Skip to main content Accessibility help
×
Home
Hostname: page-component-888d5979f-jgqf9 Total loading time: 0.266 Render date: 2021-10-28T09:37:52.378Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": true, "newCiteModal": false, "newCitedByModal": true, "newEcommerce": true, "newUsageEvents": true }

Course trajectories of unipolar depressive disorders identified by latent class growth analysis

Published online by Cambridge University Press:  07 November 2011

D. Rhebergen*
Affiliation:
Department of Psychiatry and the EMGO Institute for Health and Care Research, VU University Medical Center Amsterdam, The Netherlands
F. Lamers
Affiliation:
Department of Psychiatry and the EMGO Institute for Health and Care Research, VU University Medical Center Amsterdam, The Netherlands
J. Spijker
Affiliation:
Netherlands Institute of Mental Health and Addiction, Utrecht, The Netherlands De Gelderse Roos, Arnhem, The Netherlands
R. de Graaf
Affiliation:
Netherlands Institute of Mental Health and Addiction, Utrecht, The Netherlands
A. T. F. Beekman
Affiliation:
Department of Psychiatry and the EMGO Institute for Health and Care Research, VU University Medical Center Amsterdam, The Netherlands
B. W. J. H. Penninx
Affiliation:
Department of Psychiatry and the EMGO Institute for Health and Care Research, VU University Medical Center Amsterdam, The Netherlands
*
*Address for correspondence: Dr D. Rhebergen, Department of Psychiatry, VU University Medical Center Amsterdam, A.J. Ernststraat 887, 1081 HL Amsterdam, The Netherlands. (Email: d.rhebergen@ggzingeest.nl)

Abstract

Background

Current classification of unipolar depression reflects the idea that prognosis is essential. However, do DSM categories of major depressive disorder (MDD), dysthymic disorder (Dysth) and double depression (DD=MDD+Dysth) indeed adequately represent clinically relevant course trajectories of unipolar depression? Our aim was to test DSM categories (MDD, Dysth and DD) in comparison with empirically derived prognostic categories, using a prospectively followed cohort of depressed patients.

Method

A large sample (n=804) of out-patients with unipolar depression were derived from a prospective cohort study, the Netherlands Study of Depression and Anxiety (NESDA). Using latent class growth analysis (LCGA), empirically derived 2-year course trajectories were constructed. These were compared with DSM diagnoses and a wider set of putative predictors for class membership.

Results

Five course trajectories were identified, ranging from mild severity and rapid remission to high severity and chronic course trajectory. Contrary to expectations, more than 50% of Dysth and DD were allocated to classes with favorable course trajectories, suggesting that current DSM categories do not adequately represent course trajectories. The class with the most favorable course trajectory differed on several characteristics from other classes (younger age, more females, less childhood adversity, less somatic illnesses, lower neuroticism, higher extraversion). Older age, earlier age of onset and lower extraversion predicted poorest course trajectory.

