UNMET NEED FOR SCREENING AND TREATMENT OF NON LISS...
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UNMET NEED FOR SCREENING AND TREATMENT OF NON COMMUNICABLE DISEASES; A CROSS SECTIONAL STUDY AMONG OLDER ADULTS (60+) IN KOTTAYAM DISTRICT, KERALA LISS MARIA SCARIA Dissertation submitted in partial fulfillment of the Requirement for the award of Master of Public Health ACHUTHA MENON CENTRE FOR HEALTH SCIENCE STUDIES SREE CHITRA TIRUNAL INSTITUTE FOR MEDICAL SCIENCES AND TECHNOLOGY, TRIVANDRUM Thiruvananthapuram, Kerala. India – 695011 OCTOBER 2016
Transcript of UNMET NEED FOR SCREENING AND TREATMENT OF NON LISS...
UNMET NEED FOR SCREENING AND TREATMENT OF NON
COMMUNICABLE DISEASES; A CROSS SECTIONAL STUDY
AMONG OLDER ADULTS (60+) IN KOTTAYAM DISTRICT, KERALA
LISS MARIA SCARIA
Dissertation submitted in partial fulfillment of the
Requirement for the award of
Master of Public Health
ACHUTHA MENON CENTRE FOR HEALTH SCIENCE STUDIES
SREE CHITRA TIRUNAL INSTITUTE FOR MEDICAL SCIENCES
AND TECHNOLOGY, TRIVANDRUM
Thiruvananthapuram, Kerala. India – 695011
OCTOBER 2016
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Acknowledgements
“And my God will meet all your needs according to the riches of his glory in Christ
Jesus”. Philippians 4:19
First and foremost I would like to express my gratefulness to Lord Almighty for
bestowing his blessings on me, for being with me all the way and for never letting me
fall.
I take this opportunity to extend my earnest gratitude to my guide, Dr. Mala Ramanathan
for not only investing in me on a professional level but also in making me a better version
of myself.
I thank Dr. Ravi Prasad Varma and Dr G. Vijayakumar for their valuable inputs while
coining the research topic. My sincere thanks to all the professors of AMCHSS; Dr. KR
Thankappan, Dr. TK Sundari Ravindran, Dr. V Raman Kutty, Dr P Sankara Sarma, Dr.
Biju Soman, Dr K Srinivasan, Dr Manju Nair and Ms. VT Jissa for their valuable inputs. I
would also like to thank Dr. Sundar Jayasingh, Deputy Registrar and Ms. Jayasree
Neelakantan, UDC, AMCHSS for all the administrative support rendered to facilitate the
conduct of the study.
I acknowledge Ms Thushara M, Ms Elizabeth Scaria and Dr Neethu Suresh for helping
me with the translation of the questionnaire. I extend my gratitude to Mr. Bevin Vinay
Kumar and Ms Sunu C Thomas for their guidance and support during the writing of my
thesis.
I would like to extend my sincere thanks to my seniors especially Ms. Pritty Titus and
Ms. Athulya Thomas for their guidance throughout the course and my dear friends Ms.
Sreeja M, Dr. Revathi V, Dr. Ariba Peerzada and Dr. Asmita Behera for their support and
motivation during the course.
I would like to thank my parents and my best friend Mrs. Ashitha Muhammed for their
support and encouragement all through my work. I would like to thank my brother, Mr.
Charles Scaria especially, for standing by me during data collection. I sincerely
acknowledge his sheer perseverance and emotional strength without which I would not
have been able to complete my study.
I would also like to thank all the participants of the study for their warm welcome they
gave me and for sharing information about their life and their ailments.
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DECLARATION
I hereby declare that this dissertation titled “Unmet need for screening and
treatment of non communicable diseases; a cross sectional study among
older adults (60+) in Kottayam district, Kerala” is the bonafide record of my
original research. It has not been submitted to any other university or institution
for the award of any degree or diploma. Information derived from the published
or unpublished work of others has been duly acknowledged in the text.
Liss Maria Scaria
Achutha Menon Centre for Health Science Studies
Sree Chitra Tirunal Institute for Medical Sciences and Technology
Thiruvananthapuram, Kerala. India -695011
October, 2016
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CERTIFICATE
Certified that the dissertation titled “Unmet need for screening and treatment
of non communicable diseases; a cross sectional study among older adults
(60+) in Kottayam district, Kerala” is a record of the research work
undertaken by Ms Liss Maria Scaria, in partial fulfillment of the requirements
for the award of the degree of “Masters of Public Health” under my guidance
and supervision.
Dr. Mala Ramanathan
Professor
Achutha Menon Centre for Health Science Studies
Sree Chitra Tirunal Institute for Medical Sciences and Technology
Trivandrum, Kerala
October 2016
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TABLE OF CONTENTS
Chapters Topic Page No
List of tables and figures...................................................................................... vii
Glossary of abbreviations.................................................................................... ix
Abstract................................................................................................................ x
Chapter 1 Introduction 1-5
1.1 Background....................................................................................... 1
1.2 Rationale of the study........................................................................ 4
1.3 Research question.............................................................................. 4
1.4 Objectives.......................................................................................... 5
1.5 Chapterization plan for the dissertation............................................ 5
Chapter 2 Review of Literature 6-20
2.1 Morbidity related to NCDs among elderly........................................ 7
2.2 Diabetes Mellitus among elderly....................................................... 8
2.2.1 Prevalence, awareness, treatment and control of Diabetes Mellitus. 8
2.2.2 Complication screening of Diabetes Mellitus................................... 10
2.3 Hypertension among elderly............................................................. 11
2.4 Dyslipidemia among elderly............................................................. 13
2.5 Diabetes Mellitus, Hypertension and Dyslipidemia.......................... 14
2.5.1 Diabetes Mellitus and Dyslipidemia................................................. 16
2.5.2 Diabetes Mellitus and Hypertension................................................. 16
2.6 Factors associated with health care seeking for NCDs..................... 17
2.6.1 Health care seeking and age.............................................................. 17
2.6.2 Health care seeking and gender......................................................... 17
2.6.3 Health care seeking and socioeconomic and employment status...... 18
2.6.4 Health care seeking and level of education....................................... 18
2.6.5 Health care seeking and family History/ presence of co morbidity.. 19
2.6.6 Health care seeking and Disability.................................................... 19
2.6.7 Health care seeking and marital status and living arrangements...... 19
2.6.8 Health care seeking and accessibility, availability and affordability 19
2.7 Definitions......................................................................................... 20
2.7.1 Screening of NCDs............................................................................ 20
2.7.2 Treatment of NCDs........................................................................... 20
Chapter 3 Methodology 21-32
3.1 Study design...................................................................................... 21
3.2 Study setting...................................................................................... 21
3.3 Sample size....................................................................................... 21
3.4 Sample selection................................................................................ 22
3.5 Subject selection................................................................................ 25
3.6 Data collection tool........................................................................... 25
3.7 Data collection.................................................................................. 26
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Chapter No Page No 3.8 Ethical considerations....................................................................... 26
3.9 Data storage....................................................................................... 26
3.10 Data entry.......................................................................................... 27
3.11 Data analysis..................................................................................... 27
3.12 Variables............................................................................................ 27
3.12.1 Dependent variables.......................................................................... 27
3.12.2 Independent variables........................................................................ 29
3.13 Expected outcomes............................................................................ 32
Chapter 4 Results 33-55
4.1 Characteristics of the studied group.................................................. 33
4.1.1 Profile of the participants.................................................................. 33
4.1.2 Participants’ health status.................................................................. 36
4.2 Outcome variables............................................................................. 37
4.3 Factors associated with unmet need for screening and treatment..... 41
4.3.1 Socio demographic factors associated with unmet need for screening for the NCDs.....................................................................
41
4.3.2 Health related factors and unmet need for screening........................ 43
4.3.3 Unmet need for treatment and socio demographic factors................ 44
4.3.4 Unmet need for treatment and various health related factors............ 47
4.3.5 Unmet need for treatment of Diabetes Mellitus and socio demographic factors and health related factors.................................
48
4.4 Simultaneity in unmet need for screening and treatment for the three conditions.................................................................................
51
4.5 Unmet need for screening of the other one/two NCDs when one is diagnosed to have one/two of the NCDs...........................................
53
Chapter 5 Discussion and Conclusion 56-64
5.1 Brief summary of findings................................................................ 56
5.2 Unmet need for screening................................................................. 57
5.2.1 Diabetes Mellitus............................................................................... 58
5.2.2 Hypertension..................................................................................... 58
5.2.3 Dyslipidemia..................................................................................... 59
5.3 Unmet need for treatment................................................................. 60
5.3.1 Diabetes Mellitus............................................................................... 60
5.3.2 Hypertension..................................................................................... 61
5.3.3 Dyslipidemia..................................................................................... 62
5.4 Limitations of the study..................................................................... 62
5.5 Strengths of the study........................................................................ 63
5.6 Conclusion......................................................................................... 63
5.7 Policy Implication............................................................................. 64
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REFERENCES
ANNEXURE I- Cover sheet (English)
ANNEXURE II- Participant information sheet (English)
ANNEXURE III- Informed consent form (English)
ANNEXURE IV- Interview schedule (English)
ANNEXURE V- Cover sheet (Malayalam)
ANNEXURE VI- Participant information sheet (Malayalam)
ANNEXURE VII- Informed consent form (Malayalam)
ANNEXURE VIII- Interview schedule (Malayalam)
ANNEXURE IX- Institute ethics committee clearance letter
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List of Tables
Table No Title Page No 3.1 Computation of conditional probability for estimation of sample
size 22
4.1 Distribution of participants by socio-demographic characteristics,
Kottayam district (N=420) 35
4.2 Distribution of participants by current occupation, major
occupation during lifetime and the current means of sustenance, by sex, Kottayam district
36
4.3 Distribution of participants by their health status related
variables, Kottayam district(N=420) 37
4.4 Distribution of the participants by their chronic disease status and
unmet need for screening (outcome variables), Kottayam district 39
4.5 Distribution of participants by the reasons for not taking
treatment for the NCDs, Kottayam district 40
4.6 Distribution of participants by unmet need for screening status by
socio demographic factors, Kottayam district 42
4.7 Distribution of participants by unmet need for screening status by
health related factors, Kottayam district 44
4.8 Distribution of participants by unmet need for treatment for
NCDs status and socio demographic factors, Kottayam district 45
4.9 Distribution of participants by unmet need for treatment for
NCDs status and health related factors, Kottayam district 47
4.10 Distribution of participants by unmet need for treatment of
Diabetes Mellitus (treatment and complication screening) and socio demographic factors, Kottayam district
49
4.11 Distribution of unmet need for treatment of Diabetes Mellitus
(treatment and complication screening) and health related factors, Kottayam district
51
4.12 Distribution of participants by unmet need for screening,
Kottayam district 52
4.13 Distribution of participants with all three conditions and unmet
need for treatment, Kottayam district 53
4.14 Distribution of participants with unmet need for screening when
diagnosed to have any one /two of the diseases, Kottayam district.
55
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List of Illustrations Figure No Title Page No
2.1 Flowchart of literature review process 7
3.1 Representation of sample selection process 24
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Glossary of Abbreviations
ACC American College of Cardiology
ADA American Diabetes Association
ADL Activities of Daily Living
AHA American Heart Association
ASHA Accredited Social Health Activist
BMI Body Mass Index
BP Blood Pressure
CVD Cardio Vascular Disease
DALY Disability Adjusted Life Years
DM Diabetes Mellitus
ED Emergency Department
HbA1C Glycated haemoglobin
HDL High Density Cholesterol
JNC Joint National Committee
LDL Low Density Cholesterol
MI Myocardial Infarction
NCD Non Communicable Diseases
NCDCP Non Communicable Diseases Control Programme
NPCDCS National Program for Prevention and Control of Cancer,
Diabetes Mellitus, CVD and Stroke
NPHCE National Programme for Health Care of Elderly
NSSO National Sample Survey Organisation
SAGE South Asian Growing Economics
SPSS Statistical Package for the Social Science
WHO World Health Organization
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ABSTRACT
Background: More than half of the people in the geriatric age group have history of
at least one chronic illness, majority of which are associated with the cardio vascular
system. Hypertension, Dyslipidemia, and Diabetes Mellitus are recognized risk
factors for cardiovascular disease morbidity and mortality. The early detection,
appropriate treatment and follow up of NCDs have been found to reduce the disease
burden and the associated complications. The study aims to assess the unmet need for
screening and treatment NCDs among older adults in Kottayam district.
Methods: A cross sectional study was conducted among the 420 older adults (60
years and above) in all 11 blocks of Kottayam district using a structured interview
schedule. Statistical analysis using proportions with appropriate stratification was
undertaken using SPSS Version 21.
Results: The unmet need for screening of dyslipidemia (45.5%) was the highest
among the screening and the unmet need was the most for treatment of diabetes
mellitus (72.0%). Employment status and education were found to be associated with
unmet need for screening of dyslipidemia, while education; employment status,
current means of sustenance and socio economic status were associated with unmet
need for screening of diabetes mellitus. The unmet need for screening of only
dyslipidemia was 22.4 percent. Among the participants with both hypertension and
diabetes mellitus more than three fourths (77.0%) had an unmet need for screening of
dyslipidemia.
Conclusions: Unmet need for screening of dyslipidemia was the highest among all
the three diseases. About one eight of those aged 60 and above have not at all been
screened appropriately for all the three diseases. Any programmatic effort needs to
address this to reduce the burden of NCD morbidity among the elderly.
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CHAPTER 1
INTRODUCTION
1.1 Background
The burden of Non-Communicable Diseases (NCDs) has been increasing over the years
and in 2008 it had accounted for more than 36 million deaths out of a total of 57 million
deaths worldwide. More than 80 percent of these NCDs consisted of only four categories
of diseases, cardiovascular diseases (CVDs), cancers, diabetes mellitus and chronic
respiratory diseases (Alwan et al., 2010;WHO, 2015).
NCDs are the single largest cause of both morbidity and mortality in most developing
countries (Boutayeb et al., 2013). The WHO global non communicable disease status
report of 2014 estimates that, almost 75 percent of the non-communicable disease deaths
and majority of premature deaths due to NCDs was reported from the low and middle
income countries (WHO, 2014). The low and middle income countries add up to more
than 80 percent of cardiovascular and diabetes mellitus deaths, and about 90 percent of
deaths from chronic obstructive pulmonary disease (WHO, 2010).
The annual NCD deaths are projected to continue to rise worldwide, and the greatest
increase is expected to be seen in low- and middle-income regions because of the rise of
impact of NCDs and the ageing of population (WHO, 2010). It is estimated that by the
year 2025, the majority of the elderly people worldwide will reside in developing
countries (Health for the Millions, 1999). NCDs account for nearly 90 percent of the
disease burden for the 60 plus population in low, middle and high income countries and
75 percent of the total deaths out of 35 million deaths from NCDs worldwide in 2004
(WHO, 2010).
Developing countries are thus likely to face an enormous burden of vulnerable elderly
population who are predisposed to chronic non-communicable diseases. More than 50
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percent of the geriatric age group people have history of at least one chronic illness,
majority of which are associated with cardio vascular system (Kishore et al., 2015).
