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长期暴露于低浓度多环芳烃与血小板指数改变:中国的一项纵向研究。

Long-term exposure to low concentrations of polycyclic aromatic hydrocarbons and alterations in platelet indices: A longitudinal study in China.

机构信息

Department of Health Statistics, Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, School of Public Health, Shanxi Medical University, Taiyuan, People's Republic of China.

Department of Radiological and Environmental Medicine, State Environmental Protection Key Laboratory of Environment and Health (Taiyuan), China Institute for Radiation Protection (CIRP), Taiyuan, Shanxi, China.

出版信息

PLoS One. 2022 Nov 2;17(11):e0276944. doi: 10.1371/journal.pone.0276944. eCollection 2022.

Abstract

Long-term exposure to low polycyclic aromatic hydrocarbon (PAH) concentration may ave detrimental effects, including changing platelet indices. Effects of chronic exposure to low PAH concentrations have been evaluated in cross-sectional, but not in longitudinal studies, to date. We aimed to assess the effects of long-term exposure to the low-concentration PAHs on alterations in platelet indices in the Chinese population. During 2014-2017, we enrolled 222 participants who had lived in a village in northern China, 1-2 km downwind from a coal plant, for more than 25 years, but who were not employed by the plant or related businesses. During three follow-ups, annually in June, demographic information and urine and blood samples were collected. Eight PAHs were tested: namely 2-hydroxynaphthalene, 1-hydroxynaphthalene, 2-hydroxyfluorene, 9-hydroxyfluorene (9-OHFlu), 2-hydroxyphenanthrene (2-OHPh), 1-hydroxyphenanthrene (1-OHPh), 1-hydroxypyrene (1-OHP), and 3-hydroxybenzo [a] pyrene. Five platelet indices were measured: platelet count (PLT), platelet distribution width (PDW), mean platelet volume (MPV), platelet crit, and the platelet-large cell ratio. Generalized mixed and generalized linear mixed models were used to estimate correlations between eight urinary PAH metabolites and platelet indices. Model 1 assessed whether these correlations varied over time. Models 2 and 3 adjusted for additional personal information and personal habits. We found the following significant correlations: 2-OHPh (Model1 β1 = 18.06, Model2 β2 = 18.54, Model β3 = 18.54), 1-OHPh (β1 = 16.43, β2 = 17.42, β3 = 17.42), 1-OHP(β1 = 13.93, β2 = 14.03, β3 = 14.03) with PLT, as well as 9-OHFlu with PDW and MPV (odds ratio or Model3 ORPDW[95%CI] = 1.64[1.3-2.06], ORMPV[95%CI] = 1.33[1.19-1.48]). Long-term exposure to low concentrations of PAHs, indicated by2-OHPh, 1-OHPh, 1-OHP, and 9-OHFlu, as urinary biomarkers, affects PLT, PDW, and MPV. 9-OHFlu increased both PDW and MPV after elimination of the effects of other PAH exposure modes.

摘要

长期暴露于低浓度多环芳烃(PAH)可能会产生有害影响,包括改变血小板指数。迄今为止,已经评估了慢性暴露于低浓度 PAH 对血小板指数变化的影响,但都是在横断面研究中,而不是在纵向研究中。我们旨在评估长期暴露于低浓度 PAHs 对中国人群血小板指数变化的影响。2014 年至 2017 年期间,我们招募了 222 名参与者,他们在距离中国北方一家燃煤电厂下风方向 1-2 公里的一个村庄居住了 25 年以上,但没有在工厂或相关企业工作。在三次随访中,每年 6 月收集人口统计学信息和尿液及血液样本。检测了八种 PAHs:2-羟基萘、1-羟基萘、2-羟基芴、9-羟基芴(9-OHFlu)、2-羟基菲(2-OHPh)、1-羟基菲(1-OHPh)、1-羟基芘(1-OHP)和 3-羟基苯并[a]芘。测量了五个血小板指数:血小板计数(PLT)、血小板分布宽度(PDW)、平均血小板体积(MPV)、血小板crit 和血小板大细胞比。广义混合和广义线性混合模型用于估计八种尿 PAH 代谢物与血小板指数之间的相关性。模型 1 评估了这些相关性是否随时间变化。模型 2 和 3 调整了其他个人信息和个人习惯。我们发现以下显著相关性:2-OHPh(模型 1β1=18.06,模型 2β2=18.54,模型β3=18.54)、1-OHPh(β1=16.43,β2=17.42,β3=17.42)、1-OHP(β1=13.93,β2=14.03,β3=14.03)与 PLT 相关,以及 9-OHFlu 与 PDW 和 MPV 相关(比值比或模型 3 ORPDW[95%CI] = 1.64[1.3-2.06],ORMPV[95%CI] = 1.33[1.19-1.48])。作为尿液生物标志物,长期暴露于低浓度多环芳烃(PAH),由 2-OHPh、1-OHPh、1-OHP 和 9-OHFlu 表示,会影响 PLT、PDW 和 MPV。9-OHFlu 在消除其他 PAH 暴露模式的影响后,增加了 PDW 和 MPV。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7800/9629616/6d1f3dd16d7a/pone.0276944.g001.jpg

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