While the national prevalence of stunting in Indonesia has decreased, the level remains high in many districts/cities and there is significant variation. This ecological study employed aggregated data from the Basic Health Research Report and the District/City Poverty Data from 2018. We investigated the determinants of stunting prevalence at the district/city level, including autocorrelation applying the spatial autoregressive (SAR) model. The analyses revealed stunting prevalence above the national average in 282 districts/cities (54.9%), i.e. ≥30% in 297 districts/cities (57.8%) and ≥40% in 91 districts/cities (17.7%). Autocorrelation was found between Sumatra, Java, Sulawesi as well as Bali, East Nusa Tenggara and West Nusa Tenggara (Bali NTT NTB). The SAR modelling revealed the following variables with significant impact on the stunting prevalence in various parts of the country: closet defecation, hand washing, at least four antenatal care visits during pregnancy, poverty, immunisation and supplementary food for children under 5 years.

Objectives. To find stunting hotspots district or cities in Indonesia in seven major islands in Indonesia. Method. This is an ecological study that using aggregate data. We used data from The Basic Health Research Report of Indonesia 2018 and The Poverty Data and Information Report from the Central Bureau of Statistics 2018. We analyzed 514 districts or cities in Indonesia that spread out in 7 major Islands with 34 provinces. We used The Euclidean distance method to determine the neighborhood. Morans test was occupied to identify autocorrelation while Morans Scatter Plot particularly in the high high quadrant was used to identify stunting hotspot areas. Result. It was found that there is autocorrelation among districts or cities in four major islands namely Sumatera, Java, Sulawesi, and Bali Nusa Tenggara Timur Nusa Tenggara Barat. We identified 135 districts or cities as stunting hotspot areas that spread in 14 provinces in four islands. Conclusion. There is autocorrelation among districts or cities in Sumatera, Java, Sulawesi, and Bali NTT NTB which resulted in 135 districts or cities identified as stunting hotspots in four major islands in Indonesia Policy implication. Provide information to the government in prioritizing stunting prevention areas in Indonesia in term of the acceleration of stunting prevention.

Background Indonesia is a vast country that is still struggling to reduce its prevalence of stunting. Thus, identifying priority areas is urgent. In determining areas to prioritize, one needs to consider geographical issues, particularly the correlation among areas. This study aimed to discover whether stunting prevalence in Indonesia occurs randomly or in clusters and, if it occurs in clusters, which areas are the hotspots. Method This ecological study used aggregate data from the Basic Health Research Report of Indonesia 2018 and the Poverty Data and Information Report from the Central Bureau of Statistics 2018. We analysed 514 districts/cities across 34 provinces on seven major Indonesian islands. We used the Euclidean distance method to determine stunting hotspots. A Moran’s I test was used to identify autocorrelation, while a Moran scatter plot was used to identify stunting hotspots, particularly those in the high–high quadrant. Result Autocorrelation was found among districts/cities in Sumatera, Java, Sulawesi, and Bali Nusa Tenggara Timur (NTT) and Nusa Tenggara Barat (NTB), resulting in 135 districts/cities identified as stunting hotspots on four major islands. Conclusion Autocorrelation proves that stunting in Indonesia does not occur randomly.