Conclusions

MDD, Dysth and DD did not adequately match empirically derived course trajectories for unipolar depression. For the future classification of unipolar depression, it may be wise to retain the larger, heterogeneous category of unipolar depression, adopting cross-cutting dimensions of severity and duration to further characterize patients.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Angst, J, Gamma, A, Rossler, W, Ajdacic, V, Klein, D (2009). Long-term depression versus episodic major depression: results from the prospective Zurich study of a community sample. Journal of Affective Disorder 115, 112121.CrossRefGoogle ScholarPubMed
Angst, J, Wicki, W (1991). The Zurich Study. XI. Is dysthymia a separate form of depression? Results of the Zurich Cohort Study. European Archives of Psychiatry and Clinical Neuroscience 240, 349354.CrossRefGoogle ScholarPubMed
Bijl, R, Van Zessen, G, Ravelli, A, De Rijk, C, Langendoen, Y (1998). The Netherlands Mental Health Survey and Incidence Study (NEMESIS): objectives and design. Social Psychiatry and Psychiatric Epidemiology 33, 581586.CrossRefGoogle Scholar
Campbell, SB, Morgan-Lopez, AA, Cox, MJ, McLoyd, VC (2009). A latent class analysis of maternal depressive symptoms over 12 years and offspring adjustment in adolescence. Journal of Abnormal Psychology 118, 479493.CrossRefGoogle ScholarPubMed
Chwastiak, LA, Von Korff, M (2003). Disability in depression and back pain: evaluation of the World Health Organization Disability Assessment Schedule (WHO DAS II) in a primary care setting. Journal of Clinical Epidemiology 56, 507514.CrossRefGoogle Scholar
Colman, I, Ploubidis, GB, Wadsworth, MEJ, Jones, PB, Croudace, TJ (2007). A longitudinal typology of symptoms of depression and anxiety over the life course. Biological Psychiatry 62, 12651271.CrossRefGoogle ScholarPubMed
Costa, PT, McCrae, RR (1995). Domains and facets: hierarchical personality assessment using the revised NEO personality inventory. Journal of Personality Assessment 64, 2150.CrossRefGoogle ScholarPubMed
Fyer, AJ, Weissman, MM (1999). Genetic linkage study of panic: clinical methodology and description of pedigrees. American Journal of Medical Genetics 88, 173181.3.0.CO;2-#>CrossRefGoogle ScholarPubMed
Hayden, EP, Klein, DN (2001). Outcome of dysthymic disorder at 5-year follow-up: the effect of familial psychopathology, early adversity, personality, comorbidity, and chronic stress. American Journal of Psychiatry 158, 18641870.CrossRefGoogle ScholarPubMed
Judd, LL, Akiskal, HS (2000). Delineating the longitudinal structure of depressive illness: beyond clinical subtypes and duration thresholds. Pharmacopsychiatry 33, 37.CrossRefGoogle ScholarPubMed
Judd, LL, Schettler, PJ, Akiskal, HS (2002). The prevalence, clinical relevance, and public health significance of subthreshold depressions. Psychiatric Clinics of North America 25, 685698.CrossRefGoogle ScholarPubMed
Jung, T, Wickrama, K (2008). An introduction to LCGA and GMM. Social and Personality Psychology Compass 2, 302317.CrossRefGoogle Scholar
Keller, MB, Lavori, PW (1984). Double depression, major depression, and dysthymia: distinct entities or different phases of a single disorder? Psychopharmacology Bulletin 20, 399402.Google ScholarPubMed
Kendler, KS, Fiske, A, Gardner, CO, Gatz, M (2009). Delineation of two genetic pathways to major depression. Biological Psychiatry 65, 808811.CrossRefGoogle ScholarPubMed
Klein, DN, Schatzberg, AF, McCullough, JP, Keller, MB, Dowling, F, Goodman, D, Howland, RH, Markowitz, JC, Smith, C, Miceli, R, Harrison, WM (1999). Early- versus late-onset dysthymic disorder: comparison in out-patients with superimposed major depressive episodes. Journal of Affective Disorders 52, 187196.CrossRefGoogle ScholarPubMed
Klein, DN, Shankman, SA, Rose, S (2006). Ten-year prospective follow-up study of the naturalistic course of dysthymic disorder and double depression. American Journal of Psychiatry 163, 872880.CrossRefGoogle ScholarPubMed
