Geospatial and multivariate analysis of under-five stunting children in Rwanda using DHS 2020

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Abstract
Background: Malnutrition is a major public health concern worldwide; a recent study found that 22% of children under the age of five were stunted worldwide in 2020. Stunting in Rwanda has decreased dramatically over the last 15 years, from 51% in 2005 to 33% by 2020. However, because few geospatial studies have been conducted, geographical survey data analysis is required to effectively focus stakeholders' efforts in response to successful stewardship of health programs in the eradication of all types of malnutrition. The study's goal is to map the prevalence distribution of stunted children under the age of five, make Projections, and provide exceedance probability maps for each stunting at the 30% threshold value, as well as identify risk factors associated with stunting in Rwanda. Methods: This study makes use of Rwandan Demographic and Health Surveys (R-DHS)2019/2020. To obtain the marginal posterior distribution of stunting prevalence at each location in Rwanda, the Bayesian model was developed using an integrated nested Laplace approximation technique. The risk factors for stunting were identified using multivariate logistic regression. Results: This research finds the prevalence of stunting in 500 clusters. Kigali city clusters had the lowest prevalence, ranging from 0% to 25%. The Western Province, specifically the Congo Nile Divide, has the highest rate where some clusters have more than 60%. The 30% probability threshold enables the identification of Rwandan areas and communities most vulnerable to stunting. In Rwanda, regional disparities in childhood stunting are significant. There is statistically significant child, maternal, and socio-demographic characteristics with p-values less than 5% in a 95% confidence interval (CI). Among the risk factors are the baby's birth weight (OR:2.18, CI: [1.613-2.95], intestinal parasites (OR:1.544, 95% CI: [1.253-1.903], and the baby's age (OR:1.095, 95% CI: [1.024-1.171]. Province and altitude have ORs of 1.088 and 1.575, respectively, in socio-demographic factors. Conclusions: Finally, geospatial studies should be conducted to identify locations that require more attention in disease and epidemic control and multivariate logistic regression to identify risk factors. Therefore, more attention of malnutrition eradication should be paid to Rwanda's Western and Northern Provinces. The findings of this study may be useful to program managers and decision makers working to reduce the burden of stunting.

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