Comparing Variability, Severity, and Persistence of Depressive Symptoms as Predictors of Future Stroke Risk

Laura B. Zahodne, Paola Gilsanz, M. Maria Glymour, Laura E. Gibbons, Paul Brewster, Jamie Hamilton, Jesse Mez, Jessica R. Marden, Kwangsik Nho, Eric B. Larson, Paul K. Crane, Alden L Gross

Research output: Contribution to journalArticle

Abstract

Objective Numerous studies show that depressive symptoms measured at a single assessment predict greater future stroke risk. Longer-term symptom patterns, such as variability across repeated measures or worst symptom level, might better reflect adverse aspects of depression than a single measurement. This prospective study compared five approaches to operationalizing depressive symptoms at annual assessments as predictors of stroke incidence. Design Cohort followed for incident stroke over an average of 6.4 years. Setting The Adult Changes in Thought cohort follows initially cognitively intact, community- dwelling older adults from a population base defined by membership in Group Health, a Seattle-based nonprofit healthcare organization. Participants 3,524 individuals aged 65 years and older. Measurements We identified 665 incident strokes using ICD codes. We considered both baseline Center for Epidemiologic Studies–Depression scale (CES-D) score and, using a moving window of three most recent annual CES-D measurements, we compared most recent, maximum, average, and intra-individual variability of CES-D scores as predictors of subsequent stroke using Cox proportional hazards models. Results Greater maximum (hazard ratio [HR]: 1.18; 95% CI: 1.07–1.30), average (HR: 1.20; 95% CI: 1.05–1.36) and intra-individual variability (HR: 1.15; 95% CI: 1.06–1.24) in CES-D were each associated with elevated stroke risk, independent of sociodemographics, cardiovascular risks, cognition, and daily functioning. Neither baseline nor most recent CES-D was associated with stroke. In a combined model, intra-individual variability in CES-D predicted stroke, but average CES-D did not. Conclusions Capturing the dynamic nature of depression is relevant in assessing stroke risk. Fluctuating depressive symptoms may reflect a prodrome of reduced cerebrovascular integrity.

Original languageEnglish (US)
Pages (from-to)120-128
Number of pages9
JournalAmerican Journal of Geriatric Psychiatry
Volume25
Issue number2
DOIs
StatePublished - Feb 1 2017
Externally publishedYes

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Stroke
Depression
Nonprofit Organizations
Independent Living
International Classification of Diseases
Proportional Hazards Models
Cognition
Prospective Studies
Delivery of Health Care
Incidence
Health
Population

Keywords

  • cerebrovascular
  • Depression
  • elderly
  • variability

ASJC Scopus subject areas

  • Geriatrics and Gerontology
  • Psychiatry and Mental health

Cite this

Comparing Variability, Severity, and Persistence of Depressive Symptoms as Predictors of Future Stroke Risk. / Zahodne, Laura B.; Gilsanz, Paola; Glymour, M. Maria; Gibbons, Laura E.; Brewster, Paul; Hamilton, Jamie; Mez, Jesse; Marden, Jessica R.; Nho, Kwangsik; Larson, Eric B.; Crane, Paul K.; Gross, Alden L.

In: American Journal of Geriatric Psychiatry, Vol. 25, No. 2, 01.02.2017, p. 120-128.

Research output: Contribution to journalArticle

Zahodne, LB, Gilsanz, P, Glymour, MM, Gibbons, LE, Brewster, P, Hamilton, J, Mez, J, Marden, JR, Nho, K, Larson, EB, Crane, PK & Gross, AL 2017, 'Comparing Variability, Severity, and Persistence of Depressive Symptoms as Predictors of Future Stroke Risk', American Journal of Geriatric Psychiatry, vol. 25, no. 2, pp. 120-128. https://doi.org/10.1016/j.jagp.2016.10.009
Zahodne, Laura B. ; Gilsanz, Paola ; Glymour, M. Maria ; Gibbons, Laura E. ; Brewster, Paul ; Hamilton, Jamie ; Mez, Jesse ; Marden, Jessica R. ; Nho, Kwangsik ; Larson, Eric B. ; Crane, Paul K. ; Gross, Alden L. / Comparing Variability, Severity, and Persistence of Depressive Symptoms as Predictors of Future Stroke Risk. In: American Journal of Geriatric Psychiatry. 2017 ; Vol. 25, No. 2. pp. 120-128.
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AB - Objective Numerous studies show that depressive symptoms measured at a single assessment predict greater future stroke risk. Longer-term symptom patterns, such as variability across repeated measures or worst symptom level, might better reflect adverse aspects of depression than a single measurement. This prospective study compared five approaches to operationalizing depressive symptoms at annual assessments as predictors of stroke incidence. Design Cohort followed for incident stroke over an average of 6.4 years. Setting The Adult Changes in Thought cohort follows initially cognitively intact, community- dwelling older adults from a population base defined by membership in Group Health, a Seattle-based nonprofit healthcare organization. Participants 3,524 individuals aged 65 years and older. Measurements We identified 665 incident strokes using ICD codes. We considered both baseline Center for Epidemiologic Studies–Depression scale (CES-D) score and, using a moving window of three most recent annual CES-D measurements, we compared most recent, maximum, average, and intra-individual variability of CES-D scores as predictors of subsequent stroke using Cox proportional hazards models. Results Greater maximum (hazard ratio [HR]: 1.18; 95% CI: 1.07–1.30), average (HR: 1.20; 95% CI: 1.05–1.36) and intra-individual variability (HR: 1.15; 95% CI: 1.06–1.24) in CES-D were each associated with elevated stroke risk, independent of sociodemographics, cardiovascular risks, cognition, and daily functioning. Neither baseline nor most recent CES-D was associated with stroke. In a combined model, intra-individual variability in CES-D predicted stroke, but average CES-D did not. Conclusions Capturing the dynamic nature of depression is relevant in assessing stroke risk. Fluctuating depressive symptoms may reflect a prodrome of reduced cerebrovascular integrity.

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