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颗粒物与炎症及血液凝固标志物的短期和长期关联:一项荟萃分析。

The short- and long-term associations of particulate matter with inflammation and blood coagulation markers: A meta-analysis.

作者信息

Tang Hong, Cheng Zilu, Li Na, Mao Shuyuan, Ma Runxue, He Haijun, Niu Zhiping, Chen Xiaolu, Xiang Hao

机构信息

Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China; Global Health Institute, Wuhan University, 115# Donghu Road, Wuhan, China.

School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, 122# Luoshi Road, Wuhan, China.

出版信息

Environ Pollut. 2020 Dec;267:115630. doi: 10.1016/j.envpol.2020.115630. Epub 2020 Sep 10.

DOI:10.1016/j.envpol.2020.115630
PMID:33254709
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7687019/
Abstract

Inflammation and the coagulation cascade are considered to be the potential mechanisms of ambient particulate matter (PM) exposure-induced adverse cardiovascular events. Tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-8 (IL-8), and fibrinogen are arguably the four most commonly assayed markers to reflect the relationships of PM with inflammation and blood coagulation. This review summarized and quantitatively analyzed the existing studies reporting short- and long-term associations of PM(PM with an aerodynamic diameter ≤2.5 μm)/PM (PM with an aerodynamic diameter≤10 μm) with important inflammation and blood coagulation markers (TNF-α, IL-6, IL-8, fibrinogen). We reviewed relevant studies published up to July 2020, using three English databases (PubMed, Web of Science, Embase) and two Chinese databases (Wang-Fang, China National Knowledge Infrastructure). The OHAT tool, with some modification, was applied to evaluate risk of bias. Meta-analyses were conducted with random-effects models for calculating the pooled estimate of markers. To assess the potential effect modifiers and the source of heterogeneity, we conducted subgroup analyses and meta-regression analyses where appropriate. The assessment and correction of publication bias were based on Begg's and Egger's test and "trim-and-fill" analysis. We identified 44 eligible studies. For short-term PM exposure, the percent change of a 10 μg/m PM increase on TNF-α and fibrinogen was 3.51% (95% confidence interval (CI): 1.21%, 5.81%) and 0.54% (95% confidence interval (CI): 0.21%, 0.86%) respectively. We also found a significant short-term association between PM and fibrinogen (percent change = 0.17%, 95% CI: 0.04%, 0.29%). Overall analysis showed that long-term associations of fibrinogen with PM and PM were not significant. Subgroup analysis showed that long-term associations of fibrinogen with PM and PM were significant only found in studies conducted in Asia. Our findings support significant short-term associations of PM with TNF-α and fibrinogen. Future epidemiological studies should address the role long-term PM exposure plays in inflammation and blood coagulation markers level change.

摘要

炎症和凝血级联反应被认为是环境颗粒物(PM)暴露诱发不良心血管事件的潜在机制。肿瘤坏死因子-α(TNF-α)、白细胞介素-6(IL-6)、白细胞介素-8(IL-8)和纤维蛋白原可以说是反映PM与炎症及血液凝固之间关系最常用的四种检测标志物。本综述总结并定量分析了现有研究,这些研究报告了PM(空气动力学直径≤2.5μm的颗粒物)/PM(空气动力学直径≤10μm的颗粒物)与重要炎症和血液凝固标志物(TNF-α、IL-6、IL-8、纤维蛋白原)的短期和长期关联。我们检索了截至2020年7月发表的相关研究,使用了三个英文数据库(PubMed、Web of Science、Embase)和两个中文数据库(万方、中国知网)。对OHAT工具进行了一些修改后用于评估偏倚风险。采用随机效应模型进行Meta分析以计算标志物的合并估计值。为评估潜在的效应修饰因素和异质性来源,我们在适当情况下进行了亚组分析和Meta回归分析。基于Begg检验、Egger检验和“修剪填充”分析对发表偏倚进行评估和校正。我们共纳入了44项符合条件的研究。对于短期PM暴露,PM每增加10μg/m,TNF-α和纤维蛋白原的变化百分比分别为3.51%(95%置信区间(CI):1.21%,5.81%)和0.54%(95%置信区间(CI):0.21%,0.86%)。我们还发现PM与纤维蛋白原之间存在显著的短期关联(变化百分比=0.17%,95%CI:0.04%,0.29%)。总体分析表明,纤维蛋白原与PM和PM的长期关联不显著。亚组分析表明,纤维蛋白原与PM和PM的长期关联仅在亚洲开展的研究中显著。我们的研究结果支持PM与TNF-α和纤维蛋白原之间存在显著的短期关联。未来的流行病学研究应关注长期PM暴露在炎症和血液凝固标志物水平变化中所起的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/d50ec6790728/figs1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/0dd13cfdb1ac/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/fef65566d3a8/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/6cbd6792b7dc/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/01a3d06b0c66/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/353c23b236eb/gr4a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/df56b16d4a56/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/7ae99c44fe01/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/d50ec6790728/figs1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/0dd13cfdb1ac/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/fef65566d3a8/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/6cbd6792b7dc/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/01a3d06b0c66/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/353c23b236eb/gr4a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/df56b16d4a56/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/7ae99c44fe01/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/7687019/d50ec6790728/figs1.jpg

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