Home working and social and mental wellbeing at different stages of the COVID-19 pandemic in the UK: Evidence from 7 longitudinal population surveys.

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.

Health Behaviors and Mental Health during the COVID-19 Pandemic: Evidence from the English Longitudinal Study of Aging.

Stay-at-home and lockdown measures during the COVID-19 pandemic had an impact on health-related behaviors which in turn posed a risk to mental health, particularly among older people. In this study, we investigated how changes to health behaviors (physical activity, sleeping, eating, and drinking) impacted mental health (depression, quality of life, and life satisfaction) during and beyond the initial phase of the COVID-19 lockdown. Using data from Wave 9 (2018/19) and two COVID-19 sub-studies (June/July 2020; November/December 2020) of the English Longitudinal Study of Ageing (N = 4989), we found that health behaviors changes during lockdown were associated with poorer mental health in June/July 2020. However, in November/December 2020, higher depression, lower quality of life, and lower life satisfaction were more likely only among respondents who reported less physical activity, eating more, changes in sleep patterns, and drinking more alcohol. Public health programs should support healthy behaviors as we emerge from the pandemic.

COVID-19 precautionary behaviors and vaccine acceptance among older individuals: The role of close kin.

The family plays a central role in shaping health behaviors of its members through social control and support mechanisms. We investigate whether and to what extent close kin (i.e., partner and children) matter for older people in taking on precautionary behaviors (e.g., wearing a mask) and vaccination during the COVID-19 pandemic in Europe. Drawing on data from the Survey of Health, Ageing and Retirement in Europe (SHARE), we combine its Corona Surveys (June to September 2020 and June to August 2021) with pre-COVID information (October 2019 to March 2020). We find that having close kin (especially a partner) is associated with a higher probability of both adopting precautionary behaviors and accepting a COVID-19 vaccine. Results are robust to controlling for other potential drivers of precautionary behaviors and vaccine acceptance and to accounting for coresidence with kin. Our findings suggest that policymakers and practitioners may differently address kinless individuals when promoting public policy measures.

Changes in Grandparental Childcare During the Pandemic and Mental Health: Evidence From England.

OBJECTIVES: Policies aiming at reducing rates of hospitalization and death from coronavirus disease 2019 (COVID-19) encouraged older people to reduce physical interactions. In England, until July 2021, 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 associations between changes in grandchild care provision during the first 8/9 months of the pandemic and grandparents' mental health. METHODS: Using prepandemic data from Wave 9 (2018/2019) and the second COVID-19 substudy (November/December 2020) of the English Longitudinal Study of Ageing, we first describe changes in grandchild care provision during the pandemic to then investigate, using regression models, associations between changes in grandchild care provision and mental health (depression, quality of life, life satisfaction), while controlling for prepandemic levels of the outcome variables. RESULTS: About 10% of grandparents stopped looking after grandchildren altogether during the first 9 months of the pandemic, with 22% reporting an overall decrease in the amount of grandchild care provided. 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 prepandemic health. DISCUSSION: While 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.

Antibody levels following vaccination against SARS-CoV-2: associations with post-vaccination infection and risk factors in two UK longitudinal studies.

Background: Severe acute respiratory syndrome coronavirus 2 (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. Higher levels of SARS-CoV-2 anti-Spike antibodies are known to be associated with increased protection against future SARS-CoV-2 infection. However, variation in antibody levels and risk factors for lower antibody levels following each round of SARS-CoV-2 vaccination have not been explored across a wide range of socio-demographic, SARS-CoV-2 infection and vaccination, and health factors within population-based cohorts. Methods: Samples were collected from 9361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies and tested for SARS-CoV-2 antibodies. Cross-sectional sampling was undertaken jointly in April-May 2021 (TwinsUK, N=4256; ALSPAC, N=4622), and in TwinsUK only in November 2021-January 2022 (N=3575). Variation in antibody levels after first, second, and third SARS-CoV-2 vaccination with health, socio-demographic, SARS-CoV-2 infection, and SARS-CoV-2 vaccination variables were analysed. Using multivariable logistic regression models, 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. Results: Within TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had threefold greater odds of SARS-CoV-2 infection over the next 6-9 months (OR = 2.9, 95% CI: 1.4, 6.0), 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 (two- to fourfold) 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. Conclusions: 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. Funding: Antibody testing was funded by UK Health Security Agency. The National Core Studies program is funded by COVID-19 Longitudinal Health and Wellbeing - National Core Study (LHW-NCS) HMT/UKRI/MRC ([MC_PC_20030] and [MC_PC_20059]). Related funding was also provided by the NIHR 606 (CONVALESCENCE grant [COV-LT-0009]). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. The UK Medical Research Council and Wellcome (Grant ref: [217065/Z/19/Z]) and the University of Bristol provide core support for ALSPAC.

