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.

Mental health and well-being during the second wave of COVID-19: longitudinal analyses of the UK COVID-19 Mental Health and Wellbeing study (UK COVID-MH)

BackgroundWaves 1 to 3 (March 2020 to May 2020) of the UK COVID-19 Mental Health and Wellbeing study suggested an improvement in some indicators of mental health across the first 6 weeks of the UK lockdown;however, suicidal ideation increased.AimsTo report the prevalence of mental health and well-being of adults in the UK from March/April 2020 to February 2021.MethodQuota sampling was employed at wave 1 (March/April 2020), and online surveys were conducted at seven time points. Primary analyses cover waves 4 (May/June 2020), 5 (July/August 2020), 6 (October 2020) and 7 (February 2021), including a period of increased restrictions in the UK. Mental health indicators were suicidal ideation, self-harm, suicide attempt, depression, anxiety, defeat, entrapment, loneliness and well-being.ResultsA total of 2691 (87.5% of wave 1) individuals participated in at least one survey between waves 4 and 7. Depressive symptoms and loneliness increased from October 2020 to February 2021. Defeat and entrapment increased from July/August 2020 to October 2020, and remained elevated in February 2021. Well-being decreased from July/August 2020 to October 2020. Anxiety symptoms and suicidal ideation did not change. Young adults, women, those who were socially disadvantaged and those with a pre-existing mental health condition reported worse mental health.ConclusionsThe mental health and well-being of the UK population deteriorated from July/August 2020 to October 2020 and February 2021, which coincided with the second wave of COVID-19. Suicidal thoughts did not decrease significantly, suggesting a need for continued vigilance as we recover from the pandemic.

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 association between a lifestyle score, socioeconomic status, and COVID-19 outcomes within the UK Biobank cohort.

BACKGROUND: Infection with SARS-CoV-2 virus (COVID-19) impacts disadvantaged groups most. Lifestyle factors are also associated with adverse COVID-19 outcomes. To inform COVID-19 policy and interventions, we explored effect modification of socioeconomic-status (SES) on associations between lifestyle and COVID-19 outcomes. METHODS: Using data from UK-Biobank, a large prospective cohort of 502,536 participants aged 37-73 years recruited between 2006 and 2010, we assigned participants a lifestyle score comprising nine factors. Poisson regression models with penalised splines were used to analyse associations between lifestyle score, deprivation (Townsend), and COVID-19 mortality and severe COVID-19. Associations between each exposure and outcome were examined independently before participants were dichotomised by deprivation to examine exposures jointly. Models were adjusted for sociodemographic/health factors. RESULTS: Of 343,850 participants (mean age > 60 years) with complete data, 707 (0.21%) died from COVID-19 and 2506 (0.76%) had severe COVID-19. There was evidence of a nonlinear association between lifestyle score and COVID-19 mortality but limited evidence for nonlinearity between lifestyle score and severe COVID-19 and between deprivation and COVID-19 outcomes. Compared with low deprivation, participants in the high deprivation group had higher risk of COVID-19 outcomes across the lifestyle score. There was evidence for an additive interaction between lifestyle score and deprivation. Compared with participants with the healthiest lifestyle score in the low deprivation group, COVID-19 mortality risk ratios (95% CIs) for those with less healthy scores in low versus high deprivation groups were 5.09 (1.39-25.20) and 9.60 (4.70-21.44), respectively. Equivalent figures for severe COVID-19 were 5.17 (2.46-12.01) and 6.02 (4.72-7.71). Alternative SES measures produced similar results. CONCLUSIONS: Unhealthy lifestyles are associated with higher risk of adverse COVID-19, but risks are highest in the most disadvantaged, suggesting an additive influence between SES and lifestyle. COVID-19 policy and interventions should consider both lifestyle and SES. The greatest public health benefit from lifestyle focussed COVID-19 policy and interventions is likely to be seen when greatest support for healthy living is provided to the most disadvantaged groups.

