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Associations between greenness and predicted COVID-19–like illness incidence in the United States and the United Kingdom
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...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9916094/ https://www.ncbi.nlm.nih.gov/pubmed/36788976 http://dx.doi.org/10.1097/EE9.0000000000000244 |
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author | Chen, Kelly Klompmaker, Jochem O. Roscoe, Charlotte J. Nguyen, Long H. Drew, David A. James, Peter Laden, Francine Fecht, Daniela Wang, Weiyi Gulliver, John Wolf, Jonathan Steves, Claire J. Spector, Tim D. Chan, Andy T. Hart, Jaime E. |
author_facet | Chen, Kelly Klompmaker, Jochem O. Roscoe, Charlotte J. Nguyen, Long H. Drew, David A. James, Peter Laden, Francine Fecht, Daniela Wang, Weiyi Gulliver, John Wolf, Jonathan Steves, Claire J. Spector, Tim D. Chan, Andy T. Hart, Jaime E. |
author_sort | Chen, Kelly |
collection | PubMed |
description | 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 m(2)). 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. |
format | Online Article Text |
id | pubmed-9916094 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-99160942023-02-13 Associations between greenness and predicted COVID-19–like illness incidence in the United States and the United Kingdom Chen, Kelly Klompmaker, Jochem O. Roscoe, Charlotte J. Nguyen, Long H. Drew, David A. James, Peter Laden, Francine Fecht, Daniela Wang, Weiyi Gulliver, John Wolf, Jonathan Steves, Claire J. Spector, Tim D. Chan, Andy T. Hart, Jaime E. Environ Epidemiol Original Research Article 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 m(2)). 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. Lippincott Williams & Wilkins 2023-02-07 /pmc/articles/PMC9916094/ /pubmed/36788976 http://dx.doi.org/10.1097/EE9.0000000000000244 Text en Copyright © 2023 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Original Research Article Chen, Kelly Klompmaker, Jochem O. Roscoe, Charlotte J. Nguyen, Long H. Drew, David A. James, Peter Laden, Francine Fecht, Daniela Wang, Weiyi Gulliver, John Wolf, Jonathan Steves, Claire J. Spector, Tim D. Chan, Andy T. Hart, Jaime E. Associations between greenness and predicted COVID-19–like illness incidence in the United States and the United Kingdom |
title | Associations between greenness and predicted COVID-19–like illness incidence in the United States and the United Kingdom |
title_full | Associations between greenness and predicted COVID-19–like illness incidence in the United States and the United Kingdom |
title_fullStr | Associations between greenness and predicted COVID-19–like illness incidence in the United States and the United Kingdom |
title_full_unstemmed | Associations between greenness and predicted COVID-19–like illness incidence in the United States and the United Kingdom |
title_short | Associations between greenness and predicted COVID-19–like illness incidence in the United States and the United Kingdom |
title_sort | associations between greenness and predicted covid-19–like illness incidence in the united states and the united kingdom |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9916094/ https://www.ncbi.nlm.nih.gov/pubmed/36788976 http://dx.doi.org/10.1097/EE9.0000000000000244 |
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