ArticleBMJ public health2024
Prevalence and sociodemographic factors associated with double burden of malnutrition among children under 5: a cross-sectional analysis of NFHS-4 data in India.
Article in BMJ public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Impact of paediatric malnutrition on sevoflurane requirements and recovery: A pilot study.Indian journal of anaesthesia · 2026Article
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5 authors.
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Abstract
Background: The double burden of malnutrition (DBM), characterised by the coexistence of undernutrition and overnutrition, poses a significant public health challenge, particularly in low- and middle-income countries. India, being one of these countries, faces a rising burden of malnutrition, with persistently high levels of stunting and a significant increase in overweight and obesity among children under 5 years old. Aim: To estimate the prevalence of DBM and associated sociodemographic factors among children aged 0-5 years in India, using data from the National Family Health Survey-4 (NFHS-4). Materials and methods: A secondary data analysis of the NFHS-4 (2015-2016) a nationally representative cross-sectional data was conducted. The study population consisted of 57 951 children aged 0-5 years, and anthropometric data were extracted from the NFHS-4 India database. Child growth indicators, including stunting, overweight, obesity and DBM were analysed using internationally recognised WHO Child Growth Standards. Descriptive statistics, graphical representations and the χ Results: The analysis of data from the NFHS-4 for India revealed that the prevalence of the DBM among children aged 0-5 years was 2.3% (95% CI 2.2% to 2.5%). Conclusion: While the prevalence of DBM among children under 5 years of age in India is relatively low at 2.3%, the implications of this issue are far-reaching and enduring. Despite appearing modest, addressing DBM requires sustained attention and comprehensive strategies. Extensive research with larger samples is essential for understanding complex challenges.
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