Statistical analysis
All data were analyzed with Stata 16.1 (Stata Corp, College Station, TX,
USA) and SPSS 25.0 software (SPSS, Chicago, IL, USA). Continuous
variables were presented as mean ± SD and categorical variables were
presented as numbers (proportion). The comparisons of serum TG levels
among different periods and among groups were performed by one-way ANOVA
for continuous variables. Bonferroni test was used for pairwise
comparisons if homogeneity of variance is satisfied, and Tamhane T2 test
was used otherwise. Pearson
correlation and stepwise multiple liner regression analysis were carried
out to analyze the associations between serum TG levels during pregnancy
and 42 days postpartum. Serum TG level at 42 days postpartum was the
dependent variable. Serum TG level at each gestational week, age, GWG,
pre-BMI, GDM and gestational age were the independent variables. If α ≤
0.05, the variable was entered into the model, and the variable was
ruled out if α ≥ 0.10. A two-stage approach 12 was
carried out to analyze the associations between TG trend of change
during pregnancy and TG level and hypertriglyceridemia at 42 days
postpartum. In the first stage, a linear mixed-effect model (LME) was
constructed for TG as a function of gestational week at sampling and
predicted the best linear unbiased predictor (BLUP) of random intercept
and slope. The predicted intercept represents the mean TG level at the
6-8th gestational week. The predicted slope represents
the trend of TG level changes throughout gestation. Secondly, the BLUP
estimates of intercept and slope were used as predictors in the linear
and logistic regression models including TG level at 42 days postpartum
and hypertriglyceridemia as the outcomes, respectively. The odds ratios
(ORs) and 95% confidence intervals (95% CIs) of postpartum
hypertriglyceridemia in association with gestational TG levels were
calculated by using logistic regression analysis. The model was adjusted
for age, GWG, pre-BMI and GDM. Cutoff points of serum TG level at each
gestational week were chosen by the point nearest to the top-left most
corner of the receiver operating characteristic (ROC) curves, which was
selected by the biggest Youden Index 13. Sensitivity,
specificity, and 95% CIs were calculated. The area under the ROC curve
(AUC) was used to evaluated discrimination of the predictive model of
gestational TG level on postpartum hypertriglyceridemia.
The Hosmer-Lemeshow goodness-of-fit
test 14 was carried out for assessment of calibration.
Hierarchical logistic regression model was used for subgroup analysis
among different pre-BMI subgroups and between GDM subgroups.P value of < 0.05
was considered statistically significant.