PM2.5 Constituents and Onset of Gestational Diabetes Mellitus: Identifying Susceptible Exposure Windows.
PM2.5 Constituents and Onset of Gestational Diabetes Mellitus: Identifying Susceptible Exposure Windows.
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DOI：
10.1016/j.atmosenv.2022.119409
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发表时间：
2022-09
影响因子：
5
通讯作者：
Yi Zheng;Jiang Bian;J. Hart;F. Laden;Tony Wen;Jinying Zhao;Huaizhen Qin;Hui Hu
中科院分区：
文献类型：
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作者：
Yi Zheng;Jiang Bian;J. Hart;F. Laden;Tony Wen;Jinying Zhao;Huaizhen Qin;Hui Hu
细颗粒物 (PM2.5) 与妊娠期糖尿病 (GDM) 有关。然而，PM2.5 是一个复杂的混合物，具有很大的时空异质性，与晚发性 GDM（即在妊娠 24 周内或之后诊断）的女性相比，患有早发性 GDM（即在妊娠 24 周之前诊断出）的女性具有明显的母体特征，并且健康结果较差的风险更高。我们的目的是研究 PM2.5 及其成分对早期和后期的不同影响。迟发性 GDM，并确定相应的易感暴露窗口。我们利用了佛罗里达州 2012 年至 2017 年全州范围内链接的电子健康记录和出生记录数据。根据孕妇的居住史，PM2.5 及其成分（即硫酸盐 [SO42−]、铵 [NH4+]、硝酸盐 [NO3−]、有机物 [OM]、黑碳 [BC]、矿物粉尘 [DUST] 和海盐 [SS]）的暴露在时空上与孕妇相关。使用 Cox 比例风险模型和多项 Logistic 回归来研究 PM2.5 及其成分与 GDM 及其发病的关联。实施分布式非线性滞后模型来识别易受影响的曝光窗口。暴露于 PM2.5、SO42−、NH4+ 和 BC 与 GDM 的较高危险在统计学上显着相关。妊娠第 1-12 周期间接触 PM2.5 与 GDM 呈正相关。早发性 GDM 与妊娠第 1 期和第 2 期的 PM2.5、第 1 期和第 2 期的 SO42−以及孕前和第 1 期的 NO3− 的相关性明显强于晚发性 GDM 的观察结果。我们的研究结果表明，PM2.5 及其成分与早期和晚期之间存在不同的关联。晚发性 GDM，具有不同的易感暴露窗口。这项研究有助于更好地了解空气污染对 GDM 的影响，解释其生理异质性。
Fine particulate matter (PM2.5) has been linked to gestational diabetes mellitus (GDM). However, PM2.5is a complex mixture with large spatiotemporal heterogeneities, and women with early-onset GDM (i.e., diagnosed before 24th 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 24th gestation week). We aimed to examine differential impacts of PM2.5and 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 PM2.5and its constituents (i.e., sulfate [SO42−], 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 PM2.5and its constituents with GDM and its onsets. Distributed non-linear lag models were implemented to identify susceptible exposure windows. Exposures to PM2.5, SO42−, NH4+, and BC were statistically significantly associated with higher hazards of GDM. Exposures to PM2.5during weeks 1–12 of gestation were positively associated with GDM. Associations of early-onset GDM with PM2.5in the 1st and 2nd trimesters, SO42−in the 1st and 2nd trimesters, and NO3−in the preconception and 1st trimester were considerably stronger than observations for late-onset GDM. Our findings suggest there are differential associations of PM2.5and 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.