Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-23T21:50:07.951Z Has data issue: false hasContentIssue false

Random-mood interpretation of determinants for major depression

Published online by Cambridge University Press:  05 July 2007

KIRSTEN I. KAPTEIN
Affiliation:
Department of Psychiatry, University Medical Centre Groningen, University of Groningen, The Netherlands
PETER De JONGE
Affiliation:
Department of Psychiatry, University Medical Centre Groningen, University of Groningen, The Netherlands Department of Internal Medicine, University Medical Centre Groningen, University of Groningen, The Netherlands
JAKOB KORF
Affiliation:
Department of Psychiatry, University Medical Centre Groningen, University of Groningen, The Netherlands
JAN SPIJKER
Affiliation:
Netherlands Institute of Mental Health and Addiction, Utrecht, The Netherlands De Gelderse Roos, Institute for Mental Health Care, Arnhem, The Netherlands
RON De GRAAF
Affiliation:
Netherlands Institute of Mental Health and Addiction, Utrecht, The Netherlands
SIEBREN Y. VAN DER WERF*
Affiliation:
Kernfysisch Versneller Instituut, University of Groningen, The Netherlands
*
*Address for correspondence: Siebren Y. van der Werf, Ph.D., Kernfysisch Versneller Instituut, University of Groningen, Zernikelaan 25, 9747AA Groningen, The Netherlands. (Email: [email protected])

Abstract

Background

It has recently been proposed that major depression disorder (MDD) may, in a heterogeneous population-based cohort, be interpreted in terms of a random-mood model. Mood fluctuations are thought to result from stressors that occur randomly in time. We have investigated whether this concept also holds for more homogeneous groups, defined by known determinants for MDD, and whether the model's parameters, susceptibility (Z) and relaxation time (T), may be evaluated and used to differentiate between subcohorts.

Method

From a large epidemiological survey, the Netherlands Mental Health Survey and Incidence Study (NEMESIS), data on the duration of MDD were obtained for subcohorts, based on gender, severity of depression, recurrence and co-morbidity with dysthymia, anxiety and somatic disorder, and were compared with random-mood simulation calculations.

Results

Susceptibility, Z, is empirically found to be proportional to incidence and may be identified with a risk ratio. A second scaling rule states the proportionality of mean duration with the product of Z and T. This Z–T classification proves to be more sensitive than conventional significance tests. Notably for men/women and for co-morbid anxiety, differences are seen that have previously gone unnoticed.

Conclusions

Depression may be conceptualized as a disorder resulting from random-mood fluctuations, the response to which is influenced by a large variety of determinants or risk factors. The model's parameters can be evaluated and may be used in differentiating between risk factor-defined subgroups.

Type
Original Article
Copyright
Copyright © Cambridge University Press 2007

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

REFERENCES

Angst, J. (1996). Comorbidity of mood disorders: a longitudinal prospective study. British Journal of Psychiatry 30, 3137.CrossRefGoogle Scholar
APA (1987). Diagnostic and Statistical Manual of Mental Disorders (3rd edn, revised) (DSM-III-R). American Psychiatric Association: Washington, DC.Google Scholar
Barkow, K., Maier, W., Üstün, T. B., Gänsicke, M., Wittchen, H. U. & Heun, R. (2003). Risk factors for depression at 12-month follow-up in adult primary health care patients with major depression: an international prospective study. Journal of Affective Disorders 76, 157169.CrossRefGoogle ScholarPubMed
Benazzi, F. (1999). Gender differences in bipolar II and unipolar depressed outpatients: a 557-case study. Annals of Clinical Psychiatry 11, 5559.CrossRefGoogle ScholarPubMed
de Graaf, R., Bijl, R. V., Ravelli, A., Smit, F. & Vollebergh, W. A. M. (2002). Predictors of first incidence of DSM-III-R psychiatric disorders in the general population: findings from the Netherlands Mental Health Survey and Incidence Study. Acta Psychiatrica Scandinavica 106, 303313.CrossRefGoogle ScholarPubMed
Eaton, W. W., Anthony, J. C., Gallo, J., Cai, G., Tien, A., Romanoski, A., Lyketsos, C. & Chen, L. S. (1997). Natural history of Diagnostic Interview Schedule/DSM-IV major depression. The Baltimore Epidemiologic Catchment Area follow-up. Archives of General Psychiatry 54, 993999.CrossRefGoogle ScholarPubMed
Evans, D. L., Charney, D. S., Lewis, L., Golden, R. N., Gorman, J. M., Krishnan, K. R., Nemeroff, C. B., Bremner, J. D., Carney, R. M., Coyne, J. C., Delong, M. R., Frasure-Smith, N., Glassman, A. H., Gold, P. W., Grant, I., Gwyther, L., Ironson, G., Johnson, R. L., Kanner, A. M., Katon, W. J., Kaufmann, P. G., Keefe, F. J., Ketter, T., Laughren, T. P., Leserman, J., Lyketsos, C. G., McDonald, W. M., McEwen, B. S., Miller, A. H., Musselman, D., O'Connor, C., Petitto, J. M., Pollock, B. G., Robinson, R. G., Roose, S. P, Rowland, J., Sheline, Y., Sheps, D. S., Simon, G., Spiegel, D., Stunkard, A., Sunderland, T., Tibbits, P. & Valvo, W. J. (2005). Mood disorders in the medically ill: scientific review and recommendations. Biological Psychiatry 58, 175189.CrossRefGoogle Scholar
Gottschalk, A., Bauer, M. S. & Whybrow, P. C. (1995). Evidence of chaotic mood variation in bipolar disorder. Archives of General Psychiatry 52, 947959.CrossRefGoogle ScholarPubMed
Gottschalk, A., Bauer, M. S. & Whybrow, P. C. (1998). Reply to: Krystal AD, Greenside HS. Low-dimensional chaos in bipolar disorder? Archives of General Psychiatry 55, 275276.Google Scholar
Heiby, E. M., Pagano, I. S., Blaine, D. D., Nelson, K. & Heath, R. A. (2003). Modeling unipolar depression as a chaotic process. Psychological Assessment 15, 426434.CrossRefGoogle ScholarPubMed
Iosifescu, D. V., Bankier, B. & Fava, M. (2004). Impact of medical comorbid disease on antidepressant treatment of major depressive disorder. Current Psychiatry Reports 6, 193201.CrossRefGoogle ScholarPubMed
Kaplan, E. L. & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 53, 457481.CrossRefGoogle Scholar
Katon, W., Lin, E., Von Korff, M., Bush, T., Walker, E., Simon, G. & Robinson, P. (1994). The predictors of persistence of depression in primary care. Journal of Affective Disorders 31, 8190.CrossRefGoogle ScholarPubMed
Keitner, G. I., Ryan, C. E., Miller, I. W., Kohn, R. & Epstein, N. B. (1991). 12-month outcome of patients with major depression and comorbid psychiatric or medical illness (compound depression). American Journal of Psychiatry 148, 345350.Google ScholarPubMed
Keller, M. B., Lavori, P. W., Mueller, T. I., Endicott, J., Coryell, W., Hirschfeld, R. M. A. & Shea, T. (1992). Time to recovery, chronicity, and levels of psychopathology in major depression: a 5-year prospective follow-up of 431 subjects. Archives of General Psychiatry 49, 809816.CrossRefGoogle ScholarPubMed
Keller, M. B., Shapiro, R. W., Lavori, P. W. & Wolfe, N. (1982). Recovery in major depressive disorder. Analysis with the life table and regression models. Archives of General Psychiatry 39, 905910.CrossRefGoogle ScholarPubMed
Kleinbaum, D. G. (1996). Survival Analysis. Statistics in the Health Sciences. Springer: New York.CrossRefGoogle Scholar
