1. Summary Measures of Population Health Ian McDowell November, 2002 1. Rationale for summary measures 2. Mortality-based measures 3. Combined disability & mortality methods

2. 1. Why do we need measures of population health? We wish to monitor health of citizens … We wish to monitor health of citizens … –To set priorities for health services & policies –To evaluate social and health policies –To compare health of different regions –To identify pressing health needs –To draw attention to inequalities in health –Highlight balance between length and quality of life –Numerical index desirable: a “GNP of Health”

3. Classifying Population Health Measures by their Purpose 1. Descriptive measures: i.Current health status (e.g., health surveys) ii.Evaluative measures (e.g., to assess outcomes of health policies) 2. Analytic measures include an implicit time dimension: iii.Predictive methods (risk assessment; projections of disease burden) look forward; iv.Explanatory measures (income inequality or social cohesion) look backwards.

4. These purposes may correspond to different types of research (shown in the ellipses) Note: the figure is intended to show the typical blend of methods you might use in a particular type of study: HSR would use descriptive and analytic, for example.

5. Classifying Population Health Measures by their Focus 1. Aggregate measures combine data from individual people, summarized at regional or national levels. E.g., rates of smoking or lung cancer. 2. Environmental indicators record physical or social characteristics of the place in which people live and cover factors external to the individual, such as air or water quality, or the number of community associations that exist in a neighborhood. These can have analogues at the individual level. 3. Global indicators have no obvious analogue at the individual level. Examples include contextual indicators such as the existence of healthy public policy; laws restricting smoking in public places, or social equity in access to care; social cohesion, etc. Morgenstern H. Ecologic studies in epidemiology: concepts, principles, and methods. Annu Rev Public Health 1995; 16:61-81.

6. Linking the focus of a measure to its application Aggregate measures are typically used in descriptive studies; focus on the individuals within the population, i.e. idiographic. They measure health in the population Aggregate measures are typically used in descriptive studies; focus on the individuals within the population, i.e. idiographic. They measure health in the population Environmental measures can be used in descriptive, analytic or explanatory studies Environmental measures can be used in descriptive, analytic or explanatory studies Global measures mainly used in analytic studies; focus on generating theory (nomothetic studies). They measure health of the population Global measures mainly used in analytic studies; focus on generating theory (nomothetic studies). They measure health of the population

7. Linking the target of a population intervention to the type of measure Linking the target of a population intervention to the type of measure Interventions can target people, environmental factors, or policy in general …and to the presumed etiological sequence These correspond to Morgenstern’s categories of measures used to evaluate the intervention…

8. History of changing approaches to measuring population health Originally based on mortality rates. IMR is often used to describe level of development of a country Originally based on mortality rates. IMR is often used to describe level of development of a country With declining mortality, people with chronic disease survive; morbidity & disability gain importance. Then... With declining mortality, people with chronic disease survive; morbidity & disability gain importance. Then... Concern with quality of life, not mere survival Concern with quality of life, not mere survival To compare populations at different stages of economic development, it may be desirable to combine mortality and morbidity in a single, composite index To compare populations at different stages of economic development, it may be desirable to combine mortality and morbidity in a single, composite index

9. 2.Aggregate Measures: (i) Mortality-Based Indicators Life expectancy Expected years of life lost Potential years of life lost

10. Expectancies versus Gaps From a typical survival curve, we can either consider the life expectancy (“E”), or the gap (“G”) between current life expectancy and some ideal (here, the outer rectangle). From a typical survival curve, we can either consider the life expectancy (“E”), or the gap (“G”) between current life expectancy and some ideal (here, the outer rectangle). Expectancies are generic; gaps can be disease- specific Expectancies are generic; gaps can be disease- specific

11. Life Expectancy Summarizes all age-specific mortality rates Summarizes all age-specific mortality rates Estimates hypothetical length of life of a cohort born in a particular year Estimates hypothetical length of life of a cohort born in a particular year –This assumes that current mortality rates will continue

12. Gaps: Expected Years of Life Lost Can use population life expectancy at the individual’s age of death Can use population life expectancy at the individual’s age of death –Problem: different regions may have different life expectancies. Cannot identify impact of a disease. Or: Standard Expected Years of Life Lost Or: Standard Expected Years of Life Lost –Reference is to an “ideal” life expectancy E.g., Japan (82 years for women) E.g., Japan (82 years for women) Area between survivorship curve and the chosen norm Area between survivorship curve and the chosen norm

13. Potential Years of Life Lost (PYLL) PYLL =  ( “normal age at death” – actual age at death). Doesn’t much matter what age is chosen as reference; typically 75 PYLL =  ( “normal age at death” – actual age at death). Doesn’t much matter what age is chosen as reference; typically 75 Attempts to represent impact of a disease on the population: death at a young age is a greater loss than death of an elderly person Attempts to represent impact of a disease on the population: death at a young age is a greater loss than death of an elderly person Focuses attention on conditions that kill younger people (accidents; cancers) Focuses attention on conditions that kill younger people (accidents; cancers) All-causes or cause-specific PYLL All-causes or cause-specific PYLL

