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: 3.38). 02/2009; 113(1-2):88-99. DOI: 10.1016/j.jad.2008.05.015
Source: PubMed


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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    • "Here, subthreshold subtypes could be identified as well. The studies which based their analyses on a subsample of respondents with at least one key symptom of depression (Alexandrino-Silva et al., 2013; Carragher et al., 2009; Lee et al., 2014; Prisciandaro and Roberts, 2009; Rodgers et al., 2013; 2014; Sullivan et al., 1998; 2002) generally found a number of inbetween classes: typical, atypical, moderate and mild. Differences in study sample, design, diagnostic instrument and statistical method used thus hinder a refined comparison of the qualitative distinctions of the previously found subtypes. "
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    ABSTRACT: Background: In recent years, researchers have used various techniques to elucidate the heterogeneity in depressive symptoms. This study seeks to resolve the extent to which variations in depression reflect qualitative differences between symptom categories and/or quantitative differences in severity. Methods: Data were used from the Netherlands Mental Health Survey and Incidence Study-2, a nationally representative face-to-face survey of the adult general population. In a subsample of respondents with a lifetime key symptom of depression at baseline and who participated in the first two waves (n=1388), symptom profiles at baseline were based on symptoms reported during their worst lifetime depressive episode. Depressive symptoms and DSM-IV diagnoses were assessed with the Composite International Diagnostic Interview 3.0. Three latent variable techniques (latent class analysis, factor analysis, factor mixture modelling) were used to identify the best subtyping model. Results: A latent class analysis, adjusted for local dependence between weight change and appetite change, described the data best and resulted in four distinct depressive subtypes: severe depression with anxiety (28.0%), moderate depression with anxiety (29.3%), moderate depression without anxiety (23.6%) and mild depression (19.0%). These classes showed corresponding clinical correlates at baseline and corresponding course and outcome indicators at follow-up (i.e., class severity was linked to lifetime mental disorders at baseline, and service use for mental health problems and current disability at follow-up). Limitations: Although the sample was representative of the population on most parameters, the findings are not generalisable to the most severely affected depressed patients. Conclusions: Depression could best be described in terms of both qualitative differences between symptom categories and quantitative differences in severity. In particular anxiety was a distinguishing feature within moderate depression. This study stresses the central position anxiety occupies in the concept of depression.
    Journal of Affective Disorders 10/2015; 190. DOI:10.1016/j.jad.2015.10.040 · 3.38 Impact Factor
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    • "Odds ratios ( OR ) and 95% confidence intervals ( CI ) were used to evaluate these associations : ORs reflect the proportionate change in odds of membership of a given class , relative to the ref - erence class , associated with a one - unit change in the covariate ( Carragher et al . , 2009 ) ."
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    ABSTRACT: Aims:To develop a stability typology among opioid substitution therapy patients using a range of adherence indicators derived from clinical guidelines, and determine whether stable patients receive more unsupervised doses. Methods An interviewer-administered cross-sectional survey was used in opioid substitution therapy programs in three Australian jurisdictions, totalling 768 patients in their current treatment episode for ≥4 weeks. A structured questionnaire collated data from patients about their demographics, treatment characteristics, past 6-month drug use and medication adherence, psychosocial stability, comorbidity, child welfare concerns and levels of supervised dosing. Latent class analysis (LCA) was used to derive a stability typology. Linear regression models examined predictors of unsupervised dosing in the past month. Results LCA identified two classes: (i) a higher-adherence group (67%) who had low-moderate probabilities of endorsing the opioid substitution therapy stability indicators and (ii) a lower-adherence group (33%) who had moderate-high probabilities of endorsing the stability indicators. There was no association between adherence profile and the number of unsupervised doses. Significant predictors of receiving larger numbers of unsupervised doses included being older, living in New South Wales or South Australia (vs. Victoria), receiving methadone (vs. mono-buprenorphine), being prescribed in private clinic or general practice (vs. public clinic), reporting a longer current treatment episode, not receiving a urine drug screen in the past month, being currently employed and not having a prison history. Conclusions This study suggested that system-level factors and observable indicators of social functioning were more strongly associated with receipt of less supervised treatment. Future research should examine this using prospectively collected data.
    Drug and Alcohol Dependence 09/2014; 142. DOI:10.1016/j.drugalcdep.2014.05.018 · 3.42 Impact Factor
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    • "The latent class model assumes that each class is internally homogeneous, i.e., the probability of engaging in a particular behavior is the same for all members belonging to a particular class (Lazarsfeld and Henry, 1968). In order to choose the final model of LCA, we used the Bayesian Information Criterion [BIC] (Nylund, 2007) to indicate the most parsimonious solution (Hagenaars and McCutcheon, 2002; Weich et al., 2011), and entropy, to express how well each class is classified (Carragher et al., 2009). We ran multiple-group LCA in the general sample to examine whether symptomatological profiles among classes were different across the male and female samples. "
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    ABSTRACT: BACKGROUND: Few studies have investigated symptomatic subtypes of depression and their correlates by gender. METHODS: Data are from the São Paulo Megacity Mental Health Survey. Symptom profiles of 1207 subjects (864 women; 343 men) based upon symptoms of the worst depressive episode in lifetime were examined through latent class analysis. Correlates of gender-specific latent classes were analyzed by logistic regression. RESULTS: For both men and women, a 3-class model was the best solution. A mild class was found in both genders (41.1% in women; 40.1% in men). Gender differences appeared in the most symptomatic classes. In women, they were labeled melancholic (39.3%) and atypical (19.5%), differing among each other in somatic/vegetative symptoms. The melancholic class presented inhibition and eating/sleeping symptoms in the direction of decreasing, whereas the atypical class had increased appetite/weight, and hypersomnia. For men, symptoms that differentiate the two most symptomatic classes were related to psychomotor activity: a melancholic/psychomotor retarded (40.4%) and agitated depression (19.6%). The highest between-class proportion of agitation and racing thoughts was found among men in the agitated class, with similarity to bipolar mixed state. LIMITATIONS: Analyses were restricted to those who endorsed questions about their worst lifetime depressive episode; the standardized assessment by lay interviewers; the small male sample size. CONCLUSIONS: The construct of depression of current classifications is heterogeneous at the symptom level, where gender different subtypes can be identified. These symptom profiles have potential implications for the nosology and the therapeutics of depression.
    Journal of Affective Disorders 12/2012; 147(1-3). DOI:10.1016/j.jad.2012.11.041 · 3.38 Impact Factor
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