title: Net worth predicts symptom burden at the end of life.
abstract: OBJECTIVE
  To explore the predictors of symptom burden at the end of life.
  
  
  METHODS
  Observational, secondary analysis of Health and Retirement Study (HRS) data.
  
  
  METHODS
  USA.
  
  
  METHODS
  Two thousand six hundred four deceased, older adults.
  
  
  METHODS
  Multivariate Poisson and logistic regression to explore the relationship between sociodemographic and clinical factors with symptoms.
  
  
  RESULTS
  Fatigue, pain, dyspnea, depression, and anorexia were common and severe; 58% of participants experienced more than 3 of these during their last year of life. Sociodemographic and clinical factors were associated with the number of symptoms as well as the presence of pain, depression, and dyspnea alone. Decedents in the highest quartile of net worth had fewer symptoms (incident rate ratio [IRR] 0.90, confidence interval [CI] 0.85-0.96) and less pain (odds ratio [OR] 0.66, CI 0.51-0.85) than comparisons did. Patients with cancer experienced more pain (OR 2.02, CI 1.62-2.53) and depression (OR 1.31, CI 1.07-1.61). Patients experienced more depression (OR 2.37, CI 1.85-3.03) and dyspnea (OR 1.40, CI 1.09-1.78).
  
  
  CONCLUSIONS
  Use of proxy reports for primary data.
  
  
  CONCLUSIONS
  Older Americans experience a large symptom burden in the last year of life, largely with treatable symptoms such as pain, dyspnea, and depression. The adequacy of symptom control relates to clinical factors as well as net worth. This association between symptoms and wealth suggests that access to health care and other social services beyond those covered by Medicare may be important in decreasing symptom burden at the end of life.
authors.affiliation: VA Health Services Research & Development Center of Excellence, VA Ann Arbor Healthcare System, 300 North Ingalls Building, Ann Arbor, MI 48109-0429, USA. mariajs@umich.edu
authors.forename: Maria J
authors.initials: MJ
authors.lastname: Silveira
authors.forename: Mohammed U
authors.initials: MU
authors.lastname: Kabeto
authors.forename: Kenneth M
authors.initials: KM
authors.lastname: Langa
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003625:Data Collection; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D012720:Severity of Illness Index; D012923:Social Class; D019452:Terminally Ill; D014481:United States