PLOS ONE · 9 authors, 5 centres
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This cross-sectional study used spatial regression on national survey data to identify geographic hot spots of home birth in Ethiopia and their predictors. The central result was that rural residence, no education, poorest wealth index, Muslim religion, and no antenatal care visits were significant predictors of home delivery hotspot regions.
This study analyzed secondary data from the 2019 Ethiopian Mini Demographic and Health Survey to identify geographic patterns and predictors of home birth. Spatial regression models, including ordinary least squares (OLS) and geographically weighted regression (GWR), were then used to predict hotspot areas. The OLS model explained 76% of the variability in home birth. Key predictors identified were the proportion of women from rural residence, with no formal education, in the poorest wealth index, Muslim religion followers, and those with no antenatal care (ANC) visits. The study notes limitations related to geographic data displacement and the exclusion of some potential confounders. The findings suggest targeted public health efforts should focus on improving healthcare access and strengthening antenatal care visits, particularly for rural and socioeconomically disadvantaged women.
