A prospective community-based pilot study of risk factors for the investigation of elder mistreatment

J Am Geriatr Soc. 1994 Feb;42(2):169-73. doi: 10.1111/j.1532-5415.1994.tb04947.x.

Abstract

Purpose: To identify risk factors for the investigation of elder abuse, neglect, self-neglect, exploitation, and abandonment in a population-based observational cohort of community living elders.

Study population: Population-based sample of 2,812 community-living men and women in New Haven, Connecticut who were over age 65 in 1982.

Methods: Matching process whereby cohort members who were investigated by Connecticut's State Ombudsman on Aging in 1985 or 1986 were identified.

Analysis: Relative risks for ombudsman investigation in 1985 or 1986 were calculated based on risk factors status at baseline interview in 1982.

Results: Sixty-eight (2.4%) members of the cohort received investigation. Features at cohort entry significantly associated with investigation in multiple logistic regression included: requiring assistance with feeding (Adjusted OR 3.5, 95% CI 1.2, 11.7), being a minority elder (Adj. OR 2.3, 95% CI 1.4, 2.8), over age 75 at cohort inception (Adj. OR 1.9, 95% CI 1.1, 3.1), and having a poor social network as defined by a social network index (Adj. OR 1.7, 95% CI 1.0, 2.7). When stratified by race, requiring assistance with feeding was associated with ombudsman investigation in minority elders (Adj. OR 10.8, 95% CI 2.8, 40.5) but not non-minority elders (Adj. OR 1.1, 95% CI 0.5, 7.5).

Conclusion: Functional disability, minority status, older age, and poor social networks were associated with investigation for elder mistreatment in this prospective, community-based population of men and women over the age of 65.

Publication types

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

MeSH terms

  • Activities of Daily Living
  • Aged
  • Analysis of Variance
  • Connecticut / epidemiology
  • Elder Abuse / statistics & numerical data*
  • Female
  • Humans
  • Logistic Models
  • Male
  • Minority Groups / statistics & numerical data
  • Patient Advocacy
  • Pilot Projects
  • Prospective Studies
  • Residence Characteristics
  • Risk Factors