Fine particular matter and its constituents in air pollution and gestational diabetes mellitus

Guoqi Yu; Junjie Ao; Jing Cai; Zhongcheng Luo; Randall Martin; Aaron van Donkelaar; Haidong Kan; Jun Zhang

doi:10.1016/j.envint.2020.105880

Fine particular matter and its constituents in air pollution and gestational diabetes mellitus

Environ Int. 2020 Sep:142:105880. doi: 10.1016/j.envint.2020.105880. Epub 2020 Jun 25.

Authors

Guoqi Yu¹, Junjie Ao¹, Jing Cai², Zhongcheng Luo¹, Randall Martin³, Aaron van Donkelaar³, Haidong Kan⁴, Jun Zhang⁵

Affiliations

¹ Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai 200092, China.
² School of Public Health, Fudan University, Shanghai 200032, China.
³ Department of Physics and Atmospheric Science, Dalhousie University, 6300 Coburg Road, Halifax, Nova Scotia B3H 3J5, Canada.
⁴ School of Public Health, Fudan University, Shanghai 200032, China. Electronic address: kanh@fudan.edu.cn.
⁵ Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai 200092, China; School of Public Health, Shanghai Jiao-Tong University School of Medicine, Shanghai 200025, China. Electronic address: junjimzhang@sina.com.

PMID: 32593838
DOI: 10.1016/j.envint.2020.105880

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 PM_2.5 (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 PM_2.5 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 PM_2.5 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 PM_2.5 mass and accounting for multi-collinearity.

Conclusions: Exposure to PM_2.5 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.

Keywords: Air pollution; Chemical constituent; Gestational diabetes mellitus; Trimester.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Air Pollutants* / analysis
Air Pollutants* / toxicity
Air Pollution* / adverse effects
Air Pollution* / analysis
China / epidemiology
Cross-Sectional Studies
Diabetes, Gestational* / chemically induced
Diabetes, Gestational* / epidemiology
Female
Humans
Infant, Newborn
Particulate Matter / analysis
Particulate Matter / toxicity
Pregnancy

Substances

Air Pollutants
Particulate Matter