Hostname: page-component-848d4c4894-wg55d Total loading time: 0 Render date: 2024-05-18T07:16:20.679Z Has data issue: false hasContentIssue false
  • English
  • Français

A prospective latent analysis study of Axis I psychiatric co-morbidity of DSM-IV major depressive disorder

Published online by Cambridge University Press:  09 July 2013

T. Melartin ,
O. Mantere ,
M Ketokivi  and
E. Isometsä
T. Melartin
Affiliation:
Mood, Depression and Suicidal Behavior Unit, Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, Helsinki, Finland Department of Psychiatry, Helsinki University Central Hospital, Helsinki, Finland
O. Mantere
Affiliation:
Mood, Depression and Suicidal Behavior Unit, Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, Helsinki, Finland Department of Psychiatry, Jorvi Hospital, Helsinki University Central Hospital, Espoo, Finland
M Ketokivi
Affiliation:
Operations and Technology Department, IE Business School, Madrid, Spain
E. Isometsä*
Affiliation:
Mood, Depression and Suicidal Behavior Unit, Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, Helsinki, Finland Department of Psychiatry, Helsinki University Central Hospital, Helsinki, Finland Department of Psychiatry, University of Helsinki, Helsinki, Finland
*
*Address for correspondence: E. T. Isometsä, M.D., Ph.D., Professor of Psychiatry, Department of Psychiatry, Institute of Clinical Medicine, University of Helsinki, PO Box 22, FI-00014 Helsinki, Finland. (Email: erkki.isometsa@hus.fi)
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

We tested the degree to which longitudinal observations fit two hypotheses of psychiatric co-morbidity in DSM-IV major depressive disorder (MDD) among adult patients: (1) Axis I co-morbidity is dependent on major depressive episode (MDE) course, and (2) Axis I co-morbidity is independent of MDE course.

Method

In the Vantaa Depression Study (VDS), 269 psychiatric secondary-care patients with a DSM-IV MDD were evaluated with the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) at intake and at 6 and 18 months. Three evaluations of co-morbidity were available for 193 out of 259 living patients (75%). A latent curve model (LCM) was used to examine individual-level changes in depressive and anxiety symptoms across time. Outcome of MDD was modeled in terms of categorical DSM-IV diagnosis and Beck Depression Inventory (BDI) and Hamilton Depression Rating Scale (HAMD) scores, and co-morbidity in terms of categorical DSM-IV anxiety and alcohol use disorder (AUD) diagnoses and Beck Anxiety Inventory (BAI) scores.

Results

Depression and anxiety correlated cross-sectionally at baseline. Longitudinally, changes in depression and anxiety correlated in both the 0–6 and 6–18 months time windows. Higher baseline depression raised the likelihood of an AUD at 6 months, and patients with more depressive symptoms in the 0–6 months time window were more likely to have had an AUD at 6 months, which further linked to less improvement in depression symptoms in the 6–18 months time window.

Conclusions

Longitudinal and individual-level courses of both internalizing and externalizing disorders in adult patients with MDD seem to be dependent, albeit to differing degrees, on the course of depressive symptoms.

Keywords

Co-morbiditylatent curve modelsmajor depressive disorderprospective studies
Type
Original Articles
Information
Psychological Medicine , Volume 44 , Issue 5 , April 2014 , pp. 949 - 959
Copyright
Copyright © Cambridge University Press 2013 

