Covid-19 Risk by work-related factors: Pooled analysis of individual linked data from 14 cohorts (preprint)

BackgroundSARS-CoV-2 infection rates vary by occupation, but the association with work-related characteristics (such as home working, key-worker, 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 NHS 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. Risk Ratios (RR) were then combined using random effects meta-analysis. ResultsBetween March 2020 and March 2021, 72,290 individuals completed 167,302 surveys. Overall, 11% of 138,924 responses self-reported an infection, whereas 1.9% of 159,820 responses had a linked positive test. Self-reported infection risk was greater in key-workers vs not (RR=1.24(95%C.I.=1.17,1.31), among non-home working (1.08(0.98,1.19)) or some home working (1.08(0.97,1.17)) vs all home working. Part-time workers vs full-time (0.94(0.89,0.99)), and furlough vs not (0.97(0.88,1.01)) had reduced risk. Results for the linked positive test outcome were comparable in direction but greater in magnitude e.g. an 1.85(1.56,2.20) in key-workers. 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. What is already known on this topic- Infection of SARS-CoV2 during the pandemic was shown to vary by occupation, with occupations such as healthcare, and education at higher risk during some or all of the pandemic. - What is not clear, is how are work-related characteristics such employment status, part-time working from home, and schemes such as furlough and key worker status associated with the risk of infection. What this study adds- This is the one of the first studies to examine work-related characteristics including work related government policies, in terms of their infection risk within the working population. - This is also one of the first studies to analyse data from the UK Longitudinal Linkage Collaboration (UK-LLC), in which multiple UK national longitudinal cohorts were linked to national health data including diagnostic testing for SARS-CoV2. - We further compared definitions infection via either a self-reported case of COVID-19 or a linked diagnostic SARS-CoV2 infection. How this study might affect Research Practice or Policy- The findings contribute to our understanding of work-related characteristics and related schemes were associated with infection risk under two definitions. This is pertinent given new and emerging variants are continuing to drive an ever-changing SARS-CoV-2 infection risk within the population, along with the need to adequately prepare for future pandemics that may occur.

Trade unions and mental health during an employment crisis. Evidence from the UK before and during the COVID-19 pandemic. (preprint)

BackgroundTrade union presence within a workplace could potentially affect employees working conditions and in turn health. We assessed the relationship between union (presence and membership) at the individual level and mental health in the context of COVID-19 employment disruptions. MethodsWe analysed panel data from Understanding Society collected before and during the COVID-19 pandemic (49,915 observations across 5,988 respondents) to assess the relationship between union presence and membership and a validated epidemiological measure of common mental disorders (CMD), the 12-Item General Health Questionnaire with a score of >/4 indicating probable anxiety/depression, referred to as caseness. A mixed-effect log-linear model assessed effect heterogeneity across time and industries, with average marginal effects (AME) indicating effect differences between groups. FindingsIn our sample, 49.1% worked in a unionised workplace, among which 53.8% were union members. Caseness prevalence was higher during the pandemic (25.4%) compared to pre-pandemic (18.4%). Working in a workplace with a trade union was associated with modest protection against CMD risk; (AMEpre-pandemic:0.010, 95%CI:-0.007; 0.027), (AME- pandemic:-0.002, 95%CI:-0.019; 0.016)]. Similarly, for union membership [(AMEpre- pandemic:0.016, 95%CI:-0.007; 0.039), (AMEpandemic:-0.010, 95%CI:-0.023; 0.020)]. Industry level heterogeneity exists in the relationship between union presence and membership and mental health. InterpretationTrade union presence may have a protective effect on workers mental health in periods of crisis, such as during a pandemic. Within unionised workplaces, trade union membership further mitigated the negative effects of the pandemic on mental health. Collective negotiation within workplaces may be protective in periods of uncertainty, benefiting all workers and not only those unionised. FundingMedical Research Council, Chief Scientist Office, European Research Council, Belgian National Scientific Fund (FNRS).

