Statistical analysis
weight gain, GDM
REGRESSION, GDM
Continuous variables were expressed as mean (standard deviation), and categorical variables were expressed as numbers (percentage). Characteristics of participants were compared between the two groups, by applying the independent A modified Poisson regression for binary outcome data with a log link function and robust error variance was used to estimate relative risks (RRs) and 95% confidence intervals (CIs) for the associations between type of test and incidence of pregnancy outcomes. Adjusted variables were gestational ages at entrance and delivery, maternal BMI, gestational weight gain, type of delivery, and treatment modality. Moreover, we adjusted the GDM diagnosis in the model for comparing one or two abnormal tests. Both unadjusted and adjusted models were fitted. In all analyses related to the primary C-S outcome, those with a previous history of C-S were excluded. Penalized maximum likelihood estimation was applied in the case of sparse data.Since the study was a cluster randomized trial, the cluster effect was considered in the analysis. Finally, the plot of the relative risk was depicted for all pregnancy outcomes by type of test. Statistical analysis was performed using STATA (version 13; STATA Inc., College Station, TX, USA), and the significance level of the test was set as 0.05.