Measuring and explaining Inequities in Health Data needs

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

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 Evidence and Information for Policy World Health Organization

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

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 Evidence and Information for Policy World Health Organization

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. Evidence and Information for Policy World Health Organization

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 Evidence and Information for Policy World Health Organization

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. Evidence and Information for Policy World Health Organization

Methods: measuring (socio)economic status House characteristics Car Urban/rural Economic status Dichoto Occupation mous hierarc hical ordered probit (DIHO PIT) Evidence and Information for Policy Princ ipal comp onent s analy sis (PCA Fridge TV Phone World Health Organization

Evidence and Information for Policy World Health Organization

Inequity measures: absolute vs. relative Inequality in Infant Mortality Vietnam Mozambique IMR in the highest quintile 20 90 IMR in the lowest quintile 50 180 Pande and Gwatkin, 1999 Difference (absolute) Evidence and Information for Policy Ratio (relative) World Health Organization

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

Inequity measures: simple vs. more complicated Inequality in infant morality, by province. Iran, (1985 -1999). H Lowestosto highest quintiles odds ratio sei np oo r, Evidence 20 and Information for Policy Concentration index World Health Organization

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. Evidence and Information for Policy World Health Organization

Explaining health inequities: decomposition • 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. Evidence and Information for Policy World Health Organization

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

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

Summary and application for TB • Data needs – Availability of datasets – Required variables • Methods – Measuring socioeconomic status – Measuring inequities in health – Explaining inequities in health Evidence and Information for Policy • 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 World Health Organization