Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-18T10:45:25.813Z Has data issue: false hasContentIssue false
  • English
  • Français

Twelve-year depressive symptom trajectories and their predictors in a community sample of older adults

Published online by Cambridge University Press:  31 January 2008

Carmen Andreescu ,
Chou-Chung H. Chang ,
Benoit H. Mulsant  and
Mary Ganguli
Carmen Andreescu*
Affiliation:
Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, U.S.A. The Advanced Center in Intervention and Services Research for Late-Life Mood Disorders, and the John A. Hartford Center of Excellence in Geriatric Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, U.S.A.
Chou-Chung H. Chang
Affiliation:
Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, U.S.A. Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, U.S.A.
Benoit H. Mulsant
Affiliation:
Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, U.S.A. The Advanced Center in Intervention and Services Research for Late-Life Mood Disorders, and the John A. Hartford Center of Excellence in Geriatric Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, U.S.A. Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada
Mary Ganguli
Affiliation:
Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, U.S.A. Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, U.S.A. Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, U.S.A.
*
Correspondence should be addressed to: Dr. Carmen Andreescu, Western Psychiatric Institute and Clinic, 3811 O'Hara Street, Pittsburgh, PA 15213, U.S.A. Phone +1 412 383 5164; Fax: +1 412 383 5458. Email: [email protected].
Get access

Abstract

Introduction: The aim of this study is to understand the long-term course and outcomes of depressive symptoms among older adults in the community by examining trajectories of depressive symptoms over time and identifying profiles of depressive symptoms predicting different trajectories.

Method: We measured depressive symptoms biennially for up to 12 years, using the modified Center for Epidemiological Studies-Depression (mCES-D) scale, in 1260 community-based adults aged 65+ years. We determined latent trajectories of total mCES-D scores over time. We identified symptom profiles based on subgroups of baseline depressive symptoms derived from factor analysis, and examined their associations with the different trajectories.

Results: Six trajectories were identified. Two had one or no depressive symptoms at baseline and flat trajectories during follow-up. Two began with low baseline symptom scores and then diverged; female sex and functional disability were associated with future increases in depressive symptoms. Two trajectories began with high baseline scores but had different slopes: the higher trajectory was associated with medical burden, higher overall baseline score, and higher baseline scores on symptom profiles including low self-esteem, interpersonal difficulties, neurovegetative symptoms, and anhedonia. Mortality was higher among those in the higher trajectories.

Conclusions: In the community at large, those with minimal depressive symptoms are more likely to experience future increases in symptoms if they are women and have functional disability. Among those with higher current symptom levels, depression is more likely to persist over time in individuals who have greater medical burden and specific depressive symptoms.

Type
2007 IPA RESEARCH AWARDS – FIRST-PRIZE WINNER
Information
International Psychogeriatrics , Volume 20 , Issue 2 , April 2008 , pp. 221 - 236
Copyright
Copyright © International Psychogeriatric Association 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

