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Monitoring Progress in Equality for the Sustainable Development Goals: A Case Study of Meeting Demand for Family Planning.
Global Health, Science and Practice 2018 June 28
OBJECTIVES: Equality is a central component of the Sustainable Development Goals (SDGs). We took one SDG indicator and benchmark-percent of family planning demand met with modern contraceptives, with a benchmark of at least 75% in all countries-as a case study to illuminate recommendations for monitoring equality. Specifically, we assessed levels, patterns, and trends in disparity by key background characteristics and identified disparity measures that are programmatically relevant and easy to interpret.
METHODS: Data were from the Demographic and Health Surveys in 55 countries that have conducted at least 2 surveys since 1990. We calculated absolute difference among subgroups, disaggregated by age, education, household wealth quintile, urban/rural residence, subnational region/administrative unit, and marital status. Our unit of analysis was survey, and we conducted largely descriptive analyses. To understand trends in disparity, we used a fixed-effect linear regression model to estimate an annual rate of change in absolute differences.
RESULTS: A significant level of disparity existed across various background characteristics, ranging from a median difference of 5 percentage points by marital status to 32 percentage points by administrative unit. On average across the study countries, national level of met demand has increased over time while disparity has declined in most disaggregates including by education, wealth, residence, and age. We found statistically significant positive correlations among 4 disparity measures-education, wealth, residence, and administrative unit. Disparities by wealth quintile were easiest to interpret over time and across countries.
CONCLUSIONS: At the global level, we recommend monitoring disparity in met demand by wealth quintile, which is strongly correlated with disparity by education, residence, and region and comparable across countries and over time. For monitoring by individual countries and for programmatic purposes, we further recommend monitoring disparity by first-level administrative unit, which can provide direct programmatic relevance.
METHODS: Data were from the Demographic and Health Surveys in 55 countries that have conducted at least 2 surveys since 1990. We calculated absolute difference among subgroups, disaggregated by age, education, household wealth quintile, urban/rural residence, subnational region/administrative unit, and marital status. Our unit of analysis was survey, and we conducted largely descriptive analyses. To understand trends in disparity, we used a fixed-effect linear regression model to estimate an annual rate of change in absolute differences.
RESULTS: A significant level of disparity existed across various background characteristics, ranging from a median difference of 5 percentage points by marital status to 32 percentage points by administrative unit. On average across the study countries, national level of met demand has increased over time while disparity has declined in most disaggregates including by education, wealth, residence, and age. We found statistically significant positive correlations among 4 disparity measures-education, wealth, residence, and administrative unit. Disparities by wealth quintile were easiest to interpret over time and across countries.
CONCLUSIONS: At the global level, we recommend monitoring disparity in met demand by wealth quintile, which is strongly correlated with disparity by education, residence, and region and comparable across countries and over time. For monitoring by individual countries and for programmatic purposes, we further recommend monitoring disparity by first-level administrative unit, which can provide direct programmatic relevance.
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