Fractures after nursing home admission: incidence and potential consequences

Osteoporos Int. 2009 Oct;20(10):1775-83. doi: 10.1007/s00198-009-0852-y. Epub 2009 Feb 24.

Abstract

Summary: Fracture rates were examined in residents newly admitted to nursing homes. The risk of a fracture was highest during the first months after admission and declined thereafter. This risk pattern was observed independently of fracture site, gender or degree of care need.

Introduction and hypothesis: Residents of nursing homes are a high-risk group for fractures. The aim of the study was to analyse fracture rates as a function of time from admission to nursing home.

Methods: Fractures of the upper limb, femur, pelvis and lower leg, time to first and subsequent fractures, age, gender and care needs at admission were measured in 93,424 women and men aged 65 years and over and newly admitted to nursing homes in Bavaria between 2001 and 2006.

Results: Fracture incidence was highest during the first months after admission to nursing homes and declined thereafter. This pattern was observed for all fracture sites, in women and men and in residents with different care needs. For example, fracture rates of the upper limb declined from 30.0 to 13.5/1,000 person-years in the first 9 months after admission and for all fracture sites from 135.3 to 69.4/1,000 person-years in a corresponding time period.

Conclusion: Newly admitted residents have the highest fracture risk. The pattern of risk is similar across all fractures, suggesting a generic causal pathway. Implementation of effective fracture prevention efforts should be a priority at the time of admission to nursing homes.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Female
  • Femoral Fractures / epidemiology
  • Fractures, Bone / epidemiology*
  • Germany / epidemiology
  • Homes for the Aged / statistics & numerical data*
  • Hospitalization / statistics & numerical data
  • Humans
  • Incidence
  • Male
  • Nursing Homes / statistics & numerical data*
  • Patient Admission
  • Risk Assessment / methods
  • Sex Distribution
  • Time Factors