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COVID-19 risk by work-related factors: pooled analysis of individual linked data from 14 cohorts
by
Katikireddi, Srinivasa Vittal
, Shaw, Richard J
, Ploubidis, George
, Demou, Evangelia
, Rhead, Rebecca
, Rhodes, Sarah
, Wielgoszewska, Bożena
, Wels, Jacques
, Stevenson, Anna
, Zhu, Jingmin
, Hamilton, Olivia K L
, Badrick, Ellena
, Gittins, Matthew
, van Tongeren, Martie
in
Adult
/ Cohort analysis
/ Cohort Studies
/ Collaboration
/ COVID-19
/ COVID-19 - epidemiology
/ COVID-19 vaccines
/ Diagnostic systems
/ Diagnostic tests
/ Digital health
/ Disease transmission
/ Electronic health records
/ Female
/ Furloughs
/ Health risks
/ Health services
/ Humans
/ Immunization
/ Longitudinal Studies
/ Male
/ Meta-analysis
/ Middle Aged
/ Occupational Health
/ Occupations - statistics & numerical data
/ Pandemics
/ Population
/ Risk Factors
/ Risk management
/ SARS-CoV-2
/ Self employment
/ Self Report
/ Severe acute respiratory syndrome coronavirus 2
/ Surveys
/ Telecommuting
/ United Kingdom - epidemiology
/ Viral diseases
/ Viral infections
/ Work at home
/ Workplace
2024
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COVID-19 risk by work-related factors: pooled analysis of individual linked data from 14 cohorts
by
Katikireddi, Srinivasa Vittal
, Shaw, Richard J
, Ploubidis, George
, Demou, Evangelia
, Rhead, Rebecca
, Rhodes, Sarah
, Wielgoszewska, Bożena
, Wels, Jacques
, Stevenson, Anna
, Zhu, Jingmin
, Hamilton, Olivia K L
, Badrick, Ellena
, Gittins, Matthew
, van Tongeren, Martie
in
Adult
/ Cohort analysis
/ Cohort Studies
/ Collaboration
/ COVID-19
/ COVID-19 - epidemiology
/ COVID-19 vaccines
/ Diagnostic systems
/ Diagnostic tests
/ Digital health
/ Disease transmission
/ Electronic health records
/ Female
/ Furloughs
/ Health risks
/ Health services
/ Humans
/ Immunization
/ Longitudinal Studies
/ Male
/ Meta-analysis
/ Middle Aged
/ Occupational Health
/ Occupations - statistics & numerical data
/ Pandemics
/ Population
/ Risk Factors
/ Risk management
/ SARS-CoV-2
/ Self employment
/ Self Report
/ Severe acute respiratory syndrome coronavirus 2
/ Surveys
/ Telecommuting
/ United Kingdom - epidemiology
/ Viral diseases
/ Viral infections
/ Work at home
/ Workplace
2024
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COVID-19 risk by work-related factors: pooled analysis of individual linked data from 14 cohorts
by
Katikireddi, Srinivasa Vittal
, Shaw, Richard J
, Ploubidis, George
, Demou, Evangelia
, Rhead, Rebecca
, Rhodes, Sarah
, Wielgoszewska, Bożena
, Wels, Jacques
, Stevenson, Anna
, Zhu, Jingmin
, Hamilton, Olivia K L
, Badrick, Ellena
, Gittins, Matthew
, van Tongeren, Martie
in
Adult
/ Cohort analysis
/ Cohort Studies
/ Collaboration
/ COVID-19
/ COVID-19 - epidemiology
/ COVID-19 vaccines
/ Diagnostic systems
/ Diagnostic tests
/ Digital health
/ Disease transmission
/ Electronic health records
/ Female
/ Furloughs
/ Health risks
/ Health services
/ Humans
/ Immunization
/ Longitudinal Studies
/ Male
/ Meta-analysis
/ Middle Aged
/ Occupational Health
/ Occupations - statistics & numerical data
/ Pandemics
/ Population
/ Risk Factors
/ Risk management
/ SARS-CoV-2
/ Self employment
/ Self Report
/ Severe acute respiratory syndrome coronavirus 2
/ Surveys
/ Telecommuting
/ United Kingdom - epidemiology
/ Viral diseases
/ Viral infections
/ Work at home
/ Workplace
2024
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COVID-19 risk by work-related factors: pooled analysis of individual linked data from 14 cohorts
Journal Article
COVID-19 risk by work-related factors: pooled analysis of individual linked data from 14 cohorts
2024
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Overview
BackgroundSARS-CoV-2 infection rates vary by occupation, but the association with work-related characteristics (such as home working, keyworker or furlough) are not fully understood and may depend on ascertainment approach. We assessed infection risks across work-related characteristics and compared findings using different ascertainment approaches.MethodsParticipants of 14 UK-based longitudinal cohort studies completed surveys before and during the COVID-19 pandemic about their health, work and behaviour. These data were linked to the National Health Service digital health records, including COVID-19 diagnostic testing, within the UK Longitudinal Linkage Collaboration (UK LLC) research environment. Poisson regression modelled self-reported infection and diagnostic test confirmed infection within each cohort for work-related characteristics. Relative Risk (RR) were then combined using random effects meta-analysis.ResultsBetween March 2020 and March 2021, 74 757 individuals completed 167 302 surveys. Overall, 15 174 survey responses self-reported an infection, whereas 3053 had a linked positive test. Self-reported infection risk was greater in keyworkers versus not (RR=1.24 (95% CI 1.17, 1.31), among non-home working (1.08 (0.98, 1.19)) or some home working (1.06 (0.97, 1.17)) versus all home working. Part-time workers versus full time (0.94 (0.89, 0.99)) and furlough versus not (0.93 (0.88, 0.99)) had reduced risk. Results for the linked positive test outcome were comparable in direction but greater in magnitude, for example, a 1.85 (1.56, 2.20) in keyworkers.ConclusionThe UK LLC provides new opportunities for researchers to investigate risk factors, including occupational factors, for ill-health events in multiple largescale UK cohorts. Risk of SARS-CoV-2 infection and COVID-19 illness appeared to be associated with work-related characteristics. Associations using linked diagnostic test data appeared stronger than self-reported infection status.
Publisher
BMJ Publishing Group Ltd,BMJ Publishing Group LTD
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