Recent study results on the association between maternal exposure to ambient air pollution with preterm birth have been inconsistent. The sensitive window of exposure and influence level of air pollutants varied greatly. We aimed to explore the association between maternal exposure to ambient air pollutants and the risk of preterm birth, and to estimate the sensitive exposure time window. A total of 572,116 mother–newborn pairs, daily concentrations of air pollutants from nearest monitoring stations were used to estimate exposures for each participant during 2015–2020 in Chongqing, China. We applied a generalized additive model and estimated RRs and 95% CIs for preterm birth in each trimester and the entire pregnancy period. In the single-pollutant model, we observed that each 10 μg/m³ increase in PM_2.5 had a statistically significant effect on the third trimester and entire pregnancy, with RR = 1.036 (95% CI: 1.021, 1.051) and RR = 1.101 (95% CI: 1.075, 1.128), respectively. Similarly, for each 10 μg/m³ increase in PM₁₀, there were 2.7% (RR = 1.027, 95% CI: 1.016, 1.038) increase for PTB on the third trimester, and 3.8% (RR = 1.038, 95% CI: 1.020, 1.057) increase during the whole pregnancy. We found that for each 10 mg/m³ CO increases, the relative risk of PTB increased on the first trimester (RR = 1.081, 95% CI: 1.007, 1.162), second trimester (RR = 1.116, 95% CI: 1.035, 1.204), third trimester (RR = 1.167, 95% CI: 1.090, 1.250) and whole pregnancy (RR = 1.098, 95% CI: 1.011, 1.192). No statistically significant RR was found for SO₂ and NO₂ on each trimester of pregnancy. Our study indicates that maternal exposure to high levels of PM_2.5 and PM₁₀ during pregnancy may increase the risk for preterm birth, especially for women at the late stage of pregnancy. Statistically increased risks of preterm birth were associated with CO exposure during each trimester and entire pregnancy. Reducing exposure to ambient air pollutants for pregnant women is clearly necessary to improve the health of infants.

Background: Gestational diabetes mellitus (GDM) may lead to many adverse effects on women and their offspring. Method: 24,429 pregnant women were enrolled during early pregnancy from January 2018 to December 2021. The self-reported intake of folic acid supplements was assessed via a questionnaire. Oral glucose tolerance tests were used for the diagnosis of GDM. The association between intake or not, dose, and duration of folic acid and GDM risk was assessed. Results: 6396 (26.18%) women were diagnosed with GDM. In the univariate models, folic acid was found to be correlated with total GDM risk (OR = 0.82, 95% CI: 0.70~0.95, p = 0.009). After adjusting for potential confounders, the association with total GDM risk was not significant, but the association of folic acid with 2-h PBG diagnosed GDM risk was consistently significant (OR = 0.75, 95% CI: 0.63~0.90, p = 0.002). No significant association between the dose and duration of folic acid supplementation and GDM risk was observed in the analyses. Conclusion: Folic acid supplementation might be a protective factor for the risk of GDM caused by the high level of postprandial blood glucose, but the dose or duration-related association between folic acid supplementation and GDM risk is not clear.

Purpose: To investigate whether pregnant women’s subjective sleep quality during the first trimester independently predicted blood glucose and gestational diabetes mellitus (GDM). Methods: A total of 4550 pregnant women in the first trimester were enrolled in Chongqing Health Center for Women and Children, China, from January to October 2020.The Pittsburgh Sleep Quality Index (PSQI) was used to measure subjective sleep quality. Depression symptoms and anxiety were measured with the Patient Health Questionnaire-9 (PHQ-9) and General Anxiety Disorder-7 (GAD-7). Oral glucose tolerance tests (OGTT) and blood glucose area under the curve (AUC) were used for estimation of blood glucose and diagnosis of GDM during the second trimester. Linear, mixed model, and logistic regression were used to analyze the association between PSQI and blood glucose as well as GDM. Results: 946/4550 were diagnosed with GDM (20.8%). In the mixed model analysis, the blood glucose level of the highest-scoring group (PSQI score = 18) was 1.94 (95% CI: 0.45∼ 3.43, P = 0.011) mmol/L higher than that of the lowest-scoring group (PSQI score = 0). After adjusting for potential confounders, a one-point PSQI score increase was associated with a 0.014 (95% CI: 0.001∼ 0.027, P = 0.039) mmol/L increase in blood glucose level. Blood glucose AUC was also positively associated with PSQI scores (β = 0.034, 95% CI: 0.003∼ 0.064, P = 0.030). The results for the logistic regression model showed that PSQI was marginal positively correlated with GDM (OR = 1.146, 95% CI: 0.995∼ 1.321, P = 0.059) when age and BMI were not controlled for. When investigating the association between PSQI and the GDM-diagnosed time window, the 1-h diagnosed GDM had a borderline positive correlation with PSQI (OR = 1.182, 95% CI: 0.993∼ 1.405, P = 0.060). Conclusion: Sleep quality during the first trimester may be a risk factor for elevated blood glucose and GDM later in gestation.