Predictors for Falls and Fractures in the Longitudinal Aging Study Amsterdam
Open Access
- 1 December 1998
- journal article
- research article
- Published by Oxford University Press (OUP) in Journal of Bone and Mineral Research
- Vol. 13 (12) , 1932-1939
- https://doi.org/10.1359/jbmr.1998.13.12.1932
Abstract
The objective of this study was to identify easily measurable predictors for falls, recurrent falls, and fractures using a population-based prospective cohort study of 1469 elderly, born before 1931, in three regions of the Netherlands. The baseline at-home interview was in 1992. In 1995, falls experienced in the preceding year and fractures over the preceding 38-month period were registered. In a period of 1 year, 32% of the participants fell at least once, and 15% fell two or more times. The rate of recurrent falls was similar in men and women up until the age of 75 years. The total number of fractures was 85, including 23 wrist fractures, 12 hip fractures, and 9 humerus fractures. The incidence density per 1000 person-years for any fracture was 25.1 (95% confidence interval [CI], 18.9–31.4) for women and 8.2 (95% CI, 4.5–12.0) for men, respectively. Multiple logistic regression identified urinary incontinence, impaired mobility, use of analgetics, and use of antiepileptic drugs as the predictors most strongly associated with recurrent falls. Female gender, living alone, past fractures, inactivity, body height, and use of analgetics proved to be the predictors most strongly associated with fractures. The probabilities of recurrent falls were 4.7% (95% CI, 2.9–7.5%) to 59.2% (95% CI, 24.1–86.9%) with zero to four predictors, respectively. The probability of fractures ranged from 0.0% (95% CI, 0.0–0.4%) without any of the identified predictors to 12.9% (95% CI, 4.4–32.2%) with all six predictors present. Our study shows that the risk of recurrent falls and of fractures can be predicted using up to, respectively, four and six easily measurable predictors. This study emphasizes the importance of impaired mobility and inactivity as predictors for falls and fractures.Keywords
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