Comparing population-level mental health of UK workers before and during the COVID-19 pandemic: a longitudinal study using Understanding Society.

OBJECTIVES: The COVID-19 pandemic has substantially affected workers' mental health. We investigated changes in UK workers' mental health by industry, socioeconomic class and occupation and differential effects by UK country of residence, gender and age. METHODS: We used representative Understanding Society data from 6474 adults (41 207 observations) in paid employment who participated in pre-pandemic (2017-2020) and at least one COVID-19 survey. The outcome was General Health Questionnaire-12 (GHQ-12) caseness (score: ≥4). Exposures were industry, socioeconomic class and occupation and are examined separately. Mixed-effects logistic regression was used to estimate relative (OR) and absolute (%) increases in distress before and during pandemic. Differential effects were investigated for UK countries of residence (non-England/England), gender (male/female) and age (younger/older) using three-way interaction effects. RESULTS: GHQ-12 caseness increased in relative terms most for 'professional, scientific and technical' (OR: 3.15, 95% CI 2.17 to 4.59) industry in the pandemic versus pre-pandemic period. Absolute risk increased most in 'hospitality' (+11.4%). For socioeconomic class, 'small employers/self-employed' were most affected in relative and absolute terms (OR: 3.24, 95% CI 2.28 to 4.63; +10.3%). Across occupations, 'sales and customer service' (OR: 3.01, 95% CI 1.61 to 5.62; +10.7%) had the greatest increase. Analysis with three-way interactions showed considerable gender differences, while for UK country of residence and age results are mixed. CONCLUSIONS: GHQ-12 caseness increases during the pandemic were concentrated among 'professional and technical' and 'hospitality' industries and 'small employers/self-employed' and 'sales and customers service' workers. Female workers often exhibited greater differences in risk by industry and occupation. Policies supporting these industries and groups are needed.

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.

Ethnic and educational inequalities in COVID-19 vaccine hesitancy: cross-sectional analysis of the UK household longitudinal study

BackgroundVaccination is crucial to address the COVID-19 pandemic but inequalities in uptake may exacerbate existing health inequalities. We investigate the UK prevalence of COVID-19 vaccine hesitancy, identify which population subgroups are more likely to be vaccine hesitant, and report stated reasons for hesitancy.MethodsNationally representative survey data from 12,035 participants were collected from 24th November to 1st December 2020 for wave 6 of the UK Household Longitudinal Study (‘Understanding Society’) COVID-19 web survey. Participants self-reported ethnicity, highest educational attainment, gender, age, how likely they would be to have a vaccine if offered and their main reason for hesitancy. Weighted cross-sectional analysis assessed the prevalence of vaccine hesitancy and logistic regression models estimated independent associations.ResultsOverall vaccine hesitancy was low (18% unlikely/very unlikely). Vaccine hesitancy was higher in women (21.0% vs 14.7% in men), in younger age groups (26.5% in 16–24 year olds vs 4.5% in 75+) and in those with lower education levels (18.6% no qualifications vs 13.2% degree qualified). Vaccine hesitancy was high in Black (71.8%) and Pakistani/Bangladeshi (42.3%) ethnic groups. Odds ratios for vaccine hesitancy after adjustment for age and gender were 13.42 (95% CI:6.86, 26.24) in Black, 2.54 (95% CI:1.19, 5.44) in Pakistani/Bangladeshi groups, and 1.76 (95% CI:1.10, 2.82) for Other White (including Eastern European) ethnic groups (compared to White British/Irish). Vaccine hesitancy was not higher in all minority ethnic groups;for example, ORs were 1.11 (95% CI:0.64, 1.95) for Indian ethnicity and 0.67 (95% CI:0.24, 1.87) for Other Asian (including Chinese) ethnicity. Lower education was also related to vaccine hesitancy (no qualifications versus degree OR 3.54;95% CI:2.06, 6.09) but ethnic differences largely remained when education was included in the model. For those who were vaccine hesitant the most common stated reason for hesitancy was concerns over unknown future effects (42.7%). However, when compared to the White British/Irish group, Black participants were more likely to state they ‘Don’t trust vaccines’ (29.2% vs 5.7%) and the Pakistani/Bangladeshi ethnic group more frequently cited worries about side-effects (35.4% vs 8.6%).ConclusionVaccine hesitancy is strongly associated with education and ethnicity, with marked ethnic heterogeneity. Black and Pakistani/Bangladeshi participants reported considerably greater vaccine hesitancy than White British/Irish ethnicity, but some minority ethnic groups did not. Educational inequalities did not account for ethnic differences. Vaccine programmes need to understand reasons for vaccine hesitancy within specific population sub-groups and take urgent action to improve uptake.

