ArticleBMC public health2024
Application of the Boruta algorithm to assess the multidimensional determinants of malnutrition among children under five years living in southern Punjab, Pakistan.
Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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18 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Risk prediction models for dental caries in children and adolescents: a systematic review and meta-analysis.BMJ open · 2025Pooled it
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- Machine learning and SHAP interpretation for predicting coronary heart disease-diabetes comorbidity with dietary antioxidants.Scientific reports · 2026Article
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- Prevalence and Determinants of Undernutrition Among Children Under Five in Coastal Bangladesh: A Community-Based Study.Food science & nutrition · 2026Article
- Exclusive breastfeeding and risk of malnutrition in children: the healthcare provider-led education in Mwanza, Tanzania.Frontiers in nutrition · 2026Article
- Integrative profiling of lactylation reveals prognostic biomarkers and an immunosuppressive niche in acute myeloid leukemia.Frontiers in immunology · 2026Article
- Body mass index mediates the association between heavy metal exposure and overactive bladder risk: insights from a nationally representative cross-sectional study using explainable machine learning.Translational andrology and urology · 2025Article
- The Importance of Socioeconomic Factors Associated with Maternal Nutrition Knowledge and Undernutrition Among Children Under Five.Nutrients · 2025Article
- Development of machine learning models for chronic fatigue prediction in granulomatosis with polyangiitis.Advances in rheumatology (London, England) · 2025Article
- Improving early intervention: identifying risk factors for UK military veterans that access military charities-a case-control study and an AI-powered predictive model.European journal of public health · 2025Article
- Development and validation of a machine learning model for cardiovascular disease risk prediction in type 2 diabetes patients.Scientific reports · 2025Article
- Identifying determinants of malnutrition in under-five children in Bangladesh: insights from the BDHS-2022 cross-sectional study.Scientific reports · 2025Article
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- Delving into biomarkers and predictive modeling for CVD mortality: a 20-year cohort study.Scientific reports · 2025Article
- RISE: a novel unified framework for feature relevance in malnutrition analytics integrating statistical and expert insights.Frontiers in public health · 2025Article
- Machine learning-based early screening of mild cognitive impairment using nutrition-related biomarkers and functional indicators.Frontiers in aging neuroscience · 2025Article
- Construction of a risk prediction model for lung infection after chemotherapy in lung cancer patients based on the machine learning algorithm.Frontiers in oncology · 2024Article
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8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMalnutrition causes nutrient deficiencies that have both physical and clinical consequences in severe acute malnutrition children. Globally, there were 47 million wasted children under the age of five in 2019. One in four were located in sub-Saharan Africa, with half being in South Asia. This study aims to apply the Boruta algorithm to identify the determinants of undernutrition among children under five living in Dera Ghazi Khan, one of the marginalized districts of densely populated Punjab Province in Pakistan.
methodsA multicenter cross-sectional study design was used to collect data from 185 children with severe acute malnutrition aged under five years visiting the OTPs centers located in Dera Ghazi Khan, Punjab, Pakistan. A purposive sampling technique was used to collect data using a pretested structured questionnaire from parents/caregivers regarding family sociodemographic characteristics, child nutrition, and biological and healthcare characteristics. Anthropometric measurements, including height, weight, and mid-upper arm circumference, were collected. The Boruta models were used to incorporate the children's anthropometric, nutritional, and household factors to determine the important predictive variables for undernutrition using the Boruta package in R studio.
resultsThis study included 185 children, with a mean age of 15.36 ± 10.23 months and an MUAC of 10.19 ± 0.96 cm. The Boruta analysis identifies age, mid-upper arm circumference, weaning practices, and immunization status as important predictors of undernutrition. Income per month, exclusive breastfeeding, and immunization status were found to be key factors of undernutrition in children under the age of five.
conclusionThis study highlights age, mid-upper arm circumference, weaning practices, and immunization status as key determinants of weight-for-height and weight-for-age in children under five years. It also suggests that economic context may influence undernutrition. The findings can guide targeted strategies for combating undernutrition.
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