ABSTRACT
Background Structural barriers to testing may introduce selection bias in COVID-19 research. We explore whether changes to testing and lockdown restrictions introduce time-specific selection bias into analyses of socioeconomic position (SEP) and SARS-CoV-2 infection. Methods Using UK Biobank (N = 420 231; 55 % female; mean age = 56.3 [SD=8.01]) we estimated the association between SEP and i) being tested for SARS-CoV-2 infection versus not being tested ii) testing positive for SARS-CoV-2 infection versus testing negative and iii) testing negative for SARS-CoV-2 infection versus not being tested, at four distinct time-periods between March 2020 and March 2021. We explored potential selection bias by examining the same associations with hypothesised positive (ABO blood type) and negative (hair colour) control exposures. Finally, we conducted a hypothesis-free phenome-wide association study to investigate how individual characteristics associated with testing changed over time. Findings The association between low SEP and SARS-CoV-2 testing attenuated across time-periods. Compared to individuals with a degree, individuals who left school with GCSEs or less had an OR of 1.05 (95% CI: 0.95 to 1.16) in March-May 2020 and 0.98 (95% CI: 0.94 to 1.02) in January-March 2021. The magnitude of the association between low SEP and testing positive for SARS-CoV-2 infection increased over the same time-periods. For the same comparisons, the OR for testing positive increased from 1.27 (95% CI: 1.08 to 1.50), to 1.73 (95% CI: 1.59 to 1.87). We found little evidence of an association between both control exposures and all outcomes considered. Our phenome-wide analysis highlighted a broad range of individual traits were associated with testing, which were distinct across time-periods. Interpretation The association between SEP (and indeed many individual traits) and SARS-CoV-2 testing changed over time, indicating time-specific selection pressures in COVID-19. However, positive, and negative control analyses suggest that changes in the magnitude of the association between SEP and SARS-CoV-2 infection over time were unlikely to be explained by selection bias and reflect true increases in socioeconomic inequalities.
Subject(s)
COVID-19ABSTRACT
ObjectiveTo use the example of the effect of body mass index (BMI) on COVID-19 susceptibility and severity to illustrate methods to explore potential selection and misclassification bias in Mendelian randomisation (MR) of COVID-19 determinants. DesignTwo-sample MR analysis. SettingSummary statistics from the Genetic Investigation of ANthropometric Traits (GIANT) and COVID-19 Host Genetics Initiative (HGI) consortia. Participants681,275 participants in GIANT and more than 2.5 million people from the COVID-19 HGI consortia. ExposureGenetically instrumented BMI. Main outcome measuresSeven case/control definitions for SARS-CoV-2 infection and COVID-19 severity: very severe respiratory confirmed COVID-19 vs not hospitalised COVID-19 (A1) and vs population (those who were never tested, tested negative or had unknown testing status (A2)); hospitalised COVID-19 vs not hospitalised COVID-19 (B1) and vs population (B2); COVID-19 vs lab/self-reported negative (C1) and vs population (C2); and predicted COVID-19 from self-reported symptoms vs predicted or self-reported non-COVID-19 (D1). ResultsWith the exception of A1 comparison, genetically higher BMI was associated with higher odds of COVID-19 in all comparison groups, with odds ratios (OR) ranging from 1.11 (95%CI: 0.94, 1.32) for D1 to 1.57 (95%CI: 1.57 (1.39, 1.78) for A2. As a method to assess selection bias, we found no strong evidence of an effect of COVID-19 on BMI in a no-relevance analysis, in which COVID-19 was considered the exposure, although measured after BMI. We found evidence of genetic correlation between COVID-19 outcomes and potential predictors of selection determined a priori (smoking, education, and income), which could either indicate selection bias or a causal pathway to