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

Background Following the acute phase of the COVID-19 pandemic, record numbers of people became economically inactive (i.e., neither working nor looking for work, e.g., retired), or non-employed (including unemployed job seekers and economically inactive people). A possible explanation is people leaving the workforce after contracting COVID-19. We aim to investigate whether testing positive for SARS-CoV-2 is related to subsequent economic inactivity and non-employment, among people who were in employment prior to the pandemic. Methods The primary source of data are UK longitudinal population studies linked to English NHS digital data, held by the UK Longitudinal Linkage Collaboration (UK LLC). We pooled data from five studies (1970 British Cohort Study, English Longitudinal Study of Ageing, 1958 National Child Development Study, Next Steps, and Understanding Society), established long before the pandemic with between two and eight follow up surveys during the pandemic. The study population comprised people aged 25-65 years during the study period (March 2020 to March 2021) who were employed pre-pandemic. Outcomes were economic inactivity and non-employment status measured at the time of the last follow-up survey (November 2020 to March 2021, depending on study). For participants who could be linked to NHS England data (n=8,174), COVID-19 infection was indicated by a positive SARS-CoV-2 test. For sensitivity analyses, we used a self-reported measure of COVID-19 infection from participants (n=13,881) in the public use files of the five studies. Potential confounders included sociodemographic variables, pre-pandemic self-rated health and occupational class. Logistic regression models estimated odds ratios (ORs) with 95% confidence intervals (95%CIs). Results In adjusted analyses, 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 sensitivity analyses, self-reported test-confirmed COVID-19 was not associated with either economic inactivity (OR 1.01: 95%CI 0.70 to 1.44) or non-employment status (OR1.03 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 exiting employment. Wide confidence intervals limit the ability to make definitive conclusions, but it appears unlikely that COVID-19 disease explains the increase in economic inactivity among working-age people.

Long COVID and financial outcomes: Evidence from four longitudinal population surveys (preprint)

Background: Long-term sequelae of COVID-19 (long COVID) include muscle weakness, fatigue, breathing difficulties and sleep disturbance over weeks or months. Using UK longitudinal data, we assessed the relationship between long COVID and financial disruption. Methods: We estimated associations between long COVID (derived using self-reported length of COVID-19 symptoms) and measures of financial disruption (subjective financial well-being, new benefit claims, changes in household income) by analysing data from four longitudinal population studies, gathered during the first year of the pandemic. We employed modified Poisson regression in a pooled analysis of the four cohorts adjusting for a range of potential confounders, including pre-pandemic (pre-long COVID) factors. Results: Among 20,112 observations across four population surveys, 13% reported having COVID-19 with symptoms that impeded their ability to function normally - 10.7% had such symptoms for <4 weeks (acute COVID-19), 1.2% had such symptoms for 4-12 weeks (ongoing symptomatic COVID-19) and 0.6% had such symptoms for >12 weeks (post-COVID-19 syndrome). We found that post-COVID-19 syndrome was associated with worse subjective financial well-being (adjusted relative risk ratios (aRRR)=1.57, 95% confidence interval (CI)=1.25, 1.96) and new benefit claims (aRRR=1.79, CI=1.27, 2.53). Associations were broadly similar across sexes and education levels. These results were not meaningfully altered when scaled to represent the population by age. Conclusions: Long COVID was associated with financial disruption in the UK. If our findings reflect causal effects, extending employment protection and financial support to people with long COVID may be warranted.

The potential contribution of vaccination uptake to occupational differences in risk of SARS-CoV-2: Analysis of the ONS COVID-19 Infection Survey (preprint)

Objectives To assess variation in vaccination uptake across occupational groups as a potential explanation for variation in risk of SARS-CoV-2 infection. Design We analysed data from the UK Office of National Statistics COVID-19 Infection Survey linked to vaccination data from the National Immunisation Management System in England from December 1st 2020 to 11th May 2022. We analysed vaccination uptake and SARS-CoV-2 infection risk by occupational group and assessed whether adjustment for vaccination reduced the variation in risk between occupational groups. Setting Results Estimated rates of triple-vaccination were high across all occupational groups (80% or above), but were lowest for food processing (80%), personal care (82%), hospitality (83%), manual occupations (84%), and retail (85%). High rates were observed for individuals working in health (95% for office-based, 92% for those in patient-facing roles) and education (91%) and office-based workers not included in other categories (90%). The impact of adjusting for vaccination when estimating relative risks of infection was generally modest (ratio of hazard ratios reduced from 1.38 to 1.32), but was consistent with the hypothesis that low vaccination rates contribute to elevated risk in some groups. Conversely, estimated relative risk for some occupational groups, such as people working in education, remained high despite high vaccine coverage. Conclusions Variation in vaccination coverage might account for a modest proportion of occupational differences in infection risk. Vaccination rates were uniformly very high in this cohort, which may suggest that the participants are not representative of the general population. Accordingly, these results should be considered tentative pending the accumulation of additional evidence.

Occupational differences in the prevalence and severity of long-COVID: Analysis of the ONS Coronavirus (COVID-19) Infection Survey (preprint)

Objectives: To establish whether prevalence and severity of long-COVID symptoms vary by industry and occupation. Methods: We utilised ONS Coronavirus Infection Survey (CIS) data (February 2021-April 2022) of working-age participants (16-65 years). Exposures were industrial sector, occupation and major Standard Occupational Classification (SOC) group. Outcomes were self-reported: (1) long-COVID symptoms; and (2) reduced function due to long-COVID. Binary (outcome 1) and ordered (outcome 2) logistic regression were used to estimate odds ratios (OR) and prevalence (marginal means) for all exposures. Results: Public facing industries, including teaching and education, social care, healthcare, civil service, retail and transport industries and occupations had highest odds ratios for long-COVID. By major SOC group, those in caring, leisure and other services (OR 1.44, CIs: 1.38-1.52) had substantially elevated odds than average. For almost all exposures, the pattern of odds ratios for long-COVID symptoms followed that for SARS-CoV-2 infections, except for professional occupations (OR<1 for infection; OR>1 for long-COVID). The probability of reporting long-COVID for industry ranged from 7.7% (financial services) to 11.6% (teaching and education); whereas the prevalence of reduced function by a lot ranged from 17.1% (arts, entertainment and recreation) to 22-23% (teaching and education and armed forces ) and to 27% (those not working). Conclusions: The risk and prevalence of long-COVID differs across industries and occupations. Generally, it appears that likelihood of developing long-COVID symptoms follows likelihood of SARS-CoV-2 infection, except for professional occupations. These findings highlight sectors and occupations where further research is needed to understand the occupational factors resulting in long-COVID.

Understanding Inequalities in Mental Health by Family Structure during COVID-19 Lockdowns: Evidence from the UK Household Longitudinal Study (preprint)

Background: The COVID-19 pandemic increased psychiatric distress and impacts differed by family structure. We aimed to identify mechanisms contributing to these inequalities. Methods: Survey data were from the UK Household Longitudinal Study. Psychiatric distress (GHQ-12) was measured in April 2020 (first UK lockdown; n=10,516), and January 2021 (lockdown re-introduced following eased restrictions; n=6,893). Pre-lockdown family structure comprised partner status and presence of children (<16 years). Mediating mechanisms included: active employment, financial strain, childcare/home-schooling, caring, and loneliness. Monte Carlo g-computation simulations were used to adjust for confounding and estimate total effects and decompositions into: controlled direct effects (effects if the mediator was absent), and portions eliminated (PE; representing differential exposure and vulnerability to the mediator). Results: In January 2021, after adjustment, we estimated increased risk of distress among couples with children compared to couples with no children (RR: 1.48; 95% CI: 1.15-1.82), largely because of childcare/home-schooling (PE RR: 1.32; 95% CI: 1.00-1.64). Single respondents without children also had increased risk of distress compared to couples with no children (RR: 1.55; 95% CI: 1.27-1.83), and the largest PE was for loneliness (RR: 1.16; 95% CI: 1.05-1.27), though financial strain contributed (RR: 1.05; 95% CI: 0.99-1.12). Single parents demonstrated the highest levels of distress, but confounder adjustment suggested uncertain effects with wide confidence intervals. Findings were similar in April 2020 and when stratified by sex. Conclusions: Access to childcare/schooling, financial security and social connection are important mechanisms that need addressing to avoid widening mental health inequalities during public health crises.

Home working and its association with social and mental wellbeing at different stages of the COVID-19 pandemic: Evidence from seven UK longitudinal population surveys. (preprint)

Background: Home working rates have increased since the COVID-19 pandemic's onset, but the health implications of this transformation are unclear. We assessed the association between home working and social and mental wellbeing through harmonised analyses of seven UK longitudinal studies. Methods: We estimated associations between home working and measures of psychological distress, low life satisfaction, poor self-rated health, low social contact, and loneliness across three different stages of the COVID-19 pandemic (T1= Apr-Jun 2020 - first lockdown, T2=Jul-Oct 2020 - eased restrictions, T3=Nov 2020-Mar 2021 - second lockdown), in seven population-based cohort studies using modified Poisson regression and meta-analyses to pool results across studies. Findings: Among 34,131 observations spread over three time points, we found higher rates of home working at T1 and T3 compared with T2, reflecting lockdown periods. Home working was not associated with psychological distress at T1 (RR=0.92, 95%CI=0.79-1.08) or T2 (RR=0.99, 95%CI=0.88-1.11), but a detrimental association was found with psychological distress at T3 (RR=1.17, 95%CI=1.05-1.30). Poorer psychological distress associated with home working was observed for those educated to below degree level at T2 and T3. Men working from home reported poorer self-reported health at T2. Interpretation: No clear evidence of an association between home working and mental wellbeing was found, apart from greater risk of psychological distress associated with home working during the second lockdown, but differences across sub-groups may exist. Longer term shifts to home working might not have adverse impacts on population wellbeing in the absence of pandemic restrictions but further monitoring of health inequalities is required.

Mental health and health behaviours before and during the COVID-19 lockdown: Longitudinal analyses of the UK Household Longitudinal Study (preprint)

BackgroundThere are concerns that COVID-19 mitigation measures, including the "lockdown", may have unintended health consequences. We examined trends in mental health and health behaviours in the UK before and during the initial phase of the COVID-19 lockdown and differences across population subgroups. MethodsRepeated cross-sectional and longitudinal analysis of the UK Household Longitudinal Study, including representative samples of adults (aged 18+) interviewed in four survey waves between 2015 and 2020 (n=48,426). 9,748 adults had complete data for longitudinal analyses. Outcomes included psychological distress (General Health Questionnaire-12 (GHQ)), loneliness, current cigarette smoking, use of e-cigarettes and alcohol consumption. Cross-sectional prevalence estimates were calculated and multilevel Poisson regression assessed associations between time period and the outcomes of interest, as well as differential associations by age, gender, education level and ethnicity. ResultsPsychological distress increased one month into lockdown with the prevalence rising from 19.4% (95% CI 18.7%-20.0%) in 2017-19 to 30.3% (95% CI 29.1%-31.6%) in April 2020 (RR=1.3, 95% CI: 1.1,1.4). Groups most adversely affected included women, young adults, people from an Asian background and those who were degree educated. Loneliness remained stable overall (RR=0.9, 95% CI: 0.6,1.5). Smoking declined (RR=0.9, 95% CI=0.8,1.0) and the proportion of people drinking four or more times per week increased (RR=1.4, 95% CI: 1.3,1.5), as did binge drinking (RR=1.5, 95% CI: 1.3,1.7). ConclusionsPsychological distress increased one month into lockdown, particularly among women and young adults. Smoking declined, but adverse alcohol use generally increased. Effective measures are required to mitigate adverse impacts on health. O_LSTWhat is already known on this topicC_LSTO_LICountries around the world have implemented radical COVID-19 lockdown measures, with concerns that these may have unintended consequences for a broad range of health outcomes. C_LIO_LIEvidence on the impact of lockdown measures on mental health and health-related behaviours remains limited. C_LI O_LSTWhat this study addsC_LSTO_LIIn the UK, psychological distress markedly increased during lockdown, with women particularly adversely affected. C_LIO_LICigarette smoking fell, but adverse drinking behaviour generally increased. C_LI

