Statistical analysis
glucose dysregulation, T2D
The analyses were done at the individual level in SPSS (Version 22.0; Armonk, NY, United States). The double-entry data method was adopted to ensure data accuracy via the EpiData 3.0 software (EpiData Association, Odense, Denmark). All randomly assigned participants (The data were presented as means with SDs or as counts with percentages. Descriptive statistics were used to describe demographic and clinical characteristics. The demographic and clinical data of the intervention and control groups were compared using two independent samples t-tests and Chi-square tests. Repeated measure analyses (three points) were conducted using a generalized estimating equation (GEE) model to compare the differences between two groups in T2D risk scores, glycemic, weight-related, behavioral, and psychological variables from baseline to 18-month follow-up. GEEs were developed as an extension of the general linear model to analyze longitudinal and other correlated data. GEE models take into account the correlation between repeated measurements in the same subject; models do not require complete data and can be fitted even when individuals do not have observations at all time points [To assess if the intervention effect was statistically different between subgroups, we conducted several subgroup analyses for T2D risk scores: research site (You County, Yongding County), ethnicity (Han, minority), BMI (≤24 kg/ m2, > 24 kg/ m2), waist circumference (≤80 cm, > 80 cm), glucose dysregulation (FBG ≤6.1 mmol/L or OGTT-2 h ≤7.8 mmol/L, FBG > 6.1 mmol/L or OGTT-2 h > 7.8 mmol/L) and months after delivery (≤12, > 12). We included interaction terms (group by subgroup) in the GEE models to assess differences between subgroups.