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

APA (2000). Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. DSM-IV-TR. American Psychiatric Association: Washington, DC.Google Scholar
Beck, AT, Epstein, N, Brown, G, Steer, RA (1988). An inventory for measuring clinical anxiety: psychometric properties. Journal of Consulting and Clinical Psychology 56, 893–897.Google Scholar
Beck, AT, Ward, CH, Mendelson, M, Mock, J, Erbaugh, J (1961). An inventory for measuring depression. Archives of General Psychiatry 4, 561–571.Google Scholar
Beesdo-Baum, K, Höfler, M, Gloster, AT, Klotsche, J, Lieb, R, Beauducel, A, Bühner, M, Kessler, RC, Wittchen, HU (2009). The structure of common mental disorders: a replication study in a community sample of adolescents and young adults. International Journal of Methods in Psychiatric Research 18, 204–220.Google Scholar
Boden, JM, Fergusson, DM (2011). Alcohol and depression. Addiction 106, 906–914.Google Scholar
Bollen, KA, Curran, PJ (2006). Latent Curve Models: A Structural Equation Perspective. John Wiley and Sons: Hoboken, NJ.Google Scholar
Demyttenaere, K, Bruffaerts, R, Posada-Villa, J, Gasquet, I, Kovess, V, Lepine, JP, Angermeyer, MC, Bernert, S, de Girolamo, G, Morosini, P, Polidori, G, Kikkawa, T, Kawakami, N, Ono, Y, Takeshima, T, Uda, H, Karam, EG, Fayyad, JA, Karam, AN, Mneimneh, ZN, Medina-Mora, ME, Borges, G, Lara, C, de Graaf, R, Ormel, J, Gureje, O, Shen, Y, Huang, Y, Zhang, M, Alonso, J, Haro, JM, Vilagut, G, Bromet, EJ, Gluzman, S, Webb, C, Kessler, RC, Merikangas, KR, Anthony, JC, Von Korff, MR, Wang, PS, Brugha, TS, Aguilar-Gaxiola, S, Lee, S, Heeringa, S, Pennell, BE, Zaslavsky, AM, Ustun, TB, Chatterji, S; WHO World Mental Health Survey Consortium (2004). Prevalence, severity, and unmet need for treatment of mental disorders in the World Health Organization World Mental Health Surveys. Journal of the American Medical Association 291, 2581–2590.Google Scholar
Fergusson, DM, Boden, JM, Horwood, LJ (2009). Tests of causal links between alcohol abuse or dependence and major depression. Archives of General Psychiatry 66, 260–266.Google Scholar
Fergusson, DM, Boden, JM, Horwood, LJ (2011). Structural models of the comorbidity of internalizing disorders and substance use disorders in a longitudinal birth cohort. Social Psychiatry and Psychiatric Epidemiology 46, 933–942.Google Scholar
Fergusson, DM, Horwood, LJ, Boden, JM (2006). Structure of internalising symptoms in early adulthood. British Journal of Psychiatry 189, 540–546.Google Scholar
Grant, BF, Hasin, DS, Stinson, FS, Dawson, DA, Chou, SP, Ruan, WJ, Huang, B (2005). Co-occurrence of 12-month mood and anxiety disorders and personality disorders in the US: results from the national epidemiologic survey on alcohol and related conditions. Journal of Psychiatric Research 39, 1–9.Google Scholar
Hale, WW 3rd, Raaijmakers, QA, Muris, P, van Hoof, A, Meeus, WH (2009). One factor or two parallel processes? Comorbidity and development of adolescent anxiety and depressive disorder symptoms. Journal of Child Psychology and Psychiatry 50, 1218–1222.Google Scholar
Hamilton, M (1960). A rating scale for depression. Journal of Neurology, Neurosurgery, and Psychiatry 23, 56–62.Google Scholar
Hasin, DS, Liu, X, Alderson, D, Grant, BF (2006). DSM-IV alcohol dependence: a categorical or dimensional phenotype? Psychological Medicine 36, 1695–1705.Google Scholar
Hasin, DS, Stinson, FS, Ogburn, E, Grant, BF (2007). Prevalence, correlates, disability, and comorbidity of DSM-IV alcohol abuse and dependence in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Archives of General Psychiatry 64, 830–842.CrossRefGoogle ScholarPubMed
Helzer, JE, van den Brink, W, Guth, SE (2006). Should there be both categorical and dimensional criteria for the substance use disorders in DSM-V? Addiction 101, 17–22.Google Scholar
