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Background: Home working has increased since the Coronavirus Disease 2019 (COVID-19) pandemic's onset with concerns that it may have adverse health implications. We assessed the association between home working and social and mental wellbeing among the employed population aged 16 to 66 through harmonised analyses of 7 UK longitudinal studies. Methods and findings: We estimated associations between home working and measures of psychological distress, low life satisfaction, poor self-rated health, low social contact, and loneliness across 3 different stages of the pandemic (T1 = April to June 2020 –first lockdown, T2 = July to October 2020 –eased restrictions, T3 = November 2020 to March 2021 –second lockdown) using modified Poisson regression and meta-analyses to pool results across studies. We successively adjusted the model for sociodemographic characteristics (e.g., age, sex), job characteristics (e.g., sector of activity, pre-pandemic home working propensities), and pre-pandemic health. Among respectively 10,367, 11,585, and 12,179 participants at T1, T2, and T3, 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 to 1.08) or T2 (RR = 0.99, 95% CI = 0.88 to 1.11), but a detrimental association was found with psychological distress at T3 (RR = 1.17, 95% CI = 1.05 to 1.30). Study limitations include the fact that pre-pandemic home working propensities were derived from external sources, no information was collected on home working dosage and possible reverse association between change in wellbeing and home working likelihood. Conclusions: No clear evidence of an association between home working and mental wellbeing was found, apart from greater risk of psychological distress during the second lockdown, but differences across subgroups (e.g., by sex or level of education) 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. Jacques Wels and colleagues investigate the relationship between working from home and different indicators of mental and social wellbeing in the UK. Author summary: Why was this study done?: ➢ The number of workers working from home drastically increased during the Coronavirus Disease 2019 (COVID-19) pandemic. ➢ Little is known about the relationship between home working and mental and social wellbeing before and during the pandemic. ➢ As some home working schemes are likely to remain post-pandemic, understanding this association is important. What did the researchers do and find?: ➢ We analysed data from 7 UK-based population surveys to better understand the relationship between working from home (partially or fully) and different indicators of mental and social wellbeing. ➢ We analysed these relationships over 3 time points—i.e., April to June 2020 (T1), July to October 2020 (T2), and November 2020 to March 2021 (T3)—and controlled for sociodemographic (e.g., age, sex, and ethnicity) and job characteristics (e.g., sector of activity, key worker status). ➢ We found that home working was not associated with psychological distress at T1 or T2, but at T3 it was associated with increased psychological distress (relative risk = 1.17, 95% CI = 1.05 to 1.30). No other meaningful associations were found. ➢ We stratified these associations by sex, education level, age, and full-time versus part-time employment and found that home working was associated with greater psychological distress in those with lower than degree level education. What do these findings mean?: ➢ We found no clear evidence of a lasting association between home working, mental health, and social wellbeing which may indicate that, during the pandemic, home working was not detrimental nor beneficial for workers' wellbeing. ➢ Differences across subgroups may exist and specific impacts by sex, age, and education level need to be investigated further. [ABSTRACT FROM AUTHOR]

Background: Employment disruptions can impact smoking and alcohol consumption. During the COVID-19 pandemic, many countries implemented furlough schemes to prevent job loss. We examine how furlough was associated with smoking, vaping and alcohol consumption in the UK.Methods: Data from 27,841 participants in eight UK adult longitudinal surveys were analysed. Participants self-reported employment status and current smoking, current vaping and alcohol consumption (>4 days/week or 5+ drinks per typical occasion) both before and during the early stages of the pandemic (April-July 2020). Risk ratios were estimated within each study using modified Poisson regression, adjusting for a range of potential confounders, including pre-pandemic behaviour. Findings were synthesised using random effects meta-analysis.Results: Compared to stable employment and after adjustment for pre-pandemic