title: Contribution of multiple chronic conditions to universal health outcomes.
abstract: OBJECTIVE
  To determine the relative effect of five chronic conditions on four representative universal health outcomes.
  
  
  METHODS
  Cross-sectional.
  
  
  METHODS
  Cardiovascular Health Study.
  
  
  METHODS
  Five thousand two hundred and ninety-eight community-living participants aged 65 and older.
  
  
  METHODS
  Multiple regression and Cox models were used to determine the effect of heart failure (HF), chronic obstructive pulmonary disease (COPD), osteoarthritis, depression, and cognitive impairment on self-rated health, 12 basic and instrumental activities of daily living (ADLs and IADLs), six-item symptom burden scale, and death.
  
  
  RESULTS
  Each condition adversely affected self-rated health (P < .001) and ADLs and IADLs (P < .001). For example, persons with HF performed 0.70 ± 0.08 fewer ADLs and IADLs than those without; persons with depression and persons with cognitive impairment performed 0.59 ± 0.04 and 0.58 ± 0.06 fewer activities, respectively, than those without these conditions. Depression, HF, COPD, and osteoarthritis were associated with 1.18 ± 0.04, 0.40 ± 0.08, 0.40 ± 0.05, and 0.57 ± 0.03 more symptoms, respectively, in individuals with these conditions than in those without. HF (hazard ratio (HR) = 2.84, 95% confidence interval (CI) = 1.97-4.10), COPD (2.62, 95% CI = 1.94-3.53), cognitive impairment (2.05, 95% CI = 1.47-2.85), and depression (1.47, 95% CI = 1.08-2.01) were each associated with death within 2 years. Several paired combinations of conditions had synergistic effects on ADLs and IADLs. For example, individuals with HF plus depression performed 2.0 fewer activities than persons with neither condition, versus the 1.3 fewer activities expected from adding the effects of the two conditions together.
  
  
  CONCLUSIONS
  Universal health outcomes may provide a common metric for measuring the effects of multiple conditions and their treatments. The varying effects of the conditions across universal outcomes could inform care priorities.
authors: Department of Medicine, School of MedicineSchool of Public Health, Yale University, New Haven, Connecticut 06520, USA. mary.tinetti@yale.edu
authors: Mary E
authors: ME
authors: Tinetti
authors: Gail J
authors: GJ
authors: McAvay
authors: Sandy S
authors: SS
authors: Chang
authors: Anne B
authors: AB
authors: Newman
authors: Annette L
authors: AL
authors: Fitzpatrick
authors: Terri R
authors: TR
authors: Fried
authors: Peter N
authors: PN
authors: Peduzzi
mesh_terms: D000368:Aged; D002908:Chronic Disease / Q000453:epidemiology*; D003072:Cognition Disorders / Q000453:epidemiology; D015897:Comorbidity; D003430:Cross-Sectional Studies; D003863:Depression / Q000453:epidemiology; D005260:Female; D006304:Health Status; D006333:Heart Failure / Q000453:epidemiology; D006801:Humans; D008297:Male; D010003:Osteoarthritis / Q000453:epidemiology; D017063:Outcome Assessment, Health Care; D016016:Proportional Hazards Models; D029424:Pulmonary Disease, Chronic Obstructive / Q000453:epidemiology; D012044:Regression Analysis