14. 3. Aggregate Measures: (ii) Indicators that Combine Mortality & Morbidity Health expectancies Health gaps

15. Composite Measures Composite measures combine morbidity and mortality into a health index. An index is a numerical summary of several indicators of health Composite measures combine morbidity and mortality into a health index. An index is a numerical summary of several indicators of health Aims to represent overall health of a population Aims to represent overall health of a population Mortality data typically derived from life tables; morbidity indicators from health surveys, e.g. Mortality data typically derived from life tables; morbidity indicators from health surveys, e.g. Self-rated health Self-rated health Disability or activity limitations Disability or activity limitations A formal health index A formal health index

16. Survivorship Functions for Health States Survivors Age This diagram illustrates the composite health of a population. The lower area ‘A’ shows the proportion of people in good health (however defined); it shows healthy life expectancy. The top curve shows deaths; intermediate curves represent various levels of disability. Area ‘C’ represents the deficit of this population compared to an arbitrary ideal; this refers back to the notion of health gaps. Deaths

17. More details on the combined indicators From the previous chart: From the previous chart: –You can read from the bottom, and talk of “health expectancies.” –Or you can read from the top, and focus on the gap between current state and the ideal (these were discussed earlier) –The bands in the middle indicate that the value of a life lived in less than perfect health is less than a healthy life-year. These are “health-adjusted life expectancies” –The indicators will fall in a descending sequence: overall life expectancy, then health-adjusted life expectancy, then healthy life expectancy.

18. 2.1 Health expectancies Generic term: any expectation of life in various states of health. Includes other, more specific terms Generic term: any expectation of life in various states of health. Includes other, more specific terms Two main classes: Two main classes: –Dichotomous weighting for health states –Health state valuations for a number of categories

19. Dichotomous expectancies Here full health is rated 1, and any state of poor health (mild, moderate, or severe disability) is rated 0. Here full health is rated 1, and any state of poor health (mild, moderate, or severe disability) is rated 0. This leads to Disability-free life expectancy (DFLE): weight of 1 for “no disability” and 0 for all other states. This leads to Disability-free life expectancy (DFLE): weight of 1 for “no disability” and 0 for all other states. = Expectation of life with no disability, or Healthy Life Expectancy (HLE) = Expectation of life with no disability, or Healthy Life Expectancy (HLE) Very sensitive to threshold of disability chosen Very sensitive to threshold of disability chosen

20. Illustrating dichotomous weights: Life Expectancy and Disability-Free Life Expectancy, Canada, 1986-1991 1986 1991 Years M F Life expectancy From birth Disability-free Life expectancy

21. Polytomous states and valuations A refinement is to incorporate many levels of disability and to count time spent with each level of disability. = Polytomous model (three or more health states defined) A refinement is to incorporate many levels of disability and to count time spent with each level of disability. = Polytomous model (three or more health states defined) Weights are assigned to each state; generally 0 to 1.0. These may be added together and compared across diseases Weights are assigned to each state; generally 0 to 1.0. These may be added together and compared across diseases This forms the Health-Adjusted Life Expectancy (HALE) index This forms the Health-Adjusted Life Expectancy (HALE) index First calculated for Canada by Wilkins. He used four levels of severity & arbitrary weights. First calculated for Canada by Wilkins. He used four levels of severity & arbitrary weights. Recent work uses utility weights. E.g. from Health Utilities Index, Quality of Well-Being Scale, EUROQoL, etc. Recent work uses utility weights. E.g. from Health Utilities Index, Quality of Well-Being Scale, EUROQoL, etc.

22. Health Expectancy by Income Level and Sex, Canada, 1978 (Wilkins) Males Females Years Severely disabled Restricted Minor limitations Healthy LowHigh Income Quintiles

23. Relationship between Life Expectancy, Health Expectancy and Health-Adjusted Life Expectancy Health-Adjusted Life Expectancy Life Expectancy Healthy Life Expectancy By down-weighting the various levels of disability, the HALE falls between LE and HLE

24. Some HALE Results for Canada Wolfson & Wilkins at Statistics Canada used data from the National Population Health Survey to calculate HALEs, using the “Health Utilities Index” to weight different levels of imperfect health Wolfson & Wilkins at Statistics Canada used data from the National Population Health Survey to calculate HALEs, using the “Health Utilities Index” to weight different levels of imperfect health The difference between LE and HALE is 11% for men, and 15% for women, because women live longer and suffer more chronic disease at older ages The difference between LE and HALE is 11% for men, and 15% for women, because women live longer and suffer more chronic disease at older ages They recalculated HALEs, deleting certain types of disability, and found that sensory problems (eyesight, hearing) were the major contributor in Canada to lost years. Vision problem have a very minor effect on health status, but are very common… Pain was the second largest cause They recalculated HALEs, deleting certain types of disability, and found that sensory problems (eyesight, hearing) were the major contributor in Canada to lost years. Vision problem have a very minor effect on health status, but are very common… Pain was the second largest cause They also showed that less educated people both live shorter lives, and also experience more disability They also showed that less educated people both live shorter lives, and also experience more disability Source: Wolfson MC. Health Reports 1986;8(1):41-46 Source: Wolfson MC. Health Reports 1986;8(1):41-46

