Prediction of Birth Weight by Using Neonatal Anthropometric Parameters at Birth in Finote Selam Hospital, Ethiopia

INTRODUCTION: Birth weight is an indicator of a newborn’s chances for survival and growth. However, developing countries lack enough weighing scales to identify low birth weight babies. Therefore, finding an alternative to weighing scales is vital. OBJECTIVE: To predict birth weight from neonatal anthropometric parameters at birth in Finote Selam Hospital, Ethiopia. METHODS: A hospital-based cross-sectional study was carried out from July 13 to October 27, 2020. A total of 424 live-delivered neonates were enrolled. Based on eligibility, birth weight and neonatal anthropometric parameters like crown–heel length, foot length, hand length, mid-upper arm circumference, umbilical–nipple distance, intermammary distance and head circumference were measured within 24 hours of birth. The association between birth weight and neonatal anthropometric parameters was evaluated using correlation analysis. Birth weight predictive regression models were formulated by using simple and multiple linear regression analysis. RESULTS: All neonatal anthropometric parameters had positive significant correlation with birth weight at p<0.05. Amongst the neonatal anthropometric parameters, the highest significant correlation with birth weight was observed on mid-upper arm circumference (MUAC) followed by foot length (FL), each being r=0.474 and r=0.461, respectively. The best predictive regression models were formulated as birth weight (kg)=0.117+[0.284×MUAC (cm)] and birth weight (kg)=1.137+[0.254×FL (cm)]. As compared to individual neonatal anthropometric parameters, a combination of MUAC, hand length (HL), FL and crown–heel length (CHL) had the highest significant correlation (r=0.661), and a multiple regression equation used to estimate birth weight was formulated as birth weight (kg)=−2.489+[0.192×MUAC(cm)]+[0.078×HL(cm)]+[0.11×FL (cm)]+[0.036×CHL(cm)]. CONCLUSION: Using a combination of MUAC, HL, FL and CHL followed by individual MUAC neonatal anthropometric parameters has high significance to identify low birth weight. Prediction of neonatal birth weight from neonatal anthropometric parameters is crucial to minimize the death of neonates due to low birth weight.