Statistical Analysis
Mean (standard deviation) and frequency (percentage), respectively,
described the continuous and categorical variables. Baseline
characteristics were compared by maternal age group using Student’s
t-test for continuous variables and Pearson’s Chi-squared test for
categorical variables. The potential confounding factors included BMI,
nation, levels of education, history of passive smoking, work condition,
history of adverse pregnancy outcomes (including stillbirth, spontaneous
and induced abortion), parity, which were adjusted by following
multivariate regressions. The associations between maternal age and
hyperglycemia/macrosomia were assessed with multivariate logistic
regression model by adjusted the potential confounding factors. Odds
ratio (OR) and 95% confidence interval (95%CI) were estimated. We also
conducted
cubic
restricted splines fitted in a logistic regression model with knots at
the 5th, 35th, 65th, and 95th
percentiles, to probe the association between macrosomia and maternal
age / FPG (continuous variable). Furthermore, a causal mediation
analysis using the mediation package in R software (27) was performed to
explore the potential contribute of preconception FPG level to the
effect of advanced maternal age on offspring birthweight , with 1000
Monte Carlo draws. Average causal mediation effects (ACMEs), average
direct effects (ADEs), total effects (sum of a mediation effect and a
direct effect), and the percentage of the variability in the total
causal effect explained by the mediator were showed. Findings atp <0.05 were considered significant. Statistical
analyses were performed using R-3.6.1 software.