key: cord-0310193-915nac0z
authors: Wels, J.; Booth, C.; Wielgoszewska, B.; Green, M. J.; Di Gessa, G.; Huggins, C. F.; Griffith, G. J.; Kwong, A. S. F.; Bowyer, R. C. E.; Maddock, J.; Patalay, P.; Silverwood, R. J.; Fitzsimons, E.; Shaw, R. J.; Steptoe, A.; Hughes, A.; Chaturvedi, N.; Steves, C. J.; Katikireddi, S. V.; Ploubidis, G. B.
title: Association of COVID-19 employment disruption with mental and social wellbeing: evidence from nine UK longitudinal studies
date: 2021-11-16
journal: nan
DOI: 10.1101/2021.11.15.21266264
sha: 7823de59e72d01e6b923354e09ddb052da93fe75
doc_id: 310193
cord_uid: 915nac0z

Background: The COVID-19 pandemic has led to major economic disruptions. In March 2020, the UK implemented the Coronavirus Job Retention Scheme, known as furlough, to minimize the impact of job losses. We investigate associations between change in employment status and mental and social wellbeing during the early stages of the pandemic. Methods: Data from 25,670 respondents, aged 16 to 66, from nine UK longitudinal studies were analysed. Changes in employment (including being furloughed) were defined by comparing employment status pre-pandemic and during the first lockdown. Mental and social wellbeing outcomes included psychological distress, life satisfaction, self-rated health, social contact, and loneliness. Study-specific modified Poisson regression estimates, adjusting for socio-demographic characteristics and pre-pandemic outcome measures, were pooled using meta-analysis. Results: Compared to those who remained working, furloughed workers were at greater risk of psychological distress (adjusted risk ratio, ARR=1.12; 95% CI: 0.97, 1.29), low life satisfaction (ARR=1.14; 95% CI: 1.07, 1.22), loneliness (ARR=1.12; 95% CI: 1.01, 1.23), and fair/poor self-rated health (ARR=1.26; 95% CI: 1.05, 1.50), but risk ratios appear less pronounced compared to those no longer employed (e.g., psychological distress, ARR=1.39; 95% CI: 1.21, 1.59) or stable unemployed (e.g., psychological distress, ARR=1.33; 95% CI: 1.09, 1.62). Conclusions: During the early stages of the pandemic those furloughed had increased risk for poor mental and social wellbeing. However, their excess risk was lower in magnitude than those who became or remained unemployed, suggesting that furlough partly mitigated poorer outcomes.

2 Background COVID-19 and its associated mitigation measures, including a series of lockdowns, have had an impact on the economy in the United Kingdom (UK) and worldwide (Koltai et al., 2020;  Office for National Statistics, 2020). There is a well-established relationship between individual employment status and mental health and wellbeing Flint et al., 2013; Frasquilho et al., 2016; Parsons et al., 2021; Steele et al., 2013) . Existing literature on the effects of economic downturns on population health and health-related behaviours is complex and suggests effects are context-specific and vary across generations and between different demographic and socioeconomic groups (Catalano et al., 2011; Copeland et al., 2015; Valkonen et al., 2000) .

In addition to economic disruptions, the COVID-19 pandemic has led to healthcare disruptions, and mitigation measures resulted in the closure of non-essential retail, leisure facilities, and schools. Overall, it has been estimated that the prevalence of mental distress in the UK increased from 19.1% pre-pandemic to 30.6% in early lockdown, with greater deteriorations observed in young adults and women (Banks & Xu, 2020) . More recent longitudinal research has found a sustained worsening of psychological distress across subsequent stages of the pandemic, particularly for women and young adults (Patel et al., 2021) . However, it is unclear how employment status change is related to mental and social wellbeing in this unique context. Employment is generally considered to be associated with good health (Benach et al., 2010; Graetz, 1993) and job loss or unemployment with deleterious physical and mental health (Puig-Barrachina et al., 2011) , including lower psychological wellbeing (Murphy & Athanasou, 1999) and increased mortality (Roelfs et al., 2011) . Men and those in their early and middle career stage can be especially affected (Roelfs et al., 2011) , though some studies have found greater effects of unemployment for women (Drivakis, 2015) . Unemployment is also sometimes associated with social isolation and loneliness, but evidence on this remains mixed Lobo, 2018) .

