Association Between Maternal Predictors and Neonatal Anthropometric Measurements

Objectives investigated the relationship between maternal anthropometric and sociodemographic factors and neonatal birth outcomes—specifically birth weight, length, and head circumference—among 50 women delivering at two hospitals in Sulaymaniyah, Iraq. Methods Data collection involved direct maternal measurements, neonatal assessments immediately after birth, and a structured questionnaire capturing background variables. Key maternal predictors included gestational age, gravidity, weight, height, body mass index (BMI), weight gain, and hemoglobin concentration, as well as residence, educational level, and occupational status. Multiple linear regression analyses were employed to assess the simultaneous effects of all maternal predictors on each neonatal outcome. Additionally, Pearson product-moment correlation coefficients were calculated to evaluate bivariate associations between maternal and neonatal variables. Categorical predictors were numerically coded or dummy-encoded prior to inclusion in statistical models. Statistical significance was determined at a threshold of p < 0.05. Results showed that gestational age was the only statistically significant predictor of neonatal weight (p = 0.0266), while no other maternal or sociodemographic factor showed significant associations in the regression models for weight, length, or head circumference. Gravidity demonstrated a significant positive correlation with head circumference (r = 0.311, p = 0.028), and urban residence was significantly and negatively correlated with neonatal length (r = –0.330, p = 0.019). No significant associations were found for maternal BMI, weight gain, or hemoglobin concentration with any of the three neonatal measurements. Conclusions These findings suggest that gestational age remains a key determinant of neonatal birth weight, while gravidity and residential context may play modest roles in shaping head circumference and length, respectively. The lack of significant effects for BMI and hemoglobin may be due to sample size limitations or low variability in these measures. Further research with larger and more heterogeneous populations is recommended.