SPATIAL MODELING OF RISK FACTORS FOR UNDER-FIVE PNEUMONIA IN ROKAN HILIR DISTRICT, INDONESIA.

Abstract

Background: Under-five pneumonia remains a critical health issue in Indonesia. Identifying risk factors using spatial models is crucial for developing effective disease-prevention strategies. This study aimed to identify risk factors and create a spatial model for under-five pneumonia distribution based on regional vulnerability.

Materials and methods: This study used a mixed-method approach that integrated mathematical models and GIS to identify risk factors using generalized Poisson regression (GPR) and developed a GIS-based spatial model with inverse distance weighted (IDW) and natural break methods.

Results: The GPR model revealed significant associations between under-five pneumonia and population density (β = 0.004, Z_-score = 6.118), rainfall (β = 0.002, Z_-score = 6.031), malnutrition (β = 1.786, Z_-score = 3.696), and health facilities (β = 0.073, Z_-score = 13.527). Protective factors included exclusive breastfeeding (β = -0.004, Z_-score = -2.874), healthy homes (β = -0.021, Z_-score = -9.532), and under-five health service coverage (β = -0.003, Z_-score = -2.225). Spatial modeling classified regions into high-risk (5 subdistricts), medium-risk (11 subdistricts), and low-risk (3 subdistricts).

Conclusion: This study identified key risk factors and mapped spatial vulnerability for under-five pneumonia. Targeted, integrated interventions in high-risk areas are essential to reduce pneumonia incidence below 12 cases per 1,000 children under five by 2030, aligning with global health goals.