People with pre-existing mental health problems were more likely to experience employment disruption during the pandemic (Di Gessa et al 2021; Breslau et al., 2021) ), but it remains unclear how policies introduced to mitigate economic disruption might affect mental health. The UK government launched the Coronavirus Job Retention Scheme (CJRS, widely referred to as 'furlough') in March 2020, providing employees who were unable to work due to the pandemic with 80% of pay (capped at £2,500 per month) (Adams-Prassl et al., 2020) . Becoming furloughed differs from traditional forms of employment change for several reasons. First, furlough schemes reduce uncertainty, as cessation of work is intended to be temporary. Second, a substantial portion of income is maintained. However, while furlough helps maintain many of the advantages of employment, other benefits, such as time structure, collective purpose, social contact, and activity are likely diminished for furloughed workers (Paul & Batinic, 2010) . Thus, the implications of the novel UK furlough scheme remain unclear.

By bringing together data from nine UK longitudinal studies, we investigate how changes in employment status, in particular being furloughed, is associated with psychological distress, life satisfaction, self-rated health, social contact, and loneliness, during the early stages of the pandemic. It is plausible that these associations will not affect all groups equally, therefore we examine whether associations differ by sex, age, education, and household composition.

Participants and design Participants were 25,670 respondents from nine UK population-based longitudinal studies, who completed surveys both before and during the COVID-19 pandemic. Pandemic data were collected between April-June 2020 and pre-pandemic data constituted the most recent data available for each study prior to the pandemic. Further details of the design, sampling frame, age range, timing of the pre-pandemic and COVID-19 surveys, response rates, and sample size are in Supplementary File 1.

Five studies were age homogenous birth cohorts: the Millennium Cohort Study (MCS); the index children from the Avon Longitudinal Study of Parents and Children (ALSPAC-G1); Next Steps (NS, formerly the Longitudinal Study of Young People in England); the 1970 British Cohort Study (BCS70); and the 1958 National Child Development Study (NCDS). Four age heterogenous studies were included: Understanding Society (USOC); the English Longitudinal Study of Ageing (ELSA); the Scottish Family Health Study: Generation Scotland (GS); and the UK's largest adult twin registry (TwinsUK). Finally, the parents of the ALSPAC-G1 cohort were treated as a fifth age heterogenous study population (ALSPAC-G0).

Analytical samples were restricted to working age participants, defined as those aged 16 to 66 (the current state pension age in the UK), who had at least one wellbeing outcome in the COVID-19 survey and relevant pre-pandemic measures for confounder adjustment. Where possible, studies were weighted to be representative of their target population, accounting for sampling design and differential non-response (see, for instance, Brown et al. (2020) ). Weights were not available for GS.

Please, see Supplementary File 2 for full details on the measures and variable coding.

Employment change (or stability) was operationalised by comparing respondents' self-reported employment status during the initial stages of the pandemic and retrospectively in the months preceding the start of the pandemic. Based on this information, we created six employment change (or stability) categories: stable employed (either as self-employed or an employee, which served as the reference group); furloughed (i.e., from employed to furlough); no longer employed (i.e., from employed to not working, such as job loss or retirement); stable unemployed (i.e., unemployed at both points); became employed (i.e., from not working to employed); and stable non-employed (i.e., not available for employment at either point, including in education, early retirement, caring responsibilities, sick or disabled).

