<![CDATA[Stunting is a serious global health issue, including in Indonesia. This study aimed to analyze factors influencing stunting incidence among toddlers in Kendari City, Indonesia, using a spatial regression approach. This study employed a descriptive ecological design using secondary data from the Kendari City Health Office in 2024 across 11 sub-districts. Spatial analysis was conducted using a Queen contiguity weighting matrix. The results showed that Moran's I value was not statistically significant (p>0.05), indicating weak global spatial autocorrelation. However, Lagrange Multiplier tests revealed that the LM-Lag and Robust LM-Lag were significant (p<0.05), suggesting the presence of spatial dependence. Therefore, the Spatial Autoregressive (SAR) model was selected. The SAR model demonstrated better performance compared to the OLS model (AIC=83.20; R²=97.91%). Significant factors influencing stunting incidence included the number of toddlers, low birth weight (LBW), unmonitored child growth, lack of complementary feeding (MP-ASI), incomplete basic immunization, and lack of additional nutritional intake. These findings highlight the importance of spatial-based interventions in addressing stunting at the sub-district level.]]>
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