Keller, MB, Lavori, PW, Friedman, B, Nielsen, E, Endicott, J, McDonald-Scott, P, Andreasen, NC (1987). The Longitudinal Interval Follow-up Evaluation. A comprehensive method for assessing outcome in prospective longitudinal studies. Archives of General Psychiatry 44, 540–548.Google Scholar
Kendler, KS, Aggen, SH, Knudsen, GP, Røysamb, E, Neale, MC, Reichborn-Kjennerud, T (2011). The structure of genetic and environmental risk factors for syndromal and subsyndromal common DSM-IV axis I and all axis II disorders. American Journal of Psychiatry 168, 29–39.CrossRefGoogle ScholarPubMed
Kendler, KS, Gardner, CO (2011). A longitudinal etiologic model for symptoms of anxiety and depression in women. Psychological Medicine 41, 2035–2045.Google Scholar
Kendler, KS, Prescott, CA, Myers, J, Neale, MC (2003). The structure of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women. Archives of General Psychiatry 60, 929–937.Google Scholar
Kessler, RC, Chiu, WT, Demler, O, Walters, EE (2005). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry 62, 617–627.Google Scholar
Kessler, RC, McGonagle, KA, Zhao, S, Nelson, CB, Hughes, M, Eshleman, S, Wittchen, HU, Kendler, KS (1994). Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. Archives of General Psychiatry 51, 8–19.Google Scholar
Kotov, R, Ruggero, CJ, Krueger, RF, Watson, D, Yuan, Q, Zimmerman, M (2011). New dimensions in the quantitative classification of mental illness. Archives of General Psychiatry 68, 1003–1011.Google Scholar
Krueger, RF (1999). The structure of common mental disorders. Archives of General Psychiatry 56, 921–926.CrossRefGoogle ScholarPubMed
Krueger, RF, Caspi, A, Moffitt, TE, Silva, PA (1998). The structure and stability of common mental disorders (DSM-III-R): a longitudinal-epidemiological study. Journal of Abnormal Psychology 107, 216–227.Google Scholar
Krueger, RF, Markon, KE (2006). Reinterpreting comorbidity: a model-based approach to understanding and classifying psychopathology. Annual Review of Clinical Psychology 2, 111–133.Google Scholar
Kuo, PH, Gardner, CO, Kendler, KS, Prescott, CA (2006). The temporal relationship of the onsets of alcohol dependence and major depression: using a genetically informative study design. Psychological Medicine 36, 1153–1162.Google Scholar
Kushner, MG, Wall, MM, Krueger, RF, Sher, KJ, Maurer, E, Thuras, P, Lee, S (2012). Alcohol dependence is related to overall internalizing psychopathology load rather than to particular internalizing disorders: evidence from a national sample. Alcoholism: Clinical and Experimental Research 36, 325–331.Google Scholar
Maj, M (2005). ‘Psychiatric comorbidity’: an artefact of current diagnostic systems? British Journal of Psychiatry 186, 182–184.Google Scholar
Mantere, O, Isometsä, E, Ketokivi, M, Kiviruusu, O, Suominen, K, Valtonen, HM, Arvilommi, P, Leppämäki, S (2010). A prospective latent analyses study of psychiatric comorbidity of DSM-IV bipolar I and II disorders. Bipolar Disorders 12, 271–284.Google Scholar
McDermut, W, Mattia, J, Zimmerman, M (2001). Comorbidity burden and its impact on psychosocial morbidity in depressed outpatients. Journal of Affective Disorders 65, 289–295.Google Scholar
Melartin, TK, Haukka, J, Rytsälä, HJ, Jylhä, PJ, Isometsä, ET (2010). Categorical and dimensional stability of comorbid personality disorder symptoms in DSM-IV major depressive disorder: a prospective study. Journal of Clinical Psychiatry 71, 287–295.Google Scholar
Melartin, TK, Rytsälä, HJ, Leskelä, US, Lestelä-Mielonen, PS, Sokero, TP, Isometsä, ET (2002). Current comorbidity of psychiatric disorders among DSM-IV major depressive disorder patients in psychiatric care in the Vantaa Depression Study. Journal of Clinical Psychiatry 63, 126–134.Google Scholar
Melartin, TK, Rytsälä, HJ, Leskelä, US, Lestelä-Mielonen, PS, Sokero, TP, Isometsä, ET (2004). Severity and comorbidity predict episode duration and recurrence of DSM-IV major depressive disorder. Journal of Clinical Psychiatry 65, 810–819.Google Scholar
