Evidence map›Paper›PMID 37662323›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Associations between SARS-CoV-2 infection and subsequent economic inactivity and employment status: pooled analyses of five linked longitudinal surveys.

Richard J Shaw, Rebecca Rhead, Richard J Silverwood, Jacques Wels, Jingmin Zhu, Olivia Kl Hamilton, Giorgio Di Gessa, Ruth Ce Bowyer, Bettina Moltrecht, Michael J Green and 8 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors at 10 institutions in 3 countries.

Richard J ShawMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
Rebecca RheadCentre for Longitudinal Studies (CLS), UCL Social Research Institute, University College London, London, UK.
Richard J SilverwoodCentre for Longitudinal Studies (CLS), UCL Social Research Institute, University College London, London, UK.
Jacques WelsMRC Unit for Lifelong Health and Ageing, University College London, London, UK.
Jingmin ZhuDepartment of Epidemiology & Public Health, University College London, London, UK.
Olivia Kl HamiltonMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
Giorgio Di GessaDepartment of Epidemiology & Public Health, University College London, London, UK.
Ruth Ce BowyerDepartment of Twin Research and Genetic Epidemiology, School of Life Course & Population Sciences, King's College London, London, UK.
Bettina MoltrechtCentre for Longitudinal Studies (CLS), UCL Social Research Institute, University College London, London, UK.
Michael J GreenMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
Evangelia DemouMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
Serena PattaroScottish Centre for Administrative Data Research (SCADR), University of Glasgow, Glasgow, UK.
Paola ZaninottoDepartment of Epidemiology & Public Health, University College London, London, UK.
Andy BoydPopulation Health Sciences, University of Bristol, Bristol, UK.
Felix GreavesDepartment of Primary Care and Public Health, Imperial College London, London, UK.
Nish ChaturvediMRC Unit for Lifelong Health and Ageing, University College London, London, UK.
George B PloubidisCentre for Longitudinal Studies (CLS), UCL Social Research Institute, University College London, London, UK.
Srinivasa Vittal KatikireddiMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
University College London · GBMRC/CSO Social and Public Health Sciences Unit · GBDuke University · USImperial College London · GBKing's College London · GBMRC Unit for Lifelong Health and Ageing · GBTuring Institute · GBUniversité Libre de Bruxelles · BEUniversity of Bristol · GBUniversity of Glasgow · GB

Funding

Project-001R01AG017644 · NIA · UNIVERSITY OF LONDON INST OF NEUROLOGY · PI Andrew Steptoe · 2000 to 2026
$56.2M
Medical Research Council MC_PC_20030Medical Research Council MC_PC_20051Medical Research Council MC_PC_20059Medical Research Council MR/W021277/1Medical Research Council MR/X021556/1NIA NIH HHS R01 AG017644
6 · The paper itself

Abstract

Introduction: Following the acute phase of the COVID-19 pandemic, record numbers of people became economically inactive (i.e., neither working nor looking for work), or non-employed (including unemployed job seekers and economically inactive people). A possible explanation is people leaving the workforce after contracting COVID-19. We investigated whether testing positive for SARS-CoV-2 is related to subsequent economic inactivity and non-employment, among people employed pre-pandemic. Methods: The data came from five UK longitudinal population studies held by both the UK Longitudinal Linkage Collaboration (UK LLC; primary analyses) and the UK Data Service (UKDS; secondary analyses). We pooled data from five long established studies (1970 British Cohort Study, English Longitudinal Study of Ageing, 1958 National Child Development Study, Next Steps, and Understanding Society). The study population were aged 25-65 years between March 2020 to March 2021 and employed pre-pandemic. Outcomes were economic inactivity and non-employment measured at the time of the last follow-up survey (November 2020 to March 2021, depending on study). For the UK LLC sample (n=8,174), COVID-19 infection was indicated by a positive SARS-CoV-2 test in NHS England records. For the UKDS sample we used self-reported measures of COVID-19 infection (n=13,881). Logistic regression models estimated odds ratios (ORs) with 95% confidence intervals (95%CIs) adjusting for potential confounders including sociodemographic variables, pre-pandemic health and occupational class. Results: Testing positive for SARS-CoV-2 was very weakly associated with economic inactivity (OR 1.08 95%CI 0.68-1.73) and non-employment status (OR 1.09. 95%CI 0.77-1.55) in the primary analyses. In secondary analyses, self-reported test-confirmed COVID-19 was not associated with either economic inactivity (OR 1.01 95%CI 0.70-1.44) or non-employment status (OR 1.03 95%CI 0.79-1.35). Conclusions: Among people employed pre-pandemic, testing positive for SARS-CoV-2 was either weakly or not associated with increased economic inactivity or non-employment. Research on the recent increases in economic inactivity should focus on other potential causes.

Indexed as

COVID-19Economic inactivityEmployment StatusSARS-CoV-2UK LLC

Identifiers

PMID37662323
PMCPMC10473774
OpenAlexW4385459505

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.