characteristics, furlough was not associated with smoking (ARR = 1.05; 95% CI: 0.95-1.16; I2: 10%), vaping (ARR = 0.89; 95% CI: 0.74-1.08; I2: 0%) or drinking (ARR = 1.03; 95% CI: 0.94-1.13; I2: 48%). There were similar findings for no longer being employed, and stable unemployment, though this varied by sex: stable unemployment was associated with smoking for women (ARR = 1.35; 95% CI: 1.00-1.82; I2: 47%) but not men (0.84; 95% CI: 0.67-1.05; I2: 0%). No longer being employed was associated with vaping among women (ARR = 2.74; 95% CI: 1.59-4.72; I2: 0%) but not men (ARR = 1.25; 95% CI: 0.83-1.87; I2: 0%).Conclusions: We found no clear evidence of furlough or unemployment having adverse impacts on smoking, vaping or drinking behaviours during the early stages of the COVID-19 pandemic in the UK. Differences in risk compared to those who remained employed were largely explained by pre-pandemic characteristics. [ABSTRACT FROM AUTHOR]

The frequency of, and risk factors for, long COVID are unclear among community-based individuals with a history of COVID-19. To elucidate the burden and possible causes of long COVID in the community, we coordinated analyses of survey data from 6907 individuals with self-reported COVID-19 from 10 UK longitudinal study (LS) samples and 1.1 million individuals with COVID-19 diagnostic codes in electronic healthcare records (EHR) collected by spring 2021. Proportions of presumed COVID-19 cases in LS reporting any symptoms for 12+ weeks ranged from 7.8% and 17% (with 1.2 to 4.8% reporting debilitating symptoms). Increasing age, female sex, white ethnicity, poor pre-pandemic general and mental health, overweight/obesity, and asthma were associated with prolonged symptoms in both LS and EHR data, but findings for other factors, such as cardio-metabolic parameters, were inconclusive. Current understanding of Long COVID is limited, in part, due to lack of evidence from population-representative studies. Here, the authors analyse data from ten UK population-based studies and electronic health records, and find wide variation in the frequency of Long COVID between studies but some consistent risk factors. [ABSTRACT FROM AUTHOR]

Background: In March 2020, the UK implemented the Coronavirus Job Retention Scheme (furlough) to minimise job losses. Our aim was to investigate associations between furlough and diet, physical activity, and sleep during the early stages of the COVID-19 pandemic. Methods: We analysed data on 25,092 participants aged 16-66 years from eight UK longitudinal studies. Changes in employment, including being furloughed, were based on employment status before and during the first lockdown. Health behaviours included fruit and vegetable consumption, physical activity, and sleep. Study-specific estimates obtained using modified Poisson regression, adjusting for socio-demographic characteristics and pre-pandemic health and health behaviours, were statistically pooled using random effects meta-analysis. Associations were also stratified by sex, age, and education. Results: Across studies, between 8 and 25% of participants were furloughed. Compared to those who remained working, furloughed workers were slightly less likely to be physically inactive (RR = 0.85; [95% CI 0.75-0.97]; I² = 59%) and did not differ overall with respect to low fruit and vegetable consumption or atypical sleep, although findings for sleep were heterogenous (I² = 85%). In stratified analyses, furlough was associated with lower fruit and vegetable consumption among males (RR = 1.11; [1.01-1.22]; I² = 0%) but not females (RR = 0.84; [0.68-1.04]; I² = 65%). Considering changes in quantity, furloughed workers were more likely than those who remained working to report increases in fruit and vegetable consumption, exercise, and hours of sleep. Conclusions: Those furloughed exhibited similar health behaviours to those who remained in employment during the initial stages of the pandemic. There was little evidence to suggest that adoption of such social protection policies in the post-pandemic recovery period and during future economic crises had adverse effects on population health behaviours. