Model comparison of OLS and GWR model.

BackgroundOverweight/ obesity among under-five children is an emerging public health issue of the twenty-first century. Due to the quick nutritional and epidemiological change, non-communicable diseases, premature death, disability, and reproductive disorders have grown in low-income countries. Besides, little attention has been given. Therefore, we aimed to explore spatial variations and predictors of overweight/obesity among under-five children in Ethiopia using a geospatial technique.MethodsA total weighted sample of 3,609 under-five children was included in the study. A cross-sectional study was conducted using a nationally representative sample of the 2019 Ethiopia Mini Demographic and Health Survey data set. ArcGIS version 10.8 was used to explore the spatial variation of obesity. SaTScan version 9.6 software was used to analyze the spatial cluster detection of overweight/obesity. Ordinary least square and geographically weighted regression analysis were employed to assess the association between an outcome variable and explanatory variables. A p-value of less than 0.05 was used to declare it statistically significant.ResultsThe spatial distribution of overweight/obesity among under-five children in Ethiopia was clustered (Global Moran’s I = 0.27, p-valueConclusionsOverweight or obesity among under-five children show spatial variations across Ethiopian regions. GWR analysis identifies cesarean section, wealth index, urban residence, and child sex as significant predictors. The Ministry of Health and Ethiopian Public Health Institute should target regions with these contributing predictors, promoting localized physical education, health education campaigns, and ongoing community monitoring to encourage active lifestyles and reduce sedentary behaviors among children.