Comparing Mid-Upper Arm Circumference With Body Mass Index for Assessing Nutritional Status in Indian Adults: Evidence From the National Family Health Survey 2015-16 (NFHS-4).

Abstract

Background The surge in the twin burden of malnutrition - undernutrition and overweight/obesity - poses a severe threat worldwide including India. The adult group, primarily considered as an economic pillar of the society, suffered significant health problems, yet their nutritional issues are often neglected. Screening of nutritional status through anthropometric measurements is widely accepted. Body mass index (BMI) is commonly used but has certain limitations. Mid-upper arm circumference (MUAC), another simpler tool, is universally accepted in children, but its use in adults is debatable. The current research aims to determine the MUAC cutoffs and their predictive accuracies corresponding to BMI cutoffs for adult men and nonpregnant women. Subject and methods A cross-sectional analysis was conducted of the anthropometric data of Indian adult men and nonpregnant women collected in 2015-16 via the National Family Health Survey (NFHS-4). The receiver operating characteristic (ROC) curve analysis was performed to derive the MUAC cutoffs against BMI cutoffs. Results A significant moderate correlation for both men (r=0.56) and women (r=0.68) was observed. In relation to ROC analysis, the MUAC cutoffs against the BMI cutoffs of 18.5, 23, 25, and 30 kg/m2 were approximated to be 25, 26, 28, and 30 cm for men and 23, 25, 27, and 28 cm for women, respectively. These MUAC cutoffs showed good predictive accuracy with a high range of sensitivity and specificity for both men and women. Conclusions The non-invasive MUAC method correlates very well with BMI and offers several advantages, including accuracy, ease of measurement, and minimal logistical support and training, and can assess the nutritional status even in geographically remote areas. Therefore, it can be an important tool in public health, especially in resource-limited settings, for identifying populations at risk of malnutrition.