Measuring Global Burden of Disease

1. MeasuringGlobal Burden of Disease Ashwini Kalantri Moderator: Dr Pradeep Deshmukh

2. Global Burden of Disease • Rationale (Why?) • Assess health status over time • Input to health decision-making and planning processes

3. Global Burden of Disease – How? • Morbidity indicators • Mortality indicators • Disability indicators • Nutritional status indicators • Health Care delivery indicators • Utilization Rates • Indicators of Social and Mental Health • Environmental Indicators • Socio-economic Indicators • Health Policy Indicators • Indicators of quality of Life

4. Global Burden of Disease • Summary measures of population health: measures that combine information on mortality and non-fatal health outcomes to represent the health of a particular population as a single number

5. History • 1940s: Concept of “Years of Life Lost”. • 1971: Sullivan’s Index • 1983: Quality Adjusted Life Expectancy (QALE). • 1990: GBD study – DALYs. • 1998: HeaLY • DALE, HALE, QALY, DFLE followed

6. SMPH - Types Health Expectancy Health Gaps Health gaps measure lost years of full health in comparison with some ‘ideal’ health status or accepted standard. Potential Years of Life Lost (PYLL) Quality Adjusted Life Years (QALY), Disability Adjusted Life Years (DALY) Health expectancies measure years of life gained or years of improved quality of life. • Disability-free life expectancy (DFLE) • Disability-adjusted life expectancy (DALE) • Healthy adjusted life expectancy (HALE) • Quality adjusted life expectancy (QALE)

7. Survival Curve C B Time lost due to mortality Time lived in suboptimal health A Time lived in optimal health

8. Life Expectancy • Total life expectancy at birth is given by the area under the upper curve • Total life expectancy at birth = A + B • A = time lived in optimal health • B = time lived in suboptimal health C B A

9. Health Expectancy • Health expectancies are population indicators that estimate the average time that a person could expect to live in a defined state of health • Health Expectancy = A + f(B) • A = time lived in optimal health • B = time lived in suboptimal health • f(B) = function that assigns weights to years lived in suboptimal health (optimal health has a weight of 1) C B A

10. Health Gaps • Health gaps measure the difference between actual population health and some specified standard or goal • Health Gap = C + f (B) • B = time lived in suboptimal health • C = time lost due to mortality • f(B) = function that assigns weights to health states lived during time B, but where a weight of 1 equals to time lived in a health state equivalent to death C B A

11. DALEDisability Adjusted Life Expectancy • DALE integrates data on • Mortality • Long – term institutionalization • Activity limitations • Measures Quality and Quantity of life • A set of weights is assigned to four states of health • no activity limitations • activity limitations in leisure activities or transportation • activity limitations at work, home and/or school • institutionalization in a health care facility

12. HALEHealth Adjusted Life Expectancy • Health-adjusted life expectancy is the number of years in full health that an individual can expect to live given the current morbidity and mortality conditions. • Health-adjusted life expectancy uses the Health Utility Index (HUI) to weigh years lived in good health higher than years lived in poor health. • Measure of quantity and quality of life

13. QALYQuality Adjusted Life Years • Measures both quality and quantity • Used for cost-benefit analysis • Number of years added due to the intervention

14. DALYDisability Adjusted Life Years DALY is a measure of overall disease burden, expressed as the cumulative number of years lost due to ill-health, disability or early death

15. DALYObjectives • Inclusion of non-fatal health outcomes in the debate on international health policy • To quantify the burden of disease using a measure that could also be used for cost-effectiveness analysis.

16. DALYDisability Weights • The ‘valuation’ of time lived in non-fatal health states • Weights are measured as a number on a scale of 0 to 1, where 0 is assigned to a state comparable to death and 1 is assigned to a state of optimal health • Because the DALY measures loss of health, the weights are inverted for DALY calculation with 0 representing a state of optimal health (no loss) and 1 representing a state equivalent to death.

17. DALYDisability Weights • Weight for paraplegia of 0.57 - does not mean • Half dead • Halfway between life and death • Society values them as a person less than anyone else. • A year with blindness (weight 0.43) > a year with paraplegia (weight 0.57) > a year with unremitting unipolar major depression (weight 0.76). • A year in good health followed by death > a year with paraplegia followed by death. • A person to live three years with paraplegia followed by death > one year of good health followed by death • (3 years x (1-0.57) = 1.3 ‘healthy’ years is greater than 1 year of good health).

18. DALYDisability Weights

19. DALYDiscounting • The GBD applied a3% time discount rate to years of life lost in the future to estimate the net present value of years of life lost. • With this discount rate, a year of healthy life gained in 10 years’ time is worth 24% less than one gained now.

20. DALYDiscounting – Why? • To be consistent with measurement of health outcomes in cost-effectiveness analyses • To prevent giving excessive weight to deaths at younger ages • Disease eradication/research paradox

21. DALY Calculations DALY = Years Lived with Disability (YLD) + Years of Life Lost (YLL)

22. YLDYears Lived with Disability • YLD = I x DW x L • I = number of incident cases • DW = disability weight • L = average duration of the case until remission or death (years)

23. YLLYears of Life Lost • YLL = N x L • N = number of deaths • L = standard life expectancy at age of death in yrs

24. DALYCritique • Doesn’t help determine the right intervention • The true “burden” of disease will depend on the economic, family and social circumstances • Multi-pathology is not the same as multi-causality.

25. DALYCritique • Discriminates against young and the old • Does not assess qualitative difference in outcomes • No Male-Female difference in length of life • Discounting future health outcomes

26. The Global Burden of DiseaseStudy 2010

27. DALYs / 1,00,000GBD Study 2010

28. Global DALY Trends

29. India - DALY Trends

30. Thank You

31. References • Donev D, Zaletel-Kragelj L, Bjegović V, Burazeri G. Measuring the burden of disease: Disability Adjusted Life Years (DALY). Methods and tools in public health. 2010;30:715. • Murray CJL, Lopez AD. Global comparative assessments in the health sector: disease burden, expenditures and intervention packages : collected reprints from the Bulletin of the World Health Organization: World Health Organization; 1994. • Mathers CD, Vos T, Lopez AD, Salomon J, Ezzati M (ed.) 2001. National Burden of Disease Studies: A Practical Guide. Edition 2.0. Global Program on Evidence for Health Policy. Geneva: World Health Organization. • Murray CJL, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud C, et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990?2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet. 2012;380(9859):2197-223.

32. References • Mathers CD, Fat DM, Boerma JT, Organization WH. The Global Burden of Disease: 2004 Update: World Health Organization; 2008. • Murray CJL. Summary measures of population health, 2002: concepts, ethics, measurement and applications: World Health Organization; 2002. • Global Burden of Disease. Institute of Health Metrics and Evaluation; 2012 [cited 2013 24 July]; Available from: http://www.healthmetricsandevaluation.org/gbd. • Sayers B, Fliedner T. The critique of DALYs: a counter-reply. Bulletin of the World Health Organization. 1997;75(4):383. • Salomon JA, Vos T, Hogan DR, Gagnon M, Naghavi M, Mokdad A, et al. Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010. The Lancet. 2013;380(9859):2129-43.