1. Measuring and explaining Inequities in Health: Data needs and Methods Ahmad Hosseinpoor, MD PhD Health Equity Team Evidence and Information for Policy World Health Organization TB and Poverty: Are we doing enough? Bellagio Workshop, 6-8 December 2005

2. World Health Organization Evidence and Information for Policy Presentation outline Health: level vs. inequity The required variables for equity analysis Availability of data Measuring socioeconomic status Inequity measures Explaining health inequities: Decomposition Application to TB control among the poor

3. World Health Organization Evidence and Information for Policy Health: level vs. inequity The conceptual distinction between: –The determinants of level of health –The determinants of inequities in health The Gap The Level

4. World Health Organization Evidence and Information for Policy Steps to implement a monitoring system in inequities in health Assessment of data availability Collection of additional data, if necessary Analysis, interpretation and presentation of the data Formulating a policy response to the results, and identifying new data needs GOOD DATA ACTION

5. World Health Organization Evidence and Information for Policy The required variables for the health equity analysis A health measure, including health status, health care, determinants of health, … A measure of social position or an equity stratifier such as income or economic status, education, sex, ethnic group or geographic area.

6. World Health Organization Evidence and Information for Policy Availability of data (Regarding analysis of health inequities) Of 192 WHO member states Only 39 countries have a sufficient health information system 90 countries have only a census, an old household survey, or no data at all. Bambas, 2005

7. World Health Organization Evidence and Information for Policy Achieving standards data for the equity analysis Our primary recommendation is to support every country in meeting the minimal required data. It is also vital to plan a long-term strategy for collecting the required data for addressing health equity challenges.

8. World Health Organization Evidence and Information for Policy Urban/rural Occupation Methods: measuring (socio)economic status Principal components analysis (PCA) Dichotomous hierarchical ordered probit (DIHOPIT) model House characteristics Car Fridge TV Phone Economic status

9. World Health Organization Evidence and Information for Policy

10. World Health Organization Evidence and Information for Policy Inequity measures: absolute vs. relative Pande and Gwatkin, 1999 Difference (absolute) Inequality in Infant Mortality VietnamMozambique IMR in the highest quintile2090 IMR in the lowest quintile50180 Ratio (relative)

11. World Health Organization Evidence and Information for Policy Simple measures –Ratios –Differences More complicated measures –Concentration index and curve Inequity measures: simple vs. more complicated

12. World Health Organization Evidence and Information for Policy Inequity measures: simple vs. more complicated Lowest to highest quintiles odds ratio Inequality in infant morality, by province. Iran, (1985-1999). Concentration index Hosseinpoor, 2005

13. World Health Organization Evidence and Information for Policy Conclusions on measurement of Health Inequities Measuring inequity in a health variable could lead to different results based on the type of equity measure. Each equity measure has merits and limitations, and that different measures may be more appropriate for different settings –Simple ones: to drive policy –Complicated ones: to use in research settings/ to explaining equity in health –Inequities should be measured in both absolute and relative terms in order to understand their magnitude.

14. World Health Organization Evidence and Information for Policy An important step for policy making: To unravel and quantify the contributions of health determinants to health inequality The inequity in a health variable can be decomposed to the inequities in its determinants. In other words, it demonstrates the contribution of each determinant of a health variable to its inequity. Explaining health inequities: decomposition

15. World Health Organization Evidence and Information for Policy Decomposition Analysis – Iran, 2000 Contribution of determinants of infant mortality to its economic inequality

16. World Health Organization Evidence and Information for Policy Inequality in seeking needed outpatient care (Iran, 2003)

17. World Health Organization Evidence and Information for Policy Summary and application for TB Data needs –Availability of datasets –Required variables Methods –Measuring socioeconomic status –Measuring inequities in health –Explaining inequities in health TB datasets –TB control variables TB incidence/prevalence TB/HIV coinfection Treatment success rate Drug resistance –socioeconomic stratifier Measuring inequities in TB control variables Explaining inequities in TB control variables