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Abstract
Objective To evaluate the added value of the use of upper arm length (UAL) along with mid-upper arm circumference (MUAC) to diagnose and estimate the prevalence of wasting in comparison to current WHO standard and other MUAC-based methods.
Design UAL and usual anthropometric measurements were collected during a national cross-sectional nutritional survey. Children were classified into three upper arm length groups (UALGs): UALG1, UALG2 and UALG3 according to the following UAL limits: ≤150, 151–180 and ≥181 mm, respectively. Receiver operating characteristic curves were used to determine the best MUAC cut-off for each group using weight-for-height Z-score (WHZ) as a reference standard. Wasting prevalence, sensitivity and specificity of all diagnostic methods were compared.
Setting This study was conducted in Mauritania.
Participants National representative sample of children from 6 to 59 months old.
Results In total, 12 590 children were included in the study. Wasting prevalence was 16.1%, 5.0% and 12.5% when diagnosed by WHZ <−2, MUAC <125 mm and MUAC–UALG methods, respectively. Using the MUAC–UALG method increased the sensitivity for wasting diagnosis from 17.98% with MUAC <125 mm to 39.43% with MUAC–UALG. The specificity decreased from 97.49% with MUAC <125 mm to 92.71% with MUAC–UALG. With MUAC–height Z score and MUAC <138 mm, sensitivity was 26.04% and 69.76% and specificity were 97.40% and 75.64% respectively.
Conclusion This alternative method using MUAC tape to measure UAL increases the wasting diagnosis accuracy and allows for a better estimation of wasting prevalence. This method could be used as a potential alternative method for quick surveys in emergency settings such as Corona virus disease 2019 context.
- malnutrition
- child health
- community medicine
- global health
- nutritional status
Data availability statement
Data are available upon reasonable request by email to the corresponding author.
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Data availability statement
Data are available upon reasonable request by email to the corresponding author.
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Footnotes
Contributors MDB and MB contributed in the article equally. They designed, approved and are accountable for the work, MDB more specifically conducted the field study, carried out the data editing contributed to the design of the study, the statistical analyses, the writing of the manuscript and the coordination of coauthor inputs (study design, data collection, data analysis, data interpretation, writing). MB contributed to the design of the study conducted the statistical analyses, produced the tables and graphs, reviewed the documentation, the integration of the different inputs and the writing of the manuscript (figures, study design, data collection, data analysis, data interpretation, writing). DC and NZ participated in the analysis of the results and the interpretation of the data. TB and SNB has done a complete review of the statistical analyses of the data and tables of the results. YD reviewed the documents and provided an external perspective on the concept, analysis, interpretation and conclusions of the article (revising it critically for important intellectual content).
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests MB works for Nutriset S.A.S, Malaunay, France. This study started before he joined the company and is independent to his activity at the company. No other author has a conflict of interest related to this study.
Provenance and peer review Not commissioned; externally peer reviewed.
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