Abstract

Background: Statistics from the Nigeria demographic and health survey (NDHS) 2018 revealed that about 59% of women delivered at home and only 24% of babies were weighed at birth. Subsequently, many small babies may have been missed. It is therefore necessary to identify alternative and effective surrogates to birth weight especially in places where weighing scales are not available through the use of simple and familiar tools.Methods: It was a descriptive cross-sectional study involving the measurement of birth weight, occipitofrontal circumference (OFC), mid-upper arm circumference (MUAC), chest circumference (ChC), calf circumference (CC) and foot length (FL). Binary logistic regression analysis was used to determine degree of relationship between the anthropometric parameters and low birth weight. Cut-off values (with the highest sensitivity and specificity) were determined and diagnostic accuracy was performed using the area under the receiver’s operating characteristics (ROC) curve.Results: All anthropometric measurements correlated positively with birth weight. With each unit increase in the MUAC, the odds for low-birth weight outcome decreased with an odds ratio (OR) of 0.099 (95% CI 0.045-0.213; p<0.001). Cut-offs and area under the curve (AUC) values for OFC, MUAC, chest circumference, calf circumference and foot length were 32.9 cm, 9.8 cm, 30.2 cm, 9.8 cm and 7.4 cm; and 0.93, 0.97, 0.96, 0.96 and 0.92 respectively.Conclusions: MUAC had the best predictive performance in detecting low birth weight. The findings of this study provide an opportunity for early identification of low birth weight especially among out-of-facility births so that life-saving interventions can be instituted early.

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