title: A method for partitioning the attributable fraction of multiple time-dependent coexisting risk factors for an adverse health outcome.
abstract: OBJECTIVE
  We decomposed the total effect of coexisting diseases on a timed occurrence of an adverse outcome into additive effects from individual diseases.
  
  
  METHODS
  In a cohort of older adults enrolled in the Precipitating Events Project in New Haven County, Connecticut, we assessed a longitudinal extension of the average attributable fraction method (LE-AAF) to estimate the additive and order-free contributions of multiple diseases to the timed occurrence of a health outcome, with right censoring, which may be useful when relationships among diseases are complex. We partitioned the contribution to death into additive LE-AAFs for multiple diseases.
  
  
  RESULTS
  The onset of heart failure and acute episodes of pneumonia during follow-up contributed the most to death, with the overall LE-AAFs equal to 13.0% and 12.1%, respectively. The contribution of preexisting diseases decreased over the years, with a trend of increasing contribution from new onset of diseases.
  
  
  CONCLUSIONS
  LE-AAF can be useful for determining the additive and order-free contribution of individual time-varying diseases to a time-to-event outcome.
authors.affiliation: Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA. haiqun.lin@yale.edu
authors.forename: Haiqun
authors.initials: H
authors.lastname: Lin
authors.forename: Heather G
authors.initials: HG
authors.lastname: Allore
authors.forename: Gail
authors.initials: G
authors.lastname: McAvay
authors.forename: Mary E
authors.initials: ME
authors.lastname: Tinetti
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Gill
authors.forename: Cary P
authors.initials: CP
authors.lastname: Gross
authors.forename: Terrence E
authors.initials: TE
authors.lastname: Murphy
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002423:Cause of Death; D015331:Cohort Studies; D015897:Comorbidity; D003237:Connecticut; D005260:Female; D006333:Heart Failure / Q000401:mortality; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D011014:Pneumonia / Q000401:mortality; D011379:Prognosis; D012307:Risk Factors; D013997:Time Factors