Statistical analysis
GDM
GDM
Baseline data are presented descriptively as median (interquartile range) and number (%) for continuous and categorical variables, respectively. The analyses were carried out using the intention-to-treat approach in which enrolled participants were analyzed according to the treatment targets their hospital was randomized to and when their diagnosis of GDM was made. We used generalized linear mixed-effects models (GLMM) to evaluate the main treatment effect, with a random effect for hospital groups and the participants, and fixed effects for the intervention implementation and time. Time was estimated in months between the date the assigned targets were initiated and the date a woman enrolled. Time was included in the model to account for secular trends over time as the study design induces an association between time and outcome of interest, and failure to include time into the model might bias the effect size estimates.The analyses were conducted to examine the difference in means of biomarkers between the tighter targets group compared to the less tight targets group using their logarithm-transformed data. The tighter target group included data from women with GDM recruited in the tighter target period, while the less tight target group used data from women recruited in the less tight target period. We reported differences in the percentages between the means of the tighter and the less tight target group (95% confidence interval), which was derived from back logarithm transforming the estimated coefficients estimated from the GLMM (i.e., ~(exponential of the estimated coefficient − 1) × 100%). Compliance was defined as achieving ≥80% of either fasting, postprandial or both fasting and postprandial targets and analyses were performed as above for these subgroups. A 