Article

Subtypes of depression in a nationally representative sample

Psychology Research Institute, University of Ulster at Magee, Derry, Northern Ireland, United Kingdom.
Journal of Affective Disorders (Impact Factor: 3.71). 02/2009; 113(1-2):88-99. DOI: 10.1016/j.jad.2008.05.015
Source: PubMed

ABSTRACT Continued research efforts aim to elucidate the heterogeneity in depression. The identification of meaningful and valid subtypes has implications for research and clinical practice. Based on patterns of depressive symptomatology, this study identified a typology of depressive syndromes using data from a large, nationally representative survey.
Analyses were based on a subsample of 12,180 respondents from the 2001-2002 Wave of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Latent class analysis was applied to the DSM-IV 'A' criteria for major depression to identify homogenous subtypes or classes of depressive syndromes. Associations between the emergent latent classes and demographic and clinical characteristics were assessed.
Three clinically relevant subtypes were identified, in addition to a class who reported few depressive symptoms: severely depressed (40.9%), psychosomatic (30.6%), cognitive-emotional (10.2%) and non-depressed (18.3%). The odds of experiencing negative life events, psychiatric disorders, and having a family background of major depression were significantly higher for the severely depressed, psychosomatic and cognitive-emotional classes, compared to the non-depressed class. Several unique differences between the latent classes also emerged.
Methodological shortcomings included: reliance on lay interviewer-administered structured interviews to determine diagnoses; basing sample selection on the endorsement of screener items; and, using measures of 'any anxiety disorder', 'any mood disorder', and 'any personality disorder' to determine psychiatric disorder prevalence rates.
Significant heterogeneity in depressive symptomatology exists in this U.S. sample. Profiling symptom patterns is potentially useful as a first step in developing tailored intervention and treatment programmes.

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