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has disrupted lives and livelihoods, and people already experiencing mental ill health may have been especially vulnerable.Aims: Quantify mental health inequalities in disruptions to healthcare, economic activity and housing.Method: We examined data from 59 482 participants in 12 UK longitudinal studies with data collected before and during the COVID-19 pandemic. Within each study, we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to healthcare (medication access, procedures or appointments), economic activity (employment, income or working hours) and housing (change of address or household composition). Estimates were pooled across studies.Results: Across the analysed data-sets, 28% to 77% of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. We found 1 s.d. higher pre-pandemic psychological distress was associated with (a) increased odds of any healthcare disruptions (odds ratio (OR) 1.30, 95% CI 1.20-1.40), with fully adjusted odds ratios ranging from 1.24 (95% CI 1.09-1.41) for disruption to procedures to 1.33 (95% CI 1.20-1.49) for disruptions to prescriptions or medication access; (b) loss of employment (odds ratio 1.13, 95% CI 1.06-1.21) and income (OR 1.12, 95% CI 1.06 -1.19), and reductions in working hours/furlough (odds ratio 1.05, 95% CI 1.00-1.09) and (c) increased likelihood of experiencing a disruption in at least two domains (OR 1.25, 95% CI 1.18-1.32) or in one domain (OR 1.11, 95% CI 1.07-1.16), relative to no disruption. There were no associations with housing disruptions (OR 1.00, 95% CI 0.97-1.03).Conclusions: People experiencing psychological distress pre-pandemic were more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening mental health inequalities. [ABSTRACT FROM AUTHOR]

Background: We aimed to estimate the causal effect of health conditions and risk factors on social and socioeconomic outcomes in UK Biobank. Evidence on socioeconomic impacts is important to understand because it can help governments, policy makers and decision makers allocate resources efficiently and effectively.Methods: We used Mendelian randomization to estimate the causal effects of eight health conditions (asthma, breast cancer, coronary heart disease, depression, eczema, migraine, osteoarthritis, type 2 diabetes) and five health risk factors [alcohol intake, body mass index (BMI), cholesterol, systolic blood pressure, smoking] on 19 social and socioeconomic outcomes in 336 997 men and women of White British ancestry in UK Biobank, aged between 39 and 72 years. Outcomes included annual household income, employment, deprivation [measured by the Townsend deprivation index (TDI)], degree-level education, happiness, loneliness and 13 other social and socioeconomic outcomes.Results: Results suggested that BMI, smoking and alcohol intake affect many socioeconomic outcomes. For example, smoking was estimated to reduce household income [mean difference = -£22 838, 95% confidence interval (CI): -£31 354 to -£14 321] and the chance of owning accommodation [absolute percentage change (APC) = -20.8%, 95% CI: -28.2% to -13.4%], of being satisfied with health (APC = -35.4%, 95% CI: -51.2% to -19.5%) and of obtaining a university degree (APC = -65.9%, 95% CI: -81.4% to -50.4%), while also increasing deprivation (mean difference in TDI = 1.73, 95% CI: 1.02 to 2.44, approximately 216% of a decile of TDI). There was evidence that asthma decreased household income, the chance of obtaining a university degree and the chance of cohabiting, and migraine reduced the chance of having a weekly leisure or social activity, especially in men. For other associations, estimates were null.Conclusions: Higher BMI, alcohol intake and smoking were all estimated to adversely affect multiple social and socioeconomic outcomes. Effects were not detected between health conditions and socioeconomic outcomes using Mendelian randomization, with the exceptions of depression, asthma and migraines. This may reflect true null associations, selection bias given the relative health and age of participants in UK Biobank, and/or lack of power to detect effects. [ABSTRACT FROM AUTHOR]

Childhood poverty is associated with poorer adolescent health and health behaviours, but the importance of the timing of poverty remains unclear. There may be critical or sensitive periods in early life or early adolescence, or poverty may have cumulative effects throughout childhood. Understanding when poverty is most important can support efficient timing of interventions to raise family income or buffer against the effects of low income, but answers may vary across social contexts. The US and the UK are a useful comparison with similar liberal approaches to cash transfers, but very different approaches to healthcare provision. Utilising data from large population studies in the US (n = 9408; born 1979–1996) and UK (n = 1204; born 1991–1997), this study employs a structured life course approach to compare competing hypotheses about the importance of the timing or pattern of childhood exposure to poverty in predicting adolescent health limitations, symptoms of psychiatric distress, and smoking at age 16 (age 15/16 in US). Household income histories identified experience of poverty (measured as <60% of the national median equivalised income for a given year) in early life (ages 0–5), mid-childhood (ages 6–10) and early adolescence (ages 11–15). The Bayesian Information Criterion (BIC) compared fit across models with variables representing different life course patterns of exposure to poverty. Adolescent distress was not associated with poverty in either country. In both countries, however, variables representing cumulative or persistent experiences of poverty exhibited optimal fit of all poverty exposure variables in predicting adolescent smoking and health limitations. There was also evidence of an early life sensitive period for smoking in the US. Poverty was more persistent in the US, but associations between poverty and outcomes were consistent across countries. Although poverty can have cumulative effects on health and behaviour, early interventions may offer the best long-term protection. [ABSTRACT FROM AUTHOR]

B Correction: BMC Med 20, 147 (2022) b B https://doi.org/10.1186/s12916-022-02343-y b After publication, it came to the authors' attention that 143 individuals from ALSPAC G0 and 24 in ALSPAC G1 were incorrectly coded as "unemployed" pre-pandemic in our manuscript [[1]]. Reference 1 Wielgoszewska B. The UK Coronavirus Job Retention Scheme and diet, physical activity, and sleep during the COVID-19 pandemic: evidence from eight longitudinal population surveys. [Extracted from the article]

Transitions into work and family roles have become increasingly delayed as participation in tertiary education widens. Such transitions may have adverse or beneficial effects on health behaviours such as smoking and drinking (alcohol). Role socialisation effects may reduce smoking or drinking, but clustering of transitions may lead to role overload, weakening or reversing any role socialisation effects. Effects of transitions were examined in three UK cohorts: the 1958 National Child Development Study, the 1970 British Birth Cohort Study, and the West of Scotland: Twenty-07 Youth Cohort (from around Glasgow, growing up in the same time period as the 1970 cohort). Latent class analysis was employed to identify heterogeneous patterns of transition timing for leaving education, entering employment, starting cohabitation, having a first child, and leaving the parental home. Propensity weighting was then used to estimate causal effects of transition patterns (relative to tertiary education) on smoking and heavy drinking in early adulthood (ages 22–26), adjusting for background confounders (gender, parental socioeconomic position, family structure, parental and adolescent health behaviours, adolescent distress and school performance). Three groups made early (age 16) transitions from education to employment and then either delayed other transitions, made other transitions quickly, or staggered transitions with cohabitation beginning around ages 19–21; a fourth group transitioned from education to employment around ages 17–18. Compared to those in tertiary education with similar background characteristics, those in these groups generally had higher levels of smoking, especially where transitions were more clustered, but less heavy drinking (except those who delayed other transitions after moving into employment). Results partially supported role socialisation effects for drinking, and role overload effects for smoking. Wider participation in tertiary education could have helped reduce smoking levels in these cohorts, but might also have increased risk for heavy drinking. [ABSTRACT FROM AUTHOR]

Background and Aims If socio-economic disadvantage is associated with more adolescent smoking, but less participation in tertiary education, and smoking and tertiary education are both associated with heavier drinking, these may represent opposing pathways to heavy drinking. This paper examines contextual variation in the magnitude and direction of these associations. Design Comparing cohort studies. Setting United Kingdom. Participants Participants were from the 1958 National Child Development Study (NCDS58; n = 15 672), the British birth cohort study (BCS70; n = 12 735) and the West of Scotland Twenty-07 1970s cohort (T07; n = 1515). Measurements Participants self-reported daily smoking and weekly drinking in adolescence (age 16 years) and heavy drinking (> 14/21 units in past week) in early adulthood (ages 22-26 years). Parental occupational class (manual versus non-manual) indicated socio-economic background. Education beyond age 18 was coded as tertiary. Models were adjusted for parental smoking and drinking, family structure and adolescent psychiatric distress. Findings Respondents from a manual class were more likely to smoke and less likely to enter tertiary education (e.g. in NCDS58, probit coefficients were 0.201 and -0.765, respectively; P < 0.001 for