Hypertension, dyslipidemia, and diabetes mellitus are recognized risk factors for
cardiovascular disease morbidity and mortality. The number of diabetics is projected to
increase to 69.8 million by 2025 (Kaveeshwar and Cornwall, 2014). Around 52 percent
of diabetes mellitus-attributable mortality worldwide occurs among the elderly ((Diabetes
Prevention Program Research Group et al., 2009). Globally, the number of hypertensive
individuals is expected to rise from 118 million in 2000 to 214 million in 2025 (Kearney
et al, 2005). India already has a very high proportion of the persons with diabetes mellitus
in the world, with 41 million persons living with diabetes mellitus (Joshi and Parikh,
2007).
The size of the elderly population in India currently stands at 103 million, constituting
about 8.6 percent of the total population.(Census, 2011) Within the Indian states, Kerala
ranks first in the population of elderly (60+) in the country, constituting 13 percent
elderly people out of total population (Census, 2011). This state is moving towards the
advanced stage of epidemiological transition characterized by high prevalence of NCDs
(Alam et al., 2012; Thomas and James, 2014).
Kerala is known to have the highest prevalence of diabetes mellitus among all the states
in India and the state has a high age adjusted mortality rate of cardiovascular diseases,
comparable to that of the United States (Mohan et al., 2007; Soman et al., 2011). A study
on the risk factor profile of NCDs in Kerala in the age group of 16 to 64 showed a
diabetic prevalence of 16.2 percent. Hypertension was 32.7 percent and cholesterol levels
above 200mg/dl were found in 56.8 percent of the population and there was low
awareness of hypertension with low rates of treatment and control (Thankappan et al.,
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2010). About 74 percent and 70 percent were not getting appropriately treated for
diabetes mellitus and dyslipidemia respectively (Sankar et al, 2015; Mathew, 2013).
The Kerala state has a programme for NCDs started in the year 2010 and has been
functioning for more than five years (NCDCP, 2010). In this Non Communicable
Diseases Control Programme (NCDCP), all people who are 60 plus are screened at sub-
centre level and the field. Accredited Social Health Activists (ASHA), are expected to
mobilize people for screening and follow up. Regular screening and follow up is available
weekly at sub centres.
The central government proposed to supplement the state’s programmes on NCD by
providing technical and financial support through National Program for Prevention and
Control of Cancer, Diabetes Mellitus, CVD and Stroke (NPCDCS) (NPCDCS, 2012).
Considering the specific needs of elderly in terms of accessibility, affordability, another
programme named National Programme for Health Care of Elderly (NPHCE, 2011) was
launched with the core strategy of community based primary health care approach
including domiciliary visits. The NPCDCS can use the common infrastructure/manpower
envisaged under the programme National Program for Health Care of Elderly (NPHCE)
for the early detection of cases, diagnosis, treatment, training and monitoring (NPCDCS,
2012).
The collective synergies of the programmes – NPHCE and NPCDCS, should help the
elderly meet their NCD care needs. It is imperative to identify the need fulfilled by
NPCDCS and National Programme for Health Care of Elderly (NPHCE) from a public
health perspective of both screening for (prevention/detection) and treatment. Such a
study will help the programme to expand its potential or fulfil its potential.
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1.2 Rationale
The costs of care and treatment are more for each elderly with NCDs irrespective of their
socio economic status. The early detection and proper treatment and follow ups of NCDs
have found to reduce the disease burden and associated complications and reduction of
cost in future. Disabilities resulting from NCDs are significant in old age resulting in
compromised quality of life measured in terms of the Activities of Daily Living (ADL).
So if the elderly in the early 60s are diagnosed or screened and treated appropriately, it
can add to the quality of life in coming years.
There is an existing programme by government of Kerala for control of NCDs - Non
Communicable Diseases Control Programme (NCDCP). The age group that is most likely
to benefit from the programme is the elderly (60+). Therefore this study can enable the
programme to identify extent of unmet needs for NCD care among the elderly and enable
them to plan better in future.
The national programme for health care of elderly (NPHCE) was launched in the year
2010-11. The guideline of this programme also included special provision for elderly in
the diagnosis and treatment of NCDs by collaborating with the NCDCP. By assessing the
unmet need in screening and treatment among elderly it can be seen if the special need of
elderly is covered in the two programmes with regard to NCDs.
Among the districts of Kerala according to census 2011, the second highest proportion of
elderly was found in Kottayam district (15.5%) (Census, 2011). Therefore the study
conducted in Kottayam district will be helpful in identifying the way forward in NCD
care among the older adult population of the district.
1.3 Research questions
• Are there unmet needs for screening and treatment of non communicable diseases
among the older adults?
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• What are the factors associated with the unmet need for treatment of non-
communicable diseases among them?
1.4 Objectives
• To assess the unmet need for screening and treatment of non-communicable
diseases among older adults in Kottayam district.
• To assess the factors associated with the unmet need for treatment of non-
communicable diseases among the older adults in Kottayam district.
1.5 Chapterization plan
Chapter one of this dissertation gives a brief overview of introduction, rationale for the
study, research question and objectives. Chapter two provides a summary of the relevant
literature that was reviewed. Chapter three describes the methodology of the study
including the interview tools, data management, data analysis, variables, ethical
considerations and expected outcomes. Chapter four gives the results along with the
descriptive tables. Chapter five includes the discussion of the results, the conclusions,
strength and limitations of the study and policy implications.
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CHAPTER 2
REVIEW OF LITERATURE
The literature search was done on PubMed and Google Scholar for articles published
between 2000-2016 using the following search terms “Elderly”, “Non Communicable
Diseases”, “Screening”, “Treatment”, “Awareness”, “Control”, “Diabetes Mellitus”,
“Hypertension” and “Dyslipidemia”. Additionally the bibliography section of each article
was scanned to identify articles that might have been missed during search. After
identification and reviewing of the articles about six themes were identified and they were
grouped into diabetes mellitus, hypertension, dyslipidemia, these diseases in
combinations and the factors associated with health care seeking of NCDs.
This chapter summarizes the available literature regarding NCDs among the older adults.
It mainly falls into the headings, morbidity related to non-communicable diseases in
elderly, diabetes mellitus among elderly, hypertension among elderly, dyslipidemia
among elderly, diabetes mellitus, hypertension and dyslipidemia among elderly and the
factors associated with health care seeking for diabetes mellitus, hypertension and
dyslipidemia
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Figure 2.1: Flowchart of literature review process
2.1. Morbidity related to Non Communicable Diseases (NCDs) among elderly
A study conducted in all the six SAGE (South Asian Growing Economics) countries
among adults aged 50 and above found that India exhibited the highest undiagnosed
disease rates (35.2%) of NCDs (Arokiasamy et al., 2015).
The prevalence of one or more chronic diseases among elderly in India ranged from 50
percent to 63 percent. The majority of chronic diseases were related to musculoskeletal
and cardiovascular system. The more prevalent chronic non communicable diseases were
arthritis, high blood pressure, cataract and diabetes mellitus (Kishore et al., 2015; Mini,
2014).
Kerala had the highest prevalence of elderly having at least one NCD - 80.1 percent
(Mini, 2014). Among the elderly in Kerala, the most common NCDs were hypertension
Search from Pubmed and Google Scholar yielded 234 results
Records were screened for eligibility and full text access
Additional search for reports and guidelines on disease screening and treatment yielded five documents
43 key studies were identified (of
diabetes mellitus, of hypertension, of
dyslipidemia, regarding health care
seeking)
48 studies were included in the final review
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(39.7%) and diabetes mellitus (28.1%) and the major reason for hospitalization was
NCDs (Alam et al., 2012).
2.2. Diabetes Mellitus among elderly
According to the Global Report on diabetes mellitus by WHO released on the world
health day 2016, globally about 422 million adults were living with diabetes mellitus in
the year 2014, compared to 108 million in 1980. The age-standardized global prevalence
of diabetes mellitus has doubled since 1980, rising from 4.7 percent to 8.5 percent in the
adult population (WHO Global report on Diabetes, 2016).
A study from Kazakhstan in 2015 found that the diabetes mellitus in elderly (50-75 years)
was associated with increasing age, male sex, hypertension, obesity, increased stress,
family history and urban residence (Supiyev et al., 2016).
India ranks second in the world with 64.5 million diabetic patients in 2014 which was
only 11.9 million in 1980 (NCD Risk Factor Collaboration, 2016). A study on high
prevalence of type 2 diabetes mellitus and other metabolic disorders in rural central
Kerala showed a prevalence of 28.2 percent among the 60 plus population (Vijayakumar
et al., 2009).
2.2.1 Prevalence, awareness, treatment and control of diabetes mellitus among
elderly
The changing trends of awareness, treatment and control of diabetes mellitus over a
decade (2001-2010) were examined among Chinese elderly and this study found that the
awareness and prevalence remained high over the decade. There was an increase in
treatment (18.3%) while control rate of diabetes mellitus decreased (Liu et al., 2016).
The prevalence of diabetes mellitus among elderly varied 25.9 percent among the 60 plus
age group (only 8.6 percent were aware about their diabetic status and 17.3 percent were
diagnosed during the survey), to 12.5 percent in elderly aged 50 and above (72.3 percent
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of them were aware of their condition) in Kathmandu and Kazakhstan respectively. More
than half (65.6%) were on treatment and 27.7 percent had controlled blood sugar levels
(Chhetri and Chapman, 2009; Supiyev et al., 2016).
The awareness, treatment and control of diabetes mellitus were considerably higher in the
urban residents and among women (Liu M et al 2016). Lack of awareness of diabetes
mellitus was associated with age, disturbed sleep, and family history of hypertension
(Chhetri and Chapman, 2009). The higher treatment rates of diabetes mellitus were
related to higher education and positive family history (Supiyev et al., 2016).
The prevalence, awareness, treatment and control of diabetes among elderly persons were
studied in an urban slum of Delhi in 2009-2010, which found that the prevalence was
18.8 percent. Only 36 percent of the diabetic participants were aware of their condition
and 62.5 percent of them were on treatment. The awareness, treatment and control were
higher among women (Singh et al., 2012).
Two cross sectional studies done among adults to assess the prevalence of undetected
diabetes mellitus found 10.5 percent and 4.1percent of newly diagnosed diabetic cases in
Kerala and Karnataka respectively. The newly detected cases were higher among men
(Joseph et al., 2015; Deepthi et al, 2013).
A cross sectional study on the adherence to medications in adult diabetic patients in rural
Kerala in the year 2010 found that the prevalence of ‘poor adherence’ was 74 percent.
Poor adherence was higher among people using oral hypoglycaemic agents, who had low
socio economic status, whose blood sugar monitoring was irregular; those patients who
received only limited diabetes mellitus management instructions from the concerned
health personnel, those who resorted to only symptomatic management, and those who
did not receive family member's aid to remember medications. The study also found that
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those who did not monitor blood sugar regularly were four times more likely to have poor
adherence compared to their counterparts (Sankar et al., 2015).
2.2.2 Complication screening of diabetes mellitus
Three major studies were identified which aimed to assess the knowledge regarding
complications and undertaking complication screening among the patients with diabetes
mellitus.
A study from Singapore in the year 2002 to determine knowledge of diabetics visiting the
Emergency Department (ED) and to determine the diabetics' complication knowledge
versus practice gap in patients aged 15 and above found that the younger diabetics had
more scores of knowledge compared to older patients. More than 50 percent of people
with diabetes mellitus practised self-care but 25 percent were unaware of need for home
glucose monitoring and regular ophthalmic check-ups. Only 21.2 percent diabetics
performed home glucose monitoring while 42.1 percent of the diabetic patients did not
monitor glucose even when they knew that they should perform regular home glucose
monitoring (Tham et al., 2004).
The reasons for not receiving HbA1C tests were assessed in a study from Farmington in
the year 2003 among adult diabetic patients. About thirty-three percent of respondents
reported having diabetes mellitus and receiving fewer than two HbA1C (Glycosylated
haemoglobin) tests in the past year. The major reasons reported for not doing at least two
HbA1C tests as recommended by the American Diabetes Association (ADA) were that
the respondents were unaware that the test is recommended (49%), 38 percent were not
informed by their treating physician regarding the need for the test, 33 percent had never
heard of the HbA1C test while 19 percent were not seen on a regular basis by their
physician (Delaronde, 2005).
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A study from Kerala in 2013 among people aged 40 and above, aimed to assess the
knowledge about ophthalmic complications of diabetes mellitus found that 71.3 percent
knew that retinopathy is a complication of diabetes mellitus. But only 9.6 percent had
undergone a check-up for diabetic retinopathy and only 9.8 percent were following up eye
check-up regularly. In this study 77.2 percent also reported that they would go for an eye
check-up if only they have an eye problem (Hussain et al., 2016).
2.3. Hypertension among elderly
In the year 2000, nearly 26.4 percent of the world's adult population was hypertensive, the
actual numbers added to about one billion and by 2025, the number is expected to go up
to 29.2 percent, or about 1.56 billion people worldwide will be hypertensive (Kearney et
al., 2005).
A community based study from Singapore in the year 2009 on awareness treatment and
control of hypertension among elderly (60 plus), found a high prevalence of hypertension
(73.9%). Among those with hypertension, 30.8 percent were unaware that they had
hypertension, about 32 percent were not getting any treatment for it and 75.9 percent had
suboptimal control of their blood pressure. Among those aware of their hypertension,
about 98 percent were getting treated. But nearly 64.5 percent of treated hypertensive had
suboptimal control. Lack of awareness, treatment and control of hypertension was related
to age, gender, ethnicity, education; housing type, body mass and diabetes mellitus
(Malhotra et al., 2010).
A study among elderly aged 50 and above from Dakar, Senegal in 2009 reported that the
prevalence of hypertension was 65.4 percent and more than half of them were unaware of
their hypertensive status. Among those who were aware 29.4 percent were not getting
treated. The Blood Pressure (BP) was not controlled among 82.6 percent of those treated.
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The only factor associated with awareness, treatment and control of hypertension was the
frequency of doctor visits (Macia et al., 2012).
The WHO 2008 estimates on NCDs showed that, the high blood Pressure prevalence in
Indian adults was 32.5 percent (33.2 percent in men and 31.7 percent in women) (WHO,
2011).
The prevalence of hypertension among elderly in India varied from 28 percent in Tamil
Nadu, 40.5 percent in Puducherry, 50 percent in Raipur, to 53.5 percent in West Bengal.
The awareness of hypertension also varied among them. The study from Tamil Nadu in
the year 2009 showed that only 25 percent were aware of their condition while the study
from Raipur in 2014 and from Puducherry in 2011 had the awareness rates 50 percent and
62 percent respectively (Alam et al., 2015;Chinnakali et al., 2012;John et al., 2010;Pratim
et al., 2012).
All elderly were visiting the doctor once a month and 80 percent had their BP (blood
pressure) checked in 15 days (Alam et al., 2015; Jain and Sinha, 2015). About three
quarters of those diagnosed with hypertension had their BP checked in past 20 days of
interview. On an average, the elderly with hypertension were visiting the doctor once in a
month. Around 48 percent reported that they had missed at least one dose of anti-
hypertensive in the last three month period. About 15 percent had reported that they
skipped anti-hypertensive for a week and more (Chinnakali et al., 2012).
