Prospective cohort study on association between peri-conceptional air pollution exposure and gestational diabetes mellitus
10.3760/cma.j.issn.0253-9624.2019.08.004
- VernacularTitle: 围孕期空气污染物暴露与妊娠期糖尿病的关联研究
- Author:
Mengnan YAO
1
;
Ruixue TAO
2
;
Honglin HU
3
;
Ying ZHANG
4
;
Wanjun YIN
1
;
Dan JIN
1
;
Yang LIU
1
;
Fangbiao TAO
1
;
Peng ZHU
1
Author Information
1. Department of Maternal, Child&Adolescent Health, School of Public Health/Anhui Provincial Laboratory of Population Health and Eugenics, Anhui Medical University, Hefei 230032, China
2. Department of Gynecology and Obstetrics, Hefei First People′s Hospital, Hefei 230031, China
3. Department of Endocrinology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
4. Department of Obstetrics and Gynecology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
- Publication Type:Journal Article
- Keywords:
Diabetes, gestational;
Air pollution;
Cross-sectional studies;
Peri-conceptional period
- From:
Chinese Journal of Preventive Medicine
2019;53(8):817-823
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the association between the exposure to major air pollutants in pre-pregnancy and early pregnancy (peri-conceptional period) and gestational diabetes mellitus (GDM).
Methods:From March 2015 to April 2018, 4 817 pregnancies were recruited at three prenatal check-ups hospital in Hefei (Hefei First People′s Hospital, Hefei. Maternal and Child Care Hospital and the First Affiliated Hospital of Anhui Medical University), China. Questionnaire was used to collect the demographic data, the health status and lifestyle of pregnant women. GDM was diagnosed according to the Chinese Guidelines for the Prevention and Treatment of Type 2 Diabetes (2017 Edition). Logistic regression was used to investigate the association of exposure to major air pollutants (PM2.5, PM10, SO2, CO and NO2) during different periods of pre-pregnancy (12 weeks before pregnancy) and first trimester (12 weeks after last menstruation) and duration of exposure to high levels of pollutants with GDM.
Results:The mean±SD of the age of subjects was (29.14±4.19) years old and the prevalence of GDM was 21.4% (n=1 030). The results of multivariate logistic regression analysis showed that after adjusting for confounding factors, the risk of GDM increased gradually with the prolonged exposure time of high-concentration pollutants compared with pregnant women who were not exposed to high pollution during the pre-pregnancy (χ2=61.28, Ptrend<0.001) with the OR (95%CI) values for exposure time of 1, 2, and 3 months about 1.42 (1.10-1.84), 1.73 (1.29-2.33), and 2.51 (1.75-3.59), respectively. In the pre-pregnancy period, in every 10 μg/m3 increase of PM2.5 and PM10, the OR (95%CI) values of GDM were 1.14 (1.08-1.20) and 1.13 (1.08-1.19), respectively; for each increase of 1 μg/m3 and 0.10 mg/m3 of SO2 and CO, the OR (95% CI) values of GDM were 1.03 (1.01-1.05) and 1.07 (1.01-1.13), respectively. For every 1 μg/m3 increase in the average concentration of SO2 in the first trimester, the OR (95%CI) value of GDM was 1.02 (1.01-1.05).
Conclusion:PM2.5, PM10, SO2 and CO exposure during the pre-pregnancy and SO2 exposure in first trimester were positively correlated with the risk of GDM.
