Measuring the geographic distribution of maternal education in Africa

Thesis (Master's)--University of Washington, 2016-08

International agendas have increasingly focused on education as a powerful social determinant of child and maternal health outcomes. However, comparable indicators of educational attainment only exist at the national level, which may obscure subnational inequality in both levels and progress. The advent of increasingly granular geographic data in household surveys along with advances in the field of Bayesian model-based geostatistics (MBG) allows for precise, efficient estimation of basic educational indicators at a high spatial resolution. By applying these methods to three years of data from the Demographic Health Survey (DHS) in Uganda, Kenya, and Nigeria, this study reveals stark geographic inequality in the most basic indicators of educational attainment despite apparent national progress. Moving into the era of the Sustainable Development Goals (SDGs), this underscores the need for evaluating progress at a more local level to avoid patterns of funding that may boost national statistics but entrench existing subnational inequities.