title: Comparing Variability, Severity, and Persistence of Depressive Symptoms as Predictors of Future Stroke Risk.
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.
  
  
  METHODS
  Cohort followed for incident stroke over an average of 6.4 years.
  
  
  METHODS
  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.
  
  
  METHODS
  3,524 individuals aged 65 years and older.
  
  
  METHODS
  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.
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI. Electronic address: lzahodne@umich.edu.
authors.forename: Laura B
authors.initials: LB
authors.lastname: Zahodne
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI.
authors.forename: Paola
authors.initials: P
authors.lastname: Gilsanz
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI.
authors.forename: M Maria
authors.initials: MM
authors.lastname: Glymour
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI.
authors.forename: Laura E
authors.initials: LE
authors.lastname: Gibbons
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI.
authors.forename: Paul
authors.initials: P
authors.lastname: Brewster
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI.
authors.forename: Jamie
authors.initials: J
authors.lastname: Hamilton
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI.
authors.forename: Jesse
authors.initials: J
authors.lastname: Mez
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI.
authors.forename: Jessica R
authors.initials: JR
authors.lastname: Marden
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI.
authors.forename: Kwangsik
authors.initials: K
authors.lastname: Nho
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI.
authors.forename: Eric B
authors.initials: EB
authors.lastname: Larson
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI.
authors.forename: Paul K
authors.initials: PK
authors.lastname: Crane
authors.affiliation: Department of Psychology, University of Michigan, Ann Arbor, MI.
authors.forename: Alden L
authors.initials: AL
authors.lastname: Gross
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003863:Depression / Q000150:complications / Q000453:epidemiology*; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008824:Michigan / Q000453:epidemiology; D016016:Proportional Hazards Models; D011446:Prospective Studies; D011569:Psychiatric Status Rating Scales; D012307:Risk Factors; D020521:Stroke / Q000150:complications / Q000453:epidemiology*
keywords: Depression; cerebrovascular; elderly; variability