We investigated six different mental and social wellbeing outcomes. For each outcome, we created a binary variable using pre-validated cut-off scores where possible. Psychological is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted November 16, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 distress was measured using the Kessler-6 (MCS) (Kessler et al., 2002) , General Health Questionnaire-12 (NS, USOC) (Goldberg, 1978) , Malaise Inventory (BCS, NCDS) (Rutter, 1970) , Centre for Epidemiological Studies Depression Scale (ELSA) (Radloff, 1977) , Short Mood and Feelings Questionnaire (ALSPAC G0/G1) (Angold et al., 1995) , Patient Health Questionnaire (GS) (Kroenke & Spitzer, 2002) , and Hospital Anxiety and Depression Scale (Twins UK) (Zigmond & Snaith, 1983) . Life satisfaction was assessed using the Office for National Statistics (ONS) wellbeing scale that asks participants to rate how satisfied they are with their lives (most studies used a 0-10 scale; USOC used 1-7): those who answered less than 7 (or less than 5 in USOC) were classified as reporting low life satisfaction. Self-rated health was measured using responses to a generic question asking participants to rate their health on a five-point ordinal scale (excellent; very good; good; fair; poor): the five items were dichotomised into 'fair or poor' versus 'excellent, very good or good'. Social contact (either face-to-face, by telephone, or text message) with family and friends outside the household was assessed in most studies: we distinguished between those reporting daily versus less than daily social contact. Loneliness was assessed (MCS, NS, BCS, NCDS, ELSA, TwinsUK) using the short version of the Revised UCLA loneliness scale, with scores of 6 and higher indicating high loneliness (Russell et al., 1980) . Additionally, we also considered the direct question "How often do you feel lonely?" rated on a three-point ordinal scale (hardly ever; some of the time; often), as this was asked in two further studies (USOC, GS): we compared those reporting feeling often lonely versus other.

Two levels of confounder adjustment were applied. The basic adjustment accounted for sociodemographic characteristics: age (for age-heterogeneous studies), sex, ethnicity (White vs. non-White ethnic minority -not available in NCDS and BCS), education (degree vs. no degree parent education used for MCS), UK nation (England; Scotland; Wales; Northern Ireland), and household composition (living alone; with partner -including possible children or others; others -such as housemates or family members, but no partner). The full adjustment additionally used all the available pre-pandemic wellbeing measures, in order to determine whether differences in wellbeing outcomes could be attributed to changes taking place during the pandemic.

Within each study, each of the binary outcomes were regressed on employment status change, using a modified Poisson model with robust standard errors (Zou, 2004; Zou & Donner, 2013) , returning risk ratios. We focus on reporting risk ratios comparing stable employment to furlough, no longer employed, and stable unemployment. A sensitivity analysis was conducted with the continuous version of psychological distress (standardised within studies), using linear regression. After estimating unadjusted associations, the "basic" and then "full" confounder adjustment models were estimated. Results from each study were statistically pooled using a random effects meta-analysis with restricted maximum likelihood (maximum likelihood was used for models that failed to converge). Study-specific estimates were excluded if the number of individuals reporting the outcome of interest was very low (≤ 2). Stratification by sex, age, education, and household composition was assessed with sub-group analyses using the full confounder adjustment. We report sub-group differences that were significant at the p < .05 . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.

is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint 

Across nine studies, 25,670 participants were analysed, with the largest sample from USOC (N = 6,849), and the smallest from TwinsUK (N = 978). Mental and social wellbeing outcomes tended to be worse in younger cohorts. For example, the prevalence of psychological distress was 35.7% in the NS cohort (aged 30-31 years), which was an increase from their pre-pandemic levels (25.4%). The NCDS cohort (aged 63 years) showed 12.2% prevalence for psychological distress, compared to 14.4% pre-pandemic. Those in older cohorts tended to report poorer selfrated health, e.g., 17.1% prevalence in NCDS and 22.0% prevalence in ELSA, compared to 7.0% in MCS, although these did not change much from pre-pandemic levels. Less than daily social contact during the pandemic was common across most studies (except in ALSPAC and TwinsUK).

