Risk factors for death in homeless adults in Boston

Arch Intern Med. 1998 Jul 13;158(13):1454-60. doi: 10.1001/archinte.158.13.1454.


Background: Homeless individuals experience high mortality rates. Males, whites, and substance abusers are more likely to die, but other high-risk characteristics are unknown.

Objective: To identify demographic and clinical factors associated with an increased risk of death in homeless individuals.

Methods: We conducted a case-control study of 558 adults who were seen by a health care program for the homeless in Boston, Mass, and who died in 1988 to 1993. Age-matched paired controls were selected from among individuals seen by the program who were alive at the end of 1993. Predictive data were obtained by blinded review of medical records. Odds ratios (ORs) for death were calculated using logistic regression analysis models.

Results: In a multivariate analysis, the strongest risk factors for death were acquired immunodeficiency syndrome (OR, 55.8), symptomatic human immunodeficiency virus infection (OR, 17.7), asymptomatic human immunodeficiency virus infection (OR, 4.1), renal disease (OR, 18.4), a history of cold-related injury (OR, 8.0), liver disease (OR, 3.8), and arrhythmia (OR, 3.3). A history of substance abuse involving injection drugs (OR, 1.6) or alcohol (OR, 1.5) also increased the risk of mortality. Nonfluency in English was associated with a decreased risk of death (OR, 0.4).

Conclusions: In a group of adults seen by a health care program for the homeless, specific medical illnesses were associated with the greatest risk of death. Substance abuse alone was less strongly associated with death. Interventions to reduce mortality among the homeless should focus on individuals with high-risk characteristics.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Boston / epidemiology
  • Case-Control Studies
  • Death*
  • Female
  • Homeless Persons / statistics & numerical data*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Odds Ratio
  • Predictive Value of Tests
  • Risk Factors