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评估 9 种户外空气污染物长期暴露对 107 个意大利省份 COVID-19 空间传播及相关死亡率的影响。

Assessing the impact of long-term exposure to nine outdoor air pollutants on COVID-19 spatial spread and related mortality in 107 Italian provinces.

机构信息

Department of Economics and Management, University of Pisa, Via Cosimo Ridolfi n. 10, 56124, Pisa, Italy.

出版信息

Sci Rep. 2022 Aug 3;12(1):13317. doi: 10.1038/s41598-022-17215-x.

DOI:10.1038/s41598-022-17215-x
PMID:35922645
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9349267/
Abstract

This paper investigates the air quality in 107 Italian provinces in the period 2014-2019 and the association between exposure to nine outdoor air pollutants and the COVID-19 spread and related mortality in the same areas. The methods used were negative binomial (NB) regression, ordinary least squares (OLS) model, and spatial autoregressive (SAR) model. The results showed that (i) common air pollutants-nitrogen dioxide (NO), ozone (O), and particulate matter (PM and PM)-were highly and positively correlated with large firms, energy and gas consumption, public transports, and livestock sector; (ii) long-term exposure to NO, PM, PM, benzene, benzo[a]pyrene (BaP), and cadmium (Cd) was positively and significantly correlated with the spread of COVID-19; and (iii) long-term exposure to NO O, PM, PM, and arsenic (As) was positively and significantly correlated with COVID-19 related mortality. Specifically, particulate matter and Cd showed the most adverse effect on COVID-19 prevalence; while particulate matter and As showed the largest dangerous impact on excess mortality rate. The results were confirmed even after controlling for eighteen covariates and spatial effects. This outcome seems of interest because benzene, BaP, and heavy metals (As and Cd) have not been considered at all in recent literature. It also suggests the need for a national strategy to drive down air pollutant concentrations to cope better with potential future pandemics.

摘要

本文调查了 2014-2019 年间意大利 107 个省份的空气质量,以及这些地区暴露于九种户外空气污染物与 COVID-19 传播和相关死亡率之间的关系。使用的方法是负二项回归(NB)、普通最小二乘法(OLS)和空间自回归(SAR)模型。结果表明:(i)常见空气污染物——二氧化氮(NO)、臭氧(O)和颗粒物(PM 和 PM)——与大型企业、能源和天然气消耗、公共交通和畜牧业高度正相关;(ii)长期暴露于 NO、PM、PM、苯、苯并[a]芘(BaP)和镉(Cd)与 COVID-19 的传播呈正相关且显著相关;(iii)长期暴露于 NO、O、PM、PM 和砷(As)与 COVID-19 相关死亡率呈正相关且显著相关。具体而言,颗粒物和 Cd 对 COVID-19 流行的影响最大;而颗粒物和 As 对超额死亡率的影响最大。即使在控制了十八个协变量和空间效应后,结果仍然得到了证实。这一结果似乎很有趣,因为最近的文献中根本没有考虑苯、BaP 和重金属(As 和 Cd)。这也表明需要制定国家战略,降低空气污染物浓度,以更好地应对潜在的未来大流行。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffe4/9349267/f7e7998420ec/41598_2022_17215_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffe4/9349267/bd5aaf6f811a/41598_2022_17215_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffe4/9349267/f7e7998420ec/41598_2022_17215_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffe4/9349267/bd5aaf6f811a/41598_2022_17215_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffe4/9349267/f7e7998420ec/41598_2022_17215_Fig2_HTML.jpg

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