Estimating Global Burden of Disease Christopher W. Woods, MD, MPH September 1, 2011.

Estimating Global Burden of Disease

Christopher W. Woods, MD, MPH

September 1, 2011

Reliable health data and statistics are the foundation of health policies, strategies, and evaluation and monitoring…….

Evidence is also the foundation for sound health information for the general public.

Margaret Chan 2007

If you are going to work, work on something important

William Foege, 2006

http://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen.html

Objectives

• Summarize Measures of Population Health

• Describe the Global Burden of Disease Project – Burden of Disease– Burden of Risk

• Projecting to the Future

World Population Levels in History

Defining Health

• “A state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity”

WHO Charter, 1948

Measuring Health and Disease

• Rationale (Why)– Reduce disease consequence– Assess health status over time– Application of evidence-based public health practice*

• Burden (How)– Frequency (incidence or prevalence)– Severity (premature mortality and extent of disability)– Consequences (health, social, economic)– Type of people affected (gender, age)disparities

Life Expectancy at Birth, US 1900-2000• Common metric

– Measures average expected age at birth

– No measure of quality of life

– Strongly affected by infant and childhood mortality

Nature Medicine 10, S82 - S87 (2004)www.WorldLifeExpectancy.com

Life Expectancy around the World

Comparing Life Expectancies and Under-Five Mortality Across Countries

Source: World Health Report 2008 and World Development Group Indicators

Country Gross national income per capita

Life expectancyat birth

Under-FiveMortality Rates

Japan 34,600 82 4

Sweden 36,590 81 4

Singapore 48,520 80 3

United States 45,850 77 7

Mexico 10,030 74 27

China 5370 72 31

Thailand 7880 70 21

Uzbekistan 2,020 68 68

Honduras 2,900 67 40

Russia 10,640 65 18

India 3,460 61 74

South Africa 12,120 51 68

Haiti 1,840 50 120

Kenya 1,170 49 120

Malawi 650 41 125

Botswana 10,250 35 120

http://www.nytimes.com/2010/08/15/world/asia/15japan.html?_r=1&scp=1&sq=japan%20elderly&st=cse

Historical Perspective

• As nations become wealthier, they also become healthier, and vice versa.

Source: Marmot M. Health in an

Unequal World. The Lancet

2006;368:2081-94.

Swaziland

However, this relationship is not linear! In fact, there is a clear inflection point in the curve at US$5000 per capita.

Demographic Transition

Transition from traditional to modern society

• Decline in mortality (primarily in under 5)

• Lagging decline in fertility

• http://www.worldlifeexpectancy.com/world-population-pyramid

The Epidemiologic Transition

• Underlying reasons for the demographic transition– Change in disease pattern

• Reduction in malnutrition and communicable diseases

US Crude Mortality Rates for All Causes, Noninfectious Causes, and Infectious Diseases

Armstrong et al, JAMA, 1999.

Components of Public Health Success

• Clean water supply• Sanitary sewage disposal• Food inspection• Disease surveillance• Maternal-child health• Nutrition-free lunch/milk• Housing regulations• Worker safety, ages, hours

Vital statistics: Mortality

• Deaths defined by the Manual of International Statistical Classification of Diseases, Injuries, and Cause of Death, 10th edition (ICD-10)

• Mortality at national and sub-national levels – Fact of death unreliable in 26% of countries (age, sex, place)– Cause is unreliable (even in parts of US)

• Supplement with surveys and verbal autopsies

Murray et al, 2001

Quality of Death Information

Mathers et al., Bulletin of the World Health Organization, March 2005

Measuring disability

• Morbidity– Case Disability Ratio

• Proportion of those diagnosed with a disease who have disability

• CDR=1 for most diseases• Latent infection or genetic marker may be <1

– Extent or severity of disability• Usually rank 0 to 1

– Duration• Onset until cure and recovery or death• May have continuing permanent disability

Composite Measures of Population Health

• Health Expectancy=A+f(B)– Disability-free Life Expectancy

(DFLE)

– Health Adjusted Life Expectancy (HALE).

• Health Gap (Healthy Life Lost)=C+g(B)– Healthy Life Years (HeaLY)

– Disability Adjusted Life Year

A

B

C

AGE%

Su

rviv

ing

Disability Adjusted Life Years (DALY)

• DALY=YLL + YLD (One lost year of healthy life)

– YLL=Years of life lost to premature mortality

– YLD=Equivalent years of healthy life lost due to disability

• Ranges from 0 to 1

• Uses Life Expectancy table– compare with Japan (80 y male, 82.5 female)

• Uses health professional expert groups to define values– Discount rates for future life– Weight for life lived at different ages– Disability Weights

DALY: Years of Life Lost (YLL)

• YLL = N x Lx

YLL=Years of life lost to premature mortality

– N=Number of deaths in the population

– Lx =Standard life expectancy at age of death

– X=Age of Death

• Example:– 10 deaths at 50 = 10 x Lx=10 x 34=340 YLL

Years Lived with Disability

• YLD = I x DW x d

– YLD=Years of life lived with disability

– I = Number of incident cases in the population– DW = Disability Weight

• Scale 0 (perfect health) to 1 (death)

– d = Duration of disability (years)

• 10 cases of mental retardation due to lead at birth:– 10 x 0.36 x 80 years = 288 YLD

Value Choices for the DALY

• Time discounting: 3%– Falling mortality– Increasing costs

• Age weighting– non uniform weights– less weight to years lived at

younger and older ages

• Disability weights– Largely based on GBD 1990

study with some revisions.– For local prioritization, may

adjust to suit cultural preferences

AGE

% S

urvi

ving

Effect of discounting and age weights on YLL per Death

Criticisms of the DALY (Policy Perspective)

• Expert vs. community/patient value of health• Discriminates against young and the old• Disabilities additive in nature and could exceed “1”

– More than dead?

• No priority (weight) given to worse off• No prioritization for people with limited treatment potential• Does not assess qualitative difference in outcomes• No Male-Female difference in length of life • Discounting future health outcomes (3% vs. 7%)

Adapted from GHEC Module 21http://globalhealthedu.org/modules/Documents/21/player.html

Global Burden of Disease StudyMurray and Lopez, 1996

• Quantified Health effects for 107 diseases and injuries in 8 regions in 1990

• Comprehensive and consistent estimates of morbidity and mortality by age, sex, and region

• Introduced the DALY– YLL from premature death

and years lived in less than full health

Global Burden of Disease Goals

• Measure loss of health due to comprehensive set of disease injury and risk factor causes in a comparable way

• Decouple epidemiological assessment from advocacy

• Inject non-fatal health outcomes into health policy debate

• Use a common metric for burden of disease assessment using summary measure for population health and cost-effectiveness analysis

WHO Global Burden of Disease 2004 Report

GBD Philosophy

• Quantities of interest are total events or states at population levels

• Best available data used to make estimates

• Corrections for major known biases to improve cross-population compatibility

• Comprehensive set of disease and injury causes– nothing is left out in principle

• No blanks in the tables, only wider uncertainty intervals

• Internal consistency used as a tool to improve validity


GBD Data Sources• Mortality

– Death registration, sample registration systems, household surveys, surveillance systems, epidemiological studies, population laboratories

• Morbidity/Disability– Disease registers, population-based studies, longitudinal studies, health

facility data (injuries)

GBD 2004 Update (2008)

• YLL update by age, sex, and cause for 192 states

• YLD estimates for 52 causes

• UNAIDS, UNICEF, RBM, IARC, WHO surveillance

• Addition of “refractory errors”

• Revision of “angina pectoris” and CVA estimates

Regional Estimates by WHO Region 2004


Approximate number of data sources, GBD 2004

Mortality-causes of death

Death registration for 2001 or 2002 59

Death registration for earlier 711

Child and adult mortality-other sources 535

Epidemiological studies/registers/HS data, etc.

Group I. Communicable (+) 6,539

Group II. Non-communicable 2,127

Group III. Injuries 18

Approximate total datasets used 10,052


Number of datasets by region, GBD 2004


Death Registration

Child/adult mortality data

Epidemiologic data sources

Total sources

Asia/Pacific 117 118 1,820 2,055

Europe 149 22 971 1,142

High Income 142 16 1,830 1,988

Latin America 286 122 1,311 1,719

Middle East and North Africa

46 67 645 758

Sub-Saharan Africa

30 190 2,185 2,405

World 770 535 8,747 10,052

Methods and data for cause-of-death for 2004, by Region


Global Cause of Death by Category

• Group I– Communicable plus

maternal, perinatal and nutritional conditions

• Group II– Non-communicable

conditions (eg, heart disease, stroke, cancer)

• Group III– Injuries including motor

vehicle accidents, homicide, and suicide

58.8 million deaths, 2004

Murray and Chen, 1995

GBD 2004: Leading Causes of Death by Income


GBD 2004, Death by Age and Region


GBD 2004, Death by Gender and Category

• Cardiovascular diseases are the leading cause of death.– 32% women, 27% men

• Largest difference among intentional injuries– Twice as high among men

WHO Global Burden of Disease 2004 ReportCancer Is The World's Costliest Disease, Says American Cancer Society

MARILYNN MARCHIONE | 08/16/10 09:29 PM |

GBD: Age < 5 years


Malnutrition is an underlying cause of 53% of deaths under 2 years of age.

Proportional distribution of deaths and YLL by region, 2004


Global Mortality Projections, 2004 to 2030


Disease Burden Measured in DALY

4

396131

11-25

Global View of HIV Infection

UNAIDS, 2008 Report on the Global AIDS Epidemic

33 million people living with HIV, 2008

Burden of Disease by Region, 2002

Leading Causes of GBD, 20042030


Coming 2010….A Complete Revision 1990-2005

Implementing a BOD study

• Assess demographics• Cause of Death• Define disability by cause with

input• Assess reliability/validity• Define social preferences for

age weighting, discounting, life expectation

• Est HLL for each condition and by group

• Perform sensitivity analysis• Consider other variations

(region, age, sex)• Review policy implications• Modify as necessary for setting

For policy considerations

• Est effectiveness of each intervention under consideration.

• Work out costs of interventions• Develop Cost-effectiveness

ratios to maximize return on healthy life per expenditure

• Review expected gains of healthy life by age, sex, geographic area and adjust as necessary*

Projected Burden of Disease by Income and Major Causes, 2002 - 2030

Source: Mathers CD and Loncar D (2005) Updated projections of mortality and burden of disease, WHO.

Baseline Projections by Category, 2000-2030and Compared with GBD estimates from 1990-2020

Mathers CD, Loncar D, 2006 Projections of Global Mortality and Burden of Disease from 2002 to 2030. PLoS Med 3(11): e442.

Risks Quantified in GBD

Global Distribution of burden of disease attributable to 20 leading selected risk factors

Disease Risk Factors

Deaths and DALYs due to leading 5 risks

Deaths

No. %

DALYs (M)

No. %

Underweight 3.7 6.7% 137.8 9.5%

Unsafe sex 2.9 5.2% 91.9 6.3%

Blood pressure 7.1 12.8% 64.3 4.4%

Tobacco 4.9 8.8% 59.1 4.1%

Alcohol 1.8 3.2% 58.3 4.0%

Joint effects 31% 25%

QALY and DALY

Estimating Global Burden of Disease Christopher W. Woods, MD, MPH September 1, 2011.

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