Associations between greenness and predicted COVID-19-like illness incidence in the United States and the United Kingdom.

IF 3.3 Q2 ENVIRONMENTAL SCIENCES
Environmental Epidemiology Pub Date : 2023-02-07 eCollection Date: 2023-02-01 DOI:10.1097/EE9.0000000000000244
Kelly Chen, Jochem O Klompmaker, Charlotte J Roscoe, Long H Nguyen, David A Drew, Peter James, Francine Laden, Daniela Fecht, Weiyi Wang, John Gulliver, Jonathan Wolf, Claire J Steves, Tim D Spector, Andy T Chan, Jaime E Hart
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引用次数: 0

Abstract

Green spaces may be protective against COVID-19 incidence. They may provide outdoor, ventilated, settings for physical and social activities and therefore decrease transmission risk. We examined the association between neighborhood greenness and COVID-19-like illness incidence using individual-level data.

Methods: The study population includes participants enrolled in the COVID Symptom Study smartphone application in the United Kingdom and the United States (March-November 2020). All participants were encouraged to report their current health condition and suspected risk factors for COVID-19. We used a validated symptom-based classifier that predicts COVID-19-like illness. We estimated the Normalized Difference Vegetation Index (NDVI), for each participant's reported neighborhood of residence for each month, using images from Landsat 8 (30 m2). We used time-varying Cox proportional hazards models stratified by age, country, and calendar month at study entry and adjusted for the individual- and neighborhood-level risk factors.

Results: We observed 143,340 cases of predicted COVID-19-like illness among 2,794,029 participants. Neighborhood NDVI was associated with a decreased risk of predicted COVID-19-like illness incidence in the fully adjusted model (hazard ratio = 0.965, 95% confidence interval = 0.960, 0.970, per 0.1 NDVI increase). Stratified analyses showed protective associations among U.K. participants but not among U.S. participants. Associations were slightly stronger for White individuals, for individuals living in rural neighborhoods, and for individuals living in high-income neighborhoods compared to individuals living in low-income neighborhoods.

Conclusions: Higher levels of greenness may reduce the risk of predicted COVID-19-like illness incidence, but these associations were not observed in all populations.

Abstract Image

在美国和英国,绿色与预测的covid -19样疾病发病率之间的关系。
绿地可以预防COVID-19的发生。它们可为身体和社会活动提供室外通风环境,从而降低传播风险。我们使用个人层面的数据研究了社区绿化与covid -19样疾病发病率之间的关系。方法:研究人群包括在英国和美国(2020年3月至11月)注册了COVID症状研究智能手机应用程序的参与者。鼓励所有参与者报告他们目前的健康状况和疑似COVID-19风险因素。我们使用了一种经过验证的基于症状的分类器来预测covid -19样疾病。我们使用来自Landsat 8 (30 m2)的图像估计了每个参与者每月报告的居住地的归一化植被指数(NDVI)。我们使用时变Cox比例风险模型,在研究开始时按年龄、国家和日历月分层,并根据个人和社区水平的风险因素进行调整。结果:我们在2,794,029名参与者中观察到143,340例预测的covid -19样疾病。在完全调整模型中,邻里NDVI与预测的covid -19样疾病发病率降低相关(风险比= 0.965,95%置信区间= 0.960,0.970,每增加0.1 NDVI)。分层分析显示,英国参与者中存在保护关联,而美国参与者中没有。与生活在低收入社区的个体相比,白人个体、生活在农村社区的个体和生活在高收入社区的个体的关联略强。结论:较高的绿化水平可能会降低预测的covid -19样疾病发病率的风险,但并非在所有人群中都观察到这些关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Environmental Epidemiology
Environmental Epidemiology Medicine-Public Health, Environmental and Occupational Health
CiteScore
5.70
自引率
2.80%
发文量
71
审稿时长
25 weeks
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