Comparing population-level mental health of UK workers before and during the COVID-19 pandemic: a longitudinal study using Understanding Society

Kromydas, T., Green, M. , Craig, P. , Katikireddi, S. V. , Leyland, A. H. , Niedzwiedz, C. L. , Pearce, A. , Thomson, R. M. and Demou, E. (2022) Comparing population-level mental health of UK workers before and during the COVID-19 pandemic: a longitudinal study using Understanding Society. Journal of Epidemiology and Community Health, 76(6), pp. 527-536. (doi: 10.1136/jech-2021-218561) (PMID:35296523) (PMCID:PMC8931794)

[img] Text
264491.pdf - Published Version
Available under License Creative Commons Attribution.

3MB

Abstract

Objectives: The COVID-19 pandemic has substantially affected workers’ mental health. We investigated changes in UK workers’ mental health by industry, socioeconomic class and occupation and differential effects by UK country of residence, gender and age. Methods: We used representative Understanding Society data from 6474 adults (41 207 observations) in paid employment who participated in pre-pandemic (2017–2020) and at least one COVID-19 survey. The outcome was General Health Questionnaire-12 (GHQ-12) caseness (score: ≥4). Exposures were industry, socioeconomic class and occupation and are examined separately. Mixed-effects logistic regression was used to estimate relative (OR) and absolute (%) increases in distress before and during pandemic. Differential effects were investigated for UK countries of residence (non-England/England), gender (male/female) and age (younger/older) using three-way interaction effects. Results: GHQ-12 caseness increased in relative terms most for ‘professional, scientific and technical’ (OR: 3.15, 95% CI 2.17 to 4.59) industry in the pandemic versus pre-pandemic period. Absolute risk increased most in ‘hospitality’ (+11.4%). For socioeconomic class, ‘small employers/self-employed’ were most affected in relative and absolute terms (OR: 3.24, 95% CI 2.28 to 4.63; +10.3%). Across occupations, ‘sales and customer service’ (OR: 3.01, 95% CI 1.61 to 5.62; +10.7%) had the greatest increase. Analysis with three-way interactions showed considerable gender differences, while for UK country of residence and age results are mixed. Conclusions: GHQ-12 caseness increases during the pandemic were concentrated among ‘professional and technical’ and ‘hospitality’ industries and ‘small employers/self-employed’ and ‘sales and customers service’ workers. Female workers often exhibited greater differences in risk by industry and occupation. Policies supporting these industries and groups are needed.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Katikireddi, Professor Vittal and Demou, Dr Evangelia and Thomson, Dr Rachel and Green, Dr Michael and Kromydas, Dr Theocharis and Craig, Professor Peter and Leyland, Professor Alastair and Niedzwiedz, Dr Claire and Pearce, Dr Anna
Authors: Kromydas, T., Green, M., Craig, P., Katikireddi, S. V., Leyland, A. H., Niedzwiedz, C. L., Pearce, A., Thomson, R. M., and Demou, E.
College/School:College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > General Practice and Primary Care
College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > MRC/CSO SPHSU
Journal Name:Journal of Epidemiology and Community Health
Publisher:BMJ Publishing Group
ISSN:0143-005X
ISSN (Online):1470-2738
Published Online:16 March 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in Journal of Epidemiology and Community Health 76(6): 527-536
Publisher Policy:Reproduced under a Creative Commons licence

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
3048231Inequalities in healthAlastair LeylandMedical Research Council (MRC)MC_UU_00022/2HW - MRC/CSO Social and Public Health Sciences Unit
3048231Inequalities in healthAlastair LeylandChief Scientist Office (CSO)SPHSU17HW - MRC/CSO Social and Public Health Sciences Unit
172690Understanding the impacts of welfare policy on health: A novel data linkage studySrinivasa KatikireddiOffice of the Chief Scientific Adviser (CSO)SCAF/15/02HW - Public Health
306430Predicting the impacts of universal basic income on mental health inequalities in the UK population: a microsimulation modelRachel ThomsonWellcome Trust (WELLCOTR)218105/Z/19/ZHW - MRC/CSO Social and Public Health Sciences Unit
302182A machine learning approach to understanding comorbidity between mental and physical health conditionsClaire NiedzwiedzMedical Research Council (MRC)MR/R024774/1HW - Public Health
174091Improving life chances & reducing child health inequalities: harnessing the untapped potential of existing dataAnna PearceWellcome Trust (WELLCOTR)205412/Z/16/ZHW - MRC/CSO Social and Public Health Sciences Unit