F A Torvik1,2, E Ystrom1,2,3, K Gustavson1,2, T H Rosenström1, J G Bramness4, N Gillespie5, S H Aggen5, K S Kendler5,6, T Reichborn-Kjennerud1,7. 1. Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway. 2. Department of Psychology, University of Oslo, Oslo, Norway. 3. PharmacoEpidemiology and Drug Safety Research Group, School of Pharmacy, University of Oslo, Oslo, Norway. 4. Norwegian National Advisory Unit on Concurrent Substance Abuse and Mental Health Disorders, Brumunddal, Norway. 5. Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA. 6. Department of Human and Molecular Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA. 7. Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Abstract
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.
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.
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