Fine particular matter and its constituents in air pollution and gestational diabetes mellitus. (September 2020)

• Record Type: Journal Article
• Authors: Yu, Guoqi; Ao, Junjie; Cai, Jing; Luo, Zhongcheng; Martin, Randall; Donkelaar, Aaron van; Kan, Haidong; Zhang, Jun
• Is Part Of: Environment international. Volume 142(2020)
• Publication Date: 2020-09
• Subjects: Gestational diabetes mellitus -- Air pollution -- Chemical constituent -- Trimester; Environmental protection -- Periodicals; Environmental health -- Periodicals; Environmental monitoring -- Periodicals; Environmental Monitoring -- Periodicals; Environnement -- Protection -- Périodiques; Hygiène du milieu -- Périodiques; Environnement -- Surveillance -- Périodiques; Environmental health; Environmental monitoring; Environmental protection; Periodicals; 333.705
• DOI: 10.1016/j.envint.2020.105880
• Languages: English
• ISSNs: 0160-4120

Abstract

Highlights: This is a retrospective cohort study based on a national multi-center survey. 54, 517 pregnant women from 55 hospitals in 24 provinces were included in the final analysis; A combined geoscience-statistical model was applied to estimate the exposure concentration of PM2.5 and its components; We used a generalized mixed model to estimate the associations, and identified several components with higher risks. We conducted the model analysis across different exposure windows and found that the second trimester is a relatively sensitive window. Abstract: Background: Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, previous studies provided inconsistent findings and no study has examined the effects of complex chemical constituents of the particular matter on GDM, especially in developing countries. Therefore, we aim to investigate the associations of exposure to PM2.5 (particular matter ≤ 2.5 μm) and its constituents with GDM, and to identify susceptible exposure window in a large survey in China. Methods: The China Labor and Delivery Survey was a cross-sectional investigation conducted in 24 provinces in China between 2015 and 2016. A random sample of all deliveries in each participating hospital was selected and detailed obstetric and newborn information was extracted from medical records. Average concentrations of PM2.5 and six constituents (organic matter, black carbon, sulfate, nitrate, ammonium and soil dust) were estimated (1 km × 1 km) using a combined geoscience-statistical model. GDM was diagnosed based on an oral glucose tolerance test (OGTT) between 24 to 28 weeks of gestation and according to IADPSG criteria. Generalized linear mixed models were used to adjust for potential confounders. Results: A total of 54, 517 subjects from 55 hospitals were included. The incidence of GDM was 10.8%. An interquartile range (IQR) increase in PM2.5 exposure in the 2nd trimester of pregnancy was associated with an increased GDM risk in the single pollutant model, [adjusted odds ratio (aOR) = 1.11 and 95% confidence interval (CI): 1.01–1.22]. Exposure to organic matter (aOR = 1.14; 95%CI: 1.05–1.23), black carbon (aOR = 1.15; 95%CI: 1.07–1.25) and nitrate (aOR = 1.13; 95%CI: 1.02–1.24) during 2nd trimester were associated with increased risks of GDM. Associations between constituents and GDM were robust after controlling for total PM2.5 mass and accounting for multi-collinearity. Conclusions: Exposure to PM2.5 in 2 nd trimester of pregnancy was associated with an increased risk of GDM. Organic matter, black carbon and nitrate may be the main culprits for the association.