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BackgroundHome 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.MethodsWe 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.FindingsAmong 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.InterpretationNo 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.FundingNational Core Studies, funded by UKRI, NIHR and the Health and Safety Executive.

SARS-CoV-2 antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. From cross-sectional antibody testing of 9,361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies (jointly in April-May 2021, and TwinsUK only in November 2021-January 2022), we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection and SARS-CoV-2 vaccination variables.Within TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had 3-fold greater odds of SARS-CoV-2 infection over the next six to nine months, compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK “Shielded Patient List” had consistently greater odds (2 to 4-fold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations.These findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies.Lay summaryIn this study, we analysed blood samples from 9,361 participants from two studies in the UK: an adult twin registry, TwinsUK (4,739 individuals); and the Avon Longitudinal Study of Parents and Children, ALSPAC (4,622 individuals). We did this work as part of the UK Government National Core Studies initiative researching COVID-19. We measured blood antibodies which are specific to SARS-CoV-2 (which causes COVID-19). Having a third COVID-19 vaccination boosted antibody levels. More than 90% of people from TwinsUK had levels after third vaccination that were greater than the average level after second vaccination. Importantly, this was the case even in individuals on the UK “Shielded Patient List”. We found that people with lower antibody levels after first vaccination were more likely to report having COVID-19 later on, compared to people with higher antibody levels. People on the UK “Shielded Patient List”, and individuals who reported that they had poorer general health, were more likely to have lower antibody levels after vaccination. In contrast, people who had had a previous COVID-19 infection were more likely to have higher antibody levels following vaccination compared to people without infection. People receiving the Oxford/AstraZeneca rather than the Pfizer BioNTech vaccine had lower antibody levels after one or two vaccinations. However, after a third vaccination, there was no difference in antibody levels between those who had Oxford/AstraZeneca and Pfizer BioNTech vaccines for their first two doses. These findings support having a third COVID-19 vaccination to boost antibodies.

ObjectivesPolicies aiming at reducing rates of hospitalisation and death from COVID-19 encouraged older people to reduce physical interactions. For grandparents in England, this meant that provision of care for grandchildren was allowed only under very limited circumstances. Evidence also suggests that reduced face-to-face interactions took a toll on mental health during the pandemic. This study aims to investigate whether changes in grandchild care provision during the pandemic impacted grandparents’ mental health.MethodsUsing pre-pandemic data from Wave 9 (2018/19) and the second Covid-19 sub-study (November/December 2020) of the English Longitudinal Study of Ageing, we first describe changes in grandparenting since the start of the pandemic to then investigate, using regression models, associations between changes in grandparenting and mental health (depression, quality of life, life satisfaction) during the pandemic, while controlling for pre-pandemic levels of the outcome variables. Results: About 10% of grandparents stopped altogether to look after grandchildren during the pandemic, with 22% reporting an overall decrease in the amount of grandchild care provided and 20% an increase or similar levels. Compared to grandparents who mostly maintained unchanged their grandchild care provision, those who stopped altogether and those who mostly reduced the amount of grandchild care provided were more likely to report poorer mental health, even accounting for pre-pandemic health.DiscussionWhile measures to limit physical contact and shield older people were necessary to reduce the spread of COVID-19, policymakers should acknowledge potential adverse consequences for mental health among grandparents who experienced changes in their roles as grandchild caregivers.

BackgroundDuring the COVID-19 pandemic, older and clinically vulnerable people were instructed to shield or stay at home. Policies restricting social contact and human interaction pose a risk to mental health, but we know very little about the impact of shielding and stay-at-home orders on the mental health of older people.AimsTo understand the extent to which shielding contributes to poorer mental health.MethodWe used longitudinal data from wave 9 (2018/2019) and two COVID-19 sub-studies (June/July 2020; November/December 2020) of the English Longitudinal Study of Ageing, and constructed logistic and linear regression models to investigate associations between patterns of shielding during the pandemic and mental health, controlling for sociodemographic characteristics, pre-pandemic physical and mental health, and social isolation measures.ResultsBy December 2020, 70% of older people were still shielding or staying at home, with 5% shielding throughout the first 9 months of the pandemic. Respondents who shielded experienced worse mental health. Although prior characteristics and lack of social interactions explain some of this association, even controlling for all covariates, those shielding throughout had higher odds of reporting elevated depressive symptoms (odds ratio 1.87, 95% CI 1.22–2.87) and lower quality of life (β = −1.28, 95% CI −2.04 to −0.52) than those who neither shielded nor stayed at home. Shielding was also associated with increased anxiety.ConclusionsShielding seems associated with worse mental health among older people, highlighting the need for policy makers to address the mental health needs of those who shielded, both in the current pandemic and for the future.

BackgroundDisruptions to employment status can impact smoking and alcohol consumption. During the COVID-19 pandemic, the UK implemented a furlough scheme to prevent job loss. We examine how furlough was associated with participants’ smoking, vaping and alcohol consumption behaviours in the early stages of the pandemic.MethodsData were from 27,841 participants in eight UK adult longitudinal surveys. Participants self-reported employment status and current smoking, current vaping and drinking alcohol (>4 days/week or 5+ drinks per typical occasion) both before and during 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. Sub-group analyses were used to identify whether associations differed by gender, age or education.ResultsCompared to stable employment, neither furlough, no longer being employed, nor stable unemployment were associated with smoking, vaping or drinking, following adjustment for pre-pandemic characteristics. However, some sex differences in these associations were observed, with stable unemployment 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%). There was little indication of associations with drinking differing by age, gender or education.ConclusionsWe 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, with differences in risk compared to those who remained employed largely explained by pre-pandemic characteristics.

ImportanceHow population mental health has evolved across the COVID-19 pandemic under varied lockdown measures is poorly understood, with impacts on health inequalities unclear.ObjectiveWe investigated 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 ParticipantsData from 11 UK longitudinal population-based studies with pre-pandemic measures of psychological distress were jointly analysed and estimates pooled. Multi-level regression was used to examine changes in psychological distress from pre-pandemic to during the first year of the COVID-19 pandemic.ExposuresTrends in the prevalence of poor mental health were assessed pre-pandemic (TP0) and at three pandemic time periods: initial lockdown (TP1, Mar-June 20); easing of restrictions (TP2, July-Oct 20); and a subsequent lockdown (TP3, Nov 20-Mar 21). We stratified analyses by sex, ethnicity, education, age, and UK country.Main Outcomes and MeasuresPsychological distress was assessed using the General Health Questionnaire 12 (GHQ-12), Kessler-6, 9-item Malaise Inventory, Short Mood and Feelings Questionnaire (SMFQ), Patient Health Questionnaire-8 and 9 (PHQ-8/9), Hospital Anxiety and Depression Scale (HADS) and Centre for Epidemiological Studies – Depression (CES-D), across different studies.ResultsIn total, 49,993 adult participants (61.2% female; 8.7% Non-White) were analysed. Across the 11 studies, mental health deteriorated from pre-pandemic scores across all three pandemic time periods, but with considerable heterogeneity across the study-specific effect sizes estimated (pooled estimate TP1 Standardised Mean Difference (SMD): 0.15 (95% CI: 0.06, 0.25); TP2 SMD: 0.18 (0.09, 0.27); TP3 SMD: 0.21 (0.10, 0.32)). Changes in psychological distress across the pandemic were higher in females (TP3 SMD: 0.23 (0.11, 0.35)) than males (TP3 SMD: 0.16 (0.06, 0.26)), and lower in below-degree level educated persons at TP3 (SMD: 0.18 (0.06, 0.30)) compared to those who held degrees (SMD: 0.26 (0.14, 0.38)). Increased psychological distress was most prominent amongst adults aged 25-34 and 35-44 years compared to other age groups. We did not find evidence of changes in distress differing by ethnicity or UK country.Conclusions and RelevanceThe 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. Mental health declines have been unequal across the population, with females, those with higher degrees, and those aged 25-44 years more affected.

The impact of long COVID is increasingly recognised, but risk factors are poorly characterised. We analysed questionnaire data on symptom duration from 10 longitudinal study (LS) samples and electronic healthcare records (EHR) to investigate sociodemographic and health risk factors associated with long COVID, as part of the UK National Core Study for Longitudinal Health and Wellbeing.MethodsAnalysis was conducted on 6,899 adults self-reporting COVID-19 from 45,096 participants of the UK LS, and on 3,327 cases assigned a long COVID code in primary care EHR out of 1,199,812 adults diagnosed with acute COVID-19. In LS, we derived two outcomes: symptoms lasting 4+ weeks and symptoms lasting 12+ weeks. Associations of potential risk factors (age, sex, ethnicity, socioeconomic factors, smoking, general and mental health, overweight/obesity, diabetes, hypertension, hypercholesterolaemia, and asthma) with these two outcomes were assessed, using logistic regression, with meta-analyses of findings presented alongside equivalent results from EHR analyses.ResultsFunctionally limiting long COVID for 12+ weeks affected between 1.2% (age 20), and 4.8% (age 63) of people reporting COVID-19 in LS. The proportion reporting symptoms overall for 12+ weeks ranged from 7.8 (mean age 28) to 17% (mean age 58) and for 4+ weeks 4.2% (age 20) to 33.1% (age 56). Age was associated with a linear increase in long COVID between age 20-70. Being female (LS: OR=1.49; 95%CI:1.24-1.79; EHR: OR=1.51 [1.41-1.61]), poor pre-pandemic mental health (LS: OR=1.46 [1.17-1.83]; EHR: OR=1.57 [1.47-1.68]) and poor general health (LS: OR=1.62 [1.25-2.09]; EHR: OR=1.26; [1.18-1.35]) were associated with higher risk of long COVID. Individuals with asthma also had higher risk (LS: OR=1.32 [1.07-1.62]; EHR: OR=1.56 [1.46-1.67]), as did those categorised as overweight or obese (LS: OR=1.25 [1.01-1.55]; EHR: OR=1.31 [1.21-1.42]) though associations for symptoms lasting 12+ weeks were less pronounced. Non-white ethnic minority groups had lower 4+ week symptom risk (LS: OR=0.32 [0.22-0.47]), a finding consistent in EHR. Associations were not observed for other risk factors. Few participants in the studies had been admitted to hospital (0.8-5.2%).ConclusionsLong COVID is clearly distributed differentially according to several sociodemographic and pre-existing health factors. Establishing which of these risk factors are causal and predisposing is necessary to further inform strategies for preventing and treating long COVID.

BackgroundHealth systems worldwide have faced major disruptions due to COVID-19 which could exacerbate health inequalities. The UK National Health Service (NHS) provides free healthcare and prioritises equity of delivery, but the pandemic may be hindering the achievement of these goals. We investigated associations between multiple social characteristics (sex, age, occupational social class, education and ethnicity) and self-reported healthcare disruptions in over 65,000 participants across twelve UK longitudinal studies.MethodsParticipants reported disruptions from March 2020 up to late January 2021. Associations between social characteristics and three types of self-reported healthcare disruption (medication access, procedures, appointments) and a composite of any of these were assessed in logistic regression models, adjusting for age, sex and ethnicity where relevant. Random-effects meta-analysis was conducted to obtain pooled estimates.ResultsPrevalence of disruption varied across studies; between 6.4% (TwinsUK) and 31.8 % (Understanding Society) of study participants reported any disruption. Females (Odd Ratio (OR): 1.27 [95%CI: 1.15,1.40]; I2=53%), older persons (e.g. OR: 1.39 [1.13,1.72]; I2=77% for 65-75y vs 45-54y), and Ethnic minorities (excluding White minorities) (OR: 1.19 [1.05,1.35]; I2=0% vs White) were more likely to report healthcare disruptions. Those in a more disadvantaged social class (e.g. OR: 1.17 [1.08, 1.27]; I2=0% for manual/routine vs managerial/professional) were also more likely to report healthcare disruptions, but no clear differences were observed by education levels.ConclusionThe COVID-19 pandemic has led to unequal healthcare disruptions, which, if unaddressed, could contribute to the maintenance or widening of existing health inequalities.

