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cohort·pediatrics, nutrition, epidemiology, public health, clinical nutrition·PMC10346023

Prognostic value of different anthropometric indices over different measurement intervals to predict mortality in 6–59-month-old children

Public Health Nutrition · 16 authors, 20 centres

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TL;DR

This pooled analysis of twelve prospective cohort studies found that more frequent anthropometric measurements significantly improve the identification of children at high risk of death without markedly increasing false positives.

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WAZ < -3 identified additional children who died beyond those identified by WHZ < -3 or MUAC thresholds, but increased false positives.

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cohort

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pediatrics

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ORIGINAL PAPER

PMC10346023

Prognostic value of different anthropometric indices over different measurement intervals to predict mortality in 6–59-month-old children

Public Health Nutrition

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ABSTRACT

Abstract Objective: To compare the prognostic value of mid-upper arm circumference (MUAC), weight-for-height Z -score (WHZ) and weight-for-age Z -score (WAZ) for predicting death over periods of 1, 3 and 6 months follow-up in children. Design: Pooled analysis of twelve prospective studies examining survival after anthropometric assessment. Sensitivity and false-positive ratios to predict death within 1, 3 and 6 months were compared for three individual anthropometric indices and their combinations. Setting: Community-based, prospective studies from twelve countries in Africa and Asia. Participants: Children aged 6–59 months living in the study areas. Results: For all anthropometric indices, the receiver operating characteristic curves were higher for shorter than for longer durations of follow-up. Sensitivity was higher for death with 1-month follow-up compared with 6 months by 49 % (95 % CI (30, 69)) for MUAC < 115 mm ( P < 0·001), 48 % (95 % CI (9·4, 87)) for WHZ < -3 ( P < 0·01) and 28 % (95 % CI (7·6, 42)) for WAZ < -3 ( P < 0·005). This was accompanied by an increase in false positives of only 3 % or less. For all durations of follow-up, WAZ < -3 identified more children who died and were not identified by WHZ < -3 or by MUAC < 115 mm, 120 mm or 125 mm, but the use of WAZ < -3 led to an increased false-positive ratio up to 16·4 % (95 % CI (12·0, 20·9)) compared with 3·5 % (95 % CI (0·4, 6·5)) for MUAC < 115 mm alone. Conclusions: Frequent anthropometric measurements significantly improve the identification of malnourished children with a high risk of death without markedly increasing false positives. Combining two indices increases sensitivity but also increases false positives among children meeting case definitions. Keywords: Wasting, Stunting, Underweight, Mid-upper arm circumference, Anthropometry, Mortality

CITATION EXPORT

André Briend, Mark Myatt, James A Berkley et al.. Prognostic value of different anthropometric indices over different measurement intervals to predict mortality in 6–59-month-old children. Public Health Nutrition. (2023). https://doi.org/10.1017/S1368980023000149

AUTHORS

16 · 20 CENTRES

André Briend, Mark Myatt, James A Berkley, Robert E Black, Erin Boyd, Michel Garenne, Natasha Lelijveld, Sheila Isanaka, Christine M McDonald, Martha Mwangwome, Kieran S O’Brien, Catherine Schwinger, Heather Stobaugh, Sunita Taneja, Keith P West, Tanya Khara

1 Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Rolighedsvej 30, DK-1958, Frederiksberg, Denmark
2 Tampere Center for Child, Adolescent and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University and Tampere University Hospital, Arvo building, Arvo Ylpön katu 34, FIN-33014 Tampere, Finland
3 Brixton Health, Cilfach Greigiog, Fford Celynin, Llwyngwril, Gwynedd, UK
4 Emergency Nutrition Network, Kidlington, OX, UK
5 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
6 Centre for Tropical Medicine & Global Health, University of Oxford, UK
7 Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
8 USAID, Bureau for Humanitarian Assistance, Washington, DC, USA
9 Tufts University, Boston, MA, USA
10 IRD, UMI Résiliences, Paris, France
11 FERDI, Université d’Auvergne, Clermont-Ferrand, France
12 MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
13 Department of Research, Epicentre, Paris, France
14 Departments of Nutrition and Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
15 Departments of Pediatrics, and Epidemiology and Biostatistics, University of California, San Francisco, Oakland, CA, USA
16 Kenya Medical Research Institute (KEMRI), Centre for Geographic Medicine Research-Coast (CGMRC), Kilifi, Kenya
17 Department of Ophthalmology, University of California, Francis I. Proctor Foundation, San Francisco, CA, USA
18 Centre for Intervention Science in Maternal and Child Health, Centre for International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
19 Action Against Hunger USA, New York, NY, USA
20 Center for Health Research and Development, Society for Applied Studies, New Delhi, India