 300.4 539.5 478.3 1,318.3

Denmark 3,863 8.6 107.3 225.3 62.9 105.7 164.0 332.5

Estonia 991 17.3 67.4 104.3 38.1 65.0 68.6 171.7

Finland 3,775 6.6 101.6 148.3 0.5 42.4 207.0 249.9

France 42,546 5.6 974.6 1,415.2 457.4 829.3 1,103.1 2,389.9

Georgia, Republic of 3,681 7.6 92.2 189.1 54.2 110.3 116.9 281.3

Germany 61,895 6.3 1,849.6 2,049.5 6.4 840.5 3,052.2 3,899.1

Greece 8,069 8.0 232.4 411.6 112.4 239.4 292.2 644.0

Hungary 7,350 17.2 519.4 747.8 281.7 496.7 488.8 1,267.2

Iceland 192 5.5 5.6 4.9 1.6 3.5 5.3 10.5


Israel 3,959 5.4 129.7 82.6 43.3 85.8 83.2 212.3

Italy 43,925 5.8 1,042.0 1,513.3 467.0 800.6 1,287.6 2,555.2

Kazakhstan 10,235 5.4 207.5 344.5 98.2 250.1 203.7 552.0

Kyrgyzstan 2,896 4.9 54.9 88.2 30.7 61.1 51.3 143.1

Latvia 1,758 17.5 120.1 187.3 66.6 114.4 126.4 307.4

Lithuania 2,648 17.0 179.9 271.2 107.8 167.4 175.8 451.1

Luxembourg 327 6.0 9.9 9.7 2.5 6.1 11.0 19.6

Macedonia 1,428 7.3 36.3 67.3 22.1 44.1 37.5 103.6

Malta 280 7.5 10.1 11.0 1.3 10.7 9.1 21.1


Monacoa 23 5.5 0.5 0.8 0.3 0.4 0.6 1.3

Netherlands 11,678 5.9 352.0 334.6 90.5 232.6 363.6 686.6

Norway 3,154 8.5 85.1 183.3 53.8 84.8 129.9 268.4

Poland 27,852 16.6 1,950.2 2,675.6 1,091.8 1,952.2 1,581.8 4,625.8

Portugal 7,471 9.9 290.0 452.6 204.9 242.4 295.2 742.6

Romania 16,392 16.8 1,174.4 1,576.0 692.6 1,000.9 1,057.0 2,750.5

Russian Federation 105,244 16.9 7,009.0 10,793.1 4,050.3 7,255.9 6,495.8 17,802.0

San Marinoa 20 5.5 0.4 0.7 0.2 0.4 0.5 1.1


Slovakia 3,903 16.3 267.3 369.4 163.0 263.9 209.9 636.7

Slovenia 1,511 17.2 111.3 148.3 57.8 103.3 98.5 259.6

Spain 30,329 9.9 1,209.7 1,794.6 838.4 973.2 1,192.6 3,004.3

Sweden 6,290 9.0 181.9 383.7 98.9 169.5 297.2 565.6

Switzerland 5,310 6.1 155.6 169.1 0.5 84.6 239.7 324.8

Tajikistan 3,174 4.5 57.1 86.2 36.7 59.4 47.2 143.3

Turkey 42,411 6.2 910.4 1,735.1 798.9 1,102.9 743.6 2,645.4

Turkmenistan 2,648 4.5 46.6 73.8 30.3 53.7 36.3 120.3

Ukraine 35,625 17.3 2,410.3 3,760.7 1,360.5 2,291.0 2,519.5 6,171.0

United Kingdom 42,423 5.1 1,362.3 783.8 591.3 904.1 650.7 2,146.1

Uzbekistan 14,144 4.6 255.3 392.9 160.3 280.9 207.0 648.2

EUR Total * 621,235 10.2 26,001 37,199 13,404 23,673 26,123 63,200

Table 1.19Prevalence estimates of impaired glucose tolerance (IGT), 2003 – European Region

* The totals may not be the exact sum of the columns due to rounding.

a. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of developed world population 2003.





Population (20-79)

IGT prevalence



Albania 2,559 7.4 70.0 120.0 38.8 79.4 71.8 190.0

Andorraa 52 10.6 2.4 3.2 1.1 1.8 2.6 5.6

Austria 5,887 7.9 230.3 234.4 0.4 102.1 362.1 464.6

Azerbaijan Republic 6,793 7.6 179.4 339.7 103.6 220.6 194.9 519.1

Belarus 7,233 18.3 536.8 787.5 243.2 505.3 575.9 1,324.4

Belgium 7,658 7.4 276.6 287.1 47.3 140.7 375.7 563.7


Bulgaria 4,871 8.7 148.1 276.1 54.0 172.7 197.6 424.2

Croatia 3,304 8.4 100.8 177.9 39.3 106.3 133.1 278.7

Cyprus 637 8.1 19.3 32.3 8.5 19.3 23.9 51.7

Czech Republic 7,599 19.1 637.2 811.9 219.1 556.0 673.9 1,449.1

Denmark 3,988 9.9 128.6 267.4 56.9 99.9 239.2 396.0

Estonia 814 18.6 62.2 88.8 26.6 58.0 66.4 151.0

Finland 3,822 9.4 159.1 200.3 0.5 35.8 323.1 359.3

France 45,141 6.3 1,187.3 1,636.8 411.6 823.7 1,588.8 2,824.0

Georgia, Republic of 3,341 8.3 96.5 181.6 42.5 109.2 126.5 278.2

Germany 60,030 7.9 2,366.1 2,380.4 4.7 1,004.2 3,737.6 4,746.5

Greece 7,767 8.9 258.1 430.4 77.6 273.2 337.8 688.5

Hungary 6,807 18.7 537.6 733.3 210.7 498.6 561.7 1,271.0

Iceland 229 6.6 7.7 7.4 1.6 4.1 9.4 15.1


Israel 5,776 5.9 214.4 129.1 57.4 126.0 160.1 343.5

Italy 40,482 6.5 1,124.3 1,526.3 302.1 832.7 1,515.8 2,650.6

Kazakhstan 11,358 6.3 279.8 431.8 101.7 296.6 313.2 711.5

Kyrgyzstan 4,355 5.7 100.3 147.4 43.6 108.2 95.9 247.7

Latvia 1,610 18.6 125.4 174.6 52.2 114.9 132.8 299.9

Lithuania 2,626 18.4 202.7 279.8 88.5 184.4 209.6 482.5

Luxembourg 415 6.5 13.7 13.5 3.1 7.1 16.9 27.1

Macedonia 1,598 8.1 47.3 81.6 20.8 52.8 55.3 129.0

Malta 303 8.5 12.7 13.0 1.4 9.7 14.6 25.7


Monacoa 24 6.1 0.6 0.9 0.2 0.5 0.8 1.5

Netherlands 12,538 7.3 447.7 463.9 79.5 235.5 596.6 911.5

Norway 3,534 9.8 112.4 234.7 51.7 87.7 207.7 347.1

Poland 28,567 18.5 2,278.3 3,010.0 914.1 1,981.9 2,392.3 5,288.3

Portugal 7,456 10.6 334.2 459.2 148.4 286.5 358.5 793.4

Romania 15,860 18.1 1,246.2 1,631.4 518.0 1,225.8 1,133.8 2,877.6

Russian Federation 98,969 18.5 7,361.1 10,924.1 3,258.1 6,911.1 8,116.0 18,285.2

San Marinoa 21 6.1 0.5 0.8 0.2 0.4 0.7 1.3


Slovakia 4,127 18.3 326.0 427.9 134.1 296.6 323.2 753.9

Slovenia 1,451 19.3 124.0 156.0 40.2 103.6 136.2 280.0

Spain 29,155 10.9 1,395.2 1,780.4 506.9 1,170.3 1,498.3 3,175.5

Sweden 6,373 10.2 212.6 436.7 87.0 158.0 404.3 649.3

Switzerland 5,114 8.4 215.2 212.1 0.4 79.8 347.1 427.3

Tajikistan 5,305 5.2 114.4 163.8 58.0 126.1 94.1 278.2

Turkey 59,689 7.2 1,536.6 2,772.9 898.1 1,941.6 1,469.7 4,309.4

Turkmenistan 4,537 5.3 97.8 143.4 47.4 108.4 85.4 241.2

Ukraine 31,102 18.4 2,339.6 3,385.9 1,027.5 2,212.9 2,485.1 5,725.5

United Kingdom 45,322 5.3 1,507.9 901.2 538.8 917.3 953.0 2,409.1

Uzbekistan 22,883 5.5 521.2 743.0 236.0 571.2 457.0 1,264.2

EUR Total * 646,334 10.9 29,965 40,589 11,097 25,597 33,860 70,553

Table 1.20Prevalence estimates of impaired glucose tolerance (IGT), 2025 – European Region


a. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of developed world population from 2003 to 2025.






Anguilla Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Antigua and Barbuda Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Aruba Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Bahamas Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Barbadosa Barbados (Hennis et al, 2002)87 SR or HbA1c > 10% Known diabetes 4,104 40-79

Belize Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Bermuda Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

British Virgin Islands Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Canadab Canada (Hux et al, 2002)36 Registry Known diabetes N/A 20+

Cayman Islands Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Dominica, Commonwealth of Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Grenada Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Guadeloupea Guadeloupe (Costagliola et al, 1991)88 SR or FBG > 8.0 WHO – 1980 1,036 18+

Guyana Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Haiti Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Jamaica Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Martiniquea Guadeloupe (Costagliola et al, 1991)87 SR or FBG > 8.0 WHO – 1980 1,036 18+

Mexicoc,d Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

St Kitts and Nevis Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

St Lucia Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

St Vincent and the Grenadinesa Barbados (Hennis et al, 2002)87 SR or HbA1c > 10% Known diabetes 4,104 40-79

Trinidad and Tobago Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

USA USA (Harris et al, 1998)91 FBG ADA – 1997 18,825 20+

Table 1.21Data sources: prevalence estimates of diabetes mellitus (DM) and impaired glucose tolerance (IGT) – North American Region

a. Because of the absence of data for IGT in the study used for diabetes, IGT figures were calculated from Jamaican data.

b. Because of the absence of data for IGT in the study used for diabetes, impaired fasting glucose (IFG) figures were calculated from USA data.

c. The prevalence was obtained by combining the data from the two studies.d. Because of the absence of data for IGT in the studies used for diabetes, IGT figures were calculated from

Brazilian data.






Anguilla Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Antigua and Barbuda Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Aruba Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Bahamas Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Barbadosa Barbados (Hennis et al, 2002)87 SR or HbA1c > 10% Known diabetes 4,104 40-79

Belize Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Bermuda Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

British Virgin Islands Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Canadab Canada (Hux et al, 2002)36 Registry Known diabetes N/A 20+

Cayman Islands Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Dominica, Commonwealth of Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Grenada Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Guadeloupea Guadeloupe (Costagliola et al, 1991)88 SR or FBG > 8.0 WHO – 1980 1,036 18+

Guyana Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Haiti Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Jamaica Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Martiniquea Guadeloupe (Costagliola et al, 1991)87 SR or FBG > 8.0 WHO – 1980 1,036 18+

Mexicoc,d Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

St Kitts and Nevis Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

St Lucia Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

St Vincent and the Grenadinesa Barbados (Hennis et al, 2002)87 SR or HbA1c > 10% Known diabetes 4,104 40-79

Trinidad and Tobago Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

USA USA (Harris et al, 1998)91 FBG ADA – 1997 18,825 20+





Population (20-79)

DM prevalence



Anguillaa 8 5.5 0.3 0.1 0.2 0.2 0.1 0.3 0.1 0.4

Antigua and Barbudaa 41 5.8 1.6 0.7 1.2 1.2 0.4 1.4 0.6 2.4

Arubaa 43 9.7 2.1 2.1 0.6 2.5 1.0 4.2

Bahamas 193 9.0 6.1 11.2 2.8 9.5 5.0 17.3

Barbados 189 8.5 5.2 10.9 7.4 8.7 2.1 8.2 5.8 16.1

Belize 124 5.7 2.6 4.5 3.6 3.5 1.5 4.2 1.4 7.1

Bermudaa 39 9.7 1.9 1.9 0.6 2.3 0.9 3.8

British Virgin Islandsa 13 8.3 0.3 0.8 0.5 0.6 0.2 0.6 0.3 1.1

Canada 22,640 9.0 1,099.3 935.0 158.1 871.0 1,005.1 2,034.3

Cayman Islandsa 22 9.7 1.1 1.1 0.3 1.3 0.5 2.2

Dominica, Commonwealth of a 42 8.4 0.6 3.0 1.7 1.8 0.5 2.1 0.9 3.5

Grenadaa 54 6.8 1.6 2.1 1.8 1.9 0.6 2.2 0.9 3.7

Guadeloupe 289 6.5 0.0 18.7 8.8 10.0 2.3 9.3 7.2 18.8

Guyana 457 6.0 11.9 15.7 9.4 18.2 5.0 15.3 7.3 27.6

Haiti 4,113 5.7 109.9 126.4 79.6 156.7 41.4 127.8 67.1 236.3

Jamaica 1,528 7.2 30.0 80.6 39.4 71.3 17.7 58.0 35.0 110.6

Martinique 265 6.5 16.8 0.4 7.9 9.3 2.1 8.0 7.2 17.3

Mexico 59,336 7.4 631.8 3,776.7 1,616.7 2,791.9 646.6 2,168.7 1,593.2 4,408.5

St Kitts and Nevisa 23 6.6 0.7 0.8 0.8 0.8 0.2 0.9 0.4 1.5

St Lucia 101 6.2 2.8 3.5 3.0 3.3 1.1 3.8 1.4 6.3

St Vincent and the Grenadinesa 71 7.7 1.5 4.0 2.7 2.7 0.8 3.3 1.3 5.4

Trinidad and Tobago 861 7.9 9.7 58.3 10.9 57.0 58.4 9.3 0.2 67.9

USA 199,097 8.0 8,040.5 7,979.5 1,550.8 7,507.3 6,962.0 16,020.0

NA Total * 289,550 7.9 827 4,107 10,947 12,070 2,494 10,817 9,705 23,016

Table 1.22Prevalence estimates of diabetes mellitus (DM), 2003 – North American Region


a. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of the world population 2003.





Population (20-79)

DM prevalence



Anguillaa 11 6.7 0.4 0.3 0.4 0.4 0.1 0.4 0.2 0.7

Antigua and Barbudaa 57 8.2 1.6 3.1 2.3 2.3 0.6 2.7 1.4 4.6

Arubaa 59 10.9 3.2 3.2 0.8 3.8 1.9 6.4

Bahamas 266 11.4 10.5 19.9 3.1 15.6 11.6 30.3

Barbados 217 12.8 6.2 21.6 13.5 14.3 1.7 11.6 14.4 27.8

Belize 216 7.8 4.6 12.3 8.5 8.5 2.6 10.5 3.8 16.9

Bermudaa 54 10.9 2.9 3.0 0.7 3.4 1.7 5.9

British Virgin Islandsa 18 9.6 0.2 1.5 0.9 0.9 0.2 1.0 0.5 1.7

Canada 27,135 11.2 1,650.9 1,380.5 162.0 941.6 1,927.8 3,031.5

Cayman Islandsa 31 10.9 1.7 1.7 0.4 2.0 1.0 3.4

Dominica, Commonwealth of a 58 9.8 0.7 5.0 2.8 2.9 0.7 3.3 1.7 5.7

Grenadaa 74 8.4 1.9 4.3 3.1 3.1 0.8 3.6 1.8 6.2

Guadeloupe 345 8.2 0.0 28.3 13.4 14.9 2.0 12.1 14.1 28.3

Guyana 480 9.5 13.5 32.0 14.2 31.3 4.1 24.3 17.1 45.5

Haiti 6,679 7.0 150.1 314.2 156.5 307.7 79.8 251.1 133.3 464.2

Jamaica 2,197 9.6 39.7 170.1 75.1 134.7 24.0 110.7 75.2 209.8

Martinique 305 8.2 0.4 24.6 11.8 13.1 1.8 11.0 12.2 25.0

Mexico 87,640 10.3 968.8 8,065.8 3,234.7 5,800.0 800.9 4,452.3 3,781.4 9,034.6

St Kitts and Nevisa 32 8.0 1.0 1.6 1.3 1.3 0.3 1.5 0.8 2.6

St Lucia 132 8.4 3.7 7.4 5.4 5.7 1.3 6.6 3.2 11.1

St Vincent and the Grenadinesa 97 9.4 1.5 7.7 4.5 4.6 1.1 5.3 2.7 9.1

Trinidad and Tobago 1,042 11.8 12.2 111.0 43.7 79.5 10.9 62.0 50.3 123.2

USA 247,219 9.3 11,735.1 11,345.4 1,753.7 8,099.7 13,227.0 23,080.5

NA Total * 374,364 9.7 1,207 8,811 16,996 19,179 2,854 14,036 19,285 36,175

Table 1.23Prevalence estimates of diabetes mellitus (DM), 2025 – North American Region


a. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of world population growth from 2003 to 2025.





Population (20-79)

IGT prevalence



Anguillaa 8 11.3 0.4 0.5 0.2 0.4 0.3 0.9

Antigua and Barbudaa 41 11.3 1.9 2.8 1.3 1.9 1.5 4.6

Arubaa 43 11.3 2.0 2.9 1.3 2.0 1.5 4.9

Bahamas 193 10.7 7.7 13.0 6.5 8.5 5.7 20.7

Barbados 189 11.6 8.5 13.6 5.6 9.6 6.8 22.1

Belize 124 9.8 4.7 7.3 4.6 4.5 3.0 12.1

Bermudaa 39 11.3 1.8 2.6 1.2 1.8 1.4 4.4

British Virgin Islandsa 13 11.3 0.6 0.9 0.4 0.6 0.5 1.5

Canadab 22,640 7.1 1,002.7 601.7 277.2 723.1 604.1 1,604.4

Cayman Islandsa 22 11.3 1.0 1.5 0.7 1.0 0.8 2.5

Dominica, Commonwealth of a 42 11.3 1.9 2.8 1.3 1.9 1.5 4.8

Grenadaa 54 11.3 2.5 3.6 1.7 2.5 1.9 6.1

Guadeloupe 289 11.9 13.7 20.8 8.5 14.4 11.6 34.5

Guyana 457 10.2 16.3 30.3 16.6 18.6 11.4 46.5

Haiti 4,113 10.0 144.2 268.1 148.6 158.3 105.4 412.3

Jamaica 1,528 10.8 63.8 101.5 51.6 62.9 50.8 165.3

Martinique 265 12.2 12.8 19.6 7.8 12.7 11.9 32.4

Mexico 59,336 6.6 1,715.4 2,199.7 1,506.0 1,548.6 860.5 3,915.1

St Kitts and Nevisa 23 11.3 1.1 1.6 0.7 1.1 0.8 2.7

St Lucia 101 10.7 4.1 6.7 3.5 4.3 3.0 10.7

St Vincent and the Grenadinesa 71 11.3 3.3 4.7 2.2 3.3 2.5 8.0

Trinidad and Tobago 861 11.1 38.1 57.5 26.6 41.4 27.6 95.5

USAb 199,097 7.0 8,650.6 5,255.8 2,481.1 6,292.6 5,132.6 13,906.4

NA Total * 289,550 7.0 11,699 8,619 4,555 8,916 6,847 20,318

Table 1.24Prevalence estimates of impaired glucose tolerance (IGT), 2003 – North American Region


a. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of world population 2003.b. Prevalence figures are for impaired fasting glucose (IFG) (not IGT) as only fasting specimens were measured for the majority of NHANES III

participants.





Population (20-79)

IGT prevalence



Anguillaa 11 12.5 0.6 0.8 0.3 0.5 0.5 1.3

Antigua and Barbudaa 57 12.5 3.0 4.0 1.5 2.8 2.7 7.1

Arubaa 59 12.5 3.2 4.2 1.6 2.9 2.8 7.4

Bahamas 266 12.5 13.4 19.9 7.1 13.6 12.6 33.3

Barbados 217 14.7 14.4 17.5 4.3 12.2 15.4 31.9

Belize 216 11.3 10.0 14.2 6.7 10.5 7.1 24.3

Bermudaa 54 12.5 2.9 3.8 1.5 2.7 2.6 6.7

British Virgin Islandsa 18 12.5 1.0 1.3 0.5 0.9 0.9 2.3

Canadab 27,135 8.1 1,344.0 866.0 283.6 766.2 1,160.2 2,210.0

Cayman Islandsa 31 12.5 1.7 2.2 0.8 1.5 1.5 3.9

Dominica, Commonwealth of a 58 12.5 3.1 4.1 1.6 2.9 2.8 7.2

Grenadaa 74 12.5 4.0 5.3 2.0 3.7 3.6 9.3

Guadeloupe 345 14.1 21.1 27.5 7.7 18.2 22.7 48.6

Guyana 480 12.7 22.6 38.2 12.0 26.3 22.6 60.8

Haiti 6,679 10.5 247.1 452.1 233.4 282.2 183.6 699.2

Jamaica 2,197 12.2 110.8 157.8 60.9 110.7 97.0 268.6

Martinique 305 14.1 18.7 24.4 6.7 16.7 19.7 43.2

Mexico 87,640 7.6 2,832.7 3,841.9 1,719.9 2,987.2 1,967.4 6,674.5

St Kitts and Nevisa 32 12.5 1.7 2.3 0.9 1.6 1.5 4.0

St Lucia 132 12.6 7.0 9.6 3.5 6.9 6.2 16.6

St Vincent and the Grenadinesa 97 12.5 5.2 6.9 2.6 4.9 4.7 12.2

Trinidad and Tobago 1,042 13.7 61.6 80.9 23.9 57.6 61.0 142.4

USAb 247,219 7.8 11,790.3 7,505.9 2,826.9 6,709.0 9,760.2 19,296.2

NA Total * 374,364 7.9 16,520 13,091 5,210 11,042 13,359 29,611

Table 1.25Prevalence estimates of impaired glucose tolerance (IGT), 2025 – North American Region



b. Prevalence figures are for IFG (not IGT) as only fasting specimens were measured for the majority of NHANES III participants.






Argentinaa,b Argentina (Hernandez et al, 1987)92 2BG (50g) WHO – 1980 809 20-74

Bolivia Bolivia (Barceló et al, 2001)93 2BG WHO – 1985 2,948 25+

Brazil Brazil (Oliveira et al, 1996 and Malerbi et al, 1992)94,95 OGTT WHO – 1985 23,898 30-69

Chile Paraguay (Jimenez et al, 1998)96 OGTT WHO – 1985 1,606 20-74

Colombia Colombia (Aschner et al, 1993)97 2BG WHO – 1985 670 30-79

Costa Ricac Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

Cuba Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Dominican Republic Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Ecuador Bolivia (Barceló et al, 2001)93 2BG WHO – 1985 2,948 25+

El Salvadorc Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

French Guiana Suriname (Schaad et al, 1985)98 OGTT WHO – 1980 1,218 30+

Guatemalac Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

Hondurasc Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

Netherlands Antillesb Barbados (Hennis et al, 2002)87 SR or HbA1c > 10% Known Diabetes 4,104 40-79

Nicaraguac Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

Panamac Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

Paraguay Paraguay (Jimenez et al, 1998)96 OGTT WHO – 1985 1,606 20-74

Peru Bolivia (Barceló et al, 2001)93 2BG WHO – 1985 2,948 25+

Puerto Rico Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Suriname Suriname (Schaad et al, 1985)98 OGTT WHO – 1980 1,218 30+

Uruguay Paraguay (Jimenez et al, 1998)96 OGTT WHO – 1985 1,606 20-74

Venezuela Brazil (Oliveira et al, 1996 and Malerbi et al, 1992)94,95 OGTT WHO – 1985 23,898 30-69

Table 1.26Data sources: prevalence estimates of diabetes mellitus (DM) and impaired glucose tolerance (IGT) – South and Central American Region

a. Persons with previously diagnosed diabetes were excluded from the study, and obtained prevalence doubled.b. Because of the absence of data for IGT in the Argentinian and Barbados studies, the following countries had

IGT prevalence determined from the study indicated below: Argentina: Paraguay (Jimenez et al, 1998)97

Netherlands Antilles: Jamaica (Wilks et al, 1999)86

c. Diabetes prevalence was derived by combining the data of the two studies indicated.IGT prevalence was calculated from Brazilian data.






Argentinaa,b Argentina (Hernandez et al, 1987)92 2BG (50g) WHO – 1980 809 20-74

Bolivia Bolivia (Barceló et al, 2001)93 2BG WHO – 1985 2,948 25+

Brazil Brazil (Oliveira et al, 1996 and Malerbi et al, 1992)94,95 OGTT WHO – 1985 23,898 30-69

Chile Paraguay (Jimenez et al, 1998)96 OGTT WHO – 1985 1,606 20-74

Colombia Colombia (Aschner et al, 1993)97 2BG WHO – 1985 670 30-79

Costa Ricac Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

Cuba Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Dominican Republic Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Ecuador Bolivia (Barceló et al, 2001)93 2BG WHO – 1985 2,948 25+

El Salvadorc Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

French Guiana Suriname (Schaad et al, 1985)98 OGTT WHO – 1980 1,218 30+

Guatemalac Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

Hondurasc Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

Netherlands Antillesb Barbados (Hennis et al, 2002)87 SR or HbA1c > 10% Known Diabetes 4,104 40-79

Nicaraguac Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

Panamac Mexico (Stern et al, 1992 and Posadas-Romero et al, 1994)89,90 OGTT/FBG WHO – 1985 1,451 20-79

Paraguay Paraguay (Jimenez et al, 1998)96 OGTT WHO – 1985 1,606 20-74

Peru Bolivia (Barceló et al, 2001)93 2BG WHO – 1985 2,948 25+

Puerto Rico Jamaica (Wilks et al, 1999)86 OGTT WHO – 1980 1,303 25-74

Suriname Suriname (Schaad et al, 1985)98 OGTT WHO – 1980 1,218 30+

Uruguay Paraguay (Jimenez et al, 1998)96 OGTT WHO – 1985 1,606 20-74

Venezuela Brazil (Oliveira et al, 1996 and Malerbi et al, 1992)94,95 OGTT WHO – 1985 23,898 30-69





Population (20-79)

DM prevalence



Argentina 23,958 5.4 69.6 1,234.8 562.6 741.8 313.0 456.9 534.5 1,304.5

Bolivia 4,480 4.8 43.4 173.5 99.6 117.3 32.8 110.7 73.4 216.9

Brazil 109,901 5.2 548.1 5,133.9 2,496.0 3,186.0 732.3 2,733.7 2,216.1 5,682.0

Chile 9,864 5.6 45.3 511.9 231.2 326.0 77.7 268.2 211.2 557.1

Colombia 25,524 4.3 150.3 948.2 491.6 606.9 118.4 615.9 364.2 1,098.5

Costa Rica 2,493 6.9 52.4 119.5 66.3 105.6 22.7 87.5 61.8 172.0

Cuba 7,980 13.2 124.7 928.4 386.1 667.0 144.8 548.1 360.1 1,053.0

Dominican Republic 4,991 10.0 100.1 399.6 190.8 308.9 84.0 279.9 135.9 499.7

Ecuador 7,548 4.8 79.3 281.5 170.9 189.9 55.5 185.9 119.3 360.7

El Salvador 3,620 6.2 79.9 145.2 79.5 145.6 32.3 104.8 88.0 225.1

French Guiana 100 11.1 1.3 9.7 4.9 6.1 2.3 6.5 2.3 11.0

Guatemala 5,620 5.5 127.9 180.6 117.0 191.5 48.1 147.5 113.0 308.5

Honduras 3,302 5.7 65.0 122.4 70.6 116.9 30.7 90.3 66.5 187.5

Netherlands Antilles 148 12.3 3.1 15.2 7.4 10.8 1.6 9.5 7.1 18.2

Nicaragua 2,567 6.1 32.4 125.0 58.0 99.4 26.7 78.5 52.1 157.4

Panama 1,779 7.3 33.5 95.9 50.0 79.4 17.1 64.4 47.9 129.4

Paraguay 2,979 3.9 31.0 84.2 51.7 63.5 21.9 58.2 35.1 115.2

Peru 15,397 5.1 120.1 672.3 367.4 425.1 118.4 402.9 271.2 792.5

Puerto Rico 2,671 13.2 47.7 303.6 115.5 235.8 40.3 183.4 127.7 351.3

Suriname 251 8.6 6.5 15.1 8.4 13.3 5.7 10.0 6.0 21.7

Uruguay 2,217 6.8 6.5 143.6 54.5 95.6 15.6 60.1 74.5 150.1

Venezuela 14,460 5.2 47.7 697.8 341.3 404.2 100.9 366.2 278.3 745.5

SACA Total * 251,850 5.6 1,816 12,342 6,021 8,137 2,043 6,869 5,246 14,158

Table 1.27Prevalence estimates of diabetes mellitus (DM), 2003 – South and Central American Region






Population (20-79)

DM prevalence



Argentina 31,775 5.8 68.6 1,773.8 836.1 1,006.3 377.6 667.3 797.5 1,842.4

Bolivia 7,927 5.7 58.1 391.6 209.1 240.7 60.1 231.7 158.0 449.8

Brazil 150,418 7.1 671.8 9,984.9 4,555.5 6,101.2 855.0 4,613.8 5,188.0 10,656.7

Chile 13,327 6.8 55.1 851.2 356.0 550.3 91.9 376.9 437.5 906.3

Colombia 39,178 5.8 217.4 2,057.0 1,024.6 1,249.8 157.5 1,131.9 985.0 2,274.4

Costa Rica 3,909 9.4 77.2 290.5 139.3 228.4 33.3 164.3 170.2 367.7

Cuba 8,749 17.3 124.2 1,388.1 541.3 970.9 109.3 747.1 655.8 1,512.3

Dominican Republic 7,081 13.0 123.8 796.4 331.6 588.6 109.4 483.5 327.3 920.2

Ecuador 11,887 6.4 112.0 651.1 357.0 406.0 81.1 389.3 292.7 763.1

El Salvador 5,775 8.2 120.9 353.0 168.0 305.9 49.4 242.2 182.3 473.9

French Guiana 190 13.7 2.2 23.9 11.4 14.7 9.4 9.1 7.7 26.1

Guatemala 11,171 6.5 214.5 513.2 271.4 456.3 105.7 368.6 253.3 727.7

Honduras 6,123 7.2 105.0 336.2 163.9 277.2 60.1 219.5 161.6 441.1

Netherlands Antilles 180 15.4 3.3 24.3 11.3 16.3 1.8 10.1 15.6 27.6

Nicaragua 5,124 7.7 56.5 338.5 146.0 249.0 53.4 200.9 140.8 395.0

Panama 2,590 10.0 47.0 213.1 96.7 163.4 21.7 120.7 117.7 260.1

Paraguay 5,533 4.8 47.8 217.6 114.9 150.5 41.2 124.8 99.4 265.4

Peru 23,753 6.7 169.8 1,418.3 724.1 864.0 168.3 815.2 604.7 1,588.2

Puerto Rico 3,251 15.6 48.8 459.3 168.4 339.7 43.7 252.5 211.8 508.1

Suriname 315 12.3 8.0 30.7 15.6 23.2 5.7 21.4 11.7 38.7

Uruguay 2,627 7.2 5.8 182.6 71.6 116.8 17.7 78.1 92.6 188.4

Venezuela 22,997 6.6 67.5 1,455.4 686.4 836.5 145.4 657.4 720.1 1,522.9

SACA Total * 363,881 7.2 2,405 23,751 11,000 15,156 2,599 11,926 11,631 26,156

Table 1.28Prevalence estimates of diabetes mellitus (DM), 2025 – South and Central American Region






Population (20-79)

IGT prevalence



Argentina 23,958 9.8 798.0 1,551.5 498.7 1,188.4 662.4 2,349.4

Bolivia 4,480 7.1 124.2 193.1 103.3 115.9 98.0 317.2

Brazil 109,901 6.8 3,232.8 4,264.5 2,605.6 3,193.6 1,698.1 7,497.3

Chile 9,864 9.8 335.6 632.5 224.9 520.2 223.0 968.1

Colombia 25,524 4.5 445.4 690.9 457.7 436.8 241.8 1,136.3

Costa Rica 2,493 6.8 76.8 92.4 59.2 71.6 38.4 169.2

Cuba 7,980 12.2 407.4 563.4 241.3 388.3 341.1 970.7

Dominican Republic 4,991 10.4 206.1 313.0 168.6 214.2 136.3 519.1

Ecuador 7,548 7.1 216.3 319.0 172.2 198.1 165.0 535.2

El Salvador 3,620 6.5 103.1 133.9 93.0 88.0 56.0 237.0

French Guiana 100 7.3 2.6 4.7 2.7 3.4 1.2 7.3

Guatemala 5,620 6.3 162.5 191.9 147.8 130.2 76.4 354.4

Honduras 3,302 6.3 94.4 112.7 88.1 76.6 42.4 207.1

Netherlands Antilles 148 12.3 7.1 11.1 3.9 8.5 5.8 18.2

Nicaragua 2,567 6.2 70.8 87.8 69.1 59.8 29.6 158.5

Panama 1,779 6.9 55.1 66.8 42.6 50.4 28.9 121.9

Paraguay 2,979 8.5 91.3 161.0 75.1 132.8 44.4 252.3

Peru 15,397 7.2 441.6 668.1 351.7 406.3 351.7 1,109.7

Puerto Rico 2,671 12.2 126.3 199.9 76.5 130.8 118.9 326.2

Suriname 251 7.1 6.0 11.9 7.8 6.4 3.6 17.9

Uruguay 2,217 10.3 75.9 152.2 43.8 111.8 72.4 228.1

Venezuela 14,460 6.7 433.5 535.6 350.3 411.1 207.7 969.1

SACA Total * 251,850 7.3 7,513 10,958 5,884 7,943 4,643 18,470

Table 1.29Prevalence estimates of impaired glucose tolerance (IGT), 2003 – South and Central American Region






Population (20-79)

IGT prevalence



Argentina 31,775 10.4 1,139.2 2,162.5 630.0 1,701.4 970.2 3,301.7

Bolivia 7,927 7.5 244.5 352.2 169.1 226.9 200.8 596.7

Brazil 150,418 7.8 4,935.4 6,809.5 2,818.1 5,081.0 3,845.8 11,744.9

Chile 13,327 10.6 494.0 922.4 260.8 696.9 458.8 1,416.5

Colombia 39,178 5.0 734.3 1,211.5 577.8 739.5 628.5 1,945.8

Costa Rica 3,909 7.6 133.8 163.2 78.1 120.9 98.0 297.0

Cuba 8,749 14.6 582.3 698.2 180.3 502.3 597.9 1,280.5

Dominican Republic 7,081 12.0 349.8 500.7 202.0 346.7 301.8 850.5

Ecuador 11,887 8.3 425.8 561.3 223.0 385.6 378.4 987.0

El Salvador 5,775 7.2 177.4 239.6 123.8 186.6 106.6 417.1

French Guiana 190 7.6 5.2 9.2 4.9 5.7 3.8 14.4

Guatemala 11,171 6.6 327.1 407.0 280.7 298.8 154.6 734.1

Honduras 6,123 6.7 183.0 229.8 149.8 169.0 93.9 412.8

Netherlands Antilles 180 14.0 10.6 14.4 4.2 8.5 12.3 25.1

Nicaragua 5,124 6.7 151.4 192.3 124.4 143.7 75.7 343.8

Panama 2,590 7.8 88.6 112.4 49.4 85.8 65.9 201.0

Paraguay 5,533 9.2 184.2 327.5 130.8 261.2 119.7 511.7

Peru 23,753 8.3 831.2 1,144.3 444.6 780.1 750.7 1,975.4

Puerto Rico 3,251 13.5 179.2 259.4 76.6 173.2 188.9 438.6

Suriname 315 8.1 8.2 17.1 7.0 12.1 6.3 25.4

Uruguay 2,627 10.7 96.7 184.3 49.0 141.0 91.0 281.0

Venezuela 22,997 7.5 758.6 956.0 478.1 709.2 527.2 1,714.6

SACA Total * 363,881 8.1 12,041 17,475 7,062 12,776 9,677 29,515

Table 1.30Prevalence estimates of impaired glucose tolerance (IGT), 2025 – South and Central American Region







Bangladesh Bangladesh (Sayeed et al, 1997a, 1997b)99,100 OGTT WHO – 1980 2,371 20+

Bhutan India (Ramachandran et al, 2001)101 OGTT WHO – 1999 11,216 20+

India India (Ramachandran et al, 2001)101 OGTT WHO – 1999 11,216 20+

Maldives Sri Lanka (Fernando et al, 1994)102 OGTT WHO – 1985 633 30-64

Mauritius Mauritius (Dowse et al, 1990)49 OGTT WHO – 1985 4,929 25-74

Nepal India (Ramachandran et al, 2001)101 OGTT WHO – 1999 11,216 20+

Sri Lanka Sri Lanka (Fernando et al, 1994)102 OGTT WHO – 1985 633 30-64

Table 1.31Data sources: prevalence estimates of diabetes mellitus (DM) and impaired glucose tolerance (IGT) – South-East Asian Region

Population (20-79)

DM prevalence



Bangladesh 75,020 3.9 1,945.2 970.2 1,496.3 1,419.1 951.6 1,360.1 603.7 2,915.4

Bhutan 1,054 3.7 28.9 9.8 19.1 19.5 7.9 19.0 11.7 38.7

India 603,677 5.9 13,290.5 22,213.1 17,969.8 17,533.8 7,147.9 18,239.4 10,116.4 35,503.6

Maldives 144 1.8 1.4 1.2 1.3 1.2 0.5 1.6 0.4 2.6

Mauritius 786 10.7 34.4 50.1 41.2 43.3 14.8 45.4 24.3 84.5

Nepal 12,004 4.1 307.8 180.6 245.2 243.2 106.7 247.0 134.6 488.4

Sri Lanka 12,607 2.1 158.9 104.1 137.7 125.4 38.9 176.6 47.5 263.0

SEA Total * 705,292 5.6 15,767 23,529 19,911 19,386 8,268 20,089 10,939 39,296

Table 1.32Prevalence estimates of diabetes mellitus (DM), 2003 – South-East Asian Region


Population (20-79)

IGT prevalence



Bangladesh 75,020 7.1 2,746.9 2,596.3 2,273.6 2,137.1 932.5 5,343.2

Bhutan 1,054 14.1 73.8 74.3 77.5 47.4 23.2 148.1

India 603,677 14.2 44,069.0 41,561.5 42,484.2 30,100.3 13,046.0 85,630.4

Maldives 144 3.1 2.3 2.2 1.2 2.5 0.8 4.4

Mauritius 786 16.2 50.0 77.0 46.4 57.2 23.3 127.0

Nepal 12,004 14.0 850.8 833.5 897.4 551.3 235.7 1,684.3

Sri Lanka 12,607 3.7 240.4 220.8 93.2 281.7 86.3 461.2

SEA Total * 705,292 13.2 48,033 45,365 45,873 33,178 14,348 93,399

Table 1.34Prevalence estimates of impaired glucose tolerance (IGT), 2003 – South-East Asian Region







Bangladesh Bangladesh (Sayeed et al, 1997a, 1997b)99,100 OGTT WHO – 1980 2,371 20+

Bhutan India (Ramachandran et al, 2001)101 OGTT WHO – 1999 11,216 20+

India India (Ramachandran et al, 2001)101 OGTT WHO – 1999 11,216 20+

Maldives Sri Lanka (Fernando et al, 1994)102 OGTT WHO – 1985 633 30-64

Mauritius Mauritius (Dowse et al, 1990)49 OGTT WHO – 1985 4,929 25-74

Nepal India (Ramachandran et al, 2001)101 OGTT WHO – 1999 11,216 20+

Sri Lanka Sri Lanka (Fernando et al, 1994)102 OGTT WHO – 1985 633 30-64

Population (20-79)

DM prevalence



Bangladesh 130,288 4.8 3,034.1 3,273.0 3,217.9 3,089.2 1,439.0 3,355.1 1,513.0 6,307.1

Bhutan 2,044 4.3 51.1 37.7 44.2 44.5 19.7 44.4 24.6 88.7

India 909,790 8.1 18,553.8 54,922.1 37,275.7 36,200.2 11,827.7 37,417.5 24,230.7 73,475.9

Maldives 304 2.1 2.6 3.9 3.3 3.2 1.2 4.2 1.1 6.5

Mauritius 986 14.7 42.4 102.4 68.7 76.1 15.9 66.4 62.5 144.8

Nepal 21,644 5.1 498.5 609.8 552.7 555.6 235.8 568.6 303.9 1,108.3

Sri Lanka 15,971 2.7 192.8 242.6 217.3 218.1 45.0 279.2 111.1 435.3

SEA Total * 1,081,026 7.5 22,375 59,191 41,380 40,187 13,584 41,735 26,247 81,567

Table 1.33Prevalence estimates of diabetes mellitus (DM), 2025 – South-East Asian Region


Population (20-79)

IGT prevalence



Bangladesh 130,288 7.8 5,154.7 4,951.2 3,491.0 4,394.1 2,220.8 10,105.9

Bhutan 2,044 14.1 144.2 143.4 152.0 94.7 40.9 287.6

India 909,790 14.5 68,123.4 63,865.6 55,892.0 50,190.2 25,906.8 131,989.0

Maldives 304 3.3 5.1 4.9 2.5 5.9 1.7 10.0

Mauritius 986 17.7 70.8 104.1 45.2 74.5 55.1 174.9

Nepal 21,644 14.1 1,538.6 1,511.5 1,584.0 1,032.7 433.4 3,050.1

Sri Lanka 15,971 4.2 337.1 338.7 95.5 398.8 181.5 675.8

SEA Total * 1,081,026 13.5 75,374 70,919 61,262 56,191 28,840 146,293

Table 1.35Prevalence estimates of impaired glucose tolerance (IGT), 2025 – South-East Asian Region







Australia Australia (Dunstan et al, 2002)103 OGTT WHO – 1999 11,247 25+

Brunei Darussalam Singapore (Ministry of Health Survey, 1999)104 OGTT WHO – 1985 3,568 18-69

Cambodiaa Thailand (National Health Examination Survey, 1996 )105 FBG WHO – 1980 13,519 15+

China, Hong Kongb Hong Kong (Janus et al, 2000 and Cockram et al, 1993)106,107 OGTT WHO -1985 4,413 20-79

China, Macau Hong Kong (Janus et al, 2000 and Cockram et al, 1993)106,107 OGTT WHO -1985 4,413 20-79

China, People’s Republic of People’s Republic of China (Pan et al, 1997)108 OGTT WHO – 1985 213,515 25-64

Cook Islands Rarotonga (King et al, 1986)109 OGTT WHO – 1985 1,127 20+

East Timorc Indonesia (Waspadji et al, 1983)110 OGTT WHO – 1985 2,704 15+

Fiji Fiji (Zimmet et al, 1983)111 OGTT WHO – 1980 2,638 20+

French Polynesia Samoa (Collins et al, 1994)112 OGTT WHO – 1985 1,776 25-74

Guam Kiribati (King et al, 1984)113 OGTT WHO – 1980 2,938 20+

Indonesia Indonesia (Waspadji et al, 1983)110 OGTT WHO – 1985 2,704 15+

Japanb Japan (Ohmura et al, 1993 and Sekikawa et al, 2000)114,115 OGTT WHO – 1985 5,211 40+

Kiribati Kiribati (King et al, 1984)113 OGTT WHO – 1980 2,938 20+

Korea, Democratic People’s Republic of Republic of Korea (Park et al, 1995)116 OGTT WHO – 1985 2,520 30+

Korea, Republic of Republic of Korea (Park et al, 1995)116 OGTT WHO – 1985 2,520 30+

Lao People’s Democratic Republic Vietnam (Quoc et al, 1994)117 OGTT WHO – 1985 4,912 15+

Malaysia Singapore (Ministry of Health Survey, 1999)104 OGTT WHO – 1985 3,568 18-69

Marshall Islands Kiribati (King et al, 1984)113 OGTT WHO – 1980 2,938 20+

Micronesia Kiribati (King et al, 1984)113 OGTT WHO – 1980 2,938 20+

Mongolia Mongolia (Suvd et al, 2002)118 OGTT WHO – 1999 2,996 35+

Myanmar Vietnam (Quoc et al, 1994)117 OGTT WHO – 1985 4,912 15+

Nauru Nauru (Zimmet et al, 1984)119 OGTT WHO – 1980 1,583 20+

New Caledonia New Caledonia (Zimmet et al, 1982)120 OGTT WHO – 1980 707 20+

New Zealandc New Zealand (Ministry of Health, 2002)121 SR Known Diabetes 7,862 25+

Niue Niue (King et al, 1986)109 OGTT WHO – 1985 1,149 20+

Palau Kiribati (King et al, 1984)113 OGTT WHO – 1980 2,938 20+

Papua New Guinea Fiji Melanesians (Zimmet et al, 1983)111 OGTT WHO – 1980 1,340 20+

Philippinesa Thailand (National Health Examination Survey, 1996 )105 FBG WHO – 1980 13,519 15+

Samoa Samoa (Collins et al, 1994)112 OGTT WHO – 1985 1,776 25-74

Singapore, Republic of Singapore (Ministry of Health Survey, 1999)104 OGTT WHO – 1985 3,568 18-69

Solomon Islands Fiji Melanesians (Zimmet et al, 1983)111 OGTT WHO – 1980 1,340 20+

Taiwanb Taiwan (Chou et al, 1992, 1994)122,123 OGTT WHO – 1985 4,287 30-79

Thailanda Thailand (National Health Examination Survey, 1996 )105 FBG WHO – 1980 13,519 15+

Tokelau Samoa (Collins et al, 1994)112 OGTT WHO – 1985 1,776 25-74

Tonga Tonga (Colagiuri et al, 2002)124 OGTT WHO – 1999 1,024 15+

Tuvalu Samoa (Collins et al, 1994)112 OGTT WHO – 1985 1,776 25-74

Vanuatu Fiji Melanesians (Zimmet et al, 1983)111 OGTT WHO – 1980 1,340 20+

Vietnam Vietnam (Quoc et al, 1994)117 OGTT WHO – 1985 4,912 15+

Table 1.36Data sources: prevalence estimates of diabetes mellitus (DM) and impaired glucose tolerance (IGT) – Western Pacific Region

a. Because of the absence of data for IGT in the study used for diabetes, IGT figures were calculated from unpublished Indonesian data (862 participants).

b. The prevalences for the studies based on the Hong Kong, Japanese and Taiwanese studies were obtained by combining the data from the two studies respectively.

c. Because of the absence of data for IGT in the study used for diabetes, IGT figures were calculated from Australian data.






Australia Australia (Dunstan et al, 2002)103 OGTT WHO – 1999 11,247 25+

Brunei Darussalam Singapore (Ministry of Health Survey, 1999)104 OGTT WHO – 1985 3,568 18-69

Cambodiaa Thailand (National Health Examination Survey, 1996 )105 FBG WHO – 1980 13,519 15+

China, Hong Kongb Hong Kong (Janus et al, 2000 and Cockram et al, 1993)106,107 OGTT WHO -1985 4,413 20-79

China, Macau Hong Kong (Janus et al, 2000 and Cockram et al, 1993)106,107 OGTT WHO -1985 4,413 20-79

China, People’s Republic of People’s Republic of China (Pan et al, 1997)108 OGTT WHO – 1985 213,515 25-64

Cook Islands Rarotonga (King et al, 1986)109 OGTT WHO – 1985 1,127 20+

East Timorc Indonesia (Waspadji et al, 1983)110 OGTT WHO – 1985 2,704 15+

Fiji Fiji (Zimmet et al, 1983)111 OGTT WHO – 1980 2,638 20+

French Polynesia Samoa (Collins et al, 1994)112 OGTT WHO – 1985 1,776 25-74

Guam Kiribati (King et al, 1984)113 OGTT WHO – 1980 2,938 20+

Indonesia Indonesia (Waspadji et al, 1983)110 OGTT WHO – 1985 2,704 15+

Japanb Japan (Ohmura et al, 1993 and Sekikawa et al, 2000)114,115 OGTT WHO – 1985 5,211 40+

Kiribati Kiribati (King et al, 1984)113 OGTT WHO – 1980 2,938 20+

Korea, Democratic People’s Republic of Republic of Korea (Park et al, 1995)116 OGTT WHO – 1985 2,520 30+

Korea, Republic of Republic of Korea (Park et al, 1995)116 OGTT WHO – 1985 2,520 30+

Lao People’s Democratic Republic Vietnam (Quoc et al, 1994)117 OGTT WHO – 1985 4,912 15+

Malaysia Singapore (Ministry of Health Survey, 1999)104 OGTT WHO – 1985 3,568 18-69

Marshall Islands Kiribati (King et al, 1984)113 OGTT WHO – 1980 2,938 20+

Micronesia Kiribati (King et al, 1984)113 OGTT WHO – 1980 2,938 20+

Mongolia Mongolia (Suvd et al, 2002)118 OGTT WHO – 1999 2,996 35+

Myanmar Vietnam (Quoc et al, 1994)117 OGTT WHO – 1985 4,912 15+

Nauru Nauru (Zimmet et al, 1984)119 OGTT WHO – 1980 1,583 20+

New Caledonia New Caledonia (Zimmet et al, 1982)120 OGTT WHO – 1980 707 20+

New Zealandc New Zealand (Ministry of Health, 2002)121 SR Known Diabetes 7,862 25+

Niue Niue (King et al, 1986)109 OGTT WHO – 1985 1,149 20+

Palau Kiribati (King et al, 1984)113 OGTT WHO – 1980 2,938 20+

Papua New Guinea Fiji Melanesians (Zimmet et al, 1983)111 OGTT WHO – 1980 1,340 20+

Philippinesa Thailand (National Health Examination Survey, 1996 )105 FBG WHO – 1980 13,519 15+

Samoa Samoa (Collins et al, 1994)112 OGTT WHO – 1985 1,776 25-74

Singapore, Republic of Singapore (Ministry of Health Survey, 1999)104 OGTT WHO – 1985 3,568 18-69

Solomon Islands Fiji Melanesians (Zimmet et al, 1983)111 OGTT WHO – 1980 1,340 20+

Taiwanb Taiwan (Chou et al, 1992, 1994)122,123 OGTT WHO – 1985 4,287 30-79

Thailanda Thailand (National Health Examination Survey, 1996 )105 FBG WHO – 1980 13,519 15+

Tokelau Samoa (Collins et al, 1994)112 OGTT WHO – 1985 1,776 25-74

Tonga Tonga (Colagiuri et al, 2002)124 OGTT WHO – 1999 1,024 15+

Tuvalu Samoa (Collins et al, 1994)112 OGTT WHO – 1985 1,776 25-74

Vanuatu Fiji Melanesians (Zimmet et al, 1983)111 OGTT WHO – 1980 1,340 20+

Vietnam Vietnam (Quoc et al, 1994)117 OGTT WHO – 1985 4,912 15+





Population (20-79)

DM prevalence



Australia 13,805 6.2 475.6 378.8 39.4 319.8 495.1 854.4

Brunei Darussalam 209 10.7 3.4 18.8 9.6 12.6 2.3 14.5 5.4 22.2

Cambodia 6,332 2.0 78.0 47.2 44.3 80.9 32.4 65.0 27.7 125.2

China, Hong Kong 5,424 8.8 232.7 247.2 46.7 204.2 229.0 479.9

China, Macau 323 8.2 12.7 13.9 2.7 13.7 10.2 26.6

China, People’s Republic of 877,935 2.7 11,106.7 12,702.3 10,750.5 13,058.5 2,068.1 11,022.2 10,718.7 23,809.0

Cook Islandsa 13 6.6 0.0 0.0 0.3 0.5 0.2 0.4 0.2 0.8

East Timor 403 1.4 4.8 0.8 2.8 2.8 0.5 3.0 2.0 5.6

Fiji 480 8.3 19.0 20.7 18.4 21.3 6.9 24.4 8.4 39.7

French Polynesia 147 8.0 3.5 8.2 5.3 6.4 1.0 7.0 3.8 11.7

Guam 93 6.7 2.1 4.2 3.3 2.9 1.2 3.4 1.6 6.2

Indonesia 132,849 1.9 1,028.8 1,518.7 1,194.8 1,352.7 242.4 1,213.4 1,091.7 2,547.5

Japan 97,090 6.9 3,476.7 3,252.2 365.5 2,617.3 3,746.0 6,728.9

Kiribatia 60 6.2 1.3 2.4 1.8 1.9 0.8 1.9 1.0 3.7

Korea, Democratic People’s Republic of 14,835 5.2 171.5 602.9 430.9 343.4 147.4 375.7 251.2 774.4

Korea, Republic of 34,147 6.4 1,209.7 976.2 383.4 1,120.1 682.4 2,185.9

Lao People’s Democratic Republic 2,658 1.1 14.9 13.0 6.0 21.9 6.8 9.8 11.3 27.9

Malaysia 13,280 9.4 323.5 928.1 527.3 724.3 134.6 688.4 428.6 1,251.6

Marshall Islandsa 46 8.6 0.4 3.6 2.0 2.0 0.8 2.1 1.2 4.0

Micronesiaa 82 6.7 1.6 3.9 2.7 2.8 1.1 2.8 1.6 5.5

Mongolia 1,451 1.4 4.3 15.9 9.9 10.3 5.2 11.2 3.9 20.2

Myanmar 28,474 1.1 166.2 145.4 68.8 242.9 70.8 116.1 124.7 311.6

Naurua 8 30.2 0.0 0.0 1.1 1.2 0.5 1.3 0.5 2.3

New Caledoniab 140 3.8 0.5 4.8 2.1 3.2 0.8 2.5 2.0 5.3

New Zealand 2,603 7.6 96.8 99.8 20.3 87.6 88.8 196.6

Niuea 1 6.8 0.0 0.0 0.0 0.1 0.0 0.1 0.0 0.1

Palaua 12 8.7 0.1 0.9 0.5 0.5 0.2 0.5 0.3 1.0

Papua New Guinea 2,551 1.9 23.8 25.3 20.4 28.7 4.3 25.2 19.5 49.1

Philippines 42,133 2.4 269.0 741.2 399.2 611.1 239.5 519.3 251.4 1,010.2

Samoa 74 5.9 3.0 1.4 1.9 2.5 0.4 2.0 2.0 4.4

Singapore, Republic of 3,032 12.3 172.3 201.3 32.2 191.6 149.7 373.6

Solomon Islands 221 2.1 2.0 2.5 1.9 2.6 0.4 2.2 1.9 4.5

Taiwana 13,767 5.6 307.1 458.7 94.9 326.5 344.3 765.7

Thailand 42,236 2.1 574.9 306.6 348.4 533.1 206.3 440.6 234.5 881.5

Tokelaua 1 6.4 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.1

Tongaa 65 12.4 4.1 4.0 3.5 4.6 1.6 4.4 2.2 8.2

Tuvalua 7 8.6 0.2 0.4 0.2 0.3 0.0 0.3 0.2 0.6

Vanuatu 101 2.2 1.0 1.2 0.9 1.3 0.2 1.1 0.9 2.2

Vietnam 46,620 1.0 319.7 161.5 95.0 386.2 112.2 161.3 207.7 481.2

WP Total * 1,383,705 3.1 14,128 17,286 19,938 23,091 4,274 19,603 19,152 43,029

Table 1.37Prevalence estimates of diabetes mellitus (DM), 2003 – Western Pacific Region


a. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of world population 2003.b. For New Caledonia, the Melanesian population was ascribed as having the national urban/rural population distribution, whereas the French

population was deemed as having the diabetes prevalence of Metropolitan France, and assigned to the urban component, and each assigned 50% of the total population.





Population (20-79)

DM prevalence



Australia 16,950 7.7 720.5 580.1 41.9 377.1 881.6 1,300.6

Brunei Darussalam 332 15.0 5.1 44.9 22.1 27.9 3.3 22.5 24.2 50.0

Cambodia 12,191 2.1 119.4 140.4 98.0 161.8 67.7 120.6 71.5 259.8

China, Hong Kong 6,765 12.8 386.6 476.8 40.1 275.6 547.7 863.4

China, Macau 425 12.9 23.5 31.4 3.0 15.4 36.4 54.8

China, People’s Republic of 1,079,641 4.3 14,475.7 31,654.3 19,913.2 26,216.7 2,091.9 19,172.6 24,865.4 46,130.0

Cook Islandsa 17 7.3 0.0 0.0 0.5 0.8 0.2 0.6 0.4 1.3

East Timor 764 1.6 9.7 2.9 6.2 6.4 1.2 6.1 5.2 12.6

Fiji 641 10.3 22.2 43.8 31.2 34.8 7.6 37.1 21.3 66.0

French Polynesia 217 10.8 5.3 18.1 10.1 13.3 1.3 12.6 9.5 23.4

Guam 148 7.5 2.5 8.7 5.7 5.4 2.0 4.8 4.4 11.2

Indonesia 186,983 2.8 1,374.0 3,835.6 2,507.1 2,702.5 321.6 2,543.9 2,344.1 5,209.6

Japan 90,130 7.9 3,654.0 3,495.2 265.7 2,509.8 4,373.7 7,149.1

Kiribatia 82 7.9 1.5 5.0 3.3 3.2 1.0 3.2 2.2 6.5

Korea, Democratic People’s Republic of 18,008 6.3 177.6 957.0 635.4 499.2 150.3 586.5 397.8 1,134.6

Korea, Republic of 39,095 8.3 1,819.7 1,423.4 293.4 1,515.9 1,433.8 3,243.1

Lao People’s Democratic Republic 4,933 1.1 28.8 25.2 12.2 41.8 12.2 19.5 22.3 54.0

Malaysia 21,032 12.4 449.0 2,153.1 1,088.4 1,513.7 205.9 1,207.1 1,189.1 2,602.1

Marshall Islandsa 64 10.3 0.5 6.1 3.3 3.2 1.0 3.3 2.3 6.6

Micronesiaa 113 8.5 1.8 7.8 4.8 4.8 1.5 4.8 3.3 9.6

Mongolia 2,355 2.0 6.8 39.4 22.7 23.5 7.8 27.6 10.9 46.3

Myanmar 41,135 1.3 294.5 257.7 136.0 416.1 86.4 201.3 264.4 552.2

Naurua 10 33.0 0.0 0.0 1.7 1.7 0.6 1.9 0.9 3.5

New Caledoniab 217 4.7 0.6 9.7 3.9 6.4 1.1 4.4 4.8 10.3

New Zealand 3,106 9.0 135.2 143.0 20.6 96.2 161.3 278.1

Niuea 2 7.6 0.0 0.0 0.1 0.1 0.0 0.1 0.0 0.1

Palaua 16 10.3 0.1 1.6 0.9 0.8 0.2 0.8 0.6 1.7

Papua New Guinea 4,546 2.9 45.9 84.7 52.1 78.5 11.5 65.2 53.9 130.6

Philippines 69,936 3.0 363.3 1,707.8 811.3 1,259.8 375.0 1,066.1 630.0 2,071.2

Samoa 109 6.1 3.7 2.9 3.4 3.3 0.8 3.6 2.3 6.6


Solomon Islands 480 2.9 4.1 10.0 5.4 8.7 1.5 7.1 5.5 14.1

Taiwana 18,911 6.6 480.5 759.2 115.2 498.1 626.5 1,239.8

Thailand 55,716 2.6 940.2 518.1 570.4 887.9 198.5 719.0 540.8 1,458.3

Tokelaua 1 7.6 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.1

Tongaa 90 15.9 6.3 8.0 6.2 8.1 2.2 7.6 4.5 14.3

Tuvalua 9 10.8 0.2 0.8 0.4 0.6 0.1 0.5 0.4 1.0

Vanuatu 195 3.2 2.0 4.2 2.4 3.8 0.6 2.9 2.7 6.2

Vietnam 71,403 1.4 523.6 458.0 255.7 725.9 146.2 358.6 476.7 981.6

WP Total * 1,750,653 4.3 18,865 42,006 33,765 41,997 4,513 31,735 39,514 75,762

Table 1.38Prevalence estimates of diabetes mellitus (DM), 2025 – Western Pacific Region



b. For New Caledonia, the Melanesian population was ascribed as having the national urban/rural population distribution, whereas the French population was deemed as having the diabetes prevalence of Metropolitan France, and assigned to the urban component, and each assigned 50% of the total population.





Population (20-79)

IGT prevalence



Australia 13,805 9.4 561.0 730.0 212.0 552.1 526.9 1,291.0

Brunei Darussalam 209 20.6 22.8 20.1 16.7 22.6 3.8 43.0

Cambodia 6,332 9.0 271.2 298.7 216.5 231.7 121.7 569.9

China, Hong Kong 5,424 10.9 318.1 274.2 91.7 268.7 231.9 592.2

China, Macau 323 10.4 17.9 15.6 5.1 18.1 10.4 33.6

China, People’s Republic of 877,935 3.8 9,277.2 23,874.7 4,812.7 16,268.9 12,070.4 33,152.0

Cook Islandsa 13 10.0 0.6 0.7 0.3 0.5 0.4 1.3

East Timor 403 9.4 20.7 17.4 12.9 16.2 9.1 38.1

Fiji 480 10.2 20.3 28.8 18.1 22.1 8.9 49.1

French Polynesia 147 6.0 3.7 5.1 2.4 4.3 2.1 8.8

Guam 93 17.7 7.9 8.5 5.1 8.1 3.2 16.5

Indonesia 132,849 9.7 6,924.2 5,989.0 4,391.5 4,819.9 3,701.8 12,913.2

Japan 97,090 13.0 5,554.2 7,057.8 2,294.1 5,049.1 5,268.7 12,612.0

Kiribatia 60 17.1 4.6 5.6 3.5 4.5 2.1 10.2

Korea, Democratic People’s Republic of 14,835 8.4 634.5 605.0 272.7 559.9 406.9 1,239.5

Korea, Republic of 34,147 8.4 1,455.9 1,408.9 583.5 1,367.8 913.6 2,864.8

Lao People’s Democratic Republic 2,658 1.3 5.9 29.4 9.4 14.1 11.7 35.2

Malaysia 13,280 17.7 1,173.7 1,174.3 919.9 1,131.3 296.9 2,348.0

Marshall Islandsa 46 17.1 3.6 4.3 2.7 3.5 1.7 7.9

Micronesiaa 82 17.1 6.4 7.7 4.9 6.3 3.0 14.1

Mongolia 1,451 7.7 40.7 70.7 52.1 37.2 22.1 111.4

Myanmar 28,474 1.4 66.4 326.3 98.0 166.3 128.4 392.7

Naurua 8 20.3 0.8 0.8 0.6 0.6 0.3 1.5

New Caledonia 140 4.6 2.6 3.8 1.8 2.8 1.8 6.4

New Zealand 2,603 9.4 105.0 140.0 40.2 106.6 98.1 244.9

Niuea 1 6.9 0.0 0.0 0.0 0.0 0.0 0.1

Palaua 12 17.1 0.9 1.1 0.7 0.9 0.4 2.0

Papua New Guinea 2,551 9.1 86.7 144.9 95.9 96.2 39.6 231.7

Philippines 42,133 9.3 2,060.4 1,846.9 1,442.7 1,499.4 965.2 3,907.2

Samoa 74 5.3 1.7 2.3 1.2 1.6 1.2 4.0


Solomon Islands 221 9.0 7.4 12.5 8.6 7.6 3.8 19.9

Taiwana 13,767 3.1 196.1 235.0 103.0 177.0 151.1 431.1

Thailand 42,236 9.9 2,223.4 1,962.5 1,359.9 1,657.6 1,168.3 4,185.9

Tokelaua 1 6.4 0.0 0.0 0.0 0.0 0.0 0.1

Tongaa 65 7.2 2.1 2.6 1.2 2.5 1.0 4.7

Tuvalua 7 6.4 0.2 0.3 0.1 0.2 0.1 0.4

Vanuatu 101 9.4 3.5 6.0 3.8 3.9 1.8 9.4

Vietnam 46,620 1.4 111.3 524.3 165.2 246.5 223.9 635.6

WP Total * 1,383,705 5.7 31,445 47,088 17,384 34,663 26,487 78,534

Table 1.39Prevalence estimates of impaired glucose tolerance (IGT), 2003 – Western Pacific Region


a. Population number as described in the CIA World Factbook 2002125, with age distribution adjustment to that of world population 2003.





Population (20-79)

IGT prevalence



Australia 16,950 10.6 798.4 1,003.6 224.3 638.5 939.3 1,802.0

Brunei Darussalam 332 20.8 36.7 32.4 22.6 30.6 16.0 69.1

Cambodia 12,191 9.2 567.4 554.4 429.6 397.0 295.2 1,121.8

China, Hong Kong 6,765 14.6 479.5 505.9 78.5 350.5 556.4 985.3

China, Macau 425 14.6 28.8 33.2 5.8 19.4 36.9 62.0

China, People’s Republic of 1,079,641 5.0 14,118.8 40,145.7 4,298.8 24,699.1 25,266.6 54,264.5

Cook Islandsa 17 11.2 0.9 1.1 0.4 0.8 0.8 1.9

East Timor 764 10.2 43.1 34.6 24.3 31.1 22.4 77.8

Fiji 641 11.3 30.1 42.7 20.4 31.2 21.1 72.7

French Polynesia 217 7.1 6.7 8.6 2.9 7.1 5.3 15.3

Guam 148 17.3 12.1 13.6 8.3 9.8 7.6 25.7

Indonesia 186,983 11.2 11,801.3 9,138.8 4,925.0 8,796.2 7,219.0 20,940.2

Japan 90,130 14.1 5,663.7 7,014.4 1,633.4 4,881.6 6,163.0 12,678.0

Kiribatia 82 18.1 6.9 8.0 4.2 6.7 3.9 14.9

Korea, Democratic People’s Republic of 18,008 9.5 873.1 830.3 264.9 823.3 615.2 1,703.4

Korea, Republic of 39,095 10.8 2,164.0 2,043.9 446.2 1,838.2 1,923.6 4,208.0

Lao People’s Democratic Republic 4,933 1.4 11.6 56.2 16.9 27.9 22.9 67.8

Malaysia 21,032 18.4 1,933.5 1,926.4 1,299.5 1,802.8 757.7 3,860.0

Marshall Islandsa 64 18.1 5.3 6.2 3.3 5.2 3.1 11.5

Micronesiaa 113 18.1 9.5 11.0 5.8 9.2 5.4 20.5

Mongolia 2,355 8.7 84.6 120.5 65.2 84.9 54.9 205.0

Myanmar 41,135 1.7 122.5 558.3 121.3 286.5 272.9 680.7

Naurua 10 21.2 1.1 1.1 0.7 0.9 0.6 2.2

New Caledonia 217 5.2 5.1 6.2 2.3 4.8 4.2 11.3

New Zealand 3,106 10.8 146.5 187.6 40.8 115.3 177.9 334.1

Niuea 2 7.4 0.1 0.1 0.0 0.1 0.0 0.1

Palaua 16 18.1 1.4 1.6 0.8 1.3 0.8 3.0

Papua New Guinea 4,546 9.7 165.6 275.9 158.0 189.0 94.5 441.6

Philippines 69,936 10.4 4,002.7 3,271.1 2,105.7 2,864.0 2,304.1 7,273.8

Samoa 109 5.5 2.7 3.3 1.9 2.7 1.4 5.9


Solomon Islands 480 9.5 16.7 28.7 17.4 18.8 9.2 45.4

Taiwana 18,911 3.5 307.9 357.6 123.6 265.3 276.7 665.6

Thailand 55,716 12.0 3,773.1 2,891.3 1,302.6 2,679.0 2,682.9 6,664.4

Tokelaua 1 7.1 0.0 0.0 0.0 0.0 0.0 0.1

Tongaa 90 7.8 3.2 3.8 1.5 3.7 1.8 7.0

Tuvalua 9 7.1 0.3 0.4 0.1 0.3 0.2 0.7

Vanuatu 195 9.9 7.0 12.3 6.9 7.9 4.5 19.3

Vietnam 71,403 1.7 222.8 980.5 207.5 508.1 487.7 1,203.3

WP Total * 1,750,653 6.9 47,807 72,441 17,998 51,727 50,522 120,248

Table 1.40Prevalence estimates of impaired glucose tolerance (IGT), 2025 – Western Pacific Region







References

1. World Health Organization. Prevention of diabetes mellitus. Technical Report Series no. 844. WHO, Geneva, 1994.

2. Harris M, Zimmet P. Classification of diabetes mellitus and other categories of glucose intolerance. In International Textbook of Diabetes Mellitus second edition, ed. Alberti K, Zimmet P, DeFronzo R, Keen H (Honorary). Chichester, England: John Wiley and Sons Ltd. 1997:9-23.

3. Atkinson M, Maclaren N. The pathogenesis of insulin-dependent diabetes mellitus. N Engl J Med 1994;331:1428-1436.

4. LaPorte R, Matsushima M, Chang Y. Prevalence and incidence of insulin-dependent diabetes. In Diabetes in America, second edition, ed. NDDG NIH 1995:37-46.

5. Molbak A, Christau B, Marner B, Borch-Johnsen K, Nerup J. Incidence of insulin-dependent diabetes mellitus in age groups over 30 years in Denmark. Diabet Med 1994;11:650-655.

6. Groop L, Bottazzo G, Doniach D. Islet cell antibodies identify latent type I diabetes in patients aged 35-75 years at diagnosis. Diabetes 1986; 35:237-241.

7. Gleichmann H, Zörcher B, Greulich B, Gries F, Henrichs H, Bertrams J, Kolb H. Correlation of islet cell antibodies and HLA-DR phenotypes with diabetes mellitus in adults. Diabetologia 1984; 27:90-92.

8. Reaven GM, Bernstein R, Davis B, Olefsky J. Non-ketotic diabetes mellitus: Insulin deficiency or insulin resistance? Am J Med 1976; 60:80-88.

9. Tuomilehto J, Lindstrom J, Eriksson J, Valle T, Hamalainen H, Ilanne-Parikka P, Keinanen-Kiukaanniemi S, Laakso M, Louheranta A, Rastas M, Salminen V, Uusitupa M, Finnish Diabetes Prevention Study Group. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 2001;344:1343-1350.

10. Zimmet P, Dowse G, Finch C, Serjeantson S, King H. The epidemiology and natural history of NIDDM – lessons from the South Pacific. Diabetes Metab Res Rev 1990; 6:91-124.

11. King H, Rewers M. Global estimates for prevalence of diabetes mellitus and impaired glucose tolerance in adults. WHO Ad Hoc Diabetes Reporting Group. Diabetes Care 1993; 16:157-177.

12. American Diabetes Association. Type 2 diabetes in children and adolescents. Diabetes Care 2000; 23:381-389.

13. Kitagawa T, Owada M, Urakami T, Yamauchi K. Increased incidence of non-insulin dependent diabetes mellitus among Japanese schoolchildren correlates with an increased intake of animal protein and fat. Clin Pediatr (Phila) 1998; 37:111-115.

14. Fagot-Campagna A, Pettitt DJ, Engelgau MM, Burrows NR, Geiss LS, Valdez R, Beckles GL, Saaddine J, Gregg EW, Williamson DF, Narayan KM. Type 2 diabetes among North American children and adolescents: an epidemiologic review and a public health perspective. J Pediatr 2000;136:664-672.

15. Alberti K. The clinical implications of impaired glucose tolerance. Diabet Med 1996; 13:927-937.

16. Unwin N, Shaw J, Zimmet P, Alberti KG. Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention. Diabet Med 2002;19:708-723.

17. Shaw JE, Zimmet PZ, de Courten M, Dowse GK, Chitson P, Gareeboo H, Hemraj F, Fareed D, Tuomilehto J, Alberti KG. Impaired fasting glucose or impaired glucose tolerance. What best predicts future diabetes in Mauritius? Diabetes Care 1999; 22:399-402.

18. Perry RC, Baron AD. Impaired glucose tolerance. Why is it not a disease? Diabetes Care 1999; 22:883-885.

19. Tominaga M, Eguchi H, Manaka H, Igarashi K, Kato T, Sekikawa A. Impaired glucose tolerance is a risk factor for cardiovascular disease, but not impaired fasting glucose. The Funagata Diabetes Study. Diabetes Care 1999;22:920-924.

20. National Diabetes Data Group. Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance. Diabetes 1979; 28:1039-1057.

21. Metzger BE, Coustan DR. Summary and recommendations of the Fourth International Workshop-Conference on Gestational Diabetes Mellitus. The Organizing Committee. Diabetes Care 1998; 21 Suppl 2: B161-167.

22. Bennett P. Standardization of methods in the epidemiology of diabetes mellitus. Tohoku J Exp Med 1983; 141:29-39.

23. Bennett P. Recommendations on the standardization of methods and reporting of tests for diabetes and its microvascular complications in epidemiologic studies. Diabetes Care 1979; 2:98-104.

24. West K. Standardization of definition, classification, and reporting in diabetes-related epidemiologic studies. Diabetes Care 1979; 2:65-76.

25. American Diabetes Association. Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 1997; 20:1183-1197.

26. World Health Organization. Definition, Diagnosis and Classification of Diabetes Mellitus and its Complications; Part 1: Diagnosis and Classification of Diabetes Mellitus. WHO/NCD/NCS/99.2. Department of Noncommunicable Disease Surveillance, Geneva, 1999.

27. DECODE Study Group. Will new diagnostic criteria for diabetes mellitus change phenotype of patients with diabetes? Reanalysis of European epidemiological data. Br Med J 1998; 317:371-375.

28. International Diabetes Federation. Triennial Report(1991-1994) and Directory. International Diabetes Federation, Brussels, 1994.

29. McCarty D, Zimmet P. Diabetes 1994 to 2010: Global Estimates and Projections. International Diabetes Institute, Melbourne, 1994.

30. King H, Aubert R, Herman W. Global burden of diabetes, 1995-2025. Prevalence, numerical estimates and projections. Diabetes Care 1998; 21:1414-1431.

31. Amos A, McCarty D, Zimmet P. The rising global burden of diabetes and its complications: Estimates and projections to the year 2010. Diabet Med 1997; 14:S1-S85.

32. United Nations – Department for Economic and Social Information – Population Division. World urbanization prospects: the 1994 revision. Estimates and projections of urban and rural populations and of urban agglomerations. United Nations, New York, 1995.

33. Ramachandran A, Snehalatha C, Latha E, Manoharan M, Vijay V. Impacts of urbanisation on the lifestyle and on the prevalence of diabetes in native Asian Indian population. Diabetes Res Clin Pract 1999; 44:207-213.

34. Ramachandran A, Snehalatha C, Vijay V, King H. Impact of poverty on the prevalence of diabetes and its complications in urban southern India. Diabet Med 2002; 19:130-135.

35. Ministry of Health NZ. Diabetes in New Zealand: Models and forecasts 1996-2011. Wellington, New Zealand, 2002.

36. Hux J, Tang M. Patterns of Prevalence and Incidence of Diabetes. In Diabetes in Ontario: An ICES Practice Atlas: Institute for Clinical Evaluative Sciences, ed. Hux J, Booth G, Laupacis A. 2002:1.2-1.18.

37. Thefeld W. Prevalence of diabetes mellitus in the adult German population. Gesundheitswesen 1999;61 Spec No: S85-89.





38. Dunstan DW, Zimmet PZ, Welborn TA, De Courten MP, Cameron AJ, Sicree RA, Dwyer T, Colagiuri S, Jolley D, Knuiman M, Atkins R, Shaw JE. The rising prevalence of diabetes and impaired glucose tolerance: the Australian Diabetes, Obesity and Lifestyle Study. Diabetes Care 2002; 25:829-834.

39. Guest C, O’Dea K, Hopper J, Nankervis A, Larkins R. The prevalence of glucose intolerance in Aborigines and Europids of south-eastern Australia. Diabetes Res ClinPract 1992; 15:227-235.

40. Rathmann W, Haastert B, Icks A, Lowel H, Meisinger C, Holle R, Giani G. High prevalence of undiagnosed diabetes mellitus in Southern Germany: Target populations for efficient screening. The KORA survey 2000. Diabetologia 2003; 46:182-189.

41. Harris M, Hadden W, Knowler W, Bennett P. Prevalence of diabetes and impaired glucose tolerance and plasma glucose levels in US population aged 20-74 years. Diabetes 1987; 36:523-534.

42. McLarty DG, Swai AB, Kitange HM, Masuki G, Mtinangi BL, Kilima PM, Makene WJ, Chuwa LM, Alberti KG. Prevalence of diabetes and impaired glucose tolerance in rural Tanzania. Lancet 1989; 1:871-875.

43. Aspray TJ, Mugusi F, Rashid S, Whiting D, Edwards R, Alberti KG, Unwin NC. Rural and urban differences in diabetes prevalence in Tanzania: the role of obesity, physical inactivity and urban living. Trans R Soc Trop Med Hyg 2000; 94:637-644.

44. Mbanya JC, Ngogang J, Salah JN, Minkoulou E, Balkau B. Prevalence of NIDDM and impaired glucose tolerance in a rural and an urban population in Cameroon. Diabetologia 1997; 40:824-829.

45. Amoah AG, Owusu SK, Adjei S. Diabetes in Ghana: a community based prevalence study in Greater Accra. Diabetes Res Clin Pract 2002; 56:197-205.

46. Omar MA, Seedat MA, Motala AA, Dyer RB, Becker P. The prevalence of diabetes mellitus and impaired glucose tolerance in a group of urban South African blacks. S Afr Med J 1993; 83:641-643.

47. Levitt NS, Katzenellenbogen JM, Bradshaw D, Hoffman MN, Bonnici F. The prevalence and identification of risk factors for NIDDM in urban Africans in Cape Town, South Africa. Diabetes Care 1993; 16:601-607.

48. Elbagir MN, Eltom MA, Elmahadi EM, Kadam IM, Berne C. A population-based study of the prevalence of diabetes and impaired glucose tolerance in adults in northern Sudan. Diabetes Care 1996; 19:1126-1128.

49. Dowse GK, Gareeboo H, Zimmet PZ, Alberti KG, Tuomilehto J, Fareed D, Brissonnette LG, Finch CF. High prevalence of NIDDM and impaired glucose tolerance in Indian, Creole, and Chinese Mauritians. Mauritius Noncommunicable Disease Study Group. Diabetes 1990; 39:390-396.

50. Shera AS, Rafique G, Khawaja IA, Ara J, Baqai S, King H. Pakistan national diabetes survey: prevalence of glucose intolerance and associated factors in Shikarpur, Sindh Province. Diabet Med 1995; 12:1116-1121.

51. Shera AS, Rafique G, Khawaja IA, Baqai S, King H. Pakistan National Diabetes Survey: prevalence of glucose intolerance and associated factors in Baluchistan province. Diabetes Res Clin Pract 1999; 44:49-58.

52. Shera AS, Rafique G, Khawaja IA, Baqai S, Khan IA, King H, Ahmed KI. Pakistan National Diabetes Survey prevalence of glucose intolerance and associated factors in North West at Frontier Province (NWFP) of Pakistan. J Pak Med Assoc 1999; 49:206-211.

