Stunting is a chronic growth disorder in children under five that requires evidence-based interventions. To understand the factors that contribute to stunting in different regions of Indonesia, Bayesian Conditional Autoregressive (CAR) modeling was used to estimate the relative risk of stunting. The analysis showed that the Besag-York-Mollié (BYM) model with covariates provided the best results in estimating the risk of stunting. The data for this study were obtained from the 2018 Basic Health Research Survey. In urban areas, immunization coverage has a significant effect on stunting risk, while in rural areas, in addition to immunization, vitamin supplementation coverage and poverty level are also significant factors. Based on the modeling, the region with the highest risk in urban areas is West Sulawesi Province with a relative risk of 1.638, while the lowest is Bali Province with 0.564. In rural areas, Papua Province had the highest risk of 1.820, while North Sulawesi Province had the lowest risk of 0.599. These findings suggest that immunization coverage is instrumental in reducing stunting, both in urban and rural areas. In addition, in rural areas, increasing vitamin supplementation coverage and decreasing poverty levels can help reduce the risk of stunting. Therefore, intervention policies should be tailored to the characteristics of each region to be more effective in addressing stunting in Indonesia.
Zulhijrah et al. (Sun,) studied this question.