Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

medicine

Determining a global mid-upper arm circumference cut-off to assess underweight in adults (men and non-pregnant women)

Public Health Nutrition, Volume 23, No. 17, Year 2020

Objective: To determine if a global mid-upper arm circumference (MUAC) cut-off can be established to classify underweight in adults (men and non-pregnant women). Design: We conducted an individual participant data meta-analysis (IPDMA) to explore the sensitivity (SENS) and specificity (SPEC) of various MUAC cut-offs for identifying underweight among adults (defined as BMI < 18·5 kg/m2). Measures of diagnostic accuracy were determined every 0·5 cm across MUAC values from 19·0 to 26·5 cm. A bivariate random effects model was used to jointly estimate SENS and SPEC while accounting for heterogeneity between studies. Various subgroup analyses were performed. Setting: Twenty datasets from Africa, South Asia, Southeast Asia, North America and South America were included. Participants: All eligible participants from the original datasets were included. Results: The total sample size was 13 835. Mean age was 32·6 years and 65 % of participants were female. Mean MUAC was 25·7 cm, and 28 % of all participants had low BMI (<18·5 kg/m2). The area under the receiver operating characteristic curve for the pooled dataset was 0·91 (range across studies 0·61-0·98). Results showed that MUAC cut-offs in the range of =23·5 to =25·0 cm could serve as an appropriate screening indicator for underweight. Conclusions: MUAC is highly discriminatory in its ability to distinguish adults with BMI above and below 18·5 kg/m2. This IPDMA is the first step towards determining a global MUAC cut-off for adults. Validation studies are needed to determine whether the proposed MUAC cut-off of 24 cm is associated with poor functional outcomes.
Statistics
Citations: 50
Authors: 15
Affiliations: 11
Identifiers
Research Areas
Genetics And Genomics
Study Approach
Systematic review
Participants Gender
Male
Female