infection. Results from multivariable MR adjusting for these predictors of selection yielded similar results to the main analysis, suggesting the latter. ConclusionsWe have proposed a set of analyses for exploring potential selection and misclassification bias in MR studies of risk factors for SARS-CoV-2 infection and COVID-19 and demonstrated this with an illustrative example. Although selection by socioeconomic position and arelated traits is present, MR results are not substantially affected by selection/misclassification bias in our example. We recommend the methods we demonstrate, and provide detailed analytic code for their use, are used in MR studies assessing risk factors for COVID-19, and other MR studies where such biases are likely in the available data. SummaryO_ST_ABSWhat is already known on this topicC_ST_ABS- Mendelian randomisation (MR) studies have been conducted to investigate the potential causal relationship between body mass index (BMI) and COVID-19 susceptibility and severity. - There are several sources of selection (e.g. when only subgroups with specific characteristics are tested or respond to study questionnaires) and misclassification (e.g. those not tested are assumed not to have COVID-19) that could bias MR studies of risk factors for COVID-19. - Previous MR studies have not explored how selection and misclassification bias in the underlying genome-wide association studies could bias MR results. What this study adds- Using the most recent release of the COVID-19 Host Genetics Initiative data (with data up to June 2021), we demonstrate a potential causal effect of BMI on susceptibility to detected SARS-CoV-2 infection and on severe COVID-19 disease, and that these results are unlikely to be substantially biased due to selection and misclassification. - This conclusion is based on no evidence of an effect of COVID-19 on BMI (a no-relevance control study, as BMI was measured before the COVID-19 pandemic) and finding genetic correlation between predictors of selection (e.g. socioeconomic position) and COVID-19 for which multivariable MR supported a role in causing susceptibility to infection. - We recommend studies use the set of analyses demonstrated here in future MR studies of COVID-19 risk factors, or other examples where selection bias is likely.
Subject(s)
COVID-19 , Genetic Diseases, InbornABSTRACT
Background Non-random selection into analytic subsamples could introduce selection bias in observational studies of SARS-CoV-2 infection and COVID-19 severity (e.g. including only those have had a COVID-19 PCR test). We explored the potential presence and impact of selection in such studies using data from self-report questionnaires and national registries. Methods Using pre-pandemic data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (mean age=27.6 (standard deviation [SD]=0.5); 49% female) and UK Biobank (UKB) (mean age=56 (SD=8.1); 55% female) with data on SARS-CoV-2 infection and death-with-COVID-19 (UKB only), we investigated predictors of selection into COVID-19 analytic subsamples. We then conducted empirical analyses and simulations to explore the potential presence, direction, and magnitude of bias due to selection when estimating the association of body mass index (BMI) with SARS-CoV-2 infection and death-with-COVID-19. Results In both ALSPAC and UKB a broad range of characteristics related to selection, sometimes in opposite directions. For example, more educated participants were more likely to have data on SARS-CoV-2 infection in ALSPAC, but less likely in UKB. We found bias in many simulated scenarios. For example, in one scenario based on UKB, we observed an expected odds ratio of 2.56 compared to a simulated true odds ratio of 3, per standard deviation higher BMI. Conclusion Analyses using COVID-19 self-reported or national registry data may be biased due to selection. The magnitude and direction of this bias depends on the outcome definition, the true effect of the risk factor, and the assumed selection mechanism.
