Ambient air pollution and gestational diabetes mellitus: An updated systematic review and meta-analysis

Abstract

Objective: We aimed to evaluate the relationship between the composition of particulate matter (PM) and gestational diabetes mellitus (GDM) by a comprehensively review of epidemiological studies. Methods: We systematically identified cohort studies related to air pollution and GDM risk before February 8, 2023 from six databases (PubMed, Embase, Web of Science Core Collection, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform and Chongqing VIP Chinese Science and Technology Periodical databases). We calculated the relative risk (RR) and its 95% confidence intervals (CIs) to assess the overall effect by using a random effects model. Results: This meta-analysis of 31 eligible cohort studies showed that exposure to PM2.5, PM10, SO2, and NO2 was associated with a significantly increased risk of GDM, especially in preconception and first trimester. Analysis of the components of PM2.5 found that the risk of GDM was strongly linked to black carbon (BC) and nitrates (NO3-). Specifically, BC exposure in the second trimester and NO3- exposure in the first trimester elevated the risk of GDM, with the RR of 1.128 (1.032–1.231) and 1.128 (1.032–1.231), respectively. The stratified analysis showed stronger correlations of GDM risk with higher levels of pollutants in Asia, except for PM2.5 and BC, which suggested that the specific composition of particulate pollutants had a greater effect on the exposure-outcome association than the concentration. Conclusions: Our study found that ambient air pollutant is a critical factor for GDM and further studies on specific particulate matter components should be considered in the future.

Keywords

• Gestational diabetes mellitus
• Gaseous pollutant
• Particulate matter
• Meta-analysis