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中国石家庄地区 PM 和臭氧对流感发病率的影响:一项时间序列研究。

Impact of PM and ozone on incidence of influenza in Shijiazhuang, China: a time-series study.

机构信息

Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China.

The Department of Epidemic Treating and Preventing, Center for Disease Prevention and Control of Shijiazhuang City, Shijiazhuang, China.

出版信息

Environ Sci Pollut Res Int. 2023 Jan;30(4):10426-10443. doi: 10.1007/s11356-022-22814-2. Epub 2022 Sep 8.

Abstract

Most of the studies are focused on influenza and meteorological factors for influenza. There are still few studies focused on the relationship between pollution factors and influenza, and the results are not consistent. This study conducted distributed lag nonlinear model and attributable risk on the relationship between influenza and pollution factors, aiming to quantify the association and provide a basis for the prevention of influenza and the formulation of relevant policies. Environmental data in Shijiazhuang from 2014 to 2019, as well as the data on hospital-confirmed influenza, were collected. When the concentration of PM was the highest (621 μg/m), the relative risk was the highest (RR: 2.39, 95% CI: 1.10-5.17). For extremely high concentration PM (348 μg/m), analysis of cumulative lag effect showed statistical significance from cumulative lag0-1 to lag0-6 day, and the minimum cumulative lag effect appeared in lag0-2 (RR: 0.760, 95% CI: 0.655-0.882). In terms of ozone, the RR value was 2.28(1.19,4.38), when O concentration was 310 μg/m, and the RR was 1.65(1.26,2.15), when O concentration was 0 μg/m. The RR of this lag effect increased with the increase of lag days, and reached the maximum at lag0-7 days, RR and 95% CI of slightly low concentration and extremely high concentration were 1.217(1.108,1.337) and 1.440(1.012,2.047), respectively. Stratified analysis showed that there was little difference in gender, but in different age groups, the cumulative lag effect of these two pollutants on influenza was significantly different. Our study found a non-linear relationship between two pollutants and influenza; slightly low concentrations were more associated with contaminant-related influenza. Health workers should encourage patients to get the influenza vaccine and wear masks when going out during flu seasons.

摘要

大多数研究都集中在流感和气象因素对流感的影响上。目前,针对污染因素与流感之间的关系进行研究的较少,且结果并不一致。本研究采用分布滞后非线性模型和归因风险模型,探讨流感与污染因素之间的关系,旨在定量评估两者之间的关联,为流感的预防和相关政策的制定提供依据。收集了 2014-2019 年石家庄市的环境数据和医院确诊的流感数据。当 PM 浓度最高(621μg/m³)时,相对风险最高(RR:2.39,95%CI:1.10-5.17)。对于极高浓度的 PM(348μg/m³),累积滞后效应分析显示,从滞后 0-1 到滞后 0-6 天均有统计学意义,滞后 0-2 天的最小累积滞后效应(RR:0.760,95%CI:0.655-0.882)。对于臭氧,当 O₃浓度为 310μg/m³时,RR 值为 2.28(1.19,4.38),当 O₃浓度为 0μg/m³时,RR 值为 1.65(1.26,2.15)。这种滞后效应的 RR 值随着滞后天数的增加而增加,在滞后 0-7 天时达到最大值,略低浓度和极高浓度的 RR 值和 95%CI 分别为 1.217(1.108,1.337)和 1.440(1.012,2.047)。分层分析表明,性别差异不大,但在不同年龄组中,这两种污染物对流感的累积滞后效应存在显著差异。本研究发现两种污染物与流感之间存在非线性关系;略低浓度与污染物相关的流感相关性更强。卫生工作者应鼓励患者在流感季节外出时接种流感疫苗和佩戴口罩。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b6a/9458314/ff1d01d29e1e/11356_2022_22814_Fig1_HTML.jpg

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