In a study on prevalence, awareness, treatment and control of hypertension in an elderly
community based sample in Kerala in the year 1998, the overall prevalence of
hypertension was 51.8 percent, which increased with age. The awareness about
hypertension status was only 45 percent, 42.7 percent was on treatment and only 11
percent had controlled blood pressure. The correlates of hypertension among elderly
13
includes sex, smoking status, rural residence, marital status, increasing age Body Mass
Index (BMI), lower education and physical activity (Kalavathy et al., 2000).
2.4. Dyslipidemia among elderly
Globally, one third of the ischemic heart diseases are due to the high cholesterol levels.
Approximately 2.6 million deaths which are 4.5 percent of the total deaths are estimated
to be caused by the raised cholesterol levels. This is also responsible for 29.7 million
disability adjusted life years (DALY). WHO report says that 10 percent reduction in
serum cholesterol in men aged 40 has been reported to result in a 50 percent reduction in
heart disease within five years; the same serum cholesterol reduction for men aged 70
years can result in an average 20 percent reduction in heart disease occurrence in the next
5 years. In 2008 the global prevalence of raised total cholesterol among adults was 39
percent and the prevalence of raised cholesterol was higher among females (WHO, 2016).
A cross sectional study from Beijing in the year 2008 among 18-79 year old population
found the prevalence of dyslipidemia was 35.4 percent. Among all the participants with
dyslipidemia, 22.2 percent were aware of the diagnosis, only 10.2 percent were receiving
treatment, and 3.8 percent had controlled levels of dyslipidemia. Of those who were
aware of dyslipidemia diagnosis, 46.1 percent were on treatment; 51 percent had modified
their lifestyle, and about one quarter was neither receiving treatment nor had they
modified their lifestyle. Dyslipidemia was found to be associated with male gender,
increasing age, a family history of dyslipidemia, higher levels of education, current
smoker, overweight and obesity, high waist circumference, hypertension and diabetes
mellitus (Cai et al., 2012).
A cross sectional study was done in Malaysia in the year 2016 on hypercholesterolemia
among elderly (60 plus). This study reported the awareness for hypercholesterolemia to
be 40 percent among the elderly. The prevalence of Hypercholesterolemia was 55.4
14
percent. More than three fourths of the participants (77.7%) had treatment with
medication. The control rate for hypercholesterolemia was 53.8 percent. The factors
associated with higher awareness rate of hypercholesterolemia were being urban
residents, having secondary education level and Indian ethnicity. The factor associated
with higher treatment rates was employment status as government/semi government
employees and the factors associated with higher control rate were male gender and
Indian ethnicity (Ambigga et al., 2016).
In a study conducted within a representative population of three states of India (Tamil
Nadu, Maharashtra and Jharkhand) and one Union Territory (Chandigarh) among 20
years and older population, the overall prevalence of dyslipidemia was 79 percent and the
dyslipidemia rates were higher among females. In this study hypercholesterolemia was
associated with those aged 60 and above, urban residence, high income, overweight,
generalized obesity, abdominal obesity, fat and oil intake, diabetes, pre diabetes and
hypertension (Joshi et al, 2014).
The prevalence of 37 percent of hypercholesterolemia was found in the general
population, in a study on prevalence of metabolic disorders in Kerala in 2009
(Vijayakumar et al., 2009).
A study on the factors associated with medication adherence among adult dyslipidemia
patients in Kerala in 2013, only 30 percent of the study population was found to be taking
their drugs properly, mostly males. The adherence to drugs was found to be significantly
associated with co morbidities (Mathew, 2013).
2.5. Diabetes Mellitus, Hypertension and Dyslipidemia
This segment reviews the studies which deal with prevalence, treatment, awareness and
control of diabetes mellitus, hypertension and dyslipidemia concurrently.
15
A study from Iran in the year 2000-2001 among adults aged more than or equal to 19
years showed that the prevalence of hypertension, dyslipidemia and diabetes mellitus was
17.3 percent, 66.3 percent and 5.6 percent respectively. Awareness, treatment and control
of hypertension were 40.3 percent, 35.3 percent, and 9.1 percent respectively. Only 14.4
percent were aware of dyslipidemia status, while 7.1 were getting treated and 6.5 percent
had controlled levels of dyslipidemia. About 54.6 percent of diabetics were aware of their
disease and 46.2 percent were under treatment (Shirani et al., 2009).
A cross-sectional population-based cardiovascular risk factors survey was conducted
between 2007 and 2009 in Luxembourg. The prevalence of lack of awareness of diabetes
mellitus was 32 percent, the prevalence of lack of awareness of hypertension and
dyslipidemia was 60 percent and 85 percent respectively. About four percent were
diagnosed to be diabetic, 35 percent had hypertension and 70 percent were diagnosed
dyslipidemic during the survey.
With respect to management of these three conditions, diabetes mellitus was more likely
to be treated when compared to hypertension and dyslipidemia. Among diabetic subjects
who constituted four percent of the total population, three percent were treated. In
contrast, 22 percent of the hypertensive participants (35 percent of the population) were
not treated and 13 percent treated. When 70 percent of the total study population had
dyslipidemia only 9 percent were getting treated.
Regarding the determinants of awareness, treatment, and control, increasing age and BMI
were the protective factors against lack of awareness of hypertension and dyslipidemia.
Having a family history decreased the risk of lack of awareness of hypertension, while,
not having a family doctor doubled the odd of being unaware of hypertension. Poor health
perception reduced significantly the risk of lack of awareness of dyslipidemia.
16
In the Framingham group, the risk of developing CVD within 10 years was moderate to
high, varying from 17 percent, 27 percent and 62 percent among those with
unaware/untreated dyslipidemia, hypertension and diabetes mellitus respectively (Alkerwi
et al., 2013).
2.5.1. Diabetes Mellitus and Dyslipidemia
A retrospective cohort study from Canada from 2004 to 2005 among patients admitted
with first Myocardial Infarction (MI) on quality of diabetes mellitus and hyperlipidemia
screening before a first MI found that 27.1 percent did not get serum cholesterol
screening in the five years prior their MI and 27.5 percent of patients did not receive
fasting blood glucose in the three years before their MI. Women were more likely to be
screened than men. The screening rates increased with women and increasing age. The
number of primary care visits and the likelihood of being screened was positively
associated (Lugomirski et al., 2013).
2.5.2 Diabetes Mellitus and Hypertension
A study from Delhi among 60 plus age group in the year 2002, reported that diabetes
mellitus was seen in 24 percent and in the same population about 67 percent were
hypertensive. In the participants with diabetes mellitus, 62.3 percent were on treatment
and 33.6 percent were under control; while out of 67 percent of those with hypertension,
41 percent were under treatment and only 33 percent of them had their blood pressure
under control (Goswami et al., 2016).
A cross sectional study from rural Tamil Nadu among elderly aged 60 and above showed
that the overall prevalence of diabetes mellitus among study population was 36 percent
and the prevalence of hypertension was 59 percent. Among diabetes, the prevalence in
males was 22 percent and in females it was 15 percent. Among the hypertensives, the
prevalence in males was 33.3 percent while in females it was only 26.2 percent. Age,
17
BMI and smoking were associated with the prevalence of diabetes mellitus and
hypertension (Radhakrishnan and Balamurugan, 2013).
2.6. Factors associated with health care seeking for diabetes mellitus, hypertension
and dyslipidemia
The health seeking behaviour was found to be associated with the following factors
2.6.1 Health care seeking and age
Age was found to be positively associated with the health seeking behaviour and unmet
need for health care among elderly. Since increasing age is also related to the increasing
dependency, unmet need for treatment is related to the increasing age of the respondent.
The prevalence of NCDs were more with increase in age and at the same time the health
care seeking had a decreasing trend with increasing age (Lee et al., 2015).
Age was the main risk factor for unmet health care needs, independent of co-morbidities
and loss of autonomy, with a more than three times increase in the age group greater than
90 years compared with the age group 70–80 years (Herr et al., 2014).
Among older persons not seeking treatment for their medical condition, most considered
the morbidities as an age related phenomenon (Sharma et al., 2013).
2.6.2 Health care seeking and gender
A community based study among elderly in Uttarakhand on chronic morbidity and health
seeking behaviour reported that multiple morbidities were more frequent among men
when compared to women also the health seeking behaviour was more in elderly males
while females used home management and other remedial measures (Kishore et al.,
2015).
The awareness of government facilities was less while irregularity of medicine intake was
more among women according to a study from Mangalore in 2013 which was conducted
in elderly population aged 60 and above (Joseph et al., 2015).
18
2.6.3 Health care seeking and socioeconomic and employment status
Better economic conditions positively influence the likelihood of utilizing health care
services. A positive relation was observed between monthly per capita expenditure
quintiles and health care utilization among older widows was reported from a study on
morbidity pattern and health seeking behaviour among older widows using NSSO data
2004 (Agrawal and Keshri, 2014).
The study on the awareness of government facilities among elderly showed that those
belonging to upper middle socio economic status and those currently working had higher
awareness (Joseph N et al., 2015).
A study from Odisha in 2011 among elderly showed that the health seeking behaviour of
the elderly was found to be associated with dependency that is, dependant older adults
were found to have higher prevalence of multi morbidities and higher unmet need for
health care (Banjare and Pradhan, 2014).
2.6.4 Health care seeking and level of education
A study from India using National Sample Survey Organisation (NSSO) 60th round data
on horizontal equity in health care service utilization, reported that the likelihood of
seeking health care services increased significantly with the level of education. Compared
to illiterates, elderly persons with higher education have reported 15 percent higher health
care utilization (Joe et al., 2015).
The awareness regarding health care services was more in well-educated (graduates and
above) respondents (Joseph et al., 2015). A need assessment study among elderly in
Bhopal showed that the secondary or higher secondary level educated elderly had higher
coverage (58%) of health insurance compared to elderly with other level of education
(Help Age India, 2009).
19
2.6.5 Health care seeking and presence of co morbidity
A study from Uganda in 2010 among people aged 50 and above reported that the
likelihood of seeking health care in last one month was more among those who had other
co morbidities (Wandera et al., 2015).
2.6.6 Health care seeking and disability
The health care seeking was lower in people with disability as per the study mentioned
earlier from Uganda. About 70 percent of those disabled had reduced access to health
care. The access to health care was lower among those with vision problems (70%),
walking difficulties (63%), and memory problems (55%). About 55 percent with self-care
challenges and 49 percent with communication problems also had reduced access to
health care (Wandera et al., 2015).
2.6.7 Health care seeking and marital status and living arrangement
In treatment seeking behaviour, the older widows living with family were more likely to
seek treatment seeking compared to those living alone (Agrawal and Keshri, 2014).
Among the elderly, those relatively younger, those who lived with others and were
married were more likely to access health care when compared to their older/living
alone/single counterparts in Uganda in 2010 (Wandera et al., 2015). The couple status
was a protective factor against unmet health care needs in French people aged 70 and
above in 2008-2010 (Herr et al., 2014).
2.6.8 Health care seeking and accessibility, availability and affordability
The most common barriers reported for seeking health care were the doctor’s lack of
responsiveness to patient concerns, medical bills, transportation, and street safety in a
study from U.S which aimed to identify the patterns of use and barriers to health care
among elderly aged 65 years and older (Fitzpatrick et al., 2004).
20
A cross sectional study among elderly in Shimla in 2010-2011 reported that people who
were not seeking health care perceived the health services were too far away (Sharma et
al., 2013).
2.7. Definitions
2.7.1 Screening of NCDs
Hypertension- for 18 plus, if blood pressure less than 120/80 mm Hg screen every
two years. Yearly screening if systolic blood pressure is 120-139 mm Hg or
diastolic blood pressure is 80-89 mm Hg (Armstrong and Joint National
Committee, 2014).
Diabetes Mellitus- for 45 plus, screen once in a year (ADA, 2016).
Dyslipidemia- screen once in a year (Stone et al., 2013).
2.7.2 Treatment of NCDs
Hypertension -definition for 60 plus is >150/90mmHg. If diagnosed, BP must be
monitored at least every six weeks (Armstrong and Joint National Committee,
2014).
Diabetes Mellitus- if diagnosed, once in six weeks fasting blood sugar, at least
every six months HbA1C, once in a year complication screening for nephropathy,
neuropathy and retinopathy need to be checked. The target HbA1C level is less
stringent for older people and it is less than eight percent. These can vary with
presence of co morbidities, complications and the severity of the disease (ADA,
2016).
Dyslipidemia- total cholesterol≥200, Triglyceride≥150, LDL≥100, HDL≤50.
Initial fasting lipid panel followed by a second panel 4-12 weeks after initiation of
statin therapy to determine patient’s adherence. Thereafter assessment should be
performed 3-12 months as clinically indicated (Stone et al., 2013).
21
CHAPTER 3
METHODOLOGY
3.1. Study design
The study design was a community based cross sectional study. This design had been
used in similar studies and it was also the design of choice because of the limited time
available to complete the data collection for the dissertation.
3.2. Study setting
The study was conducted among the older adults in Kottayam district. The Government
of India has adopted ‘National Policy on Older Persons’ in January, 1999 defining elderly
as a person who is of age 60 years or above.
The study was conducted among the elderly of both sexes who were residents of
Kottayam district for the past six months. Because of limitation in time and resources the
study was limited to Kottayam district which was selected because of investigator’s
convenience.
3.3. Sample size
The sample size was calculated using Open Epi version 3.03a. The probability of not
getting treated while having NCDs was considered for calculating sample size. The
conditional probability was calculated by multiplying the two probabilities that is the
probability of having the disease and the probability of not getting treated as shown in the
table 3.1.
22
Table 3.1 Computation of conditional probability for estimation of sample size
NCDs
Prevalence of the
NCDs
Proportion not
getting treated
Probability of not
getting treated while
having the disease
Diabetes Mellitus 0.28(Vijayakumar
et al., 2009)
0.74(Sankar et al.,
2015)
0.21
Hypertension 0.36(Vijayakumar
et al., 2009)
0.80(Thankappan
et al, 2006)
0.24
Dyslipidemia 0.37(Vijayakumar
et al., 2009)
0.70(Mathew,
2013)
0.26
The lowest conditional probability among the three non-communicable diseases; diabetes
mellitus, hypertension and dyslipidemia was taken for sample size calculation. Diabetes
Mellitus had the lowest probability of getting treated - 0.21. With 95 percent confidence
interval, a precision of 6 percent and design effect 2, the sample size was calculated as
354. Considering 15 percent non response rate, the sample size was rounded off to 420.
Justification: The probability of having diabetes mellitus and not getting treated among
the older adults in Kerala was considered for sample size calculation. This
accommodated the sample size requirements for other conditions as well.
3.4. Sample selection
This study used a multistage cluster sampling. The total population in Kottayam district
was 1, 979,384 (Census, 2011). There were 11 blocks in Kottayam district. From the
district all eleven blocks was selected. The population of each block was taken from
census 2011 data and the number of sampling units to be collected from each block was
calculated proportionate to population in each block. The number of units collected from
each block were- Uzhavoor-30, Lalam-20, Erattupetta-30, Ettumanoor-50, Vaikom-30,
Kaduthuruthy-40, Pallom-60, Pampady-30, Madappally-50, Vazhoor-30 and
Kanjirappally-50. The cluster size was 10 and from each block, panchayats were
23
randomly selected from within which a cluster size of 10 was to be acheived. Number of
panchayats visited from each blocks were -Uzhavoor-3, Lalam-2, Erattupetta-3,
Ettumanoor-5, Vaikom-3, Kaduthuruthy-4, Pallom-6, Pampady-3, Madappally-5,
Vazhoor-3, and Kanjirappally-5.
From each panchayat one ward was randomly selected. This resulted in selection of 42
wards and 10 units from each ward. From a central location in the ward that is a bus stop
or main shop in the ward, by spinning a pen, the direction in which to move was decided.
The first house encountered in that direction was selected and then, every third house was
selected. Screening was done using a set of uniform questions to identify the eligible
participants in the household. In houses where there was more than one person in the age
group more than 60 years; KISH table was used to select the specific respondent.
If the specific respondent was not available in the house, follow up was done to include
the person in the study. If there were no eligible persons in the visited household, the next
third household was visited, until 10 interviews were completed in a ward.
24
Figure 3.1.Representation of sample selection process
Kottayan
(11 blocks)
Erattupatta3 out of 7 Grama
panchayats
Vazhoor 3 out of 5 Grama panchayats
Lalam2 out of 6 Grama
panchayats
Kanjirapally5 out of 7 Grama
panchayats
Madapally5 out of 7 Grama
panchayats
Vaikom3 out of 6 Grama
panchayats
EttumanoorAll the 5 Grama
panchayats
Kaduthuruthy4 out of 7 Grama
panchayats
Uzhavoor3 out of 8 Grama
panchayats
Pallom 6 out of 7 Grama panchayats
Pampady3 out of 6 Grama
panchayts
One ward
from each
Grama
panchayat
(total of
42
clusters)
25
3.5 Subject Selection
Following were the selection criteria for the study participants.
• Inclusion criteria
▫ Older adults of both sexes 60 years or older residing in Kottayam district
for last six months were selected for the study.
▫ The older adults who are willing participate in the study.
• Exclusion criteria
▫ Older adults who were terminally ill were excluded from the study.
▫ Older adults who were not able to answer the questions were not selected.
3.6. Data collection tool
Data was collected using an interview schedule. The interview schedule was structured
based on the literature review on various factors associated with unmet need and based on
the operational definitions of the selected NCDs. This structured interview schedule was
pre-tested and then translated into the local language. The pretested interview schedule
was translated into Malayalam and back translated to English by the Principal
Investigator (PI).
The interview scheduled captured the basic demographic features of the respondent
including age, sex, religion socioeconomic status, occupation, marital status, and living
arrangement.
The current health status including the status of health care received, family history,
presence of chronic diseases and disability, were included in the second section.
The diabetes mellitus, hypertension and dyslipidemia status of the respondent was
included in the next section followed by questions for screening status and treatment
position of the above non-communicable diseases.
26
3.7. Data collection
As has been mentioned earlier, a structured interview schedule was used to collect data.
The interview was carried out by the PI herself for all the respondents.
Data collection was done from June 15 to August 31, 2016. The participants were
identified as described in the section of sample selection procedure. Information sheet
and consent form were distributed first to the selected participant and if he/ she
consented, the interview was conducted. Privacy was ensured during the interview to the
extent possible and confidentiality of all the information was maintained.
3.8. Ethical considerations
The study was carried out only after review and approval by the Ethics Committee of
Sree Chitra Tirunal Institute for Medical Sciences and Technology (Ref no-
SCT/IEC/909/MAY-2016).
Confidentiality: The identity of the participant was kept confidential. Each participant
was given a unique identification number and no other identifiers were retained. All the
copies of filled interview schedules, and consent forms will be kept under the custody of
the PI.
Consent: Written informed consent was obtained from the participants before
administering questionnaire and details about the investigator were given to each
participant. The participants had the freedom to refuse at the outset or during any stage.
3.9 Data Storage
All data including the consent forms are secured by the PI, who shall bear sole
responsibility for keeping the data secure and for any breach of confidentiality. All
completed interview schedules, consent forms would be destroyed upon completion of
three years from the date of acceptance of the thesis in keeping with regulatory
requirements (ICMR, 2006).
27
3.10 Data Entry
Data entry and cleaning was done using Epi Data version 3.1 software and Microsoft
excel version 2010 and exported to SPSS version 21 in the .sav format.
3.11 Data Analysis
Data was analyzed using SPSS, version 21. The data was analyzed for the proportion of
older people with unmet need for screening and treatment of diabetes mellitus,
hypertension and dyslipidemia. Descriptive statistics were computed. All the open -
ended questions was translated into English and systematically grouped thematically for
quantification. Then further bivariate and multivariate stratified analysis was done.
3.12 Variables
3.12.1 Dependent variables
Unmet need for screening of dyslipidemia
1. If the participant has never been screened for blood cholesterol level
2. If the screening for dyslipidemia was before one year/the participant does not
check the blood cholesterol level even once a year
3. If the cholesterol level was abnormal and the participant did not visit any health
facility for treatment
If any of these three conditions were present unmet need for screening of dyslipidemia
was identified.
Unmet need for screening of hypertension
1. If the participant has never been screened for blood pressure level
2. If the screening for hypertension was before one year/the participant does not
check the blood pressure level even once a year
3. If the blood pressure level was abnormal and the participant did not visit any
health facility for treatment
28
If any of these three conditions were present unmet need for screening of hypertension
was identified.
Unmet need for screening of diabetes mellitus
1. If the participant has never been screened for blood sugar level
2. If the screening for diabetes mellitus was before one year/the participant does not
check the blood sugar level even once a year
3. If the blood sugar level was abnormal and the participant did not visit any health
facility for treatment
If any of these three conditions were present unmet need for screening of diabetes
mellitus was identified.
Unmet need for treatment of dyslipidemia
1. Diagnosed with dyslipidemia before six months and has checked blood cholesterol
level at least once in last six months
2. If the doctor’s advice regarding elevated cholesterol level is treatment and the
participant is not taking any treatment.
If any of these two conditions were present unmet need for treatment of dyslipidemia was
identified.
Unmet need for treatment of hypertension
1. If the participant is diagnosed to have hypertension before six weeks since the
date of interview and not checked the blood pressure in last six weeks
2. If the participant does not check the blood pressure at in least 1-3 months interval
during a year
3. If the doctor’s advice regarding elevated blood pressure level is treatment and the
participant is not taking any one of the treatments.
29
If any of these three conditions were present unmet need for treatment of hypertension
was identified.
Unmet need for treatment of diabetes mellitus
1. If the participant is diagnosed to have diabetes mellitus before six weeks and not
checked the blood sugar level in last six weeks
2. If the participant has not checked blood sugar level at least one to six months in
last one year
3. If the doctor’s advice regarding elevated blood sugar level is treatment and the
participant is not taking any one of the treatments.
4. The participant is diagnosed with diabetes mellitus for more than a year and not
having any one of the complications of diabetes mellitus such as diabetic foot,
retinopathy, neuropathy and nephropathy and has not checked HbA1C, vision
testing and kidney function test in the last one year.
If any of these four conditions were present unmet need for treatment of Diabetes
Mellitus was identified.
Factors associated with unmet need for treatment of dyslipidemia/hypertension/diabetes
mellitus
The reasons for not taking the prescribed treatment for dyslipidemia/
Hypertension/Diabetes Mellitus.
3.12.2 Independent variables
Age- Age of the participant. It was regrouped in to three categories. 60 -69 years, 70 -
79 years and 80 plus years to see the variation of outcome variable with advancing
age.
Sex- Participants were divided into male and female.
30
Education- The highest level of education attained by the participant-no schooling,
Primary school (class 1-7, High school (8-10 classes), Higher secondary, Degree, PG
and above and others.
Marital status- Marital status of the participant-Not married, married, widowed,
divorced, separated and others.
Living arrangement- living arrangement of the participant-(spouse, spouse and
children, living alone, children only, with relatives)
Occupation-The present occupation of the participant(retired, daily wages, self
employed, unemployed, keeping house and others) -The past occupation of the
participant(salaried employment, daily wages, self-employment, unemployed,
homemakers, others)
Current means of sustenance- Income from own current work, income from past
work, supported by children residing in the house, supported by children residing
elsewhere, supported by other relatives and others
Socioeconomic status
High income
1. If the household own a computer and has got internet connection
2. The type of flooring is marble/granite/tile
3. The monthly household expenditure is more than 15,000INR
A household was categorized into this socioeconomic status group if any of the two
among the three criteria was satisfied.
Middle income
1. If the household own a computer and does not have internet connection or if the
household does not have a computer
2. The type of flooring is marble granite, tile or cement/red oxide
31
3. The monthly household expenditure is more than 7500-15000INR
A household was categorized into this SES group if any two among the three criteria was
satisfied.
Low income
1. The household does not own a computer
2. The type of flooring is mud/cow dung
3. The monthly household expenditure is less than 7500INR
A household was categorized into this socio economic status group if all three criteria
were satisfied.
Disability- If the participant was experiencing any of the major disabilities-impaired
vision, impairment in hearing, restrictions due to musculoskeletal impairment or any
other disabilities.
Health care received- If the participant was not receiving the health care that he/she
thinks is needed for health problems.
Family history- If any members of the participant’s family had a diagnosis of diabetes
mellitus, dyslipidemia, or hypertension.
History of any other diseases- If the participant was having any other diseases than
dyslipidemia, hypertension and diabetes mellitus
Means by which blood sugar/ /blood pressure was checked- The means by which the
participant checked their blood pressure/blood sugar/ blood sugar level- From doctor
during consultations, from the nearby health facility, from the lab and any other
means.
32
3.13. Expected outcomes
In keeping with the described definitions of dependent variables, proportion of elderly
who are not screened for any of the NCDs –diabetes mellitus, hypertension or
dyslipidemia will be estimated for the study. Also the proportion of elderly who are
diagnosed to have these diseases and not fulfilling the guidelines for treatment or not on
regular follow ups will be obtained. The reasons for not taking treatment if diagnosed
with any of the diseases will be determined in the study.
33
CHAPTER 4
RESULTS
This chapter describes the findings of the study. These are presented in terms of the
profile of the participants, a description of the outcome variable of unmet need, and lastly
by a narrative of the overlap in unmet need for diabetes mellitus, hypertension and
dyslipidemia examined. The chapter also includes the appropriate bivariate analysis of the
outcome variables against socio-economic and health care related factors. Stratified
analysis has been used to explain the potential for unmet need for screening for any and
all of the three conditions.
A total number of 901 households were visited to list 556 eligible subjects for the study.
Using KISH (a statistical table to identify one randomly selected participant when more
than one are identified in any context), 420 participants were selected from among these.
All of them consented for the study. Therefore, the non response rate was zero, even
though the anticipated non response rate was 15 percent.
4.1 Characteristics of the studied group
This section has been divided into two; the first describes the basic profile of the
participants and the second section lists the other contextual health factors related to the
three study conditions, viz. dyslipidemia, diabetes mellitus and hypertension, such as
disability, family history of NCDs and experience of any other chronic conditions.
4.1.1 Profile of the participants
Table 4.1 shows the distribution of socio-demographic characteristics of the study
participants. The overall mean (SD) age of the group was 69.9 (8.5) years. The range in
age of the group was between 60 years to 98 years. More than half of the study group
belonged to the age group 60-69 years (56.9%), about twenty five percent belonged to age
34
group 70-79 years and the percentage of participants who belonged to the age group of 80
plus was 17.4 percent.
Females outnumbered males in the study sample. According to the census 2011, in
Kottayam district the percentage of males above 60 years of age was 46.7 and the female
population was 53.3 percent. The proportion of males and females in the study group are
just about the same as that of the census figures for Kottayam district (Census, 2011).
A majority of the participants (more than half) were Christians, about 38 percent were
Hindus and only five percent were Muslims. Almost 38 and 36 percent had primary
school and high school education respectively and about 10 percent were graduated.
About four percent of these older adults were illiterate.
Currently married people formed the majority of the participants (71.2 %) and there were
no divorcees in the study group. More than one quarter of the participants were widowed.
More than half of the study group lived with their spouse and children, about one quarter
lived only with children and 4.8 percent of the participants were living alone.
Majority of the participants (69.8%) belonged to the middle income group, more than one
quarter of them belonged to low income group and just about four percent belonged to
high income group.
35
Table 4.1 Distribution of participants by socio-demographic characteristics, Kottayam district (N=420) Characteristics N (%)
Age in years(mean+SD) 69.5+8.9 60-69 239(56.9) 70-79 108(25.7) 80+ 73(17.4) Sex of the participant Male 192(45.7) Female 228(54.3) Religion Christian 236(56.2) Hindu 163(38.8) Muslim 21(5.0) Education No schooling 17(4.0) Primary school(1-7) 163(38.8) High school(8-10) 155(36.9) Higher secondary(11-12) 36(8.6) Degree 45(10.7) PG and above 4(1.0) Current marital status Not married 3(0.7) Married 299(71.2) Widowed 118(28.1) Family members Spouse 53(12.6) Spouse and children 243(57.9) Children only 101(24.0) Living alone 20(4.8) Relatives 3(0.7) Socio economic status High income 17(4.0) Middle income 293(69.8) Low income 110(26.2)
The current occupation, major occupation during lifetime and the current means of
sustenance by sex was analysed (See table 4.2). This was done because work force
participation definitely varies by sex in India. About 40 percent of males had salaried
employment as the major occupation during lifetime while more than 70 percent of
females reported their major occupation during the life time as ‘homemakers’. Regarding
current occupation, 34 percent and 30 percent of males were retired and self employed
36
respectively while, 20.8 percent were currently unemployed due to health reasons.
Among females 75 percent were homemakers. An examination of the current means of
sustenance indicated that about 60 percent of females were supported by children living
in the house while majority of males had income from current work and past work.
Table 4.2 Distribution of participants by current occupation, major occupation during lifetime and the current means of sustenance, by sex, Kottayam district
Male (N=192)
Female (N=228)
Major occupation during lifetime Salaried employment 77(40.1) 30(13.2) Daily wages 40(20.8) 17(7.5) Self employment 71(37) 11(4.8) Unemployed 4(2.1) 1(0.4) Homemaker 0(0) 169(74.1)
Current occupation Retired 66(34.4) 30(13.2) Daily wages 17(8.9) 9(3.9) Self employment 61(31.8) 5(2.2) Unemployed(health reason) 40(20.8) 12(5.3) Unemployed(other reasons) 8(4.1) 1(0.4) Homemakers 0(0) 171(75)
Current means of sustenance Income from current work 58(30.2) 3(1.3) Income from past work, pension etc 69(35.9) 37(16.2) Supported by children living in the house 49(25.5) 138(60.5) Supported by children living elsewhere 11(5.7) 24(10.5)
Supported by relatives 4(2.1) 11(4.8) Income of the spouse 1(0.5) 15(6.8)
4.1.2 Participants health status
Table 4.3 describes the illness status and other related factors of the participant. About
16.7 percent of the participants perceived that they did not receive appropriate health
care. And the major barrier reported for not receiving health care was the cost of
treatment (65.7%). Another reason for not obtaining health care was that they had to
depend on someone else to travel to the health facility (27.1%). The level of disability
reported among the participants was 37.4 percent. More than half of them (55.0%) had
family history of hypertension, diabetes mellitus or dyslipidemia. About 47 percent had
37
chronic diseases other than diabetes mellitus, hypertension and dyslipidemia where 18.7
percent had heart diseases and the same number of participants had lung diseases.
