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Identifying Contextual and Spatial Risk Factors for Post-Acute Sequelae of SARS-CoV-2 Infection: An EHR-based Cohort Study from the RECOVER Program
Post-acute sequelae of SARS-CoV-2 infection (PASC) affects a wide range of organ systems among a large proportion of patients with SARS-CoV-2 infection. Although studies have identified a broad set of patient-level risk factors for PASC, little is known about the contextual and spatial risk factors...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580388/ https://www.ncbi.nlm.nih.gov/pubmed/36263067 http://dx.doi.org/10.1101/2022.10.13.22281010 |
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author | Zhang, Yongkang Hu, Hui Fokaidis, Vasilios Lewis, Colby Xu, Jie Zang, Chengxi Xu, Zhenxing Wang, Fei Koropsak, Michael Bian, Jiang Hall, Jaclyn Rothman, Russell L. Shenkman, Elizabeth A. Wei, Wei-Qi Weiner, Mark G. Carton, Thomas W. Kaushal, Rainu |
author_facet | Zhang, Yongkang Hu, Hui Fokaidis, Vasilios Lewis, Colby Xu, Jie Zang, Chengxi Xu, Zhenxing Wang, Fei Koropsak, Michael Bian, Jiang Hall, Jaclyn Rothman, Russell L. Shenkman, Elizabeth A. Wei, Wei-Qi Weiner, Mark G. Carton, Thomas W. Kaushal, Rainu |
author_sort | Zhang, Yongkang |
collection | PubMed |
description | Post-acute sequelae of SARS-CoV-2 infection (PASC) affects a wide range of organ systems among a large proportion of patients with SARS-CoV-2 infection. Although studies have identified a broad set of patient-level risk factors for PASC, little is known about the contextual and spatial risk factors for PASC. Using electronic health data of patients with COVID-19 from two large clinical research networks in New York City and Florida, we identified contextual and spatial risk factors from nearly 200 environmental characteristics for 23 PASC symptoms and conditions of eight organ systems. We conducted a two-phase environment-wide association study. In Phase 1, we ran a mixed effects logistic regression with 5-digit ZIP Code tabulation area (ZCTA5) random intercepts for each PASC outcome and each contextual and spatial factor, adjusting for a comprehensive set of patient-level confounders. In Phase 2, we ran a mixed effects logistic regression for each PASC outcome including all significant (false positive discovery adjusted p-value < 0.05) contextual and spatial characteristics identified from Phase I and adjusting for confounders. We identified air toxicants (e.g., methyl methacrylate), criteria air pollutants (e.g., sulfur dioxide), particulate matter (PM(2.5)) compositions (e.g., ammonium), neighborhood deprivation, and built environment (e.g., food access) that were associated with increased risk of PASC conditions related to nervous, respiratory, blood, circulatory, endocrine, and other organ systems. Specific contextual and spatial risk factors for each PASC condition and symptom were different across New York City area and Florida. Future research is warranted to extend the analyses to other regions and examine more granular contextual and spatial characteristics to inform public health efforts to help patients recover from SARS-CoV-2 infection. |
format | Online Article Text |
id | pubmed-9580388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-95803882022-10-20 Identifying Contextual and Spatial Risk Factors for Post-Acute Sequelae of SARS-CoV-2 Infection: An EHR-based Cohort Study from the RECOVER Program Zhang, Yongkang Hu, Hui Fokaidis, Vasilios Lewis, Colby Xu, Jie Zang, Chengxi Xu, Zhenxing Wang, Fei Koropsak, Michael Bian, Jiang Hall, Jaclyn Rothman, Russell L. Shenkman, Elizabeth A. Wei, Wei-Qi Weiner, Mark G. Carton, Thomas W. Kaushal, Rainu medRxiv Article Post-acute sequelae of SARS-CoV-2 infection (PASC) affects a wide range of organ systems among a large proportion of patients with SARS-CoV-2 infection. Although studies have identified a broad set of patient-level risk factors for PASC, little is known about the contextual and spatial risk factors for PASC. Using electronic health data of patients with COVID-19 from two large clinical research networks in New York City and Florida, we identified contextual and spatial risk factors from nearly 200 environmental characteristics for 23 PASC symptoms and conditions of eight organ systems. We conducted a two-phase environment-wide association study. In Phase 1, we ran a mixed effects logistic regression with 5-digit ZIP Code tabulation area (ZCTA5) random intercepts for each PASC outcome and each contextual and spatial factor, adjusting for a comprehensive set of patient-level confounders. In Phase 2, we ran a mixed effects logistic regression for each PASC outcome including all significant (false positive discovery adjusted p-value < 0.05) contextual and spatial characteristics identified from Phase I and adjusting for confounders. We identified air toxicants (e.g., methyl methacrylate), criteria air pollutants (e.g., sulfur dioxide), particulate matter (PM(2.5)) compositions (e.g., ammonium), neighborhood deprivation, and built environment (e.g., food access) that were associated with increased risk of PASC conditions related to nervous, respiratory, blood, circulatory, endocrine, and other organ systems. Specific contextual and spatial risk factors for each PASC condition and symptom were different across New York City area and Florida. Future research is warranted to extend the analyses to other regions and examine more granular contextual and spatial characteristics to inform public health efforts to help patients recover from SARS-CoV-2 infection. Cold Spring Harbor Laboratory 2022-10-13 /pmc/articles/PMC9580388/ /pubmed/36263067 http://dx.doi.org/10.1101/2022.10.13.22281010 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Zhang, Yongkang Hu, Hui Fokaidis, Vasilios Lewis, Colby Xu, Jie Zang, Chengxi Xu, Zhenxing Wang, Fei Koropsak, Michael Bian, Jiang Hall, Jaclyn Rothman, Russell L. Shenkman, Elizabeth A. Wei, Wei-Qi Weiner, Mark G. Carton, Thomas W. Kaushal, Rainu Identifying Contextual and Spatial Risk Factors for Post-Acute Sequelae of SARS-CoV-2 Infection: An EHR-based Cohort Study from the RECOVER Program |
title | Identifying Contextual and Spatial Risk Factors for Post-Acute Sequelae of SARS-CoV-2 Infection: An EHR-based Cohort Study from the RECOVER Program |
title_full | Identifying Contextual and Spatial Risk Factors for Post-Acute Sequelae of SARS-CoV-2 Infection: An EHR-based Cohort Study from the RECOVER Program |
title_fullStr | Identifying Contextual and Spatial Risk Factors for Post-Acute Sequelae of SARS-CoV-2 Infection: An EHR-based Cohort Study from the RECOVER Program |
title_full_unstemmed | Identifying Contextual and Spatial Risk Factors for Post-Acute Sequelae of SARS-CoV-2 Infection: An EHR-based Cohort Study from the RECOVER Program |
title_short | Identifying Contextual and Spatial Risk Factors for Post-Acute Sequelae of SARS-CoV-2 Infection: An EHR-based Cohort Study from the RECOVER Program |
title_sort | identifying contextual and spatial risk factors for post-acute sequelae of sars-cov-2 infection: an ehr-based cohort study from the recover program |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580388/ https://www.ncbi.nlm.nih.gov/pubmed/36263067 http://dx.doi.org/10.1101/2022.10.13.22281010 |
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