Ethnic and socioeconomic differences in SARS-CoV-2 infection: prospective cohort study using UK Biobank.

BACKGROUND: Understanding of the role of ethnicity and socioeconomic position in the risk of developing SARS-CoV-2 infection is limited. We investigated this in the UK Biobank study. METHODS: The UK Biobank study recruited 40-70-year-olds in 2006-2010 from the general population, collecting information about self-defined ethnicity and socioeconomic variables (including area-level socioeconomic deprivation and educational attainment). SARS-CoV-2 test results from Public Health England were linked to baseline UK Biobank data. Poisson regression with robust standard errors was used to assess risk ratios (RRs) between the exposures and dichotomous variables for being tested, having a positive test and testing positive in hospital. We also investigated whether ethnicity and socioeconomic position were associated with having a positive test amongst those tested. We adjusted for covariates including age, sex, social variables (including healthcare work and household size), behavioural risk factors and baseline health. RESULTS: Amongst 392,116 participants in England, 2658 had been tested for SARS-CoV-2 and 948 tested positive (726 in hospital) between 16 March and 3 May 2020. Black and south Asian groups were more likely to test positive (RR 3.35 (95% CI 2.48-4.53) and RR 2.42 (95% CI 1.75-3.36) respectively), with Pakistani ethnicity at highest risk within the south Asian group (RR 3.24 (95% CI 1.73-6.07)). These ethnic groups were more likely to be hospital cases compared to the white British. Adjustment for baseline health and behavioural risk factors led to little change, with only modest attenuation when accounting for socioeconomic variables. Socioeconomic deprivation and having no qualifications were consistently associated with a higher risk of confirmed infection (RR 2.19 for most deprived quartile vs least (95% CI 1.80-2.66) and RR 2.00 for no qualifications vs degree (95% CI 1.66-2.42)). CONCLUSIONS: Some minority ethnic groups have a higher risk of confirmed SARS-CoV-2 infection in the UK Biobank study, which was not accounted for by differences in socioeconomic conditions, baseline self-reported health or behavioural risk factors. An urgent response to addressing these elevated risks is required.

Correction: Multimorbidity, polypharmacy, and COVID-19 infection within the UK Biobank cohort.

[This corrects the article DOI: 10.1371/journal.pone.0238091.].

Remote history of VTE is associated with severe COVID-19 in middle and older age: UK Biobank cohort study.

