Low birth weight (LBW) is defined as a neonatal birth weight below 2500 grams. It is a major worldwide health issue. It affects one-sixth of newborns, with the highest rates in Sub-Saharan Africa. LBW is a major cause of neonatal mortality and morbidity, which contributes to 60-80% of deaths. In Tanzania, the LBW rate has decreased from 13% to 7% over the last decade. LBW infants face long-term difficulties, underscoring the importance of early detection for health interventions associated with Sustainable Development Goal (SDG) 3.2. It aims to cut neonatal mortality. Many births in rural Tanzania occur at home, which leads to a lack of immediate weighing. Research showed that anthropometric measures, which predict LBW, like foot length and head circumference, are needed in Tanzania to improve identification of at-risk newborns. The study aimed to determine which newborn anthropometric measurements can best predict LBW in neonates at Muhimbili National Hospital (MNH) in Dar es Salaam, Tanzania.
This hospital-based cross-sectional study was conducted from October 2019 to February 2020 in the MNH Neonatal Intensive Care Unit (ICU). It serves as the largest tertiary referral center in Tanzania. Of 1200 newborns screened, 471 neonates met eligibility criteria and were enrolled within 24 hours of birth. Neonates with severe congenital anomalies, major birth injuries, cyanosis, or who need respiratory support were excluded. Data were collected by using a structured questionnaire that included all maternal demographic characteristics and newborn clinical details. Anthropometric measurements like chest circumference (CHC), occipitofrontal circumference (OFC), mid-upper arm circumference (MUAC), birth weight, and foot length (FL) were measured. Each measurement was performed twice by a trained research assistant using standardized techniques, and the average range was used for analysis. Gestational age was determined using the mother’s last menstrual period, early ultrasound, or the New Ballard scoring system.
Data analysis was done by using SPSS version 23. Correlations between each anthropometric parameter and birth weight were analyzed by using Pearson’s correlation coefficient. Receiver Operating Characteristic (ROC) curves were generated to assess the diagnostic accuracy of each measure and to identify the optimal cut-off for detecting LBW. Sensitivity, specificity, and predictive values were calculated with 95% confidence intervals (CI).
Of 471 newborns, 52.2% were female, and 43.1% had LBW. The mean birth weight was 2639 ± 851 g. Male neonates weighed on average 2771 g, while females weighed 2520 g. All anthropometric measurements were correlated with birth weight (p < 0.01). The strongest correlations were observed for chest circumference (r = 0.90), head circumference (r = 0.82), foot length (r = 0.55), and MUAC (r = 0.35).
ROC analysis revealed that MUAC (AUC = 0.97), CHC (AUC = 0.97), and OFC (AUC = 0.94) were great predictors of LBW, and FL (AUC = 0.75) had moderate predictive value. The optimal cutoff points to identify LBW were CHC ≤ 29.45 cm, OFC ≤ 32.9 cm, MUAC ≤ 9.15 cm, and FL ≤ 7.05 cm. CHC showed the best diagnostic accuracy, with a sensitivity of 94%, specificity of 90%, negative predictive value of 94%, and positive predictive value of 87%. CHC predicted 85.2% of the variation in birth weight.
This study found that chest and head circumferences are reliable indicators of LBW in Tanzanian neonates. The optimal cutoff (≤ 29.45 cm) aligns with WHO standards. The result suggests that chest circumference is an effective and low-cost screening tool in the resource-limited setting. Occipitofrontal circumference predicts LBW, but the effectiveness is compromised by cranial moulding. Mid-upper arm circumference and foot length showed weak correlations. The study highlighted the importance of integrating chest circumference measurement into neonatal care to improve early detection and treatment and reduce neonatal mortality in Tanzania.
References: Abdallah NS, Kija E, Naburi H, et al. Anthropometric measurements as a surrogate for identifying low birth weight: comparison with the gold standard of measuring weight among neonates at a tertiary hospital in Tanzania. BMC Pediatrics. 2025;25:907. doi:10.1186/s12887-025-06228-w