Table 4.3 Distribution of participants by their health status related variables, Kottayam district (N =420) Characteristics N (%)
Perception of having received appropriate health care Yes 350(83.3)
No 70(16.7) Barriers to receiving health care Transport 2(2.9)
Cost 46(65.7) Timing of services 3(4.3)
Need to depend on someone else 19(27.1) Disability Yes 157(37.4) No 263(62.6)
Family history of NCDs Yes 232(55.2)
No 188(44.8) Diseases other than DM, hypertension, dyslipidemia
Yes 198(47.1) No 222(52.9) Other Chronic Diseases
Heart diseases 37(18.7) Lung diseases 37(18.7)
Arthritis 31(15.7) Cerebral diseases 20(10.1) Thyroid diseases 17(8.6)
Kidney diseases 10(5.1) Cancers 8(4.0)
Others 38(19.1) Total 198(100)
4.2 Outcome variables
Table 4.4 describes the dyslipidemia, hypertension and diabetes mellitus status of the
participants. About 25 percent had dyslipidemia and among the participants with
dyslipidemia more than a third (38.0%) had an unmet need for treatment of dyslipidemia.
While 74.5 percent had no dyslipidemia, the unmet need for screening of dyslipidemia
among them was high (60.7%).
38
About 45.5 percent had hypertension and 8.9 percent often checked blood pressure using
their own equipment. Unmet need for hypertension treatment was 29.8 percent. Among
the 54.5 percent of older adults who had no hypertension, the unmet need for screening
was 26.2 percent.
About 66 percent had no diabetes mellitus and the unmet need for screening among them
was 37.5 percent. More than a third of the participants had diabetes mellitus and six
percent used their own glucometer to check their blood sugar levels.
Regarding complications of diabetes mellitus, 25 percent of participants who were
diagnosed as having diabetes mellitus for more than one year reported that they have at
least one complication caused by it. About 25.9 percent had unmet need for treatment of
diabetes mellitus. Among the participants diagnosed to have diabetes mellitus for more
than one year but not having any complications associated with it; 62.9 percent had unmet
need for complication screening of diabetes mellitus.
Combining the unmet need for treatment and the unmet need for complication screening,
the total unmet need for treatment of diabetes mellitus was 72 percent.
39
Table 4.4 Distribution of the participants by their chronic disease status and unmet need for screening (outcome variables), Kottayam district Characteristics N (%)
Dyslipidemia
Yes 107(25.5)
No 313(74.5)
Unmet need for screening of dyslipidemia 190(60.7)
Unmet need for treatment of dyslipidemia 41(38.3)
Hypertension
Yes 191(45.5)
No 229(54.5)
Unmet need for screening of hypertension 60(26.2)
Unmet need for treatment of hypertension 57(29.8)
Means by which blood pressure is often checked
From doctor during consultations 145(75.9)
From the nearby health facility 25(13.1)
From the lab 4(2.1)
Using own equipment 17(8.9)
Diabetes Mellitus
Yes 143(34)
No 277(66)
Unmet need for screening of Diabetes Mellitus 104(37.5)
Unmet need for treatment of Diabetes Mellitus 37(25.9)
Unmet need for complication screening 90(62.9)
Unmet need for treatment and complication screening of Diabetes Mellitus
103(72.0)
Means of checking blood sugar
From doctor during consultations 117(81.8)
From the nearby health facility 12(8.4)
From the lab 5(3.5)
Own equipment 9(6.3)
The participants who were not taking all the prescribed medicines for treatment of
dyslipidemia, hypertension and diabetes mellitus were asked about the reasons for not
taking the medications. The following table (Table 4.5) describes the reasons for not
taking medicines.
Among the persons with dyslipidemia, 22 reported that they are not taking the
medications prescribed by the doctor. The most common reason reported was the absence
40
of any symptoms or complaints. The second most common reason for not taking the
medications was the cost of medicines.
A majority of the persons diagnosed with hypertension and not taking treatment cited the
cost of the treatment as a reason for non adherence (35.7%). More than a quarter of those
not taking the prescribed treatment reported that they were taking ayurvedic/herbal
treatment (28.6%).
More than 50 percent of those not taking treatment for diabetes mellitus said that
controlling diet is enough instead of treatment. A third of those not taking treatment for
diabetes mellitus said that they do not have any complaints now and they are not taking
treatment.
Table 4.5 Distribution of participants by the reasons for not taking treatment for the NCDs, Kottayam district Reasons for not taking treatment for dyslipidemia(N=22)
Presently there are no complaints(no symptoms) 11(50)
Medicines are costly, can't afford them 7(31.7)
Taking ayurveda/herbal medicines 2(9.1)
Diet control is enough 1(4.6)
Having side effects 1(4.6)
Reasons for not taking treatment for hypertension (N=14)
Medicines are costly, economic burden 5(35.7)
Taking ayurveda/herbal medicines 4(28.7)
Diet control is enough 3(23.4)
Presently there are no complaints, no symptoms 1(7.1)
Need to depend on someone to take medicine 1(7.1)
Reasons for not taking treatment for DM (N=9)
Diet control is enough 5(55.6)
Presently there are no complaints, no symptoms 3(33.3)
Medicines are costly, economic burden 1(11.1)
41
4.3. Factors associated with unmet need for screening and treatment for
dyslipidemia, hypertension and diabetes mellitus
Those with met and unmet need were categorised by socio-demographic (table 4.6) and
health related factors (table 4.7). The associations between unmet need and these factors
analysed using the chi-square test for associations (where ever necessary, the reported
chi-square values are those with Yates’ correction for size).
4.3.1 Socio demographic factors associated with unmet need for screening for the
NCDs
The unmet need for screening for all the three diseases was concentrated in the age
groups 60-69 and 80 plus. Especially, the unmet need for screening of hypertension was
the highest among 80 plus compared to other age groups. The unmet need for screening
was the least in the age group of 70-79.
Unmet need for screening of dyslipidemia was more among males while in case of
hypertension and diabetes mellitus the unmet need for screening was more among
females.
Participants with lower levels of education (up to high school only) had a higher level of
unmet need for screening for all the diseases and this difference was statistically
significant for both dyslipidemia and diabetes mellitus.
The unmet need for screening was higher for hypertension and diabetes mellitus among
currently married persons while the unmet need for hypertension screening was higher
among those not currently married. There was, however, no variation in the unmet need
for screening for any of the three diseases by the living arrangements.
The unmet need status for any of the three diseases did not seem to vary by past
occupational category. However, the unmet need for diabetes mellitus was strongly
42
associated with current work or retired status. Those not working/ home makers had a
high level of unmet need for screening for diabetes mellitus.
Participants who were economically dependent on others had more unmet needs for
screening of the diseases and this difference was statistically significant for unmet need
for screening of dyslipidemia and diabetes mellitus.
The association between income status and unmet need status was statistically significant
for diabetes mellitus. Those belonging to the lowest income category had the higher
levels of unmet need for screening for all three conditions.
Table 4.6 Distribution of participants by unmet need for screening status by socio demographic factors; Kottayam district Dyslipidemia Hypertension Diabetes Mellitus
Met
Need
(N=123)
Unmet
Need
(N=190)
Met
Need
(N=169)
Unmet
Need
(N=60)
Met
Need
(N=173)
Unmet
Need
(N=104)
Age Group
60-69 70(39.1) 109(60.9) 100(73.0) 37(27.0) 96(60.4) 63(39.6)
70-79 31(42.5) 42(57.5) 47(82.5) 10(17.5) 45(69.2) 20(30.8)
80 plus 22(36.1) 39(63.9) 22(62.9) 13(37.1) 32(60.4) 21(39.6)
P value 0.749 0.110 0.435
Sex
Male 60(40.5) 88(59.5) 79(69.3) 35(30.7) 79(61.2) 50(38.8)
Female 63(38.2) 102(61.8) 90(78.3) 25(21.7) 94(63.5) 54(36.5)
P value 0.670 0.123 0.697
Education
Up to high school
90(30.5) 167(69.5) 133(71.5) 53(28.5) 132(58.9) 92(41.1)
High school and more
33(58.9) 23(41.1) 36(83.7) 7(16.3) 41(77.4) 12(22.6)
P value 0.001 0.101 0.013
Marital status
Married 91(40.1) 136(59.9) 124(72.5) 47(27.5) 123(61.8) 76(38.2)
Unmarried/ Widowed
32(37.2) 54(62.8) 45(77.6) 13(22.4) 50(64.1) 28(35.9)
P value 0.642 0.448 0.723 Continued.....
43
Dyslipidemia Hypertension Diabetes Mellitus
Met
Need
(N=123)
Unmet
Need
(N=190)
Met
Need
(N=169)
Unmet
Need
(N=60)
Met
Need
(N=173)
Unmet
Need
(N=104)
Living arrangement
With spouse 90(40.0) 135(60.0) 122(72.2) 47(27.8) 122(62.2) 74(37.8)
Others 33(37.5) 55(62.5) 47(78.3) 13(21.7) 51(62.9) 30(37.1)
P value 0.684 0.352 0.911
Past occupation
Working 77(41.9) 107(58.1) 106(72.6) 40(27.4) 106(64.2) 59(35.8)
Homemaker/
Not working 46(35.7) 83(64.3) 63(75.9) 20(24.1) 67(59.8) 45(40.2)
P value 0.270 0.585 0.456
Current occupation
Working/
Retired 60(43.2) 79(56.8) 83(72.8) 31(27.2) 89(71.2) 36(28.8)
Homemaker/
Not working 63(36.2) 111(63.8) 86(74.8) 29(25.2) 84(55.3) 68(44.7)
P value 0.210 0.734 0.001
Current means of sustenance
Own income 59(48.8) 62(51.2) 74(75.5) 24(24.5) 78(72.9) 29(27.1)
Others 64(33.3) 128(66.7) 95(72.5) 36(27.5) 95(55.9) 75(44.1)
P value 0.007 0.611 0.004
Socio economic status
High income 94(42.7) 126(57.3) 128(77.1) 38(22.9) 133(69.3) 59(30.7)
Low income 29(31.2) 64(68.8) 41(65.1) 22(34.9) 40(47.1) 45(52.9)
P value 0.056 0.065 0.001
4.3.2 Health related factors and unmet need for screening
Table 4.7 displays the association between health related factors and the status of unmet
need for screening. Overtly, the unmet need for screening of diabetes mellitus and
hypertension was higher among those with disabilities when compared to those without
disabilities. However, the associations were not statistically significant across all three
diseases. Those who perceived that they receive appropriate health care had more unmet
needs for all the three diseases and this was statistically significant.
44
The unmet need for screening was higher among those who did not have a family history
for any of the conditions considered. This difference was statistically significant for both
hypertension and diabetes mellitus.
The unmet need for screening for dyslipidemia and diabetes mellitus were higher when
there was no history of other chronic diseases when compared to those with a history. The
unmet need for screening for hypertension did not vary by the history of other chronic
conditions.
Table 4.7 Distribution of participants by unmet need for screening status by health related factors; Kottayam district Dyslipidemia Hypertension Diabetes Mellitus Met
need (N=123)
Unmet need (N=190)
Met need (N=169)
Unmet need (N=60)
Met Need (N=173)
Unmet need (N=104)
Disability
Yes 49(41.5) 69(58.5) 52(70.1) 22(29.9) 105(60.0) 70(40.0)
No 74(37.9) 121(62.1) 117(75.5) 38(24.5) 68(66.7) 34(33.3)
P value 0.530 0.401 0.269
Perception of having received appropriate health care
Yes 109(42.3) 149(57.7) 147(76.9) 44(23.1) 149(66.8) 74(33.2)
No 14(25.5) 41(74.5) 22(57.9) 16(42.1) 24(44.4) 30(55.6)
P value 0.021 0.015 0.002
Family history
Yes 67(42.7) 90(57.3) 91(79.8) 23(20.2) 98(70.0) 42(30.0)
No 56(35.9) 100(64.1) 78(67.8) 37(32.2) 75(54.7) 62(45.3)
P value 0.220 0.039 0.009
History of any other disease
Yes 57(43.8) 73(56.2) 68(73.1) 25(26.9) 78(63.9) 44(36.1)
No 66(36.1) 117(63.9) 101(74.3) 35(25.7) 95(61.3) 60(38.7)
P value 0.165 0.846 0.652
4.3.3 Unmet need for treatment and socio demographic factors
Table 4.8 shows the unmet need for treatment against the related socio demographic
variables. The unmet need for treatment of diabetes mellitus was highest among 80 plus
45
age group (95.0%) and the unmet need for treatment of dyslipidemia were high among
the age group 70-79. The unmet need for treatment of any diseases did not seem to vary
according to the sex of the participant. For the treatment of dyslipidemia and
hypertension, the unmet need was higher among participants with lower levels of
education.
Unmarried/widowed people had higher unmet need for treatment of all the three diseases.
For those participants who did not live with their spouses, the unmet need for treatment
was higher when compared to those living with others. Among the participants whose
past and current working status was ‘not working’ or ‘homemakers’ the unmet need for
treatment of dyslipidemia was higher compared to those who were working or retired.
The unmet need for treatment of dyslipidemia and diabetes mellitus was high among
people who had their own income for sustenance. However this relation was not
statistically significant. People belonging to low income category had higher levels of
unmet need for treatment of all the three diseases when compared to people who belonged
to high income category.
Table 4.8 Distribution of participants by unmet need for treatment for NCDs status and socio demographic factors; Kottayam district Dyslipidemia Hypertension Diabetes mellitus Met
Need (N=66)
Unmet need (N=41)
Met need (N=134)
Unmet need (N=57)
Met Need (N=40)
Unmet need (N=103)
Age Group
60-69 38(63.3) 22(36.7) 71(69.6) 31(30.4) 26(32.5) 54(67.5)
70-79 19(54.3) 16(45.7) 37(72.5) 14(27.5) 13(30.2) 30(69.8)
80 plus 9(75.0) 3(25.0) 26(68.4) 12(31.6) 1(5.0) 19(95.0)
P value 0.411 0.901 0.046
Sex
Male 27(61.4) 17(38.6) 54(69.2) 24(30.8) 18(28.6) 45(71.4)
Female 39(61.9) 24(38.1) 80(70.8) 33(29.2) 22(27.5) 58(72.5)
P value 0.955 0.816 0.887
Continued...
