Anthropometric criteria for best-identifying children at high risk of mortality: a pooled analysis of twelve cohorts.
Public Health Nutr
; : 1-17, 2023 Feb 03.
Article
em En
| MEDLINE
| ID: mdl-36734049
ABSTRACT
OBJECTIVE:
To understand which anthropometric diagnostic criteria best discriminate higher from lower risk of death in children and explore programme implications.DESIGN:
A multiple cohort individual data meta-analysis of mortality risk (within 6 months of measurement) by anthropometric case definitions. Sensitivity, specificity, informedness and inclusivity in predicting mortality, face validity and compatibility with current standards and practice were assessed and operational consequences were modelled.SETTING:
Community-based cohort studies in twelve low-income countries between 1977 and 2013 in settings where treatment of wasting was not widespread.PARTICIPANTS:
Children aged 6 to 59 months.RESULTS:
Of the twelve anthropometric case definitions examined, four (weight-for-age Z-score (WAZ) <-2), (mid-upper arm circumference (MUAC) <125 mm), (MUAC < 115 mm or WAZ < -3) and (WAZ < -3) had the highest informedness in predicting mortality. A combined case definition (MUAC < 115 mm or WAZ < -3) was better at predicting deaths associated with weight-for-height Z-score <-3 and concurrent wasting and stunting (WaSt) than the single WAZ < -3 case definition. After the assessment of all criteria, the combined case definition performed best. The simulated workload for programmes admitting based on MUAC < 115 mm or WAZ < -3, when adjusted with a proxy for required intensity and/or duration of treatment, was 1·87 times larger than programmes admitting on MUAC < 115 mm alone.CONCLUSIONS:
A combined case definition detects nearly all deaths associated with severe anthropometric deficits suggesting that therapeutic feeding programmes may achieve higher impact (prevent mortality and improve coverage) by using it. There remain operational questions to examine further before wide-scale adoption can be recommended.
Texto completo:
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Base de dados:
MEDLINE
Tipo de estudo:
Etiology_studies
/
Guideline
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article