Study Population and Design
The study included mothers and children who had participated in the Born in Shenyang Cohort Study, a prospective, observational cohort study of gestational factors, pregnancy outcomes, and oﬀspring health. The study design has been described elsewhere. Briefly, the BISCS was a prospective study that enrolled healthy women with single pregnancies at 21–24 weeks gestation at 54 hospitals or community healthcare centers in the urban area of Shenyang, northeast China between April and September 2017. Of a cohort of 2068 women who were invited to participate, 1338 (mean gestation of 22 ± 1.2 weeks) agreed, and 1290 of them had live singleton births. Research fellows conducted home visits with mothers and infants within 7 days of birth and at visits to child development clinics at 1, 3, 6, 8, and 12 months of age. Follow-up data were available from 72.4% of the 1290 mothers and their children at 1 month, 71.2% at 3 months, 66.7% at 6 months, 77.8% ant 8 months, and 77.4% at 12 months.
Trained research fellows conducted face-to-face interviews at enrollment and follow-up visits. Demographic, societal, environmental, behavioral, and clinical characteristics of the mothers and children were collected by structured questionnaires. Anthropometric measurements of the children were performed at each follow-up visit. Among 1290 mother–child pairs, 210 with missing oral glucose tolerance test (OGTT) results, 133 with missing anthropometric data, and two with pregestational diabetes mellitus were excluded. The remaining 945 mother–child pairs were included in the final analysis, and the results were compared with the observations in the 345 excluded participants. The characteristics of the two groups were similar.
Gestational Diabetes Mellitus
GDM was diagnosed at 24-28 weeks of pregnancy by the occurrence of one of the following events during a 75 g OGTT: a fasting plasma glucose of ≥ 5.1 mmol/L, a 1-h plasma glucose of ≥ 10.0 mmol/L, or a 2-h plasma glucose of ≥ 8.5 mmol/L . Pregnant women were assigned to either a GDM or a non-GDM group based on the diagnosis.
Anthropometric Characteristics of Children
Birth weight and length were derived from medical records. Infant weight and length were measured by trained research fellows at 1, 3, 6, 8, and 12 months of age with calibrated infant stadiometers (Seca 416; Seca Corporation, Hamburg, Germany) and weighing scales (Seca 376+). The mean values of two successive measurements were reported. Sex- and length-specific z-scores for weight (WFLZ) and sex- and age-specific z-scores for BMI (BMIZ), weight (WFAZ), and length (LFAZ) were calculated using the World Health Organization child growth references. Infant overweight/obesity was defined as a WFLZ of > 2 according to the WHO standard .
At the enrollment visit, participants self-reported their age, ethnicity, educational attainment, income level, parity, gestational age, and pre-pregnancy weight using standard questionnaires. Height was measured with a calibrated stadiometer. Age in years and gestational age in weeks were analyzed as continuous variables. The mother’s ethnicity was recorded as either Han or other. Women were categorized by educational level to four groups (middle school or below, high school, college, graduate school or above) and by parity to either one or more than one pregnancies. Maternal pre-pregnancy and paternal BMIs were categorized to three groups, [underweight (BMI <18.5 kg/m2) vs. normal weight (18.5 kg/m2 ≤BMI <24 kg/m2) vs. overweight/obese (BMI ≥24 kg/m2)] using Chinese reference values . Overweight and obese women were included in a single category because of the limited sample size.
The longitudinal associations between GDM status, i.e., with or without GDM, and blood glucose concentration (mmol/L) and infant WFLZ, WFAZ, and LFAZ from birth to 12 months were determined using linear mixed effects (LME) models. LME takes into account within-subject correlation of repeated measurements and also compensates for incomplete outcome measurements. The models included an unstructured covariance matrix for random-effect variables (intercept and slope) and a maximum likelihood-estimation method. Crude and adjusted analyses were performed with three models. Model 1 was adjusted for linear, quadratic and, cubic terms for infant’s age to estimate the association between GDM and blood glucose concentration with z-scores growth estimates across infancy. In model 2, we further adjusted for maternal pre-pregnancy BMI, as it was associated with infant overweight/obesity status. In model 3, we further adjusted covariates associated with GDM status, including maternal age, parity and gestational age. Stratified analyses were performed to investigate the association between GDM status and infant size in women of different pre-pregnancy BMI status (underweight vs. normal weight vs. overweight/obese). Interactions of GDM status and blood glucose level with pre-pregnancy BMI category and their association with infant growth measurements were tested by including the corresponding interactions into the models. The association between GDM status and blood glucose level and infant sex- and age-specific z-scores for WFL, weight and length at birth and at 1, 3, 6, 8, and 12 months of age was estimated by multivariable linear regression. The full model was adjusted for pre-pregnancy BMI, maternal age, parity and gestational age. Multiple imputation was performed to compensate for missing values in the linear regression models. In the sensitivity analysis, BMIZ was compared with WFLZ as outcomes of the LME analysis (Table S2). To assess the robustness of the study findings, all analyses were repeated in participants without missing covariate or outcomes data (n = 524, Table S3) or repeated in models adjusted only for maternal pre-pregnancy BMI (Figure S1 and S2). The statistical analysis was performed with Stata/SE version 13 (StataCorp, College Station, TX, USA). Two-sided p-values < 0.05 were considered statistically significant.