BACKGROUND: Venous thromboembolism (VTE) is a common, life-threatening complication of COVID-19 infection. COVID-19 risk-prediction models include a history of VTE. However, it is unclear whether remote history (>9 years previously) of VTE also confers increased risk of COVID-19. OBJECTIVES: To investigate possible association between VTE and COVID-19 severity, independent of other risk factors. METHODS: Cohort study of UK Biobank participants recruited between 2006 and 2010. Baseline data, including history of VTE, were linked to COVID-19 test results, COVID-19-related hospital admissions, and COVID-19 deaths. The risk of COVID-19 hospitalization or death was compared for participants with a remote history VTE versus without. Poisson regression models were run univariately then adjusted stepwise for sociodemographic, lifestyle, and comorbid covariates. RESULTS: After adjustment for sociodemographic and lifestyle confounders and comorbid conditions, remote history of VTE was associated with nonfatal community (RR 1.61, 95% CI 1.02-2.54, p = .039), nonfatal hospitalized (RR 1.52, 95% CI 1.06-2.17, p = .024) and severe (hospitalized or fatal) (RR 1.40, 95% CI 1.04-1.89, p = .025) COVID-19. Associations with remote history of VTE were stronger among men (severe COVID-19: RR 1.68, 95% CI 1.14-2.42, p = .009) than for women (severe COVID-19: RR 1.07, 95% CI 0.66-1.74, p = .786). CONCLUSION: Our findings support inclusion of remote history of VTE in COVID-19 risk-prediction scores, and consideration of sex-specific risk scores.

Mental health and well-being during the COVID-19 pandemic: longitudinal analyses of adults in the UK COVID-19 Mental Health & Wellbeing study.

BACKGROUND: The effects of coronavirus disease 2019 (COVID-19) on the population's mental health and well-being are likely to be profound and long lasting. AIMS: To investigate the trajectory of mental health and well-being during the first 6 weeks of lockdown in adults in the UK. METHOD: A quota survey design and a sampling frame that permitted recruitment of a national sample was employed. Findings for waves 1 (31 March to 9 April 2020), 2 (10 April to 27 April 2020) and 3 (28 April to 11 May 2020) are reported here. A range of mental health factors was assessed: pre-existing mental health problems, suicide attempts and self-harm, suicidal ideation, depression, anxiety, defeat, entrapment, mental well-being and loneliness. RESULTS: A total of 3077 adults in the UK completed the survey at wave 1. Suicidal ideation increased over time. Symptoms of anxiety, and levels of defeat and entrapment decreased across waves whereas levels of depressive symptoms did not change significantly. Positive well-being also increased. Levels of loneliness did not change significantly over waves. Subgroup analyses showed that women, young people (18-29 years), those from more socially disadvantaged backgrounds and those with pre-existing mental health problems have worse mental health outcomes during the pandemic across most factors. CONCLUSIONS: The mental health and well-being of the UK adult population appears to have been affected in the initial phase of the COVID-19 pandemic. The increasing rates of suicidal thoughts across waves, especially among young adults, are concerning.

Psychological distress among people with probable COVID-19 infection: analysis of the UK Household Longitudinal Study.

Studies exploring the longer-term effects of experiencing coronavirus disease-2019 (COVID-19) on mental health are lacking. We explored the relationship between reporting probable COVID-19 symptoms in April 2020 and psychological distress (measured using the General Health Questionnaire) 1, 2, 3, 5 and 7 months later. Data were taken from the UK Household Longitudinal Study, a nationally representative household panel survey of UK adults. Elevated levels of psychological distress were found up to 7 months after probable COVID-19, compared with participants with no likely infection. Associations were stronger among younger age groups and men. Further research into the psychological sequalae of COVID-19 is urgently needed.

Unequal impact of the COVID-19 crisis on minority ethnic groups: a framework for understanding and addressing inequalities.

