BackgroundAdaptive and innovative technologies to prevent stunting are being developed continuously in various countries. This study aimed to develop and evaluate the accuracy of a stunting risk detection application based on nutrition and sanitation indicators in children aged under five years.MethodsThis cross-sectional study was conducted between June and September 2023 and involved 316 mother-child pairs selected by simple random sampling from urban (n = 244) and rural (n = 72) areas in Bogor, West Java Province, Indonesia. An application was developed to detect stunting risk based on 25 indicators: eight indicators of maternal and child characteristics, eight nutrition indicators, and nine indicators of personal hygiene and sanitation. The nutrition and sanitation indicators were determined according to the World Health Organization conceptual framework for stunting. The accuracy of the stunting prediction model was analyzed using the Area Under Curve (AUC) and the Receiver Operating Characteristics (ROC) Curve method.ResultsOf the 316 included children, 29.5% were stunting. The developed stunting risk detection application exhibited good sensitivity (88.3%) and specificity (83.3%). It accurately detected children at risk of stunting with an AUC of 89.6%. In urban areas, eight indicators were significantly predictive of stunting: mother’s height, child’s age, exclusive breastfeeding, frequency of protein consumption, balanced diet, washing hands with soap, availability of complete room functions in the house, and good household waste management. In rural areas, eight indicators were significantly predictive of stunting: mother’s height, history of infectious disease, early initiation of breastfeeding, frequency of protein consumption, complementary feeding, washing hands with soap, availability of safe food storage, and availability of clean water sources for drinking. Mother’s height was the dominant factor in predicting stunting in urban (adjusted odds ratio [aOR] = 3.321, 95% confidence interval [CI] = 1.202–3.051, p = 0.006) and rural (aOR = 3.927, 95% CI = 1.132–4.281, p = 0.001).ConclusionThe developed application exhibited good accuracy and quickly assessed the risk of stunting in children, enabling it to provide appropriate recommendations to prevent stunting. However, it must be improved by simplifying the number of included indicators and re-testing on a broader scale.
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