Predicting severe stunting and its determinants among under-five in Eastern African Countries: A machine learning algorithms

The Random Forest was the best-performing model for predicting severe stunting in Eastern African countries. To decrease the effects of severe stunting, integrated interventions should provide support for mothers with lower socioeconomic conditions, strengthen maternal education, empower women to practice exclusive breastfeeding, encourage facility deliveries, increase access for households to sanitary facilities, provide education on personal and environmental hygiene, provide mothers with information on the importance of complementary feeding for children as well as for the mothers, and provide near health facilities for mothers and essential care services.

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Publication Details

Journal
PLoS ONE
Published
2026-01-02
DOI
https://doi.org/10.1371/journal.pone.0340221
Primary Topic
Child Nutrition and Water Access
Type
article
Field-Weighted Citation Impact
0.00
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article

Predicting severe stunting and its determinants among under-five in Eastern African Countries: A machine learning algorithms

Altaseb Beyene Kassaw, Kassahun Dessie Gashu, Halid Worku Jemil, Sonia Worku Semayneh
PLoS ONE
Child Nutrition and Water Access
article

Predicting severe stunting and its determinants among under-five in Eastern African Countries: A machine learning algorithms

Altaseb Beyene Kassaw, Kassahun Dessie Gashu, Halid Worku Jemil, Sonia Worku Semayneh
article en

Abstract

The Random Forest was the best-performing model for predicting severe stunting in Eastern African countries. To decrease the effects of severe stunting, integrated interventions should provide support for mothers with lower socioeconomic conditions, strengthen maternal education, empower women to practice exclusive breastfeeding, encourage facility deliveries, increase access for households to sanitary facilities, provide education on personal and environmental hygiene, provide mothers with information on the importance of complementary feeding for children as well as for the mothers, and provide near health facilities for mothers and essential care services.

PLoS ONEVol. 21(1)
Wollo University (ET), Tikur Anbessa Hospital (ET), University of Gondar (ET)
Openalex Percentile: Top 99%
Child Nutrition and Water Access
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Predicting severe stunting and its determinants among under-five in Eastern African Countries: A machine learning algorithms — Altaseb Beyene Kassaw, Kassahun Dessie Gashu, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS