Survival after hip fracture: short- and long-term excess mortality according to age and gender

Osteoporos Int. 1999;10(1):73-8. doi: 10.1007/s001980050197.


The purpose of this study was to analyze the excess mortality after hip fracture and to reveal whether, and eventually when, the excess mortality vanished in different groups of age and gender. A population-based, prospective, matched-pair, cohort study among persons 50 years of age and older was conducted involving 1338 female and 487 male hip fracture patients with 11 086 and 8141 controls respectively. Occurrence of hip fracture and mortality were recorded from 1986 until 1995. We studied the excess mortality of the hip fracture patients versus controls by using Kaplan-Meier curves and extended Cox regression with hip fracture (yes/no) as time-dependent covariate. The male hip fracture patients had higher mortality than the women the first year after the injury, irrespective of age, both in absolute terms (31% and 17% respectively) and relative to their age-matched controls. The relative risk (RR) of dying within 1 year for hip fracture patients versus controls was 3.3 (95% confidence interval (CI) 2.1-5.2) for women and 4.2 (95% CI 2.8-6.4) for men below 75 years of age. The corresponding figures for persons 85 years and older were 1.6 (95% CI 1.2-2.0) for women and 3.1 (95% CI 2.2-4.2) for men. All groups of age and gender, except women 85 years and older, had a large and significant excess mortality lasting for many years after the hip fracture - at least 5-6 years for women below 75 years of age (RR = 3.2, 95% CI 1.9-5.6). The excess mortality after hip fracture for women 85 years and older had vanished after 3 months (RR = 1.0, 95% CI 0.8-1.1). When referring to the excess mortality after hip fracture it is therefore necessary to specify sex, age and time since injury.

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Case-Control Studies
  • Confidence Intervals
  • Female
  • Hip Fractures / mortality*
  • Humans
  • Male
  • Middle Aged
  • Prospective Studies
  • Regression Analysis
  • Risk Factors
  • Sex Factors
  • Survival Rate