Spatial Bayes Analysis on Cases of Malnutrition in East Nusa Tenggara, Indonesia

This study models and maps malnutrition cases in East Nusa Tenggara using a spatial Bayes approach with INLA. Findings show that poverty depth is the main factor influencing malnutrition, with high-risk areas identified in Sumba Barat Daya, Sumba Barat, and Sumba Utara. Other factors include immunization rates, healthcare access, population density, and breastfeeding duration.