How to mitigate selection bias in COVID-19 surveys: evidence from five national cohorts (preprint)

Background: Non-response is a common problem, and even more so during the COVID-19 pandemic where social distancing measures challenged data collections. As non-response is often systematic, meaning that respondents are usually healthier and from a better socioeconomic background, this potentially introduces serious bias in research findings based on COVID-19 survey data. The goal of the current study was to see if we can reduce bias and restore sample representativeness despite systematic non-response in the COVID-19 surveys embedded within five UK cohort studies using the rich data available from previous time points. Methods: A series of three surveys was conducted during the pandemic across five UK cohorts: National Survey of Health and Development (NSHD, born 1946), 1958 National Child Development Study (NCDS), 1970 British Cohort Study (BCS70), Next Steps (born 1989-90) and Millennium Cohort Study (MCS, born 2000-02). We applied non-response weights and utilised multiple imputation, making use of covariates from previous waves which have been commonly identified as predictors of non-response, to attempt to reduce bias and restore sample representativeness. Results: Response rates in the COVID-19 surveys were lower compared to previous cohort waves, especially in the younger cohorts. We identified bias due to systematic non-response in the distributions of variables including parental social class and childhood cognitive ability. In each cohort, respondents of the COVID-19 survey had a higher percentage of parents in the most advantaged social class, and a higher mean of childhood cognitive ability, compared to the original (full) cohort sample. The application of non-response weights and multiple imputation was successful in reducing bias in parental social class and childhood cognitive ability, nearly eliminating it for the former. Conclusions: The current paper demonstrates that it is possible to reduce bias from non-response and to a large degree restore sample representativeness in multiple waves of a COVID-19 survey embedded within long running longitudinal cohort studies through application of non-response weights or multiple imputation. Such embedded COVID-19 surveys therefore have an advantage over cross-sectional COVID-19 surveys, where non-response bias cannot be handled by leveraging previously observed information on non-respondents. Our findings suggest that, if non-response is appropriately handled, analyses based on the COVID-19 surveys within these five cohorts can contribute significantly to COVID-19 research, including studying the medium and long-term effects of the pandemic.

Patient characteristics associated with clinically coded long COVID: an OpenSAFELY study using electronic health records (preprint)

Despite reports of post-COVID-19 syndromes (long COVID) are rising, clinically coded long COVID cases are incomplete in electronic health records. It is unclear how patient characteristics may be associated with clinically coded long COVID. With the approval of NHS England, we undertook a cohort study using electronic health records within the OpenSAFELY-TPP platform in England, to study patient characteristics associated with clinically coded long COVID from 29 January 2020 to 31 March 2022. We estimated age-sex adjusted hazard ratios and fully adjusted hazard ratios for coded long COVID. Patient characteristics included demographic factors, and health behavioural and clinical factors. Among 17,986,419 adults, 36,886 (0.21%) were clinically coded with long COVID. Patient characteristics associated with coded long COVID included female sex, younger age (under 60 years), obesity, living in less deprived areas, ever smoking, greater consultation frequency, and history of diagnosed asthma, mental health conditions, pre-pandemic post-viral fatigue, or psoriasis. The strength of these associations was attenuated following two-dose vaccination compared to before vaccination. The incidence of coded long COVID was higher after hospitalised than non-hospitalised COVID-19. These results should be interpreted with caution given that long COVID was likely under-recorded in electronic health records.

BMI across adulthood, COVID-19 and long COVID in two British birth cohorts (preprint)

Longer exposure to obesity, and thus a longer period in an inflamed state, may increase susceptibility to infectious diseases and worsen severity. Previous cross-sectional work finds higher BMI is related to worse COVID-19 outcomes, but less is known about associations with BMI across adulthood. To examine this, we used body mass index (BMI) collected through adulthood in the 1958 National Child Development Study (NCDS) and the 1970 British Cohort Study (BCS70). Participants were grouped by the age they were first overweight (> 25kg/m2) and obese (> 30kg/m2). Logistic regression was used to assess associations with COVID-19 (self-reported and serology-confirmed), severity (hospital admission and contact with health services) and long-COVID reported at ages 62 (NCDS) and 50 (BCS70). Longer exposure to obesity was associated with increased odds of adverse COVID-19 outcomes, but results were mixed and often underpowered. Those with early exposure to obesity were over twice as likely in NCDS (odds ratio (OR) 2.15, 95% confidence interval (CI): 1.17 to 4.00) and three times as likely in BCS70 (OR 3.01, 95% CI: 1.74 to 5.22) to have long COVID. In NCDS they were also over four times as likely to be admitted to hospital (OR 4.69, 95% CI: 1.64 to 13.39). Most associations were somewhat explained by contemporaneous BMI or reported health, diabetes or hypertension; however, the association with hospital admission in NCDS remained. An earlier age of obesity onset is related to COVID-19 outcomes in later life, providing evidence on the long-term impact of raised BMI on infectious disease outcomes in midlife.