53. Papoz L, Ben Khalifa F, Eschwege E, Ben Ayed H. Diabetes mellitus in Tunisia: description in urban and rural populations. Int J Epidemiol 1988; 17:419-422.

54. Ghannem H, Hadj Fredj A. Prevalence of cardiovascular risk factors in the urban population of Soussa in Tunisia. J Public Health Med 1997; 19:392-396.

55. Satman I, Yilmaz T, Sengul A, Salman S, Salman F, Uygur S, Bastar I, Tutuncu Y, Sargin M, Dinccag N, Karsidag K, Kalaca S, Ozcan C, King H. Population-Based Study of Diabetes and Risk Characteristics in Turkey: Results of the Turkish Diabetes Epidemiology Study (TURDEP). Diabetes Care 2002; 25:1551-1556.

56. Al-Mahroos F, McKeigue PM. High prevalence of diabetes in Bahrainis. Associations with ethnicity and raised plasma cholesterol. Diabetes Care 1998; 21:936-942.

57. Herman WH, Ali MA, Aubert RE, Engelgau MM, Kenny SJ, Gunter EW, Malarcher AM, Brechner RJ, Wetterhall SF, DeStefano F, Thompson T, Smith P, Badran A, Sous E, Habib M, Hegazy M, abd el Shakour S, Ibrahim AS, el Moneim el Behairy A. Diabetes mellitus in Egypt: risk factors and prevalence. Diabet Med 1995; 12:1126-1131.

58. Arab M. Epidemiology of diabetes mellitus in Egypt. Egyptian J Diab 1997; 2:1-14.

59. Amini M, Afshin-Nia F, Bashardoost N, Aminorroaya A, Shahparian M, Kazemi M. Prevalence and risk factors of diabetes mellitus in the Isfahan city population (aged 40 or over) in 1993. Diabetes Res Clin Pract 1997; 38:185-190.

60. Ajlouni K, Jaddou H, Batieha A. Diabetes and impaired glucose tolerance in Jordan: prevalence and associated risk factors. J Intern Med 1998; 244:317-323.

61. Abdella N, Al Arouj M, Al Nakhi A, Al Assoussi A, Moussa M. Non-insulin-dependent diabetes in Kuwait: prevalence rates and associated risk factors. Diabetes Res Clin Pract 1998; 42:187-196.

62. Salti S, Khogali M, Alam S, Abu Haidar N, Masri A. Epidemiology of diabetes mellitus in relation to other cardiovascular risk factors in Lebanon. East Mediterr Health J 1997; 3:462-471.

63. Kadiki OA, Roaed RB. Epidemiological and clinical patterns of diabetes mellitus in Benghazi, Libyan Arab Jamahiriya. East Mediterr Health J 1999; 5:6-13.

64. Al-Lawati JA, Al Riyami AM, Mohammed AJ, Jousilahti P. Increasing prevalence of diabetes mellitus in Oman. Diabet Med 2002; 19:954-957.

65. Asfour MG, Lambourne A, Soliman A, Al-Behlani S,Al-Asfoor D, Bold A, Mahtab H, King H. High prevalence of diabetes mellitus and impaired glucose tolerance in the Sultanate of Oman: results of the 1991 national survey. Diabet Med 1995; 12:1122-1125.

66. El-Hazmi M, Warsy A, Al-Swailem A, Al-Swailem A, Sulaimani R. Diabetes mellitus as a health problem in Saudi Arabia. East Mediterr Health J 1998; 4:58-67.

67. Malik M, Bakir A, Abi Saab B, Roglic G, King H. Prevalence of Diabetes, Impaired Fasting Glucose, Impaired Glucose Tolerance, Hypertension and Obesity in the Multi-ethnic Population of the United Arab Emirates. Unpublished, Abu Dhabi, 2002.

68. Katsilambros N, Aliferis K, Darviri C, Tsapogas P, Alexiou Z, Tritos N, Arvanitis M. Evidence for an increase in the prevalence of known diabetes in a sample of an urban population in Greece. Diabet Med 1993; 10:87-90.

69. Castell C, Tresserras R, Serra J, Goday A, Lloveras G, Salleras L. Prevalence of diabetes in Catalonia (Spain): an oral glucose tolerance test-based population study. Diabetes Res Clin Pract 1999; 43:33-40.

70. Rathmann W, Haastert B, Icks A, Lowel H, Meisinger C, Holle R, Giani G. High prevalence of undiagnosed diabetes mellitus in Southern Germany: target populations for efficient screening. The KORA survey 2000. Diabetologia 2003; 46:182-189.

71. Szurkowska M, Szybinski Z, Nazim A, Szafraniec K, Jedrychowski W. Prevalence of type II diabetes mellitus in





population of Krakow. Pol Arch Med Wewn 2001;106:771-779.

72. Lopatynski J, Mardarowicz G, Nicer T, Szczesniak G, Krol H, Matej A, Szydlowski W, Paszkowski J, Dabek K, Zmurowska B, Szyprowska-Grzegorczyk E. The prevalence of type II diabetes mellitus in rural and urban population over 35 years of age in Lublin region (Eastern Poland). Pol Arch Med Wewn 2001; 106:781-786.

73. Mooy JM, Grootenhuis PA, de Vries H, Valkenburg HA, Bouter LM, Kostense PJ, Heine RJ. Prevalence and determinants of glucose intolerance in a Dutch caucasian population. The Hoorn Study. Diabetes Care 1995;18:1270-1273.

74. Eliasson M, Lindahl B, Lundberg V, Stegmayr B. No increase in the prevalence of known diabetes between 1986 and 1999 in subjects 25-64 years of age in northern Sweden. Diabet Med 2002; 19:874-880.

75. Tuomilehto J, Nissinen A, Kivela SL, Pekkanen J, Kaarsalo E, Wolf E, Aro A, Punsar S, Karvonen MJ. Prevalence of diabetes mellitus in elderly men aged 65 to 84 years in eastern and western Finland. Diabetologia 1986; 29:611-615.

76. Tuomilehto J, Korhonen HJ, Kartovaara L, Salomaa V, Stengard JH, Pitkanen M, Aro A, Javela K, Uusitupa M, Pitkaniemi J. Prevalence of diabetes mellitus and impaired glucose tolerance in the middle-aged population of three areas in Finland. Int J Epidemiol 1991; 20:1010-1017.

77. Verrillo A, de Teresa A, La Rocca S, Giarrusso PC. Prevalence of diabetes mellitus and impaired glucose tolerance in a rural area of Italy. Diabetes Res Clin Pract 1985; 2:301-306.

78. Garancini MP, Calori G, Ruotolo G, Manara E, Izzo A, Ebbli E, Bozzetti AM, Boari L, Lazzari P, Gallus G. Prevalence of NIDDM and impaired glucose tolerance in Italy: an OGTT-based population study. Diabetologia 1995; 38:306-313.

79. Vilbergsson S, Sigurdsson G, Sigvaldason H, Hreidarsson AB, Sigfusson N. Prevalence and incidence of NIDDM in Iceland: evidence for stable incidence among males and females 1967-1991 – the Reykjavik Study. Diabet Med 1997;14:491-498.

80. Unwin N, Harland J, White M, Bhopal R, Winocour P, Stephenson P, Watson W, Turner C, Alberti KG. Body mass index, waist circumference, waist-hip ratio, and glucose intolerance in Chinese and Europid adults in Newcastle, UK. J Epidemiol Community Health 1997; 51:160-166.

81. Yudkin JS, Forrest RD, Jackson CA, Burnett SD, Gould MM. The prevalence of diabetes and impaired glucose tolerance in a British population. Diabetes Care 1993; 16:1530.

82. Bar-On H, Friedlander Y, Kidron M, Kark J. Serum glucose and insulin characteristics and prevalence of diabetes mellitus and impaired glucose tolerance in the adult Jewish population of Jerusalem. J Cardiovasc Dis 1992; 2:75-81.

83. Stern E, Raz I, Weitzman S. Prevalence of diabetes mellitus among workers in Israel: a nation-wide study. Acta Diabetol 1999; 36:169-172.

84. King H, Abdullaev B, Djumaeva S, Nikitin V, Ashworth L, Dobo MG. Glucose intolerance and associated factors in the Fergana Valley, Uzbekistan. Diabet Med 1998;15:1052-1062.

85. Schranz AG. Abnormal glucose tolerance in the Maltese. A population-based longitudinal study of the natural history of NIDDM and IGT in Malta. Diabetes Res Clin Pract 1989;7:7-16.

86. Wilks R, Rotimi C, Bennett F, McFarlane-Anderson N, Kaufman JS, Anderson SG, Cooper RS, Cruickshank JK, Forrester T. Diabetes in the Caribbean: results of a population survey from Spanish Town, Jamaica. Diabet Med 1999; 16:875-883.

87. Hennis A, Wu SY, Nemesure B, Li X, Leske MC. Diabetes in a Caribbean population: epidemiological profile and implications. Int J Epidemiol 2002; 31:234-239.

88. Costagliola D, Delaunay C, Moutet JP, Kankambega P, Demeulemeester R, Donnet JP, Papoz L, Eschwege E. The prevalence of diabetes mellitus in the adult population of Guadeloupe as estimated by history or fasting hyperglycemia. Diabetes Res Clin Pract 1991; 12:209-216.

89. Stern MP, Gonzalez C, Mitchell BD, Villalpando E, Haffner SM, Hazuda HP. Genetic and environmental determinants of type II diabetes in Mexico City and San Antonio. Diabetes 1992; 41:484-492.

90. Posadas-Romero C, Yamamoto-Kimura L, Lerman-Garber I, Zamora-Gonzalez J, Fajardo-Gutierrez A, Velazquez L, Cardoso-Saldaana G. The prevalence of NIDDM and associated coronary risk factors in Mexico City. Diabetes Care 1994; 17:1441-1448.

91. Harris MI, Flegal KM, Cowie CC, Eberhardt MS, Goldstein DE, Little RR, Wiedmeyer HM, Byrd-Holt DD. Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults. The Third National Health and Nutrition Examination Survey, 1988-1994. Diabetes Care 1998; 21:518-524.

92. Hernandez RE, Cardonnet LJ, Libman C, Gagliardino JJ. Prevalence of diabetes and obesity in an urban population of Argentina. Diabetes Res Clin Pract 1987; 3:277-283.

93. Barceló A, Daroca MC, Ribera R, Duarte E, Zapata A, Vohra M. Diabetes in Bolivia. Rev Panam Salud Publica 2001; 10:318-323.

94. Oliveira JE, Milech A, Franco LJ, The Cooperative Group for the Study of Diabetes Prevalence in Rio De Janeiro. The prevalence of diabetes in Rio de Janeiro, Brazil. Diabetes Care 1996; 19:663-666.

95. Malerbi DA, Franco LJ, The Brazilian Cooperative Group on the Study of Diabetes. Multicenter study of the prevalence of diabetes mellitus and impaired glucose tolerance in the urban Brazilian population aged 30-69 yr. Diabetes Care 1992; 15:1509-1516.

96. Jimenez JT, Palacios M, Canete F, Barriocanal LA, Medina U, Figueredo R, Martinez S, de Melgarejo MV, Weik S, Kiefer R, Alberti KG, Moreno-Azorero R. Prevalence of diabetes mellitus and associated cardiovascular risk factors in an adult urban population in Paraguay. Diabet Med 1998;15:334-338.

97. Aschner P, King H, Triana de Torrado M, Rodriguez BM. Glucose intolerance in Colombia. A population-based survey in an urban community. Diabetes Care 1993; 16:90-93.

98. Schaad JD, Terpstra J, Oemrawsingh I, Nieuwenhuijzen Kruseman AC, Bouwhuis-Hoogerwerf ML. Diabetes prevalence in the three main ethnic groups in Surinam (South-America): a population survey. Neth J Med 1985;28:17-22.

99. Sayeed MA, Ali L, Hussain MZ, Rumi MA, Banu A, Azad Khan AK. Effect of socioeconomic risk factors on the difference in prevalence of diabetes between rural and urban populations in Bangladesh. Diabetes Care 1997; 20:551-555.

100. Sayeed MA, Hussain MZ, Banu A, Rumi MA, Azad Khan AK. Prevalence of diabetes in a suburban population of Bangladesh. Diabetes Res Clin Pract 1997; 34:149-155.

101. Ramachandran A, Snehalatha C, Kapur A, Vijay V, Mohan V, Das AK, Rao PV, Yajnik CS, Prasanna Kumar KM, Nair JD. High prevalence of diabetes and impaired glucose tolerance in India: National Urban Diabetes Survey. Diabetologia 2001; 44:1094-1101.

102. Fernando DJ, Siribaddana S, de Silva D. Impaired glucose tolerance and diabetes mellitus in a suburban Sri Lankan community. Postgrad Med J 1994; 70:347-349.

103. Dunstan DW, Zimmet PZ, Welborn TA, De Courten MP, Cameron AJ, Sicree RA, Dwyer T, Colagiuri S, Jolley D, Knuiman M, Atkins R, Shaw JE. The rising prevalence of diabetes and impaired glucose tolerance: the Australian





Diabetes, Obesity and Lifestyle Study. Diabetes Care 2002; 25:829-834.

104. Epidemiology and Disease Control Department. National Health Survey 1998 Singapore. Ministry of Health, Singapore, 1999.

105. Thai Health Research Institute. Report of the First National Health Examination 1991-1992. Thai Health Research Institute, Bangkok, 1996; pp. 107-110.

106. Janus ED, Watt NM, Lam KS, Cockram CS, Siu ST, Liu LJ, Lam TH on behalf of the Hong Kong Cardiovascular Risk Factor Steering Committee. The prevalence of diabetes, association with cardiovascular risk factors and implications of diagnostic criteria (ADA 1997 and WHO 1998) in a 1996 community-based population study in Hong Kong Chinese. Diabet Med 2000; 17:741-745.

107. Cockram CS, Woo J, Lau E, Chan JC, Chan AY, Lau J, Swaminathan R, Donnan SP. The prevalence of diabetes mellitus and impaired glucose tolerance among Hong Kong Chinese adults of working age. Diabetes Res Clin Pract 1993; 21:67-73.

108. Pan XR, Yang WY, Li GW, Liu J, National Diabetes Prevention and Control Cooperative Group. Prevalence of diabetes and its risk factors in China, 1994. Diabetes Care 1997;20:1664-1669.

109. King H, Taylor R, Koteka G, Nemaia H, Zimmet P, Bennett PH, Raper LR. Glucose tolerance in Polynesia. Population-based surveys in Rarotonga and Niue. Med J Aust 1986;145: 505-509.

110. Waspadji S, Ranakusuma AB, Suyono S, Supartondo S, Sukaton U. Diabetes mellitus in an urban population in Jakarta, Indonesia. Tohoku J Exp Med 1983; 141 Suppl:219-228.

111. Zimmet P, Taylor R, Ram P, King H, Sloman G, Raper LR, Hunt D. Prevalence of diabetes and impaired glucose tolerance in the biracial (Melanesian and Indian) population of Fiji: a rural-urban comparison. Am J Epidemiol 1983;118:673-688.

112. Collins VR, Dowse GK, Toelupe PM, Imo TT, Aloaina FL, Spark RA, Zimmet PZ. Increasing prevalence of NIDDM in the Pacific island population of Western Samoa over a 13-year period. Diabetes Care 1994; 17:288-296.

113. King H, Taylor R, Zimmet P, Pargeter K, Raper LR, Beriki T, Tekanene J. Non-insulin-dependent diabetes (NIDDM) in a newly independent Pacific nation: the Republic of Kiribati. Diabetes Care 1984; 7:409-415.

114. Ohmura T, Ueda K, Kiyohara Y, Kato I, Iwamoto H, Nakayama K, Nomiyama K, Ohmori S, Yoshitake T, Shinkawu A, Hasuo Y, Fujishima M. Prevalence of type 2 (non-insulin-dependent) diabetes mellitus and impaired glucose tolerance in the Japanese general population: the Hisayama Study. Diabetologia 1993; 36:1198-1203.

115. Sekikawa A, Eguchi H, Tominaga M, Igarashi K, Abe T, Manaka H, Sasaki H, Fukuyama H, Kato T, Kiyohara Y, Fujishima M. Prevalence of type 2 diabetes mellitus and impaired glucose tolerance in a rural area of Japan. The Funagata diabetes study. J Diabetes Complications 2000; 14:78-83.

116. Park Y, Lee H, Koh CS, Min H, Yoo K, Kim Y, Shin Y. Prevalence of diabetes and IGT in Yonchon County, South Korea. Diabetes Care 1995; 18:545-548.

117. Quoc PS, Charles MA, Cuong NH, Lieu LH, Tuan NA, Thomas M, Balkau B, Simon D. Blood glucose distribution and prevalence of diabetes in Hanoi (Vietnam). Am J Epidemiol 1994; 139:713-722.

118. Suvd J, Gerel B, Otgooloi H, Purevsuren D, Zolzaya H, Roglic G, King H. Glucose intolerance and associated factors in Mongolia: results of a national survey. Diabet Med 2002; 19:502-508.

119. Zimmet P, King H, Taylor R, Raper LR, Balkau B, Borger J, Heriot W, Thoma K. The high prevalence of diabetes mellitus, impaired glucose tolerance and diabetic retinopathy in Nauru – the 1982 survey. Diabetes Res Clin Pract 1984; 1:13-18.

120. Zimmet P, Canteloube D, Genelle B, LeGonidec G, Couzigou P, Peghini M, Charpin M, Bennett P, Kuberski T, Kleiber N, Taylor R. The prevalence of diabetes mellitus and impaired glucose tolerance in Melanesians and part-Polynesians in rural New Caledonia and Ouvea (Loyalty Islands). Diabetologia 1982; 23:393-398.

121. Ministry of Health NZ. Diabetes in New Zealand: Models and forecasts 1996-2011. New Zealand, Wellington, 2002.

122. Chou P, Chen HH, Hsiao KJ. Community-based epidemiological study on diabetes in Pu-Li, Taiwan. Diabetes Care 1992; 15:81-89.

123. Chou P, Liao MJ, Kuo HS, Hsiao KJ, Tsai ST. A population survey on the prevalence of diabetes in Kin-Hu, Kinmen. Diabetes Care 1994; 17:1055-1058.

124. Colagiuri S, Colagiuri R, Na’ati S, Muimuiheata S, Hussain Z, Palu T. The prevalence of diabetes in the Kingdom of Tonga. Diabetes Care 2002; 25:1378-1383.

125. CIA. World Factbook 2002. http://www.cia.gov/cia/publications/factbook/index.html. Central Intelligence Agency, 2002.





1.2 Complications of Diabetes

mainly to the rapid rise in its prevalence that has occurred in the latter part of the 20th century. The main relevance of diabetes complications in a public health perspective is the relationship to human suffering and disability, and the huge socio-economic costs through premature morbidity and mortality (1).

Chronic elevation of blood glucose, even when no symptoms are present to alert the individual to the presence of diabetes, will eventually lead to tissue damage, with consequent, and often serious, disease. Whilst evidence of tissue damage can be found in many organ systems, it is the kidneys, eyes, peripheral nerves and vascular tree, which manifest the most significant, and sometimes fatal, diabetic complications. Indeed, diabetic complications are those aspects of the disease that are most feared (such as blindness and amputation), and account for much of the social and financial burden of diabetes.

The mechanism by which diabetes leads to these complications is complex, and not yet fully understood, but involves the direct toxic effects of high glucose levels, along with the impact of elevated blood pressure, abnormal lipid levels and both functional and structural abnormalities of small blood vessels.

In an attempt to better describe and understand the burden of diabetic complications, this section presents data on the rates of myocardial infarction, stroke, diabetic retinopathy, diabetic nephropathy, diabetic peripheral neuropathy and lower extremity amputations. The results of each study are presented against the country in which it was conducted, although given the design and small size of some of the studies, the results should not necessarily be seen as being representative of that country.

Introduction

Over the last 30 years, type 2 diabetes has changed from being seen as a relatively mild ailment associated with ageing and the elderly (‘just a touch of sugar’) to one of the major contemporary causes of premature mortality and morbidity in most countries. In virtually every developed society, diabetes is ranked among the leading causes of blindness, renal failure and lower limb amputation. Through its effects on cardiovascular disease (70-80% of people with diabetes die of cardiovascular disease), it is also now one of the leading causes of death.

The changing perceptions of diabetes relate partly to a better appreciation of its devastating complications, but

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Major diabetic complications

Over the last two or three decades, there has been an increasing awareness of the magnitude of the problem presented by diabetic complications. The major complications are:

• Cardiovascular disease Cardiovascular disease is the major

cause of death in diabetes, and people with diabetes without previous myocardial infarction have been shown to have as high a risk of myocardial infarction as have non-diabetic patients with previous myocardial infarction (2) (see Chapter 3).

• Nephropathy Diabetes is an increasingly important

cause of renal failure (see Figure 1.11), and indeed has now become the single most common cause of end stage renal disease (ie that which requires either dialysis or kidney transplantation) in the USA (3).

• Neuropathy Diabetes leads to a wide range of

effects on the peripheral nervous system, but the most common manifestation of diabetic neuropathy is sensory loss in the feet. Although neuropathy can sometimes lead to severe pain, it is often silent. However, even in the absence of symptoms, it puts the individual at high risk of foot ulceration and amputation.

• Retinopathy Diabetic retinopathy is probably the

most characteristic, easily identifiable and treatable complication of diabetes, but remains an important cause of visual loss in the developed world (5). Since type 2 diabetes often remains undiagnosed for several years, a significant number of people, even in developed countries, already have retinopathy and other complications at the time of diagnosis of diabetes (6).

• Amputation Through effects on peripheral nerves

and arteries, diabetes can lead to foot ulceration, infection and the need for amputation. People with diabetes carry a risk of amputation that may be more than 25 times greater than that seen in those without diabetes (7).

Methods

Details of the methods used in this report on diabetes complications are found in Appendix 1.2. The main principles in collating available prevalence data were:

1 Studies were identified through a detailed literature search, as well as contact with IDF member organizations.

2 Studies with ≥100 participants were included; where more than one study was available for a country, preference was given to larger and population-based studies, those published after 1989, and those with the fewest restrictions.

Figure 1.11Number of people with diabetes entering the Australian dialysis register, 1980-2000 (4)

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3 Prevalences are reported for myocardial infarction, stroke, retinopathy, neuropathy and nephropathy, and incidence and prevalence for lower extremity amputations.

4 Where possible, the age ranges of the populations are reported. Where the

age range of the population was not available, the mean or median age is reported.

5 Diagnostic criteria for each complication are recorded, as variation in definitions can affect the prevalences reported.

Profile: Janelle Colquhoun

Janelle Colquhoun was determined not to let diabetes interrupt her plans to perform onstage when diagnosed with type 1 diabetes at the age of 10. Headstrong, independent and driven since childhood, Janelle became the successful opera singer that she had always wanted to be.

But now at 37, “I am not dead, but I am paying the penalty for my years of careless control,” Janelle says. “My diabetes always came second to the rest of my life, having to fit in when I had time for it.” Janelle is blind, has kidney failure and has lost sensation in her hands and feet.

“While my doctor tried to convince me that I needed to take good care of my diabetes, I heard his words as ‘live a boring and non-eventful life, doing and eating exactly the same things at the same time each day’,” says Janelle, recalling her earlier years. “I wanted to have an exciting life, travel the world, keep long hours in a theatre and do things when it suited me.” His further threats of “if you don’t get better diabetic control you’ll be dead by the time you’re 30”, only pushed Janelle towards partying harder, taking greater risks, and cramming more into life before reaching 30.

Although it is too late to reverse the complications, Janelle has well-controlled diabetes now. The turning point in her diabetes control came when she was sent to a live-in diabetic clinic for one month after she had nearly died due to hyperglycaemia caused by an extreme weight-reduction diet. The clinic changed her into an educated person with diabetes. Says Janelle: “This was the first time I became aware that I could control my diabetes and live a full and exciting life.”

“The clinic rather than lecturing me about being a bad diabetic taught me how to be a good doctor,” she explains. “We were given the same information that the doctors base their advice on to give us best control, as they explained we are living with diabetes every minute and need to make the day-to-day choices.”

At the clinic in Germany, where she was living at the time, Janelle learnt about all aspects of diabetes and how to manage it. Although it required hard work on her part, Janelle found that she was in a position to make her own decisions. “We tried out different injection





6 For some countries, results from more than one study are presented. This is usually because they cover different aspects of the diabetic population.

There are some important differences between this section and Chapter 1.1 on diabetes prevalence and IGT. The total

numbers of individuals within a country who may have complications are not estimated, nor is a national prevalence. Furthermore, data have not been projected from one country onto other countries. This is for two reasons: firstly, such calculations require knowledge of the age and sex structure of both the

regimes under the doctor’s supervision until we worked out a regime to suit our lifestyle and circumstances. For the first time I was allowed to use my own intellect to make decisions and could plan a regime that suited my timetable and lifestyle.”

Before reaching this point, Janelle was busy fulfilling her dreams to perform onstage. She sang with the Australian Opera, and subsequently travelled the world. She then lived in Germany, singing with the Frankfurt Opera. “Often I did not even bother to blood test, as I knew it would be high,” recalls Janelle, “I always had a fear of having a hypoglycaemia onstage and never working again so purposely left it this way.”

She lost her eyesight due to diabetic retinopathy while living in Germany. She went through painful laser treatment before undergoing 12 eye operations to save her sight. After a prolonged period in hospital, the eye specialists released her into a world of blackness, and she returned home to Australia.

Adjusting to life without sight was more difficult than for a person without diabetes. Since Janelle had lost all sensation in her feet and hands many years earlier due to diabetic neuropathy, identifying surfaces, temperature, even learning to walk along the street with a white cane was near impossible. Obviously learning Braille was out of the question. Fortunately, technology has helped with the use of screen reading computers and it has allowed Janelle to read and write again, and participate in the world around her.

With the help of her husband, Janelle established Salubrious Productions, a growing company which represents professional artistes with disability. Not long after her marriage, Janelle discovered a large lump in her breast, which was surgically removed and diagnosed as diabetic mastopathy, one of the lesser known complications.

Janelle’s return to the stage and an active life was cut short again when her kidneys began to fail due to diabetic nephropathy. Janelle recalls that difficult year: “I had an important year planned with many major singing engagements. I spent most of the year in bed, often unable to get up and mostly too exhausted to sing.” “I wish I had made educated choices when I was younger,” says Janelle, “however I am not without hope for the future.” She is on a waiting list for pancreas/kidney transplant and has hopes that advances in science and technology will bring her sight back. She regularly speaks at conferences and is active in Diabetes Australia. “Life continues to be full and eventful for people experiencing diabetes, and for those of us with complications also.”





original study population, and of the target (national diabetic) population. In most cases, neither of these is known. Secondly, many studies are clinic based, and so their generalizability is limited.

Results

The results are provided in Tables 1.41 – 1.50. A brief summary of results for each complication is presented below. Comments have excluded studies focusing on children.

Cardiovascular diseaseThe prevalence of coronary heart disease (CHD) in those with diabetes (both type 1 and type 2) ranged from 1.0% to 25.2% in clinic-based populations and from 1.8% to 43.4% in population-based studies. The prevalence of stroke in those with diabetes (type 1 and type 2) ranged from 1% to 11.3% in clinic-based populations and from 2.8% to 12.5% in population-based studies.

For CHD, fifty percent of the prevalences were between 0.5% and 8.7% for type 1 diabetes, and between 9.8% and 22.3% for type 2 diabetes. For stroke, fifty percent of the prevalences in type 1 diabetes were between 0.5% and 4.3%, and between 4.1% and 6.7% for type 2 diabetes.

NephropathyThe prevalence of microalbuminuria in those with type 1 diabetes ranged from 4.3% to 37.6% in clinic-based populations and from 12.3% to 27.2% in population-based studies. Among those with type 2 diabetes the prevalence of microalbuminuria ranged from 2.5% to 57.0% in clinic-based population and from 18.9% to 42.1% in population-based studies.

The prevalence of overt nephropathy in those with type 1 diabetes ranged from 0.7% to 27% in clinic-based populations and from 0.3% to 24% in population-based studies. Among those with

type 2 diabetes, the prevalence of overt nephropathy ranged from 5.4% to 20.0% in clinic-based populations and from 9.2% to 32.9% in population-based studies.

For microalbuminuria, fifty percent of the prevalences were between 18.3% and 24.5% for type 1 diabetes, and between 21.4% and 42.0% for type 2 diabetes. For overt nephropathy, fifty percent of the prevalences in type 1 diabetes were between 6.0% and 15.3%, and between 9.2% and 19.1% for type 2 diabetes.

NeuropathyThe prevalence of neuropathy in those with type 1 diabetes ranged from 3.0% to 65.8% in clinic-based populations and from 12.8% to 54.0% in population-based studies.

Among those with type 2 diabetes, the prevalence of neuropathy ranged from 7.6% to 68.0% in clinic-based populations and from 13.1% to 45.0% in population-based studies. Fifty percent of the neuropathy prevalences for type 1 diabetes were between 22.4% and 30.1%, and between 19.3% and 33.7% for type 2 diabetes.

RetinopathyThe prevalence of retinopathy in those with type 1 diabetes ranged from 10.8% to 60.0 % in clinic-based populations and from 14.5% to 79.0% in population-based studies. Among those with type 2 diabetes, the prevalence of retinopathy ranged from 10.6% to 47.3% in clinic-based populations and from 10.1% to 55.0% in population-based studies. Fifty percent of the retinopathy prevalences for type 1 diabetes were between 33.5% and 53.5%, and between 24.8% and 36.1% for type 2 diabetes.

AmputationThe prevalence of lower extremity amputations ranged from 0.2% to 4.8% and the incidence ranged from 46.1 per 100,000 diabetic population to 810 per 100,000 diabetic population. Fifty percent





of the amputation prevalences were between 0.9% and 2.4%, and between 169 per 100,000 diabetic population and 457 per 100,000 diabetic population for the incidence of amputations.

Discussion

The aims of this section were to describe the burden of diabetic complications, and to be able to examine the differences existing between countries and between ethnic groups. In order to do this with confidence, it is necessary that there is a degree of uniformity in the methodology of the different studies. This, however, was not the case.

For each of the complications, a wide range of results was found, but understanding the underlying causes of this diversity is difficult. For example, the low prevalence of neuropathy seen in Mauritius (8) could be due to a low inherent risk for neuropathy in that population, the availability of high quality diabetes care, the relative youth of a population in a developing country, the methods used in the study for defining neuropathy or the population-based study design. In the absence of similar studies, it is almost impossible to determine which of these explanations may be correct.

The problem of accurately describing the burden and making comparisons is made particularly difficult by the relative lack of population-based studies. Studies based in secondary care tend to over-represent those with advanced disease, as those requiring more intensive monitoring are generally referred on for specialist care. Furthermore, prevalences in clinic populations will depend on local referral patterns, which are likely to vary widely around the world.

Neither the diagnostic tools nor diagnostic thresholds used to define a complication were equivalent across studies. For example, neuropathy was

defined as the absence of ankle reflexes in one study (9), and as the presence of symptoms and clinical signs (using validated scales) in another (10). The inconsistent use of diagnostic tools to classify a complication has been shown to dramatically affect the prevalence reported. The Diabetes Control and Complications Trial (DCCT) compared the prevalence of neuropathy using 11 different criteria and found that within the one population, the prevalence of neuropathy varied from 0.3%, using sensory examination, reflexes and symptoms, through to 21.8% using nerve conduction tests (11).

Another example of the variability brought about by changing methodology is highlighted by a study on amputation. A study by Humphrey compared the incidence of lower extremity amputations in one population, when primary or all amputations were included (12). The incidence of lower extremity amputations varied from 276 per 100,000 person years (primary amputation) to 388 per 100,000 person years (all amputations). Further differences in amputation incidences are likely to be due to the (rather imprecise) method of estimating the total diabetic population from which those with amputations were drawn.

One large study, EURODIAB, examined the prevalence of retinopathy, neuropathy and nephropathy in type 1 diabetes across several European countries (13,14). This study used standard methodology, making it possible to gain some insight into whether observed differences in prevalence estimates are due to methodological problems or represent actual differences. The study found the prevalence of complications did vary between centres. The prevalence of retinopathy ranged from 21% in a clinic in Germany to 60% in a Portuguese clinic. However, much less variation was seen for neuropathy and microalbuminuria, for which the prevalences clustered fairly tightly around 25% and 23% respectively.



Any conclusions about the burden of disease attributable to diabetic complications must be very guarded, and comparisons between different parts of the world should be extremely cautious. Nevertheless, some tentative comments can be made:

• The prevalence of retinopathy is probably around 30% in type 2 diabetes, but notably was above this in five out of the six studies reported from the Asian and Pacific island nations of the Western Pacific Region.

• Of the six population-based studies giving figures for neuropathy in type 2 diabetes, the two with the highest prevalence were both from the USA.

• Populations from Europe had high rates of heart disease and stroke, while migrant Indian (Mauritius and Fiji) populations also had high rates of heart disease.

• No discernable patterns relating to geographic distribution or study design were apparent for nephropathy or amputations.

In summary, the interpretation of these studies of diabetic complications is severely hampered by the lack of population-based studies, and the wide variability in study design. Nevertheless, the data from EURODIAB would indicate that at least for some complications in type 1 diabetes, genuine differences exist between countries. What is absolutely clear from this review is that there are large parts of the world for which there are no useful data, and that there is a great need for population-based studies, using standardized protocols so that meaningful estimates of the prevalence of diabetic complications can be made.





Region Country Data used Study type Sample size Age sample Duration DM (yrs) Diagnostic criteria – CHD# Diagnostic criteria – stroke+

AFR

South Africa Rotchford et al, 200215 Clinic (secondary care) 253 21-81 4 ± N/A N/A Self-report / medical record review

EMME

Pakistan Hashim et al, 199916 Clinic (primary care) 805 31->70 N/A Medical record review / self-report (MI, angina) Medical record review (includes TIA)

Sudan Elmahdi et al, 199117 Clinic (secondary care) 413 20+ <5->15 Self-report confirmed by ECG (CHD) Self-report (stroke, TIA)

EUR

Austria Mühlhauser et al, 199218 Clinic (primary care) 375 median=67 median=6 Self-report (MI) Self-report (stroke)

Belgium Van Acker et al, 200119 Clinic (secondary care) 1,653 21-69 range 5-27 Medical record review (CHD) Medical record review (CBVD)

Denmark Gall et al, 199120 Clinic (secondary care) 549 <76 range 0-20 ECG (Minnesota codes) N/A

Estonia Vides et al, 200121 Register 181 15-82 11 ± 10 ECG / self-report / medical record review (CHD) Self-report / medical record review (CBVD)

Finland Hu, 200322 Population based 172 25-64 N/A Self-report Self-report

Isomaa et al, 200123 Clinic (primary care) 1,697 35-70 N/A Self-report / medical record review (MI) Self-report / medical record review (stroke)

France Le Floch et al, 200024 Clinic (primary care) 7,391 mean=63 11 ± 0.1 Self-report / medical record review (CHD) Self-report / medical record review (CBVD)

Delcourt et al, 199825 Clinic (secondary care) 427 35-74 11 ± 7 Self-report / ECG (MI) N/A

Germany Liebl et al, 200226 Clinic (primary and secondary care) 2,701 mean=67 N/A Medical record review (MI, angina, congestive heart failure,coronary bypass surgery)

Medical record review (stroke)

Netherlands Reenders et al, 199327 Clinic (primary care) 387 mean=68 8 ± 6 Medical record review (MI, angina) Medical record review (stroke)

de Visser et al, 200228 Population based 281 22-96 8 ± 7 Medical record review (MI, PTCA, coronary artery bypass) Medical record review (stroke, TIA)

Verhoeven et al, 199129 Clinic (primary care) 137 mean=68 8 ± 7 ECG (Minnesota codes) N/A

Serbia and Montenegro Miljus, 200230 N/A N/A N/A N/A N/A N/A

Vlajinac et al, 199231 Population based 152 35-54 N/A ECG (Minnesota codes) questionnaire (MI, angina) N/A

Slovakia Slovakian Diabetes Societya, 32 Clinic (secondary care) N/A N/A N/A N/A N/A

Spain Diamante, 199733 Clinic (secondary care) 1,822 >18 14 ± 9 Self-report (CHD) Self-report (stroke)

Esmatjes et al, 199634 Clinic (primary and secondary care) 1,157 45-70 9 ± 7 Self-report (CHD) Self-report (stroke)

Sweden Lundman et al, 199835 Clinic (primary and secondary care) 4,027 ≥18 10 ± 7 Medical record review (MI, angina) Medical record review (stroke)

United Kingdom Morgan et al, 200036 Clinic (primary and secondary care) 10,287 mean=61 N/A Hospital codes and primary care audit (CHD) Hospital codes and primary care audit (CBVD)

NA

USA Maser at al, 199137 Clinic (secondary care) 657 mean=28 19 ± 8 ECG / medical record review (MI, angina) N/A

Alexander et al, 200038 Population based N/A ≥20 N/A Self-report, Rose questionnaire (MI, angina) N/A

Qureshi et al, 199839 Population based 1,532 40-74 N/A Self-report (MI) Self-report (stroke)

Barzilay et al, 200140 Population based 479 ≥65 N/A Medical record review (MI, angina, congestive heart failure,coronary bypass surgery)

Medical record review (stroke, TIA)

SEA

Bangladesh Chuang et al, 2002c, 41 Clinic (secondary care) 1,607 10-91 8 ± 6 Medical record review (CHD) Medical record review (CBVD)

Sayeed et al, 199842 Clinic (secondary care) 693 30-60 0 – 2 ECG and Self-report (MI, angina) N/A

India Ramachandran et al, 1999c, 43 Clinic (secondary care) 3,010 mean=52 8 ± 6 ECG (Minnesota codes) / medical record review (MI) N/A

Ramachandran et al, 200044 Clinic (secondary care) 617 10-50 median=4 ECG (Minnesota codes) / medical record review (MI) N/A

Mauritius Collins et al, 199345 Population based 259 35-74 N/A ECG (Minnesota codes) N/A

Sri Lanka Chuang et al, 2002c, 41 Clinic (secondary care) 1,213 14-91 8 ± 7 Medical record review (CHD) Medical record review (CBVD)

Fernando et al, 199346 Clinic (secondary care) 500 mean=52 8 ± N/A ECG (Minnesota codes) Questionnaire

WP

China, People’s Republic of Chuang et al, 2002c, 41 Clinic (secondary care) 2,430 7-92 8 ± 6 Medical record review (CHD) Medical record review (CBVD)

Chi et al, 200147 Clinic (secondary care) 447 35-54 range <7-14 ECG (Minnesota codes) / self-report (MI, angina) Self-report (stroke)

Fiji (Asian Indian) Tuomilehto et al, 198848 Population based 151 N/A N/A ECG (Minnesota codes) N/A

Indonesia Chuang et al, 2002c, 41 Clinic (secondary care) 2,093 22-89 8 ± 6 Medical record review (CHD) Medical record review (CBVD)

Japan Kuzuya et al, 199449 Clinic (secondary care) 2,120 <24->75 11 ± N/A Doctor questionnaire (CHD) Doctor questionnaire (CBVD)

Korea, Republic of Chuang et al, 2002c, 41 Clinic (secondary care) 952 15-92 11 ± 7 Medical record review (CHD) Medical record review (CBVD)

Lee et al, 199550 Clinic (secondary care) 631 30-75 8 ± 7 ECG (Minnnesota codes) / self-report (MI, angina) Self-report (stroke)

Malaysia Chuang et al, 2002c, 41 Clinic (secondary care) 1,045 15-87 11 ± 7 Medical record review (CHD) Medical record review (CBVD)

Nauru Collins et al, 199345 Population based 215 35-80 N/A ECG (Minnesota codes) N/A

New Zealand (European) Simmons et al, 199651 Population based 176 median=61 N/A Self-report (MI) N/A

New Zealand (Maori) Simmons et al, 199651 Population based 286 median=50 N/A Self-report (MI) N/A

New Zealand (Pacific Islanders) Simmons et al, 199651 Population based 495 median=52 N/A Self-report (MI) N/A

Table 1.41Data sources: prevalence of cardiovascular disease






AFR

South Africa Rotchford et al, 200215 Clinic (secondary care) 253 21-81 4 ± N/A N/A Self-report / medical record review

EMME

Pakistan Hashim et al, 199916 Clinic (primary care) 805 31->70 N/A Medical record review / self-report (MI, angina) Medical record review (includes TIA)

Sudan Elmahdi et al, 199117 Clinic (secondary care) 413 20+ <5->15 Self-report confirmed by ECG (CHD) Self-report (stroke, TIA)

EUR

Austria Mühlhauser et al, 199218 Clinic (primary care) 375 median=67 median=6 Self-report (MI) Self-report (stroke)

Belgium Van Acker et al, 200119 Clinic (secondary care) 1,653 21-69 range 5-27 Medical record review (CHD) Medical record review (CBVD)

Denmark Gall et al, 199120 Clinic (secondary care) 549 <76 range 0-20 ECG (Minnesota codes) N/A

Estonia Vides et al, 200121 Register 181 15-82 11 ± 10 ECG / self-report / medical record review (CHD) Self-report / medical record review (CBVD)

Finland Hu, 200322 Population based 172 25-64 N/A Self-report Self-report

Isomaa et al, 200123 Clinic (primary care) 1,697 35-70 N/A Self-report / medical record review (MI) Self-report / medical record review (stroke)

France Le Floch et al, 200024 Clinic (primary care) 7,391 mean=63 11 ± 0.1 Self-report / medical record review (CHD) Self-report / medical record review (CBVD)

Delcourt et al, 199825 Clinic (secondary care) 427 35-74 11 ± 7 Self-report / ECG (MI) N/A

Germany Liebl et al, 200226 Clinic (primary and secondary care) 2,701 mean=67 N/A Medical record review (MI, angina, congestive heart failure,coronary bypass surgery)

Medical record review (stroke)

Netherlands Reenders et al, 199327 Clinic (primary care) 387 mean=68 8 ± 6 Medical record review (MI, angina) Medical record review (stroke)

de Visser et al, 200228 Population based 281 22-96 8 ± 7 Medical record review (MI, PTCA, coronary artery bypass) Medical record review (stroke, TIA)

Verhoeven et al, 199129 Clinic (primary care) 137 mean=68 8 ± 7 ECG (Minnesota codes) N/A

Serbia and Montenegro Miljus, 200230 N/A N/A N/A N/A N/A N/A

Vlajinac et al, 199231 Population based 152 35-54 N/A ECG (Minnesota codes) questionnaire (MI, angina) N/A


Spain Diamante, 199733 Clinic (secondary care) 1,822 >18 14 ± 9 Self-report (CHD) Self-report (stroke)

Esmatjes et al, 199634 Clinic (primary and secondary care) 1,157 45-70 9 ± 7 Self-report (CHD) Self-report (stroke)

Sweden Lundman et al, 199835 Clinic (primary and secondary care) 4,027 ≥18 10 ± 7 Medical record review (MI, angina) Medical record review (stroke)

United Kingdom Morgan et al, 200036 Clinic (primary and secondary care) 10,287 mean=61 N/A Hospital codes and primary care audit (CHD) Hospital codes and primary care audit (CBVD)

NA

USA Maser at al, 199137 Clinic (secondary care) 657 mean=28 19 ± 8 ECG / medical record review (MI, angina) N/A

Alexander et al, 200038 Population based N/A ≥20 N/A Self-report, Rose questionnaire (MI, angina) N/A

Qureshi et al, 199839 Population based 1,532 40-74 N/A Self-report (MI) Self-report (stroke)

Barzilay et al, 200140 Population based 479 ≥65 N/A Medical record review (MI, angina, congestive heart failure,coronary bypass surgery)

Medical record review (stroke, TIA)

SEA

Bangladesh Chuang et al, 2002c, 41 Clinic (secondary care) 1,607 10-91 8 ± 6 Medical record review (CHD) Medical record review (CBVD)

Sayeed et al, 199842 Clinic (secondary care) 693 30-60 0 – 2 ECG and Self-report (MI, angina) N/A

India Ramachandran et al, 1999c, 43 Clinic (secondary care) 3,010 mean=52 8 ± 6 ECG (Minnesota codes) / medical record review (MI) N/A

Ramachandran et al, 200044 Clinic (secondary care) 617 10-50 median=4 ECG (Minnesota codes) / medical record review (MI) N/A

Mauritius Collins et al, 199345 Population based 259 35-74 N/A ECG (Minnesota codes) N/A

Sri Lanka Chuang et al, 2002c, 41 Clinic (secondary care) 1,213 14-91 8 ± 7 Medical record review (CHD) Medical record review (CBVD)

Fernando et al, 199346 Clinic (secondary care) 500 mean=52 8 ± N/A ECG (Minnesota codes) Questionnaire

WP

China, People’s Republic of Chuang et al, 2002c, 41 Clinic (secondary care) 2,430 7-92 8 ± 6 Medical record review (CHD) Medical record review (CBVD)

Chi et al, 200147 Clinic (secondary care) 447 35-54 range <7-14 ECG (Minnesota codes) / self-report (MI, angina) Self-report (stroke)

Fiji (Asian Indian) Tuomilehto et al, 198848 Population based 151 N/A N/A ECG (Minnesota codes) N/A

Indonesia Chuang et al, 2002c, 41 Clinic (secondary care) 2,093 22-89 8 ± 6 Medical record review (CHD) Medical record review (CBVD)

Japan Kuzuya et al, 199449 Clinic (secondary care) 2,120 <24->75 11 ± N/A Doctor questionnaire (CHD) Doctor questionnaire (CBVD)

Korea, Republic of Chuang et al, 2002c, 41 Clinic (secondary care) 952 15-92 11 ± 7 Medical record review (CHD) Medical record review (CBVD)

Lee et al, 199550 Clinic (secondary care) 631 30-75 8 ± 7 ECG (Minnnesota codes) / self-report (MI, angina) Self-report (stroke)

Malaysia Chuang et al, 2002c, 41 Clinic (secondary care) 1,045 15-87 11 ± 7 Medical record review (CHD) Medical record review (CBVD)

Nauru Collins et al, 199345 Population based 215 35-80 N/A ECG (Minnesota codes) N/A

New Zealand (European) Simmons et al, 199651 Population based 176 median=61 N/A Self-report (MI) N/A

New Zealand (Maori) Simmons et al, 199651 Population based 286 median=50 N/A Self-report (MI) N/A

New Zealand (Pacific Islanders) Simmons et al, 199651 Population based 495 median=52 N/A Self-report (MI) N/A





Philippines Chuang et al, 2002c, 41 Clinic (secondary care) 2,657 7-93 9 ± 7 Medical record review (CHD) Medical record review (CBVD)

Singapore, Republic of Chuang et al, 2002c, 41 Clinic (secondary care) 1,674 4-91 10 ± 8 Medical record review (CHD) Medical record review (CBVD)

Thai et al, 199052 Population based 117 18+ N/A ECG (Minnesota codes) / self-report (MI, angina) N/A

Taiwan Chuang et al, 2002c, 41 Clinic (secondary care) 2,420 15-92 10 ± 7 Medical record review (CHD) Medical record review (stroke)

Fuh, 2002a, 53 Clinic (secondary care) 4,535 N/A N/A N/A N/A

Thailand Tatsanavivat et al, 199854 Population based 278 ≥30 N/A ECG (Minnesota codes) N/A

Thai Multicenter Group, 199455 Clinic (secondary care) 1,747 24-88 8 ± 7 ECG Self-report (CBVD) / examination

Tandhanand et al, 200156 Clinic (secondary care) 2,379 mean=59 10 ± 7 Medical record review (CHD) Medical record review (CBVD)

Vietnam Chuang et al, 2002c, 41 Clinic (secondary care) 1,169 3-89 6 ± 5 Medical record review (CHD) Medical record review (CBVD)

a. Unpublished datab. Abstract onlyc. Extra details supplied by authors

CBVD cerebrovascular disease CHD coronary heart disease DM diabetes mellitus ECG electrocardiogram MI myocardial infarction N/A not available PTCA percutaneous transluminal coronary angioplasty TIA transient ischaemic attack

Diagnostic tool: # – The type of CHD (eg MI or MI and angina) reported is stated. If this was not reported in the study, the term CHD is used.+ – The type of CBVD (eg stroke or stroke and TIA) reported is stated. If this was not reported in the study, the term CBVD is used.






Philippines Chuang et al, 2002c, 41 Clinic (secondary care) 2,657 7-93 9 ± 7 Medical record review (CHD) Medical record review (CBVD)

Singapore, Republic of Chuang et al, 2002c, 41 Clinic (secondary care) 1,674 4-91 10 ± 8 Medical record review (CHD) Medical record review (CBVD)

Thai et al, 199052 Population based 117 18+ N/A ECG (Minnesota codes) / self-report (MI, angina) N/A

Taiwan Chuang et al, 2002c, 41 Clinic (secondary care) 2,420 15-92 10 ± 7 Medical record review (CHD) Medical record review (stroke)

Fuh, 2002a, 53 Clinic (secondary care) 4,535 N/A N/A N/A N/A

Thailand Tatsanavivat et al, 199854 Population based 278 ≥30 N/A ECG (Minnesota codes) N/A

Thai Multicenter Group, 199455 Clinic (secondary care) 1,747 24-88 8 ± 7 ECG Self-report (CBVD) / examination

Tandhanand et al, 200156 Clinic (secondary care) 2,379 mean=59 10 ± 7 Medical record review (CHD) Medical record review (CBVD)

Vietnam Chuang et al, 2002c, 41 Clinic (secondary care) 1,169 3-89 6 ± 5 Medical record review (CHD) Medical record review (CBVD)






Prevalence of cardiovascular disease (%)

Region Country

Coronary heart disease Stroke

Total DM UnDM Type 1 DM Type 2 DM Total DM UnDM Type 1 DM Type 2 DM

AFR

South Africa 7.5

EMME

Pakistan 19.8 6.2

Sudan 5.1 4.4

EUR

Austria 11.3 6.2

Belgium 21.0 6.2 30.8

Denmark 26.4

Estonia 7.7 2.8

Finland 8.1 7.6

13.4 5.2

France 13.5 16.3 13.3 4.1 4.3 4.1

8.4

Germany 10.6 6.7

Netherlands 9.0 5.0

20.9 9.1

40.0

Serbia and Montenegro 3.3

35.5

Slovakia 6.0 5.6

Spain 0.5 0.5

11.0 5.0

Sweden 11.5 4.7 12.3 11.3 3.1 12.3

United Kingdom 25.2 9.6

NA

USA 3.4

9.8

10.7 (incl UnDM)

5.0 (incl UnDM)

43.4 12.5

SEA

Bangladesh 2.0 1.0

18.6

India 11.4

0.5

Mauritius Male 22.0 Female 33.7

Sri Lanka 6.0 2.0

12.0 3.6

WP

China, People’s Republic of 1.0 5.0

8.7 3.4

Fiji (Asian Indian) 31.3

Indonesia 5.0 4.0

Japan 2.1 5.7

Korea, Republic of 3.0 6.0

7.8 8.4

Malaysia 12.0 6.0

Nauru 15.8

New Zealand (European) 11.0

New Zealand (Maori) 11.0

New Zealand (Pacific Islanders) 6.0

Philippines 3.0 6.0

Table 1.42Prevalence of cardiovascular disease





Singapore, Republic of 5.0 3.0

12.8 (incl UnDM)

Taiwan 4.0 6.0

18.1 4.7

Thailand 1.8

10.5 3.7

3.0 3.0

Vietnam 1.0 3.0

DM diabetes mellitusTotal DM previously diagnosed diabetes (both type 1 and type 2)UnDM undiagnosed diabetes

Prevalence of cardiovascular disease (%)

Region Country

Coronary heart disease Stroke






Overt Microalbuminuria

Region Country Data used Study type Sample size Age sample Duration DM (yrs) Diagnostic criteria Diagnostic criteria

AFR

Ethiopia Rahlenbeck et al, 199757 Clinic (secondary care) 170 mean=42 6 ± 5 Albuminuria 30-299 mg/le Albuminuria >300mg/le

Nigeria Erasmus et al, 199258 Clinic (secondary care) 113 mean=51 5 ± 1 Albuminuria 20-199 µg/mine N/A

South Africa Kalk et al, 199759 Clinic (secondary care) 448 mean=54 6 ± 6 A/CR 3.0-19.9 mg/mmol A/CR >19.9 mg/mmol

Rotchford et al, 200215 Clinic (secondary care) 253 21-81 4 ± N/A Men A/CR 2.6-19.9 mg/mmol, women A/CR 3.6-19.9 mg/mmol A/CR ≥20 mg/mmol

Levitt et al, 199760 Clinic (primary care) 243 20-85 8 ± 8 A/CR >3.4 mg/mmole N/A

Zambia Rolfe, 198861 Population based 600 mean=49 9 ± 6 N/A Grade 2 proteinuria

EMME

Egypt Herman et al, 199862 Population based 283 20+ N/A A/CR 100 – 299 mg/g A/CR ≥300 mg/g

Saudi Arabia Alzaid et al, 199463 Clinic (secondary care) 211 56 10 ± 5 AER 30-300 mg/24hr Dipstick proteinuria

Sudan Elmahdi et al, 199117 Clinic (secondary care) 413 20+ <5->15 N/A Proteinuria >0.5g/24h or blood urea of >40mg%e

EUR

Austria Mühlhauser et al, 199218 Clinic (primary care) 375 median=67 median=6 Albuminuria 21-200 mg/l Albuminuria >200 mg/l

EuroDiab, 1994c, 13 Clinic (secondary care) 111 15-60 16 ± 10 AER 20-199 µg/min AER ≥200 µg/min

Belgium Bouten et al, 199664 Clinic (secondary care) 271 mean=37 15 ±10 AER 20-200 µg/mine N/A

Van Acker et al, 200119 Clinic (secondary care) 1,653 21-69 range 5-27 Albuminuria ≥ 30mg/dl N/A


Croatia EuroDiab, 1994c, 13 Clinic (secondary care) 138 15-60 14 ± 9 AER 20-199 µg/min AER ≥200 µg/min

Czech Republic Perusicova et al, 1993b, 65 Register 1,443 >18 N/A N/A N/A

Czech Health Statistics, 2002a, 66 Population based N/A N/A N/A N/A N/A

Denmark Mortensen et al, 199067 Clinic (secondary care) 957 <20 5 ± 3 AER >20-150µg/mine AER>150µg/mine

Gall et al, 199120 Clinic (secondary care) 549 <76 range 0-20 AER 31-299 mg/24hr AER ≥300 mg/24hr

Finland EuroDiab, 1994c, 13 Clinic (secondary care) 139 15-60 15 ± 10 AER 20-199 µg/min AER ≥200 µg/min

France EuroDiab, 1994c, 13 Clinic (secondary care) 116 15-60 16 ± 10 AER 20-199 µg/min AER ≥200 µg/min

Delcourt et al, 199825 Clinic (secondary care) 427 35-74 11 ± 7 AER 31-300mg/24hr AER >300 mg./24hr or proteinuria >0.5g/24h

Germany Bennett et al, 200168 Clinic (secondary care) 214 N/A N/A A/CR 30-299 mg/g A/CR ≥300 mg/g

EuroDiab, 1994c,d, 13 Clinic (secondary care) 241 15-60 15 ± 10 AER 20-199 µg/min AER ≥200 µg/min

Greece EuroDiab, 1994c, 13 Clinic (secondary care) 231 15-60 13 ± 8 AER 20-199 µg/min AER ≥200 µg/min

Ireland, Republic of EuroDiab, 1994c, 13 Clinic (secondary care) 112 15-60 15 ± 9 AER 20-199 µg/min AER ≥200 µg/min

Hungary EuroDiab, 1994c,d, 13 Clinic (secondary care) 131 15-60 15 ± 9 AER 20-199 µg/min AER ≥200 µg/min

Israel Norymberg et al, 199169 Clinic (secondary care) 1,019 31+ 12 ± 9 N/A Proteinuria >30mg/dle

Italy EuroDiab, 1994c,d, 13 Clinic (secondary care) 944 15-60 14 ± 9 AER 20-199 µg/min AER ≥200 µg/min

Luxembourg EuroDiab, 1994c, 13 Clinic (secondary care) 102 15-60 14 ± 9 AER 20-199 µg/min AER >200 µg/min

Netherlands EuroDiab, 1994c, 13 Clinic (secondary care) 128 15-60 16 ± 10 AER 20-199 µg/min AER ≥200 µg/min

Reenders et al, 199327 Clinic (primary care) 376 mean=68 8 ± 6 AER 20-200 mg/le AER >200 mg/le

Verhoeven et al, 199129 Clinic (primary care) 137 mean=68 8 ± 7 Albuminuria 20-200 µg/min Proteinuria >0.5 g/24h

Norway Joner et al, 199270 Population based 351 8-30 10 ± 3 AER 16 -200 µg/mine AER >200 µg/mine

Poland EuroDiab, 1994c, 13 Clinic (secondary care) 116 15-60 15 ± 10 AER 20-199 µg/min AER ≥200 µg/min

Bennett et al, 200168 Clinic (secondary care) 186 N/A N/A A/CR 30-299 mg/g A/CR ≥ 300 mg/g

Portugal EuroDiab, 1994c, 13 Clinic (secondary care) 137 15-60 15 ± 10 AER 20-199 µg/min AER ≥200 µg/min

Romania EuroDiab, 1994c, 13 Clinic (secondary care) 110 15-60 13 ± 8 AER 20-199 µg/min AER ≥200 µg/min


Spain Diamante, 199733 Clinic (secondary care) 1,822 >18 14 ± 9 AER 20-200 µg/mine AER >200 µg/mine

Esmatjes et al, 199634 Clinic (primary and secondary care) 1,157 45-70 9 ± 7 AER 20-200 µg/mine AER >200 µg/mine

Sweden Lundman et al, 199835 Clinic (secondary care) 4,027 18+ 10 ± 7 N/A Proteinuria ≥300mg/ge

Ukraine Kravchenko et al, 199671 Clinic (secondary care) 4,123 14-75 N/A Albuminuria ≥20 mg/le N/A

United Kingdom Higgs et al, 199272 Population based 358 6-92 11 ± N/A A/CR ≥2.5 mg/mmol Albustix reading ≥0.3 g/l

Harvey et al, 2001c, 73 Population based 903 3-80 N/A AER 20-200 µg/mine AER >200 µg/mine


NA

USA Garg et al, 200274 Population based 1,192 20-80+ N/A A/CR 3.0-37.8mg/mmol A/CR >37.8mg/mmol

Orchard et al, 199075 Clinic (secondary care) 592 18-30+ 16 ± N/A AER 20-200µg/mine AER >200 µg/mine

SACA

Brazil Foss et al, 198976 Clinic (secondary care) 546 25-84 8 ± 7 N/A Proteinuria >200 mg/24hre

Table 1.43Data sources: prevalence of diabetic nephropathy







AFR

Ethiopia Rahlenbeck et al, 199757 Clinic (secondary care) 170 mean=42 6 ± 5 Albuminuria 30-299 mg/le Albuminuria >300mg/le

Nigeria Erasmus et al, 199258 Clinic (secondary care) 113 mean=51 5 ± 1 Albuminuria 20-199 µg/mine N/A

South Africa Kalk et al, 199759 Clinic (secondary care) 448 mean=54 6 ± 6 A/CR 3.0-19.9 mg/mmol A/CR >19.9 mg/mmol

Rotchford et al, 200215 Clinic (secondary care) 253 21-81 4 ± N/A Men A/CR 2.6-19.9 mg/mmol, women A/CR 3.6-19.9 mg/mmol A/CR ≥20 mg/mmol

Levitt et al, 199760 Clinic (primary care) 243 20-85 8 ± 8 A/CR >3.4 mg/mmole N/A

Zambia Rolfe, 198861 Population based 600 mean=49 9 ± 6 N/A Grade 2 proteinuria

EMME

Egypt Herman et al, 199862 Population based 283 20+ N/A A/CR 100 – 299 mg/g A/CR ≥300 mg/g

Saudi Arabia Alzaid et al, 199463 Clinic (secondary care) 211 56 10 ± 5 AER 30-300 mg/24hr Dipstick proteinuria

Sudan Elmahdi et al, 199117 Clinic (secondary care) 413 20+ <5->15 N/A Proteinuria >0.5g/24h or blood urea of >40mg%e

EUR

Austria Mühlhauser et al, 199218 Clinic (primary care) 375 median=67 median=6 Albuminuria 21-200 mg/l Albuminuria >200 mg/l


Belgium Bouten et al, 199664 Clinic (secondary care) 271 mean=37 15 ±10 AER 20-200 µg/mine N/A

Van Acker et al, 200119 Clinic (secondary care) 1,653 21-69 range 5-27 Albuminuria ≥ 30mg/dl N/A


Croatia EuroDiab, 1994c, 13 Clinic (secondary care) 138 15-60 14 ± 9 AER 20-199 µg/min AER ≥200 µg/min

Czech Republic Perusicova et al, 1993b, 65 Register 1,443 >18 N/A N/A N/A

Czech Health Statistics, 2002a, 66 Population based N/A N/A N/A N/A N/A

Denmark Mortensen et al, 199067 Clinic (secondary care) 957 <20 5 ± 3 AER >20-150µg/mine AER>150µg/mine

Gall et al, 199120 Clinic (secondary care) 549 <76 range 0-20 AER 31-299 mg/24hr AER ≥300 mg/24hr

Finland EuroDiab, 1994c, 13 Clinic (secondary care) 139 15-60 15 ± 10 AER 20-199 µg/min AER ≥200 µg/min

France EuroDiab, 1994c, 13 Clinic (secondary care) 116 15-60 16 ± 10 AER 20-199 µg/min AER ≥200 µg/min

Delcourt et al, 199825 Clinic (secondary care) 427 35-74 11 ± 7 AER 31-300mg/24hr AER >300 mg./24hr or proteinuria >0.5g/24h

Germany Bennett et al, 200168 Clinic (secondary care) 214 N/A N/A A/CR 30-299 mg/g A/CR ≥300 mg/g

EuroDiab, 1994c,d, 13 Clinic (secondary care) 241 15-60 15 ± 10 AER 20-199 µg/min AER ≥200 µg/min

Greece EuroDiab, 1994c, 13 Clinic (secondary care) 231 15-60 13 ± 8 AER 20-199 µg/min AER ≥200 µg/min

Ireland, Republic of EuroDiab, 1994c, 13 Clinic (secondary care) 112 15-60 15 ± 9 AER 20-199 µg/min AER ≥200 µg/min

Hungary EuroDiab, 1994c,d, 13 Clinic (secondary care) 131 15-60 15 ± 9 AER 20-199 µg/min AER ≥200 µg/min

Israel Norymberg et al, 199169 Clinic (secondary care) 1,019 31+ 12 ± 9 N/A Proteinuria >30mg/dle

Italy EuroDiab, 1994c,d, 13 Clinic (secondary care) 944 15-60 14 ± 9 AER 20-199 µg/min AER ≥200 µg/min

Luxembourg EuroDiab, 1994c, 13 Clinic (secondary care) 102 15-60 14 ± 9 AER 20-199 µg/min AER >200 µg/min

Netherlands EuroDiab, 1994c, 13 Clinic (secondary care) 128 15-60 16 ± 10 AER 20-199 µg/min AER ≥200 µg/min

Reenders et al, 199327 Clinic (primary care) 376 mean=68 8 ± 6 AER 20-200 mg/le AER >200 mg/le

Verhoeven et al, 199129 Clinic (primary care) 137 mean=68 8 ± 7 Albuminuria 20-200 µg/min Proteinuria >0.5 g/24h

Norway Joner et al, 199270 Population based 351 8-30 10 ± 3 AER 16 -200 µg/mine AER >200 µg/mine

Poland EuroDiab, 1994c, 13 Clinic (secondary care) 116 15-60 15 ± 10 AER 20-199 µg/min AER ≥200 µg/min

Bennett et al, 200168 Clinic (secondary care) 186 N/A N/A A/CR 30-299 mg/g A/CR ≥ 300 mg/g

Portugal EuroDiab, 1994c, 13 Clinic (secondary care) 137 15-60 15 ± 10 AER 20-199 µg/min AER ≥200 µg/min

Romania EuroDiab, 1994c, 13 Clinic (secondary care) 110 15-60 13 ± 8 AER 20-199 µg/min AER ≥200 µg/min


Spain Diamante, 199733 Clinic (secondary care) 1,822 >18 14 ± 9 AER 20-200 µg/mine AER >200 µg/mine

Esmatjes et al, 199634 Clinic (primary and secondary care) 1,157 45-70 9 ± 7 AER 20-200 µg/mine AER >200 µg/mine

Sweden Lundman et al, 199835 Clinic (secondary care) 4,027 18+ 10 ± 7 N/A Proteinuria ≥300mg/ge

Ukraine Kravchenko et al, 199671 Clinic (secondary care) 4,123 14-75 N/A Albuminuria ≥20 mg/le N/A

United Kingdom Higgs et al, 199272 Population based 358 6-92 11 ± N/A A/CR ≥2.5 mg/mmol Albustix reading ≥0.3 g/l

Harvey et al, 2001c, 73 Population based 903 3-80 N/A AER 20-200 µg/mine AER >200 µg/mine


NA

USA Garg et al, 200274 Population based 1,192 20-80+ N/A A/CR 3.0-37.8mg/mmol A/CR >37.8mg/mmol

Orchard et al, 199075 Clinic (secondary care) 592 18-30+ 16 ± N/A AER 20-200µg/mine AER >200 µg/mine

SACA

Brazil Foss et al, 198976 Clinic (secondary care) 546 25-84 8 ± 7 N/A Proteinuria >200 mg/24hre





SEA

India Ramachandran et al, 200044 Clinic (secondary care) 617 10-50 median=4 N/A Proteinuria ≥500 mg/24hre

Ramachandran et al, 1999c, 43 Clinic (secondary care) 3,010 mean=52 8 ± 6 N/A Proteinuria ≥500 mg/24hre

Mohan et al, 200077 Clinic (secondary care) 1,848 mean=52 7 ± 6 Proteinuria 150-499 mg/24hre Proteinuria ≥500 mg/24hre

Mauritius Dowse et al, 199878 Population based 746 25+ 6 ± N/A Albuminuria 30-299 mg/ml Albuminuria ≥300 mg/ml

Sri Lanka Weerasuriya et al, 199879 Clinic (primary care) 597 25-65 0 ± 0 N/A Albuminuria >50 mg/l

WP

Australia AusDiab Study Group, 200280 Population based 459 25+ median=5 A/CR 3.5-19.9 mg/mmol A/CR ≥20 mg/mmol

China, Hong Kong Ko et al, 199981 Clinic (secondary care) 150 <40 5 ± 0 A/CR ≥3.5 mg/mmol and AER ≥20 µg/mine N/A

Chan et al, 199382 Clinic (secondary care) 397 mean=57 range 0-30 A/CR 5.4-40.3 mg/mmole A/CR >40.3 mg/mmole

China, People’s Republic of Chi et al, 200147 Clinic (secondary care) 447 35-54 N/A N/A Semi quantitative test

Indonesia Diabcare Asia, 2003a, 83 Clinic (primary care) 717 25-85 7 ± 6 Albuminuria 20-300mg/l / A/CR 2.5-25mg/mol (men)A/CR 3.5-25 mg/mol (females)

Albuminuria >300 mg/l / A/CR >25 mg/mol

Japan Kuzuya et al, 199449 Clinic (secondary care) 2,120 <24->75 11 ± N/A Doctor report Doctor report

Kawano et al, 20019 Clinic 6,472 mean=61 10 ± 10 Doctor report Doctor report

Korea, Republic of Lee et al, 199550 Clinic (secondary care) 631 30-75 8 ± 7 AER 20-200 µg/mine AER >200 µg/mine

Malaysia Shriwas et al, 199684 Clinic (secondary care) 131 0-80+ range <5->20 N/A Dipstick proteinuria or creatinine > 97µmol/l

Nauru Collins et al, 198985 Population based 318 25+ range 0->15 Albuminuria 30 -299 µg/ml Albuminuria ≥300 µg/ml

New Zealand (European) Simmons et al, 199486 Clinic (primary and secondary care) 297 18-79 range 0-47 AER 30-299 mg/24hr AER ≥300mg/24hr

New Zealand (Pacific Islanders) Simmons et al, 199486 Clinic (primary and secondary care) 123 18-79 range 0-32 AER 30-299 mg/24hr AER ≥300mg/24hr

Philippines Lantion-Ang, 200087 Clinic (primary care) 359 7-93 9 ± 7 Albuminuria 20-300 mg/l Albuminuria >300 mg/l

Samoa Collins et al, 199588 Population based 141 25-74 4 ± N/A Albuminuria 30-299 µg/ml Albuminuria ≥300 µg/ml

Singapore, Republic of Thai et al, 199052 Population based 117 18+ N/A N/A Albuminuria ≥30 mg/dl or creatinine ≥1.5 mg/dl

Taiwan Fuh, 2002a, 53 Clinic (secondary care) 4,535 N/A N/A N/A A/CR >300 mg/g or blood urea >26 mg/dl or serum creatinine >1.3 mg/dl

Thailand Thai Multicenter Group, 199455 Clinic (secondary care) 2,060 24-88 8 ± 7 N/A Dipstick proteinuria 2+

Vietnam Diabcare Asia, 2003a, 83 Clinic (primary care) 521 1-85 7 ± 5 Albuminuria 20-300mg/l / A/CR 2.5-25mg/mol (men)A/CR 3.5-25 mg/mol (females)


a. Unpublished datab. Abstract onlyc. Extra details supplied by authorsd. More than one centre used to derive prevalence figuree. Diagnosis of nephropathy required two or more urine samples

A/CR albumin/creatinine ratio AER albumin excretion rate DM diabetes mellitus N/A not available







SEA

India Ramachandran et al, 200044 Clinic (secondary care) 617 10-50 median=4 N/A Proteinuria ≥500 mg/24hre

Ramachandran et al, 1999c, 43 Clinic (secondary care) 3,010 mean=52 8 ± 6 N/A Proteinuria ≥500 mg/24hre

Mohan et al, 200077 Clinic (secondary care) 1,848 mean=52 7 ± 6 Proteinuria 150-499 mg/24hre Proteinuria ≥500 mg/24hre

Mauritius Dowse et al, 199878 Population based 746 25+ 6 ± N/A Albuminuria 30-299 mg/ml Albuminuria ≥300 mg/ml

Sri Lanka Weerasuriya et al, 199879 Clinic (primary care) 597 25-65 0 ± 0 N/A Albuminuria >50 mg/l

WP

Australia AusDiab Study Group, 200280 Population based 459 25+ median=5 A/CR 3.5-19.9 mg/mmol A/CR ≥20 mg/mmol

China, Hong Kong Ko et al, 199981 Clinic (secondary care) 150 <40 5 ± 0 A/CR ≥3.5 mg/mmol and AER ≥20 µg/mine N/A

Chan et al, 199382 Clinic (secondary care) 397 mean=57 range 0-30 A/CR 5.4-40.3 mg/mmole A/CR >40.3 mg/mmole

China, People’s Republic of Chi et al, 200147 Clinic (secondary care) 447 35-54 N/A N/A Semi quantitative test

Indonesia Diabcare Asia, 2003a, 83 Clinic (primary care) 717 25-85 7 ± 6 Albuminuria 20-300mg/l / A/CR 2.5-25mg/mol (men)A/CR 3.5-25 mg/mol (females)


Japan Kuzuya et al, 199449 Clinic (secondary care) 2,120 <24->75 11 ± N/A Doctor report Doctor report

Kawano et al, 20019 Clinic 6,472 mean=61 10 ± 10 Doctor report Doctor report

Korea, Republic of Lee et al, 199550 Clinic (secondary care) 631 30-75 8 ± 7 AER 20-200 µg/mine AER >200 µg/mine

Malaysia Shriwas et al, 199684 Clinic (secondary care) 131 0-80+ range <5->20 N/A Dipstick proteinuria or creatinine > 97µmol/l

Nauru Collins et al, 198985 Population based 318 25+ range 0->15 Albuminuria 30 -299 µg/ml Albuminuria ≥300 µg/ml

New Zealand (European) Simmons et al, 199486 Clinic (primary and secondary care) 297 18-79 range 0-47 AER 30-299 mg/24hr AER ≥300mg/24hr

New Zealand (Pacific Islanders) Simmons et al, 199486 Clinic (primary and secondary care) 123 18-79 range 0-32 AER 30-299 mg/24hr AER ≥300mg/24hr

Philippines Lantion-Ang, 200087 Clinic (primary care) 359 7-93 9 ± 7 Albuminuria 20-300 mg/l Albuminuria >300 mg/l

Samoa Collins et al, 199588 Population based 141 25-74 4 ± N/A Albuminuria 30-299 µg/ml Albuminuria ≥300 µg/ml

Singapore, Republic of Thai et al, 199052 Population based 117 18+ N/A N/A Albuminuria ≥30 mg/dl or creatinine ≥1.5 mg/dl

Taiwan Fuh, 2002a, 53 Clinic (secondary care) 4,535 N/A N/A N/A A/CR >300 mg/g or blood urea >26 mg/dl or serum creatinine >1.3 mg/dl

Thailand Thai Multicenter Group, 199455 Clinic (secondary care) 2,060 24-88 8 ± 7 N/A Dipstick proteinuria 2+

Vietnam Diabcare Asia, 2003a, 83 Clinic (primary care) 521 1-85 7 ± 5 Albuminuria 20-300mg/l / A/CR 2.5-25mg/mol (men)A/CR 3.5-25 mg/mol (females)








Prevalence of diabetic nephropathy (%)

Region Country



AFR

Ethiopia 17.1 34.1

Nigeria 57.0

South Africa 14.5 31.0

13.4 32.8

5.3 36.7a

Zambia 23.8

EMME

Egypt 6.7 6.8 14.3 14.1

Saudi Arabia 12.8 36.0

Sudan 9.2

EUR

Austria 15.0 32.0

3.6 23.4

Belgium 14.0

35.4a 37.6a 35.6a

13.0 25.2

Croatia 15.9 29.0

Czech Republic 13.8

7.3a

Denmark 0.7 4.3

14.0 27.0

Finland 15.1 23.7

France 11.2 21.6

6.1 21.8

Germany 7.9 14.5

7.5 21.6

Greece 6.5 23.8

Ireland, Republic of 12.5 17.9

Hungary 6.1 19.8

Israel 7.0

Italy 6.9 19.3

Luxembourg 3.9 23.5

Netherlands 7.0 23.4

13.0 44.0

16.0 42.0

Norway 0.3 12.3

Poland 8.6 19.8

9.7 18.8

Portugal 15.8 24.8

Romania 17.3 26.4

Slovakia 7.6

Spain 5.0 14.1

5.4 23.1

Sweden 12.1 11.8 12.1

Ukraine 9.6


9.6(cumulative prevalence)

27.2 (cumulative prevalence)

5.7 21.7

NA

USA 6.1 28.1

26.4 21.6

Table 1.44Prevalence of diabetic nephropathy





SACA

Brazil 11.3

SEA

India 7.1

19.7 (persistant

5.5%)

10.7 2.5

Mauritius 3.8 10.7

Sri Lanka 29.0a

WP

Australia 8.9 3.9 9.2 19.2 10.5 18.9

China, Hong Kong 22.7a 24.8a

20.0 27.0

China, People’s Republic of 57.1

Indonesia 3.3 4.6

Japan 20.1 27.0 19.5

27.3

Korea, Republic of 14.0 20.0

Malaysia 28.2

Nauru 24.4 32.9 38.9 42.1

New Zealand (European) 5.4 22.1

New Zealand (Pacific Islanders) 13.0 33.3

Philippines 1.0 48.7

Samoa 5.0 (incl UnDM)

19.9 (incl UnDM)

Singapore, Republic of 18.3

Taiwan 19.0

Thailand 18.7

Vietnam 6.1 14.2

a. Includes both micro and macroalbuminuria

DM diabetes mellitusTotal DM previously diagnosed diabetes (both type 1 and type 2)UnDM undiagnosed diabetes

Prevalence of diabetic nephropathy (%)

Region Country







Region Country Data used Study type Sample size Age sample Duration DM (yrs) Diagnostic criteria

AFR

South Africa Levitt et al, 199760 Clinic (primary care) 243 20-85 8 ± 8 Clinical score

Tanzania Wikblad et al, 199789 Clinic (secondary care) 153 mean=44 5 ± 6 Clinical store, quantitative sensory testing (NDS, NSS)

Zambia Rolfe, 198890 Clinic (secondary care) 600 ≥35 7 ± 6 Clinical score

EMME

Egypt Herman et al, 199862 Population based 509 ≥20 N/A Quantitative sensory testing

Saudi Arabia Akbar et al, 200091 Clinic (secondary care) 237 mean=54 11 ± 7 Clinical score (DNI)

Nielsen, 199892 Clinic (secondary care) 375 median=50 median=8 Clinical score

Sudan Elmahdi et al, 199117 Clinic (secondary care) 413 20+ N/A Clinical score

EUR

Austria Mühlhauser et al, 199218 Clinic (primary care) 395 mean=67 N/A Quantitative sensory testing

EuroDiab, 1996c, 14 Clinic (secondary care) 116 15-60 16 ± 10 Clinical score, quantitative sensory testing, autonomic function tests

Belgium Van Acker et al, 200119 Clinic (secondary care) 1,653 21-69 range 5-27 Quantitative sensory testing


Croatia EuroDiab, 1996c, 14 Clinic (secondary care) 132 15-60 14 ± 9 Clinical score, quantitative sensory testing, autonomic function tests

Czech Republic Perusicova et al, 1993b, 65 Register 1,443 >18 N/A N/A

Finland Partanen et al, 199593 Clinic 132 45-65 0 ± 0 Clinical score, electrophysiology


France EuroDiab, 1996c, 14 Clinic (secondary care) 104 15-60 16 ± 10 Clinical score, quantitative sensory testing, autonomic function tests

Detournay et al, 200094 Clinic (primary and secondary care) 4,119 mean=66 9 ± N/A Medical record review

Delcourt et al, 199825 Clinic (secondary care) 427 35-74 11 ± 7 Clinical score, quantitative sensory testing

Germany EuroDiab, 1996c,d, 14 Clinic (secondary care) 229 15-60 15 ± 10 Clinical score, quantitative sensory testing, autonomic function tests

Greece Manes et al, 200295 Population based 821 18-70 8 ± 7 Clinical score (NDS, NSS), quantitative sensory testing

EuroDiab, 1996c,d, 14 Clinic (secondary care) 216 15-60 13 ± 8 Clinical score, quantitative sensory testing, autonomic function tests

Hungary EuroDiab, 1996c, 14 Clinic (secondary care) 138 15-60 15 ± 9 Clinical score, quantitative sensory testing, autonomic function tests

Ireland, Republic of EuroDiab, 1996c, 14 Clinic (secondary care) 116 15-60 15 ± 9 Clinical score, quantitative sensory testing, autonomic function tests

Israel Norymberg et al, 199169 Clinic (secondary care) 1,019 ≥31 12 ± 9 Clinical score

Italy Veglio et al, 199396 Clinic (secondary care) 379 15-59 N/A Clinical score, autonomic function tests


Fedele et al, 199797 Clinic (secondary care) 8,757 18-70 12 ± 9 Clinical score (DNI)

Luxembourg EuroDiab, 1996c, 14 Clinic (secondary care) 107 15-60 14 ± 9 Clinical score, quantitative sensory testing, autonomic function tests

Netherlands Reenders et al, 199327 Clinic (primary care) 387 mean=68 8 ± 6 Clinical score, autonomic function tests

Verhoeven et al, 199129 Population based 137 mean=68 8 ± 7 Clinical score


Poland EuroDiab, 1996c, 14 Clinic (secondary care) 117 15-60 15 ± 10 Clinical score, quantitative sensory testing, autonomic function tests

Portugal EuroDiab, 1996c, 14 Clinic (secondary care) 130 15-60 15 ± 10 Clinical score, quantitative sensory testing, autonomic function tests

Romania EuroDiab, 1996c, 14 Clinic (secondary care) 114 15-60 13 ± 8 Clinical score, quantitative sensory testing, autonomic function tests

Spain Esmatjes et al, 199634 Clinic (primary and secondary care) 1,157 45-70 9 ± 7 Clinical score

Cabezas-Cerrato, 199898 Population based 2,644 15-74 10 ± 0 Clinical score (NDS, NSS)

Sweden Lundman et al, 199835 Clinic (primary and secondary care) 4,027 ≥18 10 ± 7 Clinical score, quantitative sensory testing

Turkey Bolukbasi, 1998b, 99 Clinic (secondary care) 297 N/A N/A Clinical score, electrophysiology

Ukraine Kravchenko et al, 199671 Clinic (secondary care) 4,123 14-75 N/A Clinical score

United Kingdom Abbott et al, 2002100 Clinic (primary and secondary care) 9,710 mean=61 9 ± 11 Clinical score (NDS)

Kumar et al, 1994101 Clinic (primary care) 811 34-96 7 ± N/A Clinical score (NDS), quantitative sensory testing


Walters et al, 1992102 Population based 1,077 30-80+ N/A Clinical score, quantitative sensory testing

Young et al, 1993103 Clinic (secondary care) 6,487 18-90 range 0-62 Clinical score (NDS, NSS)

NA

USA Orchard et al, 199075 Clinic (secondary care) 588 mean=24 16 ± N/A Clinical score

Franklin et al, 1990104 Population based 279 20-74 N/A Clinical score

Dyck et al, 199310 Population based 359 57 N/A Clinical score (NSS, NDS, NSP), quantitative sensory testing, electrophysiology, autonomic function tests

SACA

Brazil Foss et al, 1989b,c, 76 Clinic (secondary care) 546 25-84 8 ± 7 Clinical score, quantitative sensory testing

SEA

India Ramachandran et al, 200044 Clinic (secondary care) 617 10-50 median=4 Clinical score

Ramachandran et al, 199943 Clinic (secondary care) 3,010 mean=52 8 ± 6 Clinical score, quantitative sensory testing

Table 1.45Data sources: prevalence of diabetic neuropathy






AFR

South Africa Levitt et al, 199760 Clinic (primary care) 243 20-85 8 ± 8 Clinical score

Tanzania Wikblad et al, 199789 Clinic (secondary care) 153 mean=44 5 ± 6 Clinical store, quantitative sensory testing (NDS, NSS)

Zambia Rolfe, 198890 Clinic (secondary care) 600 ≥35 7 ± 6 Clinical score

EMME

Egypt Herman et al, 199862 Population based 509 ≥20 N/A Quantitative sensory testing

Saudi Arabia Akbar et al, 200091 Clinic (secondary care) 237 mean=54 11 ± 7 Clinical score (DNI)

Nielsen, 199892 Clinic (secondary care) 375 median=50 median=8 Clinical score

Sudan Elmahdi et al, 199117 Clinic (secondary care) 413 20+ N/A Clinical score

EUR

Austria Mühlhauser et al, 199218 Clinic (primary care) 395 mean=67 N/A Quantitative sensory testing


Belgium Van Acker et al, 200119 Clinic (secondary care) 1,653 21-69 range 5-27 Quantitative sensory testing


Croatia EuroDiab, 1996c, 14 Clinic (secondary care) 132 15-60 14 ± 9 Clinical score, quantitative sensory testing, autonomic function tests


Finland Partanen et al, 199593 Clinic 132 45-65 0 ± 0 Clinical score, electrophysiology


France EuroDiab, 1996c, 14 Clinic (secondary care) 104 15-60 16 ± 10 Clinical score, quantitative sensory testing, autonomic function tests

Detournay et al, 200094 Clinic (primary and secondary care) 4,119 mean=66 9 ± N/A Medical record review

Delcourt et al, 199825 Clinic (secondary care) 427 35-74 11 ± 7 Clinical score, quantitative sensory testing

Germany EuroDiab, 1996c,d, 14 Clinic (secondary care) 229 15-60 15 ± 10 Clinical score, quantitative sensory testing, autonomic function tests

Greece Manes et al, 200295 Population based 821 18-70 8 ± 7 Clinical score (NDS, NSS), quantitative sensory testing


Hungary EuroDiab, 1996c, 14 Clinic (secondary care) 138 15-60 15 ± 9 Clinical score, quantitative sensory testing, autonomic function tests

Ireland, Republic of EuroDiab, 1996c, 14 Clinic (secondary care) 116 15-60 15 ± 9 Clinical score, quantitative sensory testing, autonomic function tests

Israel Norymberg et al, 199169 Clinic (secondary care) 1,019 ≥31 12 ± 9 Clinical score

Italy Veglio et al, 199396 Clinic (secondary care) 379 15-59 N/A Clinical score, autonomic function tests


Fedele et al, 199797 Clinic (secondary care) 8,757 18-70 12 ± 9 Clinical score (DNI)

Luxembourg EuroDiab, 1996c, 14 Clinic (secondary care) 107 15-60 14 ± 9 Clinical score, quantitative sensory testing, autonomic function tests

Netherlands Reenders et al, 199327 Clinic (primary care) 387 mean=68 8 ± 6 Clinical score, autonomic function tests

Verhoeven et al, 199129 Population based 137 mean=68 8 ± 7 Clinical score


Poland EuroDiab, 1996c, 14 Clinic (secondary care) 117 15-60 15 ± 10 Clinical score, quantitative sensory testing, autonomic function tests

Portugal EuroDiab, 1996c, 14 Clinic (secondary care) 130 15-60 15 ± 10 Clinical score, quantitative sensory testing, autonomic function tests

Romania EuroDiab, 1996c, 14 Clinic (secondary care) 114 15-60 13 ± 8 Clinical score, quantitative sensory testing, autonomic function tests

Spain Esmatjes et al, 199634 Clinic (primary and secondary care) 1,157 45-70 9 ± 7 Clinical score

Cabezas-Cerrato, 199898 Population based 2,644 15-74 10 ± 0 Clinical score (NDS, NSS)

Sweden Lundman et al, 199835 Clinic (primary and secondary care) 4,027 ≥18 10 ± 7 Clinical score, quantitative sensory testing

Turkey Bolukbasi, 1998b, 99 Clinic (secondary care) 297 N/A N/A Clinical score, electrophysiology

Ukraine Kravchenko et al, 199671 Clinic (secondary care) 4,123 14-75 N/A Clinical score

United Kingdom Abbott et al, 2002100 Clinic (primary and secondary care) 9,710 mean=61 9 ± 11 Clinical score (NDS)

Kumar et al, 1994101 Clinic (primary care) 811 34-96 7 ± N/A Clinical score (NDS), quantitative sensory testing


Walters et al, 1992102 Population based 1,077 30-80+ N/A Clinical score, quantitative sensory testing

Young et al, 1993103 Clinic (secondary care) 6,487 18-90 range 0-62 Clinical score (NDS, NSS)

NA

USA Orchard et al, 199075 Clinic (secondary care) 588 mean=24 16 ± N/A Clinical score

Franklin et al, 1990104 Population based 279 20-74 N/A Clinical score

Dyck et al, 199310 Population based 359 57 N/A Clinical score (NSS, NDS, NSP), quantitative sensory testing, electrophysiology, autonomic function tests

SACA

Brazil Foss et al, 1989b,c, 76 Clinic (secondary care) 546 25-84 8 ± 7 Clinical score, quantitative sensory testing

SEA

India Ramachandran et al, 200044 Clinic (secondary care) 617 10-50 median=4 Clinical score

Ramachandran et al, 199943 Clinic (secondary care) 3,010 mean=52 8 ± 6 Clinical score, quantitative sensory testing





Mauritius Shaw et al, 19988 Population based 847 ≥25 N/A Quantitative sensory testing

Sri Lanka Weerasuriya et al, 199879 Clinic (primary care) 597 25-65 0 ± 0 Clinical score (NSS, NDS), quantitative sensory testing

Fernando, 1996105 Clinic (secondary care) 500 30-60 5 ± 6 Clinical score (NSS, NDS), quantitative sensory testing

WP

Australia Tapp et al, 2003106 Population based 398 ≥25 median=5 Clinical score (NSS, NDS), quantitative sensory testing, autonomic function tests

China, Hong Kong Ko et al, 199981 Clinic (secondary care) 150 <40 5 ± 0 Clinical score, quantitative sensory testing

China, People’s Republic of Chuang et al, 2002c, 41 Clinic (secondary care) 2,344 7-92 8 ± 6 Medical record review

Indonesia Chuang et al, 2002c, 41 Clinic (secondary care) 2,084 22-89 8 ± 6 Medical record review

Japan Kawano et al, 20019 Clinic 6,472 mean=61 10 ± 10 Clinical score

Korea, Republic of Chuang et al, 2002c, 41 Clinic (secondary care) 948 15-92 11 ± 7 Medical record review

Malaysia Chuang et al, 2002c, 41 Clinic (secondary care) 1,045 15-87 11 ± 7 Medical record review

Philippines Chuang et al, 2002c, 41 Clinic (secondary care) 2,635 7-93 9 ± 7 Medical record review

Singapore, Republic of Chuang et al, 2002c, 41 Clinic (secondary care) 1,625 4-91 10 ± 8 Medical record review

Thai et al, 199052 Population based 117 18+ N/A Clinical score

Taiwan Wang et al, 2000107 Population based 219 35-85 N/A Clinical score

Fuh, 2002a, 53 Clinic (secondary care) 4,535 N/A N/A Quantitative sensory testing

Thailand Tandhanand et al, 200156 Clinic (secondary care) 2,314 mean=59 10 ± 7 Medical record review

Vietnam Chuang et al, 2002c, 41 Clinic (secondary care) 1,179 3-89 6 ± 5 Medical record review

a. Unpublished datab. Abstract onlyc. Extra details supplied by authorsd. More than one centre used to derive prevalence figure

DM diabetes mellitusDNI diabetic neuropathy indexN/A not availableNDS neuropathy disability scoreNSP neuropathy symptom profileNSS neuropathy symptom score






Mauritius Shaw et al, 19988 Population based 847 ≥25 N/A Quantitative sensory testing

Sri Lanka Weerasuriya et al, 199879 Clinic (primary care) 597 25-65 0 ± 0 Clinical score (NSS, NDS), quantitative sensory testing

Fernando, 1996105 Clinic (secondary care) 500 30-60 5 ± 6 Clinical score (NSS, NDS), quantitative sensory testing

WP

Australia Tapp et al, 2003106 Population based 398 ≥25 median=5 Clinical score (NSS, NDS), quantitative sensory testing, autonomic function tests

China, Hong Kong Ko et al, 199981 Clinic (secondary care) 150 <40 5 ± 0 Clinical score, quantitative sensory testing



Japan Kawano et al, 20019 Clinic 6,472 mean=61 10 ± 10 Clinical score



Philippines Chuang et al, 2002c, 41 Clinic (secondary care) 2,635 7-93 9 ± 7 Medical record review


Thai et al, 199052 Population based 117 18+ N/A Clinical score

Taiwan Wang et al, 2000107 Population based 219 35-85 N/A Clinical score

Fuh, 2002a, 53 Clinic (secondary care) 4,535 N/A N/A Quantitative sensory testing








Prevalence of diabetic neuropathy (%)

Region Country Total DM UnDM Type 1 DM Type 2 DM

AFR

South Africa 27.6

Tanzania 28.1

Zambia 31.2

EMME

Egypt 21.9 13.6

Saudi Arabia 56.0

19.7

Sudan 31.5

EUR

Austria 26.0

23.3

Belgium 33.7 25.7 38.3

29.3

Croatia 57.6

Czech Republic 32.8

Finland 8.3

26.1

France 21.2

8.8

28.8

Germany 20.1

Greece 33.5

25.5

Hungary 29.0

Ireland, Republic of 24.1

Israel 23.4

Italy 28.5

26.0

32.3

Luxembourg 21.5

Netherlands 68.0

18.0

23.9

Poland 25.6

Portugal 36.9

Romania 65.8

Spain 20.0

22.7 12.9 24.1

Sweden 27.3 22.8 27.9

Turkey 26.9

Ukraine 27.9

United Kingdom 22.4

41.6

22.7

16.8 12.8 17.2

28.5 22.7 32.1

NA

USA 32.4

27.8

47.6 54.0 45.0

SACA

Brazil 50.9

Table 1.46Prevalence of diabetic neuropathy





SEA

India 3.0

27.5

Mauritius 12.7 3.6

Sri Lanka 10.0

30.6

WP

Australia 7.1 13.1

China, Hong Kong 7.3 7.6


Indonesia 55.0

Japan 41.4

Korea, Republic of 33.0

Malaysia 61.0

Philippines 42.0


15.9 (incl UnDM)

Taiwan 32.4

24.4

Thailand 27.0

Vietnam 44.0

DM diabetes mellitus Total DM previously diagnosed diabetes (both type 1 and type 2) UnDM undiagnosed diabetes

Prevalence of diabetic neuropathy (%)

Region Country Total DM UnDM Type 1 DM Type 2 DM





Table 1.47Data sources: prevalence of diabetic retinopathy


AFR

Cameroon Moukouri Dit Nyolo et al, 1995123 Clinic (secondary care) 284 10-79 range 0-20 Clinical fundoscopy

Ethiopia Seyoum et al, 2001124 Clinic (secondary care) 302 14-85 9 ± 5 Clinical fundoscopy

Nigeria Erasmus et al, 1989125 Clinic (secondary care) 377 11-60+ range 0-22 Clinical fundoscopy

South Africa Kalk et al, 199759 Clinic (secondary care) 507 mean=54 7 ± 7 Fundus photography

Rotchford et al, 200215 Clinic (secondary care) 251 21-81 4 ± N/A Clinical fundoscopy

Levitt et al, 199760 Clinic (primary care) 243 20-85 8 ± 8 Clinical fundoscopy

Zambia Rolfe et al, 1988126 Clinic (secondary care) 600 mean=49 9 ± 6 Clinical fundoscopy

Zimbabwe Bartels et al, 1999127 Clinic (secondary care) 117 N/A N/A Clinical fundoscopy

EMME

Egypt Herman et al, 199862 Population based 376 20+ N/A Fundus photography

Oman el Haddad et al, 1998128 Clinic (secondary care) 500 mean=39 9 ± 4 Clinical fundoscopy

Sudan Elmahdi et al, 199117 Clinic (secondary care) 413 20+ <5->15 Clinical fundoscopy

EUR

Austria EuroDiab, 199413 Clinic (secondary care) 122 15-60 16 ± 10 Fundus photography

Mühlhauser et al, 199218 Clinic (primary care) 375 median=67 median=6 Clinical fundoscopy or fundus photography

Belgium Van Acker et al, 200119 Clinic (secondary care) 1,653 21-69 range 5-27 Medical record review

EuroDiab, 199413 Clinic (secondary care) 123 15-60 15 ± 9 Fundus photography

Croatia EuroDiab, 199413 Clinic (secondary care) 140 15-60 14 ± 9 Fundus photography


Czech Health Statistics, 2002a, 66 Population based N/A N/A N/A N/A

Denmark Gall et al, 199120 Clinic (secondary care) 549 <76 range 0-20 Clinical fundoscopy

Finland EuroDiab, 199413 Clinic (secondary care) 141 15-60 15 ± 10 Fundus photography

Falck et al, 1993129 Clinic (secondary care) 194 4-17 5 ± 3 Fundus photography

France EuroDiab, 199413 Clinic (secondary care) 127 15-60 16 ± 10 Fundus photography

Detournay et al, 200095 Clinic (primary and secondary care) 4,119 mean=66 9 ± N/A Questionnaire

Delcourt et al, 199825 Clinic (secondary care) 427 35-74 11 ± 7 Fundus photography

Germany EuroDiab, 1994d, 13 Clinic (secondary care) 229 15-60 15 ± 10 Fundus photography

Hesse et al, 2001b, 130 Population based 2,801 mean=66 10 ± 8 Medical record review

Greece EuroDiab, 1994d, 13 Clinic (secondary care) 244 15-60 13 ± 8 Fundus photography

Hungary EuroDiab, 199413 Clinic (secondary care) 140 15-60 15 ± 9 Fundus photography

Ireland, Republic of EuroDiab, 199413 Clinic (secondary care) 124 15-60 15 ± 9 Fundus photography

Israel Norymberg et al, 199169 Clinic (secondary care) 1,019 31-71+ 12 ± 9 Clinical fundoscopy

Italy EuroDiab, 1994d, 13 Clinic (secondary care) 989 15-60 14 ± 9 Fundus photography

Segato et al, 1991131 Population based 1,291 mean=60 range <5->20 Clinical fundoscopy

Garancini et al, 1989132 Clinic (secondary care) 748 14-89 range <5->20 Clinical fundoscopy

Luxembourg EuroDiab, 199413 Clinic (secondary care) 116 15-60 14 ± 9 Fundus photography

Netherlands EuroDiab, 199413 Clinic (secondary care) 136 15-60 16 ± 10 Fundus photography

Reenders et al, 199327 Clinic (primary care) 360 mean=68 8 ± 6 Clinical fundoscopy

Verhoeven et al, 199129 Population based 137 mean=68 8 ± 7 Clinical fundoscopy and fundus photography

Norway Joner et al, 199270 Population based 371 8-30 10 ± 3 Fundus photography

Hapnes et al, 1996133 Population based 210 mean=66 9 ± 8 Clinical fundoscopy and fundus photography

Poland Luzniak et al, 1997b, 134 Clinic (secondary care) 1,334 N/A N/A N/A

Portugal Pinto-Figueiredo et al, 1992135 Clinic (secondary care) 1,302 <9-79 10 ± 10 Clinical fundoscopy and fundus photography


Russia Betts et al, 1999136 Clinic (secondary care) 266 <16 3 ± N/A Clinical fundoscopy

Slovakia Slovakian Diabetes Societya, 32 Clinic (secondary care) N/A N/A N/A N/A

Spain Esmatjes et al, 199634 Clinic (primary and secondary care) 1,157 45-70 9 ± 7 Clinical fundoscopy

Fernandez-Vigo et al, 1993137 Clinic (primary and secondary care) 1,179 8-93 range <5->15 Clinical fundoscopy and fundus photography

Sweden Kernell et al, 1997138 Population based 557 mean=15 5 ± N/A Fundus photography

Henricsson et al, 1996139 Population based 2,232 <75 8 ± 8 Fundus photography

Larsson et al, 1999140 Population based 285 15-50 17 ± 11 Clinical fundoscopy and fundus photography

Falkenberg et al, 1994141 Population based 117 <70 8 ± 5 Fundus photography

Ukraine Kravchenko et al, 199671 Clinic (secondary care) 4,123 14-75 N/A Clinical fundoscopy

United Kingdom Higgs et al, 199272 Population based 291 6-92 11 ± N/A Fundus photography

Sparrow et al, 1993142 Population based 101 28-91 7 ± 6 Clinical fundoscopy and fundus photography


Broadbent et al, 1999143 Clinic (primary care) 357 13-92 N/A Clinical fundoscopy and fundus photography






AFR

Cameroon Moukouri Dit Nyolo et al, 1995123 Clinic (secondary care) 284 10-79 range 0-20 Clinical fundoscopy

Ethiopia Seyoum et al, 2001124 Clinic (secondary care) 302 14-85 9 ± 5 Clinical fundoscopy

Nigeria Erasmus et al, 1989125 Clinic (secondary care) 377 11-60+ range 0-22 Clinical fundoscopy

South Africa Kalk et al, 199759 Clinic (secondary care) 507 mean=54 7 ± 7 Fundus photography

Rotchford et al, 200215 Clinic (secondary care) 251 21-81 4 ± N/A Clinical fundoscopy

Levitt et al, 199760 Clinic (primary care) 243 20-85 8 ± 8 Clinical fundoscopy

Zambia Rolfe et al, 1988126 Clinic (secondary care) 600 mean=49 9 ± 6 Clinical fundoscopy

Zimbabwe Bartels et al, 1999127 Clinic (secondary care) 117 N/A N/A Clinical fundoscopy

EMME

Egypt Herman et al, 199862 Population based 376 20+ N/A Fundus photography

Oman el Haddad et al, 1998128 Clinic (secondary care) 500 mean=39 9 ± 4 Clinical fundoscopy

Sudan Elmahdi et al, 199117 Clinic (secondary care) 413 20+ <5->15 Clinical fundoscopy

EUR

Austria EuroDiab, 199413 Clinic (secondary care) 122 15-60 16 ± 10 Fundus photography

Mühlhauser et al, 199218 Clinic (primary care) 375 median=67 median=6 Clinical fundoscopy or fundus photography

Belgium Van Acker et al, 200119 Clinic (secondary care) 1,653 21-69 range 5-27 Medical record review


Croatia EuroDiab, 199413 Clinic (secondary care) 140 15-60 14 ± 9 Fundus photography


Czech Health Statistics, 2002a, 66 Population based N/A N/A N/A N/A

Denmark Gall et al, 199120 Clinic (secondary care) 549 <76 range 0-20 Clinical fundoscopy

Finland EuroDiab, 199413 Clinic (secondary care) 141 15-60 15 ± 10 Fundus photography

Falck et al, 1993129 Clinic (secondary care) 194 4-17 5 ± 3 Fundus photography

France EuroDiab, 199413 Clinic (secondary care) 127 15-60 16 ± 10 Fundus photography

Detournay et al, 200095 Clinic (primary and secondary care) 4,119 mean=66 9 ± N/A Questionnaire

Delcourt et al, 199825 Clinic (secondary care) 427 35-74 11 ± 7 Fundus photography

Germany EuroDiab, 1994d, 13 Clinic (secondary care) 229 15-60 15 ± 10 Fundus photography

Hesse et al, 2001b, 130 Population based 2,801 mean=66 10 ± 8 Medical record review

Greece EuroDiab, 1994d, 13 Clinic (secondary care) 244 15-60 13 ± 8 Fundus photography

Hungary EuroDiab, 199413 Clinic (secondary care) 140 15-60 15 ± 9 Fundus photography

Ireland, Republic of EuroDiab, 199413 Clinic (secondary care) 124 15-60 15 ± 9 Fundus photography

Israel Norymberg et al, 199169 Clinic (secondary care) 1,019 31-71+ 12 ± 9 Clinical fundoscopy

Italy EuroDiab, 1994d, 13 Clinic (secondary care) 989 15-60 14 ± 9 Fundus photography

Segato et al, 1991131 Population based 1,291 mean=60 range <5->20 Clinical fundoscopy

Garancini et al, 1989132 Clinic (secondary care) 748 14-89 range <5->20 Clinical fundoscopy

Luxembourg EuroDiab, 199413 Clinic (secondary care) 116 15-60 14 ± 9 Fundus photography

Netherlands EuroDiab, 199413 Clinic (secondary care) 136 15-60 16 ± 10 Fundus photography

Reenders et al, 199327 Clinic (primary care) 360 mean=68 8 ± 6 Clinical fundoscopy

Verhoeven et al, 199129 Population based 137 mean=68 8 ± 7 Clinical fundoscopy and fundus photography

Norway Joner et al, 199270 Population based 371 8-30 10 ± 3 Fundus photography

Hapnes et al, 1996133 Population based 210 mean=66 9 ± 8 Clinical fundoscopy and fundus photography

Poland Luzniak et al, 1997b, 134 Clinic (secondary care) 1,334 N/A N/A N/A

Portugal Pinto-Figueiredo et al, 1992135 Clinic (secondary care) 1,302 <9-79 10 ± 10 Clinical fundoscopy and fundus photography


Russia Betts et al, 1999136 Clinic (secondary care) 266 <16 3 ± N/A Clinical fundoscopy

Slovakia Slovakian Diabetes Societya, 32 Clinic (secondary care) N/A N/A N/A N/A

Spain Esmatjes et al, 199634 Clinic (primary and secondary care) 1,157 45-70 9 ± 7 Clinical fundoscopy

Fernandez-Vigo et al, 1993137 Clinic (primary and secondary care) 1,179 8-93 range <5->15 Clinical fundoscopy and fundus photography

Sweden Kernell et al, 1997138 Population based 557 mean=15 5 ± N/A Fundus photography

Henricsson et al, 1996139 Population based 2,232 <75 8 ± 8 Fundus photography

Larsson et al, 1999140 Population based 285 15-50 17 ± 11 Clinical fundoscopy and fundus photography

Falkenberg et al, 1994141 Population based 117 <70 8 ± 5 Fundus photography

Ukraine Kravchenko et al, 199671 Clinic (secondary care) 4,123 14-75 N/A Clinical fundoscopy

United Kingdom Higgs et al, 199272 Population based 291 6-92 11 ± N/A Fundus photography

Sparrow et al, 1993142 Population based 101 28-91 7 ± 6 Clinical fundoscopy and fundus photography


Broadbent et al, 1999143 Clinic (primary care) 357 13-92 N/A Clinical fundoscopy and fundus photography






NA

Barbados Leske et al, 1999144 Population based 636 40-84 median=5 Clinical fundoscopy and fundus photography

Mexico Gonzalez Villalpando et al, 1994145 Population based 210 35-65 8 ± 7 Fundus photography

USA Dyck et al, 199310 Population based 380 mean=57 range 0-64 Fundus photography

Klein et al, 1992146 Population based 435 43-84 range 0-20+ Fundus photography

USA (Mexican Americans) Harris et al, 1998147 Population based 308 40+ range 0-15+ Fundus photography

USA (Non-Hispanic Blacks) Harris et al, 1998147 Population based 261 40+ range 0-15+ Fundus photography

USA (Non-Hispanic Whites) Harris et al, 1998147 Population based 345 40+ range 0-15+ Fundus photography

SACA

Brazil Foss et al, 1989b, 76 Clinic (secondary care) 546 25-84 8 ± 7 Clinical fundoscopy

SEA

Bangladesh Chuang et al, 2002c, 41 Clinic (secondary care) 1,608 10-91 8 ± 6 Medical record review

India Ramachandran et al, 200044 Clinic (secondary care) 617 10-50 median=4 Clinical fundoscopy

Rema et al, 1996148 Clinic (secondary care) 6792 mean=55 9 ± 6 Clinical fundoscopy

Ramachandran et al, 199943 Clinic (secondary care) 3010 mean=52 8 ± 6 Clinical fundoscopy

Dandona et al, 1999149 Population based 119 31-86 range 0-20+ Clinical fundoscopy

Mauritius Dowse et al, 199878 Population based 746 ≥25 6 ± N/A Fundus photography

Sri Lanka Fernando et al, 1993150 Clinic (secondary care) 1,003 mean=52 7 ± 4 Clinical fundoscopy

Weerasuriya et al, 199879 Clinic (primary care) 597 25-65 0 ± 0 Clinical fundoscopy

WP

Australia Tapp et al, 2003151 Population based 703 ≥25 median=5 Fundus photography

Fairchild et al, 1994152 Clinic (secondary care) 255 median=15 2 ± 18 Fundus photography

McKay et al, 2000153 Population based 234 40+ 9.1 ± N/A Fundus photography

China, Hong Kong Ko et al, 199981 Clinic (secondary care) 150 <40 5 ± 0 Clinical fundoscopy

Wang et al, 1998154 Clinic (secondary care) 465 mean=54 N/A Clinical fundoscopy


Hu et al, 1991155 Clinic (primary care) 423 35-74 0 ± 0 Clinical fundoscopy

Chi et al, 200147 Clinic (secondary care) 447 35-54 range <7-14 Clinical fundoscopy

Fiji Brooks et al, 1999156 Population based 403 mean=56 8 ± N/A Clinical fundoscopy


Japan Kawano et al, 20018 Clinic 6,472 mean=61 10 ± 10 Doctor report

Kuzuya et al, 199449 Clinic (secondary care) 2,120 <24->75 11 ± N/A Doctor report


Lee et al, 199550 Clinic (secondary care) 631 30-75 8 ± 7 Clinical fundoscopy


Shriwas et al, 199684 Clinic (secondary care) 140 0-80+ range <5->20 Clinical fundoscopy

New Zealand Florkowski et al, 2001157 Population based 286 mean=30 10 ± 6 Clinical fundoscopy

Phillipines Chuang et al, 2002c, 41 Clinic (secondary care) 2,398 7-93 9 ± 7 Medical record review

Samoa Collins et al, 199588 Population based 166 25-74 4 ± N/A Fundus photography


Lau et al, 1995158 Clinic (primary care) 13,296 <30->70 N/A Fundus photography

Taiwan Fuh, 2002a, 53 Clinic (secondary care) 4,535 N/A N/A N/A

Chen et al, 1992159 Population based 527 40+ <4->10 Clinical fundoscopy


Thai Multicenter Group, 199455 Clinic (secondary care) 2,060 24-88 8 ± 7 Clinical fundoscopy


a. Unpublished datab. Abstract onlyc. Extra details supplied by authorsd. More than one centre used to derive prevalence figure

DM diabetes mellitusN/A not available






NA

Barbados Leske et al, 1999144 Population based 636 40-84 median=5 Clinical fundoscopy and fundus photography

Mexico Gonzalez Villalpando et al, 1994145 Population based 210 35-65 8 ± 7 Fundus photography

USA Dyck et al, 199310 Population based 380 mean=57 range 0-64 Fundus photography

Klein et al, 1992146 Population based 435 43-84 range 0-20+ Fundus photography

USA (Mexican Americans) Harris et al, 1998147 Population based 308 40+ range 0-15+ Fundus photography

USA (Non-Hispanic Blacks) Harris et al, 1998147 Population based 261 40+ range 0-15+ Fundus photography

USA (Non-Hispanic Whites) Harris et al, 1998147 Population based 345 40+ range 0-15+ Fundus photography

SACA

Brazil Foss et al, 1989b, 76 Clinic (secondary care) 546 25-84 8 ± 7 Clinical fundoscopy

SEA

Bangladesh Chuang et al, 2002c, 41 Clinic (secondary care) 1,608 10-91 8 ± 6 Medical record review

India Ramachandran et al, 200044 Clinic (secondary care) 617 10-50 median=4 Clinical fundoscopy

Rema et al, 1996148 Clinic (secondary care) 6792 mean=55 9 ± 6 Clinical fundoscopy

Ramachandran et al, 199943 Clinic (secondary care) 3010 mean=52 8 ± 6 Clinical fundoscopy

Dandona et al, 1999149 Population based 119 31-86 range 0-20+ Clinical fundoscopy

Mauritius Dowse et al, 199878 Population based 746 ≥25 6 ± N/A Fundus photography

Sri Lanka Fernando et al, 1993150 Clinic (secondary care) 1,003 mean=52 7 ± 4 Clinical fundoscopy

Weerasuriya et al, 199879 Clinic (primary care) 597 25-65 0 ± 0 Clinical fundoscopy

WP

Australia Tapp et al, 2003151 Population based 703 ≥25 median=5 Fundus photography

Fairchild et al, 1994152 Clinic (secondary care) 255 median=15 2 ± 18 Fundus photography

McKay et al, 2000153 Population based 234 40+ 9.1 ± N/A Fundus photography

China, Hong Kong Ko et al, 199981 Clinic (secondary care) 150 <40 5 ± 0 Clinical fundoscopy

Wang et al, 1998154 Clinic (secondary care) 465 mean=54 N/A Clinical fundoscopy


Hu et al, 1991155 Clinic (primary care) 423 35-74 0 ± 0 Clinical fundoscopy

Chi et al, 200147 Clinic (secondary care) 447 35-54 range <7-14 Clinical fundoscopy

Fiji Brooks et al, 1999156 Population based 403 mean=56 8 ± N/A Clinical fundoscopy


Japan Kawano et al, 20018 Clinic 6,472 mean=61 10 ± 10 Doctor report

Kuzuya et al, 199449 Clinic (secondary care) 2,120 <24->75 11 ± N/A Doctor report


Lee et al, 199550 Clinic (secondary care) 631 30-75 8 ± 7 Clinical fundoscopy


Shriwas et al, 199684 Clinic (secondary care) 140 0-80+ range <5->20 Clinical fundoscopy

New Zealand Florkowski et al, 2001157 Population based 286 mean=30 10 ± 6 Clinical fundoscopy

Phillipines Chuang et al, 2002c, 41 Clinic (secondary care) 2,398 7-93 9 ± 7 Medical record review

Samoa Collins et al, 199588 Population based 166 25-74 4 ± N/A Fundus photography


Lau et al, 1995158 Clinic (primary care) 13,296 <30->70 N/A Fundus photography

Taiwan Fuh, 2002a, 53 Clinic (secondary care) 4,535 N/A N/A N/A

Chen et al, 1992159 Population based 527 40+ <4->10 Clinical fundoscopy


Thai Multicenter Group, 199455 Clinic (secondary care) 2,060 24-88 8 ± 7 Clinical fundoscopy






Table 1.48Prevalence of diabetic retinopathy

Prevalence of diabetic retinopathy (%)

Region Country

Total retinopathyProliferative retinopathy

Total DM UnDM Type 1 DM Type 2 DM Total DM

AFR

Cameroon 37.3

Ethiopia 37.8 34.1 41.0 1.7

Nigeria 15.1 0.0

South Africa 39.3

40.3 5.6

55.4 4.3

Zambia 34.0 4.0

Zimbabwe 35.9

EMME

Egypt 41.5 15.7

Oman 42.4 12.8

Sudan 17.4

EUR

Austria 23.0

23.3

Belgium 38.5 43.6 35.0

47.0

Croatia 59.0

Czech Republic 42.2

11.3 2.4

Denmark 35.3 4.2

Finland 54.0

10.8

France 35.0

10.6

33.5 1.4

Germany 21.0

16.1

Greece 46.7

Hungary 51.0

Ireland, Republic of 53.0

Israel 28.0

Italy 40.8

26.2 46.2 24.6 1.8

37.3 7.6

Luxembourg 30.0

Netherlands 47.0

13.5

35.0 4.0

Norway 32.8 0.0

13.8 34.4 10.1 2.4

Poland 31.4

Portugal 41.6 7.3

60.0

Russian Federation 12.0 1.1

Slovakia 17.4

Spain 29.0

44.7 5.8

Sweden 14.5 2.3

43.6 64.0 36.0 6.7

75.1 21.8

26.5 3.4

Ukraine 22.4





Prevalence of diabetic retinopathy (%)

Region Country

Total retinopathyProliferative retinopathy

Total DM UnDM Type 1 DM Type 2 DM Total DM


52.0 4.0

51.0

33.6 36.7 36.2 1.1

NA

Barbados 28.5 0.9

Mexico 49.5 5.7

USA 62.1 79.0 55.0 8.9

(incl UnDM) 36.8 10.2 68.4 1.8

USA (Mexican Americans) 33.4 5.6

USA (Non-Hispanic Blacks) 26.5 1.8

USA (Non-Hispanic Whites) 18.2 0.9

SACA

Brazil 29.1

SEA

Bangladesh 11.0

India 13.4 1.9

34.1 3.4

23.7 3.7

23.5 0.8

Mauritius (incl UnDM) 30.2 14.8 44.3 1.3

Sri Lanka 31.3 5.9

15.2

WP

Australia 24.5 6.2 21.9 2.1

42.0 0.0

29.1 4.2

China, Hong Kong 14.0 11.4

21.9


31.0 2.8

47.4

Fiji 52.6

Indonesia 17.0

Japan 34.5

38.3 56.0 35.9 10.3

Korea, Republic of 33.0

35.2 8.2

Malaysia 37.0

48.6 47.3 3.6

New Zealand 37.4

Phillipines 18.0

Samoa 15.4 43.2 4.5


21.8 0.6

Taiwan 25.1

35.0 2.2

Thailand 21.0

32.1 6.6

Vietnam 13.0

DM diabetes mellitus Total DM previously diagnosed diabetes (both type 1 and type 2) UnDM undiagnosed diabetes





Region Country Data used Study type Sample size Age sample No. of amputees Lowest level of amputation

AFR

South Africa Levitt et al, 199760 Clinic (primary care) 243 20-85 3 N/A

EMME

Saudi Arabia Nielsen, 199892 Clinic (secondary care) 375 N/A 5 N/A

EUR

Austria Mühlhauser et al, 199218 Clinic (primary care) 375 N/A 13 below ankle

Belgium Van Acker et al, 200119 Clinic (secondary care) 1,653 21-69 69 toe

Czech Republic Czech Health Statistics, 2002a, 66 Population based N/A N/A N/A

Denmark Ebskov et al, 1996108 Register 25-97 2,848 ray

Holstein et al, 2000109 Clinical records N/A 463 ankle

Finland Siitonen et al, 1993110 Operating theatre records all 254 toe

Germany Trautner et al, 2001111 Operating theatre records all 39 toe

Netherlands Reenders et al, 199327 Clinic (primary care) 387 mean=68 5 N/A

van Houtum et al, 1996112 Hospital discharge records all 1,575 toe

Norway Witso et al, 2001113 Hospital records all 74 toe

Poland Nazim, 2001b, 114 Hospital records and limb fitting centre N/A 139 toe

Slovakia Slovakian Diabetes Societya, 32 Clinic (secondary care) N/A N/A N/A

Spain Calle-Pascual et al, 19975 Operating theatre records, hospital discharge records, medical records all 48 toe

Almaraz et al, 2000b, 115 Hospital records N/A 316 N/A

Sweden Lundman et al, 199835 Clinic (primary and secondary care) 4,027 >18 73 toe

Larsson et al, 1995116 Amputation register all 21 toe

United Kingdom Abbott et al, 2002100 Clinic (primary and secondary care) 9,710 mean=62 122 toe

Deerochanawong et al, 1992117 Operation records and hospital discharge records N/A 93 toe

Morris et al, 1998118 Hospital discharge records and database of rehabilitation service 7,079 all 52 toe

NA

Canada Lawee et al, 1992119 Hospital discharge records all 926 toe

Trinidad and Tobago Gulliford et al, 2002120 Clinic (secondary care) 2,106 all 84 toe

USA Humphrey et al, 199412 Hospital discharge codes 2,015 N/A 57 toe

SACA

Brazil Spichler et al, 2001121 Register N/A N/A N/A

SEA

India Ramachandran et al, 199943 Clinic (secondary care) 3,010 mean=52 21 N/A

Mauritius Shaw et al, 19988 Population based 847 mean=54 2

Sri Lanka Fernando, 1996105 Clinic (secondary care) 500 30-60 24 N/A

WP

China, People’s Republic of Chi et al, 200147 Clinic (secondary care) 447 35-54 3 toe

Japan Kuzuya et al, 199449 Clinic (secondary care) 2,115 <24-75+ 13 N/A

Nauru Humphrey et al, 1996122 Operating theatre records, welfare office and health survey data 375 25+ 46 toe

Taiwan Wang et al, 2000107 Population based 219 35-85 3 N/A

Thailand Tandhanand et al, 200156 Clinic (secondary care) 2,378 N/A N/A N/A

Thai Multicenter Group, 199455 Clinic (secondary care) 2,060 24-88 27 toe

Table 1.49Data sources: prevalence and incidence of lower limb amputations

a. Unpublished datab. Abstract onlyc. Extra details supplied by authors

N/A not available





Region Country Data used Study type Sample size Age sample No. of amputees Lowest level of amputation

AFR

South Africa Levitt et al, 199760 Clinic (primary care) 243 20-85 3 N/A

EMME

Saudi Arabia Nielsen, 199892 Clinic (secondary care) 375 N/A 5 N/A

EUR

Austria Mühlhauser et al, 199218 Clinic (primary care) 375 N/A 13 below ankle

Belgium Van Acker et al, 200119 Clinic (secondary care) 1,653 21-69 69 toe

Czech Republic Czech Health Statistics, 2002a, 66 Population based N/A N/A N/A

Denmark Ebskov et al, 1996108 Register 25-97 2,848 ray

Holstein et al, 2000109 Clinical records N/A 463 ankle

Finland Siitonen et al, 1993110 Operating theatre records all 254 toe

Germany Trautner et al, 2001111 Operating theatre records all 39 toe

Netherlands Reenders et al, 199327 Clinic (primary care) 387 mean=68 5 N/A

van Houtum et al, 1996112 Hospital discharge records all 1,575 toe

Norway Witso et al, 2001113 Hospital records all 74 toe

Poland Nazim, 2001b, 114 Hospital records and limb fitting centre N/A 139 toe

Slovakia Slovakian Diabetes Societya, 32 Clinic (secondary care) N/A N/A N/A

Spain Calle-Pascual et al, 19975 Operating theatre records, hospital discharge records, medical records all 48 toe

Almaraz et al, 2000b, 115 Hospital records N/A 316 N/A

Sweden Lundman et al, 199835 Clinic (primary and secondary care) 4,027 >18 73 toe

Larsson et al, 1995116 Amputation register all 21 toe

United Kingdom Abbott et al, 2002100 Clinic (primary and secondary care) 9,710 mean=62 122 toe

Deerochanawong et al, 1992117 Operation records and hospital discharge records N/A 93 toe

Morris et al, 1998118 Hospital discharge records and database of rehabilitation service 7,079 all 52 toe

NA

Canada Lawee et al, 1992119 Hospital discharge records all 926 toe

Trinidad and Tobago Gulliford et al, 2002120 Clinic (secondary care) 2,106 all 84 toe

USA Humphrey et al, 199412 Hospital discharge codes 2,015 N/A 57 toe

SACA

Brazil Spichler et al, 2001121 Register N/A N/A N/A

SEA

India Ramachandran et al, 199943 Clinic (secondary care) 3,010 mean=52 21 N/A

Mauritius Shaw et al, 19988 Population based 847 mean=54 2

Sri Lanka Fernando, 1996105 Clinic (secondary care) 500 30-60 24 N/A

WP

China, People’s Republic of Chi et al, 200147 Clinic (secondary care) 447 35-54 3 toe

Japan Kuzuya et al, 199449 Clinic (secondary care) 2,115 <24-75+ 13 N/A

Nauru Humphrey et al, 1996122 Operating theatre records, welfare office and health survey data 375 25+ 46 toe

Taiwan Wang et al, 2000107 Population based 219 35-85 3 N/A

Thailand Tandhanand et al, 200156 Clinic (secondary care) 2,378 N/A N/A N/A

Thai Multicenter Group, 199455 Clinic (secondary care) 2,060 24-88 27 toe





Region CountryPrevalence

(%)Incidence per 100,000

diabetic population

AFR

South Africa 1.4

EMME

Saudi Arabia (below ankle only) 1.3

EUR

Austria 3.5

Belgium 4.2

Czech Republic 0.9

Denmark 156a

430b

Finland 480a

Germany 463a

Netherlands (type 2 DM) 1.5

251b

(age adjusted)

Norway 440a

Poland 165b

Slovakia 1.3

Spain 46.1a

136b

Sweden 1.8

410a

United Kingdom 1.3

570b

367a

NA

Canada 400b

Trinidad and Tobago 4.0

USA 271a

SACA

Brazil 181b

SEA

India (type 2 DM) 0.7

Mauritius (incl UnDM) 0.2

Sri Lanka (type 2 DM) 4.8

WP


Japan 0.6

Nauru 810a

Taiwan (incl UnDM) 1.4

Thailand 1.0

1.3

Table 1.50Prevalence and incidence of lower limb amputations

a. First amputationb. All amputations or not stated DM diabetes mellitusTotal DM previously diagnosed diabetes (both type 1 and type 2)UnDM undiagnosed diabetes





References

1. American Diabetes Association: Economic consequences of diabetes mellitus in the U.S. in 1997. Diabetes Care 1998; 21:296-309.

2. Haffner SM, Lehto S, Ronnemaa T, Pyorala K, Laakso M. Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction. N Engl J Med 1998; 339:229-234.

3. United States Renal Data System: Annual Data Report. In http://www.usrds.org/adr.htm, accessed 2002.

4. Disney A. Australia and New Zealand transplant registry, 2002. http://www.anzdata.org.au, accessed Sept 2002.

5. Rahmani B, Tielsch JM, Katz J, Gottsch J, Quigley H, Javitt J, Sommer A. The cause-specific prevalence of visual impairment in an urban population. The Baltimore Eye Survey. Ophthalmology 1996; 03:1721-1726.

6. Davis TM, Stratton IM, Fox CJ, Holman RR, Turner RC. U.K. Prospective Diabetes Study 22. Effect of age at diagnosis on diabetic tissue damage during the first6 years of NIDDM. Diabetes Care 1997; 20:1435-1441.

7. Calle-Pascual AL, Redondo MJ, Ballesteros M, Martinez-Salinas MA, Diaz JA, De Matias P, Calle JR, Gil E, Jimenez M, Serrano FJ, Martin-Alvarez PJ, Maranes JP. Nontraumatic lower extremity amputations in diabetic and non-diabetic subjects in Madrid, Spain. Diabetes Metab 1997;23:519-523.

8. Shaw J, Hodge A, de Courten M, Dowse G, Gareeboo H, Tuomilehto J, Alberti K, Zimmet P. Diabetic neuropathy in Mauritius: prevalence and risk factors. Diabetes Res Clin Pract 1998; 42:131-139.

9. Kawano M, Omori Y, Katayama S, Kawakami M, Suzuki Y, Takahashi K, Takemura Y, Nagata N, Hiratsuka A, Matsuzaki F, Kanazawa Y, Akanuma Y. A questionnaire for neurological symptoms in patients with diabetes – cross-sectional multicenter study in Saitama Prefecture, Japan. Diabetes Res Clin Pract – Suppl 2001; 54:41-47.

10. Dyck PJ, Kratz KM, Karnes JL, Litchy WJ, Klein R, Pach JM, Wilson DM, O’Brien PC, Melton LJ, 3rd, Service FJ. The prevalence by staged severity of various types of diabetic neuropathy, retinopathy, and nephropathy in a population-based cohort: the Rochester Diabetic Neuropathy Study. Neurology 1993; 43:817-824.

11. The Diabetes Control and Complications Trial. The effect of intensive diabetes therapy on the development and progression of neuropathy. Ann Intern Med 1995;122:561-568.

12. Humphrey LL, Palumbo PJ, Butters MA, Hallett JW, Jr, Chu CP, O’Fallon WM, Ballard DJ. The contribution of non-insulin-dependent diabetes to lower-extremity amputation in the community. Archives of Internal Medicine 1994;54:885-892.

13. The EURODIAB IDDM Complications Study. Microvascular and acute complications in IDDM patients. Diabetologia 1994; 37:278-285.

14. Tesfaye S, Stevens LK, Stephenson JM, Fuller JH, Plater M, Ionescu-Tirgoviste C, Nuber A, Pozza G, Ward JD. Prevalence of diabetic peripheral neuropathy and its relation to glycaemic control and potential risk factors: the EURODIAB IDDM Complications Study. Diabetologia 1996;39:1377-1384.

15. Rotchford AP, Rotchford KM. Diabetes in rural South Africa-an assessment of care and complications. S Afr Med J 2002; 92(7):536-541.

16. Hashim R, Khan FA, Khan DA, Shaukat A. Prevalence of macrovascular complications in diabetics of WAH, District Rawalpindi. J Pak Med Assoc 1999; 49(1):8-11.

17. Elmahdi EM, Kaballo AM, Mukhtar EA. Features of non-insulin-dependent diabetes mellitus (NIDDM) in the Sudan. Diabetes Res Clin Pract 1991; 11(1):59-63.

18. Mühlhauser I, Sulzer M, Berger M. Quality assessment of diabetes care according to the recommendations of the St. Vincent Declaration: a population-based study in a rural area of Austria. Diabetologia 1992; 35(5):429-435.

19. Van Acker K, Weyler J, De Leeuw I. The Diabetic Foot Project of Flanders, the northern part of Belgium: implementation of the St Vincent consensus. Sensibilisation and registration in diabetes centres. Acta Clin Belg 2001; 56(1):21-31.

20. Gall MA, Rossing P, Skott P, Damsbo P, Vaag A, Bech K, et al. Prevalence of micro- and macroalbuminuria, arterial hypertension, retinopathy and large vessel disease in European type 2 (non-insulin-dependent) diabetic patients. Diabetologia 1991; 34(9):655-661.

21. Vides H, Nilsson PM, Sarapuu V, Podar T, Isacsson A, Schersten BF. Diabetes and social conditions in Estonia. A population-based study. Eur J Public Health 2001;11(1):60-64.

22. Hu G. Personal communication, 2003.23. Isomaa B, Almgren P, Tuomi T, Forsen B, Lahti K, Nissen M,

et al. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 2001;24(4):683-689.

24. Le Floch JP, Thervet F, Desriac I, Boyer JF, Simon D. Management of diabetic patients by general practitioners in France 1997: an epidemiological study. Diabetes Metab 2000; 26(1):43-49.

25. Delcourt C, Vauzelle-Kervroedan F, Cathelineau G, Papoz L. Low prevalence of long-term complications in non-insulin-dependent diabetes mellitus in France: a multicenter study. CODIAB-INSERM-ZENECA Pharma Study Group. J Diabetes Complications 1998; 12(2):88-95.

26. Liebl A, Neiss A, Spannheimer A, Reitberger U, Wieseler B, Stammer H, et al. Complications, co-morbidity, and blood glucose control in type 2 diabetes mellitus patients in Germany – results from the CODE-2 study. Exp Clin Endocrinol Diabetes 2002; 110(1):10-16.

27. Reenders K, de Nobel E, van den Hoogen HJ, Rutten GE, van Weel C. Diabetes and its long-term complications in general practice: a survey in a well-defined population. Fam Pract 1993; 10(2):169-172.

28. de Visser CL, Bibo HJ, Groenier KH, de Visser W, Jong Meyboom-de B. The influence of cardiovascular disease on quality of life in type 2 diabetics. Qual Life Res 2002;11(3):249-261.

29. Verhoeven S, van Ballegooie E, Casparie AF. Impact of late complications in type 2 diabetes in a Dutch population. Diabet Med 1991; 8(5):435-438.

30. Miljus D. Personal communication, 2002.31. Vlajinac H, Ilic M, Marinkovic J. Cardiovascular risk factors

and prevalence of coronary heart disease in type 2 (non-insulin-dependent) diabetes. Eur J Epidemiol 1992;8(6):783-788.

32. Slovakian Diabetes Society. Personal communication, 2002.33. Diamante E. Renal involvement in type 1 (IDDM) diabetes in

Spain. Diabetes Res Clin Pract 1997; 38(2):129-137.34. Esmatjes E, Castell C, Gonzalez T, Tresserras R, Lloveras G.

Epidemiology of renal involvement in type II diabetics (NIDDM) in Catalonia. The Catalan Diabetic Nephropathy Study Group. Diabetes Res Clin Pract 1996;32 Suppl 3:157-163.





35. Lundman B, Engstrom L. Diabetes and its complications in a Swedish county. Diabetes Res Clin Pract 1998;39(2):157-164.

36. Morgan CL, Currie CJ, Stott NC, Smithers M, Butler CC, Peters JR. The prevalence of multiple diabetes-related complications. Diabet Med 2000; 17(2):146-151.

37. Maser RE, Wolfson SK, Jr, Ellis D, Stein EA, Drash AL, Becker J, et al. Cardiovascular disease and arterial calcification in insulin-dependent diabetes mellitus: interrelations and risk factor profiles. Pittsburgh Epidemiology of Diabetes Complications Study-V. Arterioscler Thromb 1991; 11(4):958-965.

38. Alexander CM, Landsman PB, Teutsch SM. Diabetes mellitus, impaired fasting glucose, atherosclerotic risk factors, and prevalence of coronary heart disease. Am J Cardiol 2000; 86(9):897-902.

39. Qureshi AI, Giles WH, Croft JB. Impaired glucose tolerance and the likelihood of nonfatal stroke and myocardial infarction: the Third National Health and Nutrition Examination Survey. Stroke 1998; 29(7):1329-1332.

40. Barzilay JI, Spiekerman CF, Kuller LH, Burke GL, Bittner V, Gottdiener JS, et al. Prevalence of clinical and isolated subclinical cardiovascular disease in older adults with glucose disorders: the Cardiovascular Health Study. Diabetes Care 2001; 24(7):1233-1239.

41. Chuang LM, Tsai ST, Huang BY, Tai TY. The status of diabetes control in Asia – a cross-sectional survey of 24 317 patients with diabetes mellitus in 1998. Diabet Med 2002;19(12):978-985.

42. Sayeed MA, Banu A, Malek MA, Khan AK. Blood pressure and coronary heart disease in NIDDM subjects at diagnosis: prevalence and risks in a Bangladeshi population. Diabetes Res Clin Pract 1998; 39(2):147-155.

43. Ramachandran A, Snehalatha C, Satyavani K, Latha E, Sasikala R, Vijay V. Prevalence of vascular complications and their risk factors in type 2 diabetes. J Assoc Physicians India 1999; 47(12):1152-1156.

44. Ramachandran A, Snehalatha C, Sasikala R, Satyavani K, Vijay V. Vascular complications in young Asian Indian patients with type 1 diabetes mellitus. Diabetes Res Clin Pract 2000; 48(1):51-56.

45. Collins VR, Dowse GK, Zimmet PZ, Tuomilehto J, Alberti KG, Gareeboo H, et al. Serum insulin and ECG abnormalities suggesting coronary heart disease in the populations of Mauritius and Nauru: cross-sectional and longitudinal associations. J Clin Epidemiol 1993; 46(12):1373-1393.

46. Fernando DJ, Siribaddana S, Perera N, Perera S, de Silva D. The prevalence of macrovascular disease and lipid abnormalities amongst diabetic patients in Sri Lanka. Postgrad Med J 1993; 69(813):557-561.

47. Chi ZS, Lee ET, Lu M, Keen H, Bennett PH. Vascular disease prevalence in diabetic patients in China: standardised comparison with the 14 centres in the WHO Multinational Study of Vascular Disease in Diabetes. Diabetologia 2001; 44 Suppl 2:S82-86.

48. Tuomilehto J, Zimmet P, Kankaanpaa J, Wolf E, Hunt D, King H, et al. Prevalence of ischaemic ECG abnormalities according to the diabetes status in the population of Fiji and their associations with other risk factors. Diabetes Res Clin Pract 1988; 5(3):205-217.

49. Kuzuya T, Akanuma Y, Akazawa Y, Uehata T. Prevalence of chronic complications in Japanese diabetic patients. Diabetes Res Clin Pract 1994; 24 Suppl:S159-164.

50. Lee KU, Park JY, Kim SW, Lee MH, Kim GS, Park SK, et al. Prevalence and associated features of albuminuria in Koreans with NIDDM. Diabetes Care 1995; 18(6):793-799.

51. Simmons D, Gatland BA, Leakehe L, Fleming C. Ethnic differences in diabetes care in a multiethnic community in

New Zealand. Diabetes Res Clin Pract 1996;34 Suppl:S89-93.

52. Thai AC, Yeo PP, Lun KC, Hughes K, Ng WY, Lui KF, et al. Diabetes mellitus and its chronic complications in Singapore: an increasing healthcare problem. Ann Acad Med Singapore 1990; 19(4):517-523.

53. Fuh M. Personal communication, 2002.54. Tatsanavivat P, Klungboonkrong V, Chirawatkul A,

Bhuripanyo K, Manmontri A, Chitanondh H, et al. Prevalence of coronary heart disease and major cardiovascular risk factors in Thailand. Int J Epidemiol 1998; 27(3):405-409.

55. Thai Multicenter Research Group on Diabetes Mellitus. Vascular complications in non-insulin dependent diabetics in Thailand. Diabetes Res Clin Pract 1994; 25(1):61-69.

56. Tandhanand S, Nitiyanant W, Chandraprasert S, Puavilai G, Jorgensen LN, Ping YJ, et al. Status of diabetes and complications in Thailand – Findings of a large observational study. Journal of the Asean Federation of Endocrine Societies 2001; 19:1-7.

57. Rahlenbeck SI, Gebre-Yohannes A. Prevalence and epidemiology of micro- and macroalbuminuria in Ethiopian diabetic patients. J Diabetes Complications 1997;11:343-349.

58. Erasmus RT, Oyeyinka G, Arije A. Microalbuminuria in non-insulin-dependent (type 2) Nigerian diabetics: relation to glycaemic control, blood pressure and retinopathy. Postgrad Med J 1992; 68:638-642.

59. Kalk WJ, Joannou J, Ntsepo S, Mahomed I, Mahanlal P, Becker PJ. Ethnic differences in the clinical and laboratory associations with retinopathy in adult onset diabetes: studies in patients of African, European and Indian origins. J Intern Med 1997; 241:31-37.

60. Levitt NS, Bradshaw D, Zwarenstein MF, Bawa AA, Maphumolo S. Audit of public sector primary diabetes care in Cape Town, South Africa: high prevalence of complications, uncontrolled hyperglycaemia, and hypertension. Diabet Med 1997; 14:1073-1077.

61. Rolfe M. Diabetic renal disease in central Africa. Diabet Med 1988; 5:630-633.

62. Herman WH, Aubert RE, Engelgau MM, Thompson TJ, Ali MA, Sous ES, Hegazy M, Badran A, Kenny SJ, Gunter EW, Malarcher AM, Brechner RJ, Wetterhall SF, DeStefano F, Smith PJ, Habib M, abd el Shakour S, Ibrahim AS, el Behairy EM. Diabetes mellitus in Egypt: glycaemic control and microvascular and neuropathic complications. Diabet Med 1998; 15:1045-1051.

63. Alzaid AA, Sobki S, De Silva V. Prevalence of microalbuminuria in Saudi Arabians with non-insulin-dependent diabetes mellitus: a clinic-based study. Diabetes Res Clin Pract 1994; 26:115-120.

64. Bouten A, Engelen W, De Leeuw I. Epidemiology of microalbuminuria in type 1 diabetic patients (IDDM) in the Antwerp University Hospital. Acta Clin Belg 1996;51:231-236.

65. Perusicova J, Neuwirt K. [The Prague Diabetes Registry.3. Retinopathies, nephropathies and neuropathies in type 1 diabetics. The Prague Diabetes Collective]. Cas Lek Cesk 1993; 132:489-493.

66. Czech Health Statistics. Personal communication, 2002.67. Mortensen HB, Marinelli K, Norgaard K, Main K, Kastrup KW,

Ibsen KK, Villumsen J, Parving HH. A nation-wide cross-sectional study of urinary albumin excretion rate, arterial blood pressure and blood glucose control in Danish children with type 1 diabetes mellitus. Danish Study Group of Diabetes in Childhood. Diabet Med 1990; 7:887-897.

68. Bennett PH, Lee ET, Lu M, Keen H, Fuller JH. Increased urinary albumin excretion and its associations in the





WHO Multinational Study of Vascular Disease in Diabetes. Diabetologia 2001;44 Suppl 2:S37-45.

69. Norymberg C, Shenkman L. Prevalence of overt diabetic nephropathy in patients with noninsulin-dependent diabetes mellitus. Isr J Med Sci 1991; 27:124-130.

70. Joner G, Brinchmann-Hansen O, Torres CG, Hanssen KF. A nationwide cross-sectional study of retinopathy and microalbuminuria in young Norwegian type 1 (insulin-dependent) diabetic patients. Diabetologia 1992;35:1049-1054.

71. Kravchenko VI, Tronko ND, Pankiv VI, Venzilovich Yu M, Prudius FG. Prevalence of diabetes mellitus and its complications in the Ukraine. Diabetes Res Clin Pract 1996; 34:S73-78.

72. Higgs ER, Kelleher A, Simpson HC, Reckless JP. Screening programme for microvascular complications and hypertension in a community diabetic population. Diabet Med 1992; 9:550-556.

73. Harvey JN, Rizvi K, Craney L, Messenger J, Shah R, Meadows PA. Population-based survey and analysis of trends in the prevalence of diabetic nephropathy in Type 1 diabetes. Diabet Med 2001; 18:998-1002.

74. Garg AX, Kiberd BA, Clark WF, Haynes RB, Clase CM. Albuminuria and renal insufficiency prevalence guides population screening: results from the NHANES III. Kidney Int 2002; 61:2165-2175.

75. Orchard TJ, Dorman JS, Maser RE, Becker DJ, Drash AL, Ellis D, et al. Prevalence of complications in IDDM by sex and duration. Pittsburgh Epidemiology of Diabetes Complications Study II. Diabetes 1990; 39(9):1116-1124.

76. Foss MC, Paccola GM, de Souza NV, Iazigi N. [Type 2 diabetic patients in a population sample from Ribeirao Preto area (Sao Paulo)]. Rev Assoc Med Bras 1989; 35:179-183.

77. Mohan V, Meera R, Premalatha G, Deepa R, Miranda P, Rema M. Frequency of proteinuria in type 2 diabetes mellitus seen at a diabetes centre in southern India. Postgrad Med J 2000; 76:569-573.

78. Dowse GK, Humphrey AR, Collins VR, Plehwe W, Gareeboo H, Fareed D, Hemraj F, Taylor HR, Tuomilehto J, Alberti KG, Zimmet PZ. Prevalence and risk factors for diabetic retinopathy in the multiethnic population of Mauritius. Am J Epidemiol 1998; 147:448-457.

79. Weerasuriya N, Siribaddana S, Dissanayake A, Subasinghe Z, Wariyapola D, Fernando DJ. Long-term complications in newly diagnosed Sri Lankan patients with type 2 diabetes mellitus. QJM 1998; 91(6):439-443.

80. AusDiab Study Group. Personal Communication, 2002.81. Ko GT, Chan JC, Lau M, Cockram CS. Diabetic

microangiopathic complications in young Chinese diabetic patients: a clinic-based cross-sectional study. J Diabetes Complications 1999; 13:300-306.

82. Chan JC, Cheung CK, Swaminathan R, Nicholls MG, Cockram CS. Obesity, albuminuria and hypertension among Hong Kong Chinese with non-insulin-dependent diabetes mellitus (NIDDM). Postgrad Med J 1993; 69:204-210.

83. The Diabcare Asia Study Group. Personal Communication, 2003.

84. Shriwas SR, Rahman Isa AB, Reddy SC, Mohammad M, Mohammad WB, Mazlan M. Risk factors for retinopathy in diabetes mellitus in Kelantan, Malaysia. Med J Malaysia 1996; 51:447-452.

85. Collins VR, Dowse GK, Finch CF, Zimmet PZ, Linnane AW. Prevalence and risk factors for micro- and macroalbuminuria in diabetic subjects and entire population of Nauru. Diabetes 1989; 38:1602-1610.

86. Simmons D, Shaw LM, Scott DJ, Kenealy T, Scragg RK. Diabetic nephropathy and microalbuminuria in the

community. The South Auckland Diabetes Survey. Diabetes Care 1994; 17:1404-1410.

87. Lantion-Ang LC. Epidemiology of diabetes mellitus in Western Pacific region: focus on Philippines. Diabetes Res Clin Pract 2000; 50 Suppl 2:S29-34.

88. Collins VR, Dowse GK, Plehwe WE, Imo TT, Toelupe PM, Taylor HR, Zimmet PZ. High prevalence of diabetic retinopathy and nephropathy in Polynesians of Western Samoa. Diabetes Care 1995; 18:1140-1149.

89. Wikblad K, Smide B, Bergstrom A, Kessi J, Mugusi F. Outcome of clinical foot examination in relation to self-perceived health and glycaemic control in a group of urban Tanzanian diabetic patients. Diabetes Res Clin Pract 1997; 37:185-192.

90. Rolfe M. The neurology of diabetes mellitus in Central Africa. Diabet Med 1988; 5:399-401.

91. Akbar DH, Mira SA, Zawawi TH, Malibary HM. Subclinical diabetic neuropathy: a common complication in Saudi diabetics. Saudi Medical Journal 2000; 21:433-437.

92. Nielsen JV. Peripheral neuropathy, hypertension, foot ulcers and amputations among Saudi Arabian patients with type 2 diabetes. Diabetes Res Clin Pract 1998; 41:63-69.

93. Partanen J, Niskanen L, Lehtinen J, Mervaala E, Siitonen O, Uusitupa M. Natural history of peripheral neuropathy in patients with non-insulin-dependent diabetes mellitus. N Engl J Med 1995; 333:89-94.

94. Detournay B, Cros S, Charbonnel B, Grimaldi A, Liard F, Cogneau J, et al. Managing type 2 diabetes in France: the ECODIA survey. Diabetes Metab 2000; 26(5):363-369.

95. Manes CH, Papazoglou N, Sossidou E, Soulis K, Milarakis A, Satsoglou A, Sakallerou A. Prevalence of diabetic neuropathy and foot ulceration: Identification of potential risk factors: A population-based study. Wounds 2002;14:11-15.

96. Veglio M, Sivieri R. Prevalence of neuropathy in IDDM patients in Piemonte, Italy. The Neuropathy Study Group of the Italian Society for the Study of Diabetes, Piemonte Affiliate. Diabetes Care 1993; 16:456-461.

97. Fedele D, Comi G, Coscelli C, Cucinotta D, Feldman EL, Ghirlanda G, Greene DA, Negrin P, Santeusanio F. A multicenter study on the prevalence of diabetic neuropathy in Italy. Italian Diabetic Neuropathy Committee. Diabetes Care 1997; 20:836-843.

98. Cabezas-Cerrato J. The prevalence of clinical diabetic polyneuropathy in Spain: a study in primary care and hospital clinic groups. Neuropathy Spanish Study Group of the Spanish Diabetes Society (SDS). Diabetologia 1998;41:1263-1269.

99. Bolukbasi O. Hospital-based diabetic neuropathy: prevalence in eastern Black Sea region of Turkey. Neuroepidemiology 1998; 17:30.

100. Abbott CA, Carrington AL, Ashe H, Bath S, Every LC, Griffiths J, Hann AW, Hussein A, Jackson N, Johnson KE, Ryder CH, Torkington R, Van Ross ER, Whalley AM, Widdows P, Williamson S, Boulton AJ. The North-West Diabetes Foot Care Study: incidence of, and risk factors for, new diabetic foot ulceration in a community-based patient cohort. Diabet Med 2002; 19:377-384.

101. Kumar S, Ashe HA, Parnell LN, Fernando DJ, Tsigos C, Young RJ, Ward JD, Boulton AJ. The prevalence of foot ulceration and its correlates in type 2 diabetic patients: a population-based study. Diabet Med 1994; 11:480-484.

102. Walters DP, Gatling W, Mullee MA, Hill RD. The prevalence of diabetic distal sensory neuropathy in an English community. Diabet Med 1992; 9:349-353.

103. Young MJ, Boulton AJ, MacLeod AF, Williams DR, Sonksen PH. A multicentre study of the prevalence of diabetic peripheral





neuropathy in the United Kingdom hospital clinic population. Diabetologia 1993; 36:150-154.

104. Franklin GM, Kahn LB, Baxter J, Marshall JA, Hamman RF. Sensory neuropathy in non-insulin-dependent diabetes mellitus. The San Luis Valley Diabetes Study. Am J Epidemiol 1990; 131:633-643.

105. Fernando DJ. The prevalence of neuropathic foot ulceration in Sri Lankan diabetic patients. Ceylon Med J 1996;41:96-98.

106. Tapp R, Shaw J, deCourten M, Dunstan D, Welborn T, Zimmet P. Foot Complications in Type 2 Diabetes: An Australian Population Based Study. Diabet Med 2003;20:105-113.

107. Wang CL, Wang M, Lin MC, Chien KL, Huang YC, Lee YT. Foot complications in people with diabetes: a community-based study in Taiwan. J Formos Med Assoc 2000; 99:5-10.

108. Ebskov B, Ebskov L. Major lower limb amputation in diabetic patients: development during 1982 to 1993. Diabetologia 1996; 39:1607-1610.

109. Holstein P, Ellitsgaard N, Olsen BB, Ellitsgaard V. Decreasing incidence of major amputations in people with diabetes. Diabetologia 2000; 43:844-847.

110. Siitonen OI, Niskanen LK, Laakso M, Siitonen JT, Pyorala K. Lower-extremity amputations in diabetic and nondiabetic patients. A population-based study in eastern Finland. Diabetes Care 1993; 16:16-20.

111. Trautner C, Haastert B, Spraul M, Giani G, Berger M. Unchanged incidence of lower-limb amputations in a German City, 1990-1998. Diabetes Care 2001; 24:855-859.

112. van Houtum WH, Lavery LA, Harkless LB. The impact of diabetes-related lower-extremity amputations in The Netherlands. J Diabetes Complications 1996; 10:325-330.

113. Witso E, Ronningen H. Lower limb amputations: registration of all lower limb amputations performed at the University Hospital of Trondheim, Norway, 1994-1997. Prosthet Orthot Int 2001; 25:181-185.

114. Nazim A. [Incidence of lower extremity amputations in diabetics]. Pol Arch Med Wewn 2001; 106:829-838.

115. Almaraz MC, Soriguer F, Zamorano D, Ruiz de Adana S, Gonzalez E, Esteva I, Garcia J, Lopez MJ. [Incidence of amputaciones of the lower extremities in the population with diabetes mellitus in Malaga (1996-1997)]. Aten Primaria 2000; 26:677-680.

116. Larsson J, Apelqvist J, Agardh CD, Stenstrom A. Decreasing incidence of major amputation in diabetic patients: a consequence of a multidisciplinary foot care team approach? Diabet Med 1995; 12:770-776.

117. Deerochanawong C, Home PD, Alberti KG. A survey of lower limb amputation in diabetic patients. Diabet Med 1992;9:942-946.

118. Morris AD, McAlpine R, Steinke D, Boyle DI, Ebrahim AR, Vasudev N, Stewart CP, Jung RT, Leese GP, MacDonald TM, Newton RW. Diabetes and lower-limb amputations in the community. A retrospective cohort study. DARTS/MEMO Collaboration. Diabetes Audit and Research in Tayside Scotland/Medicines Monitoring Unit. Diabetes Care 1998; 21:738-743.

119. Lawee D, Csima A. Diabetes-related lower extremity amputations in Ontario: 1987-88 experience. Can J Public Health 1992; 83:298-302.

120. Gulliford MC, Mahabir D. Diabetic foot disease and foot care in a Caribbean community. Diabetes Res Clin Pract 2002; 56:35-40.

121. Spichler ER, Spichler D, Lessa I, Costa e Forti A, Franco LJ, LaPorte RE. Capture-recapture method to estimate lower extremity amputation rates in Rio de Janeiro, Brazil. Rev Panam Salud Publica 2001; 10:334-340.

122. Humphrey AR, Dowse GK, Thoma K, Zimmet PZ. Diabetes and nontraumatic lower extremity amputations. Incidence, risk factors, and prevention – a 12-year follow-up study in Nauru. Diabetes Care 1996; 19:710-714.

123. Moukouri Dit Nyolo E, Noudoui C, Mbanya J. Les Aspects Cliniques De La Rétinopathie Diabétique A Yaounde. Médecine d’Afrique Noire 1995; 42:424-428.

124. Seyoum B, Mengistu Z, Berhanu P, Abdulkadir J, Feleke Y, Worku Y, Ayana G. Retinopathy in patients of Tikur Anbessa Hospital diabetic clinic. Ethiop Med J 2001; 39:123-131.

125. Erasmus RT, Alanamu RA, Bojuwoye B, Oluboyo P, Arije A. Diabetic retinopathy in Nigerians: relation to duration of diabetes, type of treatment and degree of control. East Afr Med J 1989; 66:248-254.

126. Rolfe M. Diabetic eye disease in Central Africa. Diabetologia 1988; 31:88-92.

127. Bartels MC, Macheka BM, Guramantunhu S, Scheenloop JJ, Stilma JS. Background diabetic retinopathy in Harare, Zimbabwe. Trop Doct 1999; 29:189-190.

128. el Haddad OA, Saad MK. Prevalence and risk factors for diabetic retinopathy among Omani diabetics.Br J Ophthalmol 1998; 82:901-906.

129. Falck AA, Kaar ML, Laatikainen LT. Prevalence and risk factors of retinopathy in children with diabetes. A population-based study on Finnish children. Acta Ophthalmol Scand 1993; 71:801-809.

130. Hesse L, Grusser M, Hoffstadt K, Jorgens V, Hartmann P, Kroll P. [Population-based study of diabetic retinopathy in Wolfsburg]. Ophthalmologe 2001; 98:1065-1068.

131. Segato T, Midena E, Grigoletto F, Zucchetto M, Fedele D, Piermarocchi S, Crepaldi G. The epidemiology and prevalence of diabetic retinopathy in the Veneto region of north east Italy. Veneto Group for Diabetic Retinopathy. Diabet Med 1991; 8:S11-16.

132. Garancini P, Micossi P, Valsania P, Radaelli G, Bandello F, Scialdone A, Menchini U, Brancato R, Pozza G, Gallus G. Prevalence of retinopathy in diabetic subjects from out-patient clinics in Lombardy (Italy), and associated risk factors. A multicentre epidemiologic study. Diabetes Res Clin Pract 1989; 6:129-138.

133. Hapnes R, Bergrem H. Diabetic eye complications in a medium sized municipality in southwest Norway. Acta Ophthalmol Scand 1996; 74:497-500.

134. Luzniak P, Czech A, Taton J. [Prospective studies of diabetic retinopathy in a cohort of patients with type II diabetes mellitus]. Polski Merkuriusz Lekarski 1997; 2:14-17.

135. Pinto-Figueiredo L, Moita J, Genro V, Vinagre M, Laires R, Rosa MJ, Cardoso C, Carreiras F. Diabetic retinopathy in a population of 1,302 insulin dependent diabetics (IDDM) diagnosed before 30 years of age. Int Ophthalmol 1992;16:429-437.

136. Betts PR, Logatchov M, Volkov I, Murphy H, Dombrowskaya N, Borzikh S, Ivanova I, Twyman S, Vartan J. An assessment of paediatric diabetes care in three centres in Russia and in Southampton, UK. The Paediatric Teams in Moscow, Tula, Tambov, Southampton. Diabet Med 1999;16:772-778.

137. Fernandez-Vigo J, Sanchez Macho J, Diaz Rey A, Barros J, Tome M, Bueno J. The prevalence of diabetic retinopathy in northwest Spain. An epidemiological study of diabetic retinopathy in Galicia. I. Acta Ophthalmol Scand 1993;71:22-26.

138. Kernell A, Dedorsson I, Johansson B, Wickstrom CP, Ludvigsson J, Tuvemo T, Neiderud J, Sjostrom K, Malmgren K, Kanulf P, Mellvig L, Gjotterberg M, Sule J, Persson LA, Larsson LI, Aman J, Dahlquist G. Prevalence of diabetic retinopathy in children and adolescents with IDDM.





A population-based multicentre study. Diabetologia 1997; 40:307-310.

139. Henricsson M, Nilsson A, Groop L, Heijl A, Janzon L. Prevalence of diabetic retinopathy in relation to age at onset of the diabetes, treatment, duration and glycemic control. Acta Ophthalmol Scand 1996; 74:523-527.

140. Larsson LI, Alm A, Bergenheim T, Lithner F, Bergstrom R. Retinopathy in diabetic patients aged 15-50 years in the county of Umea, Sweden. Acta Ophthalmol Scand 1999;77:430-436.

141. Falkenberg M, Finnstrom K. Associations with retinopathy in type 2 diabetes: a population-based study in a Swedish rural area. Diabet Med 1994; 11:843-849.

142. Sparrow JM, McLeod BK, Smith TD, Birch MK, Rosenthal AR. The prevalence of diabetic retinopathy and maculopathy and their risk factors in the non-insulin-treated diabetic patients of an English town. Eye 1993; 7:158-163.

143. Broadbent DM, Scott JA, Vora JP, Harding SP. Prevalence of diabetic eye disease in an inner city population: the Liverpool Diabetic Eye Study. Eye 1999; 13:160-165.

144. Leske MC, Wu SY, Hyman L, Li X, Hennis A, Connell AM, Schachat AP. Diabetic retinopathy in a black population: the Barbados Eye Study. Ophthalmology 1999; 106:1893-1899.

145. Gonzalez Villalpando ME, Gonzalez Villalpando C, Arredondo Perez B, Stern MP. Diabetic retinopathy in Mexico. Prevalence and clinical characteristics. Arch Med Res 1994; 25:355-360.

146. Klein R, Klein BE, Moss SE, Linton KL. The Beaver Dam Eye Study. Retinopathy in adults with newly discovered and previously diagnosed diabetes mellitus. Ophthalmology 1992; 99:58-62.

147. Harris MI, Klein R, Cowie CC, Rowland M, Byrd-Holt DD. Is the risk of diabetic retinopathy greater in non-Hispanic blacks and Mexican Americans than in non-Hispanic whites with type 2 diabetes? A U.S. population study. Diabetes Care 1998; 21:1230-1235.

148. Rema M, Ponnaiya M, Mohan V. Prevalence of retinopathy in non insulin dependent diabetes mellitus at a diabetes centre in southern India. Diabetes Res Clin Pract 1996;34:29-36.

149. Dandona L, Dandona R, Naduvilath TJ, McCarty CA, Rao GN. Population based assessment of diabetic retinopathy in an urban population in southern India. Br J Ophthalmol 1999; 83:937-940.

150. Fernando DJ, Siribaddana S, De S, Subasinge Z. Prevalence of retinopathy in a Sri Lankan diabetes clinic. Ceylon Med J 1993; 38:120-123.

151. Tapp R, Shaw J, Harper C, deCourten M, Balkau B, McCarty D, Taylor H, Welborn T, Zimmet P. The prevalence of and factors associated with diabetic retinopathy in the Australian population. Diabetes Care 2003; 26:1731-1737.

152. Fairchild JM, Hing SJ, Donaghue KC, Bonney MA, Fung AT, Stephens MM, Mitchell P, Howard NJ, Silink M. Prevalence and risk factors for retinopathy in adolescents with type 1 diabetes. Med J Aust 1994; 160:757-762.

153. McKay R, McCarty CA, Taylor HR. Diabetic retinopathy in Victoria, Australia: the Visual Impairment Project. Br J Ophthalmol 2000; 84:865-870.

154. Wang WQ, Ip TP, Lam KS. Changing prevalence of retinopathy in newly diagnosed non-insulin dependent diabetes mellitus patients in Hong Kong. Diabetes Res Clin Pract 1998; 39:185-191.

155. Hu YH, Pan XR, Liu PA, Li GW, Howard BV, Bennett PH. Coronary heart disease and diabetic retinopathy in newly diagnosed diabetes in Da Qing, China: the Da Qing IGT and Diabetes Study. Acta Diabetologica 1991; 28(2):169-173.

156. Brooks B, Chong R, Ho I, Capstick F, Molyneaux L, Oo TT, Tester M, Yue D. Diabetic retinopathy and nephropathy

in Fiji: comparison with data from an Australian diabetes centre. Aust N Z J Ophthalmol 1999; 27:9-13.

157. Florkowski CM, Scott RS, Coope PA, Graham PJ, Moir CL. Age at diagnosis, glycaemic control and the development of retinopathy in a population-based cohort of Type 1 diabetic subjects in Canterbury, New Zealand. Diabetes Res Clin Pract 2001; 52:125-131.

158. Lau HC, Voo YO, Yeo KT, Ling SL, Jap A. Mass screening for diabetic retinopathy – a report on diabetic retinal screening in primary care clinics in Singapore. Singapore Med J 1995; 36:510-513.

159. Chen MS, Kao CS, Chang CJ, Wu TJ, Fu CC, Chen CJ, Tai TY. Prevalence and risk factors of diabetic retinopathy among non insulin-dependent diabetic subjects. Am J Ophthalmol 1992; 114:723-730.

Diabetes in the Young: a Global PerspectiveChapter 2


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Diabetes in the Young:

a Global Perspective

Chapter 2

Diabetes is increasing in children and adolescents in many countries. The

increase in incidence in type 1 diabetes has been shown in countries having both high and low prevalence with an indication of a steeper increase in some of the low prevalence countries. Although type 1 diabetes usually accounts for only a minority of the total burden of diabetes in a population it is the predominant form of the disease in younger age groups in most developed countries.

At the same time, there is a growing awareness that type 2 diabetes in the young is an emerging problem with potentially serious outcomes. Yet our understanding of the worldwide burden of this disease is somewhat fractured, with many studies reporting on specific communities or ethnic groups.

The purpose of this chapter is to look at the global trends in childhood type 1 diabetes and to bring together for the first time, the available epidemiological data on type 2 diabetes incidence and prevalence in the young from around the world. By the inclusion of such data it is hoped to highlight deficiencies in the knowledge of the disease and also to promote strategies to deal with it.

2.1 Global Trends in Childhood Type 1 Diabetes

2.2 Type 2 Diabetes in the Young



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115

Introduction

The incidence of childhood onset diabetes is increasing in many countries in the world with an estimated overall annual increase of around 3% (1-3). There is some indication that incidence is increasing more steeply in some of the low prevalence countries. Moreover, several European studies have suggested that, in relative terms, increases are greatest in young children (4-6).

Analyses of cumulative incidence rates into the fourth decade of life (7,8) suggest that incidence is not increasing among young adults indicating rather a shift to a younger age at onset. The causes of these changes with time are unknown but the rapidity of the changes and the almost universally increasing trends in younger age groups are unlikely to be due to changes in the genetic background of the disease. Historically, studies have tended to record incidence data only up to the age of 15 years although recently studies reporting results up to the age of 30 or 35 years have become more common. However, the distinction between type 1 and type 2 diabetes becomes more difficult in these older age groups since people with type 2 diabetes may receive insulin therapy.

Type 1 diabetes in an adult may masquerade as type 2 diabetes at presentation with a slow deterioration in metabolic control, and subsequent progression to insulin dependency. This form is called latent autoimmune diabetes mellitus in adults (LADA) (9), and in the new WHO classification, LADA falls within type 1 autoimmune diabetes but in a slowly progressive form.

The predominant cause of hyperglycaemia in type 1 diabetes is an autoimmune destruction of the beta cells leading to absolute dependence on insulin treatment and a high rate of complications typically occurring at relatively young ages. Therefore type 1 diabetes places a particularly heavy burden on the individual, the family and the health services.

The continued mapping of global trends in incidence of type 1 diabetes in all age groups is thus important, and in conjunction with other scientific research may provide a logical basis for intervention studies and future primary prevention strategies which must be the ultimate goal.

Methods

Systematic searches of bibliographic databases were performed as explained in Appendix 1.3 to identify studies that provided incidence or prevalence rates of type 1 diabetes in children. Criteria were then applied to select the most suitable study in a given country or, if necessary, results from a number of studies were pooled.

For countries that had no incidence or prevalence rates available the choice of country to use for extrapolation was based on proximity, the state of economic development measured by the gross domestic product (GDP) per capita and

2.1 Global Trends in Childhood Type 1 Diabetes

Type 1 diabetes (0-14 years) 2003

Total child population (billion) 1.8Type 1 diabetes prevalence (%) 0.02Number of children with type 1 diabetes 430,000Annual increase of incidence (%) 3Estimated number of newly-diagnosed cases per year 65,000

At a glance



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115

the ethnic composition as assessed from the Central Intelligence Agency (CIA) World Factbook 2002 (10). The choice was also influenced by the quality rating of the studies in the various countries.

The majority of studies found by the literature search provided incidence rates rather than prevalence rates, and the method used to translate incidence rates to prevalence rates is described in Appendix 1.3.

The quality of estimates was assessed using the following simple rating system:A Studies from the country in question

that were based on registers that were population based with validated ascertainment levels of 90% or more.

B Other studies from the country in question, provided population denominators were given to enable rates to be calculated (so excluding case-series studies which provided no population denominator).

X Extrapolation using rates from a different country, the identity of the chosen country being indicated.

Results

The Tables contain information on population size in the 0-14 age group together with estimated numbers of prevalent cases in 2003, organized by region. In those countries for which rates were found in the literature search the following information is given:• geographical coverage;• calendar period;• number of cases;• estimated completeness of

ascertainment; and• a classification of the source as either

A or B using the criteria described under ‘Methods’. Countries for which no rates were found in the literature search were assigned the classification X (extrapolated from a source in another country) and the country whose rate was used in the extrapolation is identified.

It is estimated that on an annual basis some 65,000 children aged under 15 years develop type 1 diabetes worldwide. Of the estimated total of approximately 430,000 prevalent cases of type 1 diabetes in childhood, more than a quarter come from the South-East Asian (SEA) Region, and more than a fifth from the European (EUR) Region where reliable, up-to-date estimates of incidence were available for the majority of countries, as shown in Figure 2.1. The smallest contribution (approximately 5%) comes from the Western Pacific (WP) Region, despite it having the largest childhood population.

AfricaThe need for extrapolation of rates of childhood type 1 diabetes was particularly evident in the sub-Saharan African (AFR) Region. Published rates were found for only three of the countries in this region, and some of the studies were of poor quality and based on small numbers. Consequently imperfect estimates of rates from Nigeria, Zambia and Tanzania have had to be used for

Figure 2.1Estimated number of prevalent cases of type 1 diabetes in children by region

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widespread extrapolations because of the dearth of published studies.

Mortality among children with diabetes is likely to be high in parts of this region, but as numbers of cases in these countries were mainly derived directly from prevalence rates rather than indirectly from incidence rates the effects of mortality are incorporated in the estimates in Table 2.2. Tropical and malnutrition diabetes may account for a proportion of cases in this region, but reliable data are lacking. For these reasons the validity of the estimates of numbers of children with type 1 diabetes in many parts of this region are questionable and must therefore be treated with considerable caution.

Eastern Mediterranean and Middle EastIn contrast to the situation in sub-Saharan Africa, reliable data are available for childhood type 1 diabetes rates in a number of the African countries bordering the Mediterranean Sea. In the Eastern Mediterranean and Middle East (EMME) Region as a whole about half of the countries have published incidence rates. By far the largest contribution to the total number of estimated childhood type 1 cases for this region comes from Egypt whose estimate accounts for about a quarter of the region’s total. In Egypt the incidence of type I diabetes is reported as 8 per 100,000 population per year below the age of 15 years, while in Pakistan it is only 1 per 100,000 population.

EuropeCompared with other regions, the European Region has by far the most complete and reliable data on the rates of childhood type 1 diabetes with a large proportion of countries having registries that are either nationwide or cover several different parts of the country.

Where extrapolation for the incidence rate was necessary it was usually for countries

with small populations, and therefore any error associated with the extrapolation will have little impact on the estimate of the region’s total. The countries making the largest contribution to the total rates for childhood type 1 diabetes were United Kingdom, Germany and Russia reflecting to some degree the large childhood populations in these countries. It is worth noting that the estimates for Russia were based on a study from Novosibirsk which may not be representative of such a large country.

North AmericaAlthough no published rates were available for childhood type 1 diabetes in many of the smaller Caribbean islands in the North American (NA) Region, it was usually possible to extrapolate rates from an island in close proximity, although such rates were often based on very small numbers of cases. The USA estimate, which accounts for more than three-quarters of the region’s total, and to a lesser extent the estimate for Canada predominate.

South and Central AmericaAlthough the incidence of childhood type 1 diabetes in the South and Central American (SACA) Region is generally low, there are some sharp contrasts between the rates in neighbouring countries. This means that occasionally the choice of country to use for extrapolation can make a considerable difference to the resulting estimate (eg Bolivia, Ecuador). Such estimates must therefore be interpreted with caution. The Brazilian estimate accounts for more than half of the region’s total.

South-East AsiaOnly two countries in the South-East Asian Region have published rates for type 1 diabetes in childhood and therefore extrapolation of rates was necessary. The rate from China, although outside the region, was used for some extrapolations, but the rate for India was more frequently used and it therefore



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plays a pivotal role in the estimates for this region.

Two sources of rates for India were available, both from urban Madras and therefore probably not representative of the country as a whole. The first was a small prevalence study (11) giving an equivalent incidence rate which was less than half that of the second, larger study (12), the rate from the latter study having needed correction for under-ascertainment. Given that even the lower of these two rates far exceeds the rates reported from other countries in the area and that the incidence in urban Madras is likely to be higher than that for India as a whole, the decision was made to use the lower of these two rates even though it was based on the smaller study.

The large childhood population in India and the widespread use of the Indian data for extrapolation in this region means that this decision has important consequences not only for the total in the region but also for the worldwide estimate, both of which would be considerably larger had the higher estimate of incidence been used. Notwithstanding the use of the lower rate, the South-East Asian Region contributes more than any other to the worldwide childhood type 1 diabetes total.

Diabetes-associated mortality and tropical or malnutrition diabetes are also likely to play important roles in this region, but unfortunately there is inadequate information to address these issues. These points reinforce the need for much more detailed data on childhood diabetes in this region.

Western PacificWith the exception of Australia and New Zealand, the rates of childhood type 1 diabetes in the Western Pacific Region appear uniformly low. Few of the Pacific islands had published data and the rate for Papua New Guinea had to be

extrapolated far into the Pacific Ocean, although any error induced in the region’s total by this extrapolation is likely to be small because of the generally low rates and small populations involved.

The rate for Thailand was used extensively for extrapolation in the Indo-China peninsula. Despite its very low incidence, China accounts for almost half of the region’s total. However, the Western Pacific Region makes the smallest contribution of all to the world total of type 1 diabetes even though it has the largest childhood population.

Comments

The global distribution of childhood type 1 diabetes clearly indicates large area to area variations. This variability may partly be due to different distributions of risk genes for the disease as well as different distributions of environmental exposures, but part of the apparent variability both between countries and regions may also be due to methodological problems:

• The available incidence data sometimes covers only one small part of a large country. For example, in India incidence data were extrapolated from studies performed in Madras and data from Russia were extrapolated from a small dataset from Novosibirsk. Obviously there may be considerable variability within such large countries in both the distribution of risk genes and environmental exposures such as climate and lifestyle related factors (13).

• The need for extrapolation was particularly evident in the African continent, especially in sub-Saharan Africa. Here rates from undesirably small datasets have had to be used in extrapolations because of the lack of published studies.

• Another problem was the need to make extrapolations involving isolated



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island populations such as in Polynesia where both genetic predisposition and lifestyle habits may be very different.

• For some extrapolations, eg in parts of South America, a choice had to be made between countries whose reported incidence rates were very different, possibly on occasions because they were based on small datasets.

• Another methodological problem is the lack of data on mortality rates among children with diabetes in most populations. In less developed countries, in which mortality could have a significant impact, the disease rates were often based on small numbers of cases or on extrapolation so that the application of an adjustment to incidence data to

allow for mortality was not justified. In sub-Saharan Africa, where mortality among children with diabetes are reported to be high (14, 15), numbers of cases were mainly derived from Nigerian and Zambian prevalence rates rather than indirectly from incidence rates so that adjustment for mortality was not necessary. In such countries the relationship between incidence rate and prevalence rate is difficult to predict, and consequently incidence rates are not given for sub-Saharan Africa except for Tanzania (Table 2.2).

In addition to the geographical variation in the incidence of childhood type 1 diabetes there are also well-documented secular trends over time, which may also differ from country to country and from region to region within a country. Such time trends have not explicitly been

Map 2.1Published incidence rates of type 1 diabetes in children (0-14 age range)(cases per 100,000 population per year)

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incorporated in these estimates since reliable data are available for only a very small number of countries, but these trends are of considerable importance for healthcare planning.

The causes of such changes over time are unknown and although migration might slowly change the genetic background within a population, the rapid changes in incidence rate reported to occur within comparatively short time spans are more likely to be due to changes in environmental risk factors. These environmental risk factors may initiate autoimmunity or accelerate and precipitate an already ongoing beta cell destruction (13).

Potential risk factors which may initiate the autoimmune process include early fetal events eg blood group incompatibility (16), maternal viral infections during pregnancy (17,18), early exposure to cow’s milk components and other nutritional factors such as nitrosamines (19). Population-based case-control studies have identified some protective factors, including a long duration of breast feeding (19), early vitamin D supplementation (20),pre-school day care (as a proxy measure of infections) (21) and atopic diseases (22).

Since type 1 diabetes in childhood is associated with estimates of general wealth such as GDP (23) it has been suggested that lifestyle habits related to welfare might be responsible for the changes in trend. Wealth is awell-known determinant of birth weight and childhood growth.

Different estimates of child growth such as high birth weight, an increased height, weight, weight for height and body mass index (BMI) have repeatedly been shown to be risk factors for childhood onset diabetes (24-28). Rapid growth is associated with high growth hormone levels and an increased number

of fat cells both leading to insulin resistance and thereby an overloading of the beta cell. Although autoimmune mechanisms are responsible for the beta cell destruction leading to type 1 diabetes, overload factors may accelerate this process (29-31). Overload through accelerated child growth and body fat accumulation in association with a lifestyle with a low physical activity are potentially preventable risk factors.



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Table 2.1 Data sources: estimates of type 1 diabetes in children – African Region

Country Data used Period Geography No. of cases Completeness Classification

Angola Zambia (Rolfe et al, 1989)a, 32 X

Benin Nigeria (Afoke et al, 1992)b, 33 X

Botswana Zambia (Rolfe et al, 1989)a, 32 X

Burkina Faso Nigeria (Afoke et al, 1992)b, 33 X

Burundi Tanzania (Swai et al, 1993)34 X

Cameroon Nigeria (Afoke et al, 1992)b, 33 X

Cape Verde Nigeria (Afoke et al, 1992)b, 33 X

Central African Republic Nigeria (Afoke et al, 1992)b, 33 X

Chad Nigeria (Afoke et al, 1992)b, 33 X

Comoros Tanzania (Swai et al, 1993)34 X

Congo, Democratic Republic of Zambia (Rolfe et al, 1989)a, 32 X

Congo, Republic of Zambia (Rolfe et al, 1989)a, 32 X

Côte d’Ivoire Nigeria (Afoke et al, 1992)b, 33 X

Djibouti Sudan (Elamin et al, 1992)35 X

Equatorial Guinea Nigeria (Afoke et al, 1992)b, 33 X

Eritrea Tanzania (Swai et al, 1993)34 X

Ethiopia Tanzania (Swai et al, 1993)34 X

Gabon Nigeria (Afoke et al, 1992)b, 33 X

Gambia Nigeria (Afoke et al, 1992)b, 33 X

Ghana Nigeria (Afoke et al, 1992)b, 33 X

Guinea Nigeria (Afoke et al, 1992)b, 33 X

Guinea-Bissau Nigeria (Afoke et al, 1992)b, 33 X

Kenya Tanzania (Swai et al, 1993)34 X

Lesotho Zambia (Rolfe et al, 1989)a, 32 X

Liberia Nigeria (Afoke et al, 1992)b, 33 X

Madagascar Mauritius (Karvonen et al, 2000)36 X

Malawi Zambia (Rolfe et al, 1989)a, 32 X

Mali Nigeria (Afoke et al, 1992)b, 33 X

Mauritania Nigeria (Afoke et al, 1992)b, 33 X

Mozambique Tanzania (Swai et al, 1993)34 X

Namibia Zambia (Rolfe et al, 1989)a, 32 X

Niger Nigeria (Afoke et al, 1992)b, 33 X

Nigeria Nigeria (Afoke et al, 1992)b, 33 1990 Anambra 14 N/A B

Reunion Mauritius (Karvonen et al, 2000)36 X

Rwanda Tanzania (Swai et al, 1993)34 X

Sao Tome and Principe Nigeria (Afoke et al, 1992)b, 33 X

Senegal Nigeria (Afoke et al, 1992)b, 33 X

Seychelles Mauritius (Karvonen et al, 2000)36 X

Sierra Leone Nigeria (Afoke et al, 1992)b, 33 X

Somalia Tanzania (Swai et al, 1993)34 X

South Africa Zambia (Rolfe et al, 1989)a, 32 X

Swaziland Zambia (Rolfe et al, 1989)a, 32 X

Tanzania Tanzania (Swai et al, 1993)34 1982-91 Dar es Salaam 36 100% A

Togo Nigeria (Afoke et al, 1992)b, 33 X

Uganda Tanzania (Swai et al, 1993)34 X

Western Sahara Algeria (Karvonen et al, 2000)36 X

Zambia Zambia (Rolfe et al, 1989)a, 32 pre-1989 Copperbelt 37 90% B

Zimbabwe Zambia (Rolfe et al, 1989)a, 32 X

a. Gives prevalence for <20 years b. Gives prevalence for 5-17 years

N/A not available



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Table 2.2Estimates of type 1 diabetes in children – African Region

a. UN population projections – medium variant 2003 b. Likely high mortality rate and shortage of good-quality incidence studies makes it problematic to derive

incidence from prevalence in these countries c. Population estimates extracted from CIA World Factbook 200210 d. Adjusted to take account of the higher rates in those of European origin

Population size(000’s)

Incidence rates (cases per 100,000

population per year)b

Estimated no. of prevalent cases

Country 0-14 yrsa 0-14 yrs (000’s)

Angola 6,951 0.3

Benin 3,095 0.6

Botswana 648 0.0

Burkina Faso 6,102 1.1

Burundi 3,162 0.2

Cameroon 6,703 1.2

Cape Verde 174 0.0

Central African Republic 1,677 0.3

Chad 4,043 0.7

Comoros 327 0.0

Congo, Democratic Republic of 27,527 1.4

Congo, Republic of 1,540 0.1

Côte d’Ivoire 6,939 1.2

Djibouti 284 0.1

Equatorial Guinea 218 0.0

Eritrea 1,813 0.1

Ethiopia 30,596 1.7

Gabon 541 0.1

Gambia 560 0.1

Ghana 8,184 1.5

Guinea 3,704 0.7

Guinea-Bissau 564 0.1

Kenya 13,615 0.8

Lesotho 814 0.0

Liberia 1,510 0.3

Madagascar 7,745 0.7

Malawi 5,559 0.3

Mali 5,725 1.0

Mauritania 1,289 0.2

Mozambique 8,493 0.5

Namibia 800 0.0

Niger 6,046 1.1

Nigeria 54,789 9.9

Reunion 204 0.0

Rwanda 3,607 0.2

Sao Tome and Principec 81 0.0

Senegal 4,431 0.8

Seychellesc 22 0.0

Sierra Leone 2,263 0.4

Somalia 4,815 0.3

South Africad 14,818 4.9

Swaziland 393 0.0

Tanzania 16,670 0.9 0.5

Togo 2,144 0.4

Uganda 12,679 0.7

Western Sahara 101 0.0

Zambia 5,168 0.3

Zimbabwe 5,905 0.3

AFR Total 295,037 § 35.1



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Afghanistan Uzbekistan (Rakhimova et al, 2002)37 X

Algeria Algeria (Karvonen et al, 2000)36 1990 Oran 23 N/A B

Armenia Ukraine (Timchenko et al, 1996)38 X

Bahrain Oman (Soliman et al, 1996)39 X

Egypt Egypt (Arab et al, 1992)40 pre-1992 Alexandria, Damahour

N/A N/A B

Iran Pakistan (Staines et al, 1997)41 X

Iraq Jordan (Ajlouni et al, 1999)42 X

Jordan Jordan (Ajlouni et al, 1999)42 1992-96 Whole country 275 96% A

Kuwait Kuwait (Shaltout et al, 2002)43 1992-97 Whole country 364 90-96% A

Lebanon Jordan (Ajlouni et al, 1999)42 X

Libya Libya (Kadiki, 1998)44 1991-95 Benghazi 126 100% A

Morocco Algeria (Karvonen et al, 2000)36 X

Occupied Palestinian Territories

Jordan (Ajlouni et al, 1999)42 X

Oman Oman (Soliman et al, 1996)39 1993-94 Whole country 31 96% A

Pakistan Pakistan (Staines et al, 1997)41 1989-93 Karachi 240 N/A B

Qatar Qatar (Al-Zyoud et al, 1997)a, 45 1992-96 Whole country 80 N/A B

Saudi Arabia Saudi Arabia (Kulaylat et al, 2000)46 1986-97 Eastern Province 46 100% A

Sudan Sudan (Elamin et al, 1992)35 1987-90 Khartoum 311 95% A

Syria Jordan (Ajlouni et al, 1999)42 X

Tunisia Tunisia (Karvonen et al, 2000)36 1990-94 Beja, Gafsa, Kairoan, Monastir

168 N/A B

United Arab Emirates Oman (Soliman et al, 1996)39 X

Yemen Oman (Soliman et al, 1996)39 X

Table 2.3 Data sources: estimates of type 1 diabetes in children – Eastern Mediterranean and Middle East Region

a. Only to 12 years

N/A not available



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Incidence rates(cases per 100,000

population per year)Estimated no.

of prevalent cases


Afghanistan 10,501 1.2 0.8

Algeria 10,530 5.7 3.9

Armenia 768 8.1 0.4

Bahrain 178 2.5 0.0

Egypt 23,775 8.0 11.8

Iran 24,940 1.0 1.5

Iraq 10,085 3.2 2.0

Jordan 2,117 3.2 0.3

Kuwait 540 20.9 0.8

Lebanon 1,078 3.2 0.2

Libya 1,842 9.3 0.7

Morocco 10,515 5.7 3.7

Occupied Palestinian Territories 1,634 3.2 0.3

Oman 1,198 2.5 0.2

Pakistan 62,839 1.0 3.4

Qatar 154 11.4 0.1

Saudi Arabia 9,338 12.3 5.7

Sudan 13,182 8.0 6.5

Syria 6,704 3.2 1.3

Tunisia 2,693 6.6 1.1

United Arab Emirates 653 2.5 0.1

Yemen 10,557 2.5 1.6

EMME Total 205,822 § 46.6

Table 2.4Estimates of type 1 diabetes in children – Eastern Mediterranean and Middle East Region

a. UN population projections – medium variant 2003



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Albania Macedonia (Green et al, 2001)3 X

Andorra Spain (Green et al, 2001)3 X

Austria Austria (Green et al, 2001)3 1989-98 Whole country 1,314 98% A

Azerbaijan Republic Uzbekistan (Rakhimova et al, 2002)37 X

Belarus Belarus (Martinucci et al, 2002)47 1986-99 Gomel approx 280 100% A

Belgium Belgium (Green et al, 2001)3 1989-98 Antwerp 191 96% A

Bosnia and Herzegovina Bosnia and Herzegovina (Bratina et al, 2001)48

1990-98 Tuzla 43 100% A

Bulgaria Bulgaria (Green et al, 2001)3 1989-98 Whole country 885 100% A

Croatia Croatia (Green et al, 2001)3 1989-98 Zagreb A

Cyprus Cyprus (Skordis et al, 1997)49 1990-94 Greek population 81 N/A B

Czech Republic Czech Republic (Green et al, 2001)3 1989-98 Whole country A

Denmark Denmark (Svensson et al, 2002)50 1996-2000 Whole country 839 99% A

Estonia Estonia (Green et al, 2001)3 1989-98 Whole country 365 100% A

Finland Finland (Tuomilehto et al, 1999)51 1987-96 Whole country 3,613 100% A

France France (EURODIAB ACE, 2000)2 1989-94 Four regions 837 99% A

Georgia, Republic of Ukraine (Timchenko et al, 1996)38 X

Germany Germany (Green et al, 2001)3 1989-98 Dusseldorf, Baden Wurttemberg

2,535 90-97% A

Greece Greece (Green et al, 2001)3 1989-98 Attica, five northern regions

623 100% A

Hungary Hungary (Green et al, 2001)3 1989-98 Eighteen counties 1,385 100% A

Iceland Iceland (Green et al, 2001)3 1989-98 Whole country 89 100% A

Ireland, Republic of Ireland (Roche et al, 2002)52 1997 Whole country 140 91% A

Israel Israel (EURODIAB ACE, 2000)2 1989-94 Whole country 433 100% A

Italy Italy (Green et al, 2001)3 1989-98 Lazio, eastern Sicily 255 86-99% A/B

Kazakhstan Uzbekistan (Rakhimova et al, 2002)37 X

Kyrgyzstan Uzbekistan (Rakhimova et al, 2002)37 X

Latvia Latvia (Green et al, 2001)3 1989-98 Whole country 386 100% A

Lithuania Lithuania (Green et al, 2001)3 1989-98 Whole country 638 100% A

Luxembourg Luxembourg (Green et al, 2001)3 1989-98 Whole country 84 100% A

Macedonia Macedonia (Green et al, 2001)3 1989-98 Whole country 175 98% A

Malta Malta (Schranz, 1998)53 1990-96 Whole country 90 N/A B

Moldova, Republic of Romania (Green et al, 2001)3 X

Monaco France (EURODIAB ACE, 2000)2 X

Netherlands Netherlands (EURODIAB ACE, 2000)2 1989-94 Five regions 421 96% A

Norway Norway (Joner et al, 2000)54 1989-98 Whole country 1,866 100% A

Poland Poland (Green et al, 2001)3 1989-98 Gliwice, three cities 1,175 100% A

Portugal Portugal (Green et al, 2001)3 1989-98 Algarve, Madeira 136 85-100% A/B

Romania Romania (Green et al, 2001)3 1989-98 Bucharest 227 100% A

Russian Federation Russia (Shubnikov et al, 1999)55 1992-97 Novosibirsk N/A N/A B

San Marino Italy (Green et al, 2001)3 X

Serbia and Montenegro Serbia and Montenegro (Vlajinac et al, 1995)56

1982-92 Belgrade 259 90% A

Slovakia Slovakia (Green et al, 2001)3 1989-98 Whole country 1,156 100% A

Slovenia Slovenia (Green et al, 2001)3 1989-98 Whole country 327 100% A

Spain Spain (Green et al, 2001)3 1989-98 Catalonia 1,336 94% A

Sweden Sweden (Pundziute-Lycka et al, 2002)7 1995-98 Whole country approx 1,800 96-99% A

Switzerland Switzerland (EURODIAB ACE, 2000)2 1991-94 Whole country 353 N/A B

Tajikistan Uzbekistan (Rakhimova et al, 2002)37 X

Turkey Jordan (Ajlouni et al, 1999)42 X

Turkmenistan Uzbekistan (Rakhimova et al, 2002)37 X

Ukraine Ukraine (Timchenko et al, 1996)38 1985-92 Whole country N/A N/A B

United Kingdom United Kingdom (Green et al, 2001)3 1989-98 Leeds, Oxford, Northern Ireland, Leicester

3,419 95-100% A

Uzbekistan Uzbekistan (Rakhimova et al, 2002)37 2000 Whole country N/A N/A B

Table 2.5 Data sources: estimates of type 1 diabetes in children – European Region

N/A not available



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of prevalent cases


Albania 905 3.6 0.2

Andorrab 10 12.8 0.0

Austria 1,275 9.5 0.8

Azerbaijan Republic 2,112 1.2 0.2

Belarus 1,668 5.7 0.6

Belgium 1,713 11.8 1.3

Bosnia and Herzegovina 706 3.5 0.1

Bulgaria 1,108 8.8 0.7

Croatia 815 6.6 0.3

Cyprus 175 10.5 0.1

Czech Republic 1,567 9.8 1.0

Denmark 982 19.4 1.2

Estonia 210 11.4 0.2

Finland 899 37.4 2.5

France 10,970 8.3 5.6

Georgia, Republic of 963 8.1 0.5

Germany 12,028 12.2 10.1

Greece 1,537 9.1 0.9

Hungary 1,581 9.6 1.1

Iceland 64 13.9 0.1

Ireland, Republic of 817 16.3 0.9

Israel 1,783 5.9 0.6

Italy 8,033 9.5 5.6

Kazakhstan 3,968 1.2 0.3

Kyrgyzstan 1,603 1.2 0.1

Latvia 359 7.1 0.2

Lithuania 641 7.8 0.3

Luxembourg 84 11.9 0.1

Macedonia 434 3.6 0.1

Malta 75 15.6 0.1

Moldova, Republic of 879 5.0 0.3

Monacob 5 8.3 0.0

Netherlands 2,864 13 2.5

Norway 876 22.5 1.3

Poland 6,662 6.7 3.0

Portugal 1,674 11.5 1.3

Romania 3,694 5.0 1.2

Russian Federation 22,389 7.2 12.4

San Marinob 4 9.5 0.0

Serbia and Montenegro 1,976 8.1 1.0

Slovakia 970 9.2 0.6

Slovenia 288 8.5 0.2

Spain 5,664 12.8 4.4

Sweden 1,498 28.0 3.1

Switzerland 1,139 7.9 0.6

Tajikistan 2,244 1.2 0.2

Turkey 20,561 3.2 4.1

Turkmenistan 1,793 1.2 0.1

Ukraine 7,651 8.1 3.8

United Kingdom 10,923 18.9 13.7

Uzbekistan 8,623 1.2 0.6

EUR Total 161,460 § 90.1

Table 2.6Estimates of type 1 diabetes in children – European Region

a. UN population projections – medium variant 2003 b. Population estimates extracted from CIA World Factbook 200210



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Anguilla Antigua and Barbuda (Tull et al, 1997)a, 57 X

Antigua and Barbuda Antigua and Barbuda (Tull et al, 1997)a, 57 1989-93 Antigua 4 100 A

Aruba Venezuela (Karvonen et al, 2000)36 X

Bahamas Cuba (Karvonen et al, 2000)36 X

Barbados Barbados (Karvonen et al, 2000)36 1990-93 Whole country 5 N/A B

Belize Mexico (Karvonen et al, 2000)36 X

Bermuda Cuba (Karvonen et al, 2000)36 X

British Virgin Islands Antigua and Barbuda (Tull et al, 1997)a, 57 X

Canada Canada (Karvonen et al, 2000)36 1990-94 Alberta, Prince Edward Island

204 75-100% A/B

Cayman Islands Cuba (Karvonen et al, 2000)36 X

Dominica, Commonwealth of

Dominica (Karvonen et al, 2000)36 1990-93 Whole country 5 N/A B

Grenada Barbados (Karvonen et al, 2000)36 X

Guadeloupe Dominica (Karvonen et al, 2000)36 X

Guyana Venezuela (Karvonen et al, 2000)36 X

Haiti Puerto Rico (Karvonen et al, 2000)36 X

Jamaica Cuba (Karvonen et al, 2000)36 X

Martinique Barbados (Karvonen et al, 2000)36 X

Mexico Mexico (Karvonen et al, 2000)36 1990-93 Veracruz 9 100% B

St Kitts and Nevis Antigua and Barbuda (Tull et al, 1997)a, 57 X

St Lucia Barbados (Karvonen et al, 2000)36 X

St Vincent and the Grenadines

Barbados (Karvonen et al, 2000)36 X

Trinidad and Tobago Barbados (Karvonen et al, 2000)36 X

USA USA (Karvonen et al, 2000)36 1990-94 Allegheny, Jefferson, Chicago

607 51-100% A/B

Table 2.7 Data sources: estimates of type 1 diabetes in children – North American Region

a. Relates to 0-19 years age range

N/A not available



126



127

Population size (000’s)



of prevalent cases


Anguillab 3 3.5 0.0

Antigua and Barbudab 19 3.5 0.0

Arubab 15 0.1 0.0

Bahamas 91 2.9 0.0

Barbados 53 2.0 0.0

Belize 87 1.5 0.0

Bermudab 12 2.9 0.0

British Virgin Islandsb 5 3.5 0.0

Canada 5,759 24.1 9.1

Cayman Islandsb 8 2.9 0.0

Dominica, Commonwealth of b 20 5.7 0.0

Grenadab 32 2.0 0.0

Guadeloupe 105 5.7 0.0

Guyana 228 0.1 0.0

Haiti 3,305 17.4 3.6

Jamaica 798 2.9 0.1

Martinique 84 2.0 0.0

Mexico 32,799 1.5 2.6

St Kitts and Nevisb 11 3.5 0.0

St Lucia 48 2.0 0.0

St Vincent and the Grenadinesb 34 2.0 0.0

Trinidad and Tobago 293 2.0 0.0

USA 61,383 13.8 49.2

NA Total 105,192 § 64.7

Table 2.8Estimates of type 1 diabetes in children – North American Region




128



129


Argentina Argentina (Karvonen et al, 2000)36 1990-94 Avellaneda, Cordoba, Corrientes, Tierra del Fuego

89 88-100% A/B

Bolivia Peru (Karvonen et al, 2000)36 X

Brazil Brazil (Karvonen et al, 2000)36 1990-92 Sao Paulo 34 70-95% B

Chile Chile (Santos et al, 2001)58 1997-98 Santiago 61 100% A

Colombia Colombia (Karvonen et al, 2000)36 1990 Santa Fé de Bogotá 56 97% A

Costa Rica Colombia (Karvonen et al, 2000)36 X

Cuba Cuba (Karvonen et al, 2000)36 1990-94 Whole country 349 75-100% A

Dominican Republic Puerto Rico (Karvonen et al, 2000)36 X

Ecuador Colombia (Karvonen et al, 2000)36 X

El Salvador Mexico (Karvonen et al, 2000)36 X

French Guiana Venezuela (Karvonen et al, 2000)36 X

Guatemala Mexico (Karvonen et al, 2000)36 X

Honduras Mexico (Karvonen et al, 2000)36 X

Netherlands Antilles Venezuela (Karvonen et al, 2000)36 X

Nicaragua Mexico (Karvonen et al, 2000)36 X

Panama Colombia (Karvonen et al, 2000)36 X

Paraguay Paraguay (Karvonen et al, 2000)36 1990-94 Whole country 79 N/A B

Peru Peru (Karvonen et al, 2000)36 1990-91 Lima 16 88% B

Puerto Rico Puerto Rico (Karvonen et al, 2000)36 1990-94 Whole country 844 90-97% A

Suriname Venezuela (Karvonen et al, 2000)36 X

Uruguay Uruguay (Karvonen et al, 2000)36 1992 Montevideo 26 97% A

Venezuela Venezuela (Karvonen et al, 2000)36 1992 Caracas 43 N/A B

Table 2.9 Data sources: estimates of type 1 diabetes in children – South and Central American Region

N/A not available



128



129




of prevalent cases


Argentina 10,408 6.4 4.1

Bolivia 3,454 0.4 0.1

Brazil 48,424 8.0 23.8

Chile 4,322 4.1 1.1

Colombia 14,048 3.8 3.3

Costa Rica 1,326 3.8 0.3

Cuba 2,240 2.9 0.4

Dominican Republic 2,806 17.4 3.0

Ecuador 4,323 3.8 1.0

El Salvador 2,304 1.5 0.2

French Guiana 65 0.1 0.0

Guatemala 5,252 1.5 0.5

Honduras 2,782 1.5 0.3

Netherlands Antilles 52 0.1 0.0

Nicaragua 2,283 1.5 0.2

Panama 892 3.8 0.2

Paraguay 2,266 0.9 0.1

Peru 8,578 0.4 0.2

Puerto Rico 934 17.4 1.1

Suriname 121 0.1 0.0

Uruguay 837 8.3 0.4

Venezuela 8,322 0.1 0.1

SACA Total 126,041 § 40.4

Table 2.10Estimates of type 1 diabetes in children – South and Central American Region




130



131


Bangladesh India (Ramachandran et al, 1992)59 X

Bhutan People’s Republic of China (Karvonen et al, 2000)36

X

India India (Ramachandran et al, 1992)59 1991 Madras 30 N/A B

Maldives India (Ramachandran et al, 1992)59 X

Mauritius Mauritius (Karvonen et al, 2000)36 1990-94 Whole country 21 35-100% B

Nepal People’s Republic of China (Karvonen et al, 2000)36

X

Sri Lanka India (Ramachandran et al, 1992)59 X

Table 2.11 Data sources: estimates of type 1 diabetes in children – South-East Asian Region

N/A not available




of prevalent cases


Bangladesh 54,846 4.2 14.3

Bhutan 941 0.6 0.0

India 341,094 4.2 88.8

Maldives 135 4.2 0.0

Mauritius 296 1.4 0.0

Nepal 10,048 0.6 0.4

Sri Lanka 4,877 4.2 1.3

SEA Total 412,236 § 104.8

Table 2.12Estimates of type 1 diabetes in children – South-East Asian Region




130



131


Australia Australia (Craig et al, 2000)60 1990-96 New South Wales 1,591 99% A

Brunei Darussalam Thailand (Tuchinda et al, 2002)61 X

Cambodia Thailand (Tuchinda et al, 2002)61 X

China, Hong Kong Hong Kong (Huen et al, 2000)62 1984-96 Whole country 227 N/A B

China, Macau Hong Kong (Huen et al, 2000)62 X

China, People’s Republic of People’s Republic of China (Karvonen et al, 2000)36

1990-94 Twenty-one regions

462 69-100% A/B

Cook Islands Papua New Guinea (Ogle et al, 2001)63 X

East Timor Thailand (Tuchinda et al, 2002)61 X

Fiji Papua New Guinea (Ogle et al, 2001)63 X

French Polynesia Papua New Guinea (Ogle et al, 2001)63 X

Guam Papua New Guinea (Ogle et al, 2001)63 X

Indonesia Thailand (Tuchinda et al, 2002)61 X

Japan Japan (Karvonen et al, 2000)36 1990-93 Chiba, Hokkaido, Okinawa

167 77-100% A/B

Kiribati Papua New Guinea (Ogle et al, 2001)63 X

Korea, Democratic People’s Republic of

Republic of Korea (Ko et al, 1994)64 X

Korea, Republic of Republic of Korea (Ko et al, 1994)64 1985-88 Seoul 71 N/A B

Lao People’s Democratic Republic

Thailand (Tuchinda et al, 2002)61 X

Malaysia Thailand (Tuchinda et al, 2002)61 X

Marshall Islands Papua New Guinea (Ogle et al, 2001)63 X

Micronesia Papua New Guinea (Ogle et al, 2001)63 X

Mongolia People’s Republic of China (Karvonen et al, 2000)36

X

Myanmar Thailand (Tuchinda et al, 2002)61 X

Nauru Papua New Guinea (Ogle et al, 2001)63 X

New Caledonia Papua New Guinea (Ogle et al, 2001)63 X

New Zealand New Zealand (Karvonen et al, 2000)36 1990-94 Auckland, Canterbury

213 100% A

Niue Papua New Guinea (Ogle et al, 2001)63 X

Palau Papua New Guinea (Ogle et al, 2001)63 X

Papua New Guinea Papua New Guinea (Ogle et al, 2001)63 1996-2000 Whole country 8 N/A B

Philippines People’s Republic of China (Karvonen et al, 2000)36

X

Samoa Papua New Guinea (Ogle et al, 2001)63 X

Singapore, Republic of Singapore (Lee et al, 1998)a, 65 1992-94 Whole country 40 92% A

Solomon Islands Papua New Guinea (Ogle et al, 2001)63 X

Taiwan Hong Kong (Huen et al, 2000)62 X

Thailand Thailand (Tuchinda et al, 2002)61 1991-95 North, north-east, south and central regions

191 N/A B

Tokelau Papua New Guinea (Ogle et al, 2001)63 X

Tonga Papua New Guinea (Ogle et al, 2001)63 X

Tuvalu Papua New Guinea (Ogle et al, 2001)63 X

Vanuatu Papua New Guinea (Ogle et al, 2001)63 X

Vietnam Thailand (Tuchinda et al, 2002)61 X

Table 2.13 Data sources: estimates of type 1 diabetes in children – Western Pacific Region

a. Only to age 12 years

N/A not available



132



133




of prevalent cases


Australia 3,931 17.8 4.4

Brunei Darussalam 105 0.3 0.0

Cambodia 5,979 0.3 0.1

China, Hong Kong 1,093 1.4 0.1

China, Macau 86 1.4 0.0

China, People’s Republic of 299,371 0.6 9.3

Cook Islandsb 8 0.1 0.0

East Timor 298 0.3 0.0

Fiji 273 0.1 0.0

French Polynesia 71 0.1 0.0

Guam 59 0.1 0.0

Indonesia 64,466 0.3 1.2

Japan 18,228 1.7 1.9

Kiribatib 39 0.1 0.0

Korea, Democratic People’s Republic of 5,858 0.7 0.3

Korea, Republic of 9,576 0.7 0.4

Lao People’s Democratic Republic 2,355 0.3 0.0

Malaysia 7,785 0.3 0.1

Marshall Islandsb 36 0.1 0.0

Micronesiab 48 0.1 0.0

Mongolia 840 0.6 0.0

Myanmar 15,782 0.3 0.3

Naurub 5 0.1 0.0

New Caledonia 66 0.1 0.0

New Zealand 864 15.2 0.9

Niueb 1 0.1 0.0

Palaub 5 0.1 0.0

Papua New Guinea 2,049 0.1 0.0

Philippines 29,012 0.6 1.1

Samoa 65 0.1 0.0

Singapore, Republic of 892 2.5 0.2

Solomon Islands 221 0.1 0.0

Taiwanb 4,733 1.4 0.4

Thailand 16,775 0.3 0.3

Tokelaub 1 0.1 0.0

Tongab 42 0.1 0.0

Tuvalub 4 0.1 0.0

Vanuatu 86 0.1 0.0

Vietnam 25,090 0.3 0.5

WP Total 516,194 § 21.6

Table 2.14Estimates of type 1 diabetes in children – Western Pacific Region




132



133

References

1. Onkamo P, Vaananen S, Karvonen M, Tuomilehto J. Worldwide increase in incidence of Type I diabetes – the analysis of the data on published incidence trends. Diabetologia 1999; 42(12):1395-1403.

2. EURODIAB ACE Study Group. Variation and trends in incidence of childhood diabetes in Europe. Lancet 2000; 355(9207):873-876.

3. Green A, Patterson CC. Trends in the incidence of childhood-onset diabetes in Europe 1989-1998. Diabetologia 2001;44 Suppl 3:B3-B8.

4. Tuomilehto J, Virtala E, Karvonen M, et al. Increase in incidence of insulin-dependent diabetes mellitus among children in Finland. Int J Epidemiol 1995; 24(5):984-992.

5. Gardner SG, Bingley PJ, Sawtell PA, Weeks S, Gale EA. Rising incidence of insulin dependent diabetes in children aged under 5 years in the Oxford region: time trend analysis. The Bart’s-Oxford Study Group. BMJ 1997; 315(7110):713-717.

6. Dahlquist G, Mustonen L. Analysis of 20 years of prospective registration of childhood onset diabetes time trends and birth cohort effects. Swedish Childhood Diabetes Study Group. Acta Paediatr 2000; 89(10):1231-1237.

7. Pundziute-Lycka A, Dahlquist G, Nystrom L, et al. Type I diabetes in the 0-34 years group in Sweden. Diabetologia 2002; 45(6):783-791.

8. Weets I, De Leeuw IH, Du Caju MV, et al. The incidence of type 1 diabetes in the age group 0-39 years has not increased in Antwerp (Belgium) between 1989 and 2000: evidence for earlier disease manifestation. Diabetes Care 2002; 25(5):840-846.

9. Tuomi T, Groop LC, Zimmet PZ, et al. Antibodies to glutamic acid decarboxylase reveal latent autoimmune diabetes mellitus in adults with a non-insulin-dependent onset of disease. Diabetes 1993; 42(2):359-362.

10. Central Intelligence Agency. Central Intelligence Agency World Factbook. URL [2001], www.odci.gov/cia/publications/factbook/index.html. 2002.

11. Ramachandran A, Snehalatha C, Abdul Khader OM, Joseph TA, Viswanathan M. Prevalence of childhood diabetes in an urban population in South India. Diabetes Res Clin Pract 1992; 17:227-231.

12. Ramachandran A, Snehalatha C, Krishnaswamy CV. Incidence of IDDM in children in urban population in southern India. Madras IDDM Registry Group Madras, South India. Diabetes Res Clin Pract 1996; 34:79-82.

13. Dahlquist G. Diabetes in children: The etiology in an epidemiological perspective. In The Diabetes Annual WHO vol 8, eds Home PD, Marshall SM. Amsterdam:Elsevier, 1994.

14. Castle WM, Wicks ACB. A follow-up of 93 newly-diagnosed African diabetics for 6 years. Diabetologia 1980;18:121-123.

15. Makame MH. Childhood diabetes, insulin, and Africa. Diabet Med 1992; 9:571-573.

16. Dahlquist G, Kallen B. Maternal-child blood group incompatibility and other perinatal events increase the risk for early-onset type 1 (insulin-dependent) diabetes mellitus. Diabetologia 1992; 35(7):671-675.

17. Dahlquist GG, Ivarsson S, Lindberg B, Forsgren M. Maternal enteroviral infection during pregnancy as a risk factor for childhood IDDM. A population-based case-control study. Diabetes 1995; 44(4):408-413.

18. Hyoty H, Hiltunen M, Knip M, et al. A prospective study of the role of coxsackie B and other enterovirus infections in the pathogenesis of IDDM. Childhood Diabetes in Finland (DiMe) Study Group. Diabetes 1995; 44(6):652-657.

19. Akerblom HK, Vaarala O, Hyoty H, Ilonen J, Knip M. Environmental factors in the etiology of type 1 diabetes. Am J Med Genet 2002; 115(1):18-29.

20. EURODIAB Substudy 2 Study Group. Vitamin D supplement in early childhood and risk for Type I (insulin-dependent) diabetes mellitus. Diabetologia 1999; 42(1):51-54.

21. EURODIAB Substudy 2 Study Group. Infections and vaccinations as risk factors for childhood type I (insulin-dependent) diabetes mellitus: a multicentre case-control investigation. Diabetologia 2000; 43(1):47-53.

22. EURODIAB Substudy 2 Study Group. Decreased prevalence of atopic diseases in children with diabetes. J Pediatr 2000; 137(4):470-474.

23. Patterson CC, Dahlquist G, Soltesz G, Green A. Is childhood-onset type I diabetes a wealth-related disease? An ecological analysis of European incidence rates. Diabetologia 2001; 44 Suppl 3:B9-16.

24. Blom L, Persson LA, Dahlquist G. A high linear growth is associated with an increased risk of childhood diabetes mellitus. Diabetologia 1992; 35(6):528-533.

25. Dahlquist G, Bennich SS, Kallen B. Intrauterine growth pattern and risk of childhood onset insulin dependent (type I) diabetes: population based case-control study. BMJ 1996; 313(7066):1174-1177.

26. Stene LC, Magnus P, Lie RT, Sovik O, Joner G. Birth weight and childhood onset type 1 diabetes: population based cohort study. BMJ 2001; 322(7291):889-892.

27. Hypponen E, Virtanen SM, Kenward MG, Knip M, Akerblom HK. Obesity, increased linear growth, and risk of type 1 diabetes in children. Diabetes Care 2000;23(12):1755-1760.

28. EURODIAB Substudy 2 Study Group. Rapid early growth is associated with increased risk of childhood type 1 diabetes in various European populations. Diabetes Care 2002; 25(10):1755-1760.

29. Bjork E, Kampe O, Karlsson FA, et al. Glucose regulation of the autoantigen GAD65 in human pancreatic islets. J Clin Endocrinol Metab 1992; 75(6):1574-1576.

30. Mandrup-Poulsen T. The role of interleukin-1 in the pathogenesis of IDDM. Diabetologia 1996; 39(9):1005-1029.

31. Pipeleers D, Hoorens A, Marichal-Pipeleers M, et al. Role of pancreatic beta-cells in the process of beta-cell death. Diabetes 2001; 50 Suppl 1:S52-S57.

32. Rolfe M, Armstrong JR. Diabetes mellitus on the Zambian Copperbelt. J R Coll Physicians Lond 1989; 23:255-259.

33. Afoke AO, Ejeh NM, Nwonu EN, Okafor CO, Udeh NJ, Ludvigsson J. Prevalence and clinical picture of IDDM in Nigerian Igbo schoolchildren. Diabetes Care 1992; 15:1310-1312.

34. Swai AB, Lutale JL, McLarty DG. Prospective study of incidence of juvenile diabetes mellitus over 10 years in Dar es Salaam, Tanzania. BMJ 1993; 306:1570-1572.

35. Elamin A, Omer MI, Zein K, Tuvemo T. Epidemiology of childhood type I diabetes in Sudan, 1987-1990. Diabetes Care 1992; 15:1556-1559.

36. Karvonen M, Viik-Kajander M, Moltchanova E, Libman I, LaPorte R, Tuomilehto J. Incidence of childhood type 1 diabetes worldwide. Diabetes Mondiale (DiaMond) Project Group. Diabetes Care 2000; 23:1516-1526.

37. Rakhimova GGN, Ismailov S. Prevalence of Type 1 diabetes mellitus and its vascular complications in childhood population in the Republic of Uzbekistan according to a national register (Abstract). Diabetologia 2002;45 Suppl 2:A107.

38. Timchenko OI, Kozachok GS, Turos EI, Omel’chenko EM. [The prevalence of diabetes mellitus in children of different regions of Ukraine]. Tsitol Genet 1996; 30:70-73.



134



135

39. Soliman AT, al Salmi IS, Asfour MG. Epidemiology of childhood insulin-dependent diabetes mellitus in the Sultanate of Oman. Diabet Med 1996; 13:582-586.

40. Arab M. Diabetes mellitus in Egypt. World Health Stat Q 1992; 45:334-337.

41. Staines A, Hanif S, Ahmed S, McKinney PA, Shera S, Bodansky HJ. Incidence of insulin dependent diabetes mellitus in Karachi, Pakistan. Arch Dis Child 1997;76:121-123.

42. Ajlouni K, Qusous Y, Khawaldeh AK, Jaddou H, Batiehah A, Ammari F, Zaheri M, Mashal A. Incidence of insulin-dependent diabetes mellitus in Jordanian children aged 0-14 y during 1992-1996. Acta Paediatr Suppl 1999;88:11-13.

43. Shaltout AA, Moussa MA, Qabazard M, Abdella N, Karvonen M, Al Khawari M, Al Arouj M, Al Nakhi A, Tuomilehto J, El Gammal A. Further evidence for the rising incidence of childhood Type 1 diabetes in Kuwait. Diabet Med 2002; 19:522-525.

44. Kadiki OA, Roaeid RB, Bhairi AM, Elamari IM. Incidence of insulin-dependent diabetes mellitus in Benghazi, Libya (1991-1995). Diabetes Metab 1998; 4:424-427.

45. Al-Zyoud M, Al Ali M, Rahim A, Ibrahim M. Insulin dependant diabetes mellitus (IDDM) in children below 13 years of age in Qatar. Diabetes Insights 1997; 4-10.

46. Kulaylat NA, Narchi H. A twelve year study of the incidence of childhood type 1 diabetes mellitus in the Eastern Province of Saudi Arabia. J Pediatr Endocrinol Metab 2000; 13:135-140.

47. Martinucci ME, Curradi G, Fasulo A, Medici A, Toni S, Osovik G, Lapistkaya E, Sherbitskaya E. Incidence of childhood type 1 diabetes mellitus in Gomel, Belarus. J Pediatr Endocrinol Metab 2002; 15:53-57.

48. Bratina NU, Tahirovic H, Battelino T, Krzisnik C. Incidence of childhood-onset Type I diabetes in Slovenia and the Tuzia region (Bosnia and Herzegovina) in the period 1990-1998. Diabetologia 2001; 44 Suppl 3:B27-B31.

49. Skordis N, Hadjiloizou S. Incidence of insulin dependent diabetes mellitus in Greek Cypriot children and adolescents, 1990-1994. J Pediatr Endocrinol Metab 1997; 10:203-207.

50. Svensson J, Carstensen B, Molbak A, Christau B, Mortensen HB, Nerup J, Borch-Johnsen K. Increased risk of childhood type 1 diabetes in children born after 1985. Diabetes Care 2002; 25:2197-2201.

51. Tuomilehto J, Karvonen M, Pitkaniemi J, Virtala E, Kohtamaki K, Toivanen L, Tuomilehto-Wolf E. Record-high incidence of Type I (insulin-dependent) diabetes mellitus in Finnish children. The Finnish Childhood Type I Diabetes Registry Group. Diabetologia 1999; 42:655-660.

52. Roche EF, Menon A, Gill D, Hoey HM. Incidence of type 1 diabetes mellitis in children aged under 15 years in the Republic of Ireland. J Pediatr Endocrinol Metab 2002;15:1191-1194.

53. Schranz AG. Trends in incidence of childhood type 1 diabetes in Malta. Diabetes Care 1998; 21:194-195.

54. Joner G, Stene LC, Sovik O. No increase in incidence of type 1 diabetes in young children in Norway 1989-98 (Abstract). Diabetologia 2000; 43 Suppl 1:A27.

55. Shubnikov E, Choubnikova J. The incidence of insulin-dependent diabetes mellitus in the age-group 0-9 years in Siberia is increasing (Abstract). Diabetologia 1999; 42 Suppl 1:A86.

56. Vlajinac HD, Bojovic BM, Sipetic SB, Adanja BJ, Jarebinski MS, Radmanovic SZ, Zdravkovic DS. Insulin dependent diabetes mellitus: incidence in childhood in Belgrade 1982-92. J Epidemiol Community Health 1995; 49:107-108.

57. Tull ES, Jordan OW, Simon L, Laws M, Smith DO, Vanterpool H, Butler C. Incidence of childhood-onset IDDM in black African-heritage populations in the Caribbean.

The Caribbean African Heritage IDDM Study (CAHIS) Group. Diabetes Care 1997; 20:309-310.

58. Santos J, Carrasco E, Moore A, Perez-Bravo F, Albala C. Incidence rate and spatio-temporal clustering of type 1 diabetes in Santiago, Chile, from 1997 to 1998. Rev Saude Publica 2001; 35:96-100.

59. Ramachandran A, Snehalatha C, Abdul Khader OM, Joseph TA, Viswanathan M. Prevalence of childhood diabetes in an urban population in south India. Diabetes Res Clin Pract 1992; 17:227-231.

60. Craig ME, Howard NJ, Silink M, Chan A. The rising incidence of childhood type 1 diabetes in New South Wales, Australia. J Pediatr Endocrinol Metab 2000; 13:363-372.

61. Tuchinda C, Likitmaskul S, Unachak K, Panamonta O, Patarakijavanich N, Chetthakul T. The epidemiology of type 1 diabetes in Thai children. J Med Assoc Thai 2002;85:648-652.

62. Huen KF, Low LC, Wong GW, Tse WW, Yu AC, Lam YY, Cheung PC, Wong LM, Yeung WK, But BW, Cheung PT, Kwan EY, Karlberg JP, Lee C. Epidemiology of diabetes mellitus in children in Hong Kong: the Hong Kong childhood diabetes register. J Pediatr Endocrinol Metab 2000;13:297-302.

63. Ogle GD, Lesley J, Sine P, McMaster P. Type 1 diabetes mellitus in children in Papua New Guinea. PNG Med J 2001; 44:96-100.

64. Ko KW, Yang SW, Cho NH. The incidence of IDDM in Seoul from 1985 to 1988. Diabetes Care 1994; 17:1473-1475.

65. Lee WW, Ooi BC, Thai AC, Loke KY, Tan YT, Rajan U, Tan CL. The incidence of IDDM in Singapore children. Singapore Med J 1998; 39:359-362.



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2.2 Type 2 Diabetes in the Young

Introduction

It is well recognized that the global burden of type 2 diabetes is both significant and rising, with most of the increase registered in the last two decades. From 2003 to 2025 the worldwide prevalence of diabetes in adults is expected to rise from 5.1% to 6.3% of the adult population, or 194 million to 333 million people.

The largest proportional and absolute increase will occur in developing countries, where the prevalence will rise from 4.2% to 5.6% (see Chapter 1). In India and China the adult diabetic population is expected to double by 2025 to about 73 million in India and 46 million in China. By 2025, type 2 diabetes prevalence is expected to reach 2.8% of the adult population in Africa and 7.2% in South and Central America.

In 1990 it was estimated that 0.2% of the total global diabetic population of 118 million was under 15 years of age (1). The prevalence of type 2 diabetes increases with age and affects some 17% of all 65-74 year olds in the US, and a similar proportion in other countries, such as Australia (2-4). Amongst the young, type 2 diabetes is thought to account for 2-3% of all types of diabetes. This, however, is likely to be an underestimate as, depending on the study, 8-45% of recently diagnosed diabetes in the young in the US is due to type 2 diabetes (5). Data from the third National Health and Nutrition Examination Survey (NHANES III) in the USA indicates that 16 million Americans have type 2 diabetes (2). There are ever increasing reports of type 2 diabetes in children worldwide, with some as young as eight years of age being affected (6). These are mostly in ethnic groups known to be at high risk of

type 2 diabetes. However, there are now also reports of type 2 diabetes occurring amongst Europid (White Caucasoid) teenagers (7). In Japan, the prevalence of type 2 diabetes amongst junior high school children has almost doubled from 7.3 per 100,000 in 1976-80 to 13.9 per 100,000 in 1991-5, with type 2 diabetes now outnumbering type 1 diabetes in Japanese children (8).

Compared to adults, there is little information on type 2 diabetes incidence and prevalence in the young with many surveys being clinic based or case series with a paucity of population-based surveys, particularly outside North America (4) and Japan (8). Similarly, unlike adults, information on the natural history and aetiology of type 2 diabetes in the paediatric age range is also sparse. Other deficiencies include a lack of uniformity in case definition, data collection and follow-up, with the diagnosis often made retrospectively (9). Despite these weaknesses, it is now becoming recognized that type 2 diabetes in children is becoming a global public health issue with potentially serious health outcomes (10). In response to this the American Diabetes Association (ADA) has issued a consensus statement on the screening, diagnosis and treatment of children with type 2 diabetes (5).

The impact of misclassificationThere may be underestimation in type 2 diabetes rates due to a misclassification of the type of diabetes at initial presentation. The presence of diabetic ketoacidosis (DKA), or diabetic coma, is classically a manifestation of type 1 diabetes. However, a number of reports have shown that DKA may occur at initial presentation in patients who are eventually found to have type 2 diabetes. That is, they have elevated C-peptide and an absence of islet cell or anti GAD

• Type 2 diabetes in the young is a global phenomenon, which is on the increase.

• The risk of type 2 diabetes is clearly linked to an increasing prevalence of obesity, which is associated with changing dietary and lifestyle patterns.

• Studies have shown that youth with type 2 diabetes will also develop diabetes-related micro- and macrovascular complications, as with adults.

• The increasing prevalence of type 2 diabetes in the young may be blunted by encouraging more physical activity, and changing dietary habits.

At a glance



136



137

antibodies (4). This type of presentation has also been termed Flatbush (11,12), or atypical diabetes mellitus (ADM) (13).

Unlike type 1 diabetes, most children with type 2 diabetes are asymptomatic, however, approximately a third present with ketonuria (an excess of ketones in the urine) (14). One study found DKA occurred in 4.2% of all patients attending a paediatric clinic, all of whom were of Canadian aboriginal descent (15). A case series examining African American adolescents found that up to 42% presented with ketonuria and 25% with DKA (16). Similarly another report has shown that some 30% of Hispanic youth with type 2 diabetes can present with ketosis (17). Why type 2 diabetes can present with ketosis and in particular why this presentation is more likely to occur in African Americans or Hispanics is not clear (18).

Possible factors in type 2 diabetes development

EthnicityEthnicity is an important factor in type 2 diabetes development in both adults and children with higher rates being

reported in Asians, Hispanics, indigenous peoples (USA, Canada, Australia) and African Americans, with some of the highest rates in the world being observed amongst Pima Indians (19,20). For instance from the period 1967-76 to 1987-96 the prevalence of type 2 diabetes in Pimas increased four tosix-fold, reaching a prevalence of 22.3 per 1,000 for 10-14 year olds and 50.9 per 1,000 for 15-19 year olds by 1992-96 (14).

Obesity, diet and inactivityOn a global basis the rise in type 2 diabetes rates seems to mirror the growth in urbanization and economic development and may be due to maladaptation to a rapidly changing environment (21,22). Closely associated with this is the increase in overweight and obesity.

Obesity has been linked to changing patterns in diet and physical activity levels (23,24). Allied to this are studies from Japan which have demonstrated a parallel rise in type 2 diabetes incidence in children and levels of obesity from 1975 to 1995 (8) as shown in Figure 2.2. Of note is that over this time period there have also been significant increases in fat and animal protein intake among Japanese youth, now mirroring the kind of westernized diets consumed by Japanese-Americans (25).

Dietary changes are not only confined to the home environment. A survey of Californian public schools found that 85% sold fast food, which in turn accounted for 70% of all food sales (26). Of concern is that almost 70% of school districts allowed advertising on campus, with 24% allowing advertising in exchange for cash or equipment. The prevalence of obesity among Japanese children has increased from 5% in 1976 to 8% in 1992 and is similar to data reported from the United States (27). In the USA, the National Longitudinal

Figure 2.2 Annual incidence of type 2 diabetes and prevalenceof obesity among Japanese school children(from Kitagawa T et al, 1998 (8))

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Survey of Youth, which is a prospective cohort study conducted from 1986 to 1998, showed that over this time period the overweight prevalence increased annually by 3.2% in non-Hispanic whites, 5.8% in African Americans and 4.3% in Hispanics. Thus by 1998, 21.5% of African Americans, 21.8% of Hispanics and 12.3% of non-Hispanic whites were overweight (28).

A more recent study of nearly 5,000 children in the USA has shown that during 1999-2000, 15% of 6-19 year olds were overweight, compared to 11% in 1994-98. The biggest rises were recorded in African American and Mexican American adolescents (29). This study also showed that the prevalence of being overweight (BMI ≥25) reached a staggering 65% in US adults. Increasing obesity is also a problem elsewhere, with a recent study from Australia examining children aged 7-15 years, reporting that the prevalence of obesity has increased two to four-fold from 1985 to 1997 (30).

The problem of obesity also extends to developing nations, particularly in the more affluent urban areas. In India, a recent study found that the age adjusted prevalence of being overweight among 13-18 year olds was around 18%. Prevalence rates increased with age and decreasing physical activity and with higher socio-economic status (31). Other factors also thought to be important amongst Indian Asians are low birth weight and insulin resistance (22).

Obesity is also being increasingly observed in indigenous populations, such as the Objiwa-Cree community in Canada, where a study found that 48-51% of children aged 4-19 years have a weight more than the 90th percentile (32). Similar reports have come from other communities such as indigenous Australians, with obesity rates of up to 86% (33). Changes in traditional lifestyles among indigenous communities such as a reduction in hunting and gathering as

well as the adoption of a more sedentary life with a westernized diet are thought to contribute to rising obesity levels (34). Currently some 85% of children with type 2 diabetes are either overweight or obese at diagnosis (5).

Inactivity is one of the major contributors to being overweight. In the developed world, use of computers and increasing time spent in front of the television are some of the factors impacting on activity (24, 29).

A recent longitudinal study showed a marked decline in physical activity in adolescent girls with 56% of black and 31% of white girls aged 16-17 years having no habitual leisure-time physical activity (35). Pregnancy, cigarette smoking, higher BMI and lower parental education at baseline were all associated with a subsequent decline in physical activity. Another study highlighting racial differences in physical activity levels found that white students in the USA have generally higher physical activity levels than other ethnic groups, with boys usually more active than girls, whatever the race (36).

A lifestyle predisposing to obesity and type 2 diabetes seems to characterize families with adolescents who have type 2 diabetes, according to a study by Pinhas-Hamiel et al. Specifically the study showed that members of such families tend to be overweight, inactive and have a tendency to high fat intake and even binge eating (37). Overall in the USA, only 50% of young people aged 12-21 years are regularly involved in physical activity, with some 25% admitting to no physical activity at all. Even in schools there is a decline in physical education, with participation rates down from 41.6% in 1991 to 24.5% in 1995 (38).

Insulin resistanceThe onset of type 2 diabetes is frequently reported around puberty and is thought to coincide with the physiological rise



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in insulin resistance (IR) associated with puberty, where insulin sensitivity may be reduced by as much as 30% (9). Healthy young adolescents compensate for the peri-pubertal rise in IR by increasing insulin secretion as they have normal pancreatic beta cell function. This is not the case with adolescents with type 2 diabetes, where both insulin action and eventually beta cell function are impaired (5).

There appear to be ethnic differences in insulin resistance, with African American children being more hyperinsulinaemic (having high levels of insulin in the blood) and insulin resistant than Europids (39). Similarly, the Bogalusa Heart Study has shown that compared to Europids, African Americans (especially girls) had higher insulin levels and insulin:glucose ratios (40).

Further, a recent study has shown that compared to Europids, African American children have a combination of both lower insulin clearance and higher insulin secretion (41). Using a frequently sampled intravenous glucose tolerance test, both African American and Hispanic children demonstrated greater insulin resistance than Europid children (42). Further analysis showed no ethnic differences in the first phase insulin secretion. However, second phase secretion was significantly higher among Hispanics compared to African Americans, due to lower hepatic insulin clearance among African Americans.

Insulin resistance may be lowered by simple means such as increasing activity levels. This has been demonstrated in obese children and more recently in non-diabetic, normal weight children (43), where the more active children had lower fasting insulin and greater insulin sensitivity.

Acanthosis nigricans Acanthosis nigricans (AN) is thought to be a physical marker of insulin

resistance and is reported to occur in up to 60-90% of young people with type 2 diabetes (19). This seems to be especially true for African Americans and some Native Americans, but so far not demonstrated in other populations such as in Japan (25). However, despite its ubiquitous occurrence in some populations with type 2 diabetes, it should not exclusively be used as a reliable marker of hyperinsulinaemia and insulin resistance.

In a study conducted by Nguyen et al, only 35% of obese children with hyperinsulinaemia had AN, whether black or white (44). Similarly a recent survey of obese Hispanic children (BMI ≥95th percentile) found that there was no association between AN and markers of insulin resistance. In contrast, acanthosis nigricans was associated with BMI but negatively with birth weight (45).

Polycystic ovary syndromePolycystic ovary syndrome (PCOS) is associated with menstrual irregularities, infertility and a state of insulin resistance (46). It is also said to affect up to 5-10% of females in their reproductive years (47) and is thought to predispose to glucose intolerance, with studies showing up to 30-40% being affected by impaired glucose tolerance (IGT) and up to 7-10% with type 2 diabetes (46, 48, 49).It may explain why there are more females with type 2 diabetes amongst adolescents (9, 46).

Family history Many studies show a strong family history among affected youth with 45-80% having at least one parent with diabetes and 74-100% having a first or second degree relative with type 2 diabetes (5, 50). Children with diabetes are also more likely to have a family history of cardiovascular disease (CVD), with one study showing that up to 28% have a positive family history of CVD (51).



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The Bogalusa Heart Study (52) has shown that children of individuals with type 2 diabetes were more likely to be obese and have higher blood pressures, fasting insulin, glucose and triglycerides. In a study among Pima Indians, it was shown that the cumulative incidence of type 2 diabetes was highest in offspring if both parents had diabetes (53). Intrauterine environmentApart from genes, the intrauterine environment may be important as there is evidence of higher rates of type 2 diabetes in offspring of mothers who develop gestational diabetes (GDM) (54). A prospective study by Silverman et al found that the prevalence of IGT in the children of mothers with a diabetic pregnancy increased with time from 1.2% at less than five years of age to 19.3% at 10-16 years of age. This was compared to 2.5% in control subjects.

In addition, higher levels of amniotic fluid insulin (AFI) measured at 33-38 weeks gestation was a strong predictor of later IGT (55). AFI is also thought to correlate with later childhood obesity (56), which in turn may lead to later type 2 diabetes development.

Birth weight is strongly influenced by the intrauterine environment, particularly in diabetic pregnancies, which can be associated with high birth weight (57). Conversely there is also evidence that low birth weight can result in later adult type 2 diabetes development (58).This is most likely due to poor maternal nutrition leading to impaired islet cell development (57, 59), but may also occur in a number of other conditions such as pregnancies complicated by hypertension/pre-eclampsia, which is not an uncommon condition complicating up to 3-5% of all pregnancies (60).

There is a hypothesis that insulin resistance is a product of fetal programming and that gestational metabolic perturbations affect fetal

size, leading to low birth weight and hence later development of insulin resistance (61-64).

Two recent studies challenge this. First, a study examining 300 five-year old British children found that girls were more insulin resistant than boys, and insulin resistance was not related to birth weight (65). The second is a study from Belgium (66), which examined twins aged 18-35 years and found that among twin pairs discordant for birth weight, there was little evidence that the lighter twin had abnormal glucose-insulin metabolism in adult life. Low pre-pregnancy maternal BMI and older maternal age at delivery were independently associated with insulin resistance in the offspring. These findings suggest that maternal factors may be more important than feto-placental factors in determining glucose-insulin metabolism in the offspring.

Methods

A Medline search was conducted using Ovid (medical information service) of papers written in the English language from 1965-2002.

Key words used were: Diabetes, diabetics, non-insulin dependent diabetes, type II diabetes, impaired glucose tolerance, insulin resistance, child, childhood, young, adolescence, overweight, obesity and polycystic ovary syndrome.

The keywords related to diabetes were combined with those related to children and then further combined with terms related to obesity and then finally with polycystic ovary syndrome.

All available studies with relevant data have been included and have been grouped by study type (population based, case reports, case series and clinic based). These have further been divided into the IDF regions of Africa (AFR), Eastern Mediterranean and Middle East (EMME), Europe (EUR), North



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America (NA), South and Central America (SACA), South-East Asia (SEA) and Western Pacific (WP).

Studies which include subjects 20 years of age and under have been selected. However, data are presented for studies which have given higher age ranges but which include subjects less than 20 years of age within those ranges. In these cases it has not been possible to separate those under 20 from the information given.

Most papers have been published in peer review journals but a number are in abstract form. These are no more than three years old.

Results

Results are reported as presented in the original papers, unlike in the adult diabetes and childhood type 1 diabetes sections (see Chapters 1.1 and 2.1 respectively) in which figures have been calculated for the national population.

In some of the studies used, the prevalence of type 2 diabetes in the general population (child and adolescent) was determined from a representative population-based sample (67). However, many studies have simply reported a series of cases, sometimes supplemented by a calculation of the prevalence in the general population, using estimated figures for the size of the population from which the cases were drawn (68), or examined only a specific sub-population, such as from a diabetes registry (69-72) or an obesity clinic (73-77).

Population-based studiesIn general, it is very difficult to compare the studies due to wide differences in study design. Population-based studies were found from all regions except Europe, and South and Central America. Apart from studies from Japan (8) and Saudi Arabia (78), many of the other papers only examined relatively small numbers of people. In the case

of Africa (79-82), studies found are few and in most examples conducted some 15 years ago.

AfricaFive studies were found and included two from west Africa (79, 81) and three from east Africa (80, 82, 83). All but one, which looked only at Indians (83), showed a zero or low prevalence of diabetes. Apart from the study examining Indians, all the others were conducted in the 1980s. Therefore taking into account the current information on type 2 diabetes rates around the world, the results for Africa are probably an underestimate and may not represent the contemporary situation.

Eastern Mediterranean andMiddle EastA large study of some 25,377 individuals aged 2-77 years was conducted in Saudi Arabia by el-Hazmi et al (78). The figures for those less than 29 years of age have been selected. In the under-14 year age group, IGT prevalence was double that of type 2 diabetes (0.25% versus 0.12%). The opposite was true for the 14-29 year age group, where type 2 diabetes outnumbered IGT almost 3:1 (0.79% for type 2 diabetes versus 0.21% for IGT).

North AmericaUnlike other regions, data from North America on type 2 diabetes and IGT prevalence are more extensive and recent. The ethnicity of the study subjects is diverse with many including African Americans, Mexican Americans and non-Hispanic white Americans in the same study.

A study from Texas in 1981 examining 15-24 year old Mexican Americans found no type 2 diabetes in males and only a low prevalence of 0.4% in females (84). By 2002, a study surveying Mexican American fourth graders found not only an overall type 2 diabetes prevalence of 0.3%, but also cases of IGT (0.14%) and impaired fasting glucose (IFG)



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(0.14%) (85). In contrast another study has reported relatively high rates of type 2 diabetes (1.5%) and IFG (10.8%) in a population of Europids and African Americans (86). This study, however, is ongoing with some 50% of recruited subjects still to have an oral glucose tolerance test (OGTT). The true rates of IFG and type 2 diabetes may change once the full picture is known.

North America:Indigenous/First NationA study, which examined Pima Indians since 1967, demonstrated rising rates of glucose intolerance over time, as well as a female preponderance (87). From 1967-76 to 1987-96 the prevalence of type 2 diabetes markedly increased from 2.4% in males and 2.7% in females to 3.8% in males and 5.3% in females. A female preponderance of type 2 diabetes of almost 4:1 among Navajo subjects was also found in another study (88).

A study of American Indian and Alaskan Native adolescents reported that the prevalence of type 2 diabetes increased by 68% from 1990 to 1998 among those aged 15-19 years (0.32% to 0.54%) (20). In addition although the prevalence of type 2 diabetes was higher among females, the relative increase over this time period was greater among males (0.23% to 0.41% for males versus 0.42% to 0.68% for females). Even though the overall prevalence among under-15 year olds remained the same at 0.12%, there was regional variation, and Alaska recorded the biggest rise of 114% (0.04% to 0.09%).

From Canada, greater rates for IFG (2.6%) compared to type 2 diabetes (1.1%) were found among Cree-Objiway subjects, but no female preponderance (89).

South-East AsiaStudies in the South-East Asian Region were identified from India (90) and Bangladesh (91, 92).

A study from Chenai in south India (90), conducted eight years ago, found a zero prevalence rate for type 2 diabetes. This may, however, be an underestimate given the recent worldwide rise in type 2 diabetes in children.

Western PacificStudies from Japan (8) and Taiwan (93) were identified in the Western Pacific area. The largest study reported is from Japan (8), with some seven million youth being studied between 1976 and 1997. Over this time type 2 diabetes incidence increased 10-fold in primary school children: 0.2 per 100,000 per year from 1976 to 1980 versus 2.0 per 100,000 per year from 1991 to 1995. Similarly over the same time period, type 2 diabetes incidence doubled among junior high school children: 7.3 versus 13.9 per 100,000 per year.

A cohort of indigenous Australian children aged 7-18 years was surveyed in 1989 and again in 1994. Over the five years, the prevalence of type 2 diabetes almost doubled to 1.3%, while that for IGT increased almost seven-fold to 8.1% (94). At the follow-up, 18% of the population were overweight or obese. In addition one-third of the children had elevated cholesterol levels, with almost half reporting alcohol use and smoking.

In contrast to the Australian study, the Tongan study (95) examining 15-19 year olds found no glucose intolerance in that population.

Case reportsAlthough there are case reports of type 2 diabetes in the young from a number of countries (96), only two (both from the UK) have been included. These were included for two reasons. First, there has so far been little available data from the UK and secondly, one of the reports includes Europids (7), who until now have been thought to be at low risk of developing childhood type 2 diabetes.



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In the other report (97), all the subjects were female and of Indian/Pakistani Asian or Arab origin. They were all obese and with a strong family history of diabetes. Three out of the eight children had polycystic ovary syndrome. The finding of being overweight and having a strong family history is also a feature in the report by Drake et al (7). However, here the subjects are all Europid, with only one having PCOS.

Clinic/register-based studiesClinic and register-based studies make up the largest group of studies conducted on youth IGT and type 2 diabetes. They reveal type 2 diabetes occurring in children as young as under the age of five years (98). In addition, they have demonstrated a female preponderance (33, 70, 71, 99), strong family history (70, 100, 101), obesity (6,67,70,99-101) and acanthosis nigricans (6,67,99,101).

These studies have also shown an increase in incidence rates. One study (69) found that type 2 diabetes incidence rates rose by 9% per year from 1985 to 1994, reaching 3.8 per 100,000 per year by 1990-94, while another study (101) found a 10-fold increase in type 2 diabetes incidence rates from 0.7 per 100,000 per year in 1982 to 7.2 per 100,000 per year in 1994. Yet another study (102) reported that in 1994, 9.4% of new cases of diabetes were due to type 2 diabetes, rising to 20% by 1998. Similarly, Likitmaskul et al (67) reported a rise from 5% to 17% from 1997 to 1999 in the proportion with type 2 diabetes referred to a diabetic clinic.

A study from 1989 to 2001 from a clinic in Hungary (103) also reported rising incidence rates over time with 57% of all type 2 diabetes and 77% of all IGT

Profile: Chul Hee Han

Chul Hee Han, 15, was born in Seoul, South Korea and moved to Australia in 1994 when he was seven years old. James, as his friends call him, was diagnosed with type 2 diabetes at 14 when his mother noticed that he was gaining weight, especially around his middle.

His only medical problem had been an operation at the age of five months for a twisted bowel but apart from this, his childhood had been a healthy one. James’ father died when he was only four years old and he has little memory of his father. James’ mother tells of her husband who was a big man and who developed type 2 diabetes at the age of 28. Little treatment was given and he died of a heart attack at 32 years of age. The family then moved to Australia to be with relatives, and became Australian citizens.

On noticing his weight gain, James’ mother wanted to have him checked out for diabetes because of the family history. This led to an oral glucose tolerance test being done and the two-hour blood glucose level of 17.2mmol/l was diagnostic of diabetes. Other tests ruled out the possibility of this being type 1 diabetes and James was started on treatment for



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diagnosed in the last six years of the 13-year study.

Incidence rates also rise with age, with one study (98) demonstrating that 15-19 year olds with rates of 5.9 per 100,000 per year have three times the rate compared to 10-14 year olds with rates of 1.8 per 100,000 per year.

Although a population-based study from south India eight years ago (90) found no cases of diabetes, a very recent clinic-based study (99), also from Chenai, diagnosed 18 cases of type 2 diabetes among children aged 9-15 years. Common factors noted in this group were female preponderance, family history and obesity.