46
Dyslipidemia Hypertension Diabetes Mellitus Met
Need (N=66)
Unmet need (N=41)
Met need (N=134)
Unmet need (N=57)
Met Need (N=40)
Unmet need (N=103)
Education Up to high school
44(56.4) 34(43.6) 101(67.8) 48(32.2) 31(27.9) 80(72.1)
High school and more
22(75.9) 7(24.1) 33(78.6) 9(21.4) 9(28.2) 23(71.8)
P value 0.060 0.177 0.983
Marital status
Married 45(62.5) 27(37.5) 91(71.0) 37(29.0) 29(29.0) 71(71.0)
Unmarried/
Widowed 21(60.0) 14(40.0) 43(68.3) 20(31.7) 11(25.6) 32(74.4)
P value 0.800 0.687 0.676
Living arrangement
With spouse 45(63.3) 26(36.7) 90(70.9) 37(29.1) 29(29.0) 71(71.0)
Others 21(58.3) 15(41.7) 44(68.8) 20(31.2) 11(25.6) 32(74.4)
P value 0.612 0.763 0.676
Past occupation
Working 40(65.6) 21(34.4) 67(67.7) 32(32.3) 21(26.3) 59(73.7)
Homemaker/ not working
26(56.5) 20(43.5) 67(72.8) 25(27.2) 19(30.2) 44(69.8)
P value 0.340 0.437 0.605
Current occupation
Working/ Retired
32(65.3) 17(34.7) 51(68.9) 23(31.1) 17(26.9) 46(73.1)
Homemaker/ Not working
34(58.6) 24(41.4) 83(70.9) 34(29.1) 23(28.8) 57(71.2)
P value 0.479 0.766 0.815
Current means of sustenance
Own income/ Pension
28(60.9) 18(39.1) 50(72.5) 19(27.5) 16(26.7) 44(73.3)
Others 38(62.3) 23(37.7) 84(68.9) 38(31.1) 24(28.9) 59(71.1)
P value 0.881 0.600 0.767
Socio economic status
High income 56(62.2) 34(37.8) 105(72.9) 39(27.1) 35(29.7) 83(70.3)
Low income 10(58.8) 7(41.2) 29(61.7) 18(38.3) 5(20.0) 20(80.0)
P value 0.792 0.145 0.328
47
4.3.4 Unmet need for treatment and various health related factors
Table 4.9 displays the unmet need for treatment among the participants by the various
health related factors. Participants who reported disability had higher unmet need for
treatment of dyslipidemia and hypertension while those without any disability had a
higher level of unmet need for treatment of diabetes mellitus. Participants who perceived
that they receive the appropriate health care had higher unmet need for treatment of
diabetes mellitus and hypertension.
The unmet need for treatment of all the three diseases was higher among people with a
family history of any NCDs. Unmet need for treatment of all the three diseases was high
among participants who do not have any other chronic illness and this difference was
statistically significant in diabetes mellitus.
Table 4.9 Distribution of participants by unmet need for treatment for NCDs status and health related factors; Kottayam district Dyslipidemia Hypertension Diabetes mellitus
Met need (N=66)
Unmet need (N=41)
Met need (N=134)
Unmet need (N=57)
Met need (N=40)
Unmet need (N=103)
Disability Yes 27(69.2) 12(30.8) 60(72.3) 23(27.7) 14(25.5) 41(74.5)
No 39(57.4) 29(42.6) 74(68.5) 34(31.5) 26(29.5) 62(70.5)
P value 0.224 0.572 0.596
Perception of having received appropriate health care Yes 57(61.9) 35(38.1) 111(69.8) 48(30.2) 35(27.6) 92(72.4)
No 9(60.0) 6(40.0) 23(71.9) 9(28.1) 5(31.3) 11(68.7)
P value 0.855 0.816 0.771
Family history Yes 43(57.3) 32(42.7) 80(67.8) 38(32.2) 24(26.1) 68(73.9)
No 23(71.9) 9(28.1) 54(74.0) 19(26.0) 16(31.4) 35(68.6)
P value 0.157 0.365 0.500
History of any other disease Yes 42(61.8) 26(38.2) 79(75.2) 26(24.8) 29(38.2) 47(61.8)
No 24(61.5) 15(38.5) 55(63.9) 31(36.1) 11(16.4) 56(83.6)
P value 0.985 0.090 0.004
48
4.3.5 Unmet need for treatment of Diabetes Mellitus (treatment and complication
screening) and socio demographic factors and health related factors
The unmet need for treatment of diabetes mellitus was defined as the total of unmet need
for treatment of diabetes mellitus and the unmet need for complication screening of
diabetes mellitus. So the unmet need for complication screening and for treatment was
looked at separately to see how it varies with the socio demographic factors and the
health related factors (See table 4.10, 4.11).
The unmet need was highest in the age group 80 plus especially for the complication
screening. Only 20 percent of the 80 plus got screened for complications of diabetes
mellitus. Male participants had more unmet need for treatment of diabetes mellitus. The
complication screening did not seem to vary by sex. Participants with lower levels of
education had higher unmet need for treatment of diabetes mellitus while those with
higher levels of education had high unmet need for screening of diabetes mellitus related
complications. Unmarried/widowed people and those who did not live with their spouses
had higher unmet needs for treatment and the total unmet need for treatment of diabetes
mellitus was also high among them. But the unmet need for complication screening was
high among the currently married participants and those living with their spouses.
Participants whose past occupation status was ‘working’ had higher unmet need for
treatment compared to those who were not working/homemakers in the past and this
difference was statistically significant. The unmet need for treatment and complication
screening did not seem to vary with the current occupation. Unmet need for treatment and
complication screening was higher in participants who had their own income for
sustenance. The total unmet need for treatment and unmet need for treatment of diabetes
mellitus was more among the low income participants while those belonged to high
income category had high unmet need for complication screening.
49
Table 4.10 Distribution of participants by unmet need for treatment of Diabetes Mellitus (treatment and complication screening) and socio demographic factors, Kottayam district Diabetes Mellitus
(treatment+ complication screening)
Diabetes Mellitus treatment
Diabetes Mellitus complication screening
Met Need (N=40)
Unmet need (N=103)
Met need (N=106)
Unmet need (N=37)
Met Need (N=53)
Unmet need (N=90)
Age Group
60-69 26(32.5) 54(67.5) 58(73.0) 22(28.0) 33(41.2) 47(58.8)
70-79 13(30.2) 30(69.8) 37(86.0) 6(14.0) 16(37.2) 27(62.8)
80 plus 1(5.0) 19(95.0) 11(55.0) 9(45.0) 4(20.0) 16(80.0)
P value 0.046 0.029 0.212
Sex
Male 18(28.6) 45(71.4) 45(71.4) 18(28.6) 24(38.1) 39(61.9)
Female 22(27.5) 58(72.5) 61(76.3) 19(23.7) 29(36.3) 51(63.7)
P value 0.887 0.566 0.821
Education
Up to high school
31(27.9) 80(72.1) 79(71.2) 32(28.8) 43(38.7) 68(61.3)
High school and more
9(28.2) 23(71.8) 27(84.4) 5(15.6) 10(31.2) 22(68.8)
P value 0.983 0.133 0.440
Marital status Married 29(29.0) 71(71.0) 77(77.0) 23(23.0) 36(36.0) 64(64.0)
Unmarried/
Widowed 11(25.6) 32(74.4) 29(67.4) 14(32.6) 17(39.5) 26(60.5)
P value 0.676 0.231 0.688
Living arrangement
With spouse 29(29.0) 71(71.0) 77(77.0) 23(23.0) 36(36.0) 64(64.0)
Others 11(25.6) 32(74.4) 29(67.4) 14(32.6) 17(39.5) 26(60.5)
P value 0.676 0.231 0.688
Past occupation Working 21(26.3) 59(73.7) 56(70.0) 24(30.0) 30(37.5) 50(62.5)
Homemaker/ Not working
19(30.2) 44(69.8) 50(79.4) 13(20.6) 23(36.5) 40(63.5)
P value 0.605 0.024 0.903
Continued...
50
Diabetes Mellitus (treatment+ complication screening)
Diabetes Mellitus treatment
Diabetes Mellitus complication screening
Met Need (N=40)
Unmet need (N=103)
Met need (N=106)
Unmet need (N=37)
Met Need (N=53)
Unmet need (N=90)
Current occupation Working/retired 17(26.9) 46(73.1) 47(74.6) 16(25.4) 23(36.5) 40(63.5)
Homemaker/ Not working
23(28.8) 57(71.2) 59(73.8) 21(26.2) 30(37.5) 50(62.5)
P value 0.815 0.908 0.093
Current means of sustenance
Own income/ Pension
16(26.7) 44(73.3) 44(73.3) 16(26.7) 20(33.3) 40(66.7)
Others 24(28.9) 59(71.1) 62(74.7) 21(25.3) 33(39.8) 50(60.2)
P value 0.767 0.854 0.432
Socio economic status
High income 35(29.7) 83(70.3) 88(74.6) 30(25.4) 43(36.4) 75(63.6)
Low income 5(20.0) 20(80.0) 18(72.0) 7(28.0) 10(40.0) 15(60.0)
P value 0.328 0.789 0.738
Table 4.11 describes the unmet need for treatment of diabetes mellitus and its
accompanied screening for complications with the health related factors. The total unmet
need for treatment and the unmet need for complication screening were higher among the
people who reported disability. While the unmet need for only treatment was high among
people who did not have any physical disability.
Among people who perceived that they have received appropriate health care the unmet
need for treatment, complication screening and the total unmet need for treatment of
diabetes mellitus was higher.
The total unmet need for treatment of diabetes mellitus was more among participants with
family history of NCDs. But when analyzed separately, unmet need for treatment and
unmet need for complication screening was higher among people with no family history
of any NCDs. Participants who did not have any other chronic diseases reported higher
51
unmet need for treatment, complication screening and the total unmet need for treatment
of diabetes mellitus.
Table 4.11 Distribution of unmet need for treatment of Diabetes Mellitus (treatment and complication screening) and health related factors; Kottayam district Diabetes Mellitus
(treatment+ complication screening)
Diabetes Mellitus Treatment
Diabetes Mellitus complication screening
Met need (N=40)
Unmet need (N=103)
Met need (N=106)
Unmet need (N=37)
Met need (N=53)
Unmet need (N=90)
Disability
Yes 14(25.5) 41(74.5) 44(80.0) 11(20.0) 20(36.4) 35(63.6)
No 26(29.5) 62(70.5) 62(70.5) 26(29.5) 33(37.5) 55(62.5)
P value 0.596 0.205 0.891
Perception of having received the appropriate health care
Yes 35(27.6) 92(72.4) 94(74.0) 33(26.0) 45(35.4) 82(64.6)
No 5(31.3) 11(68.7) 12(75.0) 4(25.0) 8(50.0) 8(50.0)
P value 0.771 0.932 0.256
Family history
Yes 24(26.1) 68(73.9) 40(78.4) 11(21.6) 20(39.2) 31(60.8)
No 16(31.4) 35(68.6) 66(71.7) 26(28.3) 33(35.9) 59(64.1)
P value 0.500 0.381 0.691
History of any other disease
Yes 29(38.2) 47(61.8) 60(78.9) 16(21.1) 35(46.1) 41(53.9)
No 11(16.4) 56(83.6) 46(68.7) 21(31.3) 18(26.9) 49(73.1)
P value 0.004 0.161 0.018
4.4 Simultaneity in unmet need for screening and treatment for the three conditions
The incidence of unmet need for screening for each of the three conditions has been
examined singly. However, it is possible that screening for one condition is coterminous
with screening for any of the other two conditions. Alternatively; screening for one
condition may not be linked to screening for any of the other conditions. To examine this,
the participants were categorised by the unmet need for screening status so that each
person belonged to a uniquely identified need category, whether with unmet need for one
52
condition, for two of them or for all of them. The results of this form of categorisation are
given in table 4.12.
About 50 percent had no unmet need for screening of any of the diseases. It means that 50
percent have screened for all three diseases together. Among those with unmet need,
nearly one quarter had an unmet need for screening for all conditions (24.1 percent, not
shown in table). The unmet need for screening of only dyslipidemia was 22.4 percent. It
means, among those with an unmet need for screening for any condition, nearly half had
an unmet need for screening for dyslipidemia alone. What is indicated is that, close to one
eight of those aged 60 and above, who should be screened for these three conditions have
not been screened appropriately. The unmet need for screening of dyslipidemia and
diabetes mellitus was 9.5 percent. The least unmet need for the screening of NCDs was
for diabetes mellitus and hypertension (0.02%) followed by only hypertension (0.7%).
Table 4.12 Distribution of participants by unmet need for screening, Kottayam district Characteristics N (%)
Unmet need for screening of DM, Hypertension and Dyslipidemia 50(11.9)
Unmet need for screening of Dyslipidemia only 94(22.4)
Unmet need for screening of Hypertension only 3(0.7)
Unmet need for screening of Diabetes Mellitus only 13(3.1)
Unmet need for screening of Diabetes Mellitus and Dyslipidemia 40(9.5)
Unmet need for screening of Dyslipidemia and Hypertension 6(1.4)
Unmet need for screening of Hypertension and Diabetes Mellitus 1(0.3)
No unmet need for screening of any of the diseases 213(50.7)
Total 420(100)
Table 4.13 explore the overlapping unmet need for treatment of NCDs. For this only the
participants with all three NCDs diagnosed was considered (N=55). About 23.6 percent
had met need for treatment of all the three diseases. And the unmet need for treatment of
all the three diseases was 10.9 percent, meaning that at least one out of 10 persons with
53
all the three conditions is not getting treatment for any of them. The unmet need for
treatment of diabetes mellitus only (30.9%) was the highest. It was followed by unmet
need for treatment of dyslipidemia and diabetes mellitus (16.6%).
Table 4.13 Distribution of participants with all three conditions and unmet need for treatment, Kottayam district
4.5 Unmet need for screening of the other one/two NCDs when one is diagnosed to
have one/two of the NCDs
Being diagnosed as having a particular condition could enhance the potential for being
screened for other conditions. Alternatively, if one condition is diagnosed, it could result
in a laissez faire practice with regard to screening for other conditions. To explore the
potential for being screened for any of the three conditions after being diagnosed as
having at least one is being examined here in table 4.14. A form of stratified multivariate
analysis is attempted wherein the unmet need for screening of one or two of the diseases
is estimated after a participant is found to be diagnosed as having one or two of the
NCDs.
Among the participants with dyslipidemia, the unmet need for screening of hypertension
was non-existent. That is all the participants who had dyslipidemia had undergone regular
Characteristics N (%)
No unmet need for treatment of any of the diseases 13(23.6)
Unmet need for treatment of all three diseases 6(10.9)
Unmet need for treatment of Dyslipidemia only 1(1.8)
Unmet need for treatment of Hypertension only 1(1.8)
Unmet need for treatment of Diabetes Mellitus only 17(30.9)
Unmet need for treatment of Hypertension and DM 6(10.8)
Unmet need for treatment of Dyslipidemia and DM 9(16.6)
Unmet need for treatment of Hypertension and Dyslipidemia 2(3.6)
Total 55(100)
54
check up for blood pressure. About 9.4 percent had unmet need for screening of diabetes
mellitus only.
For those with hypertension, 18.3 percent had an unmet need for screening for
dyslipidemia. When compared to the unmet need for screening for dyslipidemia, the
unmet need for screening for diabetes mellitus was just about one fourth.