Subject(s)
COVID-19ABSTRACT
ImportanceCOVID-19 public health mitigation measures are likely to have detrimental effects on emotional and behavioural problems in children. However, longitudinal studies with pre-pandemic data are scarce. ObjectiveTo explore trajectories of childrens emotional and behavioural difficulties during the COVID-19 pandemic. Design and settingData were from children from the third generation of a birth cohort study; the Avon Longitudinal Study of Parents and Children - Generation 2 (ALSPAC-G2) in the southwest of England. ParticipantsThe study population comprised of 708 children (median age at COVID-19 data collection was 4.4 years, SD=2.9, IQR= [2.2 to 6.9]), whose parents provided previous pre-pandemic surveys and a survey between 26 May and 5 July 2020 that focused on information about the COVID-19 pandemic as restrictions from the first lockdown in the UK were eased. ExposuresWe employed multi-level mixed effects modelling with random intercepts and slopes to examine whether childrens trajectories of emotional and behavioural difficulties (a combined total difficulties score) during the pandemic differ from expected pre-pandemic trajectories. Main outcomesChildren had up to seven measurements of emotional and behavioural difficulties from infancy to late childhood, using developmentally appropriate scales such as the Emotionality Activity Sociability Temperament Survey in infancy and Strengths and Difficulties Questionnaire in childhood. ResultsThe observed normative pattern of childrens emotional and behavioural difficulties pre-pandemic, was characterised by an increase in scores during infancy peaking around the age of 2, and then declining throughout the rest of childhood. Pre-pandemic, the decline in difficulties scores after age 2 was 0.6 points per month; but was approximately one third of that in post-pandemic trajectories (there was a difference in mean rate of decline after age 2 of 0.2 points per month in pre vs during pandemic trajectories [95 % CI: 0.10 to 0.30, p <0.001]). This lower decline in scores over the years translated to older children having pandemic difficulty scores higher than would be expected from pre-pandemic trajectories (for example, an estimated 10.0 point (equivalent of 0.8 standard deviations) higher score (95% CI: 5.0 to 15.0) by age 8.5 years). Results remained similar although somewhat attenuated after adjusting for maternal anxiety and age. Conclusion and relevanceThe COVID-19 pandemic may be associated with greater persistence of emotional and behavioural difficulties after the age 2. Emotional difficulties in childhood predict later mental health problems. Further evidence and monitoring of emotional and behavioural difficulties are required to fully understand the potential role of the pandemic on young children. Key FindingsO_ST_ABSQuestionC_ST_ABSHow has the COVID-19 pandemic influenced emotional difficulties in young children? FindingsUsing repeated longitudinal data from before and during the pandemic we provide evidence that emotional difficulty scores of primary school aged children are higher by an estimated 10.0 points (0.8 standard deviations) (95% CI: 5.0 to 15.0) by age 8.5 years than would be expected based on pre pandemic data. MeaningThe level of difference in emotional difficulties found in the current study has been linked to increased likelihood of mental health problems in adolescence and adulthood. Therefore, this increase in difficulties needs careful monitoring and support.
Subject(s)
COVID-19ABSTRACT
Objectives To determine clinically important change in anxiety and depression from before to during the first UK Covid-19 lockdown and factors related to this change, including ethnic differences. Design Pre-Covid and lockdown surveys nested within two longitudinal Born in Bradford cohort studies. Participants 1,860 mothers with a child aged 0-4 or 9-13, 48% Pakistani heritage Main outcome measures Odds ratios (OR) for a clinically important increase (5 points) in depression (PHQ-8) and anxiety (GAD-7) in unadjusted regression analyses, parsimonious multivariate modelling to explore ethnicity and mental ill health and lived experience of mothers captured in open text questions. Results Clinically important depression and anxiety increased from 11% to 19%, and 10% to 16% respectively from before to during the first Covid-19 lockdown. Loneliness during lockdown was most strongly associated with increases in depression (OR: 8.37, 95% CIs: 5.70-12.27) and anxiety (8.50, 5.71-12.65), followed by financial insecurity (6.23, 3.96-9.80; 6.03, 3.82-9.51). Other strongly associated variables included food and housing insecurity, a lack of physical activity and a poor partner relationship. When level of financial insecurity was taken into account, Pakistani heritage mothers were less likely than White British mothers to experience an increase in depression (0.67, 0.51-0.89) and anxiety (0.73, 0.55-0.97). Responses to open text highlighted a complex inter-play of health anxieties, mental load, loss of social support and coping strategies, and financial insecurity contributing to mental ill health. Positive aspects of lockdown were also reported, including a more relaxed pace of life. Conclusions Mental ill health has worsened with the Covid-19 lockdown, particularly in those who are lonely, economically insecure and/or of White British ethnicity. Mental health problems may have longer term consequences for public health. Strategies to mitigate adverse impacts of future lockdowns on mental health should focus on those factors we highlight as associated with worsening mental health.
