title: Methods for incorporating death into health-related variables in longitudinal studies.
abstract: OBJECTIVE
  Longitudinal studies of health over time may be misleading if some people die. Self-rated health (excellent to poor) and the SF-36 profile scores have been transformed to incorporate death. We applied the same approaches to incorporate death into activities of daily living difficulties (ADLs), IADLs, mini-mental state examination, depressive symptoms, blocks walked per week, bed days, the timed walk, body mass index and blood pressure.
  
  
  METHODS
  The Cardiovascular Health Study of 5,888 older adults, was followed up to 9 years. Mean age was 73 at baseline, and 658 had an incident stroke during follow-up.
  
  
  METHODS
  We recoded each variable as the probability of being healthy 1 year in the future (PHF), conditional on the current value of the variable. This was done for 11 health variables, using three definitions of healthy, and two estimation models. Deaths were set to zero, and mean PHF was plotted in the 3 years before and after an incident stroke.
  
  
  RESULTS
  Analyses without the deaths were too optimistic. The effect of stroke was greatest on hospitalization, self-rated health, and IADLs. Alternative transformation approaches had slightly different results.
  
  
  CONCLUSIONS
  These methods provide an additional approach for handling death in longitudinal studies.
authors.affiliation: Department of Biostatistics, University of Washington, Seattle, 98195, USA. pdiehr@u.washington.edu
authors.forename: Paula
authors.initials: P
authors.lastname: Diehr
authors.forename: Laura Lee
authors.initials: LL
authors.lastname: Johnson
authors.forename: Donald L
authors.initials: DL
authors.lastname: Patrick
authors.forename: Bruce
authors.initials: B
authors.lastname: Psaty
mesh_terms: D000203:Activities of Daily Living; D003643:Death; D006305:Health Status Indicators; D006801:Humans; D008137:Longitudinal Studies; D016016:Proportional Hazards Models