Identifying interacting predictors of falling among hospitalized elderly in Japan: A signal detection approach
Article first published online: 7 JUN 2007
Geriatrics & Gerontology International
Volume 7, Issue 2, pages 160–166, June 2007
How to Cite
Nabeshima, A., Hagihara, A., Hayashi, K., Nabeshima, S. and Okochi, J. (2007), Identifying interacting predictors of falling among hospitalized elderly in Japan: A signal detection approach. Geriatrics & Gerontology International, 7: 160–166. doi: 10.1111/j.1447-0594.2007.00391.x
- Issue published online: 7 JUN 2007
- Article first published online: 7 JUN 2007
- Accepted for publication 6 December 2006.
- signal detection analysis
Falling is a complex phenomenon that involves interaction of multiple risk factors. The authors analyzed factors related to falls in a geriatric hospital to elucidate interaction of multiple risk factors for falls in elderly inpatients. Subjects were 364 patients (mean age, 81.7; women 76.7%) who were aged 60 years and over and had been hospitalized for more than 6 months between April 2000 and March 2001. A signal detection model was used to identify baseline variables that best divided the sample into subgroups using incidence of falling as an outcome variable. During a follow-up period, 91 patients (25%) had at least one incident of fall. Out of 14 independent variables, a higher-order interaction consisting of six significant variables was identified. Consequently, the subjects were categorized into seven subgroups whose fall rate varied 5.7–80.9%. We found that the combination of non-bedridden state, dementia, and medication of tranquilizers or sleeping drugs was the highest fall rate (80.9%). Signal detection analysis is useful to identify the combination of multiple risk factors of falling, and applicable to develop prevention programs for each subgroups.