both) than respondents from a non-manual class. Adolescent smokers were more likely to drink weekly in adolescence (0.346; P < 0.001) and more likely to drink heavily in early adulthood (0.178; P < 0.001) than adolescent non-smokers. Respondents who participated in tertiary education were more likely to drink heavily in early adulthood (0.110 for males, 0.182 for females; P < 0.001 for both) than respondents with no tertiary education. With some variation in magnitude, these associations were consistent across all three cohorts. Conclusions In Britain, young adults are more likely to drink heavily both if they smoke and participate in tertiary education (college and university) despite socio-economic background being associated in opposite directions with these risk factors. [ABSTRACT FROM AUTHOR]

Objective Smoking usually develops in adolescence and is patterned by socioeconomic position (SEP). We examined whether early adolescent smoking development and associations with SEP have changed over time in a population with well-developed tobacco control policies. We additionally investigated the relative importance of socioeconomic inequalities at different stages of smoking development. Methods An annual UK rotating panel survey including data from 5122 adolescents (51 % male) aged 11-15 years between 1994 and 2008. Rates of smoking initiation, progression to occasional smoking (experimentation), progression to daily smoking (escalation), and quitting were examined using discrete-time event history analysis. Results Initiation, experimentation and escalation rates declined over the study period while quitting rates increased. Decreases in initiation were concentrated among older adolescents and decreases in escalation among those who spent a year or two as occasional smokers. Socioeconomic disadvantage was associated with higher rates of initiation and escalation, with similar findings across SEP measures. Inequalities in initiation were stronger at younger ages. There was less evidence of associations between SEP and quitting or experimentation. Inequalities in escalation remained constant over time, while inequalities in initiation widened before narrowing. Further modelling suggested that differential initiation rates contributed more to inequalities in daily smoking at age 15 than did differential escalation. Conclusions Increasing tobacco control in the UK is associated with reduced uptake and more quitting in early adolescence, but socioeconomic inequalities remain. Interventions should focus on reducing inequalities in initiation among early adolescents. [ABSTRACT FROM AUTHOR]

Objective To assess the sensitivity and specificity of the Classification of Psoriatic Arthritis (CASPAR) Study Group criteria in early psoriatic arthritis (PsA) and to compare them with the sensitivity and specificity of the Moll and Wright criteria. Methods The CASPAR Study Group criteria were applied to patients with early PsA (<24 months symptom duration) and to control patients with other new-onset inflammatory arthritides. Both groups were naive to all disease-modifying antirheumatic drugs. The gold standard diagnosis was confirmed by the consulting rheumatologist using radiography and magnetic resonance imaging where required. Proportions of patients and control patients meeting the criteria were compared using McNemar's tests. Results We recruited a total of 111 patients with early PsA and 111 control patients with other forms of inflammatory arthritis (82 with rheumatoid arthritis, 13 with undifferentiated arthritis, 9 with spondylarthritis, 4 with inflammatory osteoarthritis, and 3 with crystal arthritis) to the study. The sensitivity of the CASPAR Study Group criteria in classifying early PsA was 87.4% compared to 80.2% for the Moll and Wright criteria. The specificity for both criteria was 99.1%. When considering different cut points for the CASPAR Study Group criteria, the best cut point for classification remained a score of ≥3 as in the original CASPAR Study Group analysis. Considering a score of ≥2 gave a higher sensitivity of 99.1% but resulted in a drop in specificity to 94.6%. Regression analysis determined that psoriasis and rheumatoid factor negativity were the most important features that differentiated PsA, followed by nail psoriasis and current or previous dactylitis. Conclusion The CASPAR Study Group criteria are more sensitive than the Moll and Wright criteria in classifying early PsA. Although their sensitivity for early PsA is lower than that for established disease, the CASPAR Study Group criteria are valid for use as inclusion criteria for trials in early PsA. [ABSTRACT FROM AUTHOR]

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. Data were from 25,670 respondents, aged 17–66, across nine UK longitudinal studies. Furlough and other employment changes were defined using employment status pre-pandemic and during the first lockdown (April–June 2020). 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 mental and social wellbeing, were pooled using meta-analysis. Associations were also stratified by sex, age, education, and household composition. 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 poor self-rated health (ARR = 1.26; 95%CI: 1.05, 1.50). Nevertheless, compared to furloughed workers, those who became unemployed had greater risk of psychological distress (ARR = 1.30; 95%CI: 1.12, 1.52), low life satisfaction (ARR = 1.16; 95%CI: 0.98, 1.38), and loneliness (ARR = 1.67; 95%CI: 1.08, 2.59). Effects were not uniform across all sub-groups. During the early stages of the pandemic, those furloughed had increased risk of poor mental and social wellbeing, but furloughed workers fared better than those who became unemployed, suggesting that furlough may have partly mitigated poorer outcomes. • The relationship between furlough and mental health and wellbeing is not well known. • We use 9 UK studies to assess this relationship at the early stage of the pandemic. • Furlough is associated with a slight decline in mental and social wellbeing. • However, the excess risk is smaller than for those no longer being employed. • Furlough occupies an intermediary position between employment and unemployment. [ABSTRACT FROM AUTHOR]

Background: People who live alone experience greater levels of mental illness; however, it is unclear whether the COVID-19 pandemic had a disproportionately negative impact on this demographic., Objective: To describe the mental health gap between those who live alone and with others in the UK prior to and during the COVID-19 pandemic., Methods: Self-reported psychological distress and life satisfaction in 10 prospective longitudinal population surveys (LPSs) assessed in the nearest pre-pandemic sweep and three periods during the pandemic. Recorded diagnosis of common and severe mental illnesses between March 2018 and January 2022 in electronic healthcare records (EHRs) within the OpenSAFELY-TPP., Findings: In 37 544 LPS participants, pooled models showed greater psychological distress (standardised mean difference (SMD): 0.09 (95% CI: 0.04; 0.14); relative risk: 1.25 (95% CI: 1.12; 1.39)) and lower life satisfaction (SMD: -0.22 (95% CI: -0.30; -0.15)) for those living alone pre-pandemic. This gap did not change during the pandemic. In the EHR analysis of c.16 million records, mental health conditions were more common in those who lived alone (eg, depression 26 (95% CI: 18 to 33) and severe mental illness 58 (95% CI: 54 to 62) more cases more per 100 000). For common mental health disorders, the gap in recorded cases in EHRs narrowed during the pandemic., Conclusions: People living alone have poorer mental health and lower life satisfaction. During the pandemic, this gap in self-reported distress remained; however, there was a narrowing of the gap in service use., Clinical Implications: Greater mental health need and potentially greater barriers to mental healthcare access for those who live alone need to be considered in healthcare planning., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: Evidence on associations between COVID-19 illness and mental health is mixed. We aimed to examine whether COVID-19 is associated with deterioration in mental health while considering pre-pandemic mental health, time since infection, subgroup differences, and confirmation of infection via self-reported test and serology data., Methods: We obtained data from 11 UK longitudinal studies with repeated measures of mental health (psychological distress, depression, anxiety, and life satisfaction; mental health scales were standardised within each study across time) and COVID-19 status between April, 2020, and April, 2021. We included participants with information available on at least one mental health outcome measure and self-reported COVID-19 status (suspected or test-confirmed) during the pandemic, and a subset with serology-confirmed COVID-19. Furthermore, only participants who had available data on a minimum set of covariates, including age, sex, and pre-pandemic mental health were included. We investigated associations between having ever had COVID-19 and mental health outcomes using generalised estimating equations. We examined whether associations varied by age, sex, ethnicity, education, and pre-pandemic mental health, whether the strength of the association varied according to time since infection, and whether associations differed between self-reported versus confirmed (by test or serology) infection., Findings: Between 21 Dec, 2021, and July 11, 2022, we analysed data from 54 442 participants (ranging from a minimum age of 16 years in one study to a maximum category of 90 years and older in another; including 33 200 [61·0%] women and 21 242 [39·0%] men) from 11 longitudinal UK studies. Of 40 819 participants with available ethnicity data, 36 802 (90·2%) were White. Pooled estimates of standardised differences in outcomes suggested associations between COVID-19 and subsequent psychological distress (0·10 [95% CI 0·06 to 0·13], I 2 =42·8%), depression (0·08 [0·05 to 0·10], I 2 =20·8%), anxiety (0·08 [0·05 to 0·10], I 2 =0·0%), and lower life satisfaction (-0·06 [-0·08 to -0·04], I 2 =29·2%). We found no evidence of interactions between COVID-19 and sex, education, ethnicity, or pre-pandemic mental health. Associations did not vary substantially between time since infection of less than 4 weeks, 4-12 weeks, and more than 12 weeks, and were present in all age groups, with some evidence of stronger effects in those aged 50 years and older. Participants who self-reported COVID-19 but had negative serology had worse mental health outcomes for all measures than those without COVID-19 based on serology and self-report. Participants who had positive serology but did not self-report COVID-19 did not show association with mental health outcomes., Interpretation: Self-reporting COVID-19 was longitudinally associated with deterioration in mental health and life satisfaction. Our findings emphasise the need for greater post-infection mental health service provision, given the substantial prevalence of COVID-19 in the UK and worldwide., Funding: UK Medical Research Council and UK National Institute for Health and Care Research., Competing Interests: Declaration of interests SVK is a member of the Scientific Advisory Group on Emergencies subgroup on ethnicity and COVID-19 and is co-chair of the Scottish Government's Ethnicity Reference Group on COVID-19. NC serves on a data safety monitoring board for trials sponsored by AstraZeneca. CJS is an academic lead on KCL Zoe Global COVID symptoms study. KT has been a paid consultant for the CHDI Foundation (member of Statistical Advisory Group) and is a member of the steering group for Living With COVID Recovery study at UCL (unpaid). All other authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Objectives: We investigated associations between multiple sociodemographic characteristics (sex, age, occupational social class, education and ethnicity) and self-reported healthcare disruptions during the early stages of the COVID-19 pandemic., Design: Coordinated analysis of prospective population surveys., Setting: Community-dwelling participants in the UK between April 2020 and January 2021., Participants: Over 68 000 participants from 12 longitudinal studies., Outcomes: Self-reported healthcare disruption to medication access, procedures and appointments., Results: Prevalence of healthcare disruption varied substantially across studies: between 6% and 32% reported any disruption, with 1%-10% experiencing disruptions in medication, 1%-17% experiencing disruption in procedures and 4%-28% experiencing disruption in clinical appointments. Females (OR 1.27; 95% CI 1.15 to 1.40; I 2 =54%), older persons (eg, OR 1.39; 95% CI 1.13 to 1.72; I 2 =77% for 65-75 years vs 45-54 years) and ethnic minorities (excluding white minorities) (OR 1.19; 95% CI 1.05 to 1.35; I 2 =0% vs white) were more likely to report healthcare disruptions. Those in a more disadvantaged social class were also more likely to report healthcare disruptions (eg, OR 1.17; 95% CI 1.08 to 1.27; I 2 =0% for manual/routine vs managerial/professional), but no clear differences were observed by education. We did not find evidence that these associations differed by shielding status., Conclusions: Healthcare disruptions during the COVID-19 pandemic could contribute to the maintenance or widening of existing health inequalities., Competing Interests: Competing interests: SVK is a member of the Scientific Advisory Group on Emergencies subgroup on ethnicity and COVID-19 and is cochair of the Scottish Government’s Ethnicity Reference Group on COVID-19. NC serves on a data safety monitoring board for trials sponsored by AstraZeneca., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Importance: How population mental health has evolved across the COVID-19 pandemic under varied lockdown measures is poorly understood, and the consequences for health inequalities are unclear., Objective: To investigate changes in mental health and sociodemographic inequalities from before and across the first year of the COVID-19 pandemic in 11 longitudinal studies., Design, Setting, and Participants: This cohort study included adult participants from 11 UK longitudinal population-based studies with prepandemic measures of psychological distress. Analyses were coordinated across these studies, and estimates were pooled. Data were collected from 2006 to 2021., Exposures: Trends in the prevalence of poor mental health were assessed in the prepandemic period (time period 0 [TP 0]) and at 3 pandemic TPs: 1, initial lockdown (March to June 2020); 2, easing of restrictions (July to October 2020); and 3, a subsequent lockdown (November 2020 to March 2021). Analyses were stratified by sex, race and ethnicity, education, age, and UK country., Main Outcomes and Measures: Multilevel regression was used to examine changes in psychological distress from the prepandemic period across the first year of the COVID-19 pandemic. Psychological distress was assessed using the 12-item General Health Questionnaire, the Kessler 6, the 9-item Malaise Inventory, the Short Mood and Feelings Questionnaire, the 8-item or 9-item Patient Health Questionnaire, the Hospital Anxiety and Depression Scale, and the Centre for Epidemiological Studies-Depression across different studies., Results: In total, 49 993 adult participants (12 323 [24.6%] aged 55-64 years; 32 741 [61.2%] women; 4960 [8.7%] racial and ethnic minority) were analyzed. Across the 11 studies, mental health deteriorated from prepandemic scores across all 3 pandemic periods, but there was considerable heterogeneity across the study-specific estimated effect sizes (pooled estimate for TP 1: standardized mean difference [SMD], 0.15; 95% CI, 0.06-0.25; TP 2: SMD, 0.18; 95% CI, 0.09-0.27; TP 3: SMD, 0.21; 95% CI, 0.10-0.32). Changes in psychological distress across the pandemic were higher in women (TP 3: SMD, 0.23; 95% CI, 0.11, 0.35) than men (TP 3: SMD, 0.16; 95% CI, 0.06-0.26) and lower in individuals with below-degree level education at TP 3 (SMD, 0.18; 95% CI, 0.06-0.30) compared with those who held degrees (SMD, 0.26; 95% CI, 0.14-0.38). Increased psychological distress was most prominent among adults aged 25 to 34 years (SMD, 0.49; 95% CI, 0.14-0.84) and 35 to 44 years (SMD, 0.35; 95% CI, 0.10-0.60) compared with other age groups. No evidence of changes in distress differing by race and ethnicity or UK country were observed., Conclusions and Relevance: In this study, the substantial deterioration in mental health seen in the UK during the first lockdown did not reverse when lockdown lifted, and a sustained worsening was observed across the pandemic period. Mental health declines have been unequal across the population, with women, those with higher degrees, and those aged 25 to 44 years more affected than other groups.

Background: Smoking contributes significantly to socioeconomic health inequalities. Vaping has captured much interest as a less harmful alternative to smoking, but may be harmful relative to non-smoking. Examining inequalities in vaping by smoking status, may offer insights into potential impacts of vaping on socioeconomic inequalities in health., Methods: Data were from 3291 youth (aged 10-15) and 35,367 adults (aged 16+) from wave 7 (2015-17) of the UK Household Longitudinal Study. In order to adjust for biases that could be introduced by stratifying on smoking status, marginal structural models were used to estimate controlled direct effects of an index of socioeconomic disadvantage (incorporating household education, occupation and income) on vaping by smoking status (among adults and youth), adjusting for relevant confounders and for selection into smoking states. We also estimated controlled direct effects of socioeconomic disadvantage on being an ex-smoker by vaping status (among adult ever-smokers; n = 18,128)., Results: Socioeconomic disadvantage was associated with vaping among never smoking youth (OR for a unit increase in the socioeconomic index: 1.17; 95%: 1.03-1.34), and among ex-smoking adults (OR: 1.17; 95% CI: 1.09-1.26), with little to no association among never smoking (OR: 0.98; 95% CI: 0.91-1.07) and current smoking (OR: 1.00; 95% CI: 0.93-1.07) adults. Socioeconomic disadvantage was also associated with reduced odds of being an ex-smoker among adult ever-smokers, but this association was moderately weaker among those who vaped (OR: 0.88; 95% CI: 0.82-0.95) than those who did not (OR: 0.82; 95% CI: 0.80-0.84; p-value for difference = 0.081)., Conclusions: Inequalities in vaping among never smoking youth and adult ex-smokers, suggest potential to widen health inequalities, while weaker inequalities in smoking cessation among adult vapers indicate e-cigarettes could help narrow inequalities. Further research is needed to understand the balance of these opposing potential impacts, and how any benefits can be maximised whilst protecting the vulnerable.