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Equitable access to programs and health services is essential to achieving national and international health goals, but it is rarely assessed because of perceived measurement challenges. One of these challenges concerns the complexities of collecting the data needed to construct asset or wealth indices, which can involve asking as many as 40 survey questions, many with multiple responses. To determine whether the number of variables and questions could be reduced to a level low enough for more routine inclusion in evaluations and research without compromising programmatic conclusions, we used data from a program evaluation in Honduras that compared a pro-poor intervention with government clinic performance as well as data from a results-based financing project in Senegal. In both, the full Demographic and Health Survey (DHS) asset questionnaires had been used as part of the evaluations. Using the full DHS results as the "gold standard," we examined the effect of retaining successively smaller numbers of variables on the classification of the program clients in wealth quintiles. Principal components analysis was used to identify those variables in each country that demonstrated minimal absolute factor loading values for 8 different thresholds, ranging from 0.05 to 0.70. Cohen's kappa statistic was used to assess correlation. We found that the 111 asset variables and 41 questions in the Honduras DHS could be reduced to 9 variables, captured by only 8 survey questions (kappa statistic, 0.634), without substantially altering the wealth quintile distributions for either the pro-poor program or the government clinics or changing the resulting policy conclusions. In Senegal, the 103 asset variables and 36 questions could be reduced to 32 variables and 20 questions (kappa statistic, 0.882) while maintaining a consistent mix of users in each of the 2 lowest quintiles. Less than 60% of the asset variables in the 2 countries' full DHS asset indices overlapped, and in none of the 8 simplified asset index iterations did this proportion exceed 50%. We conclude that substantially reducing the number of variables and questions used to assess equity is feasible, producing valid results and providing a less burdensome way for program implementers or researchers to evaluate whether their interventions are pro-poor. Developing a standardized, simplified asset questionnaire that could be used across countries may prove difficult, however, given that the variables that contribute the most to the asset index are largely country-specific.

Measurement of Health Program Equity Made Easier: Validation of a Simplified Asset Index Using Program Data From Honduras and Senegal