Employment change Figure 1 shows employment status change during the initial stages of the pandemic by each study. Around six in 10 participants in NS, BCS, GS, USOC, and ALSPAC were stable employed, although lower proportions of stable employment were found in the younger (MCS) and older cohorts (ELSA, NCDS, TwinsUK). Prevalence of furlough ranged between 6% (TwinsUK) and 23% (BCS). Across most studies approximately 3% of participants were no longer employed during the pandemic (7% in ALSPAC G0). Stable unemployment ranged in prevalence between 1% (GS) and 9% (ALSPAC G0).

The pooled results suggest a gradient in the way employment change was associated with mental and social wellbeing outcomes (see Figure 2 ). Compared to those in stable employment, those furloughed, no longer employed, and stable unemployed tended to show higher risk ratios, with associations being worst for the stable unemployed, followed by those no longer employed, and then those furloughed. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted November 16, 2021. ; https://doi.org/10.1101/2021.11.15.21266264 doi: medRxiv preprint

In unadjusted models compared to participants in stable employment, those furloughed had higher psychological distress (RR=1.21; 95% CI: 1.02, 1.44; I² = 60%), as did people no longer employed (RR=1.60; 95% CI: 1.36, 1.87; I² = 0%), and those in stable unemployment (RR=1.98; 95% CI: 1.47, 2.67; I² = 50%). Estimates were attenuated in the fully adjusted model, but less so for furlough (ARR=1.12; 95% CI: 0.97, 1.29; I² = 49%) and those no longer employed (ARR=1.39; 95% CI: 1.21, 1.59; I² = 0%), than for those in stable unemployment (ARR=1.33; 95% CI: 1.09, 1.62; I² = 50%). The sensitivity analysis conducted with the continuous version of psychological distress confirmed these results. Sub-group analyses revealed no differences by sex, education, age, or household composition (see Supplementary File 3 for model estimates).

In unadjusted models compared to participants in stable employment, those furloughed had lower life satisfaction (RR=1.19; 95% CI: 1.10, 1.30; I² = 24%), as did those no longer employed (RR=1.39; 95% CI: 1.18, 1.64; I² = 45%), and those in stable unemployment (RR=1.98; 95% CI: 1.53, 2.55; I² = 76%). Estimates were attenuated in the fully adjusted model, but less so for furlough (ARR=1.14; 95% CI: 1.07, 1.22; I² = 7%) and those no longer employed (ARR=1.32; 95% CI: 1.13, 1.56; I² = 52%), than for those in stable unemployment (ARR=1.42; 95% CI: 1.14, 1.78; I² = 65%). Sub-group analyses revealed no differences by sex, education, age, or household composition.

Compared to stable employment, risk of fair/poor self-rated health was higher in the unadjusted model for furlough (RR=1.32; 95% CI: 1.09, 1.60; I² = 43%), no longer being employed (RR=1.67; 95% CI: 1.11, 2.49; I² = 61%), and stable unemployment (RR=3.85; 95% CI: 2.12, 7.01; I² = 85%). Estimates were attenuated in the fully adjusted model, with a similar pattern of milder attenuation for furlough (ARR=1.26; 95% CI: 1.05, 1.50; I² = 44%) and those no longer employed (ARR=1.50; 95% CI: 1.04, 2.17; I² = 59%), compared to those in stable unemployment (ARR=1.69; 95% CI: 1.16, 2.47; I² = 65%).

Sub-group analyses revealed differences by sex (p = .009), where furlough was associated with poorer self-rated health for females (ARR=1.41; 95% CI: 1.11, 1.79; I² = 49%), but not males (ARR=1.01; 95% CI: 0.97, 1.07; I² = 0%). Differences were also observed by age (p = .019), with no longer being employed being more strongly associated with poorer self-rated health among those aged 30-49 years (ARR=2.86; 95% CI: 1.28, 6.36; I² = 0%), compared to those aged 50+ (ARR=1.28; 95% CI: 0.95, 1.71; I² = 42%); estimates for ages 16-29 years were not available due to data sparsity.

. CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.

is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted November 16, 2021. ; https://doi.org/10. 1101 We observed no differences in the risk of less than daily social contact across employment groups in all models. Sub-group analyses revealed no differences by sex, education, age, or household composition.

Compared to stable employment, furlough was associated with higher loneliness in the unadjusted model (RR=1.19; 95% CI: 1.05, 1.35; I² = 27%), no longer being employed showed a similar magnitude association but confidence intervals crossed the null (RR=1.14; 95% CI: 0.93, 1.40; I² = 0%), and there was a stronger association for stable unemployment (RR=1.86; 95% CI: 1.38, 2.50; I² = 50%). In the fully adjusted model, only those furloughed had increased risk for high loneliness (ARR=1.12; 95% CI: 1.01, 1.23; I² = 0%). Sub-group analyses revealed no differences by sex, education, age, or household composition.

In the unadjusted model with the single-item loneliness measure, compared to those in stable employment, there was no clear association with furlough (RR=1.10; 95% CI: 0.80, 1.53; I² = 66%), but those no longer employed were more likely to report feeling lonely (RR=2.14; 95% CI: 1.32, 3.47; I² = 68%), as were those in stable unemployment (RR=3.49; 95% CI: 2.17, 5.63; I² = 61%). Results were attenuated in the fully adjusted model for those no longer employed (ARR=1.80; 95% CI: 1.09, 2.97; I² = 72%) and stable unemployed (ARR=1.43; 95% CI: 0.99, 2.06; I² = 42%).

Sub-group analyses revealed differences by sex (p = .051), whereby no longer being employed (compared to stable employment), was strongly associated with feeling lonely for females (ARR=2.39; 95% CI: 1.41, 4.08; I² = 72%), but not males (ARR=1.40; 95% CI: 0.60, 3.30; I² = 60%). There were also differences by household composition (p < .001), whereby stable unemployment was more strongly associated with feeling lonely for those living with a partner (and possibly other family members) (ARR=4.04; 95% CI: 2.28, 7.18; I² = 4%), than for those living alone (ARR=2.07; 95% CI: 1.32, 3.25; I² = 60%), or those living with others but no partner (ARR=1.00; 95% CI: 0.69, 1.44; I² = 0%).

Across nine well-established UK longitudinal studies, we found that furlough was associated with a slight decline in mental and social wellbeing compared to stable employment during the early stages of the COVID-19 pandemic. While raised risks of psychological distress, low life satisfaction, poor self-rated health, and loneliness were seen among furloughed people, associations were generally smaller than the relative risk associated with no longer being employed or being in stable unemployment. There was little association between employment status and having daily social contact.

Understanding the impacts of furlough is important because this policy was a key measure implemented to mitigate the economic disruption of the pandemic. Due to the UK CJRS furlough scheme, unemployment only rose moderately compared to other countries (Küçük et is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted November 16, 2021. ; https://doi.org/10.1101/2021.11.15.21266264 doi: medRxiv preprint al., 2021). By December 2020, 9.9 million UK employees (about 36% of the employed workforce) had been furloughed (Hensher, 2020) and the number of people claiming unemployment-related benefits increased by 1.4 million. Unlike traditional forms of unemployment, the relationship between specific labour market policy interventions, such as furlough, and health is less well-understood (Korpi, 1997) . This is partly because job retention schemes, which focus on buffering the impact of economic downturns via subsidised employment, were uncommon in Western countries prior to the COVID-19 outbreak (Puig-Barrachina et al., 2020) .

