ArticleBMC public health2022
Bayesian geostatistical modelling of stunting in Rwanda: risk factors and spatially explicit residual stunting burden.
Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 32 citations in OpenAlex.
- Lack of Associations between Environmental Exposures and Environmental Enteric Dysfunction among 18-Month-Old Children in Rural Malawi.International journal of environmental research and public health · 2022Trial
- Article
- Altitude of area of residence as a risk factor for stunting in children aged 0-60 months: A systematic review and meta-analysis.Dialogues in health · 2026Review
- Article
- Predicting Stunting Beyond Borders: Lessons From an Ethiopian Model and Pathways for Global Application.Health science reports · 2026Article
- Bayesian spatio-temporal conditional autoregressive localized modeling techniques for socioeconomic factors and stunting in Indonesia.MethodsX · 2025Article
- BARTSIMP: Flexible spatial covariate modeling and prediction using Bayesian Additive Regression Trees.Spatial and spatio-temporal epidemiology · 2025Article
- Spatio-temporal variation of child stunting and associated risk factors in Rwanda.BMC public health · 2025Article
- Identification of amendable risk factors for childhood stunting at individual, household and community levels in Northern Province, Rwanda - a cross-sectional population-based study.BMC public health · 2025Article
- Prevalence and determinants of stunting and anaemia in children aged 6-23 months: A multilevel analysis from rural Ethiopia.Maternal & child nutrition · 2025Article
- Childhood stunting is highly clustered in Northern Province of Rwanda: A spatial analysis of a population-based study.Heliyon · 2024Article
- Socio-economic, demographic, and contextual predictors of malnutrition among children aged 6-59 months in Nigeria.BMC nutrition · 2024Article
- Spatial heterogeneity and predictors of stunting among under five children in Mozambique: a geographically weighted regression.Frontiers in public health · 2024Article
- Geospatial Overlap of Undernutrition and Tuberculosis in Ethiopia.International journal of environmental research and public health · 2023Article
- Mapping Local Variations and the Determinants of Childhood Stunting in Nigeria.International journal of environmental research and public health · 2023Article
- Spatial trends and projections of chronic malnutrition among children under 5 years of age in Ethiopia from 2011 to 2019: a geographically weighted regression analysis.Journal of health, population, and nutrition · 2022Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStunting remains a significant public health issue in Rwanda and its prevalence exhibits considerable geographical variation. We apply Bayesian geostatistical modelling to study the spatial pattern of stunting in children less than five years considering anthropometric, socioeconomic and demographic risk factors in Rwanda. In addition, we predict the spatial residuals effects to quantify the burden of stunting not accounted for by our geostatistical model.
methodsWe used the data from the 2015 Rwanda Demographic and Health Survey. We fitted two spatial logistic models with similar structures, only differentiated by the inclusion or exclusion of spatially structured random effects.
resultsThe risk factors of stunting identified in the geostatistical model were being male (OR = 1.32, 95% CI: 1.16, 1.47), lower birthweight (kg) (OR = 0.96, 95% CI: 0.95, 0.97), non-exclusive breastfeeding (OR = 1.24, 95% CI: 1.04, 1.45), occurrence of diarrhoea in the last two weeks (OR = 1.18, 95% CI: 1.02, 1.37), a lower proportion of mothers with overweight (BMI ≥ 25) (OR = 0.82, 95% CI: 0.71, 0.95), a higher proportion of mothers with no or only primary education (OR = 1.14, 95% CI: 0.99, 1.36). Also, a higher probability of living in a house with poor flooring material (OR = 1.22, 95% CI: 1.06, 1.41), reliance on a non-improved water source (OR = 1.13, 95% CI: 1.00, 1.27), and a low wealth index were identified as risk factors of stunting. Mapping of the spatial residuals effects showed that, in particular, the Northern and Western regions, followed by the Southern region of Rwanda, still exhibit a higher risk of stunting even after accounting for all the covariates in the spatial model.
conclusionsFurther studies are needed to identify the still unknown spatially explicit factors associated with higher risk of stunting. Finally, given the spatial heterogeneity of stunting, interventions to reduce stunting should be geographically targeted.
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