25. Health Expectancies and Health Gaps LE = Life Expectancy; SLE = Standard LE; HALE = Health-Adjusted LE; HLE = Healthy LE; SEYLL = Standard Expected Years of Life Lost Gaps Expectancies Age

26. Classifying Health Gaps Gaps: Compare population health to some target. = Difference between time lived in health states less than ideal health, and the specified target Gaps: Compare population health to some target. = Difference between time lived in health states less than ideal health, and the specified target The implied norm or target is arbitrary and must be explicit, but as long as same for all populations being compared, does not matter The implied norm or target is arbitrary and must be explicit, but as long as same for all populations being compared, does not matter

27. Examples of Health Gap Measures Gap measures use a weighting for intermediate health states. This is necessary to combine time lost due to ill health with time lost due to premature mortality Gap measures use a weighting for intermediate health states. This is necessary to combine time lost due to ill health with time lost due to premature mortality Quality Adjusted Life Years (QALYs) Quality Adjusted Life Years (QALYs) –Common outcome measurement in clinical trials, program evaluation –Record extra years of life provided by therapy and quality of that life –Typically use utility scale running from 0 to 1 DALYS (disability-adjusted life years) DALYS (disability-adjusted life years)

28. 4. Environmental and Global Measures Environment, Income inequalities, Health inequalities.

29. Some Examples of Environmental Indicators Environmental indicators of health status (water, air quality, etc.) Environmental indicators of health status (water, air quality, etc.) Indicators of social interactions: changing patterns of crime; volunteerism Indicators of social interactions: changing patterns of crime; volunteerism Scope of, and access to, social & mental health institutions Scope of, and access to, social & mental health institutions Urban environmental quality; housing, hospitals, etc. Urban environmental quality; housing, hospitals, etc.

30. Some Examples of Global Measures Social solidarity; sense of identity; artistic output; public interest in health issues, etc. Social solidarity; sense of identity; artistic output; public interest in health issues, etc. Indicators of societal support: the “safety net” Indicators of societal support: the “safety net” Quality of social institutions for health (health protection laws, etc.) Quality of social institutions for health (health protection laws, etc.) Social cohesion, neighbourhood quality, social capital Social cohesion, neighbourhood quality, social capital

31. Gini Coefficient: Measure of Income Inequality L(s) lies below line of equality when income inequality favours the rich L(s) lies below line of equality when income inequality favours the rich Gini coefficient is twice the area between the curve and the line of equality Gini coefficient is twice the area between the curve and the line of equality % of income % of population L(s) 0100

32. Measures of Health Inequalities (I) Index of Dissimilarity: Absolute number or percentage of all cases that must be redistributed to obtain the same mortality rate for all SES groups. Index of Dissimilarity: Absolute number or percentage of all cases that must be redistributed to obtain the same mortality rate for all SES groups. Index of Dissimilarity in Length of Life: The absolute number or proportion of person-years of life that should be redistributed among SES strata to achieve equal length of life in all. Index of Dissimilarity in Length of Life: The absolute number or proportion of person-years of life that should be redistributed among SES strata to achieve equal length of life in all.

33. Measures of Health Inequalities (II) Relative Index of Inequality: Ratio of morbidity or mortality rates between those at bottom of SES range to those at top. This is estimated using regression and corrects for other factors. Relative Index of Inequality: Ratio of morbidity or mortality rates between those at bottom of SES range to those at top. This is estimated using regression and corrects for other factors. Slope Index of Inequality: Expresses health inequality between top and bottom of social hierarchy in terms of rate differences rather than rate ratios Slope Index of Inequality: Expresses health inequality between top and bottom of social hierarchy in terms of rate differences rather than rate ratios

34. Measures of Impact of Interventions to Reduce Inequalities Population attributable risk: The reduction in mortality that would occur if everyone experienced the rates in the highest socioeconomic group Population attributable risk: The reduction in mortality that would occur if everyone experienced the rates in the highest socioeconomic group Population attributable life lost index: The absolute or proportional increase in life expectancy if everyone experienced the life expectancy of the highest SES group Population attributable life lost index: The absolute or proportional increase in life expectancy if everyone experienced the life expectancy of the highest SES group

35. Standardized Index of Health Inequality L(s) lies above line of equality when ill-health is concentrated among poor. L(s) lies above line of equality when ill-health is concentrated among poor. L*(s) is indirectly standardized curve indicating unavoidable inequality (e.g., due to age-sex distribution) L*(s) is indirectly standardized curve indicating unavoidable inequality (e.g., due to age-sex distribution) Inequality favours rich if L(s) lies above L*(s) Inequality favours rich if L(s) lies above L*(s) Cum % of ill-health Cum. % of population ordered by income 0 100 L(s) L*(s) Line of equality