BackgroundIn March 2020 the UK implemented the Coronavirus Job Retention Scheme (furlough) to minimize 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.MethodsWe analysed data from 25,092 participants aged 16 to 66 years from eight UK longitudinal studies. Changes in employment (including being furloughed) were defined by comparing employment status pre- and during the first lockdown. Health behaviours included fruit and vegetable consumption, physical activity, and sleeping patterns. 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.ResultsAcross 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, [0.75-0.97], I2=59%) and did not differ in diet and sleep behaviours, although findings for sleep were heterogenous (I2=85%). In stratified analyses, furlough was associated with low fruit and vegetable consumption among males (RR=1.11; 95%CI: 1.01-1.22; I2: 0%) but not females (RR=0.84; 95%CI: 0.68-1.04; I2: 65%). Considering change in these health behaviours, furloughed workers were more likely than those who remained working to report increased fruit and vegetable consumption, exercise, and hours of sleep.ConclusionsThose furloughed exhibited broadly similar levels of health behaviours to those who remained in employment during the initial stages of the pandemic. There was little evidence to suggest that such social protection policies if used in the post-pandemic recovery period and during future economic crises would have adverse impacts on population health behaviours.

Background The COVID-19 pandemic and its associated virus suppression measures have disrupted lives and livelihoods, potentially exacerbating inequalities. People already experiencing mental ill-health may have been especially vulnerable to disruptions. Aim Investigate associations between pre-pandemic psychological distress and disruptions during the pandemic to (1) healthcare, economic activity, and housing, (2) cumulative disruptions and 3) whether these differ by age, sex, ethnicity or education. Methods Data were from 59,482 participants in 12 UK longitudinal adult population surveys with data collected both prior to and during the COVID-19 pandemic. Participants self-reported disruptions since the start of the pandemic to: healthcare (medication access, procedures, or appointments); economic activity (negative changes in employment, income or working hours); and housing (change of address or household composition). Logistic regression models were used within each study to estimate associations between pre-pandemic psychological distress scores and disruption outcomes. Findings were synthesised using a random effects meta-analysis with restricted maximum likelihood. Results Between one to two-thirds of study participants experienced at least one disruption during the pandemic, with 2.3-33.2% experiencing disruptions in 2 or more of the 3 domains examined. One standard deviation higher pre-pandemic psychological distress was associated with: (i) increased odds of any healthcare disruptions (OR=1.30; 95% CI: 1.20 to 1.40) with fully adjusted ORs ranging from 1.33 [1.20 to 1.49] for disruptions to prescriptions or medication access and 1.24 [1.09 to 1.41] for disruption to procedures; (ii) loss of employment (OR=1.13 [1.06 to 1.21]) and income (OR=1.12 [1.06 to 1.19]) and reductions in working hours/furlough (OR=1.05 [1.00 to 1.09]); (iii) no associations with housing disruptions (OR=1.00 [0.97 to 1.03]); and (iv) increased likelihood of experiencing a disruption in at least two domains (OR=1.25 [1.18 to 1.32]) or in one domain (OR=1.11 [1.07 to 1.16]) relative to experiencing no disruption. We did not find evidence of these associations differing by sex, ethnicity, education level, or age. Conclusion Those suffering from psychological distress before the pandemic were more likely to experience healthcare disruptions, economic disruptions related to unemployment and loss of income, and to clusters of disruptions across multiple domains during the pandemic. Considering mental ill-health was already unequally distributed in the UK population, the pandemic may exacerbate existing mental health inequalities. Individuals with poor mental health may need additional support to manage these pandemic-associated disruptions.