The existing studies on subsidised employment show inconsistent, although mostly beneficial effects on health and wellbeing (Puig-Barrachina et al., 2020; Wels & Hamarat, 2021) . For example, focusing on the restaurant industry in the US using cross-sectional data, Bufquin et al. (2021) showed that working employees experienced higher levels of psychological distress, drug, and alcohol use than temporary unemployed workers. However, Korpi (1997) showed that individuals in subsidised employment occupy an intermediate position in terms of wellbeing, where they are better-off than unemployed individuals, but worse-off than those in regular employment, and our findings largely concur with this pattern. A key explanation concerns the nature of these different employment statuses. Furloughed workers had more security than those who were no longer employed, as they were expected to be reinstated into employment as soon as it was safe for them to do so. Furthermore, they still received 80% of their pay (Burchell, 2011; Maier et al., 2006) which could at least partially protect against the long-and short-term health effects of income loss (Björklund & Eriksson, 1998; Dooley et al., 1996) . Moreover, we observed when adjusting for pre-pandemic characteristics, that the excess risk associated with stable unemployment was more strongly attenuated than that for furlough or no longer being employed. This indicates that the large magnitude risks associated with stable unemployment may have had relatively more to do with characteristics that were already established before the pandemic.

Previous research shows that economic disruptions during the pandemic were not experienced by all groups equally. Younger workers, low earners, and women were more likely to work in disrupted sectors, and therefore become unemployed or furloughed (Burchell et al., 2020) . People in lower skilled jobs, living in more deprived areas, or struggling financially were more likely to be furloughed (Gray et al., 2021) . Women with young children were more likely to be furloughed (Wielgoszewska et al., 2020) and previous studies found that, during the school closure period, women took on a bigger share of housework and childcare responsibilities (Zamarro & Prados, 2021; Zhou et al., 2020) . We found little evidence of wellbeing impacts varying between population sub-groups, although a slight increase in poorer self-rated health among furloughed women than men was observed. This might be because women who remained employed, as well as those furloughed, all experienced increased burdens and stress during the initial stages of the pandemic.

As with most observational studies, unobserved confounding could have affected our estimates. Despite being embedded within long standing cohorts, survey responses during the pandemic were lower than typically achieved, and while weighting was employed to correct for this, bias due to selective non-response cannot be ruled out (Fernández-Sanlés et al., 2021;  . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.

is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted November 16, 2021. ; https://doi.org/10.1101/2021.11.15.21266264 doi: medRxiv preprint Mostafa et al., 2021) . There are other limitations that should also be considered. First, we were not able to achieve full harmonisation of measures across studies, for example, a range of different psychological distress scales were used and questions on social contact differed considerably (which may explain some of the between study differences in prevalence). Second, all cohorts and studies could not contribute to every analysis as the number of cases and available data varied between studies. Third, participation in the furlough scheme was more common during the initial stages of the pandemic than being no longer employed or in stable unemployment, which meant that estimates for the latter groups were based on small numbers with considerable heterogeneity and imprecision in estimates, especially in sub-group analyses. Finally, it is important to recognise that stable employment itself may have changed during the pandemic with potential effects of home working and changes in working practices on mental health and wellbeing, which is an area for future research.

The UK CJRS furlough scheme officially ended on the 30 th of September 2021. It might be expected that the economic downturn caused by the COVID-19 pandemic will last beyond the end of the furlough scheme, and potentially beyond the end of the pandemic (Whitehead et al., 2021) . With potentially damaging effects on mental health and wellbeing for those who stopped working (via furlough or otherwise), one pertinent question is whether the mental health and wellbeing of those who were furloughed will recover when they move back to their previous employment status. In line with this, another important question is whether those who benefited from the CJRS scheme will be more likely to experience further economic disruptions such as job or income loss in the post-furlough period, as this could exacerbate detrimental effects on health and wellbeing.

