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).