Towards identifying malnutrition among infants under 6 months: a mixed-methods study of South-Sudanese refugees in Ethiopia
Laura Moore1, Sinead O'Mahony2, Mark Shevlin3
1Centre for Global Health, University of Dublin, Trinity College, 7-9 South Leinster Street, Dublin 2, Dublin, Ireland.
Insights
Weight-for-age z-scores (WAZ) best identify malnutrition in infants under 6 months, but mid-upper arm circumference (MUAC) is more commonly used for admittance to programs. Barriers include misconceptions and protocol issues.
Area of Science:
- Global Health
- Pediatric Nutrition
- Anthropometry
Background:
- Identifying malnutrition in infants under 6 months (U6M) is critical for timely intervention.
- Existing anthropometric criteria for malnutrition may not accurately reflect distinct malnourished groups or program admittance probabilities.
- Barriers to effective malnutrition identification in U6M require investigation.
Purpose of the Study:
- To identify distinct malnourished groups among infants under 6 months (U6M) using anthropometric measures.
- To determine the probability of admittance to the Management of At Risk Mothers and Infants (MAMI) program based on group membership.
- To compare admission discrepancies between recognized anthropometric criteria and group membership, and identify barriers and solutions for U6M malnutrition identification.
Main Methods:
- A mixed-methods approach combining factor mixture modeling, chi-squared analysis, and logistic regression.
- Qualitative analysis of key informant interviews to understand barriers and solutions.
- Data collected from 3444 South-Sudanese infants under 6 months (U6M) and 11 MAMI programming experts in Ethiopian refugee camps.
Main Results:
- Distinct well-nourished and malnourished groups of U6M were identified.
- Weight-for-age z-scores (WAZ) were the most discriminating measure for malnutrition.
- Mid-upper arm circumference (MUAC) was most strongly associated with MAMI program admittance, despite WAZ's higher accuracy.
- Barriers included misconceptions about malnutrition, limited evidence, and issues with current identification protocols.
Conclusions:
- WAZ is the most discriminating anthropometric measure for identifying malnutrition in U6M.
- MUAC offers a more scalable, though potentially less accurate, alternative for U6M malnutrition screening.
- Addressing misconceptions and refining identification protocols are crucial for effective U6M malnutrition management.
Objectives:
To 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.
Design:
Mixed-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.
Setting:
Data were collected in two refugee camps in Ethiopia. Key informant interviews were conducted remotely with international MAMI programmers and nutrition experts.
Participants:
Participants were 3444 South-Sudanese U6M and eleven key informants experienced in MAMI programming.
Results:
Well-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.
Conclusions:
Our 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.
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