ArticleInternational journal of environmental research and public health2022
Spatial and Machine Learning Approach to Model Childhood Stunting in Pakistan: Role of Socio-Economic and Environmental Factors.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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4 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Artificial Intelligence in Malnutrition: A Systematic Literature Review.Advances in nutrition (Bethesda, Md.) · 2024Pooled it
- Exploring the Effects of Climate Change on Child Malnutrition: A Scoping Review.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2026Article
- Spatial Inequality in Under-Five Children Undernutrition: Evidence From Ethiopia.Journal of tropical medicine · 2026Article
- Childhood stunting is highly clustered in Northern Province of Rwanda: A spatial analysis of a population-based study.Heliyon · 2024Article
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2 authors at 1 institution in 1 country.
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Abstract
This study presents the determinants of childhood stunting as the consequence of child malnutrition. We checked two groups of factors-the socio-economic situation and climate vulnerability-using disaggregated sub-regional data in the spatial context. Data related to the percentage of stunted children in Pakistan for 2017 were retrieved from MICS 2017-18 along with other features. We used three quantitative models: ordinary least squares regression (OLS) to examine the linear relationships among the selected features, spatial regression (SDEM) to identify and capture the spatial spillover effect, and the Extreme Gradient Boosting machine learning algorithm (XGBoost) to analyse the importance of spatial lag and generate predictions. The results showed a high degree of spatial clustering in childhood stunting at the sub-regional level. We found that a 1 percentage point (p.p.) increase in multi-dimensional poverty may translate into a 0.18 p.p. increase in childhood stunting. Furthermore, high climate vulnerability and common marriages before age 15 each exacerbated childhood stunting by another 1 p.p. On the contrary, high female literacy and their high exposure to mass media, together with low climate vulnerability, may reduce childhood stunting. Model diagnostics showed that the SDEM outperformed the OLS model, as AIC
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