Stunting is a growth disorder in children caused by chronic malnutrition and recurrent infections. According to SSGI, the stunting prevalence rate in Indonesia was 21.6% in 2022, decreasing from 27.7% in 2019. However, it remains far from 5% stunting target for Golden Indonesia 2045. This study aims to analyze the determinants of stunting prevalence based on socio-economic factors accommodating spatial aspect using Bayesian Spatial analysis with inference based on INLA (Integrated Nested Laplace Approximation). The Bayesian Spatial Model used is a conditional autoregressive that incorporates stunting prevalence rate as the response variable. The spatial modelling results indicate that the food security index, percentage of households with improved drinking water services, and per capita expenditure have significant impacts on the stunting prevalence rate. Spatial mapping reveals regional bonding affecting stunting prevalence rates and shows the vulnerability distribution of regencies and municipalities with stunting prevalence above the national rate.
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