A number of studies have pre-selected subjects for obesity, AN or PCOS. One study (74) in 1965 found an

IGT prevalence of 23% in subjectspre-selected for obesity. More recently, Sinha et al (76) selected subjects whose weight was more than the 95th percentile for age and sex attending an obesity clinic and found similar rates of IGT: 25% in 4-10 year olds and 21% in 11-18 year olds.

A study by Ciampalini et al (77) from Italy have reported similar rates of 24%, but others have not been able to reproduce these results from their study population of obese youth, with Uwaifo et al (75) from USA and Invitti et al (104) from Italy reporting much lower rates of 4.1% and 4.5% respectively for IGT. Another study from Western Pacific also found lower rates of IGT (4.3%) in young obese subjects (73).

The cause for the discrepancy in results is unknown but has been suggested to

type 2 diabetes. He now does three blood tests a day and takes a tablet to control his blood glucose levels. He goes to the clinic every three months for a check-up. Says James: “I worry that my diabetes may get worse and that complications may occur. The blood glucose tests are not much of a bother and I have learnt to take my tablets every day before breakfast.”

James has continued life as before as far as school and sport is concerned, he does everything that his friends do. But he has become very careful when it comes to eating. His mother packs his lunch and he does not buy food from the tuck shop. He only rarely has fast food and avoids any junk food. “I don’t do any special sports nor do I weigh myself at home but I look after myself,” says James. “I think about my diabetes almost every time I eat and try not to eat too much. My teachers don’t know that I have diabetes and I have only told my two best friends.”

James, who is in year 10 of high school, attends a selective school for high achievers in an outer suburb of Sydney. He has known that he wants to become a dentist all his life. His mother and his relatives worry about James. “We are careful with food and stick to a Korean diet. We only choose the low fat recipes and use olive oil for cooking,” says his mother. “We pray for the diabetes to go away.”



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be due to referral bias in the study by Sinha et al (76) in favour of children who are extremely obese (75). Another reason could be the contribution of PCOS. Of note is that 40% of the subjects with IGT in Sinha et al’s (76) study had PCOS. In addition Sinha et al reported a type 2 diabetes prevalence of 3.6%, all of whom were non-Hispanic Black or Hispanic, while Invitti et al noted a much lower prevalence of 0.1%, among Europids.

Studies pre-selecting for PCOS have demonstrated significant rates of glucose intolerance. One study (47) reported an IGT prevalence of 26.9% while another (105) found a rate of 13%. However, both studies report lower prevalences of type 2 diabetes of 3.7% and 0.0% respectively.

Brickman et al (106) have conducted one of the few studies pre-selecting for the presence of AN and report an IGT prevalence of 24% in subjects with AN. They suggest that children with AN may benefit from diabetes screening and early intervention. However, AN is not a universal phenomenon in children with type 2 diabetes, and has so far not been noted to any degree among the large studies surveying Japanese youth (8).

Diabetic complications

As with adults it is expected that youth with type 2 diabetes will also develop diabetes-related micro- and macrovascular complications. This was reported recently in a study from Canada (107), where subjects who developed type 2 diabetes as children were then surveyed as young adults, aged between 18 and 33 years. Of the 51 subjects, 9% had died, 6% were on dialysis while one had a toe amputation and one was blind.

Another follow-up study from Japan (108) compared those with type 1 and type 2 diabetes diagnosed at under 30 years of age for development of nephropathy. After 30 years of diabetes, 44% of those

with type 2 and 20.2% of those with type 1 had nephropathy.

Yet another study (109) looked at incidence of retinopathy and nephropathy among Pima Indians diagnosed with type 2 diabetes at under 20 years of age (youth), 20-39 years (young adults) and 40-59 years of age (older). At less than five years duration of type 2 diabetes, nephropathy was present in all age groups (incidence/1,000 person years: 13/1,000 youth, 8/1,000 young adults and 7/1,000 older). However, retinopathy only appeared among those with youth onset diabetes after 5 to 10 years duration (incidence/1,000 person years: 10/1,000 youth, 29/1,000 young adults and 35/1,000 older).

These studies have important implications in that they highlight the risk of complications occurring at a relatively young age and as in the case of the Pima Indian study, that these complications can occur relatively soon after diagnosis. This will place a significant burden on health budgets as well as society as a whole. This is particularly so because these people would be entering their peak working and earning capacity. Early detection and intervention is therefore essential to reduce the risk of future complications.

Discussion

Compared to adults there is a paucity of information on both the epidemiology and natural history of type 2 diabetes in the young. This needs to be urgently addressed given the potential threat of an explosion in childhood type 2 diabetes.

There are only a few large scale population-based studies focusing on youth with type 2 diabetes. Most of the information available comes from case series or clinic-based studies, together with some case reports. On a global basis, the majority of data come from



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developed countries, particularly North America and Japan, with a distinct lack of information from many regions in the world, particularly from Africa and South America.

Notably, there is also a lack of standardization in study methods, with many surveys only examining small numbers of subjects, as well as using different diagnostic methods and criteria. In addition some studies have only looked at very high risk subjects, such as those with PCOS (47), presence of AN (106), or obesity (76). This can make comparisons between studies difficult.

Conclusion

Despite apparent deficiencies in research, we can still make some valid conclusions regarding type 2 diabetes in the young:

1 It is a global phenomenon, which is on the increase.

2 Children are being affected in both developed and developing nations.

3 Reports are appearing that show its existence in populations hitherto thought not to be at risk, such as British Europids.

4 The risk of type 2 diabetes is clearly linked to an increasing prevalence of obesity, which is in turn associated with changing dietary and lifestyle patterns. In particular an increase in fatty foods as well as a reduction in activity levels both at home and in the school. The change in lifestyle is a worldwide phenomenon, occurring in both developed and emerging nations, where it is most prevalent in urban areas. In these nations as well as among indigenous communities residing in developed nations, there seems to be a gradual abandonment of traditional ways of living in favour of a ‘westernized’ lifestyle.

5 A number of studies have noted an association between type 2 diabetes and polycystic ovary syndrome. Not all studies look for this condition

and it is possible that it may partly explain the female preponderance in youth onset type 2 diabetes. Future work may need to address the issue of PCOS, especially since it is amenable to treatment.

6 Studies have shown that youth with type 2 diabetes will also develop diabetes-related micro- and macrovascular complications, as with adults. These studies have important implications in that they highlight the risk of complications occurring at a relatively young age, which will place a significant burden on health budgets as well as society as a whole.

7 The increasing prevalence of type 2 diabetes in the young may be blunted by encouraging more physical activity and changing dietary habits.

8 Interventional programmes should be implemented to address the underlying cause, with an emphasis on diet, weight, exercise and lifestyle issues.

It is recognized that in an ideal world it would be possible to implement the proposed recommendations. In reality this may be difficult given the poor economic condition that many have to endure and the already tight health budgets governments have to deal with. However, many regions of the world are progressing economically and hence becoming more urbanized.

A consequence of urbanization is the parallel emergence of cardiovascular disease and diabetes, which hitherto, was mainly a problem of the developed world (see Chapter 3). Governments, therefore, will be forced to deal with the problem of type 2 diabetes in children. As such, it would be better to address the problem as a public health issue under the heading of primary care and prevention, rather than dealing with the consequences of an entrenched condition and its complications in a young population.



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Prevalence (%) DM incidence

Region Country Author Year of study Ethnicity Age (yrs) Diagnostic method Sample size DM IGT per 100,000 per year

AFR

Mali Fisch et al, 198781 1984-1985 Mixed tribal 15-24 FCG 2,558 0.39

Tanzania McLarty et al, 198982 1988 African 15-24 OGTT 1,178 0.4 6.7

Ahren et al, 198480 1982-1983 African ≤19 OGTT 1,327 0.15

Ramaiya et al, 199183 Indian 15-24 OGTT 156 Male 0.0Female 0.0

Male 2.3 Female 4.2

Togo Teuscher et al, 198779 1987 Mixed tribal <20 OGTT 864 0.0

EMME

Saudi Arabia el-Hazmi et al, 200078 1998 Arab 2-29 OGTT 9,917 (<14) <14 = 0.1214-29 = 0.79

<14 = 0.2514-29 = 0.21

NA

Canada Dean et al, 199889 1996-1997 Cree-Ojibway 4-19 FBG 717 1.1 2.6

Delisle et al, 1993110 1989 Algonquin 15-20 OGTT 106 1.9

Harris et al, 1997111 1996 Cree-Ojibway 10-19 OGTT 244 3.0 10.0

USA Harrell et al, 200286 2001-2002 Caucasian 69% African American 24%

10-15 FPG 668 1.5 10.8

Hale et al, 200285 2002 Mostly Mexican American

4th grade OGTT 1,417 0.3 0.14

Hanis et al, 199684 1981-2002 Mexican American 15-24 OGTT 729 Male 0.0Female 0.4

Chavez et al, 2002112 2002 N/A 15-19 RBG 778 0.13

Freedman et al, 199788 1991-1992 Navajo 12-19 OGTT 160 Male 3.0Female 13.0

Male 3.0Female 13.0

Dabelea et al, 199887 1987-1996 Pimas 5-19 OGTT 3,098 5-9 years: Male 0.0 Female 0.0

10-14 years: Male 1.5Female 2.9


Acton et al, 200220 1990-1998 American Indian and Alaskan native

≤19 Chart review <15 years: 0.1215-19 years: 0.54

Male: 0.41Female: 0.68

Kim et al, 1999113 1999 Navajo 13-20 OGTT 234 0.42 3.4

SEA

Bangladesh Sayeed et al, 199592 1995 South Asian rural 15-29 OGTT 371 0.5 5.7

Sayeed et al, 199791 1997 South Asian urban 15-19 OGTT 271 0.06 0.04

India Bai et al, 199590 1994 South Asian 5-19 OGTT 3,515 0.0

WP

Australia Braun et al, 199694 1989 Indigenous 7-18 OGTT 74 1.3 8.1

Australia Daniel et al, 1999114 1987-1995 Indigenous 15-24 OGTT 1,070

Japan Kitagawa et al, 19988 1991-1995 Japanese <15 Annual urinalysis.If glycosuria x2, then OGTT

386,000 Primary school 2Junior high school +13.9

Taiwan Chuang et al, 200293 1993-1999 South-East Asian 6-18 Semi-annual urinalysis.If glycosuria, then OGTT

3x106 Male 0.009Female 0.01

Tonga Colagiuri et al, 200295 1998-2000 Polynesian 15-19 OGTT 59 0.0

Table 2.15Type 2 diabetes and impaired glucose tolerance in the young – population-based studies

DM type 2 diabetesFBG fasting blood glucoseFCG fasting capillary glucoseFPG fasting plasma glucoseIGT impaired glucose toleranceN/A not availableOGTT oral glucose tolerance testRBG random blood glucose



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Region Country Author Year of study Ethnicity Age (yrs) Diagnostic method Sample size DM IGT per 100,000 per year

AFR

Mali Fisch et al, 198781 1984-1985 Mixed tribal 15-24 FCG 2,558 0.39

Tanzania McLarty et al, 198982 1988 African 15-24 OGTT 1,178 0.4 6.7

Ahren et al, 198480 1982-1983 African ≤19 OGTT 1,327 0.15

Ramaiya et al, 199183 Indian 15-24 OGTT 156 Male 0.0Female 0.0

Male 2.3 Female 4.2

Togo Teuscher et al, 198779 1987 Mixed tribal <20 OGTT 864 0.0

EMME

Saudi Arabia el-Hazmi et al, 200078 1998 Arab 2-29 OGTT 9,917 (<14) <14 = 0.1214-29 = 0.79

<14 = 0.2514-29 = 0.21

NA

Canada Dean et al, 199889 1996-1997 Cree-Ojibway 4-19 FBG 717 1.1 2.6

Delisle et al, 1993110 1989 Algonquin 15-20 OGTT 106 1.9

Harris et al, 1997111 1996 Cree-Ojibway 10-19 OGTT 244 3.0 10.0

USA Harrell et al, 200286 2001-2002 Caucasian 69% African American 24%

10-15 FPG 668 1.5 10.8

Hale et al, 200285 2002 Mostly Mexican American

4th grade OGTT 1,417 0.3 0.14

Hanis et al, 199684 1981-2002 Mexican American 15-24 OGTT 729 Male 0.0Female 0.4

Chavez et al, 2002112 2002 N/A 15-19 RBG 778 0.13

Freedman et al, 199788 1991-1992 Navajo 12-19 OGTT 160 Male 3.0Female 13.0

Male 3.0Female 13.0

Dabelea et al, 199887 1987-1996 Pimas 5-19 OGTT 3,098 5-9 years: Male 0.0 Female 0.0



Acton et al, 200220 1990-1998 American Indian and Alaskan native

≤19 Chart review <15 years: 0.1215-19 years: 0.54

Male: 0.41Female: 0.68

Kim et al, 1999113 1999 Navajo 13-20 OGTT 234 0.42 3.4

SEA

Bangladesh Sayeed et al, 199592 1995 South Asian rural 15-29 OGTT 371 0.5 5.7

Sayeed et al, 199791 1997 South Asian urban 15-19 OGTT 271 0.06 0.04

India Bai et al, 199590 1994 South Asian 5-19 OGTT 3,515 0.0

WP

Australia Braun et al, 199694 1989 Indigenous 7-18 OGTT 74 1.3 8.1

Australia Daniel et al, 1999114 1987-1995 Indigenous 15-24 OGTT 1,070

Japan Kitagawa et al, 19988 1991-1995 Japanese <15 Annual urinalysis.If glycosuria x2, then OGTT

386,000 Primary school 2Junior high school +13.9

Taiwan Chuang et al, 200293 1993-1999 South-East Asian 6-18 Semi-annual urinalysis.If glycosuria, then OGTT

3x106 Male 0.009Female 0.01

Tonga Colagiuri et al, 200295 1998-2000 Polynesian 15-19 OGTT 59 0.0



148



149

Region Country AuthorYear of study Ethnicity Age (yrs)

Diagnostic method

Type 2 cases (No.)

EUR

United Kingdom Ehtisham et al, 200097 2000 South Asian/Arab 9-16 Chart review Female 8.0

United Kingdom Drake et al, 20027 2002 Caucasian 13-15 Chart review Male 3.0Female 1.0

Table 2.16Type 2 diabetes in the young – case reports

Type 2 cases Prevalence * DM incidence *

Region Country Author Year of study Ethnicity Age (yrs) Diagnostic method Source of cases (No.) (%) per 100,000 per year

EMME

Libya Kadiki et al, 199698 1981-1990 Arab ≤19 Chart review Diabetes register and hospital clinic

0-4 years: 05-9 years: 1

10-14 years: 1115-19 years: 30

N/A 5-9 years: 0.110-14 years: 1.815-19 years: 5.9

United Arab Emirates Punnose et al, 2002115 1990-1998 Arab ≤18 Chart review Hospital clinic Male 1Female 4

N/A

EUR

United Kingdom Ehtisham et al, 200171 1993 Mixed <18 Chart review Paediatric clinics Male 2Female 15

0.004 N/A

Ehtisham et al, 200171 1999-2000 Mixed <18 Chart review Paediatric clinics 4 N/A DM 1.52

NA

Canada Harris et al, 199670 1978-1994 Cree-Ojibway <16 Chart review Diabetes register Male 1Female 14

Male 0.07Female 0.42

Total 0.25

N/A

Dean, 1998116 1996 First Nation 5-14 Chart review Diabetes register 15 0.77 N/A

USA Jones, 1998117 1993-1998 Mexican American 67% 5-17 OGTT or Sustacal challenge test Medical centre and clinics 18 N/A N/A

Lipton et al, 200269 1985-1994 African AmericanLatino

≤17 Chart review Diabetes register N/A N/A DM 3.8

Pihoker et al, 19986 1998-1995 African AmericanCaucasianHispanic

8-21 Chart review Diabetes clinic 3712

1

N/A N/A

Macaluso et al, 2002102 1994-1998 HispanicAfrican American

5-19 Chart review Diabetes clinic 92 14 N/A

WP

Australia Davis et al, 200233 1990-2002 Mixed <15 Chart review Paediatric centre Male 12Female 25

N/A N/A

Sinha et al, 200050 1999-2000 Indigenous 6-16 Chart review/OGTT Diabetes clinic 20 N/A N/A

Table 2.17Type 2 diabetes in the young – case series

* Calculated using an estimate of the total at-risk population.

DM type 2 diabetes N/A not available OGTT oral glucose tolerance test



148



149

Type 2 cases Prevalence * DM incidence *

Region Country Author Year of study Ethnicity Age (yrs) Diagnostic method Source of cases (No.) (%) per 100,000 per year

EMME

Libya Kadiki et al, 199698 1981-1990 Arab ≤19 Chart review Diabetes register and hospital clinic

0-4 years: 05-9 years: 1

10-14 years: 1115-19 years: 30

N/A 5-9 years: 0.110-14 years: 1.815-19 years: 5.9

United Arab Emirates Punnose et al, 2002115 1990-1998 Arab ≤18 Chart review Hospital clinic Male 1Female 4

N/A

EUR

United Kingdom Ehtisham et al, 200171 1993 Mixed <18 Chart review Paediatric clinics Male 2Female 15

0.004 N/A

Ehtisham et al, 200171 1999-2000 Mixed <18 Chart review Paediatric clinics 4 N/A DM 1.52

NA

Canada Harris et al, 199670 1978-1994 Cree-Ojibway <16 Chart review Diabetes register Male 1Female 14

Male 0.07Female 0.42

Total 0.25

N/A

Dean, 1998116 1996 First Nation 5-14 Chart review Diabetes register 15 0.77 N/A

USA Jones, 1998117 1993-1998 Mexican American 67% 5-17 OGTT or Sustacal challenge test Medical centre and clinics 18 N/A N/A

Lipton et al, 200269 1985-1994 African AmericanLatino

≤17 Chart review Diabetes register N/A N/A DM 3.8

Pihoker et al, 19986 1998-1995 African AmericanCaucasianHispanic

8-21 Chart review Diabetes clinic 3712

1

N/A N/A

Macaluso et al, 2002102 1994-1998 HispanicAfrican American

5-19 Chart review Diabetes clinic 92 14 N/A

WP

Australia Davis et al, 200233 1990-2002 Mixed <15 Chart review Paediatric centre Male 12Female 25

N/A N/A

Sinha et al, 200050 1999-2000 Indigenous 6-16 Chart review/OGTT Diabetes clinic 20 N/A N/A



150



151


Region Country Author Year of study Ethnicity Age (yrs) Population Diagnostic method Sample size DM IGT per 100,000 per year

EUR

Hungary Korner, 2002103 1989-2001 Caucasian ≤19 Diabetic clinic Chart review 524 10.7 N/A

Italy Invitti et al, 2003104 1994-2001 Caucasian 6-18 Obese OGTT 710 0.1 4.5 N/A

Ciampalini et al, 200277 N/A Caucasian 3-19 Obese OGTT 191 0.5 12.6 N/A

United Kingdom Barrett et al, 2002118 2000 Mixed <16 Paediatric diabetes centres Questionnaire of paediatric centres in UK

15,255 0.2 N/A

NA

USA Paulsen et al, 196874 1965 Mixed 4-16 Obese OGTT 66 0.0 23.0 N/A

Legro et al, 1999105 1983-1991 Mixed 14-20 PCOS – all female OGTT 16 0.0 13.0 N/A

Pinhas-Hamiel et al, 1996101 1984-1994 African American 68%White 32%

≤19 N/A N/A N/A 7.2

Neufeld et al, 199817 1990-1994 Mexican American <17 Diabetic clinic Chart review 55 31.0 N/A

Uwaifo et al, 200275 1996-2002 CaucasianAfrican American

6-11 Overweight BMI at ≤95th percentile

OGTT Overweight 121 Not overweight 104

0.00.0

4.10.0

N/A

Sinha et al, 200276 1999-2001 Caucasian 58%Hispanic 19%African American 23%

4-18 Obesity clinic OGTT 4-10 years: 5511-18 years: 112

0.03.6

24.023.0

N/A

Brickman et al, 2002106 1999-2002 Mixed Mean 11.9 Presence of AN OGTT 33 3.0 24.0 N/A

Palmert et al, 200247 2001 Mixed 13-19 PCOS – all female OGTT 27 3.7 26.9 N/A

SEA

India Ramachandran et al, 200399 2002-2003 Indian Asian 9-15 Diabetes clinic Chart review 18 0.0

WP

Singapore, Republic of Lee et al, 199973 1999 Malay 42%Indian 28%Chinese 33%

≤15 Obese children in a paediatric clinic

OGTT 23 17.0 4.3 N/A

Thailand Likitmaskul et al, in press67 1997-1999 South-East Asian <15 Diabetic clinic Chart review 39 17.9 N/A

New Zealand McGrath et al, 199972 1978-1998 Maori DM onset before 30 Diabetes register Chart review 51 55.0 N/A

Table 2.18Type 2 diabetes and impaired glucose tolerance in the young – clinic-based studies

AN acanthosis nigricansBMI body mass index (kg/m²)DM type 2 diabetesIGT impaired glucose toleranceN/A not availablePCOS polycystic ovary syndromeOGTT oral glucose tolerance test



150



151


Region Country Author Year of study Ethnicity Age (yrs) Population Diagnostic method Sample size DM IGT per 100,000 per year

EUR

Hungary Korner, 2002103 1989-2001 Caucasian ≤19 Diabetic clinic Chart review 524 10.7 N/A

Italy Invitti et al, 2003104 1994-2001 Caucasian 6-18 Obese OGTT 710 0.1 4.5 N/A

Ciampalini et al, 200277 N/A Caucasian 3-19 Obese OGTT 191 0.5 12.6 N/A

United Kingdom Barrett et al, 2002118 2000 Mixed <16 Paediatric diabetes centres Questionnaire of paediatric centres in UK

15,255 0.2 N/A

NA

USA Paulsen et al, 196874 1965 Mixed 4-16 Obese OGTT 66 0.0 23.0 N/A

Legro et al, 1999105 1983-1991 Mixed 14-20 PCOS – all female OGTT 16 0.0 13.0 N/A

Pinhas-Hamiel et al, 1996101 1984-1994 African American 68%White 32%

≤19 N/A N/A N/A 7.2

Neufeld et al, 199817 1990-1994 Mexican American <17 Diabetic clinic Chart review 55 31.0 N/A

Uwaifo et al, 200275 1996-2002 CaucasianAfrican American

6-11 Overweight BMI at ≤95th percentile

OGTT Overweight 121 Not overweight 104

0.00.0

4.10.0

N/A

Sinha et al, 200276 1999-2001 Caucasian 58%Hispanic 19%African American 23%

4-18 Obesity clinic OGTT 4-10 years: 5511-18 years: 112

0.03.6

24.023.0

N/A

Brickman et al, 2002106 1999-2002 Mixed Mean 11.9 Presence of AN OGTT 33 3.0 24.0 N/A

Palmert et al, 200247 2001 Mixed 13-19 PCOS – all female OGTT 27 3.7 26.9 N/A

SEA

India Ramachandran et al, 200399 2002-2003 Indian Asian 9-15 Diabetes clinic Chart review 18 0.0

WP

Singapore, Republic of Lee et al, 199973 1999 Malay 42%Indian 28%Chinese 33%

≤15 Obese children in a paediatric clinic

OGTT 23 17.0 4.3 N/A

Thailand Likitmaskul et al, in press67 1997-1999 South-East Asian <15 Diabetic clinic Chart review 39 17.9 N/A

New Zealand McGrath et al, 199972 1978-1998 Maori DM onset before 30 Diabetes register Chart review 51 55.0 N/A



152



153

References

1. King H, Aubert RE, Herman WH. Global burden of diabetes, 1995-2025: prevalence, numerical estimates, and projections. Diabetes Care 1998; 21:1414-1431.

2. Harris MI, Flegal KM, Cowie CC, Eberhardt MS, Goldstein DE, Little RR, Wiedmeyer HM, Byrd-Holt DD. Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults. The Third National Health and Nutrition Examination Survey, 1988-1994. Diabetes Care 1998; 21:518-524.

3. Dunstan DW, Zimmet PZ, Welborn TA, De Courten MP, Cameron AJ, Sicree RA, Dwyer T, Colagiuri S, Jolley D, Knuiman M, Atkins R, Shaw JE. The rising prevalence of diabetes and impaired glucose tolerance: the Australian Diabetes, Obesity and Lifestyle Study. Diabetes Care 2002; 25:829-834.

4. Callahan ST, Mansfield MJ. Type 2 diabetes mellitus in adolescents. Curr Opin Pediatr 2000; 12:310-315.

5. Anonymous. Type 2 diabetes in children and adolescents. American Diabetes Association. Diabetes Care 2000;23:381-389.

6. Pihoker C, Scott CR, Lensing SY, Cradock MM, Smith J.Non-insulin dependent diabetes mellitus in African-American youths of Arkansas. Clin Pediatr (Phila) 1998;37:97-102.

7. Drake AJ, Smith A, Betts PR, Crowne EC, Shield JP. Type 2 diabetes in obese white children. Arch Dis Child 2002; 86:207-208.

8. Kitagawa T, Owada M, Urakami T, Yamauchi K. Increased incidence of non-insulin dependent diabetes mellitus among Japanese schoolchildren correlates with an increased intake of animal protein and fat. Clin Pediatr (Phila) 1998; 37:111-115.

9. Dabelea D, Pettitt DJ, Jones KL, Arslanian SA. Type 2 diabetes mellitus in minority children and adolescents. An emerging problem. Endocrinol Metab Clin North Am 1999; 28:709-729.

10. Fagot-Campagna A, Narayan KM, Imperatore G. Type 2 diabetes in children. BMJ 2001; 322:377-378.

11. Banerji MA, Chaiken RL, Huey H, Tuomi T, Norin AJ, Mackay IR, Rowley MJ, Zimmet PZ, Lebovitz HE. GAD antibody negative NIDDM in adult black subjects with diabetic ketoacidosis and increased frequency of human leukocyte antigen DR3 and DR4. Flatbush diabetes. Diabetes 1994; 43:741-745.

12. Banerji MA. Impaired beta-cell and alpha-cell function in African-American children with type 2 diabetes mellitus – “Flatbush diabetes”. J Pediatr Endocrinol Metab 2002;15 Suppl 1:493-501.

13. Rosenbloom AL, Joe JR, Young RS, Winter WE. Emerging epidemic of type 2 diabetes in youth. Diabetes Care 1999; 22:345-354.

14. Fagot-Campagna A, Pettitt DJ, Engelgau MM, Burrows NR, Geiss LS, Valdez R, Beckles GL, Saaddine J, Gregg EW, Williamson DF, Narayan KM. Type 2 diabetes among North American children and adolescents: an epidemiologic review and a public health perspective. J Pediatr 2000; 136:664-672.

15. Sellers EA, Dean HJ. Diabetic ketoacidosis: a complication of type 2 diabetes in Canadian aboriginal youth. Diabetes Care 2000; 23:1202-1204.

16. Pinhas-Hamiel O, Dolan LM, Zeitler PS. Diabetic ketoacidosis among obese African-American adolescents with NIDDM. Diabetes Care 1997; 20:484-486.

17. Neufeld ND, Raffel LJ, Landon C, Chen YD, Vadheim CM. Early presentation of type 2 diabetes in Mexican-American youth. Diabetes Care 1998; 21:80-86.

18. Pinhas-Hamiel O. Type 2 diabetes: not just for grownups anymore. (children are now being diagnosed with type 2 diabetes). Contemporary Pediatrics 2001.

19. Scott CR, Smith JM, Cradock MM, Pihoker C. Characteristics of youth-onset noninsulin-dependent diabetes mellitus and insulin-dependent diabetes mellitus at diagnosis. Pediatrics 1997; 100:84-91.

20. Acton KJ, Burrows NR, Moore K, Querec L, Geiss LS, Engelgau MM. Trends in diabetes prevalence among American Indian and Alaska native children, adolescents, and young adults. Am J Public Health 2002; 92:1485-1490.

21. Zimmet P, Alberti KG, Shaw J. Global and societal implications of the diabetes epidemic. Nature 2001;414:782-787.

22. Narayan KM. Type 2 diabetes in children: a problem lurking for India? Indian Pediatrics 2001; 38:701-704.

23. Pinhas-Hamiel O, Zeitler P. “Who is the wise man? The one who foresees consequences”. Childhood obesity, new associated comorbidity and prevention. Prev Med 2000;31:702-705.

24. Ebbeling CB, Pawlak DB, Ludwig DS. Childhood obesity: public-health crisis, common sense cure. Lancet 2002;360:473-482.

25. Tajima N. Type 2 diabetes in children and adolescents in Japan. International Diabetes Monitor 2002; 14:1-5.

26. Craypo L, Purcell A, Samuels SE, Agron P, Bell E, Takada E. Fast food sales on high school campuses: results from the 2000 California high school fast food survey. J Sch Health 2002; 72:78-82.

27. Kitagawa T, Owada M, Urakami T, Tajima N. Epidemiology of type 1 (insulin-dependent) and type 2 (non-insulin-dependent) diabetes mellitus in Japanese children. Diabetes Res Clin Pract 1994; 24 Suppl:S7-13.

28. Strauss RS, Pollack HA. Epidemic increase in childhood overweight, 1986-1998. Jama 2001; 286:2845-2848.

29. Ogden CL, Flegal KM, Carroll MD, Johnson CL. Prevalence and trends in overweight among US children and adolescents, 1999-2000. Jama 2002; 288:1728-1732.

30. Booth ML, Chey T, Wake M, Norton K, Hesketh K, Dollman J, Robertson I. Change in the prevalence of overweight and obesity among young Australians, 1969-1997. Am J Clin Nutr 2003; 77:29-36.

31. Ramachandran A, Snehalatha C, Vinitha R, Thayyil M, Kumar CK, Sheeba L, Joseph S, Vijay V. Prevalence of overweight in urban Indian adolescent school children. Diabetes Res Clin Pract 2002; 57:185-190.

32. Dean H. Diagnostic criteria for non-insulin dependent diabetes in youth (NIDDM-Y). Clin Pediatr (Phila) 1998;7:67-71.

33. Davis EA, Burrows MR, Russell MT, Jones TW. Increasing rates of type 2 diabetes in children and adolescents in western Australia. In Australian Diabetes Society and Australian Diabetes Educators Association, Annual Scientific Meeting Adelaide, South Australia, 2002, p. 117.

34. Young TK, Dean HJ, Flett B, Wood-Steiman P. Childhood obesity in a population at high risk for type 2 diabetes. J Pediatr 2000; 136:365-369.

35. Kimm SY, Glynn NW, Kriska AM, Barton BA, Kronsberg SS, Daniels SR, Crawford PB, Sabry ZI, Liu K. Decline in physical activity in black girls and white girls during adolescence. N Engl J Med 2002; 347:709-715.

36. Troiano RP. Physical inactivity among young people.N Engl J Med 2002; 347:706-707.

37. Pinhas-Hamiel O, Standiford D, Hamiel D, Dolan LM, CohenR, Zeitler PS. The type 2 family: a setting for development and treatment of adolescent type 2 diabetes mellitus. Arch Pediatr Adolesc Med 1999; 153:1063-1067.

38. Nesmith JD. Type 2 diabetes mellitus in children and adolescents. Pediatr Rev 2001; 22:147-152.



152



153

39. Gutin B, Islam S, Manos T, Cucuzzo N, Smith C, Stachura ME. Relation of percentage of body fat and maximal aerobic capacity to risk factors for atherosclerosis and diabetes in black and white seven- to eleven-year-old children. J Pediatr 1994; 125:847-852.

40. Svec F, Nastasi K, Hilton C, Bao W, Srinivasan SR, Berenson GS. Black-white contrasts in insulin levels during pubertal development. The Bogalusa Heart Study. Diabetes 1992; 1:313-317.

41. Arslanian SA, Saad R, Lewy V, Danadian K, Janosky J. Hyperinsulinemia in african-american children: decreased insulin clearance and increased insulin secretion and its relationship to insulin sensitivity. Diabetes 2002;51:3014-3019.

42. Goran MI, Bergman RN, Cruz ML, Watanabe R. Insulin resistance and associated compensatory responses in african-american and Hispanic children. Diabetes Care 2002; 25:2184-2190.

43. Schmitz KH, Jacobs DR, Jr, Hong CP, Steinberger J, Moran A, Sinaiko AR. Association of physical activity with insulin sensitivity in children. Int J Obes Relat Metab Disord 2002; 26:1310-1316.

44. Nguyen TT, Keil MF, Russell DL, Pathomvanich A, Uwaifo GI, Sebring NG, Reynolds JC, Yanovski JA. Relation of acanthosis nigricans to hyperinsulinemia and insulin sensitivity in overweight African American and white children. J Pediatr 2001; 138:474-480.

45. Hirschler V, Aranda C, Oneto A, Gonzalez C, Jadzinsky M. Is acanthosis nigricans a marker of insulin resistance in obese children? Diabetes Care 2002; 25:2353.

46. Lewy VD, Danadian K, Witchel SF, Arslanian S. Early metabolic abnormalities in adolescent girls with polycystic ovarian syndrome. J Pediatr 2001; 138:38-44.

47. Palmert MR, Gordon CM, Kartashov AI, Legro RS, Emans SJ, Dunaif A. Screening for abnormal glucose tolerance in adolescents with polycystic ovary syndrome. J Clin Endocrinol Metab 2002; 87:1017-1023.

48. Ehrmann DA, Barnes RB, Rosenfield RL, Cavaghan MK, Imperial J. Prevalence of impaired glucose tolerance and diabetes in women with polycystic ovary syndrome. Diabetes Care 1999; 22:141-146.

49. Dowling HJ, Pi-Sunyer FX. Race-dependent health risks of upper body obesity. Diabetes 1993; 42:537-543.

50. Sinha AK, O’Rourke S, Leonard D, Yarker J. Early onset Type 2 diabetes (T2DM) in the indigenous communities of far north Queensland (FNQ). In Australian Diabetes Society Annual Scientific Meeting Cairns, Australia, 2000, p. 90.

51. Glowinska B, Urban M, Koput A. Cardiovascular risk factors in children with obesity, hypertension and diabetes: lipoprotein(a) levels and body mass index correlate with family history of cardiovascular disease. Eur J Pediatr 2002; 161:511-518.

52. Berenson GS, Radhakrishnamurthy B, Bao W, Srinivasan SR. Does adult-onset diabetes mellitus begin in childhood?: the Bogalusa Heart Study. Am J Med Sci 1995;310 Suppl 1:S77-82.

53. McCance DR, Pettitt DJ, Hanson RL, Jacobsson LT, Bennett PH, Knowler WC. Glucose, insulin concentrations and obesity in childhood and adolescence as predictors of NIDDM. Diabetologia 1994; 37:617-623.

54. Dyck RF, Klomp H, Tan L. From “thrifty genotype” to “hefty fetal phenotype”: the relationship between high birthweight and diabetes in Saskatchewan Registered Indians. Can J Public Health 2001; 92:340-344.

55. Silverman BL, Metzger BE, Cho NH, Loeb CA. Impaired glucose tolerance in adolescent offspring of diabetic mothers. Relationship to fetal hyperinsulinism. Diabetes Care 1995; 18:611-617.

56. Metzger BE, Silverman BL, Freinkel N, Dooley SL, Ogata ES, Green OC. Amniotic fluid insulin concentration as a predictor of obesity. Arch Dis Child 1990; 65:1050-1052.

57. Casey BM, Lucas MJ, McIntire DD, Leveno KJ. Pregnancy outcomes in women with gestational diabetes compared with the general obstetric population. Obstet Gynecol 1997; 90:869-873.

58. Barker DJ, Hales CN, Fall CH, Osmond C, Phipps K, Clark PM. Type 2 (non-insulin-dependent) diabetes mellitus, hypertension and hyperlipidaemia (syndrome X): relation to reduced fetal growth. Diabetologia 1993; 36:62-67.

59. Hales CN, Barker DJ. Type 2 (non-insulin-dependent) diabetes mellitus: the thrifty phenotype hypothesis. Diabetologia 1992; 35:595-601.

60. Sibai BM, Caritis S, Hauth J, Lindheimer M, VanDorsten JP, MacPherson C, Klebanoff M, Landon M, Miodovnik M, Paul R, Meis P, Dombrowski M, Thurnau G, Roberts J, McNellis D. Risks of preeclampsia and adverse neonatal outcomes among women with pregestational diabetes mellitus. National Institute of Child Health and Human Development Network of Maternal-Fetal Medicine Units. Am J Obstet Gynecol 2000; 182:364-369.

61. Barker DJ. Mothers, Babies and Health in Later Life. Edinburgh: Churchill Livingston, 1998.

62. Ravelli AC, van der Meulen JH, Michels RP, Osmond C, Barker DJ, Hales CN, Bleker OP. Glucose tolerance in adults after prenatal exposure to famine. Lancet 1998; 351:173-177.

63. Phillips DI, Barker DJ, Hales CN, Hirst S, Osmond C. Thinness at birth and insulin resistance in adult life. Diabetologia 1994; 37:150-154.

64. Flanagan DE, Moore VM, Godsland IF, Cockington RA, Robinson JS, Phillips DI. Fetal growth and the physiological control of glucose tolerance in adults: a minimal model analysis. Am J Physiol Endocrinol Metab 2000; 278:E700-706.

65. Wilkin TJ, Metcalf BS, Murphy MJ, Kirkby J, Jeffery AN, Voss LD. The relative contributions of birth weight, weight change, and current weight to insulin resistance in contemporary 5-year-olds: the EarlyBird Study. Diabetes 2002; 51:3468-3472.

66. Loos RJ, Phillips DI, Fagard R, Beunen G, Derom C, Mathieu C, Verhaeghe J, Vlietinck R. The influence of maternal BMI and age in twin pregnancies on insulin resistance in the offspring. Diabetes Care 2002;25:2191-2196.

67. Likitmaskul SKP, Chaichanwatanakul K, Punnakanta L, Angsusingha K, Tuchinda C. An increasing prevalence of type 2 diabetes in Thai children and adolescents associated with the increasing prevalence of obesity. J Pediatr Endocrinol Metab, in press.

68. Kadiki OA, Roaeid RB, Bhairi AM, Elamari IM. Incidence of insulin-dependent diabetes mellitus in Benghazi, Libya (1991-1995). Diabetes Metab 1998; 24:424-427.

69. Lipton R, Keenan H, Onyemere KU, Freels S. Incidence and onset features of diabetes in African-American and Latino children in Chicago, 1985-1994. Diabetes Metab Res Rev 2002; 18:135-142.

70. Harris SB, Perkins BA, Whalen-Brough E. Non-insulin-dependent diabetes mellitus among First Nations children. New entity among First Nations people of north western Ontario. Can Fam Physician 1996; 42:869-876.

71. Ehtisham S, Kirk J, McEvilly A, Shaw N, Jones S, Rose S, Matyka K, Lee T, Britton SB, Barrett T. Prevalence of type 2 diabetes in children in Birmingham. BMJ 2001; 322:1428.

72. McGrath NM, Parker GN, Dawson P. Early presentation of type 2 diabetes mellitus in young New Zealand Maori. Diabetes Res Clin Pract 1999; 43:205-209.



154



155

73. Lee WY, KPF Chia, YY Tan CL. Looking for NIDDM and insulin resistance in obese Singaporean children – when should we investigate? Diabetes Res Clin Pract 1999; 44:S25.

74. Paulsen EP, Richenderfer L, Ginsberg-Fellner F. Plasma glucose, free fatty acids, and immunoreactive insulin in sixty-six obese children. Studies in reference to a family history of diabetes mellitus. Diabetes 1968; 17:261-269.

75. Uwaifo GI, Elberg J, Yanovski JA. Impaired glucose tolerance in obese children and adolescents. N Engl J Med 2002;347 (4):290-292; author reply 290-292.

76. Sinha R, Fisch G, Teague B, Tamborlane WV, Banyas B, Allen K, Savoye M, Rieger V, Taksali S, Barbetta G, Sherwin RS, Caprio S. Prevalence of impaired glucose tolerance among children and adolescents with marked obesity. N Engl J Med 2002; 346:802-810.

77. Ciampalini P, Spera S, Bottazzo GF, Barbetti F, Crino A. Glucose intolerance in Italian obese children and adolescents. Diabetologia 2002; 45:A91.

78. el-Hazmi MA, Warsy AS. Prevalence of overweight and obesity in diabetic and non-diabetic Saudis. East Mediterr Health J 2000; 6:276-282.

79. Teuscher T, Baillod P, Rosman JB, Teuscher A. Absence of diabetes in a rural West African population with a high carbohydrate/cassava diet. Lancet 1987; 1:765-768.

80. Ahren B, Corrigan CB. Prevalence of diabetes mellitus in north-western Tanzania. Diabetologia 1984; 26:333-336.

81. Fisch A, Pichard E, Prazuck T, Leblanc H, Sidibe Y, Brucker G. Prevalence and risk factors of diabetes mellitus in the rural region of Mali (West Africa): a practical approach. Diabetologia 1987; 30:859-862.

82. McLarty DG, Swai AB, Kitange HM, Masuki G, Mtinangi BL, Kilima PM, Makene WJ, Chuwa LM, Alberti KG. Prevalence of diabetes and impaired glucose tolerance in rural Tanzania. Lancet 1989; 1:871-875.

83. Ramaiya KL, Swai AB, McLarty DG, Alberti KG. Impaired glucose tolerance and diabetes mellitus in Hindu Indian immigrants in Dar es Salaam. Diabet Med 1991; 8:738-744.

84. Hanis CL, Boerwinkle E, Chakraborty R, Ellsworth DL, Concannon P, Stirling B, Morrison VA, Wapelhorst B, Spielman RS, Gogolin-Ewens KJ, Shepard JM, Williams SR, Risch N, Hinds D, Iwasaki N, Ogata M, Omori Y, Petzold C, Rietzch H, Schroder HE, Schulze J, Cox NJ, Menzel S, Boriraj VV, Chen X, et al. A genome-wide search for human non-insulin-dependent (type 2) diabetes genes reveals a major susceptibility locus on chromosome 2. Nat Genet 1996; 13:161-166.

85. Hale DE, Danney MM, Caballero M, Garcia O, Trevino RP. Prevalence of type 2 diabetes mellitus in urban, Mexican American 4th graders. Diabetes 2002; 51:A25.

86. Harrell JS, McMurray RG, Davenport M, Amorim L, Buse J. Type 2 diabetes in southern middle school students. Diabetes 2002; 51:A26.

87. Dabelea D, Hanson RL, Bennett PH, Roumain J, Knowler WC, Pettitt DJ. Increasing prevalence of Type II diabetes in American Indian children. Diabetologia 1998; 41:904-910.

88. Freedman DS, Serdula MK, Percy CA, Ballew C, White L. Obesity, levels of lipids and glucose, and smoking among Navajo adolescents. J Nutr 1997; 127:2120S-2127S.

89. Dean HJ, Young TK, Flett B, Wood-Steiman P. Screening for type-2 diabetes in aboriginal children in northern Canada. Lancet 1998; 352:1523-1524.

90. Bai PV, Krishnaswami CV, Chellamarippan M, Kumar GV, Subramaniam JR, Srivatwa A, Subramanyam B, Rao MB. Prevalence of diabetes in the young in south India. Indian Pediatr 1995; 32:1173-1176.

91. Sayeed MA, Hussain MZ, Banu A, Rumi MA, Azad Khan AK. Prevalence of diabetes in a suburban population of Bangladesh. Diabetes Res Clin Pract 1997; 34:149-155.

92. Sayeed MA, Banu A, Khan AR, Hussain MZ. Prevalence of diabetes and hypertension in a rural population of Bangladesh. Diabetes Care 1995; 18:555-558.

93. Chuang LM, Sung FC, Lee CY, Lin RR, Lin CC, Chiang CC. Incidence and prevalence of childhood diabetes in Taiwan – an experience with nation-wide screening. Diabetes Res Clin Pract 2002; 56:S16.

94. Braun B, Zimmermann MB, Kretchmer N, Spargo RM, Smith RM, Gracey M. Risk factors for diabetes and cardiovascular disease in young Australian aborigines. A 5-year follow-up study. Diabetes Care 1996; 19:472-479.

95. Colagiuri S, Colagiuri R, Na’ati S, Muimuiheata S, Hussain Z, Palu T. The prevalence of diabetes in the kingdom of Tonga. Diabetes Care 2002; 25:1378-1383.

96. Fagot-Campagna A. Emergence of type 2 diabetes mellitus in children: epidemiological evidence. J Pediatr Endocrinol Metab 2000; 13 Suppl 6:1395-1402.

97. Ehtisham S, Barrett TG, Shaw NJ. Type 2 diabetes mellitus in UK children – an emerging problem. Diabet Med 2000; 17:867-871.

98. Kadiki OA, Reddy MR, Marzouk AA. Incidence of insulin-dependent diabetes (IDDM) and non-insulin-dependent diabetes (NIDDM) (0-34 years at onset) in Benghazi, Libya. Diabetes Res Clin Pract 1996; 32:165-173.

99. Ramachandran A, Snehalatha C, Satyavani K, Sivasankari S, Vijay V. Type 2 diabetes in Asian-Indian urban children. Diabetes Care 2003; 26:1022-1025.

100. Glaser NS, Jones KL. Non-insulin dependent diabetes mellitus in Mexican-American children. West J Med 1998; 168:11-16.

101. Pinhas-Hamiel O, Dolan LM, Daniels SR, Standiford D, Khoury PR, Zeitler P. Increased incidence of non-insulin-dependent diabetes mellitus among adolescents. J Pediatr 1996; 128:608-615.

102. Macaluso CJ, Bauer UE, Deeb LC, Malone JI, Chaudhari M, Silverstein J, Eidson M, Goldberg RB, Gaughan-Bailey B, Brooks RG, Rosenbloom AL. Type 2 Diabetes Mellitus Among Florida Children and Adolescents, 1994 through 1998. Public Health Rep 2002; 117:373-379.

103. Korner AM, MD. Rising tide of type 2 diabetes mellitus and impaired glucose tolerance among Hungarian children and adolescents. Diabetologica Hungarica 2002;10:22-27.

104. Invitti C, Guzzaloni G, Gilardini L, Morabito F, Viberti G. Prevalence and concomitants of glucose intolerance in European obese children and adolescents. Diabetes Care 2003; 26:118-124.

105. Legro RS, Kunselman AR, Dodson WC, Dunaif A. Prevalence and predictors of risk for type 2 diabetes mellitus and impaired glucose tolerance in polycystic ovary syndrome: a prospective, controlled study in 254 affected women. J Clin Endocrinol Metab 1999; 84:165-169.

106. Brickman WJ, Howard JC, Metzger BE. Abnormal glucose tolerance in children with acanthosis nigricans: a chart review. Diabetes 2002; 51:A429.

107. Dean H FB. Natural history of type 2 diabetes diagnosed in childhood: long term follow-up in young adult years. Diabetes 2002; 51:A24.

108. Yokoyama H, Okudaira M, Otani T, Sato A, Miura J, Takaike H, Yamada H, Muto K, Uchigata Y, Ohashi Y, Iwamoto Y. Higher incidence of diabetic nephropathy in type 2 than in type 1 diabetes in early-onset diabetes in Japan. Kidney Int 2000; 58:302-311.

109. Krakoff J, Lindsay RS, Looker HC, Nelson RG, Hanson RL, Knowler WC. Incidence of retinopathy and nephropathy in youth-onset compared with adult-onset type 2 diabetes. Diabetes Care 2003; 26:76-81.

110. Delisle HF, Ekoe JM. Prevalence of non-insulin-dependent diabetes mellitus and impaired glucose tolerance in two Algonquin communities in Quebec. CMAJ 1993; 148:41-47.



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111. Harris SB, Gittelsohn J, Hanley A, Barnie A, Wolever TM, Gao J, Logan A, Zinman B. The prevalence of NIDDM and associated risk factors in native Canadians. Diabetes Care 1997; 20:185-187.

112. Chavez RA, Strazdas LA, Lebowitz MD, Arriaga YE, Caruso Y, Dixit NM. Prevalence of type 2 diabetes in adolescents in Douglas, Arizona: is it significant. Diabetes 2002; 51:A429.

113. Kim C, McHugh C, Kwok Y, Smith A. Type 2 diabetes mellitus in Navajo adolescents. West J Med 1999; 170:210-213.

114. Daniel M, Rowley KG, McDermott R, Mylvaganam A, O’Dea K. Diabetes incidence in an Australian aboriginal population. An 8-year follow-up study. Diabetes Care 1999; 22:1993-1998.

115. Punnose J, Agarwal MM, El Khadir A, Devadas K, Mugamer IT. Childhood and adolescent diabetes mellitus in Arabs residing in the United Arab Emirates. Diabetes Res Clin Pract 2002; 55:29-33.

116. Dean H. NIDDM-Y in First Nation children in Canada. Clin Pediatr (Phila) 1998; 37:89-96.

117. Jones KL. Non-insulin dependent diabetes in children and adolescents: the therapeutic challenge. Clin Pediatr (Phila) 1998; 37:103-110.

118. Barrett TG, Ehtisham S, Smith A, Hattersley AT. UK Diabetes Survey shows type 2 diabetes present in 0.4% of newly diagnosed children, associated with overweight, female and ethnic minorities. Diabetes 2002; 51:A25.

The Widening CircleChapter 3


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The Widening Circle Chapter 3

A very disturbing feature of diabetes has been the clustering of diabetes

with other well-known cardiovascular risk factors, in particular central (abdominal) obesity. It is for this reason that a chapter on obesity and cardiovascular disease (CVD) appears in this edition of the Diabetes Atlas.

With globalization, there have been dramatic changes in the human environment, behaviour and way-of-life which have resulted in escalating rates of both diabetes and obesity. This explains the recent popularity of the term ‘diabesity’. The frequency of central obesity, hypertension and elevated blood lipids are dramatically increased in persons with diabetes and this has been called the ‘Deadly Quartet’.

The concern regarding the associated increase in cardiovascular risk becomes even greater when one considers that people with impaired glucose tolerance (IGT) and impaired fasting glucose (IFG) also have a substantial increase in cardiovascular risk factors and, like persons with diabetes, higher cardiovascular risk. Coronary artery disease and cerebrovascular disease are two to three times more common in people with diabetes than in people without diabetes.

Cardiovascular disease is the major cause of death in people with type 2 diabetes. A key strategy in reducing macro-vascular disease lies in the better understanding of the metabolic syndrome: glucose

3.1 Obesity

3.2 Cardiovascular Disease and Diabetes: Double Jeopardy



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intolerance (type 2 diabetes, IGT or IFG), hyperinsulinaemia, hypertension, dyslipidaemia and central obesity. This clustering of CVD risk factors represents a time bomb for both individuals with diabetes and the nations faced with the public health burden as it provides the driving force for a cardiovascular disease epidemic.

It is now very clear that management of diabetes should focus not only on tight blood glucose control but also on strategies for reducing the other important cardiovascular risk factors such as central obesity, hypertension, and dyslipidaemia in order to reduce cardiovascular disease complications.

It is also clear from a number of epidemiological studies that the clock starts ticking for cardiovascular disease many years before the clinical diagnosis of diabetes. This highlights the rationale for early intervention in the IGT phase. The potential for IGT and, indeed, the metabolic syndrome to be prevented is now well documented with lifestyle interventions and pharmacotherapy.

Reducing obesity through healthy nutrition along with exercise provides the logical means of prevention of both diabetes and associated cardiovascular morbidity and mortality. This is supported by three major type 2 diabetes intervention studies – the DaQing Study in China, the Diabetes Prevention Study (DPS) in Finland and the Diabetes Prevention Program (DPP) in USA. An integrated approach to preventing both diabetes and obesity can hopefully reduce the global burden.

The report on obesity was compiled by the International Obesity Task Force while the data on CVD mortality rates were compiled by the WHO Collaborating Centre at the Menzies Centre, University of Tasmania, Australia.



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Introduction

Obesity is the principal risk factor for type 2 diabetes. An excess of body fat, especially when concentrated within the abdomen, has a range of potentially harmful consequences. Classified as a disease, obesity diminishes both quality of life and life expectancy, but it is also a common risk factor for a number of other diseases from osteo-arthritis to heart disease and some types of cancer (see Box 3.1).

The World Health Organization (WHO) defines overweight as a body mass index (BMI) of at least 25 kg/m2 and obesity as a BMI of at least 30 kg/m2 (see Box 3.2). However, the health risks rise progressively above BMI levels of 20-22 kg/m2 in all populations (1). The conclusions of a WHO expert group, which considered the evidence for lower BMI action points around BMI 23 in different Asian populations, are at present under review.

WHO recommends a general limit for waist circumference of 102 cm and 88 cm in men and women respectively, but more appropriate waist circumference action levels are now being sought to specify risk levels relating to diabetes and other co-morbidities in Asian countries to help alert those with lower BMIs to their increased risks (2). Over recent years rates of overweight and obesity have escalated rapidly in many parts of the world to epidemic proportions, reflecting increased consumption of energy dense diets high in fats and sugars, compounded by declining levels of physical activity.

Using the standard classification, more than 1.1 billion people are estimated to be overweight, of whom around 320 million are now calculated to

3.1 Obesity

Box 3.1

Obesity – a risk factor

Overweight and obesity lead to adverse metabolic effects on blood pressure, cholesterol, triglycerides

and insulin resistance. Risks of coronary heart disease, ischaemic stroke and type 2 diabetes mellitus increase steadily with increasing body mass index (BMI).

Type 2 diabetes mellitus - confined to older adults for most of the 20th century - now affects obese children even before puberty. Modest weight reduction reduces blood pressure and abnormal blood cholesterol and substantially lowers risk of type 2 diabetes.

Raised BMI also increases the risks of cancer of the breast, colon, prostate, endometrium, kidney and gallbladder. Although the mechanisms that trigger these increased cancer risks are not fully understood, they may relate to obesity-induced hormonal changes. Chronic overweight and obesity contribute significantly to osteo-arthritis, a major cause of disability in adults.

be obese. The International Obesity Task Force (IOTF) estimates that up to 1.7 billion people may be exposed to weight-related health risks, taking into account varied Asian populations with a BMI of 23 or more.

Average BMI levels across Africa and Asia have been estimated at between 20-23 kg/m2, but in Europe and North America mean levels are much higher at 25-27 kg/m2, indicating that a substantial part of the population may be exposed to the health risks of higher BMIs (3). More than 2.5 million deaths each year are attributed to higher BMI, a figure that is expected to double by 2030.

Regional trends

Across the world the epidemic of obesity has been gathering momentum affecting both developed and developing countries.

A new generation is entering adulthood with unprecedented levels of obesity. This, in addition to the existing burden of adult obesity, reinforces the concern that weight-related chronic diseases will be the most significant public health concern throughout the 21st century.



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AfricaWide disparities in levels of obesity are found in this region with the highest rates in South Africa, where mean BMI values for men and women are 22.9 kg/m2 and 27.1 kg/m2 respectively, but levels of central obesity among women have been assessed at 42% (4). The South Africa Health Review 2000 indicated obesity rates from 8% among black men to 20% among white men, but among women the rates range from 20% for Indian/Asians to 30.5% for black women. In parts of sub-Saharan Africa obesity often exists alongside under-nutrition (5).

Eastern Mediterraneanand Middle East High levels of overweight and obesity exist particularly among women, in countries as diverse as Egypt and the Gulf states including Saudi Arabia. Obesity rates of 25-30% and even higher are not untypical in Kuwait, the United Arab Emirates and Bahrain. In Iran, obesity rates vary from rural to urban populations rising to 30% among women in Tehran.

In northern Africa the prevalence of obesity among women is high. Half of all women are overweight (BMI≥25) with

rates of 50.9% in Tunisia and 51.3% in Morocco, and obesity rates (BMI≥30) in women of 23% in Tunisia and 18% in Morocco, representing a three-fold increase over 20 years (6).

Europe Few countries in the European Region report obesity rates below 10%. Prevalence rates, particularly among women, rise to more than 20% in countries such as the United Kingdom, Germany, Finland and Greece. The most rapid increase is noted in England where obesity rates have risen three-fold from 1980 to 2001, with levels of morbid obesity (BMI≥40) also increasing three-fold among men and almost doubling among women during the 1990s (7).

North AmericaIn the United States obesity affects one in three adults overall, more than double the rate of 20 years ago. Ethnic minorities, particularly women, are even more adversely affected with 40% of Mexican American women and 50% of black American women having a body mass index above 30 kg/m2 compared to 30.6% of white women. Extreme obesity rates, classified as morbid or very severe obesity of BMI≥40, are as high as 15% among black American women (8). Neighbouring Canada experienced an increase of 150% in its overall adult obesity rate from 1985 to 1998 reaching 14.8%, but 40% of men and 25% of women fell into the pre-obese category (9).

In the Caribbean, obesity is a significant problem, particularly among women, with correspondingly high rates of type 2 diabetes. Abdominal obesity, using WHO waist circumference limits, ranged from 3% of men in St Lucia to 8% in Barbados, but among women was found to be as high as 34% in Jamaica, 41% in St Lucia and 45% in Barbados (10). Diabetes studies in Jamaica have demonstrated markedly high risks associated with overweight and central obesity (11).

Box 3.2

Defining body mass index (1)

Body mass index (BMI) is calculated by dividing weight in kilogrammes (kg) by the square of height in metres (m).

BMI ≥25 = overweightBMI 25-29.9 = pre-obesityBMI ≥30 = obesity

The sub-categories of obesity:Obesity class I 30.0-34.9 = moderateObesity class II 35.0-39.9 = severeObesity class III 40+ = very severe



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South and Central America Evidence of the impact of the ‘nutrition transition’ is clear in the growing levels of obesity throughout this region. Obesity rates are reported to vary for men from 7% in Peru and Brazil to more than 20% in Paraguay, where the rates in women rise to as high as 36% (12).

Western PacificVarious Asian populations may be particularly susceptible to the health risks of central obesity, regardless of BMI (13). Consequently there is an increasing focus on measuring waist circumferences, which can predict individual risk more accurately than body mass index (14). However, Japanese experts have agreed independently to redefine the criteria for obesity as a disease, with a cut-off at BMI≥25. It has also been suggested that

this apply in the Asian region. Using this standard, adult obesity in Japan would average 20%, rising to 30% in men over 30 years old and women over 40 years old, representing a three to four-fold increase over the last 40 years (15,16).

China has adopted its own standards defining overweight at a BMI of 24 or more, and obesity at a BMI of 28 or more. However abdominal obesity is defined by a waist circumference of 85 cm in men and 80 cm in women (17). Figure 3.1 shows the prevalence of obesity, using BMI ≥25 as a criterion, in selected countries in the Western Pacific.

The link between obesity and type 2 diabetes is most manifest in the Pacific area which has some of the highest levels of adult obesity. Obesity prevalence rates

Figure 3.1Prevalence of obesity using BMI ≥25 as criterion in selected countries – Western Pacific Region

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(BMI ≥30) of between 60% and 80% can be found among men and women in some islands including Samoa and Nauru. In Tonga, 60% of the adult population is obese and recently 12% of men and nearly 18% of women were identified with type 2 diabetes, a doubling of the rate over 25 years. A further 20% were found to be at risk due to elevated blood sugar levels (18).

Obesity and diabetes

Obesity and type 2 diabetes are causally linked. Weight gain leads to insulin resistance through several mechanisms. Insulin resistance places a greater demand on the pancreatic capacity to produce insulin, which also declines with age, leading to the development of clinical diabetes.

Fat accumulation induces insulin resistance through changes in its hormonal and other secretions. Protective hormones such as adiponectin decline

as fat cells expand, particularly in the abdomen. Physical inactivity, both a cause and consequence of weight gain, also contributes to insulin resistance.

The IOTF analyses, undertaken for the World Health Report 2002 and associated WHO Global Burden of Disease research, indicate that approximately 58% of diabetes mellitus globally (as well as 21% of ischaemic heart disease and 8-42% of certain cancers) can be attributed to BMI above 21 kg/m2. However in western countries, around 90% of type 2 diabetes cases are attributable to weight gain (see Figure 3.2), and childhood overweight and obesity are now leading to an unusual pattern of premature type 2 diabetes, which is particularly difficult to manage once established (19).

Among adults, clear evidence exists that surprisingly modest weight reductions can markedly reduce the development of type 2 diabetes, if not prevent it completely, in susceptible individuals,

Figure 3.2Proportion of diabetes (%) attributable to weight gain by region (30+ years)

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and that weight loss can reverse the type 2 diabetic state. The remarkable effect of weight loss through diet and increased activity has been demonstrated in the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Diabetes Prevention Program in the USA to benefit particularly the over-60s, in whom nearly three-quarters of new cases of diabetes were prevented.

This and other studies provide hope to those with impaired glucose tolerance and a susceptibility to diabetes. Dietary and activity changes to produce a 5-7% weight loss can successfully reduce the incidence of type 2 diabetes; reductions in fat and calorie intake accompanied by half an hour’s extra walking or other exercise each day have been demonstrated to lower the incidence by 58%. Great success has been achieved among people over 60 years, reducing the development of diabetes in that high-risk age group by 71% (20). Similar data have emerged from China, Scandinavia and other European studies.

Costs of obesity

The cost of obesity in economic terms has been estimated to account for 2-7% of total healthcare costs (1). Recently the combined direct and indirect costs to the USA have been re-assessed at US$123 billion in 2001 (21). This expenditure may overshadow the costs in smaller countries such as England where the Parliamentary National Audit Office assessed the cost at around £2.5 billion (£3 billion when adjusted to 2003 figures) (22). In the Pacific islands, the economic consequences of non-communicable diseases, chiefly obesity and type 2 diabetes, have been dramatic, consuming US$1.95 million, almost 60% of the health budget of Tonga, and in Fiji absorbing US$13.6 million, 39% of the health budget (23).

The human cost can be measured in terms of years of disability, which can

reduce the quality of life as well as lowering life expectancy. Higher body mass index has been shown to account for up to 16% of the global burden of disease, expressed as a percentage of disability-adjusted life years (DALYs) (see Map 3.1) (24).

Childhood obesity

Childhood obesity is a relatively recent phenomenon, which poses a critical threat to health. Significant prevalences exist in developing countries as well as in industrially developed economies. An IOTF analysis (see Figure 3.3) has shown that overweight and obesity affects one in 10 children worldwide, but the rate is double in Europe and three times as great across the entire Americas (25). The emergence of type 2 diabetes in childhood is a serious development. In the USA it has been noted that up to 45% of children with newly diagnosed diabetes have type 2 diabetes and most are overweight or obese at diagnosis (26).

Figure 3.3Overweight and obesity among school-age children(5-17 years)

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Conclusion

The most recent WHO recommendations for dietary improvements and increased levels of exercise across entire populations provide the basis for the development of global strategies to challenge the rise in obesity along with other diet and activity related chronic diseases, including type 2 diabetes (27). However even if the WHO recommendations, including those to reduce fat, sugar and salt consumption, were to be implemented, it would be some considerable time before the benefits were reflected in a reduction of obesity and co-morbidity rates.

A new generation is entering adulthood with unprecedented levels of obesity. This, in addition to the existing burden of adult obesity, reinforces the concern that

weight-related chronic diseases will be the most significant public health concern throughout the 21st century.

The provision of effective obesity treatment, which can prevent or delay the onset of type 2 diabetes, and the development of coherent strategies to halt the progressive weight gain in evidence in most populations, is lacking. Weighing the clear benefit of interventions against the significant costs in both human and financial terms of inaction, it is surprising, if not alarming, that so little has been done worldwide to attack the root causes of the twin epidemics of obesity and type 2 diabetes.

Map 3.1Proportion of DALYs attributable to overweight (high body mass index)

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Map 3.3Global prevalence of obesity (BMI ≥30) in females

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References

1. World Health Organization. Obesity: Preventing and Managing the Global Epidemic. Technical Report Series no. 894. WHO, Geneva, 2000.

2. Choo V. WHO reassesses appropriate body mass index for Asian populations. Lancet 2002; 360:234.

3. IOTF analysis of data gathered for the WHO Global Burden of Disease 2003.

4. Puoane T, Steyn K, Bradshaw D, Laubscher R, Fourie J, Lambert V, Mbananga N. Obesity in South Africa: the South African demographic and health survey. Obesity Research 2002; 10:1038-1048.

5. Maire B, Delpeuch F, Cornu A, Tchibindat F, Simondon F, Massamba JP, Salem G, Chevassus-Agnes S. Urbanization and nutritional transition in sub-saharan Africa: exemplified by Congo and Senegal. Rev Epidemiol Santé Publique 1992; 40:252-258 (article in French).

6. Mokhtar N, Elati J, Chabir R, Bour A, Elkari K, Schlossman NP, Caballero B, Aguenaou H. Diet culture and obesity in northern Africa. J Nutrition 2001; 131:887S-892S.

7. Department of Health 2001. Health Survey for England. www.doh.gov.uk/.

8. NHANES 1999-2000. www.cdc.gov/.9. Katzmarzky PT. The Canadian obesity epidemic, 1985-1998.

CMAJ 2002; 166(8):1039-1040.10. Okosun IS, Forrester TE, Rotimi CN, Osotimehin BO,

Muna WF, Cooper RS. Abdominal adiposity in six populations of West African descent: prevalence and population attributable fraction of hypertension. Obes Res 1999; 7:453-462.

11. Wilks R, Rotimi C, Bennett F, McFarlane-Anderson N, Kaufman JS, Anderson SG, Cooper RS, Cruickshank JK, Forrester T. Diabetes in the Caribbean: results of a population survey from Spanish Town, Jamaica. Diabetic Medicine 1999; 16:875-883.

12. Filozof C, Gonzales C, Sereday M, Mazza C, Braguinsky J. Obesity prevalence and trends in Latin American countries. Obesity Reviews 2001; 2:99-196.

13. James WPT, Chunming C, Inoue S. Appropriate Asian body mass indices? Obesity Reviews 2002; 3:139.

14. Lean ME, Han TS, Deurenberg P. Body composition by densitometry from simple anthropometric measurements. Am J Clinical Nutrition 1996; 63:4-14.

15. The Examination Committee of Criteria for ‘Obesity Disease’ in Japan, Japan Society for the Study of Obesity. New Criteria for ‘Obesity Disease’ in Japan. Circulation Journal 2002; 66(11):987-992.

16. Kanazawa M, Yoshiike N, Osaka T, Numba Y, Zimmet P, Inoue S. Criteria and classification of obesity in Japan and Asia-Oceania. Asia Pac J Clin Nutr 2002 Dec; 11 Suppl 8:S732-S737.

17. Zhou BF, Cooperative Meta-Analysis Group of the Working group on Obesity in China. Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults - study on optimal cut-off points of body mass index and waist circumference in Chinese adults. Biomed Environ Sci 2002; 15:83-95.

18. Colagiuri S, Colagiuri R, Na’ati S, Muimuiheata S, Hussain Z, Palu T. The prevalence of diabetes in the kingdom of Tonga. Diabetes Care 2002; 25:1378-1383.

19. James WPT, Jackson-Leach R, Mhurdu CN, Kalamara E, Shayeghi M, Rigby N, Nishida C and Rodgers A. Overweight and Obesity. In Comparative Quantification of Health Risks: Global and Regional Burden of Disease Attributable to Selected Major Risk Factors, eds. Ezzati M, Lopez AD, Rodgers A, Murray CJL. WHO, Geneva, 2003; in press.

20. Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002; 346:393-403.

21. Wolf AM, Manson JE, Colditz GA. The Economic Impact of Overweight, Obesity and Weight Loss. Ed Eckel R in Obesity. Lippincott, Williams and Wilkins, 2002.

22. National Audit Office. Tackling Obesity. National Audit Office, London 2001.

23. Dalton A and Crowley S. Economic Impact of NCD in the Pacific Islands in Obesity in the Pacific: Too Big to Ignore. Secretariat of the Pacific Community 2002.

24. World Health Organization. The World Health Report 2002. Reducing Risks, Promoting Healthy Life. IOTF research for the WHO Global Burden of Disease programme.

25. IOTF. Childhood Obesity – The New Crisis in Public Health. International Obesity Task Force, London, 2003; in press.

26. American Diabetes Association. Type 2 diabetes in children and adolescents. Diabetes Care 2000; 3:381-389.

27. WHO/FAO. Diet, Nutrition and the Prevention of Chronic Diseases. Technical Report Series no. 916. WHO, Geneva, 2003. (www.who.int/hpr/NPH/docs/who_fao_expert_report.pdf)



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Introduction

Cardiovascular disease (CVD) is a major worldwide health problem and the leading cause of death in industrialized countries. Cardiovascular disease is also the major complication of type 2 diabetes and is responsible for more than 50% and up to 80% of deaths in people with diabetes as well as for very substantial morbidity and loss of quality of life (see Chapter 1.2).

Diabetes can lead to cardiovascular damage in a number of ways. The processes do not develop independently, and each may accelerate or worsen the others. Thus, as diabetes progresses, the heart and blood vessels are exposed to multiple attacks.

Cardiovascular death rates are either high or appear to be climbing in countries where diabetes is prevalent. The outlook for cardiovascular diseases is alarming when one considers the number of people with diabetes worldwide and that this is set to more than double by 2025.

The recent decline in cardiovascular disease in the USA, Australasia and western Europe may be compromised significantly by this upsurge in diabetes. In other parts of the world where CVD has been proliferating in recent years, the additional impact of diabetes threatens to have devastating consequences.

Many cardiovascular deaths are potentially preventable in both people with and without diabetes if action is taken to systematically address the known risk factors. While some risk factors are fixed, such as age, gender and genetic background, many others are modifiable, such as high blood pressure, lipid abnormalities, obesity and smoking.

Major cardiovascular complications

The most important cardiovascular complications of diabetes are:

• coronary heart disease (CHD); • cerebrovascular disease (CBVD); and• peripheral vascular disease (PVD).

Given the global epidemic of diabetes, the double threat of diabetes and CVD is set to explode unless preventative action is taken. It is noteworthy for example that, in some Western populations, CHD rates have declined in the overall population but no consistent decline is seen in people with diabetes (1).

3.2 Cardiovascular Disease and Diabetes: Double Jeopardy

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The cardiovascular disease triad



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Diabetes as a risk factor

The impact of cardiovascular disease in diabetes is exacerbated even further by the earlier age of onset of type 2 diabetes which is now reaching down even to children and adolescents, and carries the threat of early onset of CVD. In addition advances in insulin therapy have improved the life expectancy of people with type 1 diabetes and each year of prolonged life increases the likelihood of cardiovascular complications.

Diabetes leads to cardiovascular damage by a number of mechanisms, each of which in turn may accelerate or worsen the others. It belongs to a special risk category as it has so marked an effect on cardiovascular risk. As well as being a risk factor in its own right, diabetes is associated with a higher prevalence of other common risk factors such as hypertension and dyslipidaemia, and, these risk factors, in turn, have a more harmful effect in the presence of diabetes. For each risk factor present, the risk of cardiovascular death is about three times greater in people with diabetes compared to those without diabetes.

The end result is that people with diabetes are two to four times more likely to develop CVD than the general population (see Figure 3.7). In the case of CVD, silent myocardial infarction is common and the risks of sudden death and heart failure are also increased. In the case of stroke, transient ischaemic attacks are two to six times more common in the diabetic population and vascular dementia is also more common. In the case of PVD people with diabetes have a 15-40 times increase in the risk of lower limb amputation compared to the general population.

These figures also conceal additional problems. For a given major vascular event such as myocardial infarction or stroke, the outcome is worse in people with diabetes compared to the

Figure 3.7Heart attacks in people with and without diabetes over a period of seven years (adapted from Haffner SM et al (2))

Figure 3.8Deaths in people with and without diabetes in the year following a first heart attack (adapted from Miettinen et al (4))

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Source: Diabetes and Cardiovascular Disease: Time to Act, IDF 2001 (3)

Source: Diabetes and Cardiovascular Disease: Time to Act, IDF 2001 (3)

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The use of mortality data, obtained principally from the Global Cardiovascular Infobase, does however serve to indicate the magnitude of the problem and to highlight regional differences and trends.

It should be noted that considerable differences exist in the degree of completeness of the vital registration data submitted by countries. In some countries, the vital registration data system covers only a part of the country (for example urban areas, or some provinces only). In some other countries, although the vital registration data system covers the whole country, not all deaths are registered. Further details on data sources and methodology can be found in Appendix 1.4.

It should be emphasized also that these data provide the overall picture of total CVD mortality and are not limited to CVD in the context of diabetes.

Regional and national trendsAs well as differences in total trends in different parts of the world, there may also be differences in disease patterns which are not revealed by these figures. For example, in the case of cerebrovascular disease, the proportion of deaths resulting from haemorrhagic stroke compared to thrombotic stroke is higher in Japan, China and many African countries, compared to Europe or North America. This may reflect differences in the relative importance of individual risk factors, such as hypertension.

AfricaAvailable data from Africa are very limited but show marked contrasts between countries. Botswana reports zero deaths from CHD and a low mortality from cerebrovascular disease whereas Zimbabwe occupies an intermediate position. In South Africa the mortality from cerebrovascular disease in females stands out as being equal to that of males and double that of CHD in females.

general population (see Figure 3.8). This results from both the severity and widespread nature of atherosclerosis in diabetes, combined with other causes of vascular disease in diabetes apart from atherosclerosis, such as arterial stiffness, microangiopathy and autonomic neuropathy*.

It is important to note also that even at the stage of impaired glucose tolerance (IGT), before full-blown diabetes has developed, the risk of cardiovascular disease is already increased by about two times compared to people with normal glucose tolerance.

A costly combination

About half of all the money spent on diabetes care goes towards the costs of managing diabetic complications. Cardiovascular complications frequently account for the bulk of the costs as reflected in the patterns of hospital admissions for the treatment of complications (see Figure 3.9). The trend of escalating diabetes prevalence with its impact on CVD will no doubt lead to an immense financial burden in many countries unless action is taken to prevent both diabetes and its complications.

The global burden of cardiovascular disease

The data which follow summarize the global burden of cardiovascular disease by using mortality data for coronary heart disease and cerebrovascular disease from individual countries. It needs to be emphasized that these are mortality data and do not therefore indicate levels of morbidity in survivors. They also do not include information about peripheral vascular disease.

* For further details readers are referred to Diabetes and Cardiovascular Disease: Time to Act, International Diabetes Federation, 2001 (3).

The link between diabetes and CVD is so strong that the prevention agenda for both diseases can be linked and integrated at many levels of the system. The high CVD risk in people with IGT and newly-diagnosed diabetes also emphasizes both the importance of primary prevention of diabetes in the context of overall prevention of CVD and the significance of diabetes as an ‘entry point’ for overall, comprehensive cardiovascular risk management.



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Source: International Diabetes Federation, 1999 (5)

Eastern Mediterraneanand Middle EastLimited reports from the Middle East indicate cerebrovascular disease mortality rates similar to those of western European countries with the lowest rates, for example France. Rates in Egypt are however higher and appear to be rising quite rapidly. By contrast CHD rates are relatively low in Egypt compared to Bahrain, and, particularly, Kuwait.

Europe In many western European countries CHD mortality rates have dropped appreciably in the last two decades. However the eastern European countries from the previous Soviet bloc have some of the highest rates in the world for both CHD and cerebrovascular disease. Thus Estonia has double the rate of Finland, and Georgia makes interesting comparison with France, with a five times higher rate in males and ten times higher rate in females. The Russian Federation and Ukraine also have very high rates. Similar trends are seen with cerebrovascular disease.

North AmericaCHD mortality rates have shown recent falls in both Canada and USA and are broadly similar to western European countries such as Germany, Sweden and Austria although still much higher than other European countries such as France and Portugal. Rates of cerebrovascular disease in USA and Canada are broadly similar to those in lower prevalence western European countries such as France, Netherlands and Spain.

South and Central Americaand the CaribbeanCHD mortality rates vary greatly from country to country but are generally similar to or below those for North America, with the exception of Trinidad and Cuba and a few other countries which have a relatively high mortality rate in females. Mortality rates from cerebrovascular disease are relatively much higher and approach or exceed those from CHD, a notable example being Brazil.

Figure 3.9Proportion of hospital bed days used for the treatment of diabetic complications

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South-East AsiaData are available only from Sri Lanka and Mauritius. The absence of data from India, Pakistan and Bangladesh makes detailed analysis difficult. This lack of data also causes concern given the numbers of people with diabetes in India and relatively high reported rates for CHD in migrant Indian populations.

The reported rates from Sri Lanka indicate that both CHD and cerebrovascular disease mortality rates are approximately similar to those of France, a western European country with relatively low rates. Mauritius has very high rates for both CHD and cerebrovascular disease, and is also well known for high diabetes prevalence rates.

Western PacificThis is a huge and diverse region and this diversity is reflected in the ranges of reported mortality rates. The reported mortality rates for CHD in males range from 7.9 in China to 235 in Singapore and in females range from 5.5 in China to 116 in New Zealand and 109 in Singapore.

In several countries cerebrovascular mortality is higher than CHD mortality with China and Japan providing the clearest examples of this. This is likely to reflect the importance of hypertension as a risk factor in these countries and, as commented upon above, also coincides with a relatively high ratio of haemorrhagic stroke to ischaemic stroke in these two countries.

Prevention

As stated earlier CVD is the cause of most of the deaths and much of the disability seen in people with diabetes. Good evidence now exists that much of this disease burden can be prevented or, at the very least, delayed by appropriate preventative measures. The link between diabetes and CVD is so strong that the prevention agenda for both diseases can

be linked and integrated at many levels of the system. The high CVD risk in people with IGT and newly-diagnosed diabetes also emphasizes both the importance of primary prevention of diabetes in the context of overall prevention of CVD and the significance of diabetes as an ‘entry point’ for overall, comprehensive cardiovascular risk management. An effective prevention strategy should therefore include each of the following components:

• Primary prevention of diabetes, preferably integrated with other non-communicable disease prevention programmes. A carefully balanced combination of population-wide and targeted high-risk strategies should be employed.

• Secondary prevention of diabetes complications by optimal diabetes care.

• Overall risk factor management in people with diabetes. This requires intensive treatment of the whole range of involved risk factors and metabolic abnormalities and not just hyperglycaemia.

• Provision of targeted medical and revascularisation treatments to reduce death and disability in people who have already developed CVD.

• Careful design of healthcare systems to overcome barriers, ensure flexibility and provide adequate facilities for the overall management of CVD risk.



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Map 3.5Coronary heart disease in females (35-74 years): mortality rates per 100,000 population per year

Map 3.4Coronary heart disease in males (35-74 years): mortality rates per 100,000 population per year

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Map 3.7Cerebrovascular disease in females (35-74 years): mortality rates per 100,000 population per year

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174

References

1. Gu K, Cowie CC, Harris MI. Diabetes and decline in heart disease mortality in US adults. J Am Med Assoc 1999; 281:1291-1297.

2. Haffner SM, Lehto S, Rönnemaa T, Pyörälä K, Laakso M. Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without previous myocardial infarction. N Engl J Med 1998; 339:229-234.

3. International Diabetes Federation. Diabetes and Cardiovascular Disease: Time to Act. International Diabetes Federation, Brussels, 2001.

