Addressing Health Inequities Among Poor Populations
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This document discusses how to address poverty and health inequalities in program design, implementation, and evaluation. It recommends identifying who the poor are using wealth quintiles or poverty lines, but noting these may not capture all factors like ethnicity, gender, or rural/urban residence. Interventions should focus on reaching the poor through geographic targeting, considering access barriers beyond cost of services. Programs should monitor uptake among poor subgroups and assess impact on identified health inequalities over time through surveys. Design, implementation and evaluation should account for multiple factors influencing poverty-related health inequities.
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Addressing Health Inequities Among Poor Populations
- 1. Addressing Poverty-Equity in Health Program Design, Implementation and Evaluation Karen Foreit 9 October 2009
- 12. 70% Urban-rural confound with quintiles Mali 26% 70% Place of residence source: Mali DHS
- 13. 70% Urban-rural confound with quintiles Mali 26% 70% Place of residence source: Mali DHS
- 15. source: Honduras 2005/6 DHS
- 16. Disentangling quintile and residence Mali source: Mali DHS
- 18. Are services physically accessible to the poor? Increase ability to pay Where are the poor? no yes Where are the services? Improve physical access Language, class discrimination or other social factors may be more important than ability to pay or service availability
- 23. Thank you!
Editor's Notes
- By definition, 20% of the population must fall into each wealth quintile. Percentage falling below absolute poverty lines may vary from country to country and within countries by place of residence.
- Mozambique 71% rural, 62% urban under national poverty line Guatemala 7 4% rural, 27% urban under poverty line India 30% rural, 25% urban under poverty line It is clear from this chart that the lower three quintiles in Mozambique may consist entirely of people below the national poverty line, whereas in India people in the middle quintile would all be ABOVE the national poverty line.
- Ethnic differences may also be associated with inequalities in health, not only because of lack of access to services but also because the service staff speak a different language and/or service practices (such as pelvic examinations) run counter to cultural norms. The highlands regions of Bolivia and Peru are home to high concentrations of indigenous women (who speak Quechua or Aymara rather than Spanish). Note the geographic differences in modern method contraceptive use. Similar comparisons could be made by language spoken at home (data available in DHS data set but not published in final reports).
- In Mali only 3% of rural women were classified as “wealthy”
- Comparing Quintile 1 to Quintile 5 may be comparing urban residents as a whole with poorest rural residents Cannot be solved by cross-tabulating quintile by place of residence Rank urban and rural populations into their own, separate quintiles
- in Mali, poverty-inequalities in modern method use are found only in urban areas and rural women show low levels of use regardless of relative poverty status.
- Data sources Program expenditures Household survey Census Program service records Client intercept surveys