Indicators of mental disorders in UK Biobank—A comparison of approachesKatrina A. S. Davis, Breda Cullen, Mark J. Adams et al.|International Journal of Methods in Psychiatric Research|2019 OBJECTIVES: For many research cohorts, it is not practical to provide a "gold-standard" mental health diagnosis. It is therefore important for mental health research that potential alternative measures for ascertaining mental disorder status are understood. METHODS: Data from UK Biobank in those participants who had completed the online Mental Health Questionnaire (n = 157,363) were used to compare the classification of mental disorder by four methods: symptom-based outcome (self-complete based on diagnostic interviews), self-reported diagnosis, hospital data linkage, and self-report medication. RESULTS: Participants self-reporting any psychiatric diagnosis had elevated risk of any symptom-based outcome. Cohen's κ between self-reported diagnosis and symptom-based outcome was 0.46 for depression, 0.28 for bipolar affective disorder, and 0.24 for anxiety. There were small numbers of participants uniquely identified by hospital data linkage and medication. CONCLUSION: Our results confirm that ascertainment of mental disorder diagnosis in large cohorts such as UK Biobank is complex. There may not be one method of classification that is right for all circumstances, but an informed and transparent use of outcome measure(s) to suit each research question will maximise the potential of UK Biobank and other resources for mental health research.
The Genetic Links to Anxiety and Depression (GLAD) Study: Online recruitment into the largest recontactable study of depression and anxietyMolly R. Davies, Gursharan Kalsi, Chérie Armour et al.|Behaviour Research and Therapy|2019 BACKGROUND: Anxiety and depression are common, debilitating and costly. These disorders are influenced by multiple risk factors, from genes to psychological vulnerabilities and environmental stressors, but research is hampered by a lack of sufficiently large comprehensive studies. We are recruiting 40,000 individuals with lifetime depression or anxiety and broad assessment of risks to facilitate future research. METHODS: The Genetic Links to Anxiety and Depression (GLAD) Study (www.gladstudy.org.uk) recruits individuals with depression or anxiety into the NIHR Mental Health BioResource. Participants invited to join the study (via media campaigns) provide demographic, environmental and genetic data, and consent for medical record linkage and recontact. RESULTS: Online recruitment was effective; 42,531 participants consented and 27,776 completed the questionnaire by end of July 2019. Participants' questionnaire data identified very high rates of recurrent depression, severe anxiety, and comorbidity. Participants reported high rates of treatment receipt. The age profile of the sample is biased toward young adults, with higher recruitment of females and the more educated, especially at younger ages. DISCUSSION: This paper describes the study methodology and descriptive data for GLAD, which represents a large, recontactable resource that will enable future research into risks, outcomes, and treatment for anxiety and depression.
Characteristics, comorbidities, and correlates of atypical depression: evidence from the UK Biobank Mental Health SurveyBACKGROUND: Depression is a heterogeneous disorder with multiple aetiological pathways and multiple therapeutic targets. This study aims to determine whether atypical depression (AD) characterized by reversed neurovegetative symptoms is associated with a more pernicious course and a different sociodemographic, lifestyle, and comorbidity profile than nonatypical depression (nonAD). METHODS: Among 157 366 adults who completed the UK Biobank Mental Health Questionnaire (MHQ), N = 37 434 (24%) met the DSM-5 criteria for probable lifetime major depressive disorder (MDD) based on the Composite International Diagnostic Interview Short Form. Participants reporting both hypersomnia and weight gain were classified as AD cases (N = 2305), and the others as nonAD cases (N = 35 129). Logistic regression analyses were conducted to examine differences between AD and nonAD in depression features, sociodemographic and lifestyle factors, lifetime adversities, psychiatric and physical comorbidities. RESULTS: Persons with AD experienced an earlier age of depression onset, longer, more severe and recurrent episodes, and higher help-seeking rates than nonAD persons. AD was associated with female gender, unhealthy behaviours (smoking, social isolation, low physical activity), more lifetime deprivation and adversity, higher rates of comorbid psychiatric disorders, obesity, cardiovascular disease (CVD), and metabolic syndrome. Sensitivity analyses comparing AD persons with those having typical neurovegetative symptoms (hyposomnia and weight loss) revealed similar results. CONCLUSIONS: These findings highlight the clinical and public health significance of AD as a chronic form of depression, associated with high comorbidity and lifetime adversity. Our findings have implications for predicting depression course and comorbidities, guiding research on aetiological mechanisms, planning service use and informing therapeutic approaches.
Longitudinal associations between late-life depression dimensions and cognitive functioning: a cross-domain latent growth curve analysisBACKGROUND: Cognitive impairment and depression often co-occur in older adults, but it is not clear whether depression is a risk factor for cognitive decline, a psychological reaction to cognitive decline, or whether changes in depressive symptoms correlate with changes in cognitive performance over time. The co-morbid manifestation of depression and cognitive impairment may reflect either a causal effect or a common cause, depending on the specific symptoms experienced and the cognitive functions affected. METHOD: The study sample comprised 1506 community-dwelling older adults aged ⩾65 years from the Longitudinal Aging Study Amsterdam (LASA). We conducted cross-domain latent growth curve analyses to examine longitudinal associations between late-life depression dimensions (i.e. depressed affect, positive affect, and somatic symptoms) and specific domains of cognitive functioning (i.e. processing speed, inductive reasoning, immediate recall, and delayed recall). RESULTS: Poorer delayed recall performance at baseline predicted a steeper increase in depressed affect over time. Steeper decline in processing speed correlated with a steeper increase in somatic symptoms of depression over time. CONCLUSIONS: Our findings suggest a prospective association between memory function and depressed affect, whereby older adults may experience an increase in depressed affect in reaction to poor memory function. Somatic symptoms of depression increased concurrently with declining processing speed, which may reflect common neurodegenerative processes. Our findings do not support the hypothesis that depression symptoms may be a risk factor for cognitive decline in the general population. These findings have potential implications for the treatment of late-life depression and for the prognosis of cognitive outcomes.
Common mental disorders within chronic inflammatory disorders: a primary care database prospective investigationAlex Dregan, Faith Matcham, Lisa Harber-Aschan et al.|Annals of the Rheumatic Diseases|2019