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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.
Afiliação
  • Kromydas T; MRC/CSO Social and Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, Glasgow, UK theocharis.kromydas@glasgow.ac.uk.
  • Demou E; MRC/CSO Social and Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
  • Edge R; Lancaster Medical School, Lancaster University, Lancaster, UK.
  • Gittins M; Centre for Biostatistics, The University of Manchester, Manchester, UK.
  • Katikireddi SV; MRC/CSO Social and Public Health Sciences Unit, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
  • Pearce N; Faculty of Public Health, London School of Hygiene & Tropical Medicine, London, UK.
  • van Tongeren M; Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK.
  • Wilkinson J; Centre for Occupational and Environmental Health, The University of Manchester, Manchester, UK.
  • Rhodes S; Thomas Ashton Institute for Risk and Regulatory Research, The University of Manchester, Manchester, UK.
Occup Environ Med ; 80(10): 545-552, 2023 10.
Article em En | MEDLINE | ID: mdl-37770179
ABSTRACT

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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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Prevalence_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Humans / Middle aged Idioma: En Revista: Occup Environ Med Assunto da revista: MEDICINA OCUPACIONAL / SAUDE AMBIENTAL Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Prevalence_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Humans / Middle aged Idioma: En Revista: Occup Environ Med Assunto da revista: MEDICINA OCUPACIONAL / SAUDE AMBIENTAL Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido