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Background\udGeneralized anxiety and depression are extremely prevalent and debilitating. There is evidence for age and sex variability in symptoms of depression, but despite comorbidity it is unclear whether this extends to anxiety symptomatology. Studies using questionnaire sum scores typically fail to address this phenotypic complexity.\ud\udMethod\udWe conducted exploratory and confirmatory factor analyses on Generalized Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9) items to identify latent factors of anxiety and depression in participants from the Genetic Links to Anxiety and Depression Study (N = 35,637; 16–93 years). We assessed age- and sex-related variability in latent factors and individual symptoms using multiple logistic regression.\ud\udResults\udFour factors of mood, worry, motor, and somatic symptoms were identified (comparative fit index [CFI] = 0.99, Tucker–Lewis Index [TLI] = 0.99, root mean square error of approximation [RMSEA] = 0.07, standardized root mean square residuals [SRMR] = 0.04). Symptoms of irritability (odds ratio [OR] = 0.81) were most strongly associated with younger age, and sleep change (OR = 1.14) with older age. Males were more likely to report mood and motor symptoms (p

BackgroundRisk factors for severe COVID-19 include older age, male sex, obesity, black or Asian ethnicity and underlying medical conditions. Whether these factors also influence susceptibility to developing COVID-19 is uncertain.MethodsWe undertook a prospective, population-based cohort study (COVIDENCE UK) from 1 May 2020 to 5 February 2021. Baseline information on potential risk factors was captured by an online questionnaire. Monthly follow-up questionnaires captured incident COVID-19. We used logistic regression models to estimate multivariable-adjusted ORs (aORs) for associations between potential risk factors and odds of COVID-19.ResultsWe recorded 446 incident cases of COVID-19 in 15 227 participants (2.9%). Increased odds of developing COVID-19 were independently associated with Asian/Asian British versus white ethnicity (aOR 2.28, 95% CI 1.33 to 3.91), household overcrowding (aOR per additional 0.5 people/bedroom 1.26, 1.11 to 1.43), any versus no visits to/from other households in previous week (aOR 1.31, 1.06 to 1.62), number of visits to indoor public places (aOR per extra visit per week 1.05, 1.02 to 1.09), frontline occupation excluding health/social care versus no frontline occupation (aOR 1.49, 1.12 to 1.98) and raised body mass index (BMI) (aOR 1.50 (1.19 to 1.89) for BMI 25.0–30.0 kg/m2 and 1.39 (1.06 to 1.84) for BMI >30.0 kg/m2 versus BMI 2). Atopic disease was independently associated with decreased odds (aOR 0.75, 0.59 to 0.97). No independent associations were seen for age, sex, other medical conditions, diet or micronutrient supplement use.ConclusionsAfter rigorous adjustment for factors influencing exposure to SARS-CoV-2, Asian/Asian British ethnicity and raised BMI were associated with increased odds of developing COVID-19, while atopic disease was associated with decreased odds.Trial registration numberClinicalTrials.gov Registry (NCT04330599).

SummaryBackgroundRisk factors for severe COVID-19 include older age, male sex, obesity, Black or Asian ethnicity and underlying medical conditions. Whether these factors also influence susceptibility to developing COVID-19 is uncertain.MethodsWe undertook a prospective, population-based cohort study (COVIDENCE UK) from 1stMay 2020 to 5thFebruary 2021. Baseline information on potential risk factors was captured by an online questionnaire. Monthly follow-up questionnaires captured incident COVID-19. We used logistic regression models to estimate multivariable-adjusted odds ratios (aORs) for associations between potential risk factors and risk of COVID-19.FindingsWe recorded 446 incident cases of COVID-19 in 15,227 participants (2.9%). Increased risk of developing COVID-19 was independently associated with Asian/Asian Britishvs. White ethnicity (aOR 2.31, 95% CI 1.35-3.95), household overcrowding (aOR per additional 0.5 people/bedroom 1.26, 1.11-1.43), anyvs. no visits to/from other households in previous week (aOR 1.33, 1.07-1.64), number of visits to indoor public places (aOR per extra visit per week 1.05, 1.01-1.09), frontline occupation excluding health/social carevs. no frontline occupation (aOR 1.49, 1.12-1.98), and raised body mass index (BMI) (aOR 1.51 [1.20-1.90] for BMI 25.0-30.0 kg/m2and 1.38 [1.05-1.82] for BMI >30.0 kg/m2vs. BMI 2). Atopic disease was independently associated with decreased risk (aOR 0.76, 0.59-0.98). No independent associations were seen for age, sex, other medical conditions, diet, or micronutrient supplement use.InterpretationAfter rigorous adjustment for factors influencing exposure to SARS-CoV-2, Asian/Asian British ethnicity and raised BMI were associated with increased risk of developing COVID-19, while atopic disease was associated with decreased risk.FundingBarts Charity, Health Data Research UK

BackgroundUnderstanding and improving outcomes for people with anxiety or depression often requires large studies. To increase participation and reduce costs, such research is typically unable to utilise “gold-standard” methods to ascertain diagnoses, instead relying on remote, self-report measures.AimsTo assess the comparability of remote diagnostic methods for anxiety and depression disorders commonly used in research.MethodParticipants from the UK-based GLAD and COPING NBR cohorts (N= 58,400) completed an online questionnaire between 2018-2020. Responses to detailed symptom reports were compared to DSM-5 criteria to generate algorithm-based diagnoses of major depressive disorder (MDD), generalised anxiety disorder (GAD), specific phobia, social anxiety disorder, panic disorder, and agoraphobia. Participants also self-reported any prior diagnoses from health professionals, termed single-item diagnoses. “Any anxiety” included participants with at least one anxiety disorder. Agreement was assessed by calculating accuracy, Cohen’s kappa, McNemar’s chi-squared, sensitivity, and specificity.ResultsAgreement between diagnoses was moderate for MDD, any anxiety, and GAD, but varied by cohort. Agreement was slight to fair for the phobic disorders. Many participants with single-item GAD did not receive an algorithm-based diagnosis. In contrast, algorithm-based diagnoses of the phobic disorders were more common than single-item diagnoses.ConclusionsAgreement for MDD, any anxiety, and GAD was higher for cases in the case-enriched GLAD cohort and for controls in the general population COPING NBR cohort. For anxiety disorders, single-item diagnoses classified most participants as having GAD, whereas algorithm-based diagnoses distributed participants more evenly across the anxiety disorders. Further validation against gold standard measures is required.

BackgroundUnderstanding and improving outcomes for people with anxiety or depression often requires large sample sizes. To increase participation and reduce costs, such research is typically unable to utilise “gold-standard” methods to ascertain diagnoses, instead relying on remote, self-report measures.AimsAssess the comparability of remote diagnostic methods for anxiety and depression disorders commonly used in research.MethodParticipants from the UK-based GLAD and COPING NBR cohorts (N = 58,400) completed an online questionnaire between 2018 and 2020. Responses to detailed symptom reports were compared to DSM-5 criteria to generate symptom-based diagnoses of major depressive disorder (MDD), generalised anxiety disorder (GAD), specific phobia, social anxiety disorder, panic disorder, and agoraphobia. Participants also self-reported any prior diagnoses from health professionals, termed self-reported diagnoses. “Any anxiety” included participants with at least one anxiety disorder. Agreement was assessed by calculating accuracy, Cohen’s kappa, McNemar’s chi-squared, sensitivity, and specificity.ResultsAgreement between diagnoses was moderate for MDD, any anxiety, and GAD, but varied by cohort. Agreement was slight to fair for the phobic disorders. Many participants with self-reported GAD did not receive a symptom-based diagnosis. In contrast, symptom-based diagnoses of the phobic disorders were more common than self-reported diagnoses.ConclusionsAgreement for MDD, any anxiety, and GAD was higher for cases in the case-enriched GLAD cohort and for controls in the general population COPING NBR cohort. For anxiety disorders, self-reported diagnoses classified most participants as having GAD, whereas symptom-based diagnoses distributed participants more evenly across the anxiety disorders. Further validation against gold standard measures is required.