Evidence map›Paper›PMID 33059792›Full record

ArticlePublic health nutrition2021

Towards identifying malnutrition among infants under 6 months: a mixed-methods study of South-Sudanese refugees in Ethiopia.

Laura Moore, Sinead O'Mahony, Mark Shevlin, Philip Hyland, Hatty Barthorp, Frédérique Vallières

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PubMed Full text at PMC Publisher
In one paragraph

Article in Public health nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 5 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Laura MooreCentre for Global Health, University of Dublin, Trinity College, 7-9 South Leinster Street, Dublin 2, Dublin, Ireland.
Sinead O'MahonyGOAL Global, Carnegie House, Library Road, Dun Laoighre, Co Dublin, Ireland.
Mark ShevlinPsychology Research Institute, Ulster University, Derry, Northern Ireland.
Philip HylandCentre for Global Health, University of Dublin, Trinity College, 7-9 South Leinster Street, Dublin 2, Dublin, Ireland.
Hatty BarthorpGOAL Global, Carnegie House, Library Road, Dun Laoighre, Co Dublin, Ireland.
Frédérique VallièresCentre for Global Health, University of Dublin, Trinity College, 7-9 South Leinster Street, Dublin 2, Dublin, Ireland.
Trinity College Dublin · IEUniversity of Ulster · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo determine (i) whether distinct groups of infants under 6 months old (U6M) were identifiable as malnourished based on anthropometric measures and if so to determine the probability of admittance to GOAL Ethiopia's Management of At Risk Mothers and Infants (MAMI) programme based on group membership; (ii) whether there were discrepancies in admission using recognised anthropometric criteria, compared with group membership and (iii) the barriers and potential solutions to identifying malnutrition within U6M.

designMixed-methods approaches were used, whereby data collected by GOAL Ethiopia underwent: factor mixture modelling, χ2 analysis and logistic regression analysis. Qualitative analysis was performed through coding of key informant interviews.

settingData were collected in two refugee camps in Ethiopia. Key informant interviews were conducted remotely with international MAMI programmers and nutrition experts.

participantsParticipants were 3444 South-Sudanese U6M and eleven key informants experienced in MAMI programming.

resultsWell-nourished and malnourished groups were identified, with notable discrepancies between group membership and MAMI programme admittance. Despite weight for age z-scores (WAZ) emerging as the most discriminant measure to identify malnutrition, admittance was most strongly associated with mid-upper arm circumference (MUAC). Misconceptions surrounding malnutrition, a dearth of evidence and issues with the current identification protocol emerged as barriers to identifying malnutrition among U6M.

conclusionsOur model suggests that WAZ is the most discriminating anthropometric measure for malnutrition in this population. However, the challenges of using WAZ should be weighed up against the more scalable, but potentially overly sensitive and less accurate use of MUAC among U6M.

Indexed as

MalnutritionRefugeesAnthropometryArmEthiopiaFemaleHumansInfantNutritional StatusInfants under 6 monthsMalnutritionManagement of At Risk Mothers and InfantsMid-upper arm circumferenceWeight for age z-scoresWeight-for-length

Identifiers

PMID33059792
PMCPMC10195624
OpenAlexW3093412726

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.