Location Based Stunting Modeling Using Geographically Weighted Panel Regression in Blitar Regency

Abstract

Stunting remains a significant public health issue in Blitar Regency, Indonesia, particularly in rural areas where chronic malnutrition and inadequate access to healthcare services persist as major challenges. This study aims to explore the spatial and temporal factors influencing stunting using the Geographically Weighted Panel Regression (GWPR) method. By integrating cross-sectional and time-series data from 2021 to 2023, the study evaluates various factors, including the stunting prevalence rate and independent variables such as maternal education level, per capita income, the number of postpartum mothers receiving Vitamin A supplements, immunization coverage, and the availability of healthcare personnel. The findings reveal that stunting prevalence is significantly influenced by location-specific variables, with healthcare access and nutrition being dominant factors in rural areas, while economic conditions exert a greater influence in urban areas. The GWPR model provides deeper insights into spatial heterogeneity and offers valuable guidance for designing targeted and region-specific policies to reduce stunting rates in Blitar Regency. The results indicate that the R-Square value of the GWPR model is 0.9123, meaning that 91.23% of the stunting prevalence in Blitar Regency can be explained by the independent variables in this study