Melartin, TK, Rytsälä, HJ, Leskelä, US, Lestelä-Mielonen, PS, Sokero, TP, Isometsä, ET (2005). Continuity is the main challenge in treating major depressive disorder in psychiatric care. Journal of Clinical Psychiatry 66, 220–227.Google Scholar
Merikangas, KR, Zhang, H, Avenevoli, S, Acharyya, S, Neuenschwander, M, Angst, J (2003). Longitudinal trajectories of depression and anxiety in a prospective community study: the Zurich Cohort Study. Archives of General Psychiatry 60, 993–1000.Google Scholar
Middeldorp, CM, Cath, DC, Van Dyck, R, Boomsma, DI (2005). The co-morbidity of anxiety and depression in the perspective of genetic epidemiology. A review of twin and family studies. Psychological Medicine 35, 611–624.Google Scholar
Moffitt, TE, Caspi, A, Harrington, H, Milne, BJ, Melchior, M, Goldberg, D, Poulton, R (2007). Generalized anxiety disorder and depression: childhood risk factors in a birth cohort followed to age 32. Psychological Medicine 37, 441–452.Google Scholar
Muthén, LK, Muthén, BO (2010). Mplus User's Guide, 6th edn. Muthén & Muthén : Los Angeles, CA.Google Scholar
Olino, TM, Klein, DN, Lewinsohn, PM, Rohde, P, Seeley, JR (2008). Longitudinal associations between depressive and anxiety disorders: a comparison of two trait models. Psychological Medicine 38, 353–363.Google Scholar
Olino, TM, Klein, DN, Lewinsohn, PM, Rohde, P, Seeley, JR (2010). Latent trajectory classes of depressive and anxiety disorders from adolescence to adulthood: descriptions of classes and associations with risk factors. Comprehensive Psychiatry 51, 224–235.Google Scholar
Røysamb, E, Kendler, KS, Tambs, K, Orstavik, RE, Neale, MC, Aggen, SH, Torgersen, S, Reichborn-Kjennerud, T (2011). The joint structure of DSM-IV Axis I and Axis II disorders. Journal of Abnormal Psychology 120, 198–209.Google Scholar
Rutter, M, Kim-Cohen, J, Maughan, B (2006). Continuities and discontinuities in psychopathology between childhood and adult life. Journal of Child Psychology and Psychiatry 47, 276–295.Google Scholar
Rytsälä, HJ, Melartin, TK, Leskelä, US, Lestelä-Mielonen, PS, Sokero, TP, Isometsä, ET (2001). A record-based analysis of 803 patients treated for depression in psychiatric care. Journal of Clinical Psychiatry 62, 701–706.Google Scholar
Slade, T, Watson, D (2006). The structure of common DSM-IV and ICD-10 mental disorders in the Australian general population. Psychological Medicine 36, 1593–1600.Google Scholar
Vollebergh, WA, Iedema, J, Bijl, RV, de Graaf, R, Smit, F, Ormel, J (2001). The structure and stability of common mental disorders: the NEMESIS study. Archives of General Psychiatry 58, 597–603.Google Scholar
Wang, J, Patten, SB (2001). A prospective study of sex-specific effects of major depression on alcohol consumption. Canadian Journal of Psychiatry 46, 422–425.Google Scholar
Wang, J, Patten, SB (2002). Prospective study of frequent heavy alcohol use and the risk of major depression in the Canadian general population. Depression and Anxiety 15, 42–45.Google Scholar
Wing, JK, Babor, T, Brugha, T, Burke, J, Cooper, JE, Giel, R, Jablenski, A, Regier, D, Sartorius, N (1990). SCAN. Schedules for Clinical Assessment in Neuropsychiatry. Archives of General Psychiatry 47, 589–593.Google Scholar
Wittchen, HU (1996). Critical issues in the evaluation of comorbidity of psychiatric disorders. British Journal of Psychiatry 30, 9–16.Google Scholar
Wittchen, HU, Beesdo, K, Bittner, A, Goodwin, RD (2003). Depressive episodes – evidence for a causal role of primary anxiety disorders? European Psychiatry 18, 384–393.Google Scholar
Zimmerman, M, McDermut, W, Mattia, JI (2000). Frequency of anxiety disorders in psychiatric outpatients with major depressive disorder. American Journal of Psychiatry 157, 1337–1340.Google Scholar