title: Can self-reported strokes be used to study stroke incidence and risk factors?: evidence from the health and retirement study.
abstract: OBJECTIVE
  Most stroke incidence studies use geographically localized (community) samples with few national data sources available. Such samples preclude research on contextual risk factors, but national samples frequently collect only self-reported stroke. We examine whether incidence estimates from clinically verified studies are consistent with estimates from a nationally representative US sample assessing self-reported stroke.
  
  
  METHODS
  Health and Retirement Study (HRS) participants (n=17 056) age 50+ years were followed for self- or proxy-reported first stroke (1293 events) from 1998 to 2006 (average, 6.8 years). We compared incidence rates by race, sex, and age strata with those previously documented in leading geographically localized studies with medically verified stroke. We also examined whether cardiovascular risk factor effect estimates in HRS are comparable to those reported in studies with clinically verified strokes.
  
  
  RESULTS
  The weighted first-stroke incidence rate was 10.0 events/1000 person-years. Total age-stratified incidence rates in whites were mostly comparable with those reported elsewhere and were not systematically higher or lower. However, among blacks in HRS, incidence rates generally appeared higher than those previously reported. HRS estimates were most comparable with those reported in the Cardiovascular Health Study. Incidence rates approximately doubled per decade of age and were higher in men and blacks. After demographic adjustment, all risk factors predicted stroke incidence in whites. Smoking, hypertension, diabetes, and heart disease predicted incident stroke in blacks.
  
  
  CONCLUSIONS
  Associations between known risk factors and stroke incidence were verified in HRS, suggesting that misreporting is nonsystematic. HRS may provide valuable data for stroke surveillance and examination of classical and contextual risk factors.
authors.affiliation: Department of Epidemiology, Mailman School of Public Health, New York, NY, USA. mglymour@hsph.harvard.edu
authors.forename: M Maria
authors.initials: MM
authors.lastname: Glymour
authors.forename: Mauricio
authors.initials: M
authors.lastname: Avendano
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D004812:Epidemiologic Methods; D005006:Ethnicity; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D012179:Retirement; D012307:Risk Factors; D012737:Sex Factors; D020521:Stroke / Q000175:diagnosis* / Q000453:epidemiology*; D016896:Treatment Outcome; D014481:United States / Q000453:epidemiology