Incidence of nursing home placement in a defined community

Med J Aust. 2001 Mar 19;174(6):271-5. doi: 10.5694/j.1326-5377.2001.tb143267.x.

Abstract

Objective: To assess cumulative incidence and non-cognitive factors predicting nursing home placement in a defined older population.

Design and setting: Six-year follow-up of a population-based cohort living west of Sydney.

Participants: 3654 non-institutionalised residents aged 49 years or older (82.4% of those eligible) participated in baseline examinations during 1992 to 1994.

Main outcome measures: Permanent nursing home admission for long-term institutionalised aged care in New South Wales, confirmed by records of approvals by the regional Aged Care Assessment Team and subsidy payments by government.

Results: After excluding 384 participants who moved from the area or were lost to follow-up, 162 participants (5.0%) had been admitted to nursing homes on a permanent basis by October 1999. Of participants who died since baseline, 20% had been admitted to a nursing home before death. Of those alive, 1.6% were current nursing home residents. Six-year cumulative incidence rates for nursing home placement were 0.7%, 1.1%, 2.4%, 3.9%, 9.0%, 18.3% and 34.9% for people aged 55-59, 60-64, 65-69, 70-74, 75-79, 80-84 and 85 years or older, respectively. Non-cognitive factors at baseline predicting subsequent nursing home admission included each additional year of age (risk ratio [RR], 1.14), fair or poor compared with excellent self-rated health (RR, 2.9, 3.6), walking difficulty (RR, 3.6) and current smoking (RR, 1.9). People owning their homes had a decreased likelihood of nursing home placement (RR, 0.6).

Conclusions: Incidence rates of institutional aged care doubled for each five-year interval from the age of 60 years. A range of non-cognitive factors predict nursing home placement.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Causality
  • Female
  • Health Status
  • Homes for the Aged / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • New South Wales
  • Nursing Homes / statistics & numerical data*
  • Patient Admission / statistics & numerical data*
  • Proportional Hazards Models
  • Risk