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Erschienen in:
01.12.2014 | Original Article
A Frailty Index predicts 10-year fracture risk in adults age 25 years and older: results from the Canadian Multicentre Osteoporosis Study (CaMos)
Erschienen in: Osteoporosis International | Ausgabe 12/2014
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Summary
We created a 30-item Frailty Index in the Canadian Multicentre Osteoporosis Study. A Frailty Index is a sensitive measure that can quantify fracture risk according to degree of frailty. Our results indicated that at any age, frailty was an important independent risk factor for fracture over 10 years.
Introduction
In later life, frailty has been linked to fractures. It is likely that the antecedents of fracture are seen across the life course, in ways not entirely captured by traditional osteoporosis risk factors. Using data collected from the prospective, population-based Canadian Multicentre Osteoporosis Study (CaMos), we created the 30-item CaMos Frailty Index and examined whether it was associated with incident fractures over 10 years.
Methods
All CaMos participants aged 25 years and older (n = 9,423) were included in the analysis. To examine the relationship between baseline Frailty Index scores and incident fractures, a competing risk proportional sub-distribution hazards model was used with death considered a competing risk. Analyses were adjusted for age, sex, body mass index, education level, femoral neck T-score, and antiresorptive therapy.
Results
At baseline, the mean age was 62.1 years [standard deviation (SD) 13.4], and 69.4 % were women. The mean Frailty Index score was 0.13 (SD 0.11), ranging from 0 to 0.66. For every 0.10 increase in Frailty Index scores (approximately one SD), the hazard ratio was 1.25 (p < 0.001) for all fractures, 1.18 (p = 0.043) for hip fractures, and 1.30 (p ≤ 0.001) for clinical vertebral fractures.
Conclusion
The CaMos Frailty Index quantified fracture risk according to degree of frailty. Irrespective of age and bone mineral density, the Frailty Index was associated with hip, vertebral, and all-type clinical fractures. Predicting late onset illnesses may have to consider overall health status and not just traditional risk factors.