Lamers, F, Hoogendoorn, A, Smit, J, van Dyck, R, Zitman, FG, Nolen, WA, Penninx, BW (2011). Sociodemographic and psychiatric determinants of attrition in the Netherlands Study of Depression and Anxiety (NESDA). Comprehensive Psychiatry. Published online: 10 March 2011. doi:10.1016/j.comppsych.2011.01.011.Google Scholar
Li, LW (2005). From caregiving to bereavement: trajectories of depressive symptoms among wife and daughter caregivers. Journal of Gerontology 60, 154168.Google ScholarPubMed
Lyketsos, C, Nestadt, G (1994). The life-chart method to describe the course of psychopathology. International Journal of Methods in Psychiatric Research 4, 143155.Google Scholar
Lyons, MJ, Eisen, SA, Goldberg, J, True, W, Lin, N, Meyer, JM, Toomey, R, Faraone, SV, Merla-Ramos, M, Tsuang, MT (1998). A registry-based twin study of depression in men. Archives of General Psychiatry 55, 468472.CrossRefGoogle ScholarPubMed
McCullough, JP, Klein, DN, Borian, FE, Howland, RH, Riso, LP, Keller, MB, Banks, PL (2003). Group comparisons of DSM-IV subtypes of chronic depression: validity of the distinctions, Part 2. Journal of Abnormal Psychology 112, 614622.CrossRefGoogle ScholarPubMed
McCullough, JP, Klein, DN, Keller, MB, Holzer, CE, Davis, SM, Kornstein, SG, Howland, RH, Thase, ME, Harrison, WM (2000). Comparison of DSM-III-R chronic major depression and major depression superimposed on dysthymia (double depression): validity of the distinction. Journal of Abnormal Psychology 109, 419427.CrossRefGoogle ScholarPubMed
Mondimore, FM, Zandi, PP, Mackinnon, DF, McInnis, MG, Miller, EB, Crowe, RP, Scheftner, WA, Marta, DH, Weissman, MM, Levinson, DF, Murphy-Ebenez, KP, Depaulo, JR, Potash, JB (2006). Familial aggregation of illness chronicity in recurrent, early-onset major depression pedigrees. American Journal of Psychiatry 163, 15541560.CrossRefGoogle ScholarPubMed
Muthén, LK, Muthén, BO (2007). Mplus User's Guide. Fifth Edition. Muthén & Muthén: Los Angeles, CA.Google Scholar
Nandi, A, Beard, JR, Galea, S (2009). Epidemiologic heterogeneity of common mood and anxiety disorders over the lifecourse in the general population: a systematic review. BMC Psychiatry 9, 31.CrossRefGoogle ScholarPubMed
Nylund, KL, Asparouhov, T, Muthén, BO (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Structural Equation Modeling 14, 535569.CrossRefGoogle Scholar
Olino, TM, Klein, DN, Lewinsohn, PM, Rohde, P, Seeley, JR (2010). Latent trajectory classes of depressive and anxiety disorders from adolescence to adulthood: description of classes and associations with risk factors. Comprehensive Psychiatry 51, 224235.CrossRefGoogle Scholar
Ormel, J, Oldehinkel, AJ, Nolen, WA, Vollebergh, W (2004). Psychosocial disability before, during, and after a major depressive episode: a 3-wave population-based study of state, scar, and trait effects. Archives of General Psychiatry 61, 387392.CrossRefGoogle Scholar
Penninx, BW, Beekman, AT, Smit, JH, Zitman, FG, Nolen, WA, Spinhoven, P, Cuijpers, P, De Jong, PJ, Van Marwijk, HW, Assendelft, WJ, Van der Meer, K, Verhaak, P, Wensing, M, De Graaf, R, Hoogendijk, WJ, Ormel, J, Van Dyck, R (2008). The Netherlands Study of Depression and Anxiety (NESDA): rationale, objectives and methods. International Journal of Methods in Psychiatric Research 17, 21–140.CrossRefGoogle ScholarPubMed
Rhebergen, D, Batelaan, NM, De Graaf, R, Nolen, WA, Spijker, J, Beekman, ATF, Penninx, BWJH (2011). The 7-year course of depression and anxiety in the general population. Acta Psychiatrica Scandinavica 123, 297306.CrossRefGoogle ScholarPubMed
Rhebergen, D, Beekman, AT, De Graaf, R, Nolen, WA, Spijker, J, Hoogendijk, WJ, Penninx, BW (2009). The three-year naturalistic course of major depressive disorder, dysthymic disorder and double depression. Journal of Affective Disorders 115, 450459.CrossRefGoogle ScholarPubMed