Vaccination against the virus that causes COVID-19 triggers the body to produce antibodies that help fight future infections. But some people generate more antibodies after vaccination than others. People with lower levels of antibodies are more likely to get COVID-19 in the future. Identifying people with low antibody levels after COVID-19 vaccination is important. It could help decide who receives priority for future vaccination. Previous studies show that people with certain health conditions produce fewer antibodies after one or two doses of a COVID-19 vaccine. For example, people with weakened immune systems. Now that third booster doses are available, it is vital to determine if they increase antibody levels for those most at risk of severe COVID-19. Cheetham et al. show that a third booster dose of a COVID-19 vaccine boosts antibodies to high levels in 90% of individuals, including those at increased risk. In the experiments, Cheetham et al. measured antibodies against the virus that causes COVID-19 in 9,361 individuals participating in two large long-term health studies in the United Kingdom. The experiments found that UK individuals advised to shield from the virus because they were at increased risk of complications had lower levels of antibodies after one or two vaccine doses than individuals without such risk factors. This difference was also seen after a third booster dose, but overall antibody levels had large increases. People who received the Oxford/AstraZeneca vaccine as their first dose also had lower antibody levels after one or two doses than those who received the Pfizer/BioNTech vaccine first. Positively, this difference in antibody levels was no longer seen after a third booster dose. Individuals with lower antibody levels after their first dose were also more likely to have a case of COVID-19 in the following months. Antibody levels were high in most individuals after the third dose. The results may help governments and public health officials identify individuals who may need extra protection after the first two vaccine doses. They also support current policies promoting booster doses of the vaccine and may support prioritizing booster doses for those at the highest risk from COVID-19 in future vaccination campaigns.

Inequalities in healthcare disruptions during the COVID-19 pandemic: evidence from 12 UK population-based longitudinal studies.

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; I2=54%), older persons (eg, OR 1.39; 95% CI 1.13 to 1.72; I2=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; I2=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; I2=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.

The UK Coronavirus Job Retention Scheme and smoking, alcohol consumption and vaping during the COVID-19 pandemic: evidence from eight longitudinal population surveys.

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.

The UK Coronavirus Job Retention Scheme and diet, physical activity, and sleep during the COVID-19 pandemic: evidence from eight longitudinal population surveys.

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]; I 2 = 59%) and did not differ overall with respect to low fruit and vegetable consumption or atypical sleep, although findings for sleep were heterogenous (I 2 = 85%). In stratified analyses, furlough was associated with lower fruit and vegetable consumption among males (RR = 1.11; [1.01-1.22]; I 2 = 0%) but not females (RR = 0.84; [0.68-1.04]; I 2 = 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.

Mental and social wellbeing and the UK coronavirus job retention scheme: Evidence from nine longitudinal studies.

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 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. 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 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. CONCLUSIONS: 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.

Long COVID burden and risk factors in 10 UK longitudinal studies and electronic health records.

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.

Psychological Distress Before and During the COVID-19 Pandemic Among Adults in the United Kingdom Based on Coordinated Analyses of 11 Longitudinal Studies.

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.

The impact of shielding during the COVID-19 pandemic on mental health: evidence from the English Longitudinal Study of Ageing.

BACKGROUND: During 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. AIMS: To understand the extent to which shielding contributes to poorer mental health. METHOD: We 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. RESULTS: By 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 (ß = -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. CONCLUSIONS: Shielding 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.

