Evidence map›Paper›PMID 40203025›Full record

ArticlePloS one2025

Associations between different measures of SARS-CoV-2 infection status and subsequent economic inactivity: A pooled analysis of five longitudinal surveys linked to healthcare records.

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

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Richard J ShawMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, United Kingdom.ORCID 0000-0002-7906-6066
Olivia K L HamiltonMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, United Kingdom.ORCID 0000-0002-5874-0058
Rebecca RheadCentre for Longitudinal Studies (CLS), UCL Social Research Institute, University College London, London, United Kingdom.
Richard J SilverwoodCentre for Longitudinal Studies (CLS), UCL Social Research Institute, University College London, London, United Kingdom.ORCID 0000-0002-2744-1194
Jacques WelsMRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom.
Jingmin ZhuDepartment of Epidemiology & Public Health, University College London, London, United Kingdom.
Giorgio Di GessaDepartment of Epidemiology & Public Health, University College London, London, United Kingdom.ORCID 0000-0001-6154-1845
Ruth C E BowyerDepartment of Twin Research and Genetic Epidemiology, School of Life Course & Population Sciences, King's College London, London, United Kingdom.
Bettina MoltrechtCentre for Longitudinal Studies (CLS), UCL Social Research Institute, University College London, London, United Kingdom.
Michael J GreenMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, United Kingdom.
Evangelia DemouMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, United Kingdom.ORCID 0000-0001-8616-525X
Serena PattaroScottish Centre for Administrative Data Research (SCADR), University of Glasgow, Glasgow, United Kingdom.
Paola ZaninottoDepartment of Epidemiology & Public Health, University College London, London, United Kingdom.
Andy BoydPopulation Health Sciences, University of Bristol, Bristol, United Kingdom.
Felix GreavesDepartment of Primary Care and Public Health, Imperial College London, London, United Kingdom.
Nishi ChaturvediMRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom.
George B PloubidisCentre for Longitudinal Studies (CLS), UCL Social Research Institute, University College London, London, United Kingdom.
Srinivasa Vittal KatikireddiMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, United Kingdom.

Funding

Project-001R01AG017644 · NIA · UNIVERSITY OF LONDON INST OF NEUROLOGY · PI Andrew Steptoe · 2000 to 2026
$56.2M
NIA NIH HHS R01 AG017644
6 · The paper itself

Abstract

introductionFollowing the acute phase of the COVID-19 pandemic, a record number of people became economically inactive in the UK. We investigated the association between coronavirus infection and subsequent economic inactivity among people employed pre-pandemic, and whether this association varied between self-report versus healthcare recorded infection status.

methodsWe pooled data from five longitudinal studies (1970 British Cohort Study, English Longitudinal Study of Ageing, 1958 National Child Development Study, Next Steps, and Understanding Society), in two databases: the UK Longitudinal Linkage Collaboration (UKLLC), which links study data to NHS England records, and the UK Data Service (UKDS), which does not. The study population were aged 25-65 years between April 2020 to March 2021. The outcome was economic inactivity measured at the time of the last survey (November 2020 to March 2021). The exposures were COVID-19 status, indicated by a positive SARS-CoV-2 test in NHS records (UKLLC sample only), or by self-reported measures of coronavirus infection (both samples). Logistic regression models estimated odds ratios (ORs) adjusting for potential confounders including sociodemographic variables and pre-pandemic health.

resultsWithin the UKLLC sample (N = 8,174), both a positive SARS-CoV-2 test in NHS records (5.9% of the sample; OR 1.08, 95%CI 0.68-1.73) and self-reported positive tests (6.5% of the sample; OR 1.07, 95%CI 0.68-1.69), were marginally and non-significantly associated with economic inactivity (5.3% of the sample) in adjusted analyses. Within the larger UKDS sample (n = 13,881) reliant on self-reported ascertainment of infection (6.4% of the sample), the coefficient indicated a null relationship (OR 0.98, 95%CI 0.68-1.40) with economic inactivity (5.0% of sample).

conclusionsAmong people employed pre-pandemic, testing positive for SARS-CoV-2 was not associated with increased economic inactivity, although we could not exclude small effects. Ascertaining infection through healthcare records or self-report made little difference to results. However, processes related to record linkage may introduce small biases.

Indexed as

COVID-19AdultAgedFemaleHumansLongitudinal StudiesMaleMiddle AgedPandemicsSARS-CoV-2Self ReportSurveys and QuestionnairesUnited Kingdom

Identifiers

PMID40203025
PMCPMC11981124

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.