About 24.4 percent were likely to have unmet need for screening of dyslipidemia when
they are diagnosed with diabetes mellitus. In the case of diagnosis of diabetes mellitus,
almost all (99.0%) are likely to have their needs met for screening of hypertension. That
is, among the people who have only diabetes mellitus or if they are diagnosed with only
hypertension, the unmet need for screening of dyslipidemia was found to be relatively
higher when compared to the unmet need for screening for hypertension.
Nearly 90.0 percent of those with dyslipidemia are likely to have the needs for screening
met for diabetes mellitus and hypertension. Only about two thirds (64.9 %) of those with
hypertension are likely to be screened for both diabetes mellitus and dyslipidemia.
Among those with diabetes mellitus nearly three fourths (73.3%) are likely to have their
screening needs met for hypertension and dyslipidemia.
Among these older adults with both hypertension and diabetes mellitus more than three
fourths (77.0%) will have an unmet need for screening of dyslipidemia.
Even though the question of temporality exists here, that is we do not know which
happened first; the diagnosis of the particular condition or the screening for the other
conditions, what this essentially means is that persons with dyslipidemia, are screened
appropriately for hypertension and diabetes mellitus. A person with diabetes mellitus is
less likely to be screened properly for dyslipidemia but will be screened almost surely for
hypertension. Even those diagnosed with both hypertension and diabetes mellitus, the
55
proportions of persons screened for dyslipidemia is barely one fourth. More than three
fourths of those with both these conditions are not appropriately screened.
Table 4.14 Distribution of participants with unmet need for screening when diagnosed to have any one /two of the diseases, Kottayam district. Dyslipidemia present(N=107) Hypertension Diabetes Mellitus Diabetes Mellitus and Hypertension Met need Unmet
Need Met need
Unmet Need
Met need
Unmet need
Met need for either
107(100) 0(0) 97(90.6) 10(9.4) 97(90.6) 0(0) 10(9.4) Hypertension present(N=191) Dyslipidemia Diabetes Mellitus Diabetes mellitus and Dyslipidemia Met need Unmet
need Met need
Unmet Need
Met need Unmet need
Met need for either
156(81.7) 35(18.3) 183(95.9) 8(4.1) 124(64.9) 24(12.6) 43(22.5) Diabetes Mellitus present(N=143) Dyslipidemia Hypertension Dyslipidemia and Hypertension Met need Unmet
Need Met need
Unmet Need
Met need Unmet need
Met need for either
108(75.5) 35(24.5) 142(99.3) 1(0.7) 105(73.4) 2(1.4) 36(25.2) Dyslipidemia and Hypertension present(N=84) Diabetes Mellitus Met need Unmet need 77(91.7) 7(8.3) Hypertension and Diabetes Mellitus present(N=95) Dyslipidemia Met need Unmet need 21(22.2) 74(77.8)
Dyslipidemia and Diabetes Mellitus present(N=64) Hypertension Met need Unmet need 64(100) 0(0)
The implications of these results and their import for policy are discussed in the next
chapter.
56
CHAPTER 5
DISCUSSION AND CONCLUSIONS
5.1 Brief summary of findings
The prevalence of dyslipidemia, hypertension and diabetes mellitus was 25.5 percent,
45.5 percent and 34 percent respectively. The unmet need for treatment of dyslipidemia
was the highest (38.3%) among all the three diseases. About 30 percent of people with
hypertension had unmet need for treatment. One quarter of those diagnosed with diabetes
mellitus had unmet need for treatment of diabetes mellitus while 62.9 percent of those
with diabetes mellitus had unmet need for complications screening of diabetes mellitus.
Combining both unmet need for treatment and unmet need for complication screening,
the total unmet need for treatment of diabetes mellitus was calculated as 72 percent. The
unmet need for treatment of diabetes mellitus was higher among the 80 plus and among
people with no history of any other diseases. When the unmet need for treatment was
exclusively examined among the participants with all three diseases, the unmet need for
treatment of diabetes mellitus only (30.9%) was the highest and the unmet need for
treatment of all the three diseases was 10.9 percent.
The major reason for not taking treatment for dyslipidemia was the asymptomatic nature
of the disease. That is; since there were no symptoms for the disease people ignored the
need to take medications for the condition. About 37 percent of the persons who were not
taking treatment for hypertension reported the cost of the treatment as the reason for
doing so. More than half of the patients not taking treatment for diabetes mellitus
believed diet control is enough as an alternative for treatment.
The unmet need for screening of dyslipidemia was 60.7 percent while 26.2 percent and
37.5 percent of the participants had unmet need for screening of hypertension and
57
diabetes mellitus respectively. The socio demographic and health related factors
associated with the unmet need for screening of dyslipidemia were education of the
participant, current means of sustenance, the socio economic status, family history and
perception of having received appropriate health care. The unmet need for screening of
hypertension was associated with family history and perception of having received
appropriate health care. The socio economic status, current means of sustenance, current
occupation, education, family history and the perception of having received appropriate
health care were associated with unmet need for screening of diabetes mellitus.
When the participants were grouped exclusively into need categories for screening, it was
found that half of the participants have been screened for all three diseases. Among those
with unmet need, 24.1 percent had an unmet need for screening for all the three
conditions simultaneously. This implies that nearly 12 people out of hundred who are
aged 60 and above are not screened appropriately for all the three diseases. The unmet
need for screening for dyslipidemia alone was 22.4 percent. About 24.4 percent were
likely to have unmet need for screening of dyslipidemia when they are diagnosed with
diabetes mellitus. For all these older adults with both hypertension and diabetes mellitus,
the proportion having an unmet need for screening of dyslipidemia was 77 percent.
5.2 Unmet need for screening
Screening for chronic conditions and treating them significantly reduces the disease
burden among the elderly population. However, public health explorations tend to focus
on the prevalence of disease and utilisation of health care. The early detection and proper
treatment and follow up of non communicable diseases have found to reduce the disease
burden and associated complications. In this context, examining the proportion of those
who are not screened at all, but need to be fills the gap in the prevention strategy. This
58
study has identified that one eighth of those sixty years and above were not screened
appropriately for all the three diseases.
5.2.1 Diabetes Mellitus
About 37.5 percent had an unmet need for screening of diabetes mellitus. This figure is
slightly lower when compared to the findings of a study from United States on self
reported prevalence of diabetes mellitus screening from 2005 to 2010 which reported the
prevalence of having a blood test for diabetes mellitus in the past 3 years was 60.7
percent among the 60 plus population. This study from U.S also identified the predictors
of screening as education, income, family history. The present study has also identified
similar factors as being associated with the unmet need for screening for diabetes mellitus
(Casagrande et al., 2014). It suggests that the extent of appropriate screening for diabetes
mellitus is lower among the economically and educationally underprivileged people.
5.2.2 Hypertension
The unmet need for screening of hypertension was 26.2 percent and this was associated
with family history and perception of having received appropriate health care. This
proportion is lower than that found in a study from Pakistan during the year 1990- 1995
which was conducted among the adult population. This study found that about 40.4
percent of the participants aged 50 and above had ever checked their blood pressure
(Ahmad and Jafar, 2005). The present study has less than a half of the level of unmet
need in hypertension screening when compared to the unmet need for screening among
all adults in this study from Pakistan.
The unmet need was less, probably because the chance of getting the blood pressure
checked is very high for a person going to a health care provider for any reason. A study
from U.S.A also agrees with this statement in which about 56 percent all patient
encounters included a BP measurement in the people aged 18 and above. The chances of
59
not being screened for hypertension were particularly greater for people visiting a
provider other than a primary care physician or cardiologist (Ma and Stafford, 2008).
5.2.3 Dyslipidemia
Cardiovascular diseases are the most prevalent causes of death among all the NCDs and
dyslipidemia is a major risk factor for CVDs. Due to the asymptomatic nature of lipid
disorders, screening is required for detection. Detection of dyslipidemia in earlier stages
of life can aid in the earlier management strategies such as lifestyle modification or
medications which can prevent the cardiovascular disease in future (Expert Panel on
Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults, 2001).
Regardless of all these facts the elderly population in this study had a very high unmet
need for screening of dyslipidemia. A major proportion (22.0%) of them is not screened
for dyslipidemia alone. A study from U.S reported that the screening rate of dyslipidemia
in 2009 was 94.7 percent in the elderly population (>65 years) where as in the present
study the unmet need for screening of dyslipidemia was 60.7 percentage (Centers for
Disease Control and Prevention (CDC), 2012).
The onetime expenditure for screening of dyslipidemia is higher when compared to
expenditure for screening of hypertension and diabetes mellitus. This might be a reason
for the high levels of unmet need for screening of dyslipidemia. Comparing the blood
pressure and blood glucose monitoring process, the testing process of cholesterol level is
complex. It requires blood to be collected by a lab technician and checked. It is time
consuming too. These reasons could contribute to the relatively higher extent of the
unmet need for screening of the same.
In my study the participants reported cost of treatment which included the cost of
medication, the expenditure involved in screening and expenditure incurred for travelling
cost as a barrier to receiving the require health care. At times these older adults had to
60
depend on someone else to get them to the health facility. These could be the probable
reasons for the unmet need for screening too. Lower education levels, economical
dependence, lower socio economic status and perception of having received appropriate
health care were the factors associated with unmet need for screening of dyslipidemia. A
study from Malaysia among the adult population also found that secondary level of
education was associated with higher awareness of dyslipidemia (Ambigga et al, 2016).
Another hospital based study from Canada showed that the screening rates were higher
among people belonging to higher socio economic status (Lugomirski et al., 2013). This
implies that the economically and educationally disadvantaged people had higher unmet
needs.
The results indicate that even when the elderly persons are diagnosed with hypertension
and diabetes mellitus appropriate screening for dyslipidemia was done in only about 22.2
percent of them. This essentially means that even after having been diagnosed with two
conditions that are risk factors for CVD, the elderly are not screened appropriately for the
third one, if it the third one is dyslipidemia.
5.3 Unmet need for treatment
About 10.9 percent of people with all the three diseases were not appropriately treated for
all the three diseases. Even though only 13 percent of the total participants had all the
three diseases, the unmet need for treatment for all the three diseases was not
insignificant. One out of every ten such persons remained untreated for all three
conditions, and this needs serious attention. Appropriate treatment measures can reduce
the future morbidity and mortality due to non communicable diseases.
5.3.1 Diabetes Mellitus
The overall prevalence of diabetes mellitus in the present study was found to be 34
percent which is higher than the findings from the study from central Kerala which
61
reported a prevalence of 28 percent among 60 plus population (Vijayakumar et al, 2009).
In the current study the total unmet need for treatment of diabetes mellitus was reported
as 72 percent and this matches with the recent study in Kerala which reported poor
adherence to diabetes mellitus treatment as 74 percent in the adult population (Sankar u et
al, 2015). More than half of diabetes mellitus patients who were not being treated
believed diet control was enough instead of treatment. A study on influence of patients’
disease knowledge and beliefs about medications on adherence to medical management in
Palestine found out that non adherence was related to beliefs about necessity of anti
diabetic medications (Sweileh et al., 2014).
In the present study the unmet need for complication screening was 62.9 percent which
included screening for HbA1C once a year, screening for diabetic retinopathy once a year
and a yearly screening of renal function. A study from Farmington, USA in 2005 reported
that about 33 percent of respondents having diabetes mellitus received fewer than two
HbA1C tests during the past year (Delaronde, 2005). Another study from Singapore
found out that about 25 percent were ignorant about the need for regular ophthalmic
reviews (Tham et al., 2004). The better access to or awareness in these countries could
account for the improved situation regarding complication screening for diabetes mellitus
in these settings when compared to the situation among older adults in Kottayam district,
Kerala.
5.3.2 Hypertension
The prevalence of hypertension in the current study was 45.5 percent which was less than
a recent study in 2015, in India reporting the overall prevalence of 50 percent of
hypertension among 60 plus (Alam et al.2015). About 30 percent had unmet need for
treatment of hypertension. A study from Kerala among elderly found that the proportion
of people getting treated for hypertension was 84.7 percent (Kalvathy et al, 2000). The
62
present study reports a higher level of unmet need for treatment of hypertension. The
probable reason is that the definition of unmet need for treatment also includes regular
blood pressure checkups apart from following the treatment. A study from Pondicheri,
India among adults showed that seventy-five percent of the hypertensives had their BP
checked once in 20 days on an average (Chinnakali et al., 2012) and this goes hand in
hand with the current study. In this study the participants reported the cost of the
treatment as the reason for not taking treatment and this result was in concordance with a
study done among adults in Nigeria which also identified the cost of treatment as a major
reason for non compliance of hypertension treatment (Osamor and Owumi, 2011).
5.3.3 Dyslipidemia
The overall prevalence of dyslipidemia was 25 percent which was less than the study on
prevalence of metabolic disorders in Kerala, where a prevalence of 37 percent of
hypercholesterolemia was found in the general population (Vijayakumar et al, 2009).
About 38.3 percent of the participants had unmet need for treatment of dyslipidemia.
Another study from Kerala on the drug adherence of dyslipidemia patients revealed a
poor adherence of about 70 percent. Being asymptomatic was the major reason for not
taking the treatment for dyslipidemia in this study and a executive committee report by
National Cholesterol Education Program reported that since dyslipidemia has no unusual
signs or symptoms many people fail to know that their cholesterol levels are high (Expert
Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults,
2001).
5.4 Limitations of the study
In the absence of suitable Indian guidelines this study utilizes the ADA, JNC8 and AHA
guidelines and expert opinion for the defining unmet need. In the stratified multivariate
63
analysis, the temporality of the events between the diagnosis of a particular disease and
screening of the other two diseases cannot be established.
5.5 Strengths of the study
This study analyzes both the screening and treatment status of diabetes mellitus,
dyslipidemia and hypertension in the same person at a time. Such studies among the
elderly in Kerala are rare. The non response rate was zero in the study. Efforts were made
to verify the screening and treatment status of the participants using the prescription
details or outpatient slips of last visit to the doctor.
5.6 Conclusions
Among those with an unmet need for screening for any of the three conditions, nearly half
had an unmet need for screening for dyslipidemia alone. About one eight of those aged 60
and above, have not at all been screened appropriately for all the three. At least one out of
10 persons with all the three conditions is not getting treatment for any of them. Among
the people who have only diabetes mellitus or if they are diagnosed with only
hypertension, the unmet need for screening of dyslipidemia was found to be relatively
higher when compared to the unmet need for screening for the other two. Those
diagnosed with both hypertension and diabetes mellitus, the proportions of persons
screened for dyslipidemia is barely one fourth. More than three fourths of those with both
these conditions are not appropriately screened.
There is need to ensure that older adults are screened for all the three diseases at least
once a year. The non communicable disease control programme is functioning in
Kottayam district and the programme covers not only diabetes mellitus and hypertension,
it includes all the risk factors of CVDs. But even then the coverage for dyslipidemia
screening and treatment is considerably low. The study gives clear idea about the special
needs of elderly and receiving the perceived health care was a determining factor for
64
screening and treatment in all the diseases studied. The cost of treatment, travel to facility
acts as a barrier among them in receiving health care. There is need to ensure that those
diagnosed are treated appropriately. For reducing the morbidity and mortality and cost of
health care in the long run the screening and treatment for all the three NCDs need to be
made accessible, available and affordable to the elderly population.