Minority ethnic groups have been disproportionately affected by the COVID-19 pandemic. While the exact reasons for this remain unclear, they are likely due to a complex interplay of factors rather than a single cause. Reducing these inequalities requires a greater understanding of the causes. Research to date, however, has been hampered by a lack of theoretical understanding of the meaning of 'ethnicity' (or race) and the potential pathways leading to inequalities. In particular, quantitative analyses have often adjusted away the pathways through which inequalities actually arise (ie, mediators for the effect of interest), leading to the effects of social processes, and particularly structural racism, becoming hidden. In this paper, we describe a framework for understanding the pathways that have generated ethnic (and racial) inequalities in COVID-19. We suggest that differences in health outcomes due to the pandemic could arise through six pathways: (1) differential exposure to the virus; (2) differential vulnerability to infection/disease; (3) differential health consequences of the disease; (4) differential social consequences of the disease; (5) differential effectiveness of pandemic control measures and (6) differential adverse consequences of control measures. Current research provides only a partial understanding of some of these pathways. Future research and action will require a clearer understanding of the multiple dimensions of ethnicity and an appreciation of the complex interplay of social and biological pathways through which ethnic inequalities arise. Our framework highlights the gaps in the current evidence and pathways that need further investigation in research that aims to address these inequalities.

Predictors of COVID-19 vaccine hesitancy in the UK household longitudinal study.

Vaccine hesitancy could undermine efforts to control COVID-19. We investigated the prevalence of COVID-19 vaccine hesitancy in the UK and identified vaccine hesitant subgroups. The 'Understanding Society' COVID-19 survey asked participants (n = 12,035) their likelihood of vaccine uptake and reason for hesitancy. Cross-sectional analysis assessed vaccine hesitancy prevalence and logistic regression calculated odds ratios. Overall vaccine hesitancy was low (18% unlikely/very unlikely). Vaccine hesitancy was higher in women (21.0% vs 14.7%), younger age groups (26.5% in 16-24 year olds vs 4.5% in 75 + ) and those with lower education levels (18.6% no qualifications vs 13.2% degree qualified). Vaccine hesitancy was high in Black (71.8%) and Pakistani/Bangladeshi (42.3%) ethnic groups. Odds ratios for vaccine hesitancy were 13.42 (95% CI:6.86, 26.24) in Black and 2.54 (95% CI:1.19, 5.44) in Pakistani/Bangladeshi groups (compared to White British/Irish) and 3.54 (95% CI:2.06, 6.09) for people with no qualifications versus degree. Urgent action to address hesitancy is needed for some but not all ethnic minority groups.

Modifiable and non-modifiable risk factors for COVID-19, and comparison to risk factors for influenza and pneumonia: results from a UK Biobank prospective cohort study.

OBJECTIVES: We aimed to investigate demographic, lifestyle, socioeconomic and clinical risk factors for COVID-19, and compared them to risk factors for pneumonia and influenza in UK Biobank. DESIGN: Cohort study. SETTING: UK Biobank. PARTICIPANTS: 49-83 year olds (in 2020) from a general population study. MAIN OUTCOME MEASURES: Confirmed COVID-19 infection (positive SARS-CoV-2 test). Incident influenza and pneumonia were obtained from primary care data. Poisson regression was used to study the association of exposure variables with outcomes. RESULTS: Among 235 928 participants, 397 had confirmed COVID-19. After multivariable adjustment, modifiable risk factors were higher body mass index and higher glycated haemoglobin (HbA1C) (RR 1.28 and RR 1.14 per SD increase, respectively), smoking (RR 1.39), slow walking pace as a proxy for physical fitness (RR 1.53), and use of blood pressure medications as a proxy for hypertension (RR 1.33). Higher forced expiratory volume in 1 s (FEV1) and high-density lipoprotein (HDL) cholesterol were both associated with lower risk (RR 0.84 and RR 0.83 per SD increase, respectively). Non-modifiable risk factors included male sex (RR 1.72), black ethnicity (RR 2.00), socioeconomic deprivation (RR 1.17 per SD increase in Townsend Index), and high cystatin C (RR 1.13 per SD increase). The risk factors overlapped with pneumonia somewhat, less so for influenza. The associations with modifiable risk factors were generally stronger for COVID-19, than pneumonia or influenza. CONCLUSION: These findings suggest that modification of lifestyle may help to reduce the risk of COVID-19 and could be a useful adjunct to other interventions, such as social distancing and shielding of high risk.

