Malnutrition in infants aged under 6 months

Prevalence and anthropometric assessment – analysis of 56 low- and middle-income country DHS datasets

Bibliographic Data

ID21881083
AuthorsMarko Kerac (0000-0002-3745-7317, London School of Hygiene & Tropical Medicine), Philip T James (0000-0001-5448-8193, Bridlington Hospital), Marie Mcgrath (0000-0002-0660-1873, Emergency Nutrition Network, Oxford, UK), Eilise Brennan (0000-0002-3733-9222, Bridlington Hospital), Tim J Cole (0000-0001-5711-8200, University College London), Chris Opondo (0000-0001-8155-4117, University of Oxford), Severine Frison (0000-0002-1586-9564, London School of Hygiene & Tropical Medicine)
Year2025
Volume10
Issue5
Pagese016121
Publication date2025-05-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBMJ Global Health (JOURNAL)
Journal identifiersISSN: 2059-7908 • E-ISSN: 2059-7908
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/bmjgh-2024-016121
PMID40441741
OpenAlexW4410850492
LanguageEN
Citations received2
References cited44

INTRODUCTION: Tackling malnutrition in infants aged under 6 months (u6m) is a major global priority yet evidence around this vulnerable group is weak. We aimed to support the rollout of new 2023 WHO guidelines by examining the burden of infant malnutrition and potential programme caseloads with new enrolment criteria. METHODS: Secondary analysis of Demographic and Health Survey (DHS) datasets. We calculated the number of underweight (low weight-for-age), wasting (low weight-for-length), stunting (low length-for-age) and low birth weight (LBW) infants. We assessed data quality by recording extreme or missing values. We calculated the population-weighted prevalence of anthropometric deficit and extrapolated to all low- and middle-income countries (LMICs). We regressed being underweight and wasti on infant, maternal and household characteristics using logistic regression. RESULTS: We analysed 56 DHS surveys. There were more extreme (flagged) values for length-based measures (7.5% flagged for weight-for-length, 3.8% for length-for-age) than for weight-for-age (0.6% flagged). Overall, 17.4% of infants (95% CI: 16.9 to 18.0) were underweight, 15.5% (15.0-16.0) were wasted, 19.9% (19.3-20.5) were stunted and 15.0% (14.5-15.5) were LBW. This corresponds to an estimated burden in LMICs of 10.3 million underweight infants (4.1 million severely underweight), 9.2 million wasted (4.0 million severely wasted), 11.8 million stunted (5.4 million severely stunted) and 8.9 million LBW infants. Overlap of the indicators varied markedly in different regions/countries. Numerous factors were associated with both underweight and wasting; associations tended to be stronger and have greater biological plausibility with being underweight. CONCLUSION: Malnutrition in infants u6m is a major problem in LMICs. Local epidemiology should inform case identification in contextualised care services across health and nutrition. Data quality and stronger associations with health and social characteristics support the use of underweight as a key enrolment criterion. Since vulnerability may be due to or exacerbated by multiple factors, management must go beyond feeding support to address wider infant, maternal and mental health and social circumstances through integrated, multidisciplinary care systems

Anthropometry · Body mass index · Environmental health · Logistic regression · Low birth weight · Malnutrition · Overweight · Population · Pregnancy · Underweight · Wasting · Child Nutrition and Feeding Issues · Child Nutrition and Water Access · Demography · Infant Nutrition and Health · Medicine · Pediatrics

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