Lyketsos, C. G., Nestadt, G., Cwi, J., Heithoff, K. & Eaton, W. (1994). The Life Chart Interview: a standardized method to describe the course of psychopathology. International Journal of Methods in Psychiatric Research 4, 143155.Google Scholar
Maj, M., Veltro, F., Pirozzi, R., Lobrace, S. & Magliano, L. (1992). Pattern of recurrence of illness after recovery from an episode of major depression: a prospective study. American Journal of Psychiatry 149, 795800.Google ScholarPubMed
Mueller, T. I., Keller, M. B., Leon, A. C., Solomon, D. A., Shea, M. T., Coryell, W. & Endicott, J. (1996). Recovery after 5 years of unremitting major depressive disorder. Archives of General Psychiatry 53, 794799.CrossRefGoogle ScholarPubMed
Mueller, T. I., Leon, A. C., Keller, M. B., Solomon, D. A., Endicott, J., Coryell, W., Warshaw, M. & Maser, J. D. (1999). Recurrence after recovery from major depressive disorder during 15 years of observational follow-up. American Journal of Psychiatry 156, 10001006.CrossRefGoogle ScholarPubMed
Murray, C. J. L. & Lopez, A. D. (1997). Alternative projections of mortality and disability by cause 1990–2020. Global Burden of Disease Study. Lancet 349, 14981504.CrossRefGoogle ScholarPubMed
Oldehinkel, A. J., Ormel, J. & Neeleman, J. (2000). Predictors of time to remission from depression in primary care patients: do some people benefit more from positive life change than others? Journal of Abnormal Psychology 109, 299307.CrossRefGoogle ScholarPubMed
Ormel, J., Oldehinkel, A. J. & Brilman, E. I. (2001). The interplay and etiological continuity of neuroticism, difficulties, and life events in the etiology of major and subsyndromal, first and recurrent depressive episodes in later life. American Journal of Psychiatry 158, 885891.CrossRefGoogle ScholarPubMed
Patten, S. B. (2002). A framework for simulating the impact of antidepressant medications on population health status. Pharmacoepidemiology and Drug Safety 11, 549559.CrossRefGoogle ScholarPubMed
Sargeant, J. K., Bruce, M. L., Florio, L. P. & Weissman, M. M. (1990). Factors associated with 1-year outcome of major depression in the community. Archives of General Psychiatry 47, 519526.CrossRefGoogle ScholarPubMed
Simpson, H. B., Nee, J. C. & Endicott, J. (1997). First-episode major depression. Few sex differences in course. Archives of General Psychiatry 54, 633639.CrossRefGoogle ScholarPubMed
Smeets, R. M. W. & Dingemans, P. M. A. J. (1993). Composite International Diagnostic Interview (CIDI), Version 1.1. World Health Organization: Geneva.Google Scholar
Solomon, D. A., Keller, M. B., Leon, A. C., Mueller, T. I., Shea, M. T., Warshaw, M., Maser, J. D., Coryell, W. & Endicott, J. (1997). Recovery from major depression. A 10-year prospective follow-up across multiple episodes. Archives of General Psychiatry 54, 10011006.CrossRefGoogle ScholarPubMed
Spijker, J., de Graaf, R., Bijl, R. V., Beekman, A. T., Ormel, J. & Nolen, W. A. (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 ScholarPubMed
Spijker, J., de Graaf, R., Bijl, R. V., Beekman, A. T., Ormel, J. & Nolen, W. A. (2004). Determinants of persistence of major depressive episodes in the general population. Results from the Netherlands Mental Health Survey and Incidence Study (NEMESIS). Journal of Affective Disorders 81, 231240.CrossRefGoogle ScholarPubMed
Stuart, A. & Ord, J. K. (1991). Kendall's Advanced Theory of Statistics, vol. 2 (5th edn). Oxford University Press: Oxford.Google Scholar
Swindle, R. W., Cronkite, R. C. & Moos, R. H. (1998). Risk factors for sustained nonremission of depressive symptoms: a 4-year follow-up. Journal of Nervous and Mental Disease 186, 462469.CrossRefGoogle Scholar
van der Werf, S. Y., Kaptein, K. I., de Jonge, P., Spijker, J., de Graaf, R. & Korf, J. (2006). Major depressive episodes and random mood. Archives of General Psychiatry 63, 509518.CrossRefGoogle ScholarPubMed
Von Korff, M. & Parker, R. D. (1980). The dynamics of the prevalence of chronic episodic disease. Journal of Chronic Diseases 33, 7985.CrossRefGoogle ScholarPubMed
Wittchen, H. U., Beesdo, K., Bittner, K. & Goodwin, R. D. (2003). Depressive episodes: evidence for a causal role of primary anxiety disorders? European Psychiatry 18, 384393.CrossRefGoogle ScholarPubMed