Pre-pandemic mental health and disruptions to healthcare, economic and housing outcomes during the COVID-19 pandemic: evidence from 12 UK longitudinal studies.

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.

Changes in health and social well-being in the COVID-19 clinically vulnerable older English population during the pandemic.

BACKGROUND: People with specific health profiles and diseases (such as diabetes, lung and heart conditions) have been classified as 'clinically vulnerable' (CV) to COVID-19, that is, at higher risk of severe illness and mortality from COVID-19, and were targeted for shielding. However, there is as yet little evidence on how the pandemic and shielding impacted the health and social well-being of CV older people. METHODS: We used data from wave 9 (2018/2019) and the first COVID-19 substudy (June/July 2020) of the English Longitudinal Study of Ageing. Using logistic and linear regression models, we investigated associations between being CV and health and social well-being during the pandemic, while controlling for prepandemic levels of the outcome variables. We also explored the interactions between CV and age group (50s, 60s, 70s, 80+), and between CV and shielding. RESULTS: CV people were more likely to report worse health and social well-being outcomes during the pandemic, even taking into account prepandemic differences. However, changes in health were not uniform across different age groups, and CV respondents were generally at greater risks of deterioration in health and social well-being compared with those not CV in the same age group. CV respondents who were shielding reported worse outcomes compared with those not CV and not shielding. CONCLUSIONS: While policies focusing on shielding CV older people reduce rates of hospitalisation and death from COVID-19, policymakers should also pay attention to understanding and addressing the wider needs of this group if their long-term health and social well-being are not to be compromised.

Mental health and social interactions of older people with physical disabilities in England during the COVID-19 pandemic: a longitudinal cohort study.

BACKGROUND: The COVID-19 pandemic has affected mental health, psychological wellbeing, and social interactions. People with physical disabilities might be particularly likely to be negatively affected, but evidence is scarce. Our aim was to evaluate the emotional and social experience of older people with physical disabilities during the early months of the COVID-19 pandemic in England. METHODS: In this longitudinal cohort study, we analysed data from the English Longitudinal Study of Ageing collected in 2018-19 and June-July, 2020, from participants aged 52 years and older and living in England. Physical disability was defined as impairment in basic and instrumental activities of daily living (ADL) and impaired mobility. Depression, anxiety, loneliness, quality of life, sleep quality, and amount of real-time and written social contact were assessed online or by computer-assisted telephone interviews. Comparisons of experiences during the COVID-19 pandemic of people with and without a physical disability were adjusted statistically for pre-pandemic outcome measures, age, sex, wealth, ethnicity, presence of a spouse or partner, number of people in the household, and chronic pain. All participants with full data available for both surveys were included in the analyses. FINDINGS: Between June 3 and July 26, 2020, 5820 participants responded, 4887 of whom had full data available for both the pre-pandemic measures and the COVID-19 survey and were included in the analysis. During the COVID-19 pandemic, significantly more people with ADL impairment had clinically significant symptoms of depression (odds ratio 1·78 [95% CI 1·44-2·19]; p<0·0001), anxiety (2·23 [1·72-2·89]; p<0·0001), and loneliness (1·52 [1·26-1·84]; p<0·0001) than people without ADL impairment. Significantly more people with ADL impairment also had impaired sleep quality (1·44 [1·20-1·72]; p<0·0001) and poor quality of life than people without ADL impairment. The results were similar when disability was defined by impaired mobility. People with ADL impairment had less frequent real-time contact (0·70 [0·55-0·89]; p=0·0037) and written social contact (0·54 [0·45-0·64]; p<0·0001) with family than people without ADL impairment. Results for social contact were similar when disability was defined by impaired mobility. INTERPRETATION: People with physical disability might be at particular risk for emotional distress, poor quality of life, and low wellbeing during the COVID-19 pandemic, highlighting the need for additional support and targeted mental health services. FUNDING: Economic and Social Research Council/UK Research and Innovation, National Institute on Aging, National Institute for Health Research.