4. Miettinen H, Lehto S, Salomaa VV, et al. Impact of diabetes on mortality after the first myocardial infarction. Diabetes Care 1998; 21:69-75.

5. International Diabetes Federation. Diabetes Health Economics: Facts, Figures and Forecasts. International Diabetes Federation, Brussels, 1999.

The Economic Impact of Diabetes Chapter 4


175


The economic impact of diabetes is considerable. Its costs affect health

services, national productivity as well as individuals and families. Hospital in-patient costs for the treatment of complications are the largest single contributor to direct healthcare costs. Many of these complications and, therefore, their costs are preventable. Intensive therapy, directed at the control of blood glucose, blood pressure etc, has been shown to be cost-effective in that, although initial costs are increased, it decreases longer term costs as a result of delayed or prevented complications.

The annual direct healthcare costs of diabetes worldwide, for people in the 20-79 age bracket, is estimated to be at least 153 billion international dollars* and may be as much as 286 billion, or even more.

If predictions of diabetes prevalence are fulfilled, total direct healthcare expenditure on diabetes worldwide will be between 213 billion and 396 billion international dollars in 2025. This would mean that the proportion of the world’s healthcare budget being spent, in 2025, on diabetes care will be between 7% and 13% with high prevalence countries, such as Nauru, spending up to 40% of their budget.

In many countries a substantial proportion of healthcare costs are borne by the individual and the family. Estimates of the indirect cost of diabetes ie the cost of lost production are as high as direct costs or even higher than those for direct costs.

* see footnote a, page 183.



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Calculated costs for all countries

The first edition of Diabetes Atlas looked at published empirical estimates of the current direct healthcare costs of diabetes (1). While continuing to emphasize the importance of such estimates, this chapter in the second edition is wider in scope.

It puts forward, for the first time, calculated estimates of the current direct cost of diabetes care worldwide. It also uses the same method, together with predictions of the future burden of diabetes in these countries, to estimate the likely future direct cost burden of the disease in 2025. This widening of scope reflects the inclusion, in this edition of the Atlas, of diabetes prevalence data for all countries.

These future predictions of cost are as alarming as the future predictions of prevalence. They suggest that, unless effective prevention measures are introduced, expenditure devoted to diabetes and its complications will dominate the health economies of many countries by the end of the first quarter of the current century.

Importance of economics

Economic aspects of diabetes and diabetes care continue to attract attention as the world diabetes epidemic progresses and the healthcare sectors of countries remain under pressure to accomplish more and more within constrained resources.

Governments, diabetes associations, health professionals and people with diabetes themselves need to be aware of the current and future economic impact of the disease on the healthcare sector, the individual and family, and society.

They also need to be aware of the potential for reducing this cost burden

by increasing the effectiveness of surveillance and treatment for those who already have diabetes, by implementing primary prevention measures for those who are at high risk of developing type 2 diabetes and reducing the risk profile for type 2 diabetes in the population as a whole.

Economic information is an important component in making decisions about diabetes and diabetes healthcare. Decision makers are asking, or should be asking, such questions as:

• What is the economic impact of diabetes?

• How does this impact compare with that of other current health problems?

• What information is available on the cost-effectiveness of different methods for the prevention of diabetes?

• What do we know about the cost-effectiveness of delivering diabetes care in different ways?

IDF’s Task Force on Diabetes Health Economics has recently completed a review of currently available information on the cost-effectiveness of interventions relevant to diabetes prevention and care (2). A large number of interventions – intensive blood glucose and blood pressure control, the use of lipid lowering agents, screening for and treatment of diabetic retinopathy and active care of the feet, for example – are known to be effective. Evidence is accumulating that many of these are also cost-effective, or even cost-saving. Many of the costs of diabetes and its complications are, therefore, potentially preventable.

Availability of up-to-date information

Most of the estimates in the following sections are those that have appeared in the literature since the previous edition of Diabetes Atlas.

The future predictions of cost are as

alarming as the future predictions of diabetes prevalence.

They suggest that, unless effective

prevention measures are introduced,

expenditure devoted to diabetes and its complications will

dominate the health economies of many

countries by the end of the first quarter of the

current century.



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Considerable caution is required when considering these estimates and comparisons between them can only validly be made when they have been assembled using the same methods and the same assumptions. As with all cost of illness studies, the methods used are either ‘top down’ or ‘bottom up’.

In the ‘top down’ approach, aggregate data at national or local level of treatments, healthcare utilization etc are used together with unit costs for the appropriate item.

In the ‘bottom up’ approach, affected individuals are identified, their treatments and healthcare utilization events recorded and unit costs used to calculate the totals required.Each method has its own advantages and disadvantages. A third method – the calculation of direct costs by means of formulae – has been suggested and is described here with empirically derived estimates in sections which follow.

Direct costs

It is important to distinguish between two estimates of direct healthcare costs:

1 Cost of diabetes healthcare2 Total cost of care for people with

diabetes.

Cost of diabetes healthcareThis is the cost element that is attributable to diabetes itself or to the complications of diabetes. It clearly includes the costs of hospital admissions and other healthcare episodes for diabetic ketoacidosis, hypoglycaemia and other direct results of diabetes or its therapy.

The healthcare costs of diabetic neuropathy, retinopathy and nephropathy are also usually included. It is less clear, however, how much of the costs of care for such things as a myocardial infarction or stroke in a person with diabetes should be attributed to diabetes per se.

Total cost of care forpeople with diabetesThe second cost estimate includes all episodes of care for people with diabetes – diabetes-related healthcare and also those of care in which the main reason for the encounter is apparently unrelated to diabetes. The latter would include, for example, surgery for appendicitis or hip replacement or treatment for breast cancer in people with co-existing diabetes.

This second estimate has at least two advantages. First, it sidesteps the need to decide whether, or to what extent, a condition is or is not related to diabetes and, second, it incorporates the impact which diabetes may have on the costs of care even for such conditions as appendicitis, hip replacement or breast cancer in people with co-existing diabetes.

Lengths of hospital stay may be longer if diabetes co-exists. Drug bills are likely to be larger, care in general will be more intense and rehabilitation more complex and thus more costly. If such overall cost estimates are used then the incremental (or ‘extra’) cost of diabetes is calculated by subtracting the average costs of care for a person without diabetes from those of a person with diabetes, preferably using age, sex and ethnicity matched estimates.

Costs may be calculated from the point of view of the state or the individual and family. These latter costs are sometimes termed ‘out-of-pocket’ expenditures. More and more studies are focusing on these personal costs of care and on the potential for economic issues to influence the quality of care which people receive.

Direct costs:calculations using formulae

Formulae have been proposed by Jönsson (3) which can enable countries or regions to estimate direct healthcare



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costs of diabetes, or any other disease, without the need for costly and time consuming empirical studies (see Box 4.1).

Of the three variables needed to make these calculations, estimates of the prevalence of diabetes (P) are now available for every country and the total healthcare budget (THCB) for most countries is available from published sources. However, R, the ratio of the cost of care for people with diabetes compared with the cost of care of people without diabetes, is not widely available in various countries and some assumptions need to be made in order to use these formulae.

The data to hand suggest that, at least for countries with high or moderate incomes, the value of R lies between 2 and 3, eg Rubin et al’s (4) estimate of 2.6 for the United States.

Tables 4.1-4.8 give estimates of the cost of diabetes care for persons aged 20-79 using the first formula in Box 4.1. The tables use, from the data in Chapter 1, population estimates and diabetes

prevalence estimates for the 20-79 year age group for 2003, and data on per capita health expenditure (in international dollars) as presented in the World Health Report 2002 (5). By multiplying the 20-79 year population figures by the per capita health expenditures, the total healthcare budget for that age group is derived. Calculations are then presented for values of R of 2 and 3. Figure 4.1 shows the values of R of 2 and 3 by region.

All countries are represented except for 22 countries or areas for which no value of per capita health expenditure is given in the WHO Report*. These represent 1% of the world’s population.

The calculated estimates for some countries can be validated against the empirically derived estimates listed below. For example, the American Diabetes Association’s latest estimate for the direct cost of diabetes over all age groups in the USA is US$91.8 billion in 2002 (6). This is within the range of calculated costs, by formula, using the diabetes prevalence and total healthcare budget figures for the USA which is 66.7 billion international dollars for R = 2 to 124.2 billion international dollars for R = 3 (Table 4.5). The empirically derived figure of US$91.8 billion corresponds to a value of R lying between 2.5 and 2.6.

Empirically derived cost estimates

AfricaThere is a growing interest in the economics of diabetes in Africa. However, no recent country specific estimates have been published since the work of Chale and her colleagues in Tanzania in 1992 (7). Cost of illness data from African countries is badly needed.

Box 4.1

Formulae for calculating direct healthcare costs of diabetes (3)

1. Cost of diabetes care: P(R – 1) × THCB P(R – 1) + 1

2. Cost of care for people with diabetes: P × R × THCB P(R – 1) + 1

P = prevalence of diabetesR = ratio of the cost of care for people with diabetes/

cost of care for people without diabetesTHCB = total healthcare budget

* Anguilla, Antigua and Barbuda, Aruba, Bermuda, British Virgin Islands, Cayman Islands, China Hong Kong, China Macau, East Timor, French Guiana, French Polynesia, Guadeloupe, Guam, Martinique, Occupied Palestinian Territories, Puerto Rico, Reunion, Saint Lucia, Taiwan, Tanzania, Tokelau and Western Sahara.



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Eastern Mediterraneanand Middle EastData are also extremely sparse for the countries in the Eastern Mediterranean and Middle East Region. There appears to be nothing published since the study by Arab (8) in Egypt and by Rekik et al (9) in Tunisia. It is worth noting that, in the Tunisian study, the total annual cost of medication and outpatient care for people with diabetes was 2.6 times that for people without diabetes (US$179 versus US$68) and that a clear relationship was found between higher costs and the presence of ‘degenerative complications’.

EuropeDiabetes healthcare costs in Sweden have been extensively studied since the early estimates by Jönsson and others. Recently, Norlund et al (10) have estimated that 28% of the extra cost of diabetes is attributable to the costs of healthcare (the remainder are indirect costs). This amounts to an estimated SEK9,548 (US$1,118) per person per year.

Björk (11) has estimated that three times the healthcare resources are being spent on diabetes complications compared with that spent on diabetes control while Jönsson et al (12) have made the important observation that excess costs in the first year after the diagnosis of diabetes in young adults (15-34 years at diagnosis) are considerably greater than those incurred seven years later ie eight years after diagnosis. Annual excess costs at these two time points for men were US$4,743 and US$2,010 respectively while, for women, the equivalent figures were US$4,976 and US$2,734. The cost profile during the natural history of the condition in any one person with diabetes seems, therefore, to be ‘U’ or ‘J’ shaped, with, immediately after diagnosis, relatively high costs which subsequently fall and then rise again with the onset of complications.

From France (13) comes the observation that medical care costs for people with diabetes are around 3,048 (US$3,265) per person per year (twice the average medical care consumption in the French population) while in the Netherlands, van Os et al (14) have estimated diabetes healthcare costs to be a modest 2.5% of the total healthcare budget.

Using a number of complementary data sources, Currie and colleagues have published several cost estimates for diabetes and its complications in the same defined United Kingdom (UK) population. In 1997 they published one of the few estimates of future costs of diabetes (15). More recently, they have been involved with others in developing a computer-based model for testing the effects of demographic, epidemiological and therapeutic changes on these future costs (16), thus linking descriptive estimates of the cost of diabetes with cost-effectiveness information from studies such as the UK Prospective Diabetes Study (UKPDS).

Figure 4.1Estimates of the costs of diabetes care by region

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The findings of the CODE-2 (Cost of Diabetes in Europe – Type 2) and T2ARDIS (Type 2 Diabetes Accounting for a Major Resource Demand In Society) studies agree that the financial burden of type 2 diabetes in the United Kingdom is just under 5% of the nation’s healthcare budget in 1998, that there is a strong relationship between hospital costs and the presence of complications, and that the economic and psychosocial burden of diabetes extends not only to affected individuals but also to their carers (17).

North AmericaThe most recent peer-reviewed estimate of the annual direct cost of diabetes in the USA is the American Diabetes Association’s 2002 estimate of US$91.8 billion (6). This compares with the previous estimate for 1997 of US$44 billion (18). This is a total figure covering all aspects of diabetes and its complications.

The US literature also has a number of estimates which break down the total cost figure into estimates for specific, individual complications. For example, O’Brien et al (19) estimated the ‘event cost’ of a single myocardial infarction in a person with diabetes to be US$27,630 (1996 prices). This leads on to a ‘state cost’ (ie the annual additional cost of care following such an event) of US$2,185 per annum. They point out that some early complications, such as the presence of microalbuminuria (the presence of small traces of protein in the urine), are low cost, estimated as a US$14 per annum ‘state cost’, but, if left undetected and untreated, lead to extremely high later costs, in this case the US$53,660 per annum ‘state cost’ of end-stage renal failure.

In a similar fashion, for people with diabetes receiving their healthcare from one health maintenance organization, a major cardiovascular disease event eg myocardial infarction was estimated to increase the cost of care by 360% (20).

End-stage renal failure had the effect of increasing costs by 771%.

Recent work in Canada suggests that the total direct healthcare cost of diabetes is US$3.5 billion in 1998 prices (21). Comparison with the estimates in Table 4.5 of 4.7 billion international dollars (R=2) and 8.7 billion international dollars (R=3) suggests that this may be an underestimate (or the calculated figures an overestimate).

The empirical Canadian work emphasized the dominant contribution of cardiovascular disease in people with diabetes (35% of direct and indirect costs) and declared that “the cost of preventive treatment is insignificant compared with the downstream costs of failure to adequately treat the disease”.

South and Central AmericaOf considerable interest, given the range of countries studied, is the work of Barceló et al (22). The direct healthcare costs were estimated as US$10.69 billion for 25 countries in 2000 (Table 4.9). The contributions of the various items to the direct cost total are shown in Figure 4.2, while the specific contributors to the cost of diabetic complications are shown in Figure 4.3. Indirect costs were also calculated and were around five times the direct cost total.

The method employed by Barceló et al is the ‘top down method’ (22). They used population prevalence estimates for diabetes, treatment and healthcare utilization figures taken both from individual studies and routinely collected data (see Table 4.9). These were then multiplied by unit costs for insulin, oral hypoglycaemics and other items. Like all top-down studies, the accuracy of the results is dependent on the validity of the assumptions made. Nevertheless, this work represents a considerable advance in pulling together comparable data from Latin American and Caribbean countries not previously studied (see Map 4.1).



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South-East AsiaIn India, estimates have been made of the out-of-pocket expenses resulting from diabetes. This is the direct healthcare impact on the person with diabetes who may need to spend a considerable proportion of the family income in order to receive treatment at a chosen location eg outside the public sector. In a diabetes centre in Chenai, families in the poorest section of the population may have to spend as much as 25% of their income in order to obtain the care of their choice (23).

Western PacificA similar theme, of the personal direct costs, is developed by Simmons et al (24) for patients resident in an inner suburb of Auckland, New Zealand. Not only were these patients spending a significant proportion of their income on diabetes care but between a fifth and a half (depending on income and ethnic origin) of those taking part reported that personal costs had an inhibitory effect on self-monitoring of blood glucose,self-medication and even on insulin therapy amongst those who needed it.

Taiwan has been estimated to spend 11.5% of its healthcare budget on the treatment of people with diabetes. This comes from a national extrapolation of Bureau of National Health Insurance claims between July 1997 and July 1998 (25). The average cost of care for someone with diabetes in this system was 4.3 times higher than that for a person without diabetes.

Indirect costs andintangible costs

There is much less information on the indirect costs of diabetes, ie cost of lost production, partly because of the methodological difficulties involved in its collection. When indirect costs have been calculated, they have been estimated as around the same, sometimes more than direct costs. For example, in the

American Diabetes Association 2002 study mentioned above, indirect costs were estimated to be US$39.8 billion compared with direct costs of US$91.8 billion and compared with a previous estimate of indirect costs of US$54 billion (6).

Figure 4.2Contributions to total direct healthcare cost in 25 Latin American and Caribbean countries, 2000 (adapted from Barceló et al (22))

Figure 4.3Specific contributors to the cost of diabetic complications, 2000 (adapted from Barceló et al (22))

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OHA oral hypoglycaemic agents



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In a study of 30,000 people in Manitoba, Canada, the 600 individuals who had diabetes were twice as likely not to be in the work force as those without diabetes (26). Predicted increases in the prevalence of diabetes worldwide emphasize the fact that the economically productive age groups within society will be particularly affected. Given these predictions, the effects on lost production are likely to be considerable and need to be quantified more extensively.

Considerable interest is currently being shown in information of intangible costs (quality of life) and standardized methods to obtain this are becoming available. Again, however, the data available are sparse and none are shown in this edition of the Diabetes Atlas.

Predictions of the future costs of diabetes

Apart from the Bagust et al study (16) and the predictions, for Australia, included in McCarty et al (27), there have

been no predictions of the likely future costs of diabetes. As the prevalence of diabetes increases, the likelihood is that costs will also rise although the magnitude will depend on a number of things, particularly, the extent to which complications will be prevented or delayed.

The ratio of the cost of care of people with diabetes to the cost of care of those without (R in Jönsson’s formulae – Box 4.1) may well rise initially, as the increased costs of more intensive treatment assert themselves. However, this ratio of costs is likely then to fall as the preventive effect of this more intensive therapy becomes manifest.

Using, again, the first formula listed in Box 4.1 together with the predictions of prevalence in 2025 in Chapter 1, the future costs of diabetes can be calculated given certain assumptions. If it is assumed that per capita health expenditure of the countries listed in Tables 4.2 to 4.8 will not increase in real terms, then each country’s total health expenditure in 2025 for people aged 20–79 years can be calculated using this per capita figure and the predicted population for that year.

Table 4.10 lists the overall predictions by region (see Figure 4.4) and, for each region, the predicted costs for the country with the highest diabetes care expenditure expressed as a percentage of total health expenditure. The predicted diabetes costs for all other countries are available from the author or can be calculated using the first formula given in Box 4.1 and the appropriate data for that country given in Chapter 1.

Figure 4.4Predictions of the future costs of diabetes (as % of total healthcare expenditure) by region, 2025

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Map 4.1Estimated total direct healthcare costs of diabetes per person (USD) in 25 Latin American and Caribbean countries (adapted from Barceló et al (22))

Cost of diabetes care per year (’000 international dollarsa) given values for Rb of:

Region R=2 R=3

AFR 784,539 1,522,237

EMME 3,594,864 6,677,924

EUR 42,768,723 80,520,020

NA 73,526,777 136,815,507

SACA 7,086,861 13,465,503

SEA 2,602,742 4,937,200

WP 22,635,907 42,906,055

Worldwide Total 153,000,412 286,844,446

Table 4.1 Calculated estimates of the costs of diabetes care by region

a. The international dollar is a common currency unit that takes into account differences in the relative purchasing power of various currencies. Figures expressed in international dollars are calculated using purchasing power parities (PPP), which are rates of currency conversion constructed to account for differences in price level between countries.

b. R = Ratio of cost of care for people with diabetes/cost of care for people without diabetes

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Per capita health expenditure

(international dollarsa)

Cost of diabetes care per year (’000 international dollarsa)

given values for Rb of:

Country R=2 R=3

Angola 52 7,940.6 15,477.0

Benin 27 1,652.0 3,236.0

Botswana 358 8,815.1 17,044.0

Burkina Faso 37 4,873.4 9,495.1

Burundi 16 600.0 1,184.5

Cameroon 55 3,186.4 6,322.5

Cape Verde 92 476.5 932.0

Central African Republic 37 1,493.4 2,920.6

Chad 19 1,860.5 3,624.3

Comoros 35 303.9 593.3

Congo, Democratic Republic of 21 11,313.6 22,096.7

Congo, Republic of 25 875.1 1,707.6

Côte d’Ivoire 45 8,170.3 15,976.1

Djibouti 63 888.6 1,697.4

Equatorial Guinea 103 562.8 1,099.1

Eritrea 25 888.1 1,743.8

Ethiopia 17 9,182.5 18,035.5

Gabon 171 3,140.2 6,107.1

Gambia 46 693.2 1,357.4

Ghana 51 16,482.7 31,932.0

Guinea 56 4,329.8 8,489.3

Guinea-Bissau 28 323.9 635.3

Kenya 115 40,360.2 78,826.2

Lesotho 100 3,113.9 6,046.6

Liberia 3 93.5 183.4

Madagascar 33 6,180.3 12,070.1

Malawi 38 3,258.2 6,409.4

Mali 32 3,352.3 6,573.0

Mauritania 52 2,310.8 4,469.9

Mozambique 30 7,756.9 15,065.0

Namibia 366 9,055.1 17,586.6

Niger 22 3,130.3 6,077.7

Nigeria 20 23,838.5 46,651.9

Reunion N/A

Rwanda 40 1,637.4 3,238.4

Sao Tome and Principe 23 64.9 126.5

Senegal 56 5,679.4 11,114.1

Seychelles 758 4,049.6 7,299.4

Sierra Leone 28 1,340.3 2,625.2

Somalia 7 629.8 1,232.5

South Africa 663 539,377.0 1,044,412.1

Swaziland 210 2,732.7 5,311.9

Tanzania N/A

Togo 36 1,590.9 3,119.1

Uganda 36 5,491.5 10,818.3

Western Sahara N/A

Zambia 49 6,663.1 12,945.5

Zimbabwe 171 24,779.6 48,327.5

AFR Total 784,539 1,522,237

Table 4.2 Calculated estimates of the costs of diabetes care – African Region



N/A not available



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Country R=2 R=3

Afghanistan 9 7,627.1 14,174.9

Algeria 142 99,274.1 191,019.1

Armenia 192 37,478.6 69,735.7

Bahrain 641 36,532.9 64,667.7

Egypt 138 486,102.3 892,230.6

Iran 336 450,956.0 871,535.0

Iraq 573 487,336.9 909,974.6

Jordan 325 56,198.5 105,506.7

Kuwait 542 76,044.3 136,631.8

Lebanon 696 91,739.2 173,117.5

Libya 392 43,299.1 83,644.5

Morocco 166 116,582.9 224,217.7

Occupied Palestinian Territories N/A

Oman 448 58,322.1 105,830.0

Pakistan 76 432,936.1 803,003.8

Qatar 849 46,040.1 80,924.1

Saudi Arabia 684 620,292.9 1,142,333.8

Sudan 51 25,824.0 50,117.8

Syria 51 25,364.9 47,930.4

Tunisia 472 123,476.7 236,579.9

United Arab Emirates 761 232,769.2 398,837.1

Yemen 70 40,665.5 75,911.4

EMME Total 3,594,864 6,677,924

Table 4.3 Calculated estimates of the costs of diabetes care – Eastern Mediterranean and Middle East Region



N/A not available



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Country R=2 R=3

Albania 129 9,319.4 17,978.1

Andorra 1,639 5,929.6 11,059.0

Austria 2,171 498,962.5 961,054.0

Azerbaijan Republic 57 19,055.6 35,789.7

Belarus 430 268,819.5 495,419.9

Belgium 2,269 686,248.6 1,319,504.9

Bosnia and Herzegovina 319 85,970.0 158,079.0

Bulgaria 198 106,386.3 194,996.3

Croatia 638 120,022.6 227,502.4

Cyprus 1,415 37,285.6 71,106.4

Czech Republic 1,031 691,931.6 1,273,362.9

Denmark 2,428 601,903.8 1,131,216.2

Estonia 556 48,799.6 89,656.9

Finland 1,667 425,125.2 796,447.7

France 2,335 5,832,389.7 11,017,934.3

Georgia, Republic of 199 60,669.1 112,057.3

Germany 2,754 7,030,622.9 13,504,262.2

Greece 1,390 645,813.0 1,221,304.7

Hungary 846 548,733.3 1,008,471.7

Iceland 2,626 9,532.1 18,709.6

Ireland, Republic of 1,944 168,899.1 327,168.1

Israel 2,338 614,662.6 1,152,777.9

Italy 2,040 5,513,866.1 10,388,485.7

Kazakhstan 211 111,821.8 212,633.6

Kyrgyzstan 145 17,348.4 33,320.2

Latvia 398 62,882.1 115,391.7

Lithuania 420 95,557.6 175,996.3

Luxembourg 2,740 32,989.4 63,636.6

Macedonia 300 19,991.7 38,201.2

Malta 803 18,969.8 34,988.4

Moldova, Republic of 64 14,290.0 26,547.0

Monaco 1,877 2,477.0 4,685.2

Netherlands 2,255 939,828.2 1,814,885.1

Norway 2,373 470,761.4 885,799.1

Poland 578 1,329,141.0 2,455,541.3

Portugal 1,469 796,331.3 1,484,921.8

Romania 190 264,165.7 487,023.5

Russian Federation 405 3,594,804.5 6,630,412.9

San Marino 2,805 3,175.5 6,010.7

Serbia and Montenegro 237 94,735.9 179,935.4

Slovakia 690 215,042.2 398,282.1

Slovenia 1,462 193,676.0 356,136.8

Spain 1,539 4,206,901.2 7,718,179.9

Sweden 2,097 893,237.9 1,673,172.8

Switzerland 3,229 1,054,290.7 1,986,431.5

Tajikistan 29 3,264.3 6,305.0

Turkmenistan 286 68,422.3 125,505.5

Turkey 323 893,338.1 1,677,294.1

Ukraine 152 478,529.5 879,350.3

United Kingdom 1,774 2,852,838.2 5,497,291.5

Uzbekistan 86 8,963.5 17,795.8

EUR Total 42,768,723 80,520,020

Table 4.4 Calculated estimates of the costs of diabetes care – European Region





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Country R=2 R=3

Anguilla N/A

Antigua and Barbuda N/A

Aruba N/A

Bahamas 1,137 18,049.9 33,352.5

Barbados 915 13,577.7 25,183.0

Belize 273 1,833.1 3,477.4

Bermuda N/A

British Virgin Islands N/A

Canada 2,534 4,729,909.0 8,739,290.2

Cayman Islands N/A

Dominica, Commonwealth of 340 1,098.8 2,041.1

Grenada 351 1,215.5 2,284.7

Guadeloupe N/A

Guyana 197 5,127.5 9,702.4

Haiti 54 12,066.9 22,890.1

Jamaica 208 21,452.3 40,192.1

Martinique N/A

Mexico 483 1,982,045.4 3,707,672.7

St Kitts and Nevis 658 927.7 1,750.3

St Lucia 272 1,599.0 2,997.5

St Vincent and the Grenadines 374 1,876.9 3,505.9

Trinidad and Tobago 468 29,455.4 54,899.6

USA 4,499 66,706,541.4 124,166,267.2

NA Total 73,526,777 136,815,507

Table 4.5 Calculated estimates of the costs of diabetes care – North American Region



N/A not available



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Country R=2 R=3

Argentina 1,091 1,349,719.3 2,566,892.2

Bolivia 158 32,687.7 62,489.7

Brazil 631 3,409,088.8 6,498,705.1

Chile 697 367,540.7 697,779.1

Colombia 616 648,755.2 1,246,094.6

Costa Rica 481 77,392.0 145,399.1

Cuba 186 173,025.7 309,922.1

Dominican Republic 357 162,156.2 297,257.2

Ecuador 78 26,851.5 51,360.5

El Salvador 388 82,225.6 155,356.1

French Guiana N/A

Guatemala 192 56,149.8 106,745.2

Honduras 165 29,275.4 55,565.5

Netherlands Antilles 2,255 36,541.6 65,862.6

Nicaragua 108 16,017.2 30,285.0

Panama 464 55,970.5 104,833.0

Paraguay 323 35,824.2 69,076.4

Peru 238 179,381.8 342,020.8

Puerto Rico N/A

Suriname 424 8,468.3 15,687.7

Uruguay 1,005 141,283.2 265,714.1

Venezuela 280 198,506.0 378,457.2

SACA Total 7,086,861 13,465,503

Table 4.6 Calculated estimates of the costs of diabetes care – South and Central American Region



N/A not available





Country R=2 R=3

Bangladesh 47 131,898.0 254,283.8

Bhutan 64 2,389.1 4,614.7

India 71 2,380,739.0 4,510,916.9

Maldives 254 648.7 1,274.8

Mauritius 330 25,178.2 45,900.8

Nepal 66 30,974.2 59,617.5

Sri Lanka 120 30,915.1 60,591.9

SEA Total 2,602,742 4,937,200

Table 4.7 Calculated estimates of the costs of diabetes care – South-East Asian Region





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Country R=2 R=3

Australia 2,213 1,780,583.1 3,365,036.0

Brunei Darussalam 618 12,402.2 22,631.4

Cambodia 111 13,627.7 26,737.0

China, Hong Kong N/A

China, Macau N/A

China, People’s Republic of 205 4,751,974.7 9,259,469.2

Cook Islands 426 321.0 606.9

East Timor N/A

Fiji 194 6,746.8 12,535.9

French Polynesia N/A

Guam N/A

Indonesia 84 209,963.7 412,172.4

Japan 2,009 12,642,179.4 23,745,326.3

Kiribati 140 487.9 922.3

Korea, Democratic People’s Republic of 33 24,287.4 46,278.8

Korea, Republic of 909 1,867,440.5 3,522,931.2

Lao People’s Democratic Republic of 52 1,435.7 2,841.9

Malaysia 234 267,650.0 492,852.2

Marshall Islands 312 1,148.2 2,126.2

Micronesia 343 1,767.9 3,326.7

Mongolia 120 2,390.7 4,716.7

Myanmar 24 7,397.4 14,636.5

Nauru 525 937.9 1,533.3

New Caledonia N/A

New Zealand 1,623 296,672.6 554,408.9

Niue 1,111 101.0 185.2

Palau 482 444.9 826.3

Papua New Guinea 147 7,081.4 13,900.4

Philippines 167 164,753.2 321,967.4

Samoa 221 918.0 1,738.8

Singapore, Republic of 913 303,674.6 547,303.8

Solomon Islands 97 427.8 838.8

Taiwan N/A

Thailand 237 204,644.4 401,088.9

Tokelau N/A

Tonga 312 2,274.3 4,093.9

Tuvalu 860 475.3 881.0

Vanuatu 119 256.2 501.7

Vietnam 129 61,440.6 121,638.6

WP Total 22,635,907 42,906,055

Table 4.8 Calculated estimates of the costs of diabetes care – Western Pacific Region



N/A not available



190



191

Population No. of peoplewith diabetes

Direct cost (population)

Direct cost per person with diabetes

per year

Average healthcare expenditure

per person per year

Country (000’s) (000’s) (USD million) (USD) (USD)

Argentina 34,768 1,250.3 747.0 597 320

Bahamas 279 12.8 10.7 836

Barbados 260 23.3 12.8 549

Bolivia 7,414 153.9 85.5 556 12

Brazil 159,014 4,532.6 3,952.3 872 159

Chile 14,210 496.5 295.0 594 120

Colombia 35,814 937.7 414.9 442 128

Costa Rica 3,424 154.9 96.6 624 197

Cuba 10,964 592.4 722.2 1,219

Dominican Republic 7,823 254.1 225.7 888 33

Ecuador 11,460 267.3 233.4 873 35

El Salvador 5,662 219.4 137.4 626 54

Guatemala 10,621 368.7 291.2 790 26

Guyana 856 28.4 20.4 718

Haiti 7,124 79.5 48.0 604 7

Honduras 5,654 193.0 113.8 590 23

Jamaica 2,468 181.4 136.1 750 56

Mexico 91,145 3,738.0 1,974.2 528 132

Nicaragua 4,123 136.1 85.0 625 22

Panama 2,631 120.5 104.4 866 196

Paraguay 4,828 92.5 72.0 778 46

Peru 23,532 606.8 502.4 828 56

Trinidad and Tobago 1,287 71.3 38.0 533

Uruguay 3,186 119.0 94.6 795 116

Venezuela 21,844 610.8 307.5 503 119

Total 470,391 15,241 10,691

Table 4.9 Estimated number of people with diabetes1 and estimated total direct healthcare costs of diabetes in 25 Latin American and Caribbean countries, 2000

1. Prevalence estimates taken from Amos et al, 199728.

Source: Barceló et al22



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Cost of diabetes per year(’000 international dollarsa)

Cost of diabetes per year(as % of total healthcare expenditure)

for two values of ratiob: for two values of ratiob:

Region Country R = 2 R = 3 R = 2 R = 3

AFR 1,192,556.3 2,305,837.2 3.3 6.3

Seychellesc 6,595.2 11,673.8 13 23

EMME 7,335,249.7 13,511,171.7 8.0 14.7

United Arab Emiratesc 371,147.6 620,376.7 19.7 32.8

EUR 50,539,601.5 94,318,016.1 6.7 12.5

Tajikistanc 8,378.1 15,142.0 10.7 19.3

NA 106,030,745.8 195,147,133.0 8.7 15.9

Barbadosc 22,547.0 40,493.4 11.4 20.4

SACA 12,509,955.8 23,469,465.1 6.4 12.0

Cubac 239,831.9 418,051.8 14.7 25.7

SEA 5,278,860.5 9,842,467.0 7.7 14.4

Mauritiusc 41,665.2 73,871.2 12.8 22.7

WP 30,696,300.4 57,700,700.3 5.7 10.8

Nauruc 1,316.1 2,104.7 25.1 40.1

Total 213,583,269.9 396,294,790.4 7.3 13.5

Table 4.10 Predictions of the future costs of diabetes by region (20-79 age group), 2025


b. R = Ratio of cost of care for people with diabetes/cost of care for people without diabetesc. Costs for countries within each region that have the highest value of diabetes costs as percentage of total

national health expenditure.



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References

1. International Diabetes Federation. The Costs of Diabetes. In Diabetes Atlas 2000. International Diabetes Federation, Brussels, 2000; 225–235.

2. International Diabetes Federation. Cost-effective approaches to diabetes care and prevention. IDF Task Force on Diabetes Health Economics. International Diabetes Federation, Brussels, 2003.

3. Jönsson B. The economic impact of diabetes. Diabetes Care 1998; 21 Suppl 3: C7-C10.

4. Rubin R, Altman WM, et al. Healthcare expenditures for people with diabetes mellitus, 1992. J Clin Endocrinol Metab 1994; 78: 809A-809F.

5. World Health Organization. The World Health Report 2002. World Health Organization, Geneva, 2003.

6. American Diabetes Association. Economic Costs of Diabetes in the U.S. in 2002. Diabetes Care 2003; 26:917-932.

7. Chale SS, Swai AB, Mujinja PG, McLarty DG. Must diabetes be a fatal disease in Africa? Study of costs of treatment. BMJ 1992; 304:1215-1218.

8. Arab M. Diabetes mellitus in Egypt. World Health Statistics Quarterly 1992; 45:334-337.

9. Rekik M, Abid M, Hachicha J, Abbes R, Moujahed M, Jarraya A. Direct cost of the ambulatory management of diabetes at the outpatient clinic of the National Social Security Fund of Sfax. Bulletin of the World Health Organization 1994;72:611-614.

10. Norlund A, Apelqvist J, Bitzen PO, Nyberg P, Schersten B. Cost of illness of adult diabetes mellitus underestimated if comorbidity is not considered. J Intern Med 2001; 250:57-65.

11. Björk S. The cost of diabetes and diabetes care. Diabetes Res Clin Pract 2001; 54 Suppl 1:S13-S18.

12. Jönsson P, Marke LA, Nystrom L, Wall S, Ostman J. Excess costs of medical care 1 and 8 years after diagnosis of diabetes: estimates from young and middle-aged incidence cohorts in Sweden. Diabetes Res Clin Pract 2000; 50 Suppl 1:35-47.

13. Detournay B, Fagnani F, Phillippo M, Pribil C, Charles MA, Sermet C, Basdevant A, Eschwege E. Obesity morbidity and healthcare costs in France: an analysis of the 1991-1992 Medical Care Household Survey. Int J Obes Relat Metab Disord 2000; 24:151-155.

14. van Os N, Niessen LW, Koopmanschap MA, van der Lei J. Detailed analysis of the societal costs of diabetes mellitus. Ned Tijdschr Geneeskd 2000; 29:842-846.

15. Currie CJ, Kraus D, Morgan CL, Gill L, Stott NCH, Peters JR. NHS Acute Sector Expenditure for Diabetes: the Present, Future, and Excess In-patient Cost of Care. Diabet Med 1997; 14:686-692.

16. Bagust A, Hopkinson PK, Maier W, Currie CJ. An economic model of the long-term healthcare burden of Type II diabetes. Diabetologia 2001; 44:2140-2155.

17. Williams R, Gillam S, Murphy M, Holmes J, Pringle M, Bootle S, Bottomley J, Baxter H, Chandler F. The True Costs of Type 2 Diabetes in the UK – Findings from T2ARDIS and CODE-2 UK. Monograph of studies supported by GlaxoSmithKline. GlaxoSmithKline UK, Uxbridge, 2002.

18. American Diabetes Association. Economic Consequences of Diabetes Mellitus in the U.S. in 1997. Diabetes Care 1998; 21:296-309.

19. O’Brien JA, Shomphe LA, Kavanagh PL, Raggio G, Caro JJ. Direct Medical Costs of Complications Resulting from Type 2 Diabetes in the US. Diabetes Care 1998;21:1122-1128.

20. Brown JB, Pedula KL, Bakst AW. The Progressive Cost of Complications in Type 2 Diabetes Mellitus. Arch Intern Med 1999; 159:1873-1880.

21. Dawson KD, Gomes D, Gerstein H, Blanchard JF, Kahler KH. The Economic Cost of Diabetes in Canada, 1998. Diabetes Care 2002; 25:1303-1307.

22. Barceló A, Aedo C, Rajpathak S, Robles S. The cost of diabetes in Latin America and the Caribbean. Bulletin of the World Health Organization 2002; in press.

23. Shobhana R, Rao PR , Lavanya A, Williams R, Vijay V, Ramachandran A. Expenditure on healthcare incurred by diabetic subjects in a developing country - a study from southern India. Diabetes Res Clin Pract 2000; 48:37-42.

24. Simmons D, Peng A, Cecil A, Gatland B. The personal costs of diabetes: a significant barrier to care in South Auckland. N Z Med J 1999; 112:383-385.

25. Lin T, Chou P, Lai M, Tsai S, Tai T. Direct cost-of-illness of patients with diabetes mellitus in Taiwan. Diabetes Res Clin Pract 2001; 54 Suppl 1:43-46.

26. Kraut A, Walld R, Tate R, Mustard C. Impact of Diabetes on Employment and Income in Manitoba, Canada. Diabetes Care 2001; 24:64-68.

27. McCarty DJ, Zimmet P, et al. The Rise and Rise of Diabetes in Australia. International Diabetes Institute, Victoria, 1996.

28. Amos A, McCarty DL, et al. The rising global burden of diabetes and its complications: estimates and projections to the year 2010. Diabet Med 1997; 14 Suppl 5:S1-S85.

Access to Insulin and Diabetes SuppliesChapter 5


193

Access to Insulin

and Diabetes Supplies

Chapter 5

One of the major breakthroughs in medical sciences of the last century was the discovery of insulin in 1921. This discovery meant that people with diabetes who were insulin-treated survived the acute effects of the disease. The fact of the matter is that some eighty years later so many people in the world are still dying because of lack of access to insulin. Unfortunately, international economics still determines who should live or die, while we all watch on. This lack of access to insulin may be chronic or acute depending on the circumstances.

Acute lack of access to insulin occurs due to natural disaster, for example the earthquake in the Democratic Republic of Congo, civil unrest including war, for example the recent Balkan war, or financial crisis as was the case in Argentina. Nevertheless, the major problem lies in the widespread chronic lack of access to insulin that poses a serious threat to the developing countries of the world.

For proper delivery of diabetes care, insulin, insulin syringes and needles should be available, accessible and at an affordable cost to all people with diabetes who require them. Continuous accessibility to insulin is still a major problem in many developing countries especially those in sub-Saharan Africa such that there are reports of premature deaths due to the chronic lack of access to insulin in some of these countries.

The fact of the matter is that some eighty years after the discovery of insulin so many people in the world are still dying because of lack of access to insulin. Unfortunately, international economics still determines who should live or die, while we all watch on.



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This chapter focuses on the chronic lack of access to insulin because the International Diabetes Federation (IDF) Task Force on Insulin and major insulin manufacturers have put in place a mechanism to alleviate the acute lack of access to insulin whenever a situation arises.

Magnitude of the problem

The IDF Task Force on Insulin conducted a survey on the global access to insulin in 1997. In that survey, 48 of the 73 responding countries reported continual and uninterrupted availability of insulin in urban areas, whereas 20 reported that insulin was available 25-99% of the time and 5 reported availability of less than 25%.

The 1997 survey showed that in the seven IDF regions access to insulin,

syringes and needles 100% of the time was greater in urban than in rural areas (48 vs 32 for insulin and 41 vs 29 for syringes and needles) whereas the reverse was true for lack of access ie less than 25% of the time (21 vs 5 for insulin and 20 vs 7 for syringes and needles). The chronic lack of access to insulin, syringes and needles was more common in Africa than elsewhere. South and Central America also suffered from the chronic lack of access to syringes and needles. Both these problems were least common in Europe.

A similar survey, the Global Access to Insulin and Diabetes Supplies Survey, was conducted by the IDF Task Force on Insulin in 2003. The results of this survey are summarized in this chapter. Eighty-five participants from 74 countries completed the questionnaire on insulin accessibility.

It is regrettable that many developing countries did not participate in this survey despite several reminders. There are several shortcomings in drawing absolute conclusions from such a survey; however, it is the only reliable document which we have to assess global access to insulin, syringes and needles.

Global access to insulin

Forty-four and 40 of the 74 countries reported continual and uninterrupted access to insulin for people with type 1 and type 2 diabetes respectively. However, it is significant to note that people with type 1 diabetes in 30 countries did not have access to insulin 100% of the time (see Table 5.1), while people with type 2 diabetes in 34 countries did not have 100% access (see Table 5.2).

The distribution of access to insulin was different in the various regions for both people with type 1 and type 2 diabetes (see Figures 5.1 and 5.2). Only Africa had no country with 100%

Box 5.1

What is Insulin?

Insulin is the internal secretion of the pancreas formed by groups of cells called the islets of Langerhans in this

organ. It is the hormone needed to enable glucose to enter the cells and provide energy. Insulin is also important in keeping blood glucose levels within the acceptable limits.

Insulin is injected into the body by people with type 1 diabetes in whom the cells that produce insulin have been destroyed. This is the most common form of diabetes in children and young adults, and they depend on insulin for survival. Insulin may also be used by people with type 2 diabetes. In type 2 diabetes, the body needs more insulin than it can produce.

Since the landmark discovery of insulin by Frederick Banting and Charles Best in 1921, huge steps forward have been made in research and development in creating genetically engineered human insulin. Until recently insulin was derived from a limited resource of the pancreas of cattle and pigs.



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accessibility to insulin. The countries with the lowest accessibility were the Democratic Republic of Congo where people with type 1 diabetes had access to insulin for less than 25% of the time and Zambia where those with type 2 diabetes had access only 26-49% of the time. In Europe, Ukraine had the lowest accessibility to insulin (less than 25%); in South and Central America, El Salvador and Peru (26-49%) and in North America, Guyana (50-74 %).

Causes of lack of access to insulinThe most important causes of the lack of access to insulin in both people with type 1 and type 2 diabetes were (see Figure 5.3):

• insulin is too expensive;• lack of availability in all regional areas;• transportation problems;• lack of adequate supply to meet

demand; and• very poor quality of insulin.

High cost was the most important cause for the lack of access to insulin in people with type 1 diabetes in most countries in Africa (7 out of 9), but less so in South and Central America (3 out of 8) and North America (2 out of 10) (see Table 5.3). Two countries, Zambia and Sri Lanka, reported poor quality of insulin as a cause of lack of access to insulin in people with type 2 diabetes (see Table 5.4).

Cost of insulin

At present, human insulin is the most available form of insulin in the world, according to the results of the survey. This is followed by pork, beef and pork/beef mixture, as shown in Figure 5.4.

Animal insulin is considerably cheaper in those countries where both human and animal insulin are available, except in some countries in the North

Figure 5.1Access to insulin for people with type 1 diabetes by region

Figure 5.2Access to insulin for people with type 2 diabetes by region

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Figure 5.3Causes of lack of access to insulin

Figure 5.4Types of insulin available around the world

Bangladesh (SEA), and Japan and Hong Kong (WP).

In many countries, insulin in vial form is significantly cheaper than the same type of insulin in pen-fill cartridge form. Insulin in vial form should continue to be available in economically developing countries to people who otherwise would have to pay a higher price for the same insulin in pen-fill form.

Taxes are still a significant factor affecting the price of insulin (and other diabetes supplies) in a great number of countries even though WHO essential drugs guidelines state there should be no taxes on insulin. Taxes were added on the price of insulin in 7 out of 8 countries in SACA; 5 out of 9 in Africa; 4 out of 8 in WP; 12 out of 31 in Europe; 1 out of 3 in SEA; and 2 out of 10 in NA (see Figure 5.6). No taxes were levied in the four responding countries in EMME. Taxes varied from 1% of cost in Kazakhstan to 80% in Poland. Specifically in Africa, it was 14% in South Africa and 48% in Togo.

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American and Western Pacific Regions, as shown in Figure 5.5 and Table 5.5. In Africa, for example, the average cost of human insulin is twice as expensive as animal insulin. A box of 10 ml U-100 human insulin was cheapest and most expensive respectively in Senegal and Kenya (AFR), Qatar and Libya (EMME), Romania and Italy (EUR), Commonwealth of Dominica and USA (NA), Cuba and El Salvador (SACA), Sri Lanka and



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Cost implicationsTable 5.6 shows that when the price of insulin is compared to the gross national product (GNP) of the countries, insulin is 3 to 26 times less affordable in Africa than in all other regions. Human insulin is most affordable in Western Pacific and Europe, and least affordable in Africa while animal insulin is most affordable in South and Central America and Europe, and least affordable in Africa.

The main reason for the expansion of diabetes services in the developed countries was the discovery and introduction of insulin. Developing countries face major scourges including AIDS, TB and malaria, which compete for health priority with diabetes. Although insulin is a life-saving drug, in a situation of grossly restricted medical resources, the ‘opportunity cost’ of keeping alive a resource-consuming person with diabetes is a valid if chilling question. This explains why four African countries reported an awareness of death due to lack of access to insulin in people with type 1 diabetes.

Access to diabetes supplies

It would appear from the Global Access to Insulin and Diabetes Supplies Survey, 2003 that blood glucose testing strips are even less accessible than insulin. Urine testing strips are significantly more accessible because they are much more affordable. They provide a viable testing method in the absence of affordable glucose testing. There seems to be evidence that the use of urine strips may be decreasing without a commensurate increase in the use of blood glucose testing strips.

Only 40 countries had access to insulin syringes and needles 100% of the time. Among the regions, Africa had the lowest access to insulin syringes and needles. Europe had the highest access followed by North America (see Table 5.7). The average cost of 100 insulin syringes was

Figure 5.5Average cost of 10 ml vial of U-100 insulin by region

Figure 5.6Average percentage of taxes on imported and locally produced insulin in four regions

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Figure 5.7Average cost of 100 insulin syringes by region

Figure 5.8Self-monitoring of glucose and methods used

highest in North America, followed by South and Central America and Africa, and cheapest in South-East Asia and Western Pacific (see Figure 5.7).

Self-monitoring of diabetesUrine testing seems to be the method of choice of self-monitoring of diabetes (see Figure 5.8).

In fact, in 71 countries there are individuals who do not monitor their diabetes either by blood glucose or urine testing.

According to the survey, the main reasons for not practising self-monitoring were (see Figure 5.9):

• high cost of testing supplies;• lack of diabetes education;• lack of interest by patients; and• lack of testing supplies.

High cost of supplies was the major reason given by all responding countries in Africa, 75% of the countries in EMME, 71% in Europe, 90% in North America, 88% in SACA and 86% in Western Pacific (see Figure 5.10).

Cost of diabetes supplies

There was a great disparity in the cost of diabetes supplies among the different regions, for instance blood glucose meters cost, on average, US$105 per glucose meter in the Western Pacific and US$61 in South and Central America (see Table 5.8). Similarly, a box of 50 blood glucose strips costs US$50 in North America and US$20 in South-East Asia while a box of 100 urine glucose strips costs US$20 in North America and US$5 in South-East Asia (see Figure 5.11). In some countries, however, these diabetes supplies are subsidized or supplied free of charge to particular groups of people with diabetes.

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Figure 5.9Reasons why people with diabetes do not practise self-monitoring of blood glucose

Figure 5.10Main reasons for not practising self-monitoring by region

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Conclusion

The chronic lack of access to insulin and diabetes supplies in most regions especially the developing countries pose serious challenges to the international diabetes community. IDF has positioned itself to look for long-term solutions to these problems. Our individual and collective responsibilities are important to alleviate these problems. At the national level IDF can serve as a catalyst to massive price reductions as it has been the case in India. The Task Force on Insulin will continue to work with other groups within and outside IDF to establish national collaborative projects.

It still appears that Derek Wall, an ecologist, was right when he said, “At present cats have more power and influence than the poor of this planet. Accidents of geography and colonial history should no longer determine who gets the fish.” The international diabetes family can defend the rights of those who will die because they lack insulin, and work towards a world where insulin and other diabetes supplies are freely available to all those with diabetes.

Figure 5.11Average cost of diabetes supplies by region

a. Blood glucose meter b. 100 urine test strips c. 50 blood glucose strips

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Profile: Hamisi Rashidi

Twice a day Hamisi Rashidi removes a vial of insulin from a mud pot filled with water for his daily injections. The mud pot is the only way Hamisi, 12, can store his supply of insulin

without it being destroyed. Sometimes, he says, “the water seeps into the insulin bottles diluting the insulin, and due to that I get high blood glucose even if I have injected insulin.”

Storage is a major problem for Hamisi, who has had type 1 diabetes since he was three. His parents cannot afford to buy a refrigerator; they live in a one-room house without electricity or running water in Dar es Salaam, Tanzania.

His parents also cannot afford to buy syringes although Hamisi obtains his insulin free of charge from the District Hospital. He uses a disposable syringe for about two and a half weeks before buying a new one. His parents worry greatly about sustaining his insulin treatment with their meagre earnings. Hamisi’s father does odd jobs while his mother is a housewife.

An added expense has now arisen with his weakened eyesight, which was discovered during a recent screening programme conducted by the Tanzanian Diabetes Association on World Diabetes Day. He has been advised to wear spectacles.

Hamisi has learnt to cope with the ups and downs and to find the right balance in order to avoid hypoglycaemia and hyperglycaemia. His parents have taught him to keep to a strict schedule for his meals and insulin injections. Says his mother, “Whenever he is not well we ask him to tell us if the sugar levels are high or low. He knows and understands more than we do and is the best judge during such a time.”

Optimistic and cheerful by nature, Hamisi welcomes his insulin injections rather than dreads them: “I’m not afraid; I like to inject insulin as it makes me hungry and I feel better. Otherwise I don’t feel hungry and I don’t like to eat anything.”

Hamisi, the second child in a family of six children, is the only one to have diabetes. His parents had never heard about the disease and were heartbroken on hearing the diagnosis. They were not sure what they would do and how they would treat Hamisi. “I was so worried about my child that I stopped eating and sleeping and would watch him all the time,” recalls his mother.

Although Hamisi wonders at times why he is the only one in the family to have diabetes, he does not see much difference between himself and his friends who do not have the disease, “I can do what they can do. I will be a doctor when I grow up and help people with diabetes.”



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AFR EMME EUR NA SACA SEA WP Total

No. of countries 9 4 32 10 8 3 8 74

<25% 2 0 0 0 0 0 0 2

26-49% 1 0 0 0 0 0 0 1

50-74% 3 0 0 1 3 0 0 7

75-99% 3 1 4 5 2 2 3 20

100% 0 3 28 4 3 1 5 44

Table 5.1 Access to insulin for people with type 1 diabetes

Table 5.2 Access to insulin for people with type 2 diabetes


No. of countries 9 4 32 10 8 3 8 74

<25% 1 0 1 0 0 0 0 2

26-49% 2 0 0 0 3 0 0 5

50-74% 2 0 1 1 0 0 1 5

75-99% 4 1 5 5 3 2 2 22

100% 0 3 25 4 2 1 5 40


No. of countries 9 4 32 10 8 3 8 74

Insulin is too expensive 7 0 2 2 3 1 0 15

Not available in regional areas 5 1 1 2 4 1 0 14

Transportation problems 3 0 0 0 2 1 1 7

Supply is less than required 2 0 1 1 2 0 0 6

Insulin is of very poor quality 0 0 1 0 1 1 0 3

Table 5.3 Causes of lack of access to insulin for people with type 1 diabetes

Table 5.4 Causes of lack of access to insulin for people with type 2 diabetes


No. of countries 9 4 32 10 8 3 8 74

Insulin is too expensive 6 0 1 0 1 1 0 9

Not available in regional areas 4 1 1 1 2 1 1 11

Transportation problems 3 0 0 0 1 1 0 5

Supply is less than required 2 0 2 1 2 0 0 7

Insulin is of very poor quality 1 0 0 0 0 1 0 2

Preference is given to type 1 0 0 1 1 3 1 0 6

AFR African RegionEMME Eastern Mediterranean and Middle East RegionEUR European RegionNA North American RegionSACA South and Central American RegionSEA South-East Asian RegionWP Western Pacific Region



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No. of countries 9 4 32 10 8 3 8 74

Human insulin

No. of countries 7 4 22 9 7 3 6 58

Cost per box of 10 ml vial 18 (2-21) 4.6 (1-8) 14 (6-26) 14 (5.6-45) 19 (0.04-32) 10 (3-12.5) 9 (3-15) 13 (0.04-45)

Pork insulin

No. of countries 4 0 5 3 4 2 1 19

Cost per box of 10 ml vial 8 (2.5-11) 7 (5-25) 25 (10-45) 11 (0.04-20) 7 (6-8) 11 9 (0.04-45)

Beef insulin

No. of countries 2 1 3 0 2 1 0 9

Cost per box of 10 ml vial 9 (7-11) 3.4 28 (8.5-43) 6 (0.04-12) 3 8.5 (0.04-43)

Mixture of beef/pork insulin


Cost per box of 10 ml vial 9 (7-11) N/A 0.04 7 (0.04-11)

Table 5.5 Number of countries where 10 ml vial of U-100 insulin is available and cost(median and minimum-maximum) (USD) of human and animal insulin by region


No. of countries 9 4 32 10 8 3 8 74

Human insulin

No. of countries 7 4 22 9 7 3 6 58

Cost (x1000/GNP) per box of 10 ml vial 13 (1-37) 2 (0.3-5) 1 (0.3-4) 2 (1-3) 2 (0.01-8) 4 (0.4-7) 0.5 (0.1-4) 1.3 (0.01-37)

Pork insulin

No. of countries 4 0 5 3 4 2 1 19

Cost (x1000/GNP) per box of 10 ml vial 11 (5-13) 1 (0.4-2) 1.5 (1-2) 2 (0.01- 2) 4 (2-6) 5 1.6 (0.01-13)

Beef insulin


Cost (x1000/GNP) per box of 10 ml vial 10.6 (9.5-12) 2 1.4 (1-2) 0.5 (0.01-1) 1 1.4 (0.01-12)

Mixture of beef/pork insulin


Cost (x1000/GNP) per box of 10 ml vial 11 (9-12) N/A 0.01 10 (0.01-12)

Table 5.6 Number of countries where 10 ml vial of U-100 insulin is available and cost reported to GNP(median and minimum-maximum) (USD) of human and animal insulin by region

N/A not available

GNP gross national productN/A not available



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No. of countries 9 4 32 10 8 3 8 74

<25% 2 0 0 0 0 0 1 3

26-49% 2 0 2 0 1 0 0 5

50-74% 0 0 0 1 3 0 2 6

75-99% 5 2 5 5 1 2 0 20

100% 0 2 25 4 3 1 5 40

Table 5.7 Access to insulin syringes and needles for people with diabetes

AFR EMME EUR* NA* SACA SEA WP Total*

No. of countries 9 4 32 10 8 3 8 74

Cost of 100 syringes 14 (5-30) 11 (4-30) 12 (0-300) 23 (19-30) 15 (0.5-25) 10 (10-12.5) 10 (7-32) 13 (0-300)

Cost of one insulin pen 40 (30-50) 36 (21-97) 39 (0-103) 0 (0-30) 12.5 (0-30) 10 (3-20) 25 (0-44) 25 (0-103)

Cost of one blood glucose meter 96 (35-207) 65 (60-80) 65 (0-150) 65 (0-105) 61 (30-110) 90 (50-110) 105 (10-130) 70 (0-207)

Cost of 50 blood glucose test strips 36 (15-45) 22 (15-35) 31 (0-50) 50 (20-55) 30 (20-48) 20 (20-21) 29 (3-45) 30 (0-55)

Cost of 100 urine test strips 12 (5-30) 9 (7-30) 10 (0-100) 20 (0-30) 15 (8-30) 5 (2-10) 8 (5-25) 10 (0-100)

Table 5.8 Cost of other diabetes supplies (median and minimum-maximum) (USD)

* The minimum cost is zero when the diabetes supply was given free to the patient.



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List of countries which participated in the Global Access to Insulin and Diabetes Supplies Survey, 2003

Africa (AFR)Cameroon, Democratic Republic of Congo, Côte d’Ivoire, Kenya, Senegal, South Africa, Tanzania, Togo and Zambia.

Eastern Mediterranean and Middle East (EMME)Egypt, Libya, Pakistan and Qatar.

Europe (EUR)Albania, Austria, Belgium, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, Georgia, Germany, Greece, Hungary, Ireland, Israel, Italy, Kazakhstan, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania, Serbia and Montenegro, Slovenia, Spain, Sweden, Turkey, UK and Ukraine.

North America (NA)Anguilla, Belize, Bermuda, British Virgin Islands, Canada, Commonwealth of Dominica, Guyana, Jamaica, Mexico and USA.

South and Central America (SACA)Argentina, Bolivia, Brazil, Chile, Cuba, El Salvador, Peru and Uruguay.

South-East Asia (SEA)Bangladesh, Mauritius and Sri Lanka.

Western Pacific (WP)Australia, China Hong Kong, Japan, New Zealand, Philippines, Singapore, Taiwan and Thailand.

Bibliography

1. Chale SS, Swai AB, Mujinja PG, McLarty DG. Must diabetes be a fatal disease in Africa? Study of costs of treatment. BMJ 1992; 304:1215-1218.

2. Jervell J. Variations in the utilization and cost of insulin. IDF Bulletin 1996; 41:1-2.

3. IDF Task Force on Insulin. Access to insulin. A report of the IDF Task Force on Insulin 1994-97. International Diabetes Federation, Brussels, 1997.

4. King H. Insulin: availability, affordability, and harmonization. World Health Organization, Drug, Geneva, 1998. 4:219-223.

5. Shobhana R, Rao PR , Lavanya A, Williams R, Vijay V, Ramachandran A. Expenditure on healthcare incurred by diabetic subjects in a developing country – a study from southern India. Diabetes Res Clin Pract 2000; 48:37-42.

6. Lin T, Chou P, Lai M, Tsai S, Tai T. Direct cost-of-illness of patients with diabetes mellitus in Taiwan. Diabetes Res Clin Pract 2001; 54 Suppl 1:43-46.

Diabetes EducationChapter 6


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Diabetes Education Chapter 6

Diabetes education has been shown to be effective and is now considered

an integral part of diabetes care. In acknowledging the critical importance of education, the International Diabetes Federation (IDF) established the Diabetes Education Consultative Section (DECS) to address the education needs of IDF member associations.

In continued recognition and support of education, this chapter of the Diabetes Atlas is devoted specifically to diabetes education and is divided into three sections: the first summarizes the evidence-based studies supporting the effectiveness of diabetes education, the second is a report of education practices in the seven IDF regions based on a comprehensive survey, and the final section provides projected cost savings associated when people with diabetes receive education.

6.1 Effectiveness of Self-management Education

6.2 Educational Practices:a Global View

6.3 Cost-effectiveness of Diabetes Education



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Introduction

Although the medical dimensions of diabetes care such as eye exams and blood glucose monitoring have improved in recent years, outcomes for many people with diabetes remain poor (1,2). While many factors contribute to poor outcome, this apparent contradiction also reflects the central role that people with diabetes themselves play in determining their health status, and the challenges associated with supporting their efforts to manage their self-care (3).

Diabetes self-management is among the most difficult of all chronic illness self-management regimens. To effectively self-manage diabetes, those with the disease must identify symptoms of emerging health crises, adhere to often complex medication schedules, and modify long-standing lifestyle behaviours such as their diet and physical activity levels. Not surprisingly, many people have difficulty meeting the demands of their illness and experience poorer outcomes as a result.

This section reviews the findings from recent research on diabetes self-management supports for adults. More detailed reviews have been published previously, and readers are encouraged to seek these out for additional information about specific topics such as foot care education, medication adherence enhancement, or promotion of smoking cessation within primary care clinics (4-11).

Goal of diabetes education

The goal of diabetes self-management education is to support the efforts of people with diabetes to:1 understand the nature of their illness

and its treatment;2 identify emerging health problems in

early, reversible stages;

3 adhere to self-care practices; and4 make needed changes in their health

habits.

More broadly, diabetes self-management education assists people in coping with the mental and physical demands of their illness, given their unique economic, cultural and social circumstances.

Why is self-management important?

Improving outcomesGlucose self-monitoring is essential for identifying episodes of extremely high and low blood glucose (hyperglycaemia and hypoglycaemia), especially among people with type 1 diabetes. This was the conclusion of a review of scientific evidence by Piette and Glasgow supporting various diabetes self-care practices and their promotion through self-management supports (see Box 6.1) (9). There is no evidence, however, that glucose self-monitoring improves outcomes among people with type 2 diabetes (12, 13), although this could change if effective systems are put in place to address the cause of their problems.

Foot self-care is essential for people with diabetes in order to avoid infections and ulcers leading to amputation. Foot self-care education is an effective means of improving foot care practices and outcomes (14, 15). Assisting people with diabetes in taking their medication as prescribed is also important, and a variety of low-cost and simple interventions such as day-specific pill containers and simplified dosing schedules are effective in doing this (16-19).

Changing lifestyleWith regard to lifestyle behaviours, smoking cessation is an essential aspect of diabetes self-care, and interventions

6.1 Effectiveness of Self-management Education

Diabetes self-management education

is a multi-faceted process involving much

more than helping people with diabetes monitor their blood

glucose, or take their medication as

prescribed. Diabetes education must be an

ongoing process rather than a one-time event

because a person’s health status and need

for support changes over time.



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to help people quit smoking increase cessation rates (20, 21). Brief advice to quit smoking produces important effects, although behavioural counselling accompanied by medication and ongoing support has the greatest impact (22, 23).

Many people with type 2 diabetes are sedentary, and increasing their physical activity levels can be important. Effective physical activity counselling strategies have been identified that can improve glucose control (24) of people with type 2 diabetes as well as other cardiovascular risk factors, such as blood pressure (25) and cholesterol levels (26). Counselling and support to decrease the amount of dietary fat and overall caloric intake have shown some success (11, 27, 28). Two important studies recently demonstrated that lifestyle interventions promoting physical activity plus dietary changes can delay the onset of type 2 diabetes among high-risk individuals (29, 30).

Where should education take place?

Group visits in medical settingsPeople with diabetes often learn as much or more within a group context than they do on their own or through one-to-one visits with clinicians. In one study, participants in group visits had fewer emergency department visits, visits to sub-specialists and repeat hospitalizations (31). Similar effects of group visits, including improvements in glycaemia control, satisfaction, healthcare utilization and costs of care, have been reported in a wide range of populations and health systems, including large health maintenance organizations (32, 33), under-served populations (34) and health systems in different countries (35, 36).

Community-basedpeer-support groups People with diabetes also can improve their self-care through classes led by non-clinician peers and structured to improve their understanding of their illness and

confidence or ‘self-efficacy’ regardingself-management.

A successful programme for achieving these goals has been developed by Kate Lorig and colleagues at Stanford University (37) in the USA. The programme can be delivered in multiple languages, and recent evaluations indicate that it produces lasting reductions in symptoms, physician visits and costs relative to others receiving usual care (38). Ongoing research is evaluating the impact of this intervention on diabetes treatment outcomes among low-income Spanish-speakers in northern California.

In another community-based study, elderly people with diabetes received disability prevention and disease self-management education in a senior centre (39). Individuals receiving the intervention had substantially less decline in physical function, greater levels of physical activity and less reliance on medications. Those participating in the groups also used less hospital care than those in a comparison group. Community-based groups such as these may be particularly important in settings where people with diabetes have difficulty accessing care within traditional healthcare settings.

Box 6.1

Issues to be addressed by diabetesself-management education

• Glucose self-monitoring (for some)• Foot care• Medication adherence• Smoking cessation• Increasing physical activity• Reducing dietary fat and caloric intake



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Ongoing home support via telephoneSelf-management support provided through regular telephone follow-up improves outcomes of people with diabetes. In one study (40) among elderly men with type 2 diabetes, monthly calls by a nurse-educator improved glycaemic control, and a more recent study had similar results (41). These studies are consistent with the broader literature on telephone care, showing that telephone calls can improve the health of those who are chronically ill and may even serve as an effective alternative to face-to-face office visits (28, 42, 43).

Effective communication

When people with diabetes play central roles in setting their own self-care goals, they are more likely to adhere to treatment plans (44-46). Diabetes educators can contribute to this process by providing them with the information they need for priority-setting and problem-solving, assisting them in identifying realistic targets for behavioural changes, and providing ongoing emotional support and encouragement.

Through these efforts, educators can improve the long-term ability of people with diabetes to maintain an effective self-management regimen and help them avoid emotional burnout (47, 48). More effective communication between the individual and educator can lead to better self-care behaviour as well as improvements in health outcomes (49-53).

Characteristics of patients, providers and health systems may influence the quality of patient-provider interactions. Race and ethnicity may constitute barriers to communication with potentially negative effects on patients’ willingness to receive necessary services and follow self-care plans.

Female physicians often engage in more patient-centred communication than their male counterparts (54), and patients are more satisfied with female providers (55-58). Continuity of care has been associated with better communication among asthma patients (59) and greater patient satisfaction and quality in general (60, 61).

A training programme developed by Robert Anderson and colleagues (62) for diabetes educators to help them learn how to teach people with diabetes more effective communication strategies and become more actively involved in their own treatment. Following training, educators show significant improvement in their counselling skills and in their attitudes toward supporting patient autonomy (62).

The empowerment approach has been demonstrated to produce better patient outcomes than usual care (63), and another approach to empowering patients at the time of clinic visits has also been shown to improve glucose levels (64).

Role of emerging health technologies

A variety of novel technologies has been developed to support self-care efforts of people with diabetes and provide an alternative to traditional education occurring within outpatient clinics (65).

Interactive softwareInteractive software accessed on a personal computer using CD-ROMs or other hardware represents one strategy for delivering behaviour change interventions efficiently and effectively in the context of busy primary care practices. These systems can be placed in clinic waiting rooms where they can reach large numbers of people, require minimal staffing, and provide self-paced and tailored educational messages (66).



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A clinic-based touch-screen computer system was developed by Glasgow and colleagues to assist diabetes patients assess their health behaviours, self-management goals and barriers to goal attainment (67). Compared to similar patients, those using the CD-ROM system had improvements in their diet and lower cholesterol levels (68, 69).

Automated telephone systemsAutomated telephone systems can allow for frequent follow-up with individuals who have difficulty accessing clinic-based services or who lack the computer supports necessary for more ‘high-tech’ interventions. Those who are chronically ill can provide valid and reliable information using their touch-tone telephone during automated monitoring calls (70, 71).

A study, by Piette and colleagues, found that a group of low-income English- and Spanish-speaking people with diabetes receiving bi-weekly automated calls with telephone nurse follow-up responded to the calls consistently over the 12-month study period (72). These individuals used the calls to access self-care education (73), and reported information that identified those at greatest risk for developing problems (74).

The intervention improved their blood glucose self-monitoring, foot care, weight self-monitoring and medication adherence (75). The study also found improvements in their glucose control, diabetes-related symptoms and symptoms of depression (76). These same investigators replicated this study in another US health system and had similar findings (77).

Internet-based supportInternet-based diabetes self-care support has the potential to reach large numbers of people, and even computer novices are willing to use internet-based diabetes education programmes (78-80). Such systems can enhance the educational

experience by using audio and video, and are potentially available 24 hours per day. Internet-based diabetes supports also allow people with diabetes to communicate with their clinicians, experts in self-care, or one another.

One of the most definitive studies of internet-based diabetes supports (81) evaluated a web-based self-management programme in which participants were encouraged to log on to a specially-designed website, review their progress toward self-management goals, and access other services such as an online log of their progress and personal counselling and support. At follow-up, those using the website and those in the comparison group improved in their self-reported physical activity, however there were no significant differences between the two groups. Individuals who used the system more frequently reported greater change in physical activity than those who used it less often.

Summary

Diabetes self-management education is a multi-faceted process involving much more than helping people with diabetes monitor their blood glucose, or take their medication as prescribed. Diabetes

Box 6.2

Components of effective self-management programmes

• Ongoing support rather than one-time counselling• Group visits and peer-to-peer counselling• Telephone care including the use of automated

telephone calls• Effective communication with providers to set self-

management goals and overcome barriers• Use of interactive technologies• A coordinated systems approach



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education must be an ongoing process rather than a one-time event because a person’s health status and need for support changes over time (Box 6.2) (11).

One-on-one counselling may be helpful to improving self-care, although group sessions led either by clinicians or others with diabetes also can be effective. Telephone care can be a vital link between people with diabetes and their healthcare providers for ongoing self-management support, especially when there is difficulty accessing face-to-face services. Automated telephone calls can extend the reach of self-management education when staffing is limited or an individual needs frequent monitoring and behaviour change supports.

Effective communication with healthcare providers is strongly linked to improvements in self-care and outcomes, and self-management educators can play an important role in empowering people with diabetes to become active participants in identifying self-care goals and overcoming barriers to their achievement. Overall, self-management education is most likely to be successful when it is part of a comprehensive and coordinated approach to diabetes care (82).



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References

1. Harris MI. Healthcare and health status and outcomes for patients with type 2 diabetes. Diabetes Care 2000; 23:754-758.

2. Saaddine JB, Engelgau MM, Beckles GL, Gregg EW, Thompson TJ, Narayan KM. A diabetes report card for the United States: quality of care in the 1990’s. Ann Intern Med 2002; 136:565-574.

3. Goldman DP, Smith JP. Can patient self-management help explain the SES health gradient? PNAS 2002; 99:10929-10934.

4. Brown SA. Effects of educational interventions in diabetes care: a meta-analysis of findings. Nurs Res 1988; 37:223-230.

5. Brown SA. Diabetes patient education interventions and outcomes: a meta-analysis revisited. Patient Educ Couns 1990; 16:189-215.

6. Brown SA. Meta-analysis of diabetes patient education research: variations in intervention effects across studies. Res Nurs Health 1992; 15:409-419.

7. Clement S. Diabetes self-management education. Diabetes Care 1995; 18(8):1204-1214.

8. Padgett D, Mumford E, Hynes M, Carter R. Meta-analysis of the effects of educational and psychosocial interventions on management of diabetes mellitus. J Clin Epidemiol 1988; 41(10):1007-1030.

9. Piette JD, Glasgow R. Strategies for improving behavioral and health outcomes among patients with diabetes: self-management education. In Evidence-Based Diabetes Care, eds Gerstein HC, Haynes RB. Ontario, Canada: BC Decker Publishers 2001, pp 207-251.

10. Brown SA. Interventions to promote diabetes self-management: state of the science. Diabetes Educator 1999; 25 Suppl 6:52-61.

11. Norris SL, Engelgau MM, Narayan KMV. Effectiveness of self-management training in type 2 diabetes. A systematic review of randomized controlled trials. Diabetes Care 2001; 24:561-587.

12. Faas A, Schellevis FG, Van Ejik JTM. The efficacy of self-monitoring of blood glucose in NIDDM subjects: a criteria-based literature review. Diabetes Care 1997; 20:1482-1486.

13. Gallichan M. Self monitoring of glucose by people with diabetes: evidence based practice. BMJ 1997; 314:964-967.

14. Litzelman DK, Slemenda CW, Langefeld CD, Hays LM, Welch MA, Bild DE, Ford ES, Vinicor F. Reduction of lower extremity clinical abnormalities in patients with non-insulin-dependent diabetes mellitus. Ann Intern Med 1993; 119(1):36-41.

15. Uccioli L, Faglia E, Monticone G, Favales F, Durola L, Aldeghi A, Quarantiello A, Calia P, Menzinger G. Manufactured shoes in the prevention of diabetic foot ulcers. Diabetes Care 1995; 18:1376-1378.

16. McKenney JM, Munroe WP, Wright JT Jr. Impact of an electronic medication compliance aid on long-term blood pressure control. J Clin Pharmacol 1992; 32(3):277-283.

17. Friedman RH, Kazis LE, Jette A, Smith MB, Stollerman J, Torgerson J, Carey K. A telecommunications system for monitoring and counseling patients with hypertension. Impact on medication adherence and blood pressure control. Am J Hypertens 1996; 9(4 Pt 1):285-292.

18. Rich MW, Gray MB, Beckham V, Wittenberg C, Luther P. Effect of a multidisciplinary intervention on medication compliance in elderly patients with congestive heart failure. Am J Med 1996; 101(3):270-276.

19. Roter D, Debra L, Hall JA, Merisca R, Nordstrom B, Cretin D, Svardstad B. Effectiveness of interventions to improve

patient compliance: a meta-analysis. Medical Care 1998;36:1138-1161.

20. Fiore M, Bailey W, Cohen S. Smoking Cessation. Clinical Practice Guideline Number 18. Rockville: U.S. Department of Health and Human Services, Public Health Service, Agency for Health Care Policy and Research, 1996.

21. Haire-Joshu D, Glasgow RE, Tibbs TL. Technical review: smoking and diabetes. Diabetes Care 1999; 22:1887-1898.

22. Tang J, Law M, Wald N. How effective is nicotine replacement therapy in helping people to stop smoking? BMJ 1994; 308:21-26.

23. Fiore M, Smith S, Jorenby D, Baker T. The effectiveness of the nicotine patch for smoking cessation: a meta-analysis. JAMA 1994; 271:1940-1947.

24. Boule NG, Haddad E, Kenny GP, Wells GA and Sigal RJ. Effects of exercise on glycemic control and body mass in type 2 diabetes mellitus: a meta-analysis of controlled clinical trials. JAMA 2001; 286:1218-1227.

25. Wareham NH, Wong MY, Hennings S, et al. Quantifying the association between habitual energy expenditure and blood pressure. Int J Epidemiol 2000; 29:655-660.

26. Parkkari JM, Natri AM, Kannus P, et al. A controlled trial of the health benefits of regular walking on a golf course. Am J Med 2000; 109:102-108.

27. Lacey KO, Kimberly O, Chyun DA, Grey M. An integrative literature review of cardiac risk factor management in diabetes education interventions. The Diabetes Educator 2000; 26:812-820.

28. Debusk RF, Houston Miller N, Superko HR, et al. A case-management system for coronary risk factor modification after acute myocardial infarction. Ann Intern Med 1994; 120:721-729.

29. Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002; 346:393-403.

30. Tuomilehto J, Lindstrom J, Eriksson JG, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 2001; 344:1343-1350.

31. Beck A, Scott J, Williams P, Robertson B, Jackson D, Gade G, Cowan P. A randomized trial of group outpatient visits for chronically ill older HMO members: the cooperative health care clinic [see comments]. J Amer Geriatr Soc 1997; 45(5):543-549.

32. Sadur C, Moline N, Costa M, et al. Diabetes management in a health maintenance organization: efficacy of care management using cluster visits. Diabetes Care 1999; 22:2011-2017.

33. Wagner E, et al. Chronic care clinics for diabetes in primary care: a system-wide randomized trial. Diabetes Care 2001; 24(4):695-700.

34. Keyserling TC, et al. A randomized trial of an intervention to improve self-care behaviors of African-American women with type 2 diabetes: impact on physical activity. Diabetes Care 2002; 25(9):1576-1583.

35. Trento M, et al. Lifestyle intervention by group care prevents deterioration of type II diabetes: a 4-year RCT. Diabetologia 2002; 45(9):1231-1239.

36. Trento M, Passera P, Tomalino M, Bajardi M, Pomero F, Allione A, Vaccari P, Molinatti GM, Porta M. Group visits improve metabolic control in type 2 diabetes: a 2-year follow-up. Diabetes Care 2001; 24(6):995-1000.

37. Lorig KR, Mazonson PD, Holman HR. Evidence suggesting that health education for self-management in patients with chronic arthritis has sustained health benefits while reducing health care costs. Arthritis Rheum 1993; 36(4):439-446.

38. Lorig KR, Sobel DS, Stewart AL, Brown BW Jr, Bandura A, Ritter P, Gonzalez VM, Laurent DD, Holman HR. Evidence



214



215

suggesting that a chronic disease self-management program can improve health status while reducing hospitalization: a randomized trial. Med Care 1999; 37(1):5-14.

39. Leveille SG, Wagner EH, Davis C, Grothaus L, Wallace J, LoGerfo M, Kent D. Preventing disability and managing chronic illness in frail older adults: A randomized trial of a community-based partnership with primary care [see comments]. J Amer Geriatr Soc 1998; 46(10):1191-1198.

40. Weinberger M, Kirkman MS, Samsa GP, Shortliffe A, Landsman PB, Cowper PA, Simel DL, Feussner JR. A nurse-coordinated intervention for primary care patients with non-insulin-dependent diabetes mellitus: impact on glycemic control and health-related quality of life. J Gen Intern Med 1995; 10(2):59-66.

41. Aubert RE, Herman WH, Waters J, Moore W, Sutton D, Peterson BL, Bailey CM, Koplan JP. Nurse case management to improve glycemic control in diabetic patients in a health maintenance organization: a randomized, controlled trial. Ann Intern Med 1998; 129(8):605-612.

42. Weinberger M, Tierney WM, Booher P, Katz BP. Can the provision of information to patients with osteoarthritis improve functional status? A randomized, controlled trial. Arthritis Rheum 1989; 32:1577-1583.

43. Wasson J, Gaudette C, Whaley F, Sauvigne A, Baribeau P, Welch HG. Telephone care as a substitute for routine clinic follow-up. JAMA 1992; 267(13):1788-1793.

44. Glasgow RE, Anderson RM. In diabetes care, moving from compliance to adherence is not enough. Something entirely different is needed. Diabetes Care 1999; 22:2090-2092.

45. Anderson RM, Funnell MM. Compliance and adherence are dysfunctional concepts in diabetes care. The Diabetes Educator 2000; 26:597-604.

46. Olivarius NF, Beck-Nielsen H, Andreasen AH, Horder M, Pedersen PA. Randomised controlled trial of structured personal care of type 2 diabetes mellitus. BMJ 2001; 323:946-947.