Akiskal, H. 2005. Mood disorders: clinical features. In Sadock, B. and Sadock, V. (eds.) Comprehensive Textbook of Psychiatry (pp. 1611–1652). New York: Lippincott Williams and Wilkins.Google Scholar
Alexopoulos, G. S. 2005. Depression in the elderly. Lancet, 365, 1961–1970.Google Scholar
Anderson, E. 1936. Prognosis of the depressions of later life. American Journal of Psychiatry, 559–588.Google Scholar
Beekman, A. T., Deeg, D. J., Braam, A. W., Smit, J. H. and Van Tilburg, W. 1997. Consequences of major and minor depression in later life: a study of disability, well-being and service utilization. Psychological Medicine, 27, 1397–1409.Google Scholar
Beekman, A. T., Copeland, J. R. and Prince, M. J. 1999. Review of community prevalence of depression in later life. British Journal of Psychiatry, 174, 307–311.CrossRefGoogle ScholarPubMed
Beekman, A. T. et al. 2002. The natural history of late-life depression: a 6-year prospective study in the community. Archives of General Psychiatry, 59, 605–611.Google Scholar
Blazer, D. G. 2003. Depression in late life: review and commentary. Journal of Gerontology Series A: Biological Sciences and Medical Sciences, 58, 249–265.Google Scholar
Bruce, M. L., Seeman, T. E., Merrill, S. S. and Blazer, D. G. 1994. The impact of depressive symptomatology on physical disability: MacArthur Studies of Successful Aging. American Journal of Public Health, 84, 1796–1799.Google Scholar
Charney, D. S. et al. 2003. Depression and Bipolar Support Alliance consensus statement on the unmet needs in diagnosis and treatment of mood disorders in late life. Archives of General Psychiatry, 60, 664–672.Google Scholar
Cole, M. G. and Dendukuri, N. 2003. Risk factors for depression among elderly community subjects: a systematic review and meta-analysis. American Journal of Psychiatry, 160, 1147–1156.Google Scholar
Cole, M. G., Bellavance, F. and Mansour, A. 1999. Prognosis of depression in elderly community and primary care populations: a systematic review and meta-analysis. American Journal of Psychiatry, 156, 1182–1189.CrossRefGoogle ScholarPubMed
Dew, M. A. et al. 1997. Temporal profiles of the course of depression during treatment: predictors of pathways toward recovery in the elderly. Archives of General Psychiatry, 54, 1016–1024.CrossRefGoogle ScholarPubMed
Doble, S. E. and Fisher, A. G. 1998. The dimensionality and validity of the Older Americans Resources and Services (OARS) Activities of Daily Living (ADL) Scale. Journal of Outcome Measurement, 2, 4–24.Google Scholar
Folstein, M. F., Folstein, S. E. and McHugh, P. R. 1975. “Mini-mental State”: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.Google Scholar
Gallo, J. J., Rabins, P. V. and Anthony, J. C. 1999. Sadness in older persons: 13-year follow-up of a community sample in Baltimore, Maryland. Psychological Medicine, 29, 341–350.CrossRefGoogle ScholarPubMed
Ganguli, M. et al. 1993. Sensitivity and specificity for dementia of population-based criteria for cognitive impairment: the MoVIES project. Journal of Gerontology: Medical Sciences, 48, M152–161.CrossRefGoogle ScholarPubMed
Ganguli, M., Gilby, J., Seaberg, E. and Belle, S. 1995. Depressive symptoms and associated factors in a rural elderly population: the MoVIES Project. American Journal of Geriatric Psychiatry, 3, 144–160.CrossRefGoogle Scholar
Ganguli, M., Mulsant, B., Richards, S., Stoehr, G. and Mendelsohn, A. 1997. Antidepressant use over time in a rural older adult population: the MoVIES Project. Journal of the American Geriatrics Society, 45, 1501–1503.CrossRefGoogle Scholar
Ganguli, M., Dodge, H. H. and Mulsant, B. H. 2002. Rates and predictors of mortality in an aging, rural, community-based cohort: the role of depression. Archives of General Psychiatry, 59, 1046–1052.Google Scholar
Gildengers, A. G. et al. 2005. Trajectories of treatment response in late-life depression: psychosocial and clinical correlates. Journal of Clinical Psychopharmacology, 25, S8–13.Google Scholar
Hintze, J. 2005. NCSS and PASS. Number Cruncher Statistical System. Kaysville, UT: www.ncss.com.Google Scholar
Judd, L. L. and Akiskal, H. S. 2002. The clinical and public health relevance of current research on subthreshold depressive symptoms to elderly patients. American Journal of Geriatric Psychiatry, 10, 233–38.CrossRefGoogle Scholar
Judd, L. L., Schettler, P. J. and Akiskal, H. S. 2002. The prevalence, clinical relevance, and public health significance of subthreshold depressions. The Psychiatric Clinics of North America, 25, 685–698.CrossRefGoogle Scholar
Katon, W. J., Fan, M. Y., Lin, E. H. and Unutzer, J. 2006. Depressive symptom deterioration in a large primary care-based elderly cohort. American Journal of Geriatric Psychiatry, 14, 246–254.Google Scholar
Kendler, K. S., Gatz, M., Gardner, C. O. and Pedersen, N. L. 2006. Personality and major depression: a Swedish longitudinal, population-based twin study. Archives of General Psychiatry, 63, 1113–1120.Google Scholar
Krishnan, K. R. et al. 2002. Comorbidity of depression with other medical diseases in the elderly. Biological Psychiatry, 52, 559–588.CrossRefGoogle ScholarPubMed
Lenze, E. J. et al. 2005. The course of functional decline in older people with persistently elevated depressive symptoms: longitudinal findings from the Cardiovascular Health Study. Journal of the American Geriatrics Society, 53, 569–575.Google Scholar
Lyness, J. M., King, D. A., Cox, C., Yoediono, Z. and Caine, E. D. 1999. The importance of subsyndromal depression in older primary care patients: prevalence and associated functional disability. Journal of the American Geriatrics Society, 47, 647–652.Google Scholar
Mehta, K. M., Yaffe, K., Langa, K. M., Sands, L., Whooley, M. A. and Covinsky, K. E. 2003. Additive effects of cognitive function and depressive symptoms on mortality in elderly community-living adults. Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 58, M461–467.Google Scholar
Mulder, R. T., Joyce, P. R. and Luty, S. E. 2003. The relationship of personality disorders to treatment outcome in depressed outpatients. Journal of Clinical Psychiatry, 64, 259–264.CrossRefGoogle ScholarPubMed
Mulsant, B. H. and Ganguli, M. 1999. Epidemiology and diagnosis of depression in late life. Journal of Clinical Psychiatry, 60 (Suppl. 20), 9–15.Google ScholarPubMed
Paykel, E. S. et al. 1999. Prevention of relapse in residual depression by cognitive therapy: a controlled trial. Archives of General Psychiatry, 56, 829–835.CrossRefGoogle ScholarPubMed
Radloff, L. 1977. The CES-D Scale: a self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401.Google Scholar
Shafer, A. B. 2006. Meta-analysis of the factor structures of four depression questionnaires: Beck, CES-D, Hamilton, and Zung. Journal of Clinical Psychology, 62, 123–146.Google Scholar
Shea, M. T., Widiger, T. A. and Klein, M. H. 1992. Comorbidity of personality disorders and depression: implications for treatment. Journal of Consulting and Clinical Psychology, 60, 857–868.Google Scholar
Steffens, D. C. et al. 2005. Biological and social predictors of long-term geriatric depression outcome. International Psychogeriatrics, 17, 41–56.Google Scholar
Thase, M. E., Friedman, E. S. and Howland, R. H. 2001. Management of treatment-resistant depression: psychotherapeutic perspectives. Journal of Clinical Psychiatry, 62 (Suppl. 18), 18–24.Google Scholar
Unutzer, J., Patrick, D. L., Marmon, T., Simon, G. E. and Katon, W. J. 2002. Depressive symptoms and mortality in a prospective study of 2,558 older adults. American Journal of Geriatric Psychiatry, 10, 521–530.Google Scholar
Van Londen, L., Molenaar, R. P., Goekoop, J. G., Zwinderman, A. H. and Rooijmans, H. G. 1998. Three- to 5-year prospective follow-up of outcome in major depression. Psychological Medicine, 28, 731–735.Google Scholar