The varying burden of depressive symptoms across adulthood: Results from six NHANES cohorts.

BACKGROUND: Depressive symptoms differ from each other in the degree of functional impairment they cause. The incidence of depression varies across the adult lifespan. We examined whether age moderates the impairment caused by depressive symptoms. METHODS: The study sample (n = 21,056) was adults drawn from six multistage probability samples from the National Health and Nutrition Examination Survey series (NHANES, years 2005-2016) conducted in the United States using cross-sectional, representative cohorts. Depressive symptoms were assessed with the nine-item Patient Health Questionnaire (PHQ-9). We used regression models to predict high functional impairment, while controlling for sociodemographic variables and physical disorders. RESULTS: Age moderated the association between depressive symptoms and functional impairment: middle-aged adults perceived moderate and severe symptoms as more impairing than did others. Older adults reported slightly higher impairment due to mild symptoms. The individual symptoms of low mood, feelings of worthlessness and guilt, and concentration difficulties were more strongly related to high impairment in mid-adulthood as compared to early and late adulthood. LIMITATIONS: Cross-sectional data allows only between-person comparisons. The PHQ-9 is brief and joins compound symptoms into single items. There was no information available concerning comorbid mental disorders. Co-occurring physical disorders were self-reported. CONCLUSIONS: Symptoms of depression may imply varying levels of impairment at different ages. The results suggest a need for age adjustments when estimating the functional impact of depression in the general population. Additionally, they show a need for more accurate assessments of depression-related impairment at older ages. Evidence-based programs may generally benefit from symptom- and age-specific findings.

Diagnostic and genetic overlap of three common mental disorders in structured interviews and health registries.

OBJECTIVE: To investigate whether diagnostic data from structured interviews, primary care and specialist care registries on major depressive disorder (MDD), anxiety disorders (AD) and alcohol use disorder (AUD) identify the same individuals, yield comparable comorbidity estimates and reflect the same genetic influences. METHODS: Registry data from primary and specialist care were available for 11 727 twins and diagnostic interview data for 2271 of these. We used logistic regression analyses and biometric modelling to investigate the overlap between the data sources. RESULTS: Most individuals meeting diagnostic criteria at interview were not registered with a corresponding diagnosis. The rates of registration were higher for MDD (36% in primary care and 15% in specialist care) and AD (21% and 18%) than for AUD (3% and 7%). Comorbidity estimated as odds ratios, but not as polychoric correlations, was higher in the registries than in the interviews. Genetic influences on the disorders were highly correlated across data sources (median r = 0.81), bordering unity for MDD and AD. CONCLUSION: Prevalence and comorbidity estimates differ between registries and population-based assessment. Nevertheless, diagnoses from health registries reflect the same genetic influences as common mental disorders assessed in the general population, indicating generalizability of aetiological factors across data sources.

Symptom severity and disability in psychiatric disorders: The U.S. Collaborative Psychiatric Epidemiology Survey.

BACKGROUND: While most psychiatric diagnoses are based on simple counts of symptoms, some symptoms may be sign of a more severe mental syndrome than others. This calls for validated estimates of the relative severity specific symptoms imply within a disorder. We focused on four diagnostic disorders: Manic Episode (ME), Major Depressive Episode (MDE), Post-traumatic Stress Disorder (PTSD) and Generalized Anxiety Disorder (GAD). Symptom-specific severity parameters were estimated, and validated by examining their association with levels of self-reported disability in daily activities over and above the number of symptoms. METHODS: Data from the cohort study of the U.S. Collaborative Psychiatric Epidemiology Surveys (CPES) was used, which comprises the National Comorbidity Survey Replication, National Survey of American Life, and the National Latino and Asian American Study. The four analytic datasets included respondents who endorsed disorder-specific pre-screening symptoms according to the World Mental Health Survey Initiative's version of the Composite International Diagnostic Interview. Disability was measured using the WHO Disability Assessment Schedule. Item Response Theory and Tobit models were implemented. RESULTS: For ME, PTSD, and GAD (not MDE) symptom severity based on psychometric Item Response Theory predicted disability outcomes after adjusting for symptom count. For PTSD, symptom count was not associated with disability. LIMITATIONS: The analytic sample for each psychiatric disorder was based on a pre-selection stemming from index criteria (e.g. sadness or pleasure loss for MDE), which implies that our results are only generalizable to those individuals at risk rather than for the entire population. Additionally, we acknowledge that the use of unidimensional models is only one of the several options to model psychopathological constructs. CONCLUSIONS: The same number of symptoms may be related to different levels of disability, depending on the specific symptoms from which the person suffers. Diagnostic procedures and treatment decisions may benefit from such additional information without extra costs.

Do DSM-5 Section II personality disorders and Section III personality trait domains reflect the same genetic and environmental risk factors?

BACKGROUND: DSM-5 includes two conceptualizations of personality disorders (PDs). The classification in Section II is identical to the one found in DSM-IV, and includes 10 categorical PDs. The Alternative Model (Section III) includes criteria for dimensional measures of maladaptive personality traits organized into five domains. The degree to which the two conceptualizations reflect the same etiological factors is not known. METHODS: We use data from a large population-based sample of adult twins from the Norwegian Institute of Public Health Twin Panel on interview-based DSM-IV PDs and a short self-report inventory that indexes the five domains of the DSM-5 Alternative Model plus a domain explicitly targeting compulsivity. Schizotypal, Paranoid, Antisocial, Borderline, Avoidant, and Obsessive-compulsive PDs were assessed at the same time as the maladaptive personality traits and 10 years previously. Schizoid, Histrionic, Narcissistic, and Dependent PDs were only assessed at the first interview. Biometric models were used to estimate overlap in genetic and environmental risk factors. RESULTS: When measured concurrently, there was 100% genetic overlap between the maladaptive trait domains and Paranoid, Schizotypal, Antisocial, Borderline, and Avoidant PDs. For OCPD, 43% of the genetic variance was shared with the domains. Genetic correlations between the individual domains and PDs ranged from +0.21 to +0.91. CONCLUSION: The pathological personality trait domains, which are part of the Alternative Model for classification of PDs in DSM-5 Section III, appears to tap, at an aggregate level, the same genetic risk factors as the DSM-5 Section II classification for most of the PDs.