Predicting stunting incidence in Pidie, Indonesia using SEM-PLS and GIS: A multilevel analysis of determinants

Stunting is a complex child health issue caused by poor nutrition, infections, and environmental factors. The Pidie District in Aceh, Indonesia, has been identified as a high-priority area for stunting intervention, with five sub-districts showing high prevalence rates. This study aims to identify the key determinants of stunting at the individual, household, and community levels and to develop a predictive model for stunting incidence in these areas. Structural Equation Modeling-Partial Least Squares (SEM-PLS) and Geographic Information Systems (GIS) were used to analyze the causal relationships and spatial distribution of stunting. Data were collected using a structured questionnaire and total sampling method, involving 988 mother-child pairs across Tangse (211), Tiro (46), Kembang Tanjong (321), Simpang Tiga (361), and Mutiara Timur (49). SEM-PLS results indicated that stunting is consistent with the Conceptual Childhood Stunting Model and the Social Determinants of Health (CSDH) framework, with the model explaining 73.2% of the variance in stunting cases (R² = 0.732). GIS mapping showed that Kembang Tanjong had the highest number of cases (184), while Tiro had the lowest (25). The main contributing factors were individual characteristics, household socioeconomic status, and community conditions. These findings suggest that targeted interventions addressing local risk factors, along with improvements in nutrition, healthcare access, and socioeconomic development, are essential to reduce stunting in the Pidie District.