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On the basis of epidemiological survey findings, anxiety disorders are the most prevalent mental disorders around the world and are associated with significant comorbidity and morbidity. Such surveys rely on advances in psychiatric nosology and may also contribute usefully to revisions of the nosology. There are a number of questions at the intersection of psychiatric epidemiology and nosology. This review addresses the following: What is the prevalence of anxiety disorders and how do we best explain cross-national differences in prevalence estimates? What are the optimal diagnostic criteria for anxiety disorders, and how can epidemiological data shed light on this question? What are the comorbidities of anxiety disorders, and how do we best understand the high comorbidities seen in these conditions? What is the current treatment gap for anxiety disorders, and what are the implications of current understandings of psychiatric epidemiology and nosology for policy-making relevant to anxiety disorders? Here, we emphasize that anxiety disorders are the most prevalent of the psychiatric conditions, and that rather than merely contrasting cross-national prevalence in anxiety disorders, it is more productive to delineate cross-national themes that emerge about the epidemiology of these conditions. We discuss that optimizing diagnostic criteria for anxiety disorders is an iterative process to which epidemiological data can make a crucial contribution. Additionally, high comorbidity in anxiety disorders is not merely artefactual; it provides key opportunities to explore pathways to mental disorders and to intervene accordingly. Finally, work on the epidemiology and nosology of anxiety disorders has provided a number of important targets for mental health policy and for future integrative work to move between bench and bedside, as well as between clinic and community.

Citation

Dan J Stein, Kate M Scott, Peter de Jonge, Ronald C Kessler. Epidemiology of anxiety disorders: from surveys to nosology and back. Dialogues in clinical neuroscience. 2017 Jun;19(2):127-136


PMID: 28867937

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