During the early stages of the COVID-19 pandemic, employment disruption was associated with change in mental and social wellbeing. Furloughed workers occupied an intermediate position with respect to their mental and social wellbeing, between those who remained working during the early stages of the pandemic, and those who had left employment or remained unemployed. This suggests that furlough may have helped to mitigate the detrimental impacts of the COVID-19 pandemic on mental health, but nevertheless, furloughed workers still experienced a modest deterioration in their mental and social wellbeing and may need additional support to recover from pandemic-related disruptions.

. CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.

is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted November 16, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.

is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted November 16, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 Zigmond, A. S., & Snaith, R. P. (1983) . The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica, 67(6) . https://doi.org/10.1111/j. 1600 -0447.1983 .tb09716.x Zou, G. (2004 is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted November 16, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint Caption: Error bars show 95% confidence intervals; Stable employment is the reference category; Basic adjustment includes: age, sex, ethnicity, education, household composition; Full adjustment includes: psychological distress, life satisfaction, self-rated health, social contact, loneliness. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted November 16, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 Funding This work was supported by the National Core Studies, an initiative funded by UKRI, NIHR and the Health and Safety Executive. The COVID-19 Longitudinal Health and Wellbeing National Core Study was funded by the Medical Research Council (MC_PC_20030).

Understanding Society is an initiative funded by the Economic and Social Research Council and various Government Departments, with scientific leadership by the Institute for Social and Economic Research, University of Essex, and survey delivery by NatCen Social Research and Kantar Public. The Understanding Society COVID-19 study is funded by the Economic and Social Research Council (ES/K005146/1) and the Health Foundation (2076161). The research data are distributed by the UK Data Service. The Millennium Cohort Study, Next Steps, British Cohort Study 1970 and National Child Development Study 1958 are supported by the Centre for Longitudinal Studies, Resource Centre 2015-20 grant (ES/M001660/1) and a host of other co-founders. The COVID-19 data collections in these four cohorts were funded by the UKRI grant Understanding the economic, social and health impacts of COVID-19 using lifetime data: evidence from 5 nationally representative UK cohorts (ES/V012789/1).

The English Longitudinal Study of Ageing was developed by a team of researchers based at University College London, NatCen Social Research, the Institute for Fiscal Studies, the University of Manchester and the University of East Anglia. The data were collected by NatCen Social Research. The funding is currently provided by the National Institute on Aging in the US, and a consortium of UK government departments coordinated by the National Institute for Health Research. Funding has . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.

is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint

The copyright holder for this this version posted November 16, 2021. ; https://doi.org/10.1101 https://doi.org/10. /2021 

The Development of a Questionnaire for Use in Epidemiological Studies of Depression in Children and Adolescents

The mental health effects of the first two months of lockdown and social distancing during the Covid-19 pandemic in the UK

Six employment conditions and health inequalities: A descriptive overview

Unemployment and mental health: Evidence from research in the Nordic countries

A longitudinal study of predictors of serious psychological distress during COVID-19 pandemic

COVID-19 Survey in Five National Longitudinal Studies Waves 1 and 2 User Guide (Version 2) How to cite this guide Survey in Five National Longitudinal Studies: Waves 1 and 2 User Guide (Version 2). London: UCL Centre for Longitudinal Studies and

Employee work status, mental health, substance use, and career turnover intentions: An examination of restaurant employees during COVID-19

A temporal comparison of the effects of unemployment and job insecurity on wellbeing

Cut hours, not people: no work, furlough, short hours and mental health during the covid-19 pandemic in the UK

The health effects of economic decline

Grim up North or Northern grit? Recessions and the English spatial health divide (1991-2010)

Mental health inequalities in healthcare, economic, and housing disruption during COVID-19: an investigation in 12 longitudinal studies

Health and Unemployment

The effect of unemployment on self-reported health and mental health in Greece from 2008 to 2013: A longitudinal study before and during the financial crisis

Bias from questionnaire invitation and response in COVID-19 research: an example using ALSPAC

Do labour market status transitions predict changes in psychological well-being

Mental health outcomes in times of economic recession: A systematic literature review Health behavior, health promotion and society

Health consequences of employment and unemployment: Longitudinal evidence for young men and women

Characteristics of those most vulnerable to employment changes during the COVID-19 pandemic: A nationally representative cross-sectional study in Wales

Social contact and inequalities in depressive symptoms and loneliness among older adults: A mediation analysis of the English Longitudinal Study of Ageing. SSM -Population Health

Covid-19, unemployment, and health: time for deeper solutions?

