Spatial variation of zero vitamin A-rich food consumption and associated factors among children aged 6-23 month in Ethiopia

Abstract Zero vitamin A-rich food consumption defined as the absence of any vitamin A-rich food intake among children aged 6–23 months within a 24-hour recall period. Substantial regional, socioeconomic, and agro-ecological disparities suggest that zero vitamin A-rich food consumption may exhibit geographic variation across the country. However, evidence on its spatial distribution and context-specific determinants remains limited. Therefore, this study aimed to assess the spatial variation of zero vitamin A-rich food consumption and its associated factors among children aged 6–23 months in Ethiopia using nationally representative data. Methods : A community-based cross-sectional study was conducted using nationally representative data from the 2019 EMDHS. The study included a weighted sample of 1,543 children aged 6–23 months with complete information on vitamin A-rich food consumption. Stratified two-stage cluster sampling technique was applied in the original survey. Data were analyzed using Stata 16, ArcGIS 10.8, SaTScan 9.6, and MGWR 2.0. Spatial autocorrelation was assessed using Global Moran’s I, and hot spot analysis was performed using the Getis-Ord Gi* statistic. Model comparison was conducted using adjusted R² and AICc values, and statistical significance was declared at p < 0.05 with a 95% confidence interval. Result : The spatial distribution of zero vitamin A-rich food consumption among children aged 6–23 months was non-random in Ethiopia (Moran’s I = 0.874, p < 0.001). Hot spot and spatial scan analyses identified 74 significant clusters. Maternal current pregnancy status, marital status, maternal education, number of under-five children, and age of the child were significant predictors of the spatial variation of zero vitamin A-rich food consumption. Conclusion : Significant geographic variation in zero vitamin A-rich food consumption was observed across Ethiopia. Maternal education, current pregnancy status, number of under-five children, marital status, and child age were significant predictors. These findings highlight the need for geographically targeted, context-specific interventions.