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Occupational differences in the prevalence and severity of long-COVID: analysis of the Coronavirus (COVID-19) Infection Survey

OBJECTIVES: To establish whether prevalence and severity of long-COVID symptoms vary by industry and occupation. METHODS: We used Office for National Statistics COVID-19 Infection Survey (CIS) data (February 2021–April 2022) of working-age participants (16–65 years). Exposures were industry, occupat...

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Autores principales: Kromydas, Theocharis, Demou, Evangelia, Edge, Rhiannon, Gittins, Matthew, Katikireddi, Srinivasa Vittal, Pearce, Neil, van Tongeren, Martie, Wilkinson, Jack, Rhodes, Sarah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615205/
https://www.ncbi.nlm.nih.gov/pubmed/37770179
http://dx.doi.org/10.1136/oemed-2023-108930
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author Kromydas, Theocharis
Demou, Evangelia
Edge, Rhiannon
Gittins, Matthew
Katikireddi, Srinivasa Vittal
Pearce, Neil
van Tongeren, Martie
Wilkinson, Jack
Rhodes, Sarah
author_facet Kromydas, Theocharis
Demou, Evangelia
Edge, Rhiannon
Gittins, Matthew
Katikireddi, Srinivasa Vittal
Pearce, Neil
van Tongeren, Martie
Wilkinson, Jack
Rhodes, Sarah
author_sort Kromydas, Theocharis
collection PubMed
description OBJECTIVES: To establish whether prevalence and severity of long-COVID symptoms vary by industry and occupation. METHODS: We used Office for National Statistics COVID-19 Infection Survey (CIS) data (February 2021–April 2022) of working-age participants (16–65 years). Exposures were industry, occupation and major Standard Occupational Classification (SOC) group. Outcomes were self-reported: (1) long-COVID symptoms and (2) reduced function due to long-COVID. Binary (outcome 1) and ordered (outcome 2) logistic regression were used to estimate odds ratios (OR)and prevalence (marginal means). RESULTS: Public facing industries, including teaching and education, social care, healthcare, civil service, retail and transport industries and occupations, had the highest likelihood of long-COVID. By major SOC group, those in caring, leisure and other services (OR 1.44, 95% CIs 1.38 to 1.52) had substantially elevated odds than average. For almost all exposures, the pattern of ORs for long-COVID symptoms followed SARS-CoV-2 infections, except for professional occupations (eg, some healthcare, education, scientific occupations) (infection: OR<1; long-COVID: OR>1). The probability of reporting long-COVID for industry ranged from 7.7% (financial services) to 11.6% (teaching and education); whereas the prevalence of reduced function by ‘a lot’ ranged from 17.1% (arts, entertainment and recreation) to 22%–23% (teaching and education and armed forces) and to 27% (not working). CONCLUSIONS: The risk and prevalence of long-COVID differs across industries and occupations. Generally, it appears that likelihood of developing long-COVID symptoms follows likelihood of SARS-CoV-2 infection, except for professional occupations. These findings highlight sectors and occupations where further research is needed to understand the occupational factors resulting in long-COVID.
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spelling pubmed-76152052023-10-13 Occupational differences in the prevalence and severity of long-COVID: analysis of the Coronavirus (COVID-19) Infection Survey Kromydas, Theocharis Demou, Evangelia Edge, Rhiannon Gittins, Matthew Katikireddi, Srinivasa Vittal Pearce, Neil van Tongeren, Martie Wilkinson, Jack Rhodes, Sarah Occup Environ Med Workplace OBJECTIVES: To establish whether prevalence and severity of long-COVID symptoms vary by industry and occupation. METHODS: We used Office for National Statistics COVID-19 Infection Survey (CIS) data (February 2021–April 2022) of working-age participants (16–65 years). Exposures were industry, occupation and major Standard Occupational Classification (SOC) group. Outcomes were self-reported: (1) long-COVID symptoms and (2) reduced function due to long-COVID. Binary (outcome 1) and ordered (outcome 2) logistic regression were used to estimate odds ratios (OR)and prevalence (marginal means). RESULTS: Public facing industries, including teaching and education, social care, healthcare, civil service, retail and transport industries and occupations, had the highest likelihood of long-COVID. By major SOC group, those in caring, leisure and other services (OR 1.44, 95% CIs 1.38 to 1.52) had substantially elevated odds than average. For almost all exposures, the pattern of ORs for long-COVID symptoms followed SARS-CoV-2 infections, except for professional occupations (eg, some healthcare, education, scientific occupations) (infection: OR<1; long-COVID: OR>1). The probability of reporting long-COVID for industry ranged from 7.7% (financial services) to 11.6% (teaching and education); whereas the prevalence of reduced function by ‘a lot’ ranged from 17.1% (arts, entertainment and recreation) to 22%–23% (teaching and education and armed forces) and to 27% (not working). CONCLUSIONS: The risk and prevalence of long-COVID differs across industries and occupations. Generally, it appears that likelihood of developing long-COVID symptoms follows likelihood of SARS-CoV-2 infection, except for professional occupations. These findings highlight sectors and occupations where further research is needed to understand the occupational factors resulting in long-COVID. BMJ Publishing Group 2023-10 2023-09-28 /pmc/articles/PMC7615205/ /pubmed/37770179 http://dx.doi.org/10.1136/oemed-2023-108930 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Workplace
Kromydas, Theocharis
Demou, Evangelia
Edge, Rhiannon
Gittins, Matthew
Katikireddi, Srinivasa Vittal
Pearce, Neil
van Tongeren, Martie
Wilkinson, Jack
Rhodes, Sarah
Occupational differences in the prevalence and severity of long-COVID: analysis of the Coronavirus (COVID-19) Infection Survey
title Occupational differences in the prevalence and severity of long-COVID: analysis of the Coronavirus (COVID-19) Infection Survey
title_full Occupational differences in the prevalence and severity of long-COVID: analysis of the Coronavirus (COVID-19) Infection Survey
title_fullStr Occupational differences in the prevalence and severity of long-COVID: analysis of the Coronavirus (COVID-19) Infection Survey
title_full_unstemmed Occupational differences in the prevalence and severity of long-COVID: analysis of the Coronavirus (COVID-19) Infection Survey
title_short Occupational differences in the prevalence and severity of long-COVID: analysis of the Coronavirus (COVID-19) Infection Survey
title_sort occupational differences in the prevalence and severity of long-covid: analysis of the coronavirus (covid-19) infection survey
topic Workplace
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615205/
https://www.ncbi.nlm.nih.gov/pubmed/37770179
http://dx.doi.org/10.1136/oemed-2023-108930
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