title: Stroke-associated differences in rates of activity of daily living loss emerge years before stroke onset.
abstract: OBJECTIVE
  To compare typical age-related changes in activities of daily living (ADLs) independence in stroke-free adults with long-term ADL trajectories before and after stroke.
  
  
  METHODS
  Prospective, observational study.
  
  
  METHODS
  Community-dwelling Health and Retirement Study (HRS) cohort.
  
  
  METHODS
  HRS participants who were stroke free in 1998 and were followed through 2008 (average follow-up 7.9 years) (N = 18,441).
  
  
  METHODS
  Strokes were assessed using self- or proxy-report of a doctor's diagnosis and month and year of event. Logistic regression was used to compare within-person changes in odds of self-reported independence in five ADLs in those who remained stroke free throughout follow-up (n = 16,816), those who survived a stroke (n = 1,208), and those who had a stroke and did not survive to participate in another interview (n = 417). Models were adjusted for demographic and socioeconomic covariates.
  
  
  RESULTS
  Even before stroke, those who later developed stroke had significantly lower ADL independence and were experiencing faster independence losses than similar-aged individuals who remained stroke free. Of those who developed a stroke, survivors experienced slower pre-stroke loss of ADL independence than those who died. ADL independence declined at the time of stroke and decline continued afterwards.
  
  
  CONCLUSIONS
  In adults at risk of stroke, disproportionate ADL limitations emerge well before stroke onset. Excess disability in stroke survivors should not be entirely attributed to effects of acute stroke or quality of acute stroke care. Although there are many possible causal pathways between ADL and stroke, the association may be noncausal. For example, ADL limitations may be a consequence of stroke risk factors (e.g., diabetes mellitus) or early cerebrovascular ischemia.
authors.affiliation: Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, Massachusetts.|Carolina Population Center, University of North Carolina, Chapel Hill, North Carolina.
authors.forename: Beatrix D
authors.initials: BD
authors.lastname: Capistrant
authors.affiliation: Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts.
authors.forename: Qianyi
authors.initials: Q
authors.lastname: Wang
authors.affiliation: Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, Massachusetts.|Harvard Center for Population and Development Studies, Harvard University, Cambridge, Massachusetts.
authors.forename: Sze Y
authors.initials: SY
authors.lastname: Liu
authors.affiliation: Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, Massachusetts.
authors.forename: M Maria
authors.initials: MM
authors.lastname: Glymour
mesh_terms: D000203:Activities of Daily Living; D017668:Age of Onset; D000368:Aged; D000369:Aged, 80 and over; D001499:Bayes Theorem; D004185:Disability Evaluation; D006233:Persons with Disabilities / Q000534:rehabilitation / Q000706:statistics & numerical data*; D005260:Female; D005500:Follow-Up Studies; D015577:Geriatric Assessment / Q000379:methods*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009017:Morbidity / Q000639:trends; D011446:Prospective Studies; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012959:Socioeconomic Factors; D020521:Stroke / Q000453:epidemiology / Q000503:physiopathology; D000071939:Stroke Rehabilitation; D015996:Survival Rate / Q000639:trends; D017741:Survivors / Q000706:statistics & numerical data*; D013997:Time Factors; D014481:United States / Q000453:epidemiology