Occupation and risk of COVID-19: prospective cohort study of 120,621 UK Biobank participants (preprint)

Objectives: To investigate COVID-19 risk by occupational group. Design: Prospective study of linked population-based and administrative data. Setting: UK Biobank data linked to SARS-CoV-2 test results from Public Health England from 16 March to 3 May 2020. Participants: 120,621 UK Biobank participants who were employed or self-employed at baseline (2006-2010) and were 65 years or younger in March 2020. Overall, 29% (n=37,890) were employed in essential occupational groups, which included healthcare workers, social and education workers, and other essential workers comprising of police and protective service, food, and transport workers. Poisson regression models, adjusted for baseline sociodemographic, work-related, health, and lifestyle-related risk factors were used to assess risk ratios (RRs) of testing positive in hospital by occupational group as reported at baseline relative to non-essential workers. Main outcome measures: Positive SARS-CoV-2 test within a hospital setting (i.e. as an inpatient or in an Emergency Department). Results: 817 participants were tested for SARS-CoV-2 and of these, 206 (0.2%) individuals had a positive test in a hospital setting. Relative to non-essential workers, healthcare workers (RR 7.59, 95% CI: 5.43 to 10.62) and social and education workers (RR 2.17, 95% CI: 1.37 to 3.46) had a higher risk of testing positive for SARS-CoV-2 in hospital. Using more detailed groupings, medical support staff (RR 8.57, 95% CI: 4.35 to 16.87) and social care workers (RR 2.99, 95% CI: 1.71 to 5.24) had highest risk within the healthcare worker and social and education worker categories, respectively. In general, adjustment for covariates did not substantially change the pattern of occupational differences in risk. Conclusions: Essential workers in health and social care have a higher risk of severe SARS-CoV-2 infection. These findings underscore the need for national and organisational policies and practices that protect and support workers with elevated risk of SARS-CoV-2 infection.

Ethnic and socioeconomic differences in SARS-CoV2 infection in the UK Biobank cohort study (preprint)

Background Understanding of the role of ethnicity and socioeconomic position in the risk of developing SARS-CoV-2 infection is limited. We investigated this in the UK Biobank study. Methods The UK Biobank study recruited 40-70 year olds in 2006-2010 from the general population, collecting information about self-defined ethnicity and socioeconomic variables (including area-level socioeconomic deprivation and educational attainment). SARS-CoV-2 test results from Public Health England were linked to baseline UK Biobank data. Poisson regression with robust standard errors was used to assess risk ratios (RRs) between the exposures and dichotomous variables for: being tested, having a positive test and testing positive in hospital. We also investigated whether ethnicity and socioeconomic position were associated with having a positive test amongst those tested. We adjusted for covariates including age, sex, social variables (including healthcare work and household size), behavioural risk factors and baseline health. Results Among 428,225 participants in England, 1,474 had been tested and 669 tested positive between 16 March and 13 April 2020. Black, south Asian and white Irish people were more likely to have confirmed infection (RR 4.01 (95%CI 2.92-5.12); RR 2.11 (95%CI 1.43-3.10); and RR 1.60 (95% CI 1.08-2.38) respectively) and were more likely to be hospital cases compared to the White British. While they were more likely to be tested, they were also more likely to test positive. Adjustment for baseline health and behavioural risk factors led to little change, with only modest attenuation when accounting for socioeconomic variables. Socioeconomic deprivation and having no qualifications were consistently associated with a higher risk of confirmed infection (RR 2.26 (95%CI 1.76-2.90); and RR 1.91 (95%CI 1.53-2.38) respectively). Conclusions Some minority ethnic groups have a higher risk of confirmed SARS-CoV-2 infection in the UK Biobank study which was not accounted for by differences in socioeconomic conditions, measured baseline health or behavioural risk factors. An urgent response to addressing these elevated risks is required.