The Severe Stunting Cases of Children in Central Java Province Explained by Negative Binomial Regression Model

Rhendy K. P. Widiyanto; Fatkhurokhman Fauzi; Achmad Fauzan; Anang Kurnia

doi:10.31764/jtam.v10i1.34846

The Severe Stunting Cases of Children in Central Java Province Explained by Negative Binomial Regression Model

Rhendy K. P. Widiyanto, Fatkhurokhman Fauzi, Achmad Fauzan, Anang Kurnia

Abstract

Severe stunting, or very short stature among children, remains a critical public health concern in Central Java Province. Robust statistical modelling is essential to identify the key factors associated with these cases and to guide targeted interventions. This study employs count regression models with an offset variable to analyze the factors influencing severe stunting cases across districts in Central Java. By using 2023 official data in districts level taken from the Ministry of Home Affairs and the Statistics Indonesia, we initially utilize a Poisson regression model in this study. However, due to evidence of overdispersion, a Negative Binomial regression model was adopted. Backward elimination was then applied to obtain the most parsimonious model. The Negative Binomial regression successfully addressed overdispersion. Five factors were identified as having a statistically significant influence on severe stunting cases: (1) the proportion of pregnant mothers with Chronic Energy Deficiency receiving nutritious food supplements, (2) the percentage of toddlers (6-23 months) receiving complementary nutritious food, (3) the proportion of households with access to good sanitation, (4) Gross Domestic Product per capita, and (5) the number of local healthcare facilities. These factors have negative relation to the stunting rates, meaning improving these factors will reduce the rates of severe stunting. The findings provide a validated statistical model for severe stunting and offer clear policy directions. To mitigate severe stunting, local governments should prioritize: enhancing nutritious food support for pregnant mothers and toddlers, improving household sanitation, stimulating local economic growth, and increasing accessibility to healthcare facilities.

Keywords

Backward Elimination; Severe Stunting; Negative Binomial Regression; Overdispersion; Poisson Regression.

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DOI: https://doi.org/10.31764/jtam.v10i1.34846