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

ABSTRACT:

Introduction

Severe stunting is one of the primary public health challenges in LMIC including Eastern African Countries, which affects millions of children. In addition, it was a major contributor for mortality and related complication of children aged under five. However, there is limited study conducted severe form of stunting by employing Machine learning (ML) in Eastern African Countries. Therefore, our study was demonstrated to predict and identify its major determinants using ML algorithms, furthermore, to improve model explainablity. Our study used Shapley Additive explanations (SHAP) and ARM to identify the determinants of severe stunting among under-five.

Methods

cross-sectional study was conducted using DHS data from 2012-2022 in East Africa. 136,074 children were

SUBMITTER: Jemil HW 

PROVIDER: S-EPMC12758688 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature