Determinants of fracture risk in a UK-population-based cohort of older women: a cross-sectional analysis of the Cohort for Skeletal Health in Bristol and Avon (COSHIBA)

Background: identification of individuals with high fracture risk from within primary care is complex. It is likely that the true contribution of falls to fracture risk is underestimated. Methods: cross-sectional analysis of a population-based cohort of 3,200 post-menopausal women aged 73 ± 4 years. Self-reported data were collected on fracture, osteoporosis clinical risk factors and falls/mobility risk factors. Self-reported falls were compared with recorded falls on GP computerised records. Multivariable logistic regression was used to identify independent risk factors for fracture. Results: a total of 838 (26.2%) reported a fracture after aged 50; 441 reported falling more than once per year, but 69% of these had no mention of falls on their computerised GP records. Only age [odds ratios (OR): 1.37 per 5 year increase, 95% confidence interval (CI): 1.23–1.53], height (1.02 per cm increase, 95% CI: 1.01–1.04), weight (OR: 0.99 per kg increase, 95% CI: 0.98–0.99) and falls (OR: 1.49 for more than once per year compared with less, 95% CI: 1.13–1.94) were independent risk factors for fracture. Falls had the strongest association. Conclusion: when identifying individuals with high fracture risk we estimate that more than one fall per year is at least twice as important as height and weight. Furthermore, using self-reported falls data is essential as computerised GP records underestimate falls prevalence.