5.7 Policy Implication
The coverage of the Non Communicable Disease Programme should be increased among
elderly. The Non Communicable Disease Control Programme should give more attention
to the screening and treatment of all the three conditions especially for dyslipidemia
among elderly. A comprehensive screening strategy for all the three NCDs should be
formed considering the special needs of elderly. Just like diabetes mellitus and
hypertension, screening facility for dyslipidemia should also be available to this
population at risk. If the elderly find it difficult to access care for screening for
dyslipidemia, the nearest health facility can facilitate this process by establishing a blood
collection point or a mobile blood collection unit or envisaging similar strategies. It will
also help in the appropriate follow up among those diagnosed. In addition, subsidizing the
cost of screening and treatment and increasing the accessibility will aid in appropriate
screening and treatment, particularly among this vulnerable group.
65
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ANNEXURE I
Cover sheet
Sl.No Household
number
How many
people usually
live in this
household
(include
servants who
stay
permanently,
but not
children who
are studying
elsewhere)
Of
these,
how
many
are
aged
60 or
more?
Can you say
how many
of those
aged 60 and
more are
men/women
and list
them?
Selected
by
KISH
Selected
person is
available
Selected
person
consented
Name Sex
ANNEXURE II
Participant information sheet
ACHUTHA MENON CENTRE FOR HEALTH SCIENCE STUDIES
SREE CHITRA TIRUNAL INSTITUTE FOR MEDICAL SCIENCES & TECHNOLOGY,
TRIVANDRUM, KERALA-695011
Sl.No
Unmet need for screening and treatment of non communicable diseases and the factors
associated with the unmet needs for treatment among the older adults in Kottayam
district.
I am Liss Maria Scaria, studying for Masters of Public Health (MPH) at Achutha Menon
Centre for Health Sciences Studies, Sree Chitra Tirunal Institute for Medical Sciences and
Technology, Trivandrum. I am conducting this study as part of my Masters Dissertation
work. This study aims to gain a better understanding of the screening status or the treatment
of Non Communicable Diseases in terms of Diabetes Mellitus, Hypertension and
Hyperlipidemia among the elderly.
Participation involves answering a set of questions. The interview will take approximately
20-30 minutes, depending on your answers. There are no direct benefits to you for
participating in this interview. I would like to assure you that all the information shared with
me will be kept confidential and will only be used for research and publications purpose.
Your individual identity will never be used in any research output nor will be shared with
anyone else in process of communication of data.
You are free to refuse to answer any of the questions at any time. For any clarifications
regarding the study, you can contact me directly (Mob.9400686876). In case you wish to seek
any clarification regarding this study, you can contact the member Secretary of the Institute
Ethics committee of SCTIMST. The Member Secretary can be contacted at the following
number: Dr Mala Ramanathan, Ph.: 0471-2524234. E-mail Id:[email protected]
Signature:
Liss Maria Scaria
Date:
ANNEXURE III
Informed consent form
ACHUTHA MENON CENTRE FOR HEALTH SCIENCE STUDIES
SREE CHITRA TIRUNAL INSTITUTE FOR MEDICAL SCIENCES & TECHNOLOGY,
TRIVANDRUM, KERALA-695011
Sl.No
Unmet need for screening and treatment of non communicable diseases and the factors
associated with the unmet needs for treatment among the older adults in Kottayam
district.
Consent form
I have read the details in the participant information sheet. The purpose of the study and my
involvement in the study has been explained to me. By signing on this consent form, I
indicate that I understand what will be expected from me and that I am willing to participate
in this study. I know that I can withdraw my participation at any time during the interview
without any explanation. I have also been informed about who should be contacted if further
clarifications.
I ..............................................................................................agree to participate in the study.
Place: ...........................
Date: ........................... Signature: .................
Thank you.
Signature of interviewer: ..............................
Name of the interviewer……………………
ANNEXURE IV
ACHUTHA MENON CENTRE FOR HEALTH SCIENCE STUDIES
SREE CHITRA TIRUNAL INSTITUTE FOR MEDICAL SCIENCES & TECHNOLOGY,
TRIVANDRUM, KERALA-695011
Unmet need for screening and treatment of non communicable diseases and
the factors associated with the unmet needs for treatment among the older
adults in Kottayam district.
ID No.
Name of the taluk
Date of interview
Time of interview
Sl.
No
Question
Response
SOCIO-DEMOGRAPHIC DETAILS
1.
What is your age as on your last
birthday?
......................
2.
Sex
Male ..................1
Female .................2
3.
What is your religious affiliation?
Christian .................1
Hindu .................2
Muslim .................3
Others ..................4
5.
What is your current marital status?
Not married.......................1
Married.............................2
Widowed...........................3
Divorced...........................4
Separated..........................5
Others(specify)................6
6.
In your family, who all live with you
now?
Spouse.....................1
Spouse & children...2
Children only...........3
Living alone.....................4
Relatives..................5
Others (specify -----).......6
7.
On an average, what is the amount of
money that your household spends in a
month?
..................................................
8.
What was your major occupation during
lifetime; that is the work that you did for
a major portion of your life?
Salaried employment..............1
Daily wages............................2
Self employment.....................3
Unemployed........................... 4
Others (specify
____).......................................5
9.
What is your current occupation?
Retired...................................1
Daily wages...........................2
Self-employed.......................3
Unemployed (health
reason)...................................4
Unemployed (other
reason)...................................5
Keeping house/Home-
maker.....................................6
Others (specify____)..............7
10
Does the household own a computer?
Yes.......................1
No.......................2
(if 10=2
skip to
Q.12)
11.
Does the computer have an internet
connection?
Yes.......................1
No.......................2
12.
What is the type of flooring in your
house?
Marble/granite/tile..................1
Mosaic/cement/red
oxide.......................................2
Mud/cow dung........................3
13.
What is your current means of
subsistence?
Income from own current
work........................................1
Income from past work,
pension etc..............................2
Supported by children residing
in the house............................3
Supported by children residing
elsewhere................................4
Supported by other relatives...5
Others.....................................6
(multiple
answers
possible)
14.
Are you receiving the health care that you
need for your health problems?
Yes..................1
No...................2
If 14=2
skip to
Q.16
15.
If no, what are the barriers to receiving
health care?
Distance ..............................1
Transportation .....................2
Waiting time .......................3
Cost .....................................4
Timing of services ..............5
Need to depend on someone
else......................................6
Others (specify)...................7
16.
Have any of the members of your immediate family or other relatives been
diagnosed with Diabetes, Hypertension or Hypercholesterolemia?
16a Hypercholesterolemia
Yes...............1
No.................2
16b Diabetes Mellitus
Yes...............1
No.................2
16c Hypertension
Yes...............1
No.................2
Health status
17.
Which of the following restrictions or impairment do you experience?
17a. Impaired vision Yes...................1
No...................2
17b. Impairment in hearing Yes...................1
No...................2
17c. Restrictions due to musculoskeletal
dysfunction
Yes...................1
No...................2
17d. Others............................(specify)
Yes...................1
No...................2
18. Have you ever been treated or diagnosed (said by the health professional)
for any of the following diseases?
If 18a=2
skip to Q.20
If18A=1ski
p to Q.35
If18b=2
skip to
Q.25; If
18b=1 skip
to Q. 43
18a. Dyslipidemia Yes...................1
No...................2
18b. Hypertension Yes...................1
No...................2
18c. Diabetes mellitus Yes...................1
No...................2
If 18 c=2,
skip to Q.30
;if 18c=1
skip to Q.54
18d. Others Yes...................1
No....................2
If 18 d=1
skip to Q.19
19. Which disease/diseases do you
have?
..................................
SCREENING
Screening for Dyslipidemia
20.
Have you ever checked your cholesterol
level?
Yes..................................1
No....................................2
21.
When was the last time you checked your
blood cholesterol?
........................
22.
How often you get your cholesterol levels
checked?
Two or more times a year........1
Once a year...............................2
Not even once in a year.............3
23.
What was the cholesterol level during the
last screening?
Normal................................1
Abnormal............................2
24. If abnormal, did you visit any health
facility for treatment?
Yes......................................1
No.......................................2
Screening for hypertension
25. Have you ever checked your blood
pressure?
Yes......................................1
No.......................................2
26.
When was the last time you checked your
BP?
...........................
27.
How often you get your blood pressure
checked?
More than once a year...............1
Once a year...............................2
Not even once in a year.............3
28.
What was the blood pressure level during
the last screening?
Normal................................1
Abnormal............................2
29.
If abnormal, did you visit any health
facility / a doctor for treatment?
Yes......................................1
No.......................................2
Screening for Diabetes Mellitus
30.
Have you ever checked your blood sugar
level?
Yes......................................1
No.......................................2
31.
When was the last time you checked your
blood sugar?
.........................................
32.
How often you get your blood sugar
levels checked?
More than once a year...............1
Once a year...............................2
Not even once in a year.............3
33.
How was the blood sugar level during the
last screening?
Normal................................1
Abnormal............................2
34.
If abnormal, did you visit any health
facility for treatment?
Yes......................................1
No.......................................2
TREATMENT
If diagnosed with Hypercholesterolemia
35. How long ago were you diagnosed as
having hypercholesterolemia?
Last one month.......................1
During the past one year.........2
Between 1-2 years................ 3
For2-4 years...........................4
5 years and more....................5
36. How often did you get your blood
cholesterol level checked in the last six
months?
1-6 months.............................1
More than six months............2
Not checked in last one
month.....................................3
37. What is your doctor’s advice regarding elevated cholesterol level?
If 37a=2
skip to
Q.41 37a. To start treatment with medication
Yes......................................1
No.......................................2
37b. Diet control Yes......................................1
No.......................................2
37c. Physical activity
Yes......................................1
No.......................................2
37d. Others(specify)
Yes......................................1
No.......................................2
38.
(If 37a=1)
What is the name and dosage of the
medication that has been prescribed for
your hypercholesterolemia?
......................
Name of drug/Dosage
39.
Are you taking the prescribed medicines
by your doctor?
Yes......................................1
No........................................2
40.
If no, what are the reasons for not taking
the medicine
..............................
41. How do you often get your blood
cholesterol levels checked?
From doctor during
consultations...........................1
From the nearby health
facility....................................2
From the lab........................... 3
Others......................................4
42.
How will you define your treatment for
hypercholesterolemia?
Regular.......................1
Timely........................2
Delayed......................3
No treatment..............4
If diagnosed with Hypertension
43.
How long ago were you diagnosed as
having hypertension?
Last one month......................1
During the past one year........2
Between 1-2 years.................3
For2-4 years...........................4
5 years and more....................5
44.
How often have you been advised by
your doctor to check blood pressure?
.................................
45. How long has it been since you last
checked your blood pressure level?
.................................
46. How much was your blood pressure
during last check up?
................................(verify
with records if available)
47. How often do you get your blood
pressure levels checked in last one
year?
Less than 2 weeks.....................1
2-4 weeks..................................2
1-3 months................................3
More than three months...........4
48. What is your doctor’s advice regarding elevated blood pressure?
If 48a=2
skip to
Q.52
48a. To start treatment with medication Yes......................................1
No.......................................2
48b. Diet control Yes......................................1
No.......................................2
48c. Physical activity Yes......................................1
No.......................................2
48d. Others(specify) Yes......................................1
No.......................................2
49. (If 48a=1)
What is the name and dosage of the
medication that has been prescribed for
your hypertension?
......................
Name of drug/Dosage
50. Are you taking the prescribed medicines
by your doctor?
Yes......................................1
No.......................................2
51. If no, what are the reasons for not taking
the medicine?
.................................
52. How do you often get your blood
pressure checked?
From doctor during
consultations...........................1
From the nearby health
facility....................................2
From the lab........................... 3
Own apparatus........................4
Others......................................5
53. How will you define your treatment for
Hypertension?
Regular.......................1
Timely........................2
Delayed......................3
No treatment..............4
If diagnosed with Diabetes mellitus
54.
How long ago were you diagnosed as
having Diabetes mellitus?
Last one month.....................1
During the past one year......2
Between 1-2 years................3
For2-4 years......................... 4
5 years and more..................5
55. How often have you been advised by
your doctor to check blood sugar levels?
.................................
56. When the last time you checked your
blood sugar level?
.................................
57. How much was your blood sugar level
during last check up?
................................(verify
with records if available)
58. How often did you get your blood sugar
levels checked in last one year?
One month to six months..........1
More than six months................2
Not checked in last one year.....3
59. What is your doctor’s advice regarding elevated blood sugar level?
If 59a=2
skip to
Q.63
59a. To start treatment with medication
Yes......................................1
No.......................................2
59b. Diet control
Yes......................................1
No.......................................2
59c. Physical activity
Yes......................................1
No.......................................2
59d. Others(specify)
Yes......................................1
No.......................................2
60. (If 59a=1)
What is the name and dosage of the
medication that has been prescribed for
your hypertension?
......................
Name of drug/Dosage
61.
Are you taking the prescribed medicines
by your doctor?
Yes......................................1
No.......................................2
62.
If no, what are the reasons for not taking
the medicine?
.........................
63. How do you often get your blood sugar
checked?
From doctor during
consultations...........................1
From the nearby health
facility....................................2
From the lab........................... 3
Own apparatus........................4
Others......................................5
64. How will you define your treatment for
diabetes mellitus?
Regular.......................1
Timely........................2
Delayed......................3
No treatment..............4
65. Some people who have experienced
diabetes mellitus for a prolonged period
of time develop additional conditions
caused by it. Do you have any
complications related to diabetes?
Yes......................1
No.......................2
Don’t know.........3
If 65=2 or
3
Skip Q.67
66. If yes, which complication do you have?
66a. Diabetic foot Yes......................1
No.......................2
66b. Retinopathy Yes......................1
No.......................2
66c. Nephropathy Yes......................1
No.......................2
66d. Neuropathy Yes......................1
No.......................2
66e. Others(specify)
Yes......................1
No.......................2
If 66a, 66b, 66c, 66d=2 and diagnosed with DM for more than a year,
67.
Have you checked your HbA1C?
Yes......................1
No.......................2
Don’t know..........3
If 67=2
or 3 skip
to Q.68
68.
If yes, When was the last time you
checked HbA1C?
.................
69.
Have you tested your vision?
Yes......................1
No.......................2
If 69=2
or 3 skip
o Q. 71
70.
When was the last time you tested your
vision?
.................
71.
Have you checked your kidney function?
Yes......................1
No.......................2
Don’t know..........3
72.
When was the last time you tested your
kidney function?
................
KISH
ANNEXURE V
S.No.
ANNEXURE VI
E-mail: [email protected]
ANNEXURE VII
ANNEXURE VIII
Q.
A
B
C
A
B
C
D
A A=2
A=
1
B B = 2
B=
1
C C = 2
C= 1
D D =1
A A
B
C
D
A A
B
C
D
A A=2
B
-C
D.
A
B
C
D
E
A B C D
HbAIC
HbAIC
ANNEXURE IX
