The cross-national epidemiology of specific phobia in the World Mental Health Surveys.

BACKGROUND: Although specific phobia is highly prevalent, associated with impairment, and an important risk factor for the development of other mental disorders, cross-national epidemiological data are scarce, especially from low- and middle-income countries. This paper presents epidemiological data from 22 low-, lower-middle-, upper-middle- and high-income countries. METHOD: Data came from 25 representative population-based surveys conducted in 22 countries (2001-2011) as part of the World Health Organization World Mental Health Surveys initiative (n = 124 902). The presence of specific phobia as defined by the Diagnostic and Statistical Manual of Mental Disorders, fourth edition was evaluated using the World Health Organization Composite International Diagnostic Interview. RESULTS: The cross-national lifetime and 12-month prevalence rates of specific phobia were, respectively, 7.4% and 5.5%, being higher in females (9.8 and 7.7%) than in males (4.9% and 3.3%) and higher in high- and higher-middle-income countries than in low-/lower-middle-income countries. The median age of onset was young (8 years). Of the 12-month patients, 18.7% reported severe role impairment (13.3-21.9% across income groups) and 23.1% reported any treatment (9.6-30.1% across income groups). Lifetime co-morbidity was observed in 60.5% of those with lifetime specific phobia, with the onset of specific phobia preceding the other disorder in most cases (72.6%). Interestingly, rates of impairment, treatment use and co-morbidity increased with the number of fear subtypes. CONCLUSIONS: Specific phobia is common and associated with impairment in a considerable percentage of cases. Importantly, specific phobia often precedes the onset of other mental disorders, making it a possible early-life indicator of psychopathology vulnerability.

The effects of co-morbidity in defining major depression subtypes associated with long-term course and severity.

BACKGROUND: Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question. METHOD: Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes. RESULTS: Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6-72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors. CONCLUSIONS: Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.

A comparative analysis of role attainment and impairment in binge-eating disorder and bulimia nervosa: results from the WHO World Mental Health Surveys.

Background. Cross-national population data from the WHO World Mental Health surveys are used to compare role attainments and role impairments associated with binge-eating disorder (BED) and bulimia nervosa (BN). Methods. Community surveys assessed 23 000 adults across 12 countries for BED, BN and ten other DSM-IV mental disorders using the WHO Composite International Diagnostic Interview. Age-of-onset was assessed retrospectively. Ten physical disorders were assessed using standard conditions checklists. Analyses examined reciprocal time-lagged associations of eating disorders (EDs) with education, associations of early-onset (i.e., prior to completing education) EDs with subsequent adult role attainments and cross-sectional associations of current EDs with days of role impairment. Results. BED and BN predicted significantly increased education (females). Student status predicted increased risk of subsequent BED and BN (females). Early-onset BED predicted reduced odds of current (at time of interview) marriage (females) and reduced odds of current employment (males). Early-onset BN predicted increased odds of current work disability (females and males). Current BED and BN were both associated with significantly increased days of role impairment (females and males). Significant BED and BN effects on adult role attainments and impairments were explained by controls for comorbid disorders. Conclusions. Effects of BED on role attainments and impairments are comparable with those of BN. The most plausible interpretation of the fact that these associations are explained by comorbid disorders is that causal effects of EDs are mediated through secondary disorders. Controlled treatment effectiveness studies are needed to trace out long-term effects of BED-BN on secondary disorders.