Is older age associated with COVID-19 mortality in the absence of other risk factors? General population cohort study of 470,034 participants.

INTRODUCTION: Older people have been reported to be at higher risk of COVID-19 mortality. This study explored the factors mediating this association and whether older age was associated with increased mortality risk in the absence of other risk factors. METHODS: In UK Biobank, a population cohort study, baseline data were linked to COVID-19 deaths. Poisson regression was used to study the association between current age and COVID-19 mortality. RESULTS: Among eligible participants, 438 (0.09%) died of COVID-19. Current age was associated exponentially with COVID-19 mortality. Overall, participants aged ≥75 years were at 13-fold (95% CI 9.13-17.85) mortality risk compared with those <65 years. Low forced expiratory volume in 1 second, high systolic blood pressure, low handgrip strength, and multiple long-term conditions were significant mediators, and collectively explained 39.3% of their excess risk. The associations between these risk factors and COVID-19 mortality were stronger among older participants. Participants aged ≥75 without additional risk factors were at 4-fold risk (95% CI 1.57-9.96, P = 0.004) compared with all participants aged <65 years. CONCLUSIONS: Higher COVID-19 mortality among older adults was partially explained by other risk factors. 'Healthy' older adults were at much lower risk. Nonetheless, older age was an independent risk factor for COVID-19 mortality.

Mental health and health behaviours before and during the initial phase of the COVID-19 lockdown: longitudinal analyses of the UK Household Longitudinal Study.

BACKGROUND: There are concerns that COVID-19 mitigation measures, including the 'lockdown', may have unintended health consequences. We examined trends in mental health and health behaviours in the UK before and during the initial phase of the COVID-19 lockdown and differences across population subgroups. METHODS: Repeated cross-sectional and longitudinal analysis of the UK Household Longitudinal Study, including representative samples of over 27,000 adults (aged 18+) interviewed in four survey waves between 2015 and 2020. A total of 9748 adults had complete data for longitudinal analyses. Outcomes included psychological distress (General Health Questionnaire-12), loneliness, current cigarette smoking, use of e-cigarettes and alcohol consumption. Cross-sectional prevalence estimates were calculated and multilevel Poisson regression assessed associations between time period and the outcomes of interest, as well as differential associations by age, gender, education level and ethnicity. RESULTS: Psychological distress increased 1 month into lockdown with the prevalence rising from 19.4% (95% CI 18.7% to 20.1%) in 2017-2019 to 30.6% (95% CI 29.1% to 32.3%) in April 2020 (RR=1.3, 95% CI 1.2 to 1.4). Groups most adversely affected included women, young adults, people from an Asian background and those who were degree educated. Loneliness remained stable overall (RR=0.9, 95% CI 0.6 to 1.5). Smoking declined (RR=0.9, 95% CI=0.8,1.0) and the proportion of people drinking four or more times per week increased (RR=1.4, 95% CI 1.3 to 1.5), as did binge drinking (RR=1.5, 95% CI 1.3 to 1.7). CONCLUSIONS: Psychological distress increased 1 month into lockdown, particularly among women and young adults. Smoking declined, but adverse alcohol use generally increased. Effective measures are required to mitigate negative impacts on health.

Multimorbidity, polypharmacy, and COVID-19 infection within the UK Biobank cohort.

BACKGROUND: It is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity (≥2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. METHODS AND FINDINGS: We studied data from UK Biobank (428,199 participants; aged 37-73; recruited 2006-2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96-1.30)), whereas those with ≥2 LTCs had 48% higher risk; RR 1.48 (1.28-1.71). Compared with no cardiometabolic LTCs, having 1 and ≥2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12-1.46) and 1.77 (1.46-2.15), respectively. Polypharmacy was associated with a dose response higher risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI ≥40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09-3.78); 2.79 (2.00-3.90); 2.66 (1.88-3.76); 2.13 (1.46-3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. CONCLUSIONS: Increasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19.