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

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

Mental health outcomes following COVID-19 infection: Evidence from 11 UK longitudinal population studies (preprint)

Background Evidence on associations between COVID-19 illness and mental health is mixed. We examined longitudinal associations between COVID-19 and mental health while considering: 1) pre-pandemic mental health, 2) time since infection; 3) subgroup differences; and 4) confirmation of infection via self-reported test, and serology data. Methods Using data from 11 UK longitudinal studies, involving 54,442 participants, with 2 to 8 repeated measures of mental health and COVID-19 between April 2020 and April 2021, we standardised continuous mental health scales within each study across time. We investigated associations between COVID-19 (self-report, test-confirmed, serology-confirmed) and mental health using multilevel generalised estimating equations. We examined whether associations varied by age, sex, ethnicity, education and pre-pandemic mental health. Effect-sizes were pooled in random-effects meta-analyses. Outcomes Pooled estimates of the standardized difference in outcome between those with and without self-reported COVID-19 suggested associations with subsequent psychological distress (0.10 [95%CI: 0.06; 0.13], I 2 =42.8%), depression (0.08 [0.05; 0.10], I 2 =20.8%), anxiety (0.08 [0.05; 0.10], I 2 =0%), and lower life satisfaction (−0.06 [-0.08; -0.04], I 2 =29.2%). Associations did not vary by time since infection until 3+ months and were present in all age groups, with some evidence of stronger effects in those aged 50+. Self-reported COVID-19, whether suspected or test-confirmed and irrespective of serology status, was associated with poorer mental health. Interpretation Self-reporting COVID-19 was longitudinally associated with deterioration in mental health and life satisfaction. Our findings have important implications for mental health service provision, given the substantial prevalence of COVID-19 in the UK and worldwide. Funding MRC and NIHR

Psychological Distress Before and During the COVID-19 Pandemic: Sociodemographic Inequalities in 11 UK Longitudinal Studies (preprint)

Background: How population mental health has evolved across the COVID-19 pandemic under varied lockdown measures is poorly understood, with impacts on health inequalities unclear. We investigated changes in mental health and sociodemographic inequalities from before and across the first year of the pandemic in 11 longitudinal studies. Methods: Data from 11 UK longitudinal population-based studies with pre-pandemic measures of psychological distress were analysed and estimates pooled. Trends in the prevalence of poor mental health were assessed across the pandemic at three time periods: initial lockdown (TP1, Mar-June 20); easing of restrictions (TP2, July-Oct 20); and a subsequent lockdown (TP3, Nov 20-Mar 21). Multi-level regression was used to examine changes in psychological distress compared to pre-pandemic; with stratified analyses by sex, ethnicity, education, age, and UK country. Results: Across the 11 studies (n=54,609), mental health had deteriorated from pre-pandemic scores across all three pandemic time periods (TP1 Standardised Mean Difference (SMD): 0.13 (95% CI: 0.03, 0.23); TP2 SMD: 0.18 (0.09, 0.27); TP3 SMD: 0.20 (0.09, 0.31)). 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 slightly lower in below-degree level educated persons at some time periods (TP3 SMD: 0.18 (0.06, 0.30)) compared to those who held degrees (TP3 SMD: 0.26 (0.14, 0.38)). Increased distress was most prominent amongst adults aged 35-44 years (TP3 SMD: 0.49 (0.15, 0.84)). We did not find evidence of changes in distress differing by ethnicity or UK country. Conclusions: The substantial deterioration in mental health seen in the UK during the first lockdown did not reverse when lockdown lifted, and a sustained worsening is observed across the pandemic. Mental health declines have not been equal across the population, with females, those with higher degrees, and younger adults more affected.

