PM_2.5 Constituents and Onset of Gestational Diabetes Mellitus: Identifying Susceptible Exposure Windows

Fine particulate matter (PM_2.5) has been linked to gestational diabetes mellitus (GDM). However, PM_2.5 is a complex mixture with large spatiotemporal heterogeneities, and women with early-onset GDM (i.e., diagnosed before 24^th gestation week) have distinct maternal characteristics and a higher risk of worse health outcomes compared with those with late-onset GDM (i.e., diagnosed in or after 24^th gestation week). We aimed to examine differential impacts of PM_2.5 and its constituents on early- vs. late-onset GDM, and to identify corresponding susceptible exposure windows. We leveraged statewide linked electronic health records and birth records data in Florida in 2012-2017. Exposures to PM_2.5 and its constituents (i.e., sulfate [SO₄ ^2-], ammonium [NH₄ ⁺], nitrate [NO₃ ^-], organic matter [OM], black carbon [BC], mineral dust [DUST], and sea-salt [SS]) were spatiotemporally linked to pregnant women based on their residential histories. Cox proportional hazards models and multinomial logistic regression were used to examine the associations of PM_2.5 and its constituents with GDM and its onsets. Distributed non-linear lag models were implemented to identify susceptible exposure windows. Exposures to PM_2.5, SO₄ ^2-, NH₄ ⁺, and BC were statistically significantly associated with higher hazards of GDM. Exposures to PM_2.5 during weeks 1-12 of gestation were positively associated with GDM. Associations of early-onset GDM with PM_2.5 in the 1^st and 2^nd trimesters, SO₄ ^2- in the 1^st and 2^nd trimesters, and NO₃ ^- in the preconception and 1^st trimester were considerably stronger than observations for late-onset GDM. Our findings suggest there are differential associations of PM_2.5 and its constituents with early- vs. late-onset GDM, with different susceptible exposure windows. This study helps better understand the impacts of air pollution on GDM accounting for its physiological heterogeneity.