Regression analysis of birth weight predictors
A univariate linear regression analysis was performed to identify demographic, obstetric and psychosocial variables as potential risk factors of low birth weight. A lower maternal weight and BMI before pregnancy, higher parity, an increased STAIt score and preterm birth below 37 weeks of gestation (p=0.008, p=0.015, p=0.028, p=0.047, and p=0.022, respectively), were identified as predictive risk factors for low birth weight percentiles.
In addition, an increased STAIs score, tobacco use, and a lower gestational age at the beginning of the lockdown period showed a trend for prediction of lower birth weight percentiles, as shown in Table 2.
A multivariate lineal regression analysis (Table 3) was performed with those variables identified as risk factors for low birth weight percentiles in the univariate linear regression analysis. When combining maternal weight before pregnancy, parity, STAIt score and smoking status, only a lower maternal weight before pregnancy and an increased STAIt score were independent predictors for low birth weight percentile (p=0.020, p=0.049, respectively).