Risk factors for long COVID: analyses of 10 longitudinal studies and electronic health records in the UK (preprint)

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. Methods Analysis 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. Results Functionally 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%). Conclusions Long 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.

Pre-pandemic mental health and disruptions to healthcare, economic, and housing outcomes during COVID –19: evidence from 12 UK longitudinal studies (preprint)

Background The COVID-19 pandemic and associated virus suppression measures have disrupted lives and livelihoods and people already experiencing mental ill-health may have been especially vulnerable. Aim To quantify mental health inequalities in disruptions to healthcare, economic activity and housing. Method 59,482 participants in 12 UK longitudinal adult population studies with data collected prior to 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 three domains: healthcare (medication access, procedures, or appointments); economic activity (employment, income, or working hours); and housing (change of address or household composition). Meta-analyses were used to pool estimates across studies. Results Across the analysed datasets, one to two-thirds of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. One standard deviation higher pre-pandemic psychological distress was associated with: (i) increased odds of any healthcare disruptions (OR=1.30; [95% CI:1.20–1.40]) with fully adjusted ORs ranging from 1.24 [1.09–1.41] for disruption to procedures and 1.33 [1.20– 1.49] for disruptions to prescriptions or medication access; (ii) loss of employment (OR=1.13 [1.06–1.21]) and income (OR=1.12 [1.06 –1.19]) and reductions in working hours/furlough (OR=1.05 [1.00–1.09]); (iii) no associations with housing disruptions (OR=1.00 [0.97–1.03]); and (iv) increased likelihood of experiencing a disruption in at least two domains (OR=1.25 [1.18–1.32]) or in one domain (OR=1.11 [1.07–1.16]) relative to no disruption. Conclusion People experiencing psychological distress pre-pandemic have been 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 the existing inequalities in mental health.

Changes in the behavioural determinants of health during the coronavirus (COVID-19) pandemic: gender, socioeconomic and ethnic inequalities in 5 British cohort studies (preprint)

BackgroundThe coronavirus (COVID-19) pandemic and consequent physical distancing measures are expected to have far-reaching consequences on population health, particularly in already disadvantaged groups. These consequences include changes in health impacting behaviours (such as exercise, sleep, diet and alcohol use) which are arguably important drivers of health inequalities. We sought to add to the rapidly developing empirical evidence base investigating the impacts of the pandemic on such behavioural outcomes. MethodsUsing data from five nationally representative British cohort studies (born 2001, 1990, 1970, 1958, and 1946), we investigated sleep, physical activity (exercise), diet, and alcohol intake (N=14,297). Using measures of each behaviour reported before and during lockdown, we investigated change in each behaviour, and whether such changes differed by age/cohort, gender, ethnicity, and socioeconomic position (SEP; childhood social class, education attainment, and adult reporting of financial difficulties). Binary or ordered logistic regression models were used, adjusting for prior measures of each health behaviour and accounting for study design and non-response weights. Meta-analyses were used to pool cohort-specific estimates and formally test for heterogeneity across cohorts. ResultsChanges in these outcomes occurred in in both directions ie, shifts from the middle part of the distribution to both declines and increases in sleep, exercise, and alcohol use. For all outcomes, older cohorts were less likely to report changes in behaviours compared with younger cohorts. In the youngest cohort (born 2001), the following shifts were more evident: increases in exercise, fruit and vegetable intake, sleep, and less frequent alcohol consumption. After adjustment for prior behaviour levels, during lockdown females were less likely to sleep within the typical range (6-9 hours) yet exercised more frequently; lower SEP was associated with lower odds of sleeping within the typical range (6-9 hours), lower exercise participation, and lower consumption of fruit and vegetables; and ethnic minorities were less likely than White participants to sleep within the typical range (6-9 hours), exercise less frequently, yet reported less frequent alcohol consumption. ConclusionsOur findings highlight the multiple changes to behavioural outcomes that may have occurred due to COVID-19 lockdown, and the differential impacts across generation, gender, SEP and ethnicity. Such changes require further monitoring given their possible implications to population health and the widening of health inequalities.