Subject(s)
COVID-19 , Anxiety Disorders , Depressive DisorderABSTRACT
BackgroundThe economic and reproductive medicine response to the COVID-19 pandemic in the United States has reduced the affordability and accessibility of fertility care. We sought to determine the impact of the 2008 financial recession and the COVID-19 recession on fertility treatments and cumulative live-births. MethodsWe examined annual US natality, CDC IVF cycle activity and live birth data from 1999 to 2018 encompassing 3,286,349 treatment cycles, to estimate the age-stratified reduction in IVF cycles undertaken after the 2008 financial recession, with forward quantitative modelling of IVF cycle activity and cumulative live-births for 2020 to 2023. ResultsThe financial recession of 2008 caused a four-year plateau in fertility treatments with a predicted 53,026 (95% CI 49,581 to 56,471) fewer IVF cycles and 16,872 (95% CI 16,713 to 17,031) fewer live births. A similar scale of economic recession would cause 67,386 (95% CI: 61,686 to 73,086) fewer IVF cycles between 2020 and 2023, with women younger than 35 years overall undertaking 22,504 (95% CI 14,320 to 30,690) fewer cycles, as compared to 4,445 (95% CI 3,144 to 5749) fewer cycles in women over the age of 40 years. This equates to overall 25,143 (95% CI: 22,408 to 27,877) fewer predicted live-births from IVF, of which only 490 (95% CI 381 to 601) are anticipated to occur in women over the age of 40 years. ConclusionsThe COVID-19 recession could have a profound impact on US IVF live-birth rates in young women, further aggravating pre-existing declines in total fertility rates. Trial registration numbernot applicable
Subject(s)
COVID-19ABSTRACT
Background: The impact of COVID-19 on mental health is unclear. Evidence from longitudinal studies with pre pandemic data are needed to address (1) how mental health has changed from pre-pandemic levels to during the COVID-19 pandemic and (2), whether there are groups at greater risk of poorer mental health during the pandemic? Methods: We used data from COVID-19 surveys (completed through April/May 2020), nested within two large longitudinal population cohorts with harmonised measures of mental health: two generations of the Avon Longitudinal Study of Parents and Children (ALPSAC): the index generation ALSPAC-G1 (n= 2850, mean age 28) and the parents generation ALSPAC-G0 (n= 3720, mean age = 59) and Generation Scotland: Scottish Family Health Study (GS, (n= 4233, mean age = 59), both with validated pre-pandemic measures of mental health and baseline factors. To answer question 1, we used ALSPAC-G1, which has identical mental health measures before and during the pandemic. Question 2 was addressed using both studies, using pre-pandemic and COVID-19 specific factors to explore associations with depression and anxiety in COVID-19. Findings: In ALSPAC-G1 there was evidence that anxiety and lower wellbeing, but not depression, had increased in COVID-19 from pre-pandemic assessments. The percentage of individuals with probable anxiety disorder was almost double during COVID-19: 24% (95% CI 23%, 26%) compared to pre-pandemic levels (13%, 95% CI 12%, 14%), with clinically relevant effect sizes. In both ALSPAC and GS, depression and anxiety were greater in younger populations, women, those with pre-existing mental and physical health conditions, those living alone and in socio-economic adversity. We did not detect evidence for elevated risk in key workers or health care workers. Interpretation: These results suggest increases in anxiety and lower wellbeing that may be related to the COVID-19 pandemic and/or its management, particularly in young people. This research highlights that specific groups may be disproportionally at risk of elevated levels of depression and anxiety during COVID-19 and supports recent calls for increasing funds for mental health services. Funding: The UK Medical Research Council (MRC), the Wellcome Trust and University of Bristol.