Robison, EJ, Shankman, SA, McFarland, BR (2009). Independent associations between personality traits and clinical characteristics of depression. Journal of Nervous and Mental Disorders 197, 476483.CrossRefGoogle Scholar
Rush, AJ, Giles, DE, Schlesser, MA, Fulton, CL, Weissenburger, J, Burns, C (1986). The Inventory for Depressive Symptomatology (IDS): preliminary findings. Psychiatry Research 18, 6587.CrossRefGoogle ScholarPubMed
Rush, AJ, Gullion, CM, Basco, MR, Jarrett, RB, Trivedi, MH (1996). The Inventory of Depressive Symptomatology (IDS): psychometric properties. Psychological Medicine 26, 477486.CrossRefGoogle ScholarPubMed
Shankman, SA, Klein, DN (2002). Dimensional diagnosis of depression: adding the dimension of course to severity, and comparison to the DSM. Comprehensive Psychiatry 43, 420426.CrossRefGoogle ScholarPubMed
Skipstein, A, Janson, H, Stoolmiller, M, Mathiesen, KS (2010). Trajectories of maternal symptoms of anxiety and depression. A 13-year longitudinal study of a population-based sample. BMC Public Health 10, 589.CrossRefGoogle ScholarPubMed
Spijker, J, De Graaf, R, Bijl, RV, Beekman, AT, Ormel, J, Nolen, WA (2002). Duration of major depressive episodes in the general population: results from The Netherlands Mental Health Survey and Incidence Study (NEMESIS). British Journal of Psychiatry 181, 208213.CrossRefGoogle Scholar
Stoolmiller, M, Kim, HK, Capaldi, DM (2005). The course of depressive symptoms in men from early adolescence to young adulthood: identifying latent trajectories and early predictor. Journal of Abnormal Psychology 114, 331345.CrossRefGoogle Scholar
Sullivan, PF, Kessler, RC, Kendler, KS (1998). Latent class analysis of lifetime depressive symptoms in the National Comorbidity Survey. American Journal of Psychiatry 155, 13981406.CrossRefGoogle ScholarPubMed
Taylor, DH, Ezell, M, Kuchibhatla, M, Ostbye, T, Clipp, EC (2008). Identifying trajectories of depressive symptoms for women caring for their husbands with dementia. Journal of the American Geriatrics Society 16, 322327.CrossRefGoogle Scholar
Vuorilehto, MS, Melartin, TK, Isometsa, ET (2009). Course and outcome of depressive disorders in primary care: a prospective 18-month study. Psychological Medicine 39, 16971707.CrossRefGoogle ScholarPubMed
WHO (1998). Composite International Diagnostic Interview (CIDI), version 2.1. World Health Organization: Geneva.Google Scholar
Wiersma, JE, Hovens, JG, van Oppen, P, Giltay, EJ, van Schaik, DJ, Beekman, AT, Penninx, BW (2009). The importance of childhood trauma and childhood life events for chronicity of depression in adults. Journal of Clinical Psychiatry 70, 983989.CrossRefGoogle ScholarPubMed
Wiersma, JE, van Oppen, P, van Schaik, DJF, van der Does, AJW, Beekman, ATF, Penninx, BWJH (2011). Psychological characteristics of chronic depression: a longitudinal cohort study. Journal of Clinical Psychiatry 72, 288294.CrossRefGoogle ScholarPubMed
Wittchen, HU (1994). Reliability and validity studies of the WHO-Composite International Diagnostic Interview (CIDI): a critical review. Journal of Psychiatric Research 28, 5784.CrossRefGoogle ScholarPubMed
Wittchen, HU, Zhao, S, Abelson, JM, Abelson, JL, Kessler, RC (1996). Reliability and procedural validity of UM-CIDI DSM-III-R phobic disorders. Psychological Medicine 26, 11691177.CrossRefGoogle Scholar
Yang, T, Dunner, DL (2001). Differential subtyping of depression. Depression and Anxiety 13, 1117.3.0.CO;2-W>CrossRefGoogle Scholar
48
Cited by

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Course trajectories of unipolar depressive disorders identified by latent class growth analysis
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Course trajectories of unipolar depressive disorders identified by latent class growth analysis
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Course trajectories of unipolar depressive disorders identified by latent class growth analysis
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *