Diagnostic Accuracy of Mid-Upper Arm Circumference for Screening Maternal Malnutrition: A Community-based Cross-sectional Study from Eastern India

Objective: Maternal malnutrition, encompassing both undernutrition and overnutrition, can adversely affect maternal and foetal health and therefore requires effective nutritional assessment during antenatal care. Although body mass index (BMI) is commonly used for nutritional assessment, its application during pregnancy has limitations and may be difficult to implement in low-resource settings. Mid-upper arm circumference (MUAC) is a simple, inexpensive and easily interpretable anthropometric measure that may be suitable for community-based screening. This study aimed to evaluate the diagnostic accuracy and utility of MUAC for screening malnutrition among pregnant women in a community-based setting in eastern India. Design: This is a secondary analysis of data from a cross-sectional study. Anthropometric measurements were obtained using standardised procedures. Nutritional status assessed by MUAC was compared with body mass index (BMI). Diagnostic performance was evaluated using sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), Cohen Kappa, simple linear regression and receiver operating characteristic (ROC) curve analysis. Setting: Selected health sub-centres (Ayushman Arogya Mandir) under the rural field practice area of a medical college in Ranchi district of Jharkhand, a state in eastern India. Participant: A total of 337 pregnant women were randomly selected from antenatal care registers and enrolled after obtaining informed consent. Women with chronic medical conditions, such as hypertension, diabetes mellitus and hypothyroidism were excluded. Result: Based on BMI, 21.4% of participants were underweight, while MUAC classified 38.3% as having moderate malnutrition and 0.6% as having severe acute malnutrition. For detecting undernutrition, MUAC demonstrated 94.4% sensitivity, 70.3% specificity, 76.4% accuracy, 51.9% PPV and 97.4% NPV. Agreement between BMI and MUAC was moderate (Cohen Kappa=0.509, p<0.001). ROC analysis identified 22.8 cm as the optimal cut-off for undernutrition, and 24.8 cm for overnutrition. Conclusion: MUAC may be a useful and effective screening tool for maternal malnutrition, particularly in community and low-resource settings where conventional anthropometric assessment may be difficult. Further studies are required to establish robust MUAC cut-offs across different populations and gestational ages.