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.
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.
Authors: Jordan W Smoller; Matthew Allison; Barbara B Cochrane; J David Curb; Roy H Perlis; Jennifer G Robinson; Milagros C Rosal; Nanette K Wenger; Sylvia Wassertheil-Smoller Journal: Arch Intern Med Date: 2009-12-14
Authors: Tara W Strine; Ali H Mokdad; Shanta R Dube; Lina S Balluz; Olinda Gonzalez; Joyce T Berry; Ron Manderscheid; Kurt Kroenke Journal: Gen Hosp Psychiatry Date: 2008 Mar-Apr Impact factor: 3.238
Authors: Paul Muntner; Jeff Whittle; Amy I Lynch; Lisandro D Colantonio; Lara M Simpson; Paula T Einhorn; Emily B Levitan; Paul K Whelton; William C Cushman; Gail T Louis; Barry R Davis; Suzanne Oparil Journal: Ann Intern Med Date: 2015-09-01 Impact factor: 25.391
Authors: Ronald C Kessler; Patricia Berglund; Olga Demler; Robert Jin; Doreen Koretz; Kathleen R Merikangas; A John Rush; Ellen E Walters; Philip S Wang Journal: JAMA Date: 2003-06-18 Impact factor: 56.272