47. Charman D. Burnout and diabetes: reflections from working with educators and patients. J Clin Psychol 2000; 56:607-617.

48. Hoover JW. Patient burnout, and other reasons for noncompliance. The Diabetes Educator 1983; 9:41-43.

49. Heisler M, Bouknight RR, Hayward RA. The relative importance of physician communication, participatory decision-making, and patient understanding in diabetes self-management. J Gen Intern Med 2002; 17:243-252.

50. DiMatteo MR. The physician-patient relationship: effects on the quality of health care. Clin Obstet Gynecol 1994; 37:149-161.

51. Sherbourne CD, Hays RD, Ordway L, DiMatteo MR, Kravitz RL. Antecedents of adherence to medical recommendations: results from the Medical Outcomes Study. J Behav Med 1992; 15:447-468.

52. Kaplan SH, Greenfield S, Ware JE, Jr. Assessing the effects of physician-patient interactions on the outcomes of chronic disease [published erratum] appears in Med Care 1989; 27:S110-127.

53. Stewart MA. Effective physician-patient communication and health outcomes: a review. CMAJ 1995; 152:1423-1433.

54. Roter DL, Hall JA, Aoki Y. Physician gender effects in medical communication: a meta-analytic review. JAMA 2002; 288:756-767.

55. Sprague-Jones J. Gender effects in physician-patient interaction. In The Medical Interview: Clinical Care, Education, and Research, eds Lipkin M, Putnam SM, Lazare A. Springer-Verlag, New York, 1995; pp 163-171.

56. Arnold RM, Martin SC, Parker RM. Taking care of patients – does it matter whether the physician is a woman? West J Med 1988; 149:729-733.

57. Zare N, Sorenson JR, Heeren T. Sex of provider as a variable in effective genetic counseling. Soc Sci Med 1984; 19:671-675.

58. Linn LS, Cope DW, Leake B. The effect of gender and training of residents on satisfaction ratings by patients. J Med Educ 1984; 59:964-966.

59. Love MM, Mainous AG, 3rd, Talbert JC, Hager GL. Continuity of care and the physician-patient relationship: the importance of continuity for adult patients with asthma. J Fam Pract 2000; 49:998-1004.

60. Howie JG, Heaney DJ, Maxwell M, et al. Quality at general practice consultations: cross sectional survey. BMJ 1999; 319:738-743.

61. Hjortdahl P, Laerum E. Continuity of care in general practice: effect on patient satisfaction. BMJ 1992; 304:1287-1290.

62. Anderson RM, Funnell MM, Barr PA, Dedrick RF, Davis WK. Learning to empower patients: results of a professional education program for diabetes educators. Diabetes Care 1991; 14(2):584-590.

63. Anderson RM, Funnell MM, Butler PM, Arnold MS, Fitzgerald JT, Feste CC. Patient empowerment. Results of a randomized controlled trial. Diabetes Care 1995; 18(7):943-949.

64 . Greenfield S, Kaplan S, Ware JE Jr. Expanding patient involvement in care. Effects on patient outcomes. Ann Intern Med 1985; 102:520-528.

65. Piette JD. Enhancing support via interactive technologies. Current Diabetes Reports 2002; 2(2):160-165.

66. Castaldini M, Saltmarch M, Luck S, Sucher K. The development and pilot testing of a multimedia CD-ROM for diabetes education. The Diabetes Educator 1998; 24(3):285-296.

67. Glasgow RE, Toobart DJ, Hampson. Effects of a brief office-based intervention to facilitate diabetes dietary self-management. Diabetes Care 1996; 19(8):835-842.

68. Glasgow RE, La Chance PA, Toobert DJ, Brown J, Hampson SE, Riddle MC. Long-term effects and costs of brief behavioural dietary intervention for patients with diabetes delivered from the medical office. Patient Educ Couns 1997; 32(3):175-184.

69. Glasgow RE, Toobert DJ. Brief, computer-assisted diabetes dietary self-management counseling: effects on behavior, physiologic outcomes, and quality of life. Med Care 2000; 38:1062-1073.

70. Piette JD. Moving diabetes management from clinic to community: development of a prototype based on automated voice messaging. The Diabetes Educator 1997; 23(6):672-679.

71. Piette JD. Interactive voice response systems in the diagnosis and management of chronic disease. Am J Manag Care 2000; 6(7):817-827.

72. Piette JD, Mah CA. The feasibility of automated voice messaging as an adjunct to outpatient diabetes care. Diabetes Care 1997; 20(1):15-21.

73. Piette JD. Patient education via automated calls: a study of English and Spanish speakers with diabetes. Am J Prev Med 1999; 17(2):138-141.

74. Piette JD, McPhee SJ, Weinberger M, Mah CA, Kraemer FB. Use of automated telephone disease management calls in an ethnically diverse sample of low-income patients with diabetes. Diabetes Care 1999; 22(8):1302-1309.

75. Piette JD, Weinberger M, McPhee SJ, Crapo LA, Kraemer FB. Do automated calls with nurse follow-up improve self-care and glycemic control among english- and spanish-speaking patients with diabetes? A randomized controlled trial. Am J Med 2000; 108(1):20-27.

76. Piette JD, Weinberger M, McPhee SJ. The effect of automated calls with telephone nurse follow-up on patient-centered



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215

outcomes of diabetes care (a randomized controlled trial); Med Care 2000; 38:218-230.

77. Piette JD, Weinberger M, Kraemer FB, McPhee SJ. Impact of automated calls with nurse follow-up on diabetes treatment outcomes in a Department of Veterans Affairs healthcare system: a randomized controlled trial. Diabetes Care 2001; 24(2):202-208.

78. McKay HG, Feil EG, Glasgow RE, Brown JE. Feasibility and use of an internet support service for diabetes self-management. The Diabetes Educator 1998; 24(2):174-179.

79. Feil EG, Glasgow RE, Boles S, McKay HG. Who participates in Internet-based self-management programs? A study among novice computer users in a primary care setting. The Diabetes Educator 2000; 26(5):806-811.

80. Zrebiec JF, Jacobson AM. What attracts patients with diabetes to an Internet support group? A 21-month long website study. Diabet Med 2001; 18:154-158.

81. McKay HG, King D, Eakin EG, Seeley JR, Glasgow RE. The diabetes network internet-based physical activity intervention: a randomized pilot study. Diabetes Care 2001; 24(8):1328-1334.

82. Renders CM, Valk GD, Griffin SJ, Wagner EH, et al. Interventions to improve the management of diabetes in primary care, outpatient, and community settings: A systematic review. Diabetes Care 2001; 24:1821-1833.



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Introduction

The efforts of the IDF Diabetes Education Consultative Section (DECS) are targeted to address the needs of three audiences: the person with diabetes and those affected by the disease, the healthcare professional responsible for providing diabetes care, and the public. In an attempt to capture educational practices that apply to each of these audiences, DECS members representing all diabetes disciplines from each of the IDF regions designed a survey that was sent to member associations.

The survey was designed to gain an understanding of diabetes educational practice as it applies to all three of the audiences: the person with diabetes, health professionals and the public. Members of the consultative section recognize that this survey serves as a crude methodology in capturing data and information; however it does offer the first opportunity to gain a baseline understanding of practices and concerns. It is hoped that this attempt and its findings will pique continued interest in diabetes education efforts and the development of future tracking, reporting and intervention efforts.

Survey response

The survey questionnaire was sent to all IDF members associations by mail and electronically. At every opportunity DECS members, regional chairs and managers distributed and encouraged survey responses. Some 122 survey questionnaires were returned and analysed. The vast majority of the respondents completing the survey for each country identified themselves as physicians and in some cases educators.The surveys responses represented:

• 57 countries• 7 regions

– Africa (AFR) (n=7)– Eastern Mediterranean and

Middle East (EMME) (n=5)– Europe (EUR) (n=35)– North America (NA) (n=6)– South and Central America

(SACA) (n=18)– South-East Asia (SEA) (n=8)– Western Pacific (WP) (n=36)

Summary of results

The following summarizes survey findings according to regions since efforts of the consultative section are often targeted with far-reaching regional approaches. More detailed information for each member country is available in addressing country-specific needs.

Educational resourcesPhysicians were identified as the main provider of diabetes education in most regions, as shown in Figure 6.1, when respondents were asked who provides education in their country. The exception was in the Eastern Mediterranean and Middle East Region, where pharmacists were most likely to provide education.

Short training courses of 40-120 hours were most often the mechanism for

6.2 Educational Practices: a Global View

Figure 6.1Providers of diabetes education

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training, as shown in Figure 6.2, when respondents were asked how people were trained to be educators. However, the African and South-East Asian Regions reported that there was very limited or no educator training available.

Teaching tools are reported to be available in all regions, but every region supported the need for computerized resources and networking opportunities. The media proved to be the tool most available in all the regions, as indicated in Figure 6.3.

Respondents expressed interest in having an international summit addressing the global needs and problems related to diabetes education, and identified IDF as a resource for support in training and the development of standards for practice (see Box 6.3).

Role of diabetes educatorsAll regions reported that people with diabetes understood and appreciated the role of diabetes educators, as shown in Figure 6.4. This was in contrast to health authorities, and to some extent, physicians, not many of whom were

Figure 6.2Type of training available to diabetes educators

Figure 6.3Availability of teaching tools

Figure 6.4Understanding and appreciating the role of diabetes educators

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Box 6.3

Diabetes education training course: the Caribbean example

The Diabetes Education Consultative Section (DECS) has successfully organized training courses in collaboration with IDF regions and local diabetes associations. The Caribbean Diabetes Education

Course, organized by the IDF North American Region in collaboration with the Diabetes Association of Barbados, is a good example of such training courses.

The course, which was based on models developed by DECS and the Declaration of the Americas on Diabetes (DOTA), was run in two parts. Part one was held in the Barbados and part two, held in the Bahamas, was a follow-up a year later.

Nurses, dietitians, pharmacists and educators from 13 Caribbean island countries attended the five-day course in Barbados. Participants came away with updated knowledge in the management of diabetes and its complications as well as developing their skills in diabetes education and organization. An important objective was to facilitate the establishment of a programme plan for diabetes education in each participant’s country.

Mentors were assigned to participants and worked with them throughout the week. This proved to be an invaluable tool as the evaluation at the end of the course showed: “Excellent guidance for the programme and ongoing projects – the mentoring concept keeps the group focused.”

Course content included both theory and practical application. Participants were also asked to work on projects such as foot care education programmes for patients and healthcare professionals, educating healthcare professionals on diabetes management and healthy lifestyle education which was aimed at prevention. Projects were to be developed in the next year with strict deadlines. Participants who completed the project were invited to the follow-up meeting in the Bahamas the following year.

The course was geared towards motivating the participants to apply their training on returning to their countries. Each participant was asked to propose changes they would make to their practice.

The follow-up course, which took place a year later in the Bahamas, was organized this time in association with the Bahamas Diabetic Association.

The follow-up course programme was developed based on the IDF International Curriculum for Diabetes Health Professional Education (1). The course also included a poster presentation of the projects that the participants from the Barbados course had worked on in collaboration with their mentors.

reported to show understanding of the role of diabetes educators in some of the regions. Nonetheless, respondents reported that the majority of physicians in all regions, except Africa, did promote and refer patients for diabetes education. In addition, all of the respondents were aware of published studies validating the importance of education.

Access to educationAlthough all countries reported that people with diabetes have access to diabetes education, they nonetheless identified barriers to access. Barriers were analysed according to four categories outlined in the ‘Barriers to Diabetes Care’ instrument (2) used to measure



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the healthcare provider’s perceptions of barriers.

Each of the four categories refers to specific problems:

1 Psychological: addresses health beliefs/self-efficacy;

2 Educational: refers to lack of knowledge or education services;

3 Internal physical: refers to other diabetes-related problems such as heart or kidney disease and the effects of treatment; and

4 External physical: refers to problems that are financial or limitations to proper access.

The categories most frequently reported as being significant barriers were the external physical and educational, as shown in Figure 6.5. In other words, financial resources, limited access, lack of knowledge and educational resources are perceived to be the biggest challenges.

Training and advocacy efforts directed toward health ministers and public awareness were some of the mechanisms most often identified as means to address these barriers, as seen in Figure 6.6.

Figure 6.5Barriers to education

Discussion

LimitationsThere are several limitations to the interpretation of the summary report based on challenges inherent in the information gathered through the survey. Although all IDF member associations received the survey forms, response rates varied. Some regions, such as Europe and Western Pacific, had a high number of responses while other regions had a lower participation. This could be reflective of the make-up of a particular region. For example, the Western Pacific represents 19 member associations with many smaller islands, while South-East Asia with a large population affected by diabetes has only five member associations.

Each of the regions has a diverse group of member countries that vary in size, populations, culture, healthcare practices and socio-economics. For example, the North American Region includes large developed countries such as Canada and the United States, and developing countries such as Mexico and the small Caribbean islands.

The regional descriptions in the survey provide summary information and do not provide the detail needed to appreciate

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the practices and needs of specific countries. Descriptions according to countries and regions will vary in their level of detail in accordance with the information that was received.

Common themesDespite the apparent limitations consistent themes were reported that need to be addressed as the world incidence and prevalence of diabetes grow. From the survey it appears that although some countries do have national health programmes that include attention to diabetes education others do not. All the regions reported poor funding for education. Recurrent themes for potential solutions occurred and should be considered. For prevention and treatment of diabetes to be successful through education initiatives, governments, and local, national and international health associations need to organize efforts to promote the training, financial support, access and public awareness of diabetes education.

References

1. IDF Consultative Section on Diabetes Education. International Curriculum for Diabetes Health Professional Education. International Diabetes Federation, Brussels, 2002.

2. Simmons D, Weblemoe T, Voyle J, Prichard A, Leakehe L, Gatland B. Personal barriers to diabetes care: Lessons from a multi-ethnic community in New Zealand. Diabetic Medicine 1998; 15(11):958-964.

Figure 6.6Means to overcome barriers to diabetes education

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Introduction

Economic issues in diabetes care are garnering great attention throughout the world today. This attention has been particularly pronounced in recent years. Cost issues in diabetes self-management training are of interest because of three current and significant influences; first, the recognition that diabetes is increasing throughout the world, second, the recognition that self-management training is effective in improving the health of persons with diabetes, and third, the desire of many healthcare payers to limit healthcare costs.

In this light, cost-effectiveness analyses are often used to evaluate the economic arguments surrounding diabetes treatments and interventions. A cost-effectiveness analysis generally summarizes the impact of an intervention by characterizing the cost of the intervention relative to the health outcomes obtained. These studies are used to advocate for the adoption of a healthcare intervention. Typically, the policy decision is whether a new intervention is better able to meet a healthcare goal than the existing standard of care at a reasonable cost.

Current understanding

Economic arguments for the adoption of self-management training can be a powerful tool for advocates and others seeking to improve the health of the diabetes population. Does the implementation of diabetes education represent value for money? The answer is not clearly understood at this time. Both the multi-faceted nature of diabetes self-management and the dynamic way in which it is used in diabetes care make it difficult to decipher the economic benefit related to diabetes education alone.

Three independent reviews note that the economic costs and benefits of diabetes education have not been fully addressed (1-3). Several studies provide either a poor accounting of costs (such as neglecting to account for the programme costs inherent in providing education), or an inadequate comparison group to assess the impact on diabetes-related outcomes.

Despite the recognized limitations in economic methodology, Klonoff and Schwartz (1) conclude that self-management training in diabetes is probably cost-effective. This judgment is based on a large number of studies that suggest an economic benefit to self-management training programmes.

For example, reduced future hospitalizations associated with self-management interventions have been noted in several (1), though, not all reports (4, 5). Hospital costs represent the largest expenditure for diabetes care in several countries and reducing hospital costs thereby generally saves money. A multi-centre intervention in 10 countries in Latin America has also demonstrated that an educational programme can reduce the cost of drugs by 62% (6). Another programme in Argentina found a reduction in diabetes-related costs of 38% (7).

Diabetes education is also an integral part of several interventions that have been shown to save money. These include interventions that address diabetes and pregnancy (8, 9) and those that shift the initiation of insulin therapy from inpatient to outpatient settings (10-13).

More recently, self-management and diabetes education have been a vital component in landmark intensive treatment and lifestyle modification

A multi-centre intervention in 10 countries in Latin America has demonstrated that an educational programme can reduce the cost of drugs by 62%. Another programme in Argentina found a reduction in diabetes-related costs of 38%.

6.3 Cost-Effectiveness of Diabetes Education



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clinical trials. Intensive treatment, as practised in the Diabetes Control and Complications Trial (DCCT) and United Kingdom Prospective Diabetes Study (UKPDS), is now generally regarded as being cost effective, where health benefits can be obtained at a reasonable additional cost (14, 15). Emerging work from the Diabetes Prevention Program gives promise to the economic benefit of preventing diabetes through lifestyle changes.

Future needs

In the current healthcare environment, questions arise over the cost of self-care and diabetes education programmes and who will pay for it. While most evidence is encouraging regarding the economic benefits of diabetes education, the multi-faceted nature of self-management training and the team approach to diabetes care limits our ability to conclusively demonstrate its economic effect. As economic data provide effect to advocacy arguments, future evaluations of education interventions should seek to fully describe the associated economic costs and benefits.



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References

1. Klonoff DC, Schwartz DM. An economic analysis of interventions for diabetes. Diabetes Care 2000; 23(3):390-404.

2. Norris SL, Engelgau MM, Narayan KMV. Effectiveness of self-management training in type 2 diabetes; a systematic review of randomized controlled trials. Diabetes Care 2001; 24:561-587.

3. Kaplan RM, Davis WK. Evaluating the costs and benefits of outpatient diabetes education and nutrition counseling. Diabetes Care 1986; 9(1):81-86.

4. Rettig BA, Shrauger DG, Recker RR, Gallagher TF, Wiltse H. A randomized study of the effects of a home diabetes education program. Diabetes Care 1986; 9(2):173-178.

5. de Weerdt I, Visser AP, Kok GJ, de Weerdt O, Van der Veen EA. Randomized controlled multicentre evaluation of an education programme for insulin-treated diabetic patients: effects on metabolic control, quality of life, and costs of therapy. Diabet Med 1991; 8:338-345.

6. White F, Vega J, Aedo C, Jadue L, Robles S, Salazar R, Delgado I. Proyecto de demostración en educación en diabetes. Informe Final. Organización Pan Americana de la Salud, Eli Lilly, 1998.

7. Gagliardino JJ, Etchegoyen G. A model educational program for people with type 2 diabetes: a cooperative Latin American implementation study (PEDNID-LA). Diabetes Care 2001; 24(6):1001-1007.

8. Scheffler RM, Feuchtbaum LB, Phibbs CS. Prevention: the cost-effectiveness of the California diabetes and pregnancy program. Am J Public Health 1992; 82:168-175.

9. Elixhauser A, Weschler JM, Kitzmiller JL, Marks JS, Bennert Jr HW, Coustan DR, Gabbe SG, Herman WH, Kaufmann RC, Ogata ES, Sepe SJ. Cost-benefit analysis of preconception care for women with established diabetes mellitus. Diabetes Care 1993; 16(8):1146-1157.

10. Simell T, Moren R, Keltikangas-Jarvinen L, Hakalax J, Simell O. Short-term and long-term initial stay in hospital of children with insulin-dependent diabetes: adjustment of families after two years. Acta Paediatr 1995; 84:41-50.

11. Penfornis A, Millot L. Initiating insulin treatment in insulin-requiring type 2 diabetic patients: comparative efficiency and cost of outpatient and inpatient management. INNOV Study Group. Diabetes Metab 1998; 24(2):137-142.

12. Mengistu M, Lungi Y, Mamo F. Inpatient or outpatient initiation of insulin therapy. Experience and cost effective analysis in a suboptimal clinical setting. Trop Geogr Med 1991; 43(1-2):180-183.

13. Dougherty G, Schiffrin A, White D, Soderstrom L, Sufrategui M. Home-based management can achieve intensification cost-effectively in Type 1 diabetes. Pediatrics 1999; 103(1):122-128.

14. The DCCT Research Group. Lifetime benefits and costs of intensive therapy as practiced in the DCCT. JAMA 1996; 276:1409-1415.

15. Gray A, Raikou M, McGuire A, Fenn P, Stevens R, Cull C, et al. Cost effectiveness of an intensive blood glucose control policy in patients with type 2 diabetes: Economic analysis alongside randomised controlled trial (UKPDS 41). BMJ 2000; 320:1373-1378.

Meeting the ChallengesChapter 7


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Meeting the Challenges Chapter 7

While other chapters discuss diabetes from a global perspective, this

chapter looks at it from a regional viewpoint. This close-up of the seven regions, reflecting the IDF regional structure, will provide readers with an overview of diabetes prevalence, care and management as well as the challenges posed by the diabetes epidemic.

The seven regions are:

• Africa (AFR)• Eastern Mediterranean and Middle East

(EMME)• Europe (EUR)• North America (NA)• South and Central America (SACA)• South-East Asia (SEA)• Western Pacific (WP)

Although diabetes is the common enemy, evidence shows that the challenges differ from region to region as a result of several complex and interrelated factors. Actions carried out at regional levels also indicate that culturally appropriate strategies must be identified in order to improve the lives of people with diabetes as well as prevent those at risk from developing the disease.

7.1 Africa

7.2 Eastern Mediterranean and Middle East

7.3 Europe

7.4 North America

7.5 South and Central America

7.6 South-East Asia

7.7 Western Pacific



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Introduction

Diabetes exerts a considerable toll on health resources of the developing countries of sub-Saharan Africa. The chronicity of the disease and diabetic complications also place a heavy burden on people with diabetes and their families.

Of the 49 least developed countries in the world, as defined by the United Nations Economic and Social Council, 33 are in sub-Saharan Africa. The economic cost of diabetes and its complications cannot be met by most of the individuals and families in these countries whose incomes are insufficient to purchase insulin, oral hypoglycaemic agents and other supplies for diabetes management.

The rate at which new cases of diabetes are emerging poses an additional burden on countries already stretched to the limit by common life-threatening infections such as malaria, tuberculosis and HIV/AIDS.

The landscape of sub-Saharan Africa is dominated by the twin disasters of poverty and HIV infection. All of the countries, except South Africa, Gabon and Zimbabwe, currently have per capita gross domestic products (GDPs) of less than US$2,000, and for half of these countries the figure is less than US$1,000. The greatest life expectancy is in Senegal (63 years), and in over half the countries life expectancy at birth is less than 50 years. Two of the three countries with higher GDPs, South Africa and Zimbabwe, have HIV infection rates currently estimated at 20% and 25% respectively (1).

While HIV infection and AIDS so dominate the health needs for sub-Saharan Africa, there is only a small proportion of the population reaching ages at which type 2 diabetes becomes a major health concern. For all sub-Saharan Africa, only 9.7% of the population is currently 50 years of age or older, and this is expected to increase to only 10.5% by 2025. Thus the effects of HIV and malnutrition combine to greatly reduce the size of the groups most at risk for type 2 diabetes.

Diabetes and IGT prevalence

There are marked discrepancies between the prevalences of diabetes among different communities in sub-Saharan Africa (see Chapter 1). The highest prevalences are among the ethnic Indian population of Tanzania (2) and South Africa (3). The studies from Tanzania (4, 5) (urban:rural ratio of 5:1) and Cameroon (6) (ratio of 2:1) both confirm the marked urban/rural discrepancy in diabetes prevalence, with the consequent likely increases as more people move to urban areas.

The availability of prevalence data for sub-Saharan Africa is very limited, and nearly all the data in Chapter 1 were

7.1 Africa


Total population (millions) 666.6 1,107.4Adult population (millions) (20-79 years) 295.1 541.1Diabetes prevalence (%) (20-79 years) 2.4 2.8Diabetes numbers (millions) (20-79 years) 7.1 15.0IGT prevalence (%) (20-79 years) 7.3 7.3IGT numbers (millions) (20-79 years) 21.4 39.4

At a glance



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derived from studies from South Africa (7, 8), Tanzania (4, 5), Ghana (9), Cameroon (6) and Sudan (10). This meant that data from these studies were applied to populations living up to several thousand

kilometres from where the study was undertaken.

It should be noted that the Cameroon and Ghana studies indicated markedly

Figure 7.1Prevalence estimates of diabetes in selected countries – African Region

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Figure 7.2Prevalence estimates of impaired glucose tolerance in selected countries – African Region

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different prevalences of diabetes and IGT among the urban participants surveyed, and these differences are too pronounced to be a consequence of the changed WHO diagnostic criteria since 1999 (11). Notwithstanding that Cameroon and Ghana are about 1,000 kilometres apart, and classified by the United Nations (12) as being in different parts of Africa (central and western, respectively), it was decided to use the average of the results of the two studies to apply to the other African countries not otherwise applying the Tanzanian, South African or Sudanese data.

That the data should need to be extrapolated to such distant and probably dissimilar countries and populations indicates the great need for further epidemiological investigation in the region. Such a need can also be linked with the high rate of diabetes that had not been previously detected, but found only at the time of surveying. Undiagnosed diabetes accounted for 60% of those with the disease in Cameroon (6), 70% in Ghana (9) and over 80% of the recent Tanzania survey (5).

The impact of type 2 diabetes is bound to continue if nothing is done to curb the

rising prevalence of impaired glucose tolerance (IGT), which now varies between 2.2% and 16.2%.

Incidence of type 1 diabetes The need for extrapolation of rates of childhood type 1 diabetes was also particularly evident in the sub-Saharan African region. Published rates were found for only three of the countries in this region, and some of the studies were of poor quality and based on small numbers. Consequently imperfect estimates of rates from Nigeria, Zambia and Tanzania have had to be used for widespread extrapolations because of the dearth of published studies (see Chapter 2).

Diabetes care

Most of the diabetes care services in the developing countries of sub-Saharan Africa have been established through unsystematic, needs-based efforts. This is due to the limited resources of these countries which have to be divided between fighting poverty, implementing education strategies, providing housing and appropriate sanitation, as well as the social, economic and health burden of fighting the increasing prevalence and incidence of HIV and AIDS.

As the burden of diabetes and its complications increases with modernization, economic wellbeing and westernized lifestyle, these resource-limited countries are unable to provide even minimum care in some instances, let alone secondary and tertiary care.

There is an urgent need for a multi-sectoral approach in which governments, the pharmaceutical industry, national diabetes associations, healthcare providers and people with diabetes can play a role in providing at least minimum standards of care that would help those affected maintain the best possible quality of life.

Type 1 diabetes 2003

Child population (millions) (0-14 years) 295.0

Type 1 diabetes prevalence (%) (0-14 years) 0.01

Type 1 diabetes numbers (thousands) (0-14 years) 35.1

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References

1. CIA. World Factbook 2002. Central Intelligence Agency, 2002.

2. Ramaiya KL, Denver E, Yudkin JS. Diabetes, impaired glucose tolerance and cardiovascular disease risk factors in the Asian Indian Bhatia community living in Tanzania and in the United Kingdom. Diabet Med 1995; 12(10):904-910.

3. Omar MA, Seedat MA, Dyer RB, Motala AA, et al. South African Indians show a high prevalence of NIDDM and bimodality in plasma glucose distribution patterns. Diabetes Care 1994; 17(1):70-73.

4. McLarty DG, Swai AB, Kitange AM, Masuki G, et al. Prevalence of diabetes and impaired glucose tolerance in rural Tanzania. Lancet 1989; 1(8643):871-875.

5. Aspray TJ, Mugusi F, Rashid S, Whiting D, et al. Rural and urban differences in diabetes prevalence in Tanzania: the role of obesity, physical inactivity and urban living. Trans R Soc Trop Med Hyg 2000; 94(6):637-644.

6. Mbanya JC, Ngogang J, Salah JN, Minkoulou E, et al. Prevalence of NIDDM and impaired glucose tolerance in a rural and an urban population in Cameroon. Diabetologia 1997; 40(7):824-829.

7. Omar MA, Seedat MA, Motala AA, Dyer RB, et al. The prevalence of diabetes mellitus and impaired glucose tolerance in a group of urban South African blacks. S Afr Med J 1993; 83(9):641-643.

8. Levitt NS, Katzenellenbogen JM, Bradshaw D, Hoffman MN, et al. The prevalence and identification of risk factors for NIDDM in urban Africans in Cape Town, South Africa. Diabetes Care 1993; 16(4):601-607.

9. Amoah AG, Owusu SK, Adjei S. Diabetes in Ghana: a community based prevalence study in Greater Accra. Diabetes Res Clin Pract 2002; 56(3):197-205.

10. Elbagir MN, Eltom MA, Elmahadi EM, Kadam IM, Berne C. A population-based study of the prevalence of diabetes and impaired glucose tolerance in adults in northern Sudan. Diabetes Care 1996;19:1126-1128.

11. World Health Organization. Definition, Diagnosis and Classification of Diabetes Mellitus and its Complications; Part 1: Diagnosis and Classification of Diabetes Mellitus. World Health Organization, Department of Noncommunicable Disease Surveillance, Geneva, 1999.

12. United Nations Population Division. World Population Prospects: The 2000 Revision. United Nations, Geneva, 2001.

Regional initiatives

The IDF African Region has addressed two critical issues by forming task forces on diabetes clinical care guidelines and diabetes education.

The objective of the Task Force on Diabetes Clinical Care Guidelines is to provide standardized clinical guidelines for diabetes care and to promote its implementation and use in order to improve the quality of care provided to people with diabetes.

The aim of the Task Force on Diabetes Education is to provide high quality information by adequately trained individuals to people with diabetes so as to improve their standard of care.

A standardized curriculum taking into consideration socio-economic variations within the region will be developed using existing resources such as the IDF Diabetes Education Consultative Section (DECS) and the Pan African Diabetes Education Study Group (PADEG).



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Introduction

Diabetes prevalence in some countries of the Eastern Mediterranean and Middle East Region (EMME) are among the highest in the world. This vast region extends from Pakistan in the east to Morocco in the west, and the population is a mosaic of several ethnic groups. The age distribution pattern of the population is pyramidal with about 50% of the population below the age of 20 years.

Over the past three decades major social and economic changes have occurred in the majority of these nations. These include progressive urbanization, decreasing infant mortality and increasing life expectancy. Current life expectancy exceeds 65 years in most member countries, while per capita GDP varies markedly, from US$800 in Afghanistan to US$21,200 in Qatar.

Rapid economic development, especially among the more wealthy oil-producing countries, has been associated with tremendous changes in lifestyle towards the westernized pattern reflected by changes in nutrition, less physical activity, tendency to increased obesity and more smoking (1-5).


The last two decades have witnessed a change in diabetes epidemiology. It is now recognized that it is the developing countries, and the migrant population from the Indian subcontinent living in the developed countries, which presently face the greatest burden of diabetes.

The explosion of diabetes in the EMME Region is mainly due to type 2 diabetes. An estimated 19.2 million people, or 7% of the adult population, have diabetes. This is anticipated to more than double by 2025. Similarly the number of persons

with IGT is expected to also double from 18.7 million today to 36.5 million in 2025, increasing the likelihood of further increases in the prevalence of diabetes as the century proceeds.

The ageing of populations, together with socio-economic changes and westernization, has resulted in the dramatic increase in the diabetes prevalence. Studies conducted in different populations have reported prevalences as high as 20% in the United Arab Emirates (6), 16% in Qatar and 15% in Bahrain (7), but even in much less affluent Pakistan the prevalence is 8.5% (8-10).

Four of the countries of the region – United Arab Emirates, Bahrain, Kuwait and Oman (6, 7, 11, 12) – have had studies performed showing their current diabetes prevalence to be among the world’s 10 highest, and a similar situation applies for the IGT prevalence of these countries (see Chapter 1). As with many other countries with high diabetes prevalence, the onset of type 2 diabetes tends to occur at a relatively young age.

7.2 Eastern Mediterranean and Middle East


Total population (millions) 544.6 839.2Adult population (millions) (20-79 years) 276.0 493.6Diabetes prevalence (%) (20-79 years) 7.0 8.0Diabetes numbers (millions) (20-79 years) 19.2 39.4IGT prevalence (%) (20-79 years) 6.8 7.4IGT numbers (millions) (20-79 years) 18.7 36.5

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Figure 7.3Prevalence estimates of diabetes in selected countries – Eastern Mediterranean andMiddle East Region

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In contrast to Africa, there are a large number of studies ascertaining diabetes prevalence, so that of the 22 countries of the region, 13 have data from which national prevalence estimates could be derived.

Differences in prevalence rates in different geographic areas and among various ethnic groups are quite marked. In general, prevalences of both diabetes and impaired glucose tolerance (IGT) are higher in urban areas compared to rural communities. Certain rural communities, furthermore, seem to be protected and have appreciably lower prevalence rates, such as the Bedouins in the Egyptian deserts (3).

Recent studies confirm the tremendous effect of migration from rural to urban

areas with the changes in lifestyle leading to increased prevalence of diabetes and all related metabolic dysfunctions. A good example is the migration of Nubians from southern Egypt to the northern cities (13) and of Indo-Pakistanis to western countries (14,15).

Whereas in some countries gestational diabetes mellitus (GDM) is reported to be about 3.5%, GDM was detected in 10.2% of pregnant women in the high risk group and 0.6% in cases with no risk factor in a study from Pakistan (16).

Incidence of type 1 diabetesIn the EMME Region about half of the countries have published incidence rates for type 1 diabetes. By far the largest contribution to the total number of estimated childhood type 1 cases for this



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Figure 7.4Prevalence estimates of impaired glucose tolerance in selected countries – Eastern Mediterranean and Middle East Region

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region comes from Egypt whose estimate accounts for about a quarter of the region’s total (see Chapter 2).

Diabetic complications

In some recent unpublished studies on the epidemiology of diabetic complications in Pakistan and Egypt, there are indications that nephropathy occurs in 14-20% of people with diabetes, neuropathy 40%, retinopathy 32-43%, foot ulcers 4-7%, associated obesity 80% and hypertension 64% (17, 18). Lack of proper glycaemic control was present in 50-80% of those studied.

Costs of diabetes

With progressive economic development in the region, health parameters, such

as life expectancy, infant mortality, availability of hospital beds, number of physician and nurse per capita, are improving. Furthermore, some of these parameters are satisfactory, even in countries with lower incomes, such as Egypt (1, 19).

Although government and household expenditures on health vary in the region, the general pattern of these two parameters is nearer to that typical in developing countries. So, in contrast to the developed European countries, expenditure on health constitutes a smaller fraction of the total national production compared to expenditures on food, defence and education (1, 4, 5).

In general, the economic burden of diabetes in the EMME countries is great



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because of the high prevalence rate coupled with the high cost of diabetes and limited resources. This is more evident in the lower income countries with big populations such as Egypt, Morocco and Pakistan (1, 4, 5, 19).

Some earlier studies have indicated that the direct cost of diabetes, ie ambulatory and hospital care, may make up more than one-third of total available government resources for health expenditure. Moreover, the progressively increasing prices of recently introduced medications place a further burden on people with diabetes, especially in the lower income countries. Therefore, programmes for government subsidies, whether partial or whole, are available in different forms in some countries.

Diabetes care

Standards for diabetes care provision differ between different countries according to available resources, although not exactly corresponding to their absolute levels of per capita income (4).

National diabetes programmes based on IDF and WHO recommendations were adopted by several countries in the region.

These programmes were more easily implemented by countries with smaller population and high income than in countries with larger populations.

In general higher standards of diabetes care are provided in urban than rural areas. Primary care for diabetes is generally carried out by general practitioners or physicians and less commonly by diabetologists in diabetes clinics at university hospitals and diabetes institutes. Diabetes clinics with elaborate facilities and organized referral systems provide services at secondary and tertiary levels in the capitals and major cities of all countries. However, certain aspects of diabetes care are evidently lacking, such as services of dietitians and more seriously, foot care specialists.

Diabetes camps and day school programmes for children and adolescents are organized by several EMME countries eg Tunisia, Qatar, Bahrain, Iran, Syria and Egypt.

Diabetes associations

Most of the countries in this area have diabetes associations. The diabetes associations vary markedly in their membership size from less than 200 to more than 14,000, and in their capacities to carry full diabetes programmes for care, advocacy and education.

Some national diabetes associations eg in Pakistan, Egypt and Iran have regular diabetes magazines published in local languages while others also have regular scientific diabetes journals such as the Egyptian Diabetes Journal.

Educational courses for people with diabetes and for physicians are organized by almost all of the national associations, and frequently also by health authorities. Recently, educational programmes for nurses and pharmacists are gaining interest (19).





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Public awareness about self-care and prevention of complications has increased over the years through programmes carried out by the national associations, especially during World Diabetes Day events.

Sociological considerations

Although misconceptions about diabetes may still exist widely in some areas, they are being actively corrected through educational efforts. The high rate of illiteracy in some countries indicates the use of specific tools for public and patient education. Television programmes play an important role to achieve this objective.

Since Moslems constitute the majority of the population, certain aspects of the Moslem faith have close interaction with diabetes management, through its doctrines of encouragement of exercise, moderation of food intake, cleanliness and self preservation of health. Fasting, during the holy month of Ramadan, requires some modification of diabetes management, in order to avoid the hazards of hypoglycaemia or of disturbing the metabolic control. Exemption from fasting is allowed during sickness, while travelling, for the elderly and whenever there is risk of endangering health and safety (4).

Diabetes research

Scientific research in the EMME Region is mostly carried out at state universities and medical institutes. Specific research on national diabetes problems, particularly in the fields of epidemiology and socio-economics, is gaining increased interest. Some diabetes associations have contributed and published extensive epidemiological studies on diabetes and its complications, the cost of diabetes and the effect of lifestyle changes in the region.

References

1. Arab M. The Economics of Diabetes Care in the Middle East. In International Text Book of Diabetes Mellitus, Eds Alberti KGMM, et al. J Wiley & Sons second edition, 1997.

2. Arab M. Epidemiology of Diabetes Mellitus in Egypt. Egypt J of Diab 1997; 2:1-14.

3. Arab M, El Sewi F. Diabetes in the Egyptian Deserts: a very low prevalence. Diabetes Care 1996; 19:90.

4. Arab M. Socioeconomic background of Diabetes in Mediterranean countries. Proceedings of MGSD, Madrid. Medicographia 1993;16 suppl 1.

5. The World Bank. World Bank Data, WHO parameters, 1999-2000.

6. Malik M, Bakir A, Abi Saab B, Roglic G, et al. Prevalence of Diabetes Impaired Fasting Glucose, Impaired Glucose Tolerance, Hypertension and Obesity in the Multi-ethnic Population of the United Arab Emirates. Unpublished. Abu Dhabi, 2002.

7. Al-Mahroos, McKeigue FPM. High prevalence of diabetes in Bahrainis. Associations with ethnicity and raised plasma cholesterol. Diabetes Care 1998; 21(6):936-942.

8. Shera AS, Rafique G, Khawaja IA, Baqai S, et al. Pakistan National Diabetes Survey: prevalence of glucose intolerance and associated factors in Baluchistan province. Diabetes Res Clin Pract 1999; 44(1):49-58.

9. Shera AS, Rafique G, Khwaja IA, Ara J, et al. Pakistan national diabetes survey: prevalence of glucose intolerance and associated factors in Shikarpur, Sindh Province. Diabet Med 1995; 12(12):1116-1121.

10. Shera AS, Rafique G, Khwaja IA, Baqai S, et al. Pakistan National Diabetes Survey prevalence of glucose intolerance and associated factors in North West at Frontier Province (NWFP) of Pakistan. J Pak Med Assoc 1999; 49(9):206-211.

11. Abdella N, Al Arouj M, Al Nakhi A, Al Assoussi A, et al. Non-insulin-dependent diabetes in Kuwait: prevalence rates and associated risk factors. Diabetes Res Clin Pract 1998; 42(3):187-196.

12. Al-Lawati JA, Al Riyami AM, Mohammed AJ, Jousilahti P. Increasing prevalence of diabetes mellitus in Oman. Diabet Med 2002; 19(11):954-957.

13. Arab M, Abdel–Rehim A, Khalifa KMA, Kafrawy N, El-Guisery D. Prevalence of diabetes and related metabolic changes among the Egyptian Nubians and the effect of changes in their lifestyle as a result of migration to urbanized communities. The Egyptian Diabetes Journal July 1997; 2:59-64.

14. Mather HM, Keen H. The Southall Diabetes Survey: prevalence of diabetes in Asians and Europeans. BMJ 1985; 291:1081-1084.

15. Simmons D, Williams DRR, Powell MJ. Prevalence of diabetes in a predominantly Asian community: preliminary findings of the Coventry diabetes study. BMJ 1989; 298:18-21.

16. Samad N, Shera As, Ara JH. Gestational Diabetes Mellitus – Screening in a Developing Country. J Pak Med Assoc 1996; 46(11):249-252.

17. Shera AS, Jawad F, Maqsood A, Jamal S, Azfar M, Ahmed U. Prevalence of chronic complications and associated factors in type 2 diabetes. Diabetic Association of Pakistan and WHO Collaborating Centre for Diabetes. Unpublished. Karachi, Pakistan, 2003.

18. Arab M, Kafrawy N, Kamel M, Rifaie M. Epidemiology of diabetes complications in Egypt. Unpublished. Egypt, 2003.

19. Arab M. The socio-economic impact of diabetes in developing countries. Proc. of “Advances in type 2 Diabetes Management” Meeting, Istanbul, May 2002.



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Introduction

Among the European Region’s 51 countries, which extend from Kyrgyzstan in the east to Iceland in the northwest, exists a great diversity of populations and affluence, with GDP varying from over US$40,000 per capita for Luxembourg to less than US$4,000 for several of the former socialist republics.


Abnormal glucose tolerance in this region shows little association with affluence, and there was no evidence that any difference in urban/rural prevalence existed except in Turkey (1), and the Central Asian Republics of Kazakhstan, Kyrgyzstan, Tajikistan and Turkmenistan (for which data were extrapolated from neighbouring Uzbekistan (2)). Prevalence rates for diabetes show a wide variation from 2.0% in Iceland to 10.2% in Germany (see Figure 7.5).

The lack of data from many of the former socialist republics required that data for many countries be extrapolated from two studies from Poland - urban Krakow (3), and the urban and rural areas near Lublin (4). These data suggested high levels of diabetes currently, and such high levels of IGT that the diabetes prevalence will almost certainly increase by 2025 to levels above those indicated in Tables 1.18 and 1.20 in Chapter 1, as these took no account of the higher incidence of diabetes among those with IGT.

Surprisingly there is a paucity of good data from many of the more affluent western countries of the region. The largest nationwide survey from Germany indicated only those with known diabetes (5), with total diabetes prevalence determined by applying the 1:1 ratio for known:newly diagnosed diabetes determined from an age restricted survey

from Augsburg (6). Similarly data from two regions of Italy (7, 8) were applied to more than 100 million people from Italy and France. There is a clear need for better data from those countries that can afford to ascertain the extent of the epidemic.

To a large degree the high prevalence of abnormal glucose tolerance is a consequence of the relatively old population of the region, such that currently a third of the region’s population is over 50 years of age, which is expected to increase to over 40% by 2025. Thus the number of persons with diabetes and IGT will increase, although the total regional population will have decreased. This will place an increasing financial burden on the declining working age population to provide resources for the health consequences of rising diabetes prevalence in the older population. The region has the resources to be at the forefront of efforts to amend lifestyle factors contributing to the prevalence of diabetes.

7.3 Europe



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Incidence of type 1 diabetesCompared with other regions, the European Region has by far the most complete and reliable data on the rates of childhood type 1 diabetes with a large proportion of countries having registries that are either nationwide or cover several different parts of the country. The countries making the largest contribution to the total rates for childhood type 1 diabetes were United Kingdom, Germany and Russia reflecting to some degree the large childhood populations in these countries (see Chapter 2).

Diabetes care

The European Region is characterized by a wide variety of diabetes care delivery due to differences in national healthcare systems and available resources of the country.

Within the region, it is possible to find the most advanced healthcare systems and some of the most deprived. The level of the quality of diabetes care in the western and northern areas of the continent is rather high with a tendency towards a certain degree of homogeneity in European Union (EU) member countries, although some differences still exist even in that cluster.





At a glanceIn the central European countries formerly related to the Soviet bloc, such as Hungary, Poland, Czech Republic, Romania, Slovenia and Slovakia, the quality of care is rapidly evolving to the most advanced standards. In other countries such as Bulgaria, Georgia, Ukraine, Moldova, Belarus and Russia, existing economic and environmental difficulties have an impact on the availability of good quality diabetes care throughout the country, although the growth of specialized and advanced centres is creating a basis for positive development when it will be allowed by more favourable conditions.

In the most eastern part of the region, socio-economic and geographical conditions make it difficult to foresee a satisfactory progression towards adequate standards of care in the near future if appropriate international support is not provided. In the Balkan area, for instance, there are significant gradients in adequate diabetes care availability within a restricted geographical area. Diabetes care in Croatia has benefited from long-standing experience and from stability for nearly a decade, while other countries and provinces are still affected from the recent civil war and still unstable political situations.

In the most advanced countries the shared care approach consisting of an integration of different levels of care, from highly specialized to primary care with the involvement of medical and non-medical professionals such as dietitians, podologists, nurse educators, psychologists, is becoming an increasing reality while in nearby deprived countries regular access to insulin is still a major issue.

In some countries, intensified therapy both for type 1 and type 2 diabetes is the normal standard, and campaigns for screening of undiagnosed diabetes and for complications are regularly



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Figure 7.5Prevalence estimates of diabetes in selected countries – European Region

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performed. There are also widespread pilot initiatives, primarily in Finland, for the primary prevention of type 2 diabetes, while in other countries resources are lacking for minimal interventions for the prevention of major complications and to even secure the survival of people with diabetes.

A pressing issue has arisen from migration within the European Region and from other parts of the world. The need is more and more evident for greater attention to be paid to migrants affected by diabetes in order to guarantee

an adequate level of care, which would overcome language and cultural barriers and take into consideration differences in nutritional habits, behaviours, beliefs, values and, in most of the cases,socio-economic circumstances.

National diabetes programmes

Most countries in the European Region have a national diabetes programme. The St Vincent Declaration has been used by many as a framework for strategic action (see Chapter 8). The prevention of type 2 diabetes is the main focus of many



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national diabetes programmes with key action being taken to raise awareness among the public.

While some countries have yet to implement their programmes, others have made great strides in implementation and development. A good example is Finland where an extensive national diabetes programme is now underway (see Box 7.1). The programme, implemented in 2000, was developed with the participation of different stakeholders in diabetes care,

especially the Finnish Diabetes Association which played a leading role.

Each national model should be unique to meet national needs and cultural specifics. The expertise gathered in other countries however could be very useful for a specific country when planning a national diabetes programme. Cyprus, for instance, has recently started working on a national plan for diabetes using the Finnish model and learning from the Finns’ practical experiences from preparing a national programme.

Figure 7.6Prevalence estimates of impaired glucose tolerance in selected countries – European Region

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The United Kingdom (UK) is a good example of a governmental approach towards tackling the problem of diabetes but in general, the role of governments has not been strong enough in this area. The St Vincent Declaration has been in existence since the late 1980s but its goals related to improving health outcome have yet to be reached in most countries and thus are still valid. However, the raised awareness of diabetes, increased research and greater practical collaboration with regard to complications, diabetes economics and prevention can be attributed in some way to the St Vincent Declaration and its original action programme. Today, there are enough knowledge and skills in the region to really start building and implementing concrete national diabetes programmes.

Initiatives

The problem of overweight and lack of physical activity is as much an issue in this region as elsewhere in the world. Awareness campaigns in favour of a healthy lifestyle are being promoted at EU, regional and national levels by diabetes organizations. These campaigns are meeting with success in convincing top decision makers to take action to prevent or delay type 2 diabetes. A recent event held at the European Parliament, for example, obtained strong support from the European Commission President as well as the EU Health Commissioner and President of the European Parliament.

Another key initiative has been the establishment of an EU diabetes working group by members of the European Parliament to discuss issues such as the inclusion of diabetes on the public health agenda and in EU policy, discrimination against people with diabetes and the diabetes situation in EU candidate countries. The IDF European Region has also been instrumental in organizing a yearly round

Box 7.1

National diabetes programme:the Finnish model

Finland has a very extensive national programme called the Development Programme for the Prevention and

Care of Diabetes in Finland (DEHKO 2000−2010). The programme took two years, between 1998 and 2000, to develop by nearly 100 diabetes experts, including people with diabetes. It was approved at a consensus meeting in 2000, and implementation started in the same year.

By the beginning of 2003 there had been three rounds of auditing carried out by external auditors. The programme itself was audited in 2000, feedback by primary healthcare professionals were audited in 2001, and the preparation process and the first three years of implementation were audited in 2003.

The programme defines clear goals and 25 action recommendations, of which 10 are key actions. Through these, the programme covers the primary, secondary and tertiary prevention of diabetes and its complications. The most important key action is prevention of type 2 diabetes, and a detailed prevention programme for 2002-2003 was prepared and distributed to primary and occupational healthcare institutions.

The national diabetes programme is initiated and coordinated by the Finnish Diabetes Association (FDA) and financed by a governmental body, corporate partners and the FDA. The programme is available in English, both printed and on the website: www.diabetes.fi.

table at the European Parliament in order to involve decision makers at the highest level in influencing policies and for raising awareness on the ‘diabetes time bomb’.

Diabetes organizations have also taken initiatives at the national level with the aim to eradicate laws which discriminate against people with diabetes. Issues regarding discrimination in driving licences, insurance and at work are being raised in some parliaments, for example in the UK, and studies are being



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undertaken in several countries including Ireland, Denmark and UK.

Cultural and strategic initiatives promoted by the IDF European Region, especially under the umbrella of the St Vincent Declaration, have raised awareness of diabetes throughout the region and a further follow-up is taking place, adapted to new environmental and behavioural circumstances.

Diabetes research

Diabetes research is carried out in the European Region at the highest level in all possible fields, from basic to more clinically oriented. A number of centres of excellence have been established throughout the region. However the amount of funds made available by national governments and international agencies is not adequate. One result of this has been the drain of scientists towards better funded institutions, in particular in the United States.

Nonetheless, an alliance between the IDF European Region and the European Association for the Study of Diabetes (EASD) has resulted in success in influencing the European Commission to reintroduce research funding for diabetes within the Sixth Framework Programme for research, the most important research programme in the EU. IDF member associations played a significant role, coordinated by the IDF European Region, in mobilizing national governments and parliaments in a successful lobbying initiative that was unprecedented, and at the same time gained IDF an accreditation as the reference institution for any diabetes initiative in Europe.

References

1. Satman I, Yilmaz T, Sengul A, Salman S, et al. Population-Based Study of Diabetes and Risk Characteristics in Turkey: Results of the Turkish Diabetes Epidemiology Study (TURDEP). Diabetes Care 2002; 25(9):1551-1556.

2. King H, Abdullaev B, Djumaeva S, Nikitin V, et al. Glucose intolerance and associated factors in the Fergana Valley, Uzbekistan. Diabet Med 1998; 15(12):1052-1062.

3. Szurkowska M, Szybinski S, Nazim A, Szafraniec K, et al. Prevalence of type II diabetes mellitus in population of Krakow. Pol Arch Med Wewn 2001; 106(3):771-779.

4. Lopatynski J, Mardarowicz G, Nicer T, Szczesniak G, et al. The prevalence of type II diabetes mellitus in rural urban population over 35 years of age in Lublin region (Eastern Poland). Pol Arch Med Wewn 2001; 106(3):781-786.

5. Thefeld W. Prevalence of diabetes mellitus in the adult German population. Gesundheitswesen 1999;61 Spec No.:S85-89.

6. Rathmann W, Haastert B, Icks A, Lowel H, et al. High prevalence of undiagnosed diabetes mellitus in Southern Germany: Target populations for efficient screening. The KORA survey 2000. Diabetologia 2003; 46(2):182-189.

7. Garancini MP, Calori G, Ruotolo G, Manara E, et al. Prevalence of NIDDM and impaired glucose tolerance in Italy: an OGTT-based population study. Diabetologia 1995;38(3):306-313.

8. Verrillo A, de Teresa A, La Rocca S, Giarrusso PC. Prevalence of diabetes mellitus and impaired glucose tolerance in a rural area of Italy. Diabetes Res 1985; 2(6):301-306.



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7.4 North America

Introduction

The North American (NA) Region has the highest prevalence of diabetes among the IDF regions with 7.9%, or 23 million, in the adult population. The countries in the region represent not only different geographical characteristics and levels of socio-economic development but also diverse cultures.

Faced with a dramatic increase in diabetes as well as mounting costs in diabetes care, the Declaration of the Americas on Diabetes (DOTA) was created in 1996 with the collaboration of the IDF’s North American, and South and Central American Regions, the Pan American Health Organization (PAHO) and industry. The Declaration recognizes diabetes as a common, growing, serious and costly public health problem affecting millions in the Americas and PAHO has endorsed it as a guide to national programme development (see Chapter 8).

The North American Region has focused its efforts over the last few years in implementing the goals relating to education, awareness and quality of care in the Declaration.

Although the region has 23 countries and areas, 69% of the adult population resides in the USA, with a further 20% living in Mexico and 8% in Canada. The remaining 3% of the region’s adult population reside in the other 20 smaller nations. Whereas the USA, Canada and Bermuda have per capita GDPs of over US$25,000, many of the smaller nations have per capita GDPs of less than US$5,000 with Haiti having the lowest at US$1,700.


The high prevalence of abnormal glucose tolerance in Canada and the USA are very much a consequence of their older age distribution, such that 29% of their population are currently over 50 years of age, and this is expected to increase to 37% by 2025. This contrasts with 14% increasing to 25% for Mexico, and 19% increasing to 28% for the Caribbean (see Chapter 1).

The data published in Tables 1.24 and 1.25 in Chapter 1 indicated the expected number of persons with impaired fasting glucose (IFG) for Canada and the USA, based on the data from NHANES III, which concentrated on assessment based on the fasting glucose. When the published data were extrapolated to determine IGT numbers, the results suggested that in 2003 for the USA, the prevalence of IGT would be 11% (21.6 million persons), and for Canada also 11% (2.5 million persons); both figures being about 50% higher than the IFG numbers and prevalences. By 2025 the expected prevalences are expected to be about 12%, with numbers still about 50% higher than for IFG.

As all the Caribbean islands other than Barbados, Guadeloupe and Martinique had their estimates extrapolated from



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Figure 7.7Prevalence estimates of diabetes in selected countries – North American Region

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Jamaican data (1), the differences in prevalence are a consequence only of different age distributions for the islands, and for those islands whose population distributions were based on the world population (2), their lower prevalences suggest that their actual age structure is probably older than the world distribution.

Incidence of type 1 diabetesAlthough no published rates were available for childhood type 1 diabetes in many of the smaller Caribbean islands in the North American Region, it was usually possible to extrapolate rates from an island in close proximity, although such rates were often based on very small numbers of cases. The USA estimate, which accounts for more than three-quarters of the region’s total, and to a lesser extent the estimate for Canada predominate (see Chapter 2).

United States of AmericaDiabetes is the fifth leading cause of disease in the United States, where some 16 million people, or 8% of the adult population have diabetes. While an estimated 11 million people have

been diagnosed, some five million unfortunately are not aware that they have the disease.

Each day approximately 2,700 people are diagnosed with diabetes; about one million people will be diagnosed this year. The prevalence is expected to increase to 9%, affecting some 23 million adults by 2025. The prevalence of diabetes rises





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Figure 7.8Prevalence estimates of impaired glucose tolerance in selected countries – North American Region

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* Prevalence estimates are for IFG

with age in the United States, as it does in other parts of the world. While the rate of diabetes for all adults 20 years or older is 8%, the prevalence rate climbs to 20%, or 7 million, for the age group 65 and older.

The problem of diabetes is likely to be compounded by the high prevalence rate of IGT in the adult population. Today, some 21 million people, or 11% in the adult population, have IGT.

Of the 16 million adults with diabetes, more than 90% have type 2 diabetes. Type 2 diabetes is more common among these ethnic groups:

• African Americans are twice as likely to have type 2 diabetes as the general population. An estimated 2.8 million African Americans, or 13%, have diabetes.

• Hispanic/Latino Americans are almost twice as likely to have type 2 diabetes as the general population. Diabetes affects 2 million, or 10%, of the Hispanic/Latino population in the United States.

• Native Americans and Alaska natives have the highest prevalence of diabetes in the United States, with

an overall rate 2.6 times that of the general population. The rate varies greatly by region and tribe; in some tribes over 50% of the adults have diabetes.

Diabetes is one of the most costly health problems in America. The total annual economic cost of diabetes in 2002 was estimated to be US$131 billion dollars, including some US$91 billion in direct medical and treatment costs and almost US$40 billion for indirect costs attributed to disability and mortality.

CanadaDiabetes mellitus is a major health problem affecting some 9%, or 2 million, in the adult Canadian population. The prevalence of diabetes is expected to rise to some 3 million, or 11% in the adult population by 2025.

As in many other western countries about 90% of the diabetic population have type 2 diabetes with prevalence on the increase as the general population ages. The prevalence of diabetes in the indigenous population, however, appears to be increasing much more rapidly than in other population groups.



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In addition the growing multicultural nature of the country means that new Canadians are unusually susceptible to type 2 diabetes as they assume western culture. This rising trend is reflected in the high prevalence of IGT which affects 2.5 million adults, or 11% in the adult population.

Major studies into the risks and complications of diabetes are underway or have been recently completed. The linkage between diabetes and obesity has been identified while the complications of heart disease, renal failure, blindness and lower extremity amputations have been explored. Action is being taken to increase public and professional awareness of these linkages.

The major challenge facing Canada is to change the behaviour of its people so that they assume increased responsibility for their own health and wellbeing. Governments are considering preventative healthcare strategies to assist in this regard.

MexicoThe estimated prevalence rate in Mexico is 7% in the adult population, or 4.4 million people, which puts it among the top 10 countries in the world in terms of the number of people with diabetes. Estimates show that the number of people is expected to more than double to some 9 million by 2025.

Data for IGT show that almost as many people, some 4 million, have the condition, and that this too is set to increase to 6 million by 2025.

Caribbean islandsThere are few studies done on diabetes prevalence in the Caribbean. There is a study currently underway on the prevalence of diabetes and hypertension in Haiti as well as a pilot project on quality of care. Nonetheless, estimates from the islands based on previous studies indicate diabetes prevalence

rates of between 5% and 10% in the adult population, and IGT prevalence rates of between 7% and 18%.

New advances

The overall thrust in this region has been to raise awareness of diabetes among the general population and intensify diabetes education amongst the health team and people with diabetes in particular.

There are new advances on the horizon in the prevention and treatment of diabetes. Government-supported and industry researchers in the region, mainly USA and Canada, are pursuing advances in treatment and prevention for both type 1 and type 2 diabetes. For prevention of type 1, studies are underway to identify environmental triggers that may be subject to modification or elimination, which could effectively prevent type 1 diabetes in those at risk. In type 2 diabetes, recently concluded trials have shown that a majority of this type of diabetes can be prevented or at least delayed by sustained lifestyle changes (diet and exercise).

Other research is aimed at lessening the burden of diabetes by improving glucose monitoring, including the use of non-invasive or minimally invasive glucose sensors. New types of insulin and insulin delivery devices are being developed that may allow needle-free insulin delivery and more physiologically normal insulin delivery. Drug development sponsored by industry is exploring new methods to improve management of type 2 diabetes and to arrest and even reverse the progression of complications such as neuropathy, nephropathy and vascular disease.



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References

1. Wilks R, Rotimi C, Bennett F, McFarlane-Anderson N, Kaufman JS, Anderson SG, Cooper RS, Cruickshank JK, Forrester T. Diabetes in the Caribbean: results of a population survey from Spanish Town, Jamaica. Diabet Med 1999; 16:875-883.

2. United Nations Population Division. World Population Prospects: The 2000 Revision. United Nations, Geneva, 2001.



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Introduction

The South and Central American (SACA) Region encompasses 22 countries with a population of more than 420 million. Most of the countries are still developing economically, with Argentina, having the highest per capita GDP (US$10,200) despite a recent fall, and Cuba the lowest at US$2,300 (1).

Some 82% of the region’s population live in South America, 9% in Central America and 9% in the Caribbean islands. The admixture between native Indians, white Iberians and black Africans has been occurring since the 16th century. There are still countries such as Bolivia, Guatemala and Peru where more than 40% of the population is considered American Indian.

The proportion of mestizos (descendants of American Indians and Spaniards) in the population range from 80% or more in Chile, Ecuador, El Salvador, Honduras

7.5 South and Central America

and Paraguay to less than 20% in Argentina and Uruguay, where there was a strong white non-Hispanic immigration, mainly from Italy. There has also been a significant immigration from Japan and the Middle East.

Diabetes prevalence

Considerable extrapolation was required in this region as 15 countries do not have any epidemiological data from which diabetes prevalence could be derived (see Chapter 1).

Nonetheless, both South America and Central America have similar age distribution profiles, currently about 15% of the population older than 50 years, with this figure likely to increase to 25% by 2025. Thus the region has a markedly younger age distribution than most of North America, and otherwise would have a similar burden of diabetes. The likelihood is that diabetes will become a more major health priority for the region given the decreasing difference in age distribution between this region and North America, and with the continuing momentum for urbanization.

Between 30% and 50% of people with type 2 diabetes are not aware that they have the condition (in the rural areas it can be as high as 100%). Type 2 is often diagnosed late.

Incidence of type 1 diabetesThe variable ethnic composition of the SACA Region may have an influence on the incidence of type 1 diabetes mellitus. For example, the incidence of type 1 diabetes is relatively high in Uruguay (mainly Caucasoid population) and very low in Peru (mainly mestizos population). There are some exceptions such as Puerto Rico, where, although its population has an admixture of Hispanic, African and Taíno Indian, there is a high incidence of



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Figure 7.9Prevalence estimates of diabetes in selected countries – South and Central American Region

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type 1 diabetes in youngsters that has been increasing recently. Thus, although the incidence of childhood type 1 diabetes in the SACA Region is generally low, there are some sharp contrasts between the rates in neighbouring countries (see Chapter 2).

Diabetes care

National diabetes associations have been the main promoters of public awareness and diabetes education in the SACA Region. The oldest, such as the Uruguayan and the Colombian Diabetes Associations, have been active for more than 40 years. These non-governmental and non-profit organizations, usually with very small budgets, provide educational courses and materials, and organize diabetes awareness programmes.

The associations in some countries run diabetes care centres which offer specialized medical care and education as well as medications, laboratory tests and self-monitoring equipment at a very low cost. This has been for a long time the only means for many people with low and very low incomes to keep their diabetes

under control, particularly in the case of those who are insulin-dependent.

In many countries of the region less than 20% of the population are covered by social security and the rest have to rely on very deficient and overcrowded public health centres with scarce resources, or go to the private sector which most cannot afford. Only a few countries such as Costa Rica and Cuba have a social





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Figure 7.10Prevalence estimates of impaired glucose tolerance in selected countries – South and Central American Region

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security system that covers the whole population.

In countries such as Argentina, Chile, Uruguay, Puerto Rico and Colombia, health maintenance organizations provide a basic health plan for most of the working population and their families which includes some medicines such as insulin and a few oral agents but no self-monitoring elements. Everyone, including the unemployed, has the legal right to benefit from this plan in some countries but the resources needed to make this possible are still far from adequate. Argentina has passed a law protecting people with diabetes but its enforcement has been slow and difficult for the same reasons.

In the Dominican Republic, IDF member associations in collaboration with the community have established the National Institute of Diabetes, Endocrinology and Nutrition (INDEN), the only diabetes hospital in Latin America, which provides excellent services for people with diabetes. It is also a training centre for multidisciplinary healthcare professions.

The Latin American Diabetes Association, ALAD, a scientific organization formed by health professionals, has developed evidence-based guidelines for the prevention and treatment of type 2 diabetes and its complications. The ALAD working groups on diabetes and pregnancy, GTDE, and on diabetes in children and adolescents, GELADNA, have also developed guidelines on the treatment of these specific problems.

National diabetes programmes

The interest in diabetes mellitus as a public health problem is increasing in the region. The prevention and treatment of non-communicable chronic diseases is now considered one of the main priorities in most countries where not long ago most of the resources went to the mother and child programmes. Some countries such as Argentina, Brazil, Chile, Colombia, Cuba, Costa Rica, Paraguay and Venezuela are implementing national diabetes programmes.

The impetus to implement national diabetes programmes was given a boost



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with the signing of the Declaration of the Americas on Diabetes (DOTA) in 1996, in San Juan, Puerto Rico (see Chapter 8).

Regional initiatives

The IDF SACA Region is the most representative organization, and the most structured at national and regional levels in Latin America in the field of diabetes, with participation by people with diabetes and their relatives, as well as healthcare professionals and industry partners. Different task forces have been appointed to meet particular regional needs, such as the Task Forces on Emergencies, Diabetes in Children, Education, Association Development and National Diabetes Programmes. Examples of the work of these task forces include the involvement of the Task Force on Emergencies in procuring aid during disaster situations in Venezuela, Colombia, Peru and El Salvador. A task force on anti-fraud in medications has dealt with unethical medication issues and has been successful recently in identifying a network from another region marketing and selling products as though they were in Latin America.

In addition, the Task Force on National Diabetes Programmes has developed a model diabetes law for Latin American countries that is being considered by several national assemblies or parliaments in the region.

Training courses for diabetes educators, with field testing courses in three model centres in Puerto Rico, Colombia and Argentina, have been organized by the Task Force on Education. Ongoing projects include national training courses for educators in Brazil, and possibly in Uruguay and Bolivia.

Reference

1. CIA. World Factbook 2002. Central Intelligence Agency, 2002.



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Introduction

The South-East Asian (SEA) Region includes only seven countries, but as with the USA numerically dominating the North America Region, so here does India, with its adult population comprising 85% of the region. Mauritius has the highest per capita GDP at US$10,800, while the other countries all have per capita GDPs of less than US$4,000, although India with a current annual growth of 5% is experiencing economic development at a faster pace than almost anywhere in the world except its neighbour, China.


Economic progress is inevitably associated with increasing urbanization, and it appears that features of urban life tend to increase the prevalence of diabetes among adults of Indian ethnic background to a greater extent than for other populations (1), which is why a 4:1 ratio for urban:rural prevalence was applied for the Indian, Nepalese and Bhutan populations (see Chapter 1).

The anticipated increase in diabetes prevalence for the region from 5.6% to 7.5% by 2025 is very much a consequence of the increasing life expectancy in India, where the proportion of the population over 50 years is expected to increase from 15% to 23% between 2003 and 2025, and the urban proportion from 30% to 42% (2). Evidence suggests that in more affluent parts of the country the rural prevalence is higher than less affluent rural areas (3), indicating that increasing economic growth will escalate diabetes prevalence in India even more than these possibly conservative estimates have suggested.

India currently has the world’s largest diabetic population with an estimated 35 million people. This is expected to more

than double to 73 million by 2025. The world’s highest regional IGT prevalence is further evidence of the likely marked increase in the diabetes prevalence.

Mauritius, the second smallest country in the region, highlights the extent to which persons of Indian ethnicity appear predisposed to diabetes, when exposed to more affluent economic circumstances. This island has the world’s eighth highest diabetes prevalence, currently 11% and expected to rise to 15% by 2025, and a similarly high IGT prevalence of 16%, likely to increase to nearly 18% (see Figures 7.11 and 7.12).

A substantial number of clinical and epidemiological studies on diabetes have been published by various centres in India and by the Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM). These centres have also developed basic research facilities on diabetes and related areas.

7.6 South-East Asia


Total population (millions) 1,251.4 1,629.7Adult population (millions) (20-79 years) 705.3 1,081.0Diabetes prevalence (%) (20-79 years) 5.6 7.5Diabetes numbers (millions) (20-79 years) 39.3 81.6IGT prevalence (%) (20-79 years) 13.2 13.5IGT numbers (millions) (20-79 years) 93.4 146.3

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Figure 7.11Prevalence estimates of diabetes – South-East Asian Region

Incidence of type 1 diabetesOnly two countries in the region have published rates for type 1 diabetes in childhood and therefore extrapolation of rates was necessary for the data in Chapter 2. The rate from China, although outside the region, was used for some extrapolations, but the rate for India was

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At a glancemore frequently used and it therefore plays a pivotal role in the estimates for this region.

The South-East Asian Region contributes more than any other to the worldwide childhood type 1 diabetes total. Diabetes-associated mortality and tropical or malnutrition diabetes are also likely to play important roles in this region, but unfortunately there is inadequate information to address these issues. These points reinforce the need for much more detailed data on childhood diabetes in this region.

Diabetes care

Increasing prevalence of diabetes and diabetes-related disorders and complications pose a serious threat to the healthcare delivery systems in the region. This region is expected to have the largest diabetic population in the world by 2025 with almost 82 million people. Unfortunately, diabetes is not yet considered a national problem with high priority in almost all the countries of the



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Figure 7.12Prevalence estimates of impaired glucose tolerance – South-East Asian Region

of trained manpower, non-availability of comprehensive care and absence of good tertiary care departments dedicated to diabetes. According to a World Bank report the public sector is still the main provider of healthcare services and is grossly under-funded.

Private sector careAs a result of the inadequate care in the public sector, a number of people with diabetes go to private practitioners and clinics for their care. In reality, there is a substantial contribution of public sector to this type of private sector. For example, almost all public sector physicians are engaged in private practice in chamber, clinic and private hospitals. With the exception of a few centres, no well-planned system of diabetes care, particularly in primary services, have been developed in this sector.

Education and awareness

Professional bodies, healthcare societies and associations, in general, play an appreciable role in creating awareness about diabetes, and its prevention and

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region, where only diabetes associations give focused attention to the disease. In general diabetes is treated as any other ordinary disease in national health policy. There is no demand analysis and separate budget for diabetes care and research. It is now important to integrate diabetes healthcare into national health policies and also into the curricula of undergraduate and postgraduate studies.

The existing system of diabetes healthcare may be broadly divided into two sectors: public and private. The relative contribution of the different sectors greatly varies from country to country and even locality to locality.

Public sector care Reasonable infrastructure has already been built for delivering a good level of services in the region. However, diabetes care is still inadequate in public facilities due to governmental priority to communicable diseases over non-communicable diseases. This situation is exacerbated by a lack of focused attention to diabetes, scarcity



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management through media. It is the national diabetes associations, however, which have played a significant role in diabetes healthcare in the region.

The Diabetic Association of India plays an important role in creating public awareness and also in training healthcare providers and professionals particularly through the All India Institute of Diabetes in Bombay (4). The Institute also provides diabetes healthcare to a substantial number of people with diabetes.

Bangladesh appears to have the most well organized diabetes association with countrywide coordination among branches and a dynamic system of comprehensive healthcare delivery for people with diabetes. It has become highly successful in creating diabetes awareness. It also has a programme of manpower development, community mobilization and generation of resources for self-sustenance.

A programme for diabetes education in the public sector is generally absent in this region. There are, however, educational activities run by the national diabetes associations. These activities include both training for healthcare providers as well as diabetes education for people with diabetes. Other educational activities include public awareness promotion, for example in India, through newsletters and journals (4).

The Diabetic Association of Bangladesh provides a more systematic series of programmes on diabetes education. Through its central institute, BIRDEM, it also runs postgraduate degrees and diplomas under the University of Dhaka. BIRDEM has been a World Health Organization collaborating centre since 1980.

References

1. Ramachandran A, Snehalatha C, Latha E, Manoharan M, Vijay V. Impacts of urbanisation on the lifestyle and on the prevalence of diabetes in native Asian Indian population. Diabetes Res Clin Pract 1999; 44:207-213.

2. United Nations. Department for Economic and Social Information - Population Division. World urbanization prospects: the 1994 revision. Estimates and projections of urban and rural populations and of urban agglomerations. United Nations, New York, 1995.

3. Kutty VR, Soman CR, Joseph A, Pisharody R, Vijayakumar K. Type 2 diabetes in southern Kerala: variation in prevalence among geographic divisions within a region. Natl Med J India 2000; 13:287-292.

4. Diabetic Association of India. 1999 Problem Census Report of India. Questionnaire proforma of IDF SEA Region for the mid-term regional meeting held on March 26, 1999.



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Introduction

The Western Pacific (WP) Region is a huge region in terms of both geography and population. The region extends from Mongolia and Japan in the north to New Zealand in the south. Apart from sheer size, the region is characterized by great diversity of lifestyle, affluence, economics, culture, social circumstances and geography.

The world’s most populous region contains 39 disparate countries and territories with populations ranging from 1.3 billion for China to less than 5,000 in the smallest Pacific island nations of Niue and Tokelau. Similarly the economic profile varies from per capita GDPs of about US$25,000 for Australia, Hong Kong, Japan and Singapore to less than US$2,000 in Cambodia and some of the smallest Pacific islands.

The less economically advanced countries of the region struggle with the double burden of managing infectious diseases

7.7 Western Pacific

as well as the diabetes epidemic, and the problem of limited resources and lack of government awareness of the seriousness of the diabetes threat to their populations.

The countries also have populations of diverse ethnicity, with Singapore having large Chinese, Malay and Indian communities, Australia and New Zealand being principally Caucasian but also having extremely culturally diverse populations, and the Pacific islands having Polynesian, Melanesian and Micronesian populations, as well as more recent Indian immigrant communities.


Not surprisingly there is a great diversity in the prevalence of diabetes in adults, with the world’s highest found in the Micronesian population of Nauru, and the ethnically mixed population of Singapore currently has the sixth highest documented prevalence (see Chapter 1).

However, simply because of its population size, it is in China that the diabetes epidemic has the greatest potential to explode. Although the current prevalence there of 2.7% is among the region’s lowest, the high prevalence among Chinese populations in the more urbanized and affluent cities of Hong Kong and Singapore indicate what may develop as China rapidly urbanizes and expands economically. The data indicated for 2025 are likely to represent an underestimate of the diabetes problem in China if it continues to develop economically faster than almost any other country in the world.

These numbers, while alarming in their own right, still do not tell the whole story. Although type 1 diabetes is relatively less common in the region, with the exception of Australia and New


Total population (millions) 2,110.7 2,445.7Adult population (millions) (20-79 years) 1,383.6 1,750.5Diabetes prevalence (%) (20-79 years) 3.1 4.3Diabetes numbers (millions) (20-79 years) 43.0 75.8IGT prevalence (%) (20-79 years) 5.7 6.9IGT numbers (millions) (20-79 years) 78.6 120.2

At a glance



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Figure 7.13Prevalence estimates of diabetes in selected countries – Western Pacific Region

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Zealand, than among countries with predominantly Caucasian populations, there is an emerging problem of type 2 diabetes in children and adolescents, particularly in an urbanized setting and in strong association with rising rates of obesity in children.

In Japan, for example, 80% of children with diabetes now have type 2 diabetes. In the adult population also, increasing numbers of young adults are developing the condition and the age group under greatest threat from the rising prevalence rates is the 40-59 year age group. This age group now comprises the largest group, about 45% in the diabetic

population. This trend towards a younger age of development of the disease has major health implications, particularly as it targets specifically the economically productive sector of the population.

Incidence of type 1 diabetesWith the exception of Australia and New Zealand, the rates of childhood type 1 diabetes in this region appear uniformly low. Despite its very low incidence, China accounts for almost half of the region’s total. However, the Western Pacific Region makes the smallest contribution of all to the world total of type 1 diabetes even though it has the largest childhood population (see Chapter 2).



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At a glance

Diabetes initiatives

Western Pacific Declaration on DiabetesThe working relationship between the IDF WP Region and the WHO Western Pacific Regional Office (WHO/WPRO) is of prime importance to the development of effective programmes and strategies within the region. This relationship continues to grow following the formation of the alliance with the Secretariat of the Pacific Community (SPC) that brought about the Western Pacific Declaration on Diabetes (WPDD), co-signed in 2000 by these three partner organizations (see Chapter 8).

A plan of action, to facilitate and guide implementation of the WPDD, has been endorsed by IDF member associations in the region, health ministers of the WHO/WPRO member countries and territories as well as those of the SPC.

The WPDD Plan of Action sets clear goals covering primary prevention, early diagnosis and care of the diagnosed, and building the capacity of health systems to provide equitable, accessible, affordable and effective prevention and care services to people with or at risk of diabetes.

The plan proposes objectives, strategies and expected outcomes for each goal and provides examples of activities which might be undertaken at a regional, national or local level to work towards achievement of the goals.

National diabetes programmes As would be expected from a region as large and diverse as this, standards of management and care show much variation, as do healthcare delivery systems. Standards of management and care vary from very high indeed in centres of excellence in the more developed and affluent nations to almost non-existent in impoverished or strife-torn nations.

The WPDD and its action plan recognize the need to address these discrepancies and provide a mechanism for countries to plan and put into place countermeasures. Further, steps are being taken now that the action plan has provided a structure within which work can be done.

The priority given to diabetes by governments also varies greatly, but increased cooperation within the WPDD structure has led to more governments identifying diabetes as a key health initiative and integrating such initiatives with their non-communicable diseases programmes. While the seriousness of the problems facing countries of the Western Pacific Region cannot be ignored, the enthusiastic adoption of the WPDD and the significance of the plan of action provide real hope that the region is moving to address this epidemic.

Examples of the influence of the WPDD include a range of different levels and types of activities. The WHO/WPRO is supporting the development of national action plans in individual countries and fostering the development of national diabetes guidelines throughout the region.



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The WPDD was also responsible for the Royal Australasian College of Surgeons adding a diabetes component to its Pacific Islands Project and many countries, such as Korea, are using the WPDD and its plan of action to lobby their governments for increased resources for diabetes and to create broad awareness of the disease as a public health threat.

EducationThe region has seen a continuation and expansion of education and awareness programmes utilizing mechanisms pioneered in the region. Of note was the workshop entitled ‘Implementation

of Diabetes Education Strategies for IDF WP Region and WPDD’. This workshop was outcome driven and charged representatives with the responsibility of returning to their country to develop and implement a new diabetes education strategy and provide a feedback report. This approach is in keeping with the philosophy of the WPDD Plan of Action.

The SPC, also in support of the WPDD, has developed and is implementing an introductory diabetes training manual for health workers in Pacific island countries in an effort to raise the quality of diabetes care provided at the community

Figure 7.14Prevalence estimates of impaired glucose tolerance in selected countries – Western Pacific Region

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level. This manual, entitled ‘Diabetes is Everybody’s Business’, promotes personal responsibility among community health workers for identifying people at risk of diabetes, gives basic risk factor advice, and provides improved routine care for people with diagnosed diabetes.

Practical targets and treatmentsThe Western Pacific Region is at the forefront of the diabetes epidemic, with the potential for devastating health consequences. The overwhelming evidence is, however, that optimal glycaemic control of type 2 diabetes can minimize risks and complications and that one of the ways to assist the achievement of good control is through the provision of treatment guidelines.

The third edition of the ‘Asia Pacific Type 2 Diabetes Practical Targets and Treatments’ was produced by the Asia Pacific Type 2 Diabetes Policy Group (1). The goal has been, since the first edition, to target the prevention and management of type 2 diabetes. The third edition deals with new medications and data on the prevention of type 2 diabetes and addresses the increasing incidence of type 2 in children and adolescents. It seeks not to be a substitute for national guidelines but to complement them and add the authority that can be provided by a regional approach. It also seeks to provide guidelines where there are none.

Tasks ahead

The region faces enormous difficulties and all indications are that this will worsen in the immediate future. The availability of epidemiological and other data continues to grow enhancing knowledge of the true situation in many countries in the region and with it the capacity to take effective action. These data continue to provide a basis for increased action in many parts of the region through a number of cooperative ventures. Together, the countries of the region are working to improve the

provision of diabetes services where three years ago no service was provided.

Major tasks on the work plan of the WPDD Steering Committee for the near future focus on taking stock of diabetes activities in the region, increasing the development and implementation of national diabetes programmes where they are not already in place, and promoting strategies aimed at wide implementation of recognized standards of diabetes care and prevention.

Many countries have made genuine and positive progress, assisted by IDF, WHO, SPC and WPDD initiatives in the development of disease management programmes and in the enhancement of diabetes awareness and education. Cultural barriers, for example in the use of non-healthcare professionals in diabetes care, are now being broken down.

Diabetes is now recognized as an issue of vital importance by many governmental and non-governmental agencies and cooperation within the region is increasing steadily. In addition, through the increasing influence of the WPDD, governments are taking greater interest in the need for investment in addressing the diabetes problem in their communities, and more governments are introducing diabetes programmes, often integrated with non-communicable disease programmes and frequently with the support and involvement of other governmental agencies from within the region. These issues provide a glimmer of hope in what otherwise appears as a desperate situation in many countries.

Reference

1. Asia Pacific Type 2 Diabetes Policy Group. Asia Pacific Type 2 Diabetes Practical Targets and Treatments. Third edition. International Diabetes Federation, Western Pacific Region, and World Health Organization, Western Pacific Regional Office, 2002.

Reducing the BurdenChapter 8


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Reducing the Burden Chapter 8

In facing the challenges brought about by the diabetes epidemic, diabetes

associations and regional organizations have galvanized into action. Declarations on diabetes, spelling out strategic actions, have been signed in five regions: Eastern Mediterranean and Middle East, Europe, North America together with South and Central America, and Western Pacific.

These declarations reflect the significance of strategic alliances with organizations such as the World Health Organization (WHO) at all levels, as well as with other stakeholders in healthcare including governments and industry.

While the declarations are couched in culturally appropriate terms and geared toward regional needs, the core of these initiatives are nonetheless similar. They seek to implement national diabetes programmes, empower people with diabetes, improve the quality of diabetes care, promote research and raise public awareness of a costly health problem.

8.1 St Vincent Declaration

8.2 Declaration of the Americas on Diabetes

8.3 Western Pacific Declaration on Diabetes

8.4 Declaration of the Eastern Mediterranean and Middle East Region



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Introduction

Diabetes is a major and growing chronic disease with a strong impact in terms of health and costs, both at individual and societal levels, as shown in the earlier chapters. In spite of medical progress, a large number of people with diabetes still suffer from the consequences of the disease as a result of low quality of care and social inequalities (1).

Several studies had shown a wide variation of care provided throughout Europe; moreover in some cases the quality of healthcare was far from set standards and recognized goals. This was mainly due to the poor use of available resources, related in the majority of cases to a lack of programmatic activities and clear healthcare policies.

Recognizing the wide variation in the standard of diabetes care, a meeting was convened in St Vincent, Italy, in 1989, to discuss how to implement better quality healthcare for people with diabetes (2). The meeting was organized under the auspices of the Regional Offices of IDF and the World Health Organization (WHO), and involved diabetes experts, representatives of governments and organizations of people with diabetes from a number of European countries.

The immediate outcome of the meeting was the St Vincent Declaration (SVD), a document identifying goals and targets for the improvement of the quality of life of people with diabetes.

Goals and targets

The SVD established two general goals for people with diabetes:

• Sustained improvement in health experiences and a life approaching

normal expectations in quality and quantity.

• Prevention and cure of diabetes and of its complications by intensifying research efforts.

A series of specific targets was also identified in order to reach these two goals, in particular to combat diabetic complications:

1 Reduce new blindness due to diabetes by one-third or more.

2 Reduce numbers of people entering end-stage diabetic renal failure by at least one-third.

3 Reduce by one-half the rate of limb amputations for diabetic gangrene.

4 Cut morbidity and mortality from coronary heart disease in people with diabetes by vigorous programmes of risk factor reduction.

5 Achieve pregnancy outcome in women with diabetes that approximates that of non-diabetic women.

Reducing diabetic complications

Since 1989, several actions have been undertaken at different levels throughoutEurope for the implementation of quality of care programmes according to SVD goals and targets. Some 51 governments have nominated liaison persons for formal relationships with the SVD movement, and 46 have created national diabetes task forces with the mission to develop and implement national and local diabetes programmes.

In 37 European countries, representing 72% of the total, a national diabetes programme has been designed and officially endorsed by national governments (3). It was clear from the beginning, however, that the major obstacle to the achievement

The first decade of the SVD has demonstrated

the feasibility and possibility of new

approaches to diabetes care and the importance

of focusing on the real outcomes of the

disease rather than on the processes. It has

also demonstrated that local solutions to local

problems need to be defined.

8.1 The St Vincent Declaration



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of the desired results was the lack of information about the real entity of the problem.

A questionnaire sent to national liaison persons indicated that data was available in 55% of the countries for blindness due to diabetes, 60% for end-stage renal disease leading to kidney transplantation and 50% for amputations above ankle (4). Some of the countries also produced various national data on the impact of the disease in terms of late complications (4).

Guidelines for better care

A number of SVD working groups were created with the remit to develop guidelines for better care. As a result of their activity, the St Vincent Declaration Action Programme, a plan for the practical implementation of the declaration, was developed (5).

The programme was accompanied by a series of guidelines for various aspects of diabetes care with particular attention to late complications, including a protocol for the screening of diabetic retinopathy, and guidelines for the prevention of renal failure, foot ulcers and amputations, and coronary artery disease.

These guidelines were subsequently updated in the SVD Action Programme Implementation Document (6). The need for an adaptation of the guidelines according to local circumstances was highly recommended.

RetinopathyThe protocol for the screening of diabetic retinopathy was approved by experts representing 30 diabetes and ophthalmic societies across Europe. The aim of the protocol was the definition of a reliable screening tool able to identify early lesions and the most appropriate use of resources in order to guarantee the same opportunities for access to eye examination for people with diabetes in Europe. A diabetic retinopathy screening

card was produced for data collection and a specific computer program, Save Eyes in Europe (SEE), was developed for the management of the screening protocol.

NephropathyThe guidelines for the prevention of renal failure were subdivided into indications for screening and indications for treatment. The section on screening provided guidance on the best procedures for the detection of microalbuminuria or persistent proteinuria. The second part provided clear guidelines for treatment of kidney disease according to the stage of progression.

AmputationThe guidelines for the prevention of foot ulcers and amputations provided suggestions for screening and diagnostic procedures, follow-up of people at risk and for care of overt lesions. Particular attention was given to the definition of the team of professionals involved in foot care and to the fundamental role of education in the prevention of the onset or the progression of lesions.

Cardiovascular disease The guidelines on cardiovascular disease (CVD) and stroke covered primary and secondary prevention. Particular attention was paid to the control of the risk factors for macrovascular disease and to the target levels for each risk factor.

Local initiatives

The SVD recommendations generated several initiatives for local implementation, some of which focused mainly on organizational and educational aspects, while others aimed more at clinical elements.

Eye complicationsThe SVD implementation in the Stockholm County initiative comprised both organizational and educational aspects in which an educational programme



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combined with a campaign for screening diabetic eye disease and evaluating a monitoring system for new blindness (7).

The educational programme was divided into two sections. The first aimed at increasing awareness and competence of healthcare professionals, people with diabetes, administrators and politicians, and highlighted the effectiveness of preventative measures. The second was a two-week continuous medical educational programme for professionals working in the primary healthcare centres.

The campaign for screening eye disease was conducted through a mobile photo-screening service, which contacted all diabetic patients from hospital inpatient registers, followed by an immediate referral to an ophthalmologist in cases of people at risk.

Data collection covered the period 1981–1995 while the screening was performed from 1990 to 1995 (8). Results showed progressive decrease of blindness incidence. The final reduction was equivalent to around one-third with respect to the basal level, indicating the achievement of the SVD target for diabetic retinopathy.

A prerequisite for planning effective treatment strategies is the availability of facilities. A study was conducted in the UK in 1991 to determine which treatment facilities were available and how treatment was provided (9). Responses, from a questionnaire to all ophthalmologists in England and Wales, showed that screening facilities were inadequate for a large number of people and that there was a wide variation in care provided, especially in waiting times for first visit and treatment in different centres.

A similar study was repeated in 1996 to evaluate the possible changes (10); the data confirmed a wide variation of care provided for screening, from 25% of cases

in some centres to 90% in others. These results showed that the first step in the reduction of complication should be a coordinated effort both for screening and treatment.

A more recent survey was carried out in Germany with data on new cases of blindness collected from 1990 to 1998 (11). The study showed a reduction in the incidence rate of 3% for each year of observation. All these results showed that screening is an effective measure for reducing eye complications in accordance with the SVD specific guidelines.

Kidney complicationsThe PROSIT Project (Proteinuria Screening and Intervention Project) was launched in Germany as part of the national implementation of the SVD (12). The project focused on identification procedures for facilitating the screening of diabetic nephropathy.

One of the major achievements of the project was the validation of self-testing for microalbuminuria. The study showed that the available self-test methods could be effectively used for screening. The combination of the effectiveness of the test and the low price of equipment created the conditions for widespread screening for diabetic nephropathy. Further, the need for action was highlighted in a preliminary study within the same project which showed that only a minority of people with diabetes was screened annually for diabetic nephropathy in Germany.

A recent study was conducted in 20 European countries to evaluate the compliance to guidelines for first referral to nephrologists (13). It was found that only 30% of type 1 and 22% of type 2 diabetic patients had first referral according to the guidelines. Moreover 50% of those who were placed in replacement therapy had the first referral within three months prior to replacement. The results highlighted



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the low standardization of care and the negative impact on outcomes.

AmputationsThe Danish Amputation Register Study Group analysed the incidence of major lower limb amputations from 1982 to 1993 (14). In total, 2,848 cases were studied: a progressive reduction of incidence, with a total of 40% reduction occurred by 1993.

Amongst the activities carried out within the regional diabetes project in Umbria, Italy, a survey on diabetes-related amputations highlighted that 1,283 non-traumatic amputations were performed in that region from 1991 to 1998. No significant changes were observed in the overall incidence rate during the observational period; however, the ratio between major amputations (above the ankle) and minor amputations (below the ankle) was significantly reduced (15).

Evaluating the SVD impact

A report, based on information provided by SVD national liaison persons and published data, found that the following results had been achieved (4):

• reduction of blindness in three countries;

• reduction of cardiovascular disease and end-stage renal disease in three countries;

• reduction in major amputations in six countries;

• reduction in hospitalization due to late complications of diabetes in five countries; and

• reduction in healthcare expenditure related to diabetes in two countries.

However, one of the major issues in SVD-related projects is the difficulty of scientifically documenting the evidence of the outcomes due to the intrinsic characteristics of such activities, which means that the results are usually

produced as reports from healthcare implementation initiatives. At the same time, methodologies adopted for scientific protocols, eg randomized and control group comparison, are not appropriate for evaluating the effectiveness of the action programmes.

Moreover, the factors that influence the outcome are not always identifiable, and unpredictable environmental variations might intervene in long-term, large-scale initiatives, such as political changes, variability of available resources, prevailing educational and cultural standards, and conflicts. This has been particularly true in Europe in the last decade.

Other factors that make difficult the documentation of the outcomes are the lack of precise and well-defined healthcare plans of action that have in their stead healthcare policies which produce scattered initiatives, and the difficulty in coordinating multidisciplinary initiatives. Moreover it is difficult to define the role of the SVD movement in ongoing activities that might or might not have taken advantage of the SVD climate.

A further element of difficulty is represented by the absence of baseline data collected according to appropriate epidemiological procedures in areas where the interventions have been carried out. Data collected in the quality development process have frequently been used for providing the evidence that should have been produced according to accepted epidemiological analysis. However, the information required for quality development is gathered according to procedures designed for satisfying that specific process and not for epidemiological purposes.



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Platform for further development

The major achievements of the SVD (16) may be summarized as:

• the consolidated awareness of the need for and the feasibility of broad partnership;

• the promotion of appropriate approaches for the planning of interventions;

• the identification and implementation of specific methodologies for quality development; and

• the need to define and apply correct methods for producing evidence.

In many European countries SVD-related initiatives produced national programmes for diabetes adopted by governments, the impact of which, however, is extremely difficult to quantify owing to the complexity and variability of the different environments.

The promotion of defined and structured methodologies for the development of quality of care has been a major focus of the SVD movement. Benchmarking and external comparison, and quality circles are well-known procedures, whose applicability in diabetes care has been demonstrated in many initiatives. For example, within the DiabCare project, indicators for diabetes care have been identified mostly in terms of outcomes and processes (17).

Instruments for data collection have been produced, such as the Basic Information Sheet, and various systems for data transmission such as the DiabCare programme and DiabCare Fax solution within the DiabCare Quality Network (Qnet). In some countries, for example France (18), Germany (19), the Netherlands (20), Italy (21) and Spain (22), broad initiatives have proven the feasibility and effectiveness of large-scale data collection and benchmarking for the improvement of quality of diabetes care.

The development and implementation of diabetes registries has been a step taken to reconcile evidence-based studies and quality care benchmarking. Once in place the registries will provide reliable population-based epidemiological data that are continuously updated, allowing monitoring of the diabetes problem.

The platform produced by the quality care networks and installed for the registries supports the implementation of standards of care and facilitates a widespread adoption of shared care. A number of projects are flourishing in Europe, where advanced projects have been developed in countries such as the United Kingdom, Denmark, France, Germany, Italy, the Netherlands, Finland and Greece (23).

While the technological aspects no longer represent a critical issue, the most challenging topics are the regulatory ones, such as the ownership of data, confidentiality, access rights, etc, and also the human, cultural and environmental barriers that need to be surmounted and that are currently responsible for the difficulties in realizing large-scale projects (24).

Conclusion

The first decade of the SVD has demonstrated the feasibility and possibility of new approaches to diabetes care and the importance of focusing on the real outcomes of the disease rather than on the processes. It has also demonstrated that local solutions to local problems need to be defined.

The experience gained has also shown that available knowledge is poorly applied, and this problem is not just found in the less advanced countries. The awareness of such widely accepted findings is creating the conditions for concrete initiatives aimed at large-scale prevention of end-stage diabetes complications.



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However, given the nature and time scale for the development of diabetic complications such as eye disease, kidney disease and CVD, the real benefit of the SVD movement will require a greater length of time to be evident.

It is not inappropriate to claim that, in many countries worldwide, the effect of national action plans for diabetes produced a change in attitude in healthcare professionals, people with diabetes and other stakeholders. This change is likely to reduce successfully the burden of diabetes by decreasing the prevalence of blindness, end-stage renal failure, stroke and myocardial infarction in the years to come, which would not have been the case without the SVD movement.

Adapted from ‘The St Vincent Declaration: experience

gained for better outcome of cardiovascular, eye

and kidney complications in the future’ by M Massi

Benedetti, J Akwe Akwi, P Ferolla, MO Federici. In

Diabetes: From Research to Diagnosis and Treatment,

ed. Itamar R, Skyler J, Eleazar S. London: Martin

Dunitz, 2003.



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References

1. World Health Organization (Europe) and International Diabetes Federation (Europe). The action programme for the implementation of the St Vincent Declaration for the improvement of diabetes healthcare. Jointly organized by WHO Europe and IDF Europe. World Health Organization, ICT/CLR 055, 23 Oct 1990 (8438r).

2. World Health Organization (Europe) and International Diabetes Federation (Europe). Diabetes care and research in Europe: the St Vincent Declaration. Diabet Med 1990; 7:360.

3. Background to St Vincent. The SVD Newsletter issue 1998; 13 Summer:4.

4. Bergrem H, Kalo I, Staehr Johansen K. The St Vincent Declaration - Monitoring the St Vincent Declaration activities. The SVD Newsletter 10th Anniversary Issue 1999; 14 Autumn:8.

5. Krans HMJ, Porta M, Keen H, Staehr Johansen K. Diabetes care research in Europe: St Vincent Declaration action programme. WHO Office, Copenhagen, 1995; EUR/ICT/CLR 055/3.

6. Krans HMJ, Porta M, Keen H, Staehr Johansen K. Diabetes care research in Europe: St Vincent Declaration action programme. Implementation document. Giornale Italiano di Diabetologia 1995; 15:1.

7. Rosenqvist U. Implementation of the St Vincent Declaration in Stockholm county, Sweden. Giornale Italiano di Diabetologia 1993; 13 Suppl:75–76.

8. Backlund LB, Algvere PV, Rosenqvist U. New blindness in diabetes reduced by more than one-third in Stockholm County. Diabet Med 1997; Sep 14:732–740.

9. Kohner EM, Lavin M, Hamilton AM. The management of diabetic retinopathy. Giornale Italiano di Diabetologia 1993; 13 Suppl:77–79.

10. Bagga P, Verma D, Walton C, et al. Survey of diabetic retinopathy screening services in England and Wales. Diabet Med 1998; 15:780–782.

11. Tautner C, Haastert B, Giani G, Berger M. Incidence of blindness in southern Germany between 1990 and 1998. Diabetologia 2001; 44:147–150.

12. Piehlmeier W, Renner R, Kimmerling T, et al. Evaluation of the Micral-Test S, a qualitative immunologic patient self-test for microalbuminuria: the PROSIT project. Proteinuria Screening and Intervention. Diabet Med 1998; 15:883–885.

13. Bergrem H. Quality of care for persons with diabetic nephropathy: Timeliness of first referral to nephrologist. Diabetes Nutr Metab 2002; 15:109–115.

14. Ebskov B, Ebskov L. Major lower limb amputation in diabetic patients: development during 1982 to 1993. Diabetologia 1996; 39:1607–1610.

15. Scionti L, Massi Benedetti M, on behalf of the Cooperative Study Group of the ‘Progetto Umbria Diabete’. A 8-year population-based survey of non-traumatic lower extremity amputations in diabetic and non-diabetic patients in an Italian region. Diabetes 2001; 50 Suppl 2:A228.

16. Bergrem H, Kalo I, Staehr Johansen K. The St Vincent Declaration - The main achievements. The SVD Newsletter 10th Anniversary Issue 1999; 14 Autumn:8.

17. Piewernetz K, Home PD, Snorgaard O, et al. Monitoring the targets of the St Vincent Declaration and the implementation of quality management in diabetes care: the DiabCare Initiative. Diabet Med 1993; 10:371–377.

18. Attali J, Klinebreil L. The support of young students in the implementation of DiabCare QNet and the St Vincent declaration. The St Vincent Declaration Newsletter 1995; Suppl 1:27–28.

19. Selbmann HK, Pietsch-Breitfeld B. DiabCare QNet activities Germany. The St Vincent Declaration Newsletter 1995; Suppl 1:28–29.

20. DiabCare Q-Net NL. St Vincent goals into practice. Diabetes Nutr Metab 1997; 10 Suppl 1:59.

21. Massi Benedetti M, Norgiolini R, Capani F, et al. The DiabCare Quality Network as an instrument for quality development in diabetes. Diabetes Nutr Metab 1997; 10 Suppl:68.

22. Brugues E, Bosch F, Corcoy R, et al. Benefits of the combined operation of DiabCare Q-Net and Diabcard system: ‘the Spanish experience’. Diabetes Nutr Metab 1997; 10 Suppl 1:64.

23. Diabetes ‘Registers’ Into the Millennium, 7th Workshop of the DOIT EASD Study Group Gubbio, (PG-Italy), 12–14th May 2000. www.doit-easd.org/en/meetings.

24. Vaughan NJA. Confidentiality and diabetes registers. Diabetes Nutr Metab 2001; 14:114–117.



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Box 8.1

Preamble

A specially convened meeting, Diabetes in Asia, was held in Colombo, Sri Lanka in 2002 for the express purpose of arriving at an aetiological consensus on type 2 diabetes mellitus and the

development of a primary prevention strategy. This meeting was hosted by the Diabetes Association of Sri Lanka and attended by over 350 opinion leaders representing 30 countries worldwide.At the conclusion of the deliberations a consensus was reached on the aetiology and primary prevention of type 2 diabetes, which was submitted for information and possible action by IDF and WHO.

Consensus DocumentA consensus was reached on the ‘Aetiology and Prevention of Type 2 Diabetes Mellitus’ at the Diabetes in Asia 2002 meeting held on 6-7 July 2002 in Colombo, Sri Lanka.

Proposition• Current increase in the prevalence of type 2

diabetes mellitus worldwide accepted with Level ‘A’ evidence*

• Increased incidence of type 2 diabetes mellitus in childhood and adolescence accepted with Level ‘A’ evidence

GeneticsGenetics is recognized as playing an important role in the aetiopathogenesis of diabetes. Monogenic forms have been identified. Susceptibility genes have also been identified in the common forms of type 2 diabetes mellitus. Genetic studies have contributed to the discovery of new pathogenic mechanisms.

Accepted as a significant aetiological factor – Level ‘A’ evidence.Further studies need to be pursued.Genetic counseling not recommended at present.

Foetal originsEpidemiological studies have reported a higher incidence of type 2 diabetes mellitus in subjects with a low birth weight. The hypothesis that nutrition of the mother can profoundly affect the metabolic outcome of the offspring has been confirmed by elegant mechanistic animal studies.

Low birth weight accepted as a significant aetiological factor – Level ‘A’ evidence.• Poor nourishment of the foetus increases risk

of metabolic syndrome and type 2 diabetes mellitus and postnatal over-nutrition may aggravate the syndrome.

• Animal studies are confirmatory. Further clinical research in human beings recommended.

LifestyleThere is a global epidemic of obesity affecting all ages. Obesity is associated with insulin resistance. There is a strong association between Obesity, Diabetes, Impaired Glucose Tolerance (IGT) and

Consensus on the aetiology of type 2 diabetes mellitus

* Level ‘A’ evidence – indicates full acceptance* Level ‘B’ evidence – partial acceptance with more evidence

needed.

Cardiovascular Disease (CVD). Physical inactivity is independently associated with increased insulin resistance. Lifestyle changes in subjects with IGT decreases progression to diabetes.

Accepted as a significant aetiological factor – Level ‘A’ evidence.

StressCompelling animal evidence and mechanistic studies suggest a relationship between Stress and Insulin Resistance with predisposition to Type 2 Diabetes Mellitus.

Accepted as an aetiological factor– Level ‘B’ evidence*.• Further evaluation recommended

Primary preventionAll of the above are likely to underline the urgent need for the primary prevention of type 2 diabetes mellitus and facilitate the introduction of programmes, which must be tailored to local circumstances in order to be effective. These should include lifestyle changes in all those at risk.

Concerted actions, by governments and non-governmental organizations, should be directed to the following:• Increasing awareness• Promotion of education at all levels• Multi-sectoral advocacy



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Introduction

The Declaration of the Americas on Diabetes (DOTA) movement began with a consensus development conference in 1996 when the Declaration was drafted. The Declaration recognized diabetes as a pandemic and called for strategic action in diabetes education, awareness and advocacy, quality of care, national diabetes programme development, epidemiology and organizational alliances. A resolution was then passed by the Pan American Health Organization Directing Council recognizing the Declaration as a guide to national programme development.

The founding organizations were the North American (NA) and South and Central American (SACA) Regions of IDF, the Pan American Health Organization (PAHO), and industry partners.

DOTA has expanded its partnerships to include other diabetes-related organizations in the Americas such as the Latin American Diabetes Association (ALAD), the Diabetes Association of the Caribbean, the International Society for Pediatric and Adolescent Diabetes, the National Diabetes Education Program (US), and the American Association for Diabetes Educators. Future targets include expanding partnerships to support projects at the country level.

Priorities

The DOTA coalition has prioritized the following core areas in its strategic plan:

• diabetes education;• epidemiology (quality of care systems

and surveillance);• children and adolescents and diabetes;• national programme development; and• awareness.

Diabetes educationA standardized programme on diabetes education to train diabetes educators was developed and initially carried out at three centres in Argentina, Colombia and Puerto Rico. An overall diabetes education strategy in DOTA’s strategic plan addresses the need for more diabetes educators in Latin America.

At the same time, the DOTA coalition has developed a set of educational standards for diabetes programmes for people with diabetes in Latin America and the Caribbean. These were based on standards already established by the American Diabetes Association (ADA), the American Association for Diabetes Educators and the IDF Diabetes Education Consultative Section (DECS).

A Caribbean Diabetes Education course, supported by DOTA, was organized in Barbados by the IDF North American Region in association with the Diabetes Association of Barbados (see Box 6.3 in Chapter 6). In addition to utilizing the DOTA standardized model programme and the DECS model, the course incorporated a successful mentor system.

A DOTA-PAHO regional workshop, Building Blocks in Diabetes Education, brought together representatives from 24 countries across the Americas in the Dominican Republic. The aim of the workshop was to develop a building blocks model for educational activities based on three scenarios detailing national capacity levels. During the workshop, the scenarios and educational activities to fit each scenario were identified.

8.2 Declaration of the Americas on Diabetes

Diabetes mellitus is a growing pandemic.

In 1996, an estimated 30 million people with

diabetes live in the Americas, more than a quarter of the world’s

total case load. By the year 2010 the Americas case load is expected to increase to 45 million,

taking into account demographic ageing of populations and

trends in underlying risk factors which are related to the process of modernization that is taking place in all developing countries.

Declaration of the Americas on Diabetes



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Quality of careA three-year programme on data collection and assessment, Qualidiab, has also been started to measure and evaluate quality of care in six countries - Argentina, Brazil, Chile, Colombia, Paraguay and Uruguay. The initial results from Qualidiab indicate that there is a need for better quality of care.

A Caribbean pilot on assessment of quality of care is also underway. The pilot currently includes Jamaica and St Lucia, and potentially will include the Bahamas and Trinidad and Tobago.

Association developmentDevelopment and leadership courses, organized by IDF and PAHO, have been carried out to strengthen diabetes associations. This is regarded as an important step in creating the structures and cooperation necessary to establish national diabetes programmes and to expand DOTA through multi-sectoral collaborations. A DOTA strategic planning workshop carried out by PAHO in Bolivia has supported the efforts on diabetes and has led to the establishment of a national diabetes programme.

Public awarenessDOTA has also facilitated the development of a model public awareness plan and has encouraged the development of local awareness campaigns. A strategic plan on awareness was formulated at a strategic planning workshop, which took place in Trinidad and Tobago. The workshop was supported by DOTA and organized by the IDF North American Region in association with the Diabetes Association of Trinidad and Tobago (DATT). The strategic plan is currently being implemented by DATT.

For more information on DOTA and its initiatives, please visit www.dota.org.



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8.3 Western Pacific Declaration on Diabetes

Introduction

The Western Pacific Declaration on Diabetes (WPDD) was introduced in recognition of the massive diabetes problem in the Western Pacific Region, with current estimates of at least 43 million affected individuals, together with the clear need for a concerted and collaborative approach to tackle the problem and to stem predicted future rises.

The WPDD, launched in 2000, is an alliance between three partner organizations in the region: the IDF Western Pacific Region, the Secretariat of the Pacific Community (SPC) and the World Health Organization Western Pacific Regional Office (WHO/WPRO).

The different strengths, approaches and overlapping profiles of these three partner organizations are being utilized within the WPDD to maximize and strengthen the resources required for the fight against diabetes. For example WHO works through governments whereas IDF works through its member associations. The SPC also works through governments of member countries, the Pacific islands, and has a particular interest in nutrition and lifestyle.

The potential for synergy is clear. Thus the agreement of the three partners to the proposals made in the Declaration can, by both separate and combined endeavour, allow more effective action to combat the region’s problems.

Main goals

The Declaration consists of an eight-point statement supported by a background explanatory document. There is also a comprehensive, detailed five-year plan of action, 2001 to 2005, organized within the framework of three main goals:

• Goal 1: Primary prevention of diabetes• Goal 2: Secondary prevention

(detection and management of diabetes and prevention of diabetes complications)

• Goal 3: Organization of healthcare systems.

Endorsement by partners

Since the launch of the WPDD in Malaysia, the Declaration and its plan of action has been endorsed and taken into policy by all three partner organizations. These endorsements are essential to empower the WPDD to develop its important role of advocacy on behalf of the cause of diabetes in the region.

Endorsement at the Regional Committee Meeting of WHO/WPRO took place in the Philippines in the same year the WPDD was launched. This endorsement by governments was unanimous and led to a resolution urging the WHO Regional Director to promote activities supporting the Declaration. This was followed by further endorsement at a meeting of the Pacific Island Country Health Ministers held in Papua New Guinea the following year. The WPDD is also fully endorsed by the IDF Western Pacific Regional Council as well as by the IDF Executive Board.

A corporate partner and supporters group has also been formed within the structure of the WPDD and has made seeding financial donations to assist with the development of the Declaration and the implementation of the plan of action.

Initiatives

A number of activities have already been initiated in support of all three goals of the WPDD. Numerous individual programmes have been initiated in areas in support of diabetes prevention (Goal 1). These have been initiated,

A point of particular importance in the

Western Pacific Region is that the largest

rise in the number of people with diabetes is

likely to occur in the economically-productive

age groups. The huge cost of diabetes

care and the loss of productivity due to

illness will impose a heavy burden on many developing countries in

the future.

Western Pacific Declaration on Diabetes



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delegates from developing countries. The WHO/WPRO and SPC made additional funding available to allow some of these delegates to attend the Third World Congress on Diabetes Prevention in Hong Kong.

3 The WHO/WPRO and SPC also made funds available, under the auspices of the WPDD, to allow delegates from Mongolia, Philippines, Vietnam, Tonga and Fiji to attend the Third World Congress on Diabetes Prevention and to contribute by making presentations at a one-day workshop held by the WPDD during the congress.

4 Other activities included support for a train-the-trainer course for diabetes educators in Singapore, and funds for translation of an information leaflet into Chinese for distribution at the IDF Western Pacific Regional Congress in Beijing. An exhibition was mounted to promote the aims and goals of the WPDD at this congress.

For further information about the WPDD and its activities, and to obtain copies of the various documents including the Declaration Statement and Background Document, and Plan of Action, please visit www.wpdd.org.

promoted or supervised by WHO/WPRO. Examples include programmes within Vietnam, China, Mongolia, Philippines and several Pacific island countries.

A document written from a regional perspective, ‘Type 2 Diabetes: Practical Targets and Treatments’, has been endorsed as being consistent with the goal of secondary prevention (Goal 2). This is a simple reference guide for front-line workers caring for people with diabetes in the region.

The development of IDF member associations is an example of an activity related to the organization of healthcare systems (Goal 3). New associations in Cambodia, Samoa and Vietnam indicate the success of this.

A number of projects have also been supported financially by the WPDD. Examples include:

1 The Second Asia-Pacific Diabetes Epidemiology Training Course held at the Chinese University of Hong Kong. The course received funding support from WPDD as well as the National Institutes of Health, USA, the Hong Kong Foundation for Research and Development in Diabetes, and further support from Japan and Korea. Students from 15 countries and areas attended the course - Australia, Cambodia, China, Hawaii, Hong Kong, Indonesia, Japan, Korea, Malaysia, Mongolia, Philippines, Taiwan, Thailand, Tonga and Vietnam. Several of the students are already engaged in major activities in their own countries eg Vietnam, Cambodia and Mongolia.

2 The IDF Western Pacific Region together with the IDF Diabetes Education Consultative Section (DECS) held a leadership workshop in Hong Kong. Funding was made available to support the activities of the workshop and, in particular, to assist



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8.4 Declaration of the Eastern Mediterraneanand Middle East Region

Introduction

The Declaration of the Eastern Mediterranean and Middle East (EMME) Region was adopted in 2001 by IDF member associations in recognition of the increasing prevalence of diabetes in their region, the emergence of diabetes complications as a cause of early morbidity and mortality, and the enormous and mounting burden on healthcare.

The declaration seeks to establish diabetes as priority health concern and recognize it as a serious, common health

problem with great human and economic burdens. It called for action in the following core areas:• National diabetes strategies• Prevention of diabetes and its

complications• Diabetes education• Research• Collaboration with stakeholders• Discrimination

National diabetes strategiesThe declaration called for the development of national diabetes strategies with clear objectives, process indicators and outcome measures,

The EMME Declaration seeks to establish

diabetes as priority health concern and

recognize it as a serious, common health

problem with great human and economic

burdens.

Profile: Zehra Naeemullah

“I had no knowledge of diabetes, because no one in my or my husband’s family, or any of our close friends had diabetes,” says 60 year-old Zehra Naeemullah from Pakistan. “My first contact with this condition was when my youngest daughter got married and we learned that her father-in-law and his sister had diabetes. I was perturbed as now this disease would come into our family never contemplating that very soon I too would be affected.”

Zehra, a housewife and mother of three grown-up daughters, was diagnosed with type 2 diabetes about two years ago when she went to the doctor because the frequency of urination was combined with an urgency that became very intense and intolerable. The random blood sugar report of 450mg/dl was a complete surprise and she could not believe it to be true. “I just could not imagine at first that the diagnosis was correct and told my doctor that no one in our family has diabetes, so how can I have it?”

She now firmly believes that the media can and should play a central role in increasing knowledge about diabetes. “A lot still needs to be done to raise awareness about diabetes,” she points out. “The doctors dealing with it should write more articles in newspapers and

give talks on television. If everyone with diabetes knows more about their condition, they could take better care of themselves without any difficulty.” She adds: “Even if one does not have diabetes one should know what diabetes is as anyone may get it any time just the way it happened to me.”



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which would lead to the creation and implementation of national diabetes programmes according to national health priorities. It also recognized the role of national organizations in the creation and implementation of national diabetes programmes and thus the need to develop these organizations in order for them to participate in the process.

In addition, the declaration emphasized the need to develop and implement a unique and comprehensive healthcare model, involving people with diabetes and healthcare professionals, that could be integrated with related non-communicable disease programmes and the primary healthcare system. Such a model should ensure universal access to quality care, training, and essential

medications and supplies, especially insulin. A common information system for diabetes to enable health services to monitor and control the quality of healthcare was also crucial.

Prevention of diabetesand its complicationsSeveral courses of action were identified to meet the goals of the declaration including raising public awareness by all possible means of the growing problems of diabetes and its complications.

The declaration also called for the allocation of adequate, appropriate and sustainable resources to prevent diabetes where possible, and to make effective and efficient use of these resources for

Not long after diagnosis, Zehra had a frightening experience when she had a hypo [too low level of glucose in the blood] and had to be rushed to hospital. It made her realize the importance of having more knowledge about her condition. Her doctor, besides introducing her to self-monitoring, advised her to attend the education sessions organized under a diabetes care programme. She attended a series of lectures where she learned the basics of diabetes including the need for good blood sugar control, the complications of uncontrolled diabetes, the importance of exercise in controlling weight and blood sugar, and the need for regular follow-up. Says Zehra: “I think one does not need to know everything about the disease like doctors, but people with diabetes should have enough knowledge to be able to take care of themselves.”

Receiving education and learning self-monitoring has changed Zehra’s life. She is now in good control, regularly performing blood glucose monitoring at home and feeling much healthier. Although she still gets a hypo once in awhile but with her glucometer within reach she feels much more confident in dealing with it. She has also made it a routine to take regular exercise and go for a daily walk for an hour in the late afternoon.

Zehra believes that if one works sufficiently hard one can achieve anything in life. She married at 16 when she had just completed her matriculation. She resumed her education along with the responsibilities of married life and three children. She finally graduated with a master’s degree (MA) in economics at the age of 30. Zehra is now ready to fulfill another of her dreams and that is to open a day-care centre for working mothers so that they can pursue their careers without any hindrance.



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the development of a regional plan and activities.

The declaration emphasized the need to improve the detection and control of diabetes and impaired glucose tolerance (IGT), and reduce the onset of diabetic complications with special focus on gestational diabetes mellitus, and diabetes in the elderly and children.

Diabetes educationDiabetes education for people with diabetes and healthcare professionals was another key area in the declaration. The declaration identified the promotion of health education for people with diabetes, health professionals and the public in the prevention and management of diabetes, and the setting up of standards and norms for education. It also called for the establishment of centres of excellence in diabetes education and research.

Diabetes education was also crucial to encouraging self-care for people with diabetes in order for them acquire knowledge and skills necessary for effective self-management of the disease.

ResearchFurther, the declaration sought to encourage and promote research to allow for new knowledge, effective prevention and better healthcare and management as well as to collect epidemiological data through registry and screening.

Collaboration with stakeholdersThe declaration also recognized the importance of collaboration internationally as well as among the major stakeholders involved in diabetes healthcare.

DiscriminationDiscrimination against people with diabetes was another issue the declaration addressed and called for action for its removal.

Diabetes Associations: from Patients to PartnersChapter 9


283

Diabetes Associations:

from Patients to Partners

Chapter 9

Diabetes associations play a crucial role in improving the quality of life

of people with diabetes. It is not only in their position as advocate that diabetes associations have taken on a much more proactive role in enhancing the lives of people with diabetes. An example can be found in the provision of diabetes education, a cornerstone of diabetes management, by associations from all over the world. The results of the survey on diabetes associations around the world undertaken by the International Diabetes Federation (IDF) show a dynamic process at work.

The number of diabetes associations continues to grow worldwide as seen in the rise of membership in IDF. The number of people with diabetes that IDF member associations represent is well over two million. The growth in diabetes associations in the last 20 years possibly reflects the mounting numbers of people with diabetes as well as the gradual

International Diabetes Federation

Number of member associations: 183

Number of member countries: 142

Number of people with diabetes represented: 2.7 million

At a glance



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empowerment of those affected by the disease over the years.

It is significant to note that the majority of associations, which responded to the survey, have both people with diabetes and healthcare professionals in their membership. This could be due to the breakdown of traditional barriers between healthcare professionals and their patients as well as a reflection of a more collaborative approach to diabetes care and management.

It would also seem that a new role has emerged for diabetes associations. Whereas previously, diabetes associations worked primarily on behalf of their members, more than 70% of those which responded indicated that they now engaged in activities for the primary prevention of type 2 diabetes.

While diabetes associations vary in size and influence, they nonetheless reflect the changing role of people with diabetes from being patients to being partners in the healthcare process.

ResultsThis was the second survey undertaken by IDF on diabetes associations. The survey questionnaire was sent to all IDF member associations but was also made available to non-members. The Federation received 92 questionnaires which represented a response rate of approximately 50%.

The first survey conducted in 1999 resulted in a 72.5% response rate. As a result, there is no attempt to make any comparisons between the two surveys in this chapter as this could lead to misinterpretations.

However, the number of responses was sufficient to give a good representation of the structure, organization and activities of diabetes associations around the world.

IDF membershipSince its inception in 1950, IDF has grown from 16 member associations in 15 countries to 183 member associations in 142 countries in 2003.

Figure 9.1IDF membership growth, 1950 – 2003

Stop discrimination, defend the rights and

enhance the lives of people with diabetes

Mission statement,Georgian Diabetes

Federation

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The increase has been very steady in the last twenty five years, as shown in Figure 9.1. This trend reflects the increasing number of people with diabetes as well as the need for people with diabetes, and their families, to play an active role in their care and management of the disease.

GoalsThe primary objective of most diabetes associations could be summarized as follows: to improve the quality of life of people with diabetes and their families.

To achieve this important mission, the efforts of the associations have focused on:

• improving quality care and services;• promoting education of both

people with diabetes and healthcare professionals;

• promoting self-management and empowerment;

• encouraging prevention and early diagnosis of diabetes;

• raising awareness on diabetes and its complications;

• providing assistance and protection, and defending the rights of people with diabetes;

• establishing national diabetes programmes; and

• influencing healthcare policies.

Organizational structureThe results of the survey indicated that 88% of the respondents were national associations while 8% were national federations, as shown in Figure 9.2. Some 4% declared a different structure, such as scientific societies, foundations, etc.

Some 84% of the associations charged a membership fee while 38% offered free membership to people with diabetes.

Most diabetes associations have elected bodies governed by a constitution. Some 92% of the respondents indicated that they have a constitution and by-laws

Figure 9.2Organizational structure of diabetes associations

Figure 9.3Governing bodies and strategies

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while about 86% have elected bodies. In terms of strategy, close to 79% have a mission statement and 70% produce an action plan, as indicated in Figure 9.3.

Type of membershipDiabetes associations with a mixed membership, ie both people with diabetes and healthcare providers, represented 43% of the respondents. Some 33% of the respondents were associations representing only people with diabetes and their families while 15% were organizations for healthcare professionals only, as shown in Figure 9.4. Healthcare centres make up 7% of the organizations which responded to the survey.



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Figure 9.5Size of diabetes associations

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Profile: Dijana Lukoseviciene

It came as a surprise to Dijana Lukoseviciene, 50, and to those who knew her, when she was diagnosed with type 2 diabetes. Dijana was energetic and active, and enjoyed gardening in

the spring and going to the opera in the winter. She found out very quickly after her recent diagnosis that diabetes is not just a disease but a way of life. “The truth of this came to me on the first day home from the hospital,” she says. “A few times a day for the rest of my life I will have to control the level of blood glucose, observe a special diet, inject insulin before any substantial meal. What it means is that I will never have a chance to forget the disease, I will have to live in constant tension to a certain degree.”

Dijana, who works for the Vilnius municipality in Lithuania, also realized that she had to take responsibility to learn more about the disease in order to manage her diabetes in the best possible way. “Unfortunately the hospital personnel hardly helped in finding my way through the labyrinth of this complex disease,”

she recalls. “The diabetes school was organized in such a way that only 15 to 20 minutes were allocated to each patient, this was not satisfactory.”

Instead Dijana turned to the Lithuanian Diabetes Association for support and used the internet as a resource. “I realized that it was necessary to communicate with people who

Size of organizationsThe majority of associations, 48% of respondents, have fewer than 999 members. This was followed by medium-sized associations of between 1,000 and 9,999 members, 34%, while 12% were large associations of between 10,000

and 49,999. Only 6% of the respondents have more than 50,000 members, as shown in Figure 9.5. However, it is important to note that this small number of associations covers around 75% of all members represented by IDF diabetes associations.



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Figure 9.5Size of diabetes associations

Figure 9.6Activities undertaken by diabetes associations

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ActivitiesEducation, public awareness and the organization of meetings are the most common activities undertaken by the associations that responded to the survey, as indicated in Figure 9.6.

EducationOf those who organized diabetes education, 82% organized courses for people with diabetes while 67% had courses for healthcare professionals, as shown in Figure 9.7. Some 67% produced their own education materials.

Public awarenessActivities to raise public awareness included World Diabetes Day, media events, other national campaigns and diabetes fairs, as shown in Figure 9.8.

It is also significant to note that almost 77% of respondents were involved in activities for the primary prevention of type 2 diabetes.

have the same illness, so I became a member of the Lithuanian Diabetes Association and subscribed to their quarterly magazine, Diabetas [Diabetes].”

Dijana found that she had to make several adjustments to her life: psychological, dietary and physical. She also had to learn to manage her insulin dosage, which she found the most difficult. “At the beginning I thought it would be enough to measure the level of blood glucose, and regulate the amount of insulin and carbohydrate intake,” she states, “today I know this understanding is quite limited.” Dijana found that her blood glucose level could rise in a stressful situation or during a complicated conversation with a colleague.

The diabetes association provided advice and helped answer her many questions. Says Dijana: “There were things that I did not understand due to my lack of experience with the disease. Practical suggestions helped a lot.” The association’s doctor gave her advice about diet, as well as an easy nutrition plan and a guide to principles of healthy nutrition. “He also taught me not to be afraid to reduce the insulin doses depending on fluctuations of the level of glucose.”

For the first two months following diagnosis Dijana found that she had more energy and strength than before. However, her doctor as well as the association’s doctor warned her that this was the so-called ‘honeymoon’ period. She was then prepared to meet what was to come – the fluctuations in her level of glucose, and to adjust her insulin dosage accordingly.

“It is vital to learn from my own mistakes,” emphasizes Dijana, “and to listen to suggestions from friends with a common fate, share our experiences and just to live on.”



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MeetingsMeetings organized by the associations were mostly seminars (80% of respondents) followed by workshops and congresses. These meetings were in most cases addressed to healthcare professionals and to a lesser extent to people with diabetes.

AdvocacyThe top three issues in advocacy were:

1 ensuring quality care;2 defending the rights of people with

diabetes; and3 promoting education to people

with diabetes and healthcare professionals.

These top issues were fully in line with the goals set by the associations in their mission statements. Other major issues raised were prevention, screening, cost of insulin, costs/reimbursement of care, insurance, driving licence, empowerment, and influencing public health policies through collaboration with governments, health organizations, other non-governmental organizations (NGOs) and universities.

MagazinesMagazines published by the diabetes associations are largely addressed to people with diabetes (92% of respondents), while 80% targeted healthcare professionals and only 48% focused on opinion leaders, as shown in Figure 9.9. Half of these magazines were addressed to all three target groups at the same time.

National diabetes programmesMore than half of the associations that responded, close to 58%, indicated that there is a national diabetes programme in their country. In 83% of the cases, the programme is being implemented with 73% of the associations involved in its implementation.

Figure 9.7Diabetes education: type of activity

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Figure 9.8Public awareness activities

Figure 9.9Magazines: target groups

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More than 90% of the associations co-operate with a national health authority in their country, this authority in many cases being the Ministry or Department of Health.

Healthcare centresActivities undertaken by diabetes healthcare centres are multiple. All of them provide education for people with diabetes and a large majority offer consultation, dietary guidance, foot care, eye examination as well as seminars for healthcare providers, as seen in Figure 9.10.

Figure 9.10Services provided by healthcare centres

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Region Country Name of organizationYear of

establishment

No. ofindividualmembers

No. of full time employees

No. of active volunteers

Constitution and by-laws Elected bodies Action plan Membership fee

Free membership

for people with diabetes

AFR

Cameroon Cameroon Diabetes Association (ACADIA) 1989 1,000 ü ü § § ü

Central African Republic Association des Diabétiques en Centrafrique / Central Africa Diabetes Association

Chad Association Tchadienne de lutte contre le Diabète / Chad Association for the Fight against Diabetes

Congo, Democratic Republic of Association Nationale du Diabète de la République Démocratique du Congo

Côte d’Ivoire Association des Diabétiques de Côte d’Ivoire (ADIACI) 1994 4,000 0 10 ü § § ü §

Eritrea Eritrean Diabetes Association 1997 5,000 ü

Ethiopia Ethiopian Diabetes Association 1985 5,000 1 10 ü ü §

Gabon Association des Diabétiques du Gabon

Gambia Gambia Diabetes Association 1993 600 0 6 ü ü § ü ü

Ghana Ghana Diabetes Association 1,738

Guinea Association Guinéenne d’Education et d’Aide aux Diabétiques / Guinean Association for the Education and Help to Diabetics

Kenya Diabetes Educators Association of Kenya 1999 65 0 65 ü ü ü ü §

Kenya Diabetes Association 1971 10,524 0 6 ü § § ü §

Madagascar Association Malgache contre le Diabète 1983 6,000 1 100 ü ü ü ü ü

Mali Association Malienne de Lutte contre le Diabète (AMLD) 1991

Mozambique Associação Moçambicana dos Diabéticos

Nigeria Diabetes Association of Nigeria 1982 3,000 5 15 ü ü ü ü §

Senegal Association Sénégalaise de Soutien aux Diabétiques (ASSAD) 1967 19,928 10 19 ü § § ü ü

South Africa Diabetes South Africa 1969 5,040

Society for Endocrinology, Metabolism and Diabetes of South Africa (SEMDSA) 1960 250 0 10 ü § § ü §

Tanzania Diabetes Association of Zanzibar (DAZ) 1986 450 0 0 ü § ü ü §

Tanzania Diabetes Association 1985 625 0 5 ü ü ü ü

Togo Association Togolaise du Diabète (ATD) 1992 2,000 4 ü ü § ü §

Uganda Uganda Diabetic Association

Zambia Diabetes Association of Zambia 1989 1,000 0 10 ü ü ü ü §

Zimbabwe Zimbabwe Diabetic Association 1989 1,500 2 8 ü ü ü ü §

EMME

Bahrain Bahrain Diabetes Association 1989 150

Egypt Egyptian Diabetes Association 1970 8,032 4 100 ü ü ü ü ü

Iran Iranian Diabetes Society (IDS) 1968 14,599 12 80 ü ü ü § ü

Iraq Iraqi Diabetes Association 1982 100

Jordan Jordanian Association for the Care of Diabetes 717

Kuwait Kuwait Diabetes Society 1996 1,086 8 20 ü ü ü ü

Lebanon Lebanese Diabetes Association 1982 260

Libya Libyan Diabetic Association 400

Morocco Ligue Marocaine de Lutte contre le Diabète 1991 1,850

Pakistan Diabetic Association of Pakistan 1996 8,480 40 ü ü ü ü §

Qatar Qatar Diabetes Association 1995 474 15 40 ü § ü §

Saudi Arabia Saudi Diabetes and Endocrine Association 1993 3,850

Sudan Sudan Diabetic Association

Syria Syrian Diabetes Association 1973 220

Tunisia Association Tunisienne des Diabétiques / Tunisian Diabetes Association 1971 3,500

United Arab Emirates Emirates Diabetes Society 124

EUR

Albania Shoqata Shqipëtare Diabetike / Albanian Diabetes Association 1992 1,000 0 7 § ü § § ü

Austria Österreichische Diabetes-Gesellschaft / Austrian Diabetes Society 1969 580

Österreichische Diabetiker Vereinigung / Austrian Diabetes Organization 5,900

Azerbaijan, Republic of Azerbaijan Diabetes Society 3,000 § ü ü

Belarus Belarussian Humanitarian Organization ‘Children’s Diabetes’ 3,003

Belgium Association Belge du Diabète / Belgian Diabetes Association 1942 7,500

Vlaamse Diabetes Vereniging / Flemish Diabetes Association 1972 18,580 8 418 ü ü ü ü §

Table 9.1Structure and organization of diabetes associations, 2003



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establishment





Free membership


AFR

Cameroon Cameroon Diabetes Association (ACADIA) 1989 1,000 ü ü § § ü

Central African Republic Association des Diabétiques en Centrafrique / Central Africa Diabetes Association

Chad Association Tchadienne de lutte contre le Diabète / Chad Association for the Fight against Diabetes

Congo, Democratic Republic of Association Nationale du Diabète de la République Démocratique du Congo

Côte d’Ivoire Association des Diabétiques de Côte d’Ivoire (ADIACI) 1994 4,000 0 10 ü § § ü §

Eritrea Eritrean Diabetes Association 1997 5,000 ü

Ethiopia Ethiopian Diabetes Association 1985 5,000 1 10 ü ü §

Gabon Association des Diabétiques du Gabon

Gambia Gambia Diabetes Association 1993 600 0 6 ü ü § ü ü

Ghana Ghana Diabetes Association 1,738

Guinea Association Guinéenne d’Education et d’Aide aux Diabétiques / Guinean Association for the Education and Help to Diabetics

Kenya Diabetes Educators Association of Kenya 1999 65 0 65 ü ü ü ü §

Kenya Diabetes Association 1971 10,524 0 6 ü § § ü §

Madagascar Association Malgache contre le Diabète 1983 6,000 1 100 ü ü ü ü ü

Mali Association Malienne de Lutte contre le Diabète (AMLD) 1991

Mozambique Associação Moçambicana dos Diabéticos

Nigeria Diabetes Association of Nigeria 1982 3,000 5 15 ü ü ü ü §

Senegal Association Sénégalaise de Soutien aux Diabétiques (ASSAD) 1967 19,928 10 19 ü § § ü ü

South Africa Diabetes South Africa 1969 5,040

Society for Endocrinology, Metabolism and Diabetes of South Africa (SEMDSA) 1960 250 0 10 ü § § ü §

Tanzania Diabetes Association of Zanzibar (DAZ) 1986 450 0 0 ü § ü ü §

Tanzania Diabetes Association 1985 625 0 5 ü ü ü ü

Togo Association Togolaise du Diabète (ATD) 1992 2,000 4 ü ü § ü §

Uganda Uganda Diabetic Association

Zambia Diabetes Association of Zambia 1989 1,000 0 10 ü ü ü ü §

Zimbabwe Zimbabwe Diabetic Association 1989 1,500 2 8 ü ü ü ü §

EMME

Bahrain Bahrain Diabetes Association 1989 150

Egypt Egyptian Diabetes Association 1970 8,032 4 100 ü ü ü ü ü

Iran Iranian Diabetes Society (IDS) 1968 14,599 12 80 ü ü ü § ü

Iraq Iraqi Diabetes Association 1982 100

Jordan Jordanian Association for the Care of Diabetes 717

Kuwait Kuwait Diabetes Society 1996 1,086 8 20 ü ü ü ü

Lebanon Lebanese Diabetes Association 1982 260

Libya Libyan Diabetic Association 400

Morocco Ligue Marocaine de Lutte contre le Diabète 1991 1,850

Pakistan Diabetic Association of Pakistan 1996 8,480 40 ü ü ü ü §

Qatar Qatar Diabetes Association 1995 474 15 40 ü § ü §

Saudi Arabia Saudi Diabetes and Endocrine Association 1993 3,850

Sudan Sudan Diabetic Association

Syria Syrian Diabetes Association 1973 220

Tunisia Association Tunisienne des Diabétiques / Tunisian Diabetes Association 1971 3,500

United Arab Emirates Emirates Diabetes Society 124

EUR

Albania Shoqata Shqipëtare Diabetike / Albanian Diabetes Association 1992 1,000 0 7 § ü § § ü

Austria Österreichische Diabetes-Gesellschaft / Austrian Diabetes Society 1969 580

Österreichische Diabetiker Vereinigung / Austrian Diabetes Organization 5,900

Azerbaijan, Republic of Azerbaijan Diabetes Society 3,000 § ü ü

Belarus Belarussian Humanitarian Organization ‘Children’s Diabetes’ 3,003

Belgium Association Belge du Diabète / Belgian Diabetes Association 1942 7,500

Vlaamse Diabetes Vereniging / Flemish Diabetes Association 1972 18,580 8 418 ü ü ü ü §



292



293

Bulgaria Bulgarian Diabetes Association 1990 15,300 5 250 § ü § § ü

Bulgarian Society of Endocrinology and Gerontology 1954 160

Croatia Hrvatska Dijabeticka Udruga / Croatian Diabetes Association 1957 7,000 2 700 ü ü ü

Cyprus Cyprus Diabetic Association 1979 6,000 1 50 ü ü § ü ü

Czech Republic Ceska Diabetologicka Spolecnost / Czech Diabetes Society 1963 682

SVAZ Diabetiku Ceske Republiky / Union of Diabetics of the Czech Republic 1991 16,000 6 600 ü ü ü ü ü

Denmark Diabetesforeningen / Danish Diabetes Association 1940 54,000 27 500 ü ü ü ü

Estonia Estonian Diabetes Association 1992 0 All ü ü ü ü §

Finland Finnish Diabetes Association 1955 52,000 60 1,500 ü ü ü

France Association Française des Diabétiques (AFD) / French Diabetes Association 1938 26,000

Georgia, Republic of Georgian Diabetes Federation 1992 4,000 0 100 ü ü ü

Germany Deutsche Diabetes-Union e V / German Diabetes Union 1990 46,136

Greece Hellenic Diabetologic Association 1974 2,086

Hellenic Federation of Diabetics 1997 300 1 10 ü ü ü

Hungary Magyar Diabetes Tarsasag / Hungarian Diabetes Association 1971 1,480 0 0 ü ü ü ü §

Iceland Samtök Sykursjúkra / Icelandic Diabetes Association 1971 750

Ireland Diabetes Federation of Ireland 1967 3,087 6 200 ü ü ü ü §

Irish Endocrine Society 1984 165

Israel Israel Diabetes Association 1954 12,000 6 220 ü ü ü ü

Italy Associazione Italiana Diabetici (AID) 1964

Associazione Medici Diabetologi (AMD) 1974 1,582 3 200 ü ü ü ü §

FAND 1982 80,000 0 11 ü ü ü ü §

Società Italiana di Diabetologia (SID) / Italian Society of Diabetology 1,943

Kazakhstan Diabetes Association of the Kazakhstan Republic 1995 3,000 10 ü ü ü ü ü

Kyrgyzstan Diabetes Association of Kyrgyzstan

Lithuania Lithuanian Diabetes Association 1989 5,000 4 52 ü ü ü ü ü

Luxembourg Association Luxembourgeoise du Diabète / Luxembourg Diabetes Association 1979 906 0 15 ü ü ü ü §

Macedonia Macedonian Diabetes Association 1991 2,500

Malta Ghaqda Kontra D-Dijabete / Maltese Diabetes Association 1983 900 0 ü ü § ü §

Netherlands Diabetesvereniging Nederland (DVN) / Dutch Diabetes Association 1945 53,630 27 4,000 ü ü ü ü §

Nederlandse Vereniging voor Diabetes Onderzoek (NVDO) / Dutch Association for Diabetes Research

1974 300

Norway Norges Diabetesforbund / Norwegian Diabetes Association 1948 33,000 18 1,200 ü ü ü ü §

Poland Polskie Stowarzyszenie Diabetyków Zarzad Glowny / Polish Diabetes Association 1981 100,000 5 1,200 ü ü § ü ü

Polskie Towarzystwo Diabetologiczne / Polish Diabetological Association 1983 500

Portugal Associação Protectora dos Diabeticos de Portugal (APDP) / Portuguese Diabetic Association

4,389

Sociedade Portuguesa de Diabetologia (SPD) 1926 452

Romania Association for the Protection of Romanian Children and Youth with Diabetes 750

Societatea Romana de Diabet, Nutritie si Boli Metabolice / Romanian Society of Diabetes, Nutrition and Metabolic Diseases

Russian Federation Russian Diabetes Federation 1,000,000

Serbia and Montenegro Diabetes Association of Serbia and Montenegro 1997 7,000 0 3 ü ü ü § ü

Slovakia Slovenska Diabetologicka Spolocnost / Slovak Diabetes Society 1968

ZVAZ Diabetikov Slovenska / Association of Diabetic Patients of Slovakia 1990 669 0 55 ü ü ü ü §

Slovenia Zveza Društev Diabetikov Slovenije (SLODA) / Slovenian Diabetes Association 1956 3,000

Spain Asociación de Diabéticos de Tenerife 200 1 10 ü § § ü ü

Federación Española de Diabetes / Spanish Federation of Diabetes 2,000

Sociedad Española de Diabetes / Spanish Diabetes Society 1954 830 1 0 ü ü § ü §

Sweden Svenska Diabetes Förbundet / Swedish Diabetes Association 1943 35,500 14 ü ü ü ü §

Swedish Society for Diabetology 1982 3,000

Switzerland Schweizerische Diabetes-Gesellschaft / Swiss Diabetes Association 1957 25,000

Turkey Türk Diabet Cemiyeti / Turkish Diabetes Association 1955 2,250

Turkish Diabetes Foundation 1996 750 3 10 ü ü ü ü ü

Ukraine Ukrainian Diabetic Federation 1993 17,000 3 75 ü ü ü

United Kingdom Diabetes UK 1934 183,000 170 ü ü ü ü §

NA

Anguilla Anguilla Diabetes Association

Antigua and Barbuda Antigua and Barbuda Diabetes Association 1986 60 0 6 § ü


establishment





Free membership




294



295

Aruba Aruba Diabetes Foundation 1975 50 0 15 ü ü ü § ü

Bahamas Bahamas Diabetic Association 1986 350 1 20 ü ü § ü ü

Barbados Diabetes Association of Barbados 1975 1,600 ü ü § ü ü

Belize Belize Diabetes Association 1991 357 0 10 ü ü § ü ü

Bermuda Bermuda Diabetes Association 1979 700 0 12 ü ü ü ü §

British Virgin Islands British Virgin Islands Diabetes Association 1982 150 0 12 § ü §

Canada Canadian Diabetes Association 1953 50,000 310 ü ü ü ü §

Diabète Québec 1954 22,000 20 2,000 ü ü ü ü §

Cayman Islands Cayman Islands Diabetic Association 2000 139 0 § ü § § ü

Dominica, Commonwealth of Dominica Diabetes Association 300

Grenada Grenada Diabetes Association 1983 250

Guyana Guyana Diabetic Association 1973 100 0 7 ü ü ü ü §

Haiti Fondation Haïtienne de Diabète et de Maladies Cardiovasculaires (FHADIMAC) 80

Jamaica Diabetes Association of Jamaica 1983 35,000 38 7 § ü § ü §

Mexico Federación Mexicana de Diabetes / Mexican Diabetes Federation 1979 965 6 15 ü ü ü

Sociedad Mexicana de Nutrición y Endocrinología / Mexican Society of Nutrition and Endocrinology

500

St Kitts and Nevis St Kitts Diabetes Association

St Lucia St Lucia Diabetic and Hypertensive Association

Trinidad and Tobago Diabetes Association of Trinidad and Tobago 1976 2,100

USA American Diabetes Association 1936 400,000 900 50,000 ü ü ü ü §

SACA

Argentina Liga Argentina de Protección al Diabético (LAPDI) / Argentine League for the Protection of Diabetics

1964 2,000 3 10 ü ü ü ü ü

Mutual Integral Provincial de Ayuda al Diabético (MIPADI) 1994 310

Sociedad Argentina de Diabetes / Argentinian Diabetes Society 1954 765

Bolivia Sociedad Boliviana de Endocrinología, Metabolismo y Nutrición / Bolivian Society of Endocrinology, Metabolism and Nutrition

56 0 56 ü ü § ü §

Brazil Associação de Diabetes Juvenil (ADJ) 1980 1,000

Federação Nacional de Associações de Diabéticos (FENAD) 1988 10 58 ü ü ü

Sociedade Brasileira de Diabetes (SBD) / Brazilian Diabetes Society 1970 920

Chile Fundación Diabetes Juvenil de Chile / Juvenile Diabetes Foundation of Chile 1988 4,258

Sociedad Chilena de Endocrinología y Metabolismo / Chilean Society of Endocrinology and Metabolism

206

Colombia Asociación Colombiana de Diabetes 1954 8,000

Federación Diabetológica Colombiana (FDC) 1997 300

Costa Rica Asociación Costarricense de Endocrinología Diabetes y Nutrición (ACEDYN) 35

Cuba Sociedad Cubana de Diabetes / Cuban Society of Diabetes 1959 131 0 131 ü ü ü ü §

Dominican Republic Instituto Nacional de Diabetes, Endocrinología y Nutrición (INDEN) 1972 343

Sociedad Dominicana de Diabetes (SODODIA) / Dominican Diabetes Society 1966 150

Ecuador Asociación Ecuatoriana de Diabeticos (AED)

Federación Ecuatoriana de Diabetes (FEDIabetes)

El Salvador Asociación Salvadoreña de Diabéticos (ASADI) 1988 3,200 10 40 ü § ü ü ü

Guatemala Patronato de Pacientes Diabéticos de Guatemala

Honduras Coordinadora Nacional de Lucha contra la Diabetes (CONALUDI)

Netherlands Antilles Sociedat Kurasoleno di Diabetiko (SOKUDI) / Diabetic Association of Curaçao

Nicaragua Fundación Pro Ayuda a Enfermos Crónicos (FUNPEC) 1994 600 ü ü ü § ü

Panama Asociación Panameña de Diabeticos / Panamanian Diabetes Association 980

Paraguay Fundación Paraguaya de Diabetes

Sociedad Paraguaya de Diabetología / Paraguayan Society of Diabetology 1970 40 ü ü ü ü §

Peru Asociación de Diabéticos Juveniles del Péru (ADJ) / Juvenile Diabetes Association of Peru

1990 50 4 12 ü ü ü ü ü

Asociación Peruana de Diabetes / Peruvian Diabetes Association 1973 1,000

Puerto Rico Asociación Puertorriqueña de Diabetes 1988 350 6 ü § § ü

Asociación Puertorriqueña de Educadores en Diabetes / Puerto Rican Association of Diabetes Educators

47

Sociedad Puertorriqueña de Endocrinología y Diabetología (SPED) / Puerto Rican Society of Endocrinology and Diabetology

1977 70

Suriname Stichting Diabetes Educatie Suriname 1988 15 ü § §


establishment





Free membership




296



297

Uruguay Asociación de Diabéticos del Uruguay / Uruguayan Diabetes Association 1951 5,413 19 100 ü ü ü ü

Sociedad de Diabetología y Nutrición del Uruguay 1978 250

Venezuela Asociación Venezolana de Diabetes / Venezuelan Diabetes Association

Federación Venezolana de Asociaciones y Unidades de Diabetes (FENADIABETES) 1990 250

Fundación de Atención al Diabético (FUNDIABETES) 1,000

Sociedad Venezolana de Endocrinología y Metabolismo / Venezuelan Endocrinology and Metabolism Society

1957 150

SEA

Bangladesh Diabetic Association of Bangladesh (DAB) 1956 569

India Diabetic Association of India 1955 12,270 ü ü ü ü §

Mauritius Mauritius Diabetic Association 1981 300 1 24 ü ü ü ü §

Nepal Nepal Diabetes Association 1990 300 3 10 ü ü ü ü ü

Sri Lanka Diabetes Association of Sri Lanka 1984 494 18 48 ü ü ü ü §

WP

Australia Diabetes Australia 1952 94,044

South Eastern Sidney Division of General Practitioners 1992 205 6 0 ü ü § ü §

Cambodia Cambodian Diabetes Association 1998 338 0 12 ü ü ü § ü

China, Hong Kong Diabetes Hong Kong 1996 2,301 3 103 ü ü ü § ü

Society for the Study of Endocrinology, Metabolism and Reproduction 1983 70

China, Macau Macau Diabetes Association 1997 328 0 5 ü ü ü § ü

China, People’s Republic of Chinese Diabetes Society of the Chinese Medical Association (CMA) 1991 500

Fiji Fiji National Diabetes Foundation 1986 75

Indonesia Persatuan Diabetes Indonesia / Indonesian Diabetes Association 1986 5,000

Japan Japan Diabetes Society 1957 20,000 4 ü § ü ü §

Korea, Republic of Korean Diabetes Association 1968 26,318 2 ü ü ü ü ü

Malaysia Persatuan Diabetis Malaysia / Malaysian Diabetes Association 1981 2,800

New Zealand Diabetes New Zealand 1962 13,479 3 ü ü ü ü §

Papua New Guinea Diabetic Association of Papua New Guinea 16

Philippines Philippine Diabetes Association 1958 500 1 ü ü § ü §

Samoa Samoa Diabetes Association

Singapore, Republic of Diabetic Society of Singapore 1971 3,500 12 10 ü § § ü §

Taiwan Chinese Taipei Diabetes Association 1980 633 1 14 § § ü ü

Thailand Diabetes Association of Thailand 1966 369

Tonga Tonga Diabetes Association 1997 700

Total 2,699,006 1,863 64,642 § § § § §


establishment





Free membership




298



299

Region Country Name of healthcare centreTotal no. of

registered patients ConsultationEye

examination Hospitalization

Education for people with

diabetes

Seminar for healthcare providers

Dietary guidance Foot care

Magazine for patients

Routine laboratory

test

AFR

Côte d’Ivoire Centre Antidiabétique d’Abidjan et Service d’Endocrino-Diabétologie du CHU de Yopougon 24,000 ü § ü ü ü ü ü § §

Kenya Diabetes Care and Training Ltd 1,456 ü § § ü ü ü § ü ü

Madagascar Maison du Diabète 5,500 ü ü § ü ü ü ü § ü

Senegal Centre de Diabétologie Marc Sankale 19,928

EMME

Libya National Centre for Diabetes and Endocrinology 16,094 ü ü ü ü § ü ü § ü

Pakistan Diabetic Association of Pakistan 8,477 ü ü § ü ü ü ü ü §

EUR

Georgia, Republic of Georgian Diabetes Federation 1,500 ü ü § ü ü § § § §

NA

Bermuda BHB Diabetes Centre 1,500 ü § § ü ü ü ü § §

Jamaica Diabetes Association of Jamaica 35,000 ü ü § ü ü ü ü ü ü

SACA

Nicaragua Fundación Pro Ayuda a Enfermos Crónicos Clinica 1,500 ü ü § ü ü ü ü ü ü

Venezuela Fundación de Atención al Diabético 840 § § § ü ü ü ü § §

SEA

Bangladesh Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM)

245,842 ü ü ü ü ü ü ü ü ü

India All India Institute of Diabetes 67,332 ü ü ü ü ü ü ü ü ü

Sri Lanka National Diabetes Centre 130,000 ü ü § ü ü ü ü ü ü

WP

Singapore, Republic of Diabetes Education and Care Centre N/A ü ü § ü § ü ü § §

Total 558,969 § § § § § § § § §

Table 9.2Number of registered patients and services provided by diabetes healthcare centres, 2003

N/A not available



298



299

Region Country Name of healthcare centreTotal no. of

registered patients ConsultationEye

examination Hospitalization

Education for people with

diabetes

Seminar for healthcare providers

Dietary guidance Foot care

Magazine for patients

Routine laboratory

test

AFR

Côte d’Ivoire Centre Antidiabétique d’Abidjan et Service d’Endocrino-Diabétologie du CHU de Yopougon 24,000 ü § ü ü ü ü ü § §

Kenya Diabetes Care and Training Ltd 1,456 ü § § ü ü ü § ü ü

Madagascar Maison du Diabète 5,500 ü ü § ü ü ü ü § ü

Senegal Centre de Diabétologie Marc Sankale 19,928

EMME

Libya National Centre for Diabetes and Endocrinology 16,094 ü ü ü ü § ü ü § ü

Pakistan Diabetic Association of Pakistan 8,477 ü ü § ü ü ü ü ü §

EUR

Georgia, Republic of Georgian Diabetes Federation 1,500 ü ü § ü ü § § § §

NA

Bermuda BHB Diabetes Centre 1,500 ü § § ü ü ü ü § §

Jamaica Diabetes Association of Jamaica 35,000 ü ü § ü ü ü ü ü ü

SACA

Nicaragua Fundación Pro Ayuda a Enfermos Crónicos Clinica 1,500 ü ü § ü ü ü ü ü ü

Venezuela Fundación de Atención al Diabético 840 § § § ü ü ü ü § §

SEA

Bangladesh Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM)

245,842 ü ü ü ü ü ü ü ü ü

India All India Institute of Diabetes 67,332 ü ü ü ü ü ü ü ü ü

Sri Lanka National Diabetes Centre 130,000 ü ü § ü ü ü ü ü ü

WP

Singapore, Republic of Diabetes Education and Care Centre N/A ü ü § ü § ü ü § §

Total 558,969 § § § § § § § § §

Prevention and Strategic ActionChapter 10


301

Prevention and Strategic Action Chapter 10

The current mission of the International Diabetes Federation

(IDF) is “to work with its member associations to enhance the lives of people with diabetes”. To fulfil its mission and its role as the global advocate for people with diabetes, IDF has engaged in activities to advocate, educate and inform.

As such, for the last 50 years, the actions of the Federation have been targeted accordingly:

• recruiting more member associations;• organizing activities in the Federation’s

seven regions;• raising public awareness about

diabetes;• promoting solidarity through the

associations’ twinning programmes;• defending the cause of people with

diabetes at national, regional and international levels;

• cooperating with the World Health Organization (WHO) and numerous non-governmental bodies;

Priorities

Prevention of diabetes and its complications

Improve quality of life

Ensure affordable insulin and diabetes supplies

Raise global awareness

Promote education

At a glance



302



303

• helping to educate healthcare professionals to improve diabetes management through the Federation’s Education Foundation;

• promoting diabetes education;• evaluating the costs of diabetes; and• disseminating information about

diabetes through its newsletters, periodicals, non-serial publications, triennial congresses, website and the Diabetes Atlas.

The need for prevention

As evidenced by the information gathered in this edition of the Diabetes Atlas, the time has come to consider adding diabetes prevention to the mission of the Federation. Indeed, estimations and projections all concur that the number of people with diabetes which may be reached in the next 25 years would qualify diabetes as the largest epidemic humanity has ever experienced.

If this indeed occurs, and there is little reason to believe it will not if action is not taken, there is a significant risk that governments and social security systems may fail to ensure the appropriate care to the some 333 million people who will be affected by diabetes in 2025. Some 90% of these people will have type 2 diabetes mellitus. Recent studies have shown that type 2 diabetes and its complications may be prevented or delayed given the right action.

By promoting diabetes prevention, IDF will ensure that those millions who already have diabetes will not face the nightmare of a regression in the quality of care they deserve while, on the contrary, there is a great need in many parts of the world to improve it.

Although representing only less than 10% of all forms of diabetes, the absolute number of people with type 1 diabetes will definitely increase in the coming years. This is due to the conjunction of an increased life expectancy, a reason

for satisfaction, and of a rise in incidence (number of new cases each year), a cause for concern.

Preventing type 1 diabetes to occur is still a dream. However, the worldwide efforts to better understand the mechanisms of the disease, identify what is inherited and what may be due to the environment, and to recognize early those at risk offer great hopes that type 1 diabetes may one day be prevented, halted early in its progression and ultimately cured.

Priorities for strategic action

Type 1 diabetes mellitusThe priority of the priorities today for the International Diabetes Federation is to ensure that insulin and blood glucose control materials are available and affordable everywhere in the world for those who need them, an objective followed assiduously by the IDF Task Force on Insulin.

The contribution of IDF to the prevention of type 1 diabetes will be to maintain pressure on raising awareness, encourage research in the field and support all those who, through innovative efforts, try to better understand the mechanisms of this complex disease.

Type 2 diabetes mellitusPathways for direct action by IDF are more obvious regarding type 2 diabetes mellitus, which affect some 90% of the 194 million with diabetes today, and probably even more than 90% tomorrow. As emphasized in a recent consensus statement (see Box 8.1 in Chapter 8) (1), there is strong evidence that genetics plays an important role together with overweight or obesity resulting from excess caloric intake and reduction in physical activity.

Furthermore, there is evidence that a low birth weight, as a consequence of poor nourishment of the foetus, significantly increases the risk of type 2 diabetes

By promoting diabetes prevention, IDF will

ensure that those millions who already

have diabetes will not face the nightmare of a

regression in the quality of care they deserve

while, on the contrary, there is a great need in many parts of the world

to improve it.



302



303

mellitus and the related ‘metabolic syndrome’ in the offspring. In addition, some mechanistic studies suggest a relationship between stress and insulin resistance with predisposition to type 2 diabetes mellitus.

Recent studies have shown that lifestyle changes (and also some medications) are effective in preventing type 2 diabetes in individuals at risk, such as those with impaired glucose tolerance (2-5). IDF is committed to advancing concerted actions by governments and non-governmental organizations to raise awareness about the seriousness of type 2 diabetes, promote education at all levels and exercise multisectoral advocacy.

Global awareness, advocacy and action in diabetes programmeA major action in the coming years is the ambitious ‘Global awareness, advocacy and action in diabetes’ programme developed by the WHO Department of Noncommunicable Diseases Management in Geneva and the International Diabetes Federation. Supported by the World Diabetes Foundation, this programme aims to enhance awareness about diabetes and its complications amongst the public, health professionals and decision makers, with major emphasis on prevention, particularly in low income countries.

The programme is designed to support WHO/IDF regions and countries in the reorganization of their health services in response to the current epidemic by developing coordinated programmes to promote effective management of people with diabetes as well as primary prevention of type 2 diabetes. In these programmes, emphasis will be put on healthy dietary habits, promotion of physical activity, and appropriate quantitative and qualitative nutrition of the pregnant mother.

Improve quality of lifeThe cornerstone of the action of the Federation remains helping all those affected by diabetes to improve their quality of life, prevent diabetes complications to occur and, if these occur, slowdown their progression, even if primary prevention of diabetes must now be considered by IDF.

In our times of ‘evidence-based’ medicine, numerous studies performed over the last 20 years (6) have provided strong evidence that strict control of blood glucose reduces the incidence of retinopathy, nephropathy and neuropathy in both type 1 and type 2 diabetes mellitus, that control of blood pressure reduces the risk of cardiovascular events and deaths, and that intensive treatment of blood pressure reduces the risk of aggravation of nephropathy in people with microalbuminuria or incipiens renal failure.

The time has come to act…NOW!

As emphasized by Nathan (6), the net effect of these controlled clinical trials has been an expansion of lifespan and an improvement in quality of life for persons affected by diabetes. IDF’s role is to disseminate the conclusions of these trials to its member associations, and raise awareness about the progress in this field among the public, healthcare providers, social security authorities and governments.

Diabetes programmesIDF recognizes some remarkable national programmes for diabetes such as the National Framework Programme on Diabetes in the United Kingdom, the 2000-2010 Development Programme for Prevention and Care in Finland, the



304

References

1. Diabetes in Asia 2002 Meeting. Consensus on the Aetiology of Type 2 Diabetes Mellitus and Development of a Primary Prevention Strategy for Type 2 Diabetes Mellitus. Colombo, Sri Lanka, July 2002.

2. Pan X-R, Li G-W, Wang J-X, et al. Effect of diet and exercise in preventing NIDDM in people with impaired glucose tolerance: the Da Quing IGT and Diabetes Study. Diabetes Care 1997; 20:537-544.

3. Tuomilehto J, Lindström J, Eriksson JG, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 2001; 344:1343-1350.

4. Diabetes prevention programme research group. Reduction in the incidence of Type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002; 346:393-403.

5. Chiasson J-L, Josse RG, Gomis R, Hanefeld M, Karasik A and Laakso M for the Stop-NIDDM Trial Research Group. Acarbose for prevention of type 2 diabetes mellitus: the STOP-NIDDM randomised trial. Lancet 2002; 359:2072-2077.

6. Nathan DM. The impact of clinical trials on the treatment of diabetes mellitus. J Clin Endocr Metab 2002; 87:1929-1937.

National Plan against Diabetes in France, and the coming National Prevention Programme for Diabetes in Sri Lanka, to mention only a few.

Through its regions, IDF has contributed to major programmes through the St Vincent Declaration in Europe, Declaration of the Americas on Diabetes in North, South and Central America, Western Pacific Declaration on Diabetes in the Western Pacific and EMME Declaration on Diabetes in the Eastern Mediterranean and Middle East. The Federation will continue to encourage similar initiatives in other parts of the world.

Conclusion

Monitoring the global diabetes epidemic, evaluating the overall cost of the disease, assessing the access to insulin and diabetes supplies worldwide, reviewing the progress of diabetes education, and promoting the work and achievements of its member associations are key features of the present edition of the Diabetes Atlas. However, to observe and report is one course of action, to act to improve the condition of people with diabetes and preventing the disease to affect millions is another. The time has come to act…NOW!

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