Education differences in sickness absence and the role of health behaviors: a prospective twin study.

BACKGROUND: Long-term sickness absences burden the economy in many industrialized countries. Both educational attainment and health behaviors are well-known predictors of sickness absence. It remains, however, unclear whether these associations are causal or due to confounding factors. The co-twin control method allows examining causal hypotheses by controlling for familial confounding (shared genes and environment). In this study, we applied this design to study the role of education and health behaviors in sickness absence, taking sex and cohort differences into account. METHODS: Participants were two cohorts of in total 8806 Norwegian twins born 1948 to 1960 (older cohort, mean age at questionnaire = 40.3, 55.8% women), and 1967 to 1979 (younger cohort, mean age at questionnaire = 25.6, 58.9% women). Both cohorts had reported their health behaviors (smoking, physical activity and body mass index (BMI)) through a questionnaire during the 1990s. Data on the twins' educational attainment and long-term sickness absences between 2000 and 2014 were retrieved from Norwegian national registries. Random (individual-level) and fixed (within-twin pair) effects regression models were used to measure the associations between educational attainment, health behaviours and sickness absence and to test the effects of possible familial confounding. RESULTS: Low education and poor health behaviors were associated with a higher proportion of sickness absence at the individual level. There were stronger effects of health behaviors on sickness absence in women, and in the older cohort, whereas the effect of educational attainment was similar across sex and cohorts. After adjustment for unobserved familial factors (genetic and environmental factors shared by twin pairs), the associations were strongly attenuated and non-significant, with the exception of health behaviors and sickness absence among men in the older cohort. CONCLUSIONS: The associations between educational attainment, health behaviors, and sickness absence seem to be confounded by unobserved familial factors shared by co-twins. However, the association between health behaviors and sickness absence was consistent with a causal effect among men in the older cohort. Future studies should consider familial confounding, as well as sex and age/cohort differences, when assessing associations between education, health behaviors and sickness absence.

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.

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.

The association between personality disorders with alcohol use and misuse: A population-based twin study.

BACKGROUND: A clearer understanding of the etiological overlap between DSM-IV personality disorders (PDs) and alcohol use (AU) and alcohol use disorder (AUD) is needed. To our knowledge, no study has modeled the association between all 10 DSM-IV PDs and lifetime AU and AUD. The aim of the present study is to identify which PDs are most strongly associated with the phenotypic, genetic, and environmental risks of lifetime AU and AUD, and to determine if these associations are stable across time. METHODS: Participants were Norwegian twins assessed at two waves. At Wave 1, 2801 twins were assessed for all 10 DSM-IV PD criteria, lifetime AU, and DSM-IV AUD criteria. At Wave 2, six of the 10 PDs were again assessed along with AU and AUD among 2393 twins. Univariate and multiple logistic regressions were run. Significant predictors were further analyzed using bivariate twin Cholesky decompositions. RESULTS: Borderline and antisocial PD criteria were the strongest predictors of AU and AUD across the two waves. Despite moderate phenotypic and genetic correlations, genetic variation in these PD criteria explained only 4% and 3% of the risks in AU, and 5% to 10% of the risks in AUD criteria, respectively. At Wave 2, these estimates increased to 8% and 23% for AU, and 17% and 33% for AUD. CONCLUSIONS: Among a large Norwegian twin sample, borderline and antisocial PD criteria were the strongest predictors of the phenotypic and genotypic liability to AU and AUD. This effect remained consistent across time.