Diagnostic Accuracy of Mid-Upper Arm Circumference for Screening Maternal Malnutrition: A Community-based Cross-sectional Study from Eastern India
- 1Sheikh Bhikhari Medical College, Hazaribag
Abstract
ObjectiveMaternal 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.
DesignThis 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), Cohens Kappa, simple linear regression and receiver operating characteristic (ROC) curve analysis.
SettingSelected 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.
ParticipantA 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.
ResultBased 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 (Cohens 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.
ConclusionMUAC 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.
Key PointsO_ST_ABSWhat is already known on this topicC_ST_ABSMaternal malnutrition is associated with adverse maternal and foetal outcomes, but nutritional assessment during pregnancy remains challenging. Mid-upper arm circumference (MUAC) is simple and feasible in low-resource settings, but evidence on its diagnostic performance and appropriate cut-offs in pregnant women is limited.
What this study addsThis study provides evidence of a strong correlation between MUAC and body mass index (BMI), a fairly high accuracy of MUAC for detecting undernutrition and optimal cut-offs of MUAC for undernutrition and overnutrition in the population under study.
How this study might affect research, practice or policyThe findings of this study provide evidence about the diagnostic accuracy of MUAC for screening of malnutrition in pregnant women, which can lead to further studies for deriving optimal cut-offs of MUAC in different populations. It also provides a basis for the government to adopt MUAC for detection of malnutrition in low-resource and community settings.
Related
- Effect of eligibility for referral following mass screening for severe acute malnutrition using mid-upper arm circumference: A prospective regression discontinuity design
- Uptake of sickle cell screening among sexually active unmarried young adults in Gulu City, northern Uganda: a community-based cross-sectional study
- Performance Assessment of an Artificial Intelligence System Used for Case Detection in a Large Community-based Diabetic Retinopathy Screening Program: A Retrospective Diagnostic Accuracy Validation Study.
- Association of homocysteine and waist-to-height ratio with poor sleep quality in community-dwelling individuals at high risk of stroke: a cross-sectional study based on two community screening rounds in 2015 and 2025
- Diagnostic Accuracy of PID-5-BF for Screening Personality Disorders: A Cross-Sectional Study in Clinical and Nonclinical Samples.
BibTeX
@misc{hembrom2026diagnostic,
title = {{Diagnostic Accuracy of Mid-Upper Arm Circumference for Screening Maternal Malnutrition: A Community-based Cross-sectional Study from Eastern India}},
author = {S. S. Hembrom and K. A. Kiran and M. Kujur and M. P. Murmu and S. Sahu and P. Anand},
howpublished = {medRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.20.26363198},
url = {https://www.medrxiv.org/content/10.64898/2026.09.20.26363198v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Diagnostic Accuracy of Mid-Upper Arm Circumference for Screening Maternal Malnutrition: A Community-based Cross-sectional Study from Eastern India
AU - S. S. Hembrom
AU - K. A. Kiran
AU - M. Kujur
AU - M. P. Murmu
AU - S. Sahu
AU - P. Anand
PY - 2026
DA - 2026/09/20
PB - medRxiv
DO - 10.64898/2026.09.20.26363198
UR - https://www.medrxiv.org/content/10.64898/2026.09.20.26363198v1
AB - ObjectiveMaternal 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. DesignThis 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), Cohens Kappa, simple linear regression and receiver operating characteristic (ROC) curve analysis. SettingSelected 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. ParticipantA 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. ResultBased 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 (Cohens 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. ConclusionMUAC 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. Key PointsO_ST_ABSWhat is already known on this topicC_ST_ABSMaternal malnutrition is associated with adverse maternal and foetal outcomes, but nutritional assessment during pregnancy remains challenging. Mid-upper arm circumference (MUAC) is simple and feasible in low-resource settings, but evidence on its diagnostic performance and appropriate cut-offs in pregnant women is limited. What this study addsThis study provides evidence of a strong correlation between MUAC and body mass index (BMI), a fairly high accuracy of MUAC for detecting undernutrition and optimal cut-offs of MUAC for undernutrition and overnutrition in the population under study. How this study might affect research, practice or policyThe findings of this study provide evidence about the diagnostic accuracy of MUAC for screening of malnutrition in pregnant women, which can lead to further studies for deriving optimal cut-offs of MUAC in different populations. It also provides a basis for the government to adopt MUAC for detection of malnutrition in low-resource and community settings.
ER -