Abstract
Stunting remains a significant public health burden in sub-Saharan Africa and has far reaching consequences. Identifying the drivers of stunting and high burden regions is key to developing effective and targeted intervention strategies. The objective of the study was to identify the risk factors and explore spatial patterns of stunting across counties in Kenya. Secondary data from 2022 Kenya Demographic Health Survey (KDHS) was utilized. A total of 13,016 children aged between 0 - 59 months were included in the analysis. A multilevel logistic regression was applied to identify individual, household and community level determinants of stunting, spatial regression models to analyze spatial dependency and geographically weighted regression to explore spatial heterogeneity in the association between childhood stunting and county level determinants. In the multilevel logistic regression, Children from urban residence exhibited a significantly increased odds of stunting compared to those in rural areas (aOR = 1.25, 95% CI: 1.03 - 1.51, p = 0.02). Children from households categorized as poorer, middle, richer, and richest all exhibited significantly reduced odds of stunting compared to those from the poorest households. Children whose mothers had attained secondary education exhibit higher odds of stunting compared to those with no education (aOR = 1.32, 95% CI: 1.01 - 1.72, p = 0.04). Male children show significantly higher odds of stunting compared to females (aOR = 1.50, 95% CI: 1.33 - 1.70, p < 0.001). Children aged 12-23 months exhibit the highest odds of stunting (aOR = 2.65, 95% CI: 2.23 - 3.14, p < 0.001) compared to those aged < 6 months). Spatial analysis indicated that stunting prevalence varies geographically, with some areas exhibiting higher clustering. The geographically weighted regression further revealed that the influence of socioeconomic and climatic factors on stunting prevalence differed across locations highlighting the need for geographically targeted interventions.
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