Short screening scales to monitor population prevalences and trends in non-specific psychological distress

Changing probability of experiencing food insecurity by socioeconomic and demographic groups during the COVID-19 pandemic in the UK. MedRxiv

Is utility related to employment status? Employment, unemployment, labor market policies and subjective well-being among Swedish youth

The PHQ-9: A New Depression Diagnostic and Severity Measure

UK economic outlook: Brexit Britain in Covid recovery ward. Ational Institute UK Economic Outlook

Unemployment and leisure: the Marienthal legacy

Effects of short-and long-term unemployment on physical work capacity and on serum cortisol

Missing at random assumption made more plausible: evidence from the 1958 British birth cohort

The effect of unemployment on mental health

Coronavirus and the latest indicators for the UK economy and society

The UK Coronavirus Job Retention Scheme and changes in diet, physical activity and sleep during the COVID-19 pandemic: Evidence from eight longitudinal studies

Psychological Distress Before and During the COVID-19 Pandemic: Sociodemographic Inequalities in 11 UK Longitudinal Studies

The need for work: Jahoda's latent functions of employment in a representative sample of the German population

The impact of Active Labour Market Policies on health outcomes: A Scoping review

Monitoring Social Determinants of Health Inequalities: The Impact of Unemployment among Vulnerable Groups

The CES-D Scale: A Self-Report Depression Scale for Research in the General Population

Losing life and livelihood: A systematic review and meta-analysis of unemployment and all-cause mortality

The Revised UCLA Loneliness Scale: Concurrent and Discriminant Validity Evidence

Education, health and behaviour

Adjusting for selection bias in longitudinal analyses using simultaneous equations modeling: The relationship between employment transitions and mental health

Changes in socioeconomic inequalities in mortality during an economic boom and recession among middle-aged men and women in Finland

Are employment arrangements implemented during the first wave of COVID-19 associated with better health outcomes for women aged 55 and over?

Poverty, health, and covid-19

Finances and employment during lockdown. UCL Centre for Longitudinal Studies

Gender differences in couples' division of childcare, work and mental health during COVID-19

received by the Economic and Social Research Council. The English Longitudinal Study of Ageing Covid-19 Substudy was supported by the UK Economic and Social Research Grant

We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The second COVID-19 data sweep was also supported by the Faculty Research Director's discretionary fund

Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Wellcome Trust Clinical Research Facility, Edinburgh, Scotland and was funded by the Medical Research Council UK and the Wellcome Trust (Wellcome Trust Strategic Award "STratifying Resilience and Depression Longitudinally" (STRADL) Reference 104036/Z/14/Z). Generation Scotland is funded by the Wellcome Trust

SVK acknowledges funding from a NRS Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2) and the Scottish Government Chief Scientist Office (SPHSU17)

The funders had no role in the methodology, analysis or interpretation of the findings presented in this manuscript

The contributing studies have been made possible because of the tireless dedication, commitment and enthusiasm of the many people who have taken part. We would like to thank the participants and the numerous team members involved in the studies including interviewers, technicians, researchers, administrators, managers, health professionals and volunteers. We are additionally grateful to our funders for their financial input and support in making this research happen.

All datasets included in this analysis have established data sharing processes, and for most included studies the anonymised datasets with corresponding documentation can be downloaded for use by researchers from the UK Data Service. We have detailed the processes for each dataset in Supplementary File 1.

No conflicts of interest were declared by the authors, except SVK who is a member of the Scientific Advisory Group on Emergencies.