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1.
Epidemiol Psychiatr Sci ; 29: e153, 2020 Aug 12.
Article in English | MEDLINE | ID: mdl-32782057

ABSTRACT

AIMS: Epidemiological studies indicate that individuals with one type of mental disorder have an increased risk of subsequently developing other types of mental disorders. This study aimed to undertake a comprehensive analysis of pair-wise lifetime comorbidity across a range of common mental disorders based on a diverse range of population-based surveys. METHODS: The WHO World Mental Health (WMH) surveys assessed 145 990 adult respondents from 27 countries. Based on retrospectively-reported age-of-onset for 24 DSM-IV mental disorders, associations were examined between all 548 logically possible temporally-ordered disorder pairs. Overall and time-dependent hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazards models. Absolute risks were estimated using the product-limit method. Estimates were generated separately for men and women. RESULTS: Each prior lifetime mental disorder was associated with an increased risk of subsequent first onset of each other disorder. The median HR was 12.1 (mean = 14.4; range 5.2-110.8, interquartile range = 6.0-19.4). The HRs were most prominent between closely-related mental disorder types and in the first 1-2 years after the onset of the prior disorder. Although HRs declined with time since prior disorder, significantly elevated risk of subsequent comorbidity persisted for at least 15 years. Appreciable absolute risks of secondary disorders were found over time for many pairs. CONCLUSIONS: Survey data from a range of sites confirms that comorbidity between mental disorders is common. Understanding the risks of temporally secondary disorders may help design practical programs for primary prevention of secondary disorders.


Subject(s)
Mental Disorders/epidemiology , Adolescent , Adult , Aged , Comorbidity , Cross-Sectional Studies , Diagnostic and Statistical Manual of Mental Disorders , Female , Health Surveys , Humans , Male , Mental Disorders/classification , Middle Aged , Prevalence , Proportional Hazards Models , Psychotic Disorders/epidemiology , Retrospective Studies , Risk Factors , Young Adult
2.
Psychol Med ; 44(4): 707-22, 2014 Mar.
Article in English | MEDLINE | ID: mdl-23721650

ABSTRACT

BACKGROUND: The World Mental Health Survey Initiative (WMHSI) has advanced our understanding of mental disorders by providing data suitable for analysis across many countries. However, these data have not yet been fully explored from a cross-national lifespan perspective. In particular, there is a shortage of research on the relationship between mood and anxiety disorders and age across countries. In this study we used multigroup methods to model the distribution of 12-month DSM-IV/CIDI mood and anxiety disorders across the adult lifespan in relation to determinants of mental health in 10 European Union (EU) countries. METHOD: Logistic regression was used to model the odds of any mood or any anxiety disorder as a function of age, gender, marital status, urbanicity and employment using a multigroup approach (n = 35500). This allowed for the testing of specific lifespan hypotheses across participating countries. RESULTS: No simple geographical pattern exists with which to describe the relationship between 12-month prevalence of mood and anxiety disorders and age. Of the adults sampled, very few aged ≥ 80 years met DSM-IV diagnostic criteria for these disorders. The associations between these disorders and key sociodemographic variables were relatively homogeneous across countries after adjusting for age. CONCLUSIONS: Further research is required to confirm that there are indeed stages in the lifespan where the reported prevalence of mental disorders is low, such as among younger adults in the East and older adults in the West. This project illustrates the difficulties in conducting research among different age groups simultaneously.


Subject(s)
Anxiety Disorders/epidemiology , Global Health , Mood Disorders/epidemiology , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Europe/epidemiology , Female , Global Health/statistics & numerical data , Humans , Logistic Models , Male , Middle Aged , Prevalence , Time Factors , Young Adult
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