Liang Weiqi, Zhu Hui, Xu Jin, Zhao Zhijia, Zhou Liming, Zhu Qiong, Cai Jie, Ji Lindan
Department of Preventive Medicine, School of Medicine, Ningbo University, Ningbo, China.
Department of Internal Medicine, School of Medicine, Ningbo University, Ningbo, China.
Ecotoxicol Environ Saf. 2023 Apr 15;255:114802. doi: 10.1016/j.ecoenv.2023.114802. Epub 2023 Mar 17.
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.
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.
This meta-analysis of 31 eligible cohort studies showed that exposure to PM, PM, SO, and NO was associated with a significantly increased risk of GDM, especially in preconception and first trimester. Analysis of the components of PM found that the risk of GDM was strongly linked to black carbon (BC) and nitrates (NO). Specifically, BC exposure in the second trimester and NO 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 PM and BC, which suggested that the specific composition of particulate pollutants had a greater effect on the exposure-outcome association than the concentration.
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.
我们旨在通过全面回顾流行病学研究来评估颗粒物(PM)成分与妊娠期糖尿病(GDM)之间的关系。
我们从六个数据库(PubMed、Embase、Web of Science核心合集、中国知网、万方数据知识服务平台和重庆维普中文科技期刊数据库)中系统地识别了2023年2月8日前与空气污染和GDM风险相关的队列研究。我们使用随机效应模型计算相对风险(RR)及其95%置信区间(CIs)以评估总体效应。
这项对31项合格队列研究的荟萃分析表明,暴露于PM、PM、SO和NO与GDM风险显著增加相关,尤其是在孕前和孕早期。对PM成分的分析发现,GDM风险与黑碳(BC)和硝酸盐(NO)密切相关。具体而言,孕中期暴露于BC和孕早期暴露于NO会增加GDM风险,RR分别为1.128(1.032 - 1.231)和1.128(1.032 - 1.231)。分层分析表明,在亚洲,除PM和BC外,GDM风险与较高水平污染物的相关性更强,这表明颗粒物污染物的具体成分对暴露 - 结局关联的影响大于浓度。
我们的研究发现环境空气污染物是GDM的一个关键因素,未来应考虑对特定颗粒物成分进行进一步研究。