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The health gap between so-called haves and have-nots is a phenomenon documented throughout the world. Health gaps exist between rich and poor well-educated and less-educated rural and urban--even between impoverished and marginalized groups. The initiation of the Millennium Development Goals (MDGs) brings new energy and resources to the development agenda with a strong emphasis on health outcomes. However ensuring that such goals are met in an equitable manner with the worst-off groups benefiting at the same or greater rate as the better-off groups is a central challenge. One place to start is by identifying inequity between different population groups and across different social strata. Inequity baselines can be created to illuminate how different indicators and social stratifiers yield different patterns of disparity. Using population-based surveys such baselines can be established even in data-poor countries. Using survey data from Ghana Ethiopia Kenya Tajikistan Dominican Republic and Cambodia this Guide demonstrates how to establish such a baseline. This Guide is for researchers program staff and policymakers interested in undertaking equity-sensitive monitoring of key health (or other development) indicators within a given country (as opposed to cross-national studies). The Guide provides a method for analyzing indicators across a number of social strata including wealth ethnicity education region sex and geography. The methodology presented includes both single and simultaneous stratification that allow for the generation of fairly simple quick equity-monitoring tools. The mode of presentation is instructional rather than theoretical. Although the examples used here are based on the DHS and MICS the methods can be easily adapted for use with other surveys including those that are not nationally representative. Currently countries lacking vital registration systems rely on population-based surveys for MDG monitoring. As long as a country has at least one population-based household survey containing information on social characteristics as well as health analysts can also use this data source for equity monitoring Furthermore although the Guide is based upon the health MDGs the techniques described herein could be adapted for non-health MDGs (e.g. education water and sanitation) as well as other development goals at the national or subnational level. (excerpt)
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