加泰罗尼亚地区 COVID-19 后短期暴露于空气污染和入院情况:COVAIR-CAT 研究。

IF 6.4 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Anna Alari, Otavio Ranzani, Sergio Olmos, Carles Milà, Alex Rico, Joan Ballester, Xavier Basagaña, Payam Dadvand, Talita Duarte-Salles, Mark Nieuwenhuijsen, Rosa Maria Vivanco-Hidalgo, Cathryn Tonne
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引用次数: 0

摘要

背景:越来越多的证据表明,长期暴露于空气污染与不良 COVID-19 结果之间存在正相关。关于短期空气污染的研究结果并不一致,其中大部分来自生态研究设计。我们利用个人层面的数据,研究了空气污染物[二氧化氮(NO2)、直径为0.1微米的颗粒物]的短期变化与不良后果之间的关系:COVAIR-CAT(空气污染与 COVID-19 发病率和死亡率的关系:西班牙加泰罗尼亚大型人群队列研究)队列是西班牙加泰罗尼亚地区的一个大型人群队列,包括 240 902 名从 2020 年 3 月 1 日至 12 月 31 日在初级保健系统中被诊断为 COVID-19 的患者。我们的研究结果是确诊 COVID-19 后 30 天内的住院情况。我们使用个人居住地址来分配每日空气污染暴露量,并使用机器学习方法进行时空预测。对于每一次大流行,我们都建立了考克斯比例危害模型,并考虑了前 7 天非线性分布的滞后暴露量:结果:不同大流行波的结果差异很大。在第二波大流行期间,每周空气污染累积暴露量(滞后 0_7)在四分位数范围内的增加与 COVID-19 二氧化氮住院率增加 12%(95% CI:4%-20%)、PM2.5 增加 8%(95% CI:1%-16%)和 PM10 增加 9%(95% CI:3%-15%)有关。我们观察到,当天(滞后 0 天)的暴露量存在一致的正相关性,而滞后 0 天后的特定暴露量的相关性通常没有统计学意义:我们的研究表明,二氧化氮、PM2.5 和 PM10 与第二波期间确诊为 COVID-19 的患者的住院风险呈正相关。累积危险比主要受住院当天的暴露影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short-term exposure to air pollution and hospital admission after COVID-19 in Catalonia: the COVAIR-CAT study.

Background: A growing body of evidence has reported positive associations between long-term exposure to air pollution and poor COVID-19 outcomes. Inconsistent findings have been reported for short-term air pollution, mostly from ecological study designs. Using individual-level data, we studied the association between short-term variation in air pollutants [nitrogen dioxide (NO2), particulate matter with a diameter of <2.5 µm (PM2.5) and a diameter of <10 µm (PM10) and ozone (O3)] and hospital admission among individuals diagnosed with COVID-19.

Methods: The COVAIR-CAT (Air pollution in relation to COVID-19 morbidity and mortality: a large population-based cohort study in Catalonia, Spain) cohort is a large population-based cohort in Catalonia, Spain including 240 902 individuals diagnosed with COVID-19 in the primary care system from 1 March until 31 December 2020. Our outcome was hospitalization within 30 days of COVID-19 diagnosis. We used individual residential address to assign daily air-pollution exposure, estimated using machine-learning methods for spatiotemporal prediction. For each pandemic wave, we fitted Cox proportional-hazards models accounting for non-linear-distributed lagged exposure over the previous 7 days.

Results: Results differed considerably by pandemic wave. During the second wave, an interquartile-range increase in cumulative weekly exposure to air pollution (lag0_7) was associated with a 12% increase (95% CI: 4% to 20%) in COVID-19 hospitalizations for NO2, 8% (95% CI: 1% to 16%) for PM2.5 and 9% (95% CI: 3% to 15%) for PM10. We observed consistent positive associations for same-day (lag0) exposure, whereas lag-specific associations beyond lag0 were generally not statistically significant.

Conclusions: Our study suggests positive associations between NO2, PM2.5 and PM10 and hospitalization risk among individuals diagnosed with COVID-19 during the second wave. Cumulative hazard ratios were largely driven by exposure on the same day as hospitalization.

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来源期刊
International journal of epidemiology
International journal of epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
13.60
自引率
2.60%
发文量
226
审稿时长
3 months
期刊介绍: The International Journal of Epidemiology is a vital resource for individuals seeking to stay updated on the latest advancements and emerging trends in the field of epidemiology worldwide. The journal fosters communication among researchers, educators, and practitioners involved in the study, teaching, and application of epidemiology pertaining to both communicable and non-communicable diseases. It also includes research on health services and medical care. Furthermore, the journal presents new methodologies in epidemiology and statistics, catering to professionals working in social and preventive medicine. Published six times a year, the International Journal of Epidemiology provides a comprehensive platform for the analysis of data. Overall, this journal is an indispensable tool for staying informed and connected within the dynamic realm of epidemiology.
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