School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8SQ, Scotland, United Kingdom.
Department of Mathematics and Statistics, University of Strathclyde, Glasgow, G1 1XH, Scotland, United Kingdom; Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow G2 6QE, Scotland, United Kingdom.
Spat Spatiotemporal Epidemiol. 2022 Aug;42:100523. doi: 10.1016/j.sste.2022.100523. Epub 2022 Jun 8.
Better understanding the risk factors that exacerbate Covid-19 symptoms and lead to worse health outcomes is vitally important in the public health fight against the virus. One such risk factor that is currently under investigation is air pollution concentrations, with some studies finding statistically significant effects while other studies have found no consistent associations. The aim of this paper is to add to this global evidence base on the potential association between air pollution concentrations and Covid-19 hospitalisations and deaths, by presenting the first study on this topic at the small-area scale in Scotland, United Kingdom. Our study is one of the most comprehensive to date in terms of its temporal coverage, as it includes all hospitalisations and deaths in Scotland between 1st March 2020 and 31st July 2021. We quantify the effects of air pollution on Covid-19 outcomes using a small-area spatial ecological study design, with inference using Bayesian hierarchical models that allow for the residual spatial correlation present in the data. A key advantage of our study is its extensive sensitivity analyses, which examines the robustness of the results to our modelling assumptions. We find clear evidence that PM concentrations are associated with hospital admissions, with a 1 μgm increase in concentrations being associated with between a 7.4% and a 9.3% increase in hospitalisations. In addition, we find some evidence that PM concentrations are associated with deaths, with a 1 μgm increase in concentrations being associated with between a 2.9% and a 10.3% increase in deaths.
更好地了解加剧新冠病毒症状并导致更糟糕健康结果的风险因素，对于与病毒作斗争的公共卫生来说至关重要。目前正在研究的一个风险因素是空气污染浓度，一些研究发现具有统计学意义的影响，而其他研究则没有发现一致的关联。本文旨在为空气污染浓度与新冠病毒住院和死亡之间的潜在关联这一全球证据基础做出贡献，为此，我们在苏格兰（英国）进行了该主题的小型区域研究，这是该主题的首个研究。我们的研究在时间覆盖范围方面是迄今为止最全面的研究之一，因为它包括了 2020 年 3 月 1 日至 2021 年 7 月 31 日期间苏格兰的所有住院和死亡病例。我们使用小型区域空间生态研究设计来量化空气污染对新冠病毒结果的影响，并使用贝叶斯层次模型进行推断，该模型允许存在于数据中的剩余空间相关性。我们的研究的一个关键优势是其广泛的敏感性分析，这检验了结果对我们建模假设的稳健性。我们发现明确的证据表明 PM 浓度与住院有关，浓度增加 1 微克/立方米，住院人数增加 7.4%至 9.3%。此外，我们发现一些证据表明 PM 浓度与死亡有关，浓度增加 1 微克/立方米，死亡人数增加 2.9%至 10.3%。
