Predictive Model of the Risk of Fall Based on Physical Fitness Assessment in Older Adults

Authors

HORÁKOVÁ Andrea SVOBODOVÁ Lenka SEBERA Martin GIMUNOVÁ Marta

Year of publication 2023
Type Article in Periodical
Magazine / Source Studia Sportiva
MU Faculty or unit

Faculty of Sports Studies

Citation
web https://journals.muni.cz/studiasportiva/article/view/35471
Doi http://dx.doi.org/10.5817/StS2023-2-12
Keywords TUG; physical tests; elderly; falling; prevention
Description Falls occurring during activities of daily living pose a major threat and are the third most common cause of death in seniors. In clinical evaluations, mostly single tests are used to assess the risk of fall. However, a complex set of tests would lead to a more comprehensive assessment of the risk of falls. The purpose of this study was to develop a predictive model of the risk of falls in older adults aimed to prevent injuries. This study involved 159 older adults (?65, 77% women) who underwent laboratory testing consisting of questionnaires, physical tests and basic anthropometric data measurement. The data were processed by a statistical method of regression analysis, the Classification and Regression Tree. Based on the analysis a predictive model of the risk of fall for older adults was created. The most important variables for the predictive model were total % of body fat mass, Timed Up and Go Test and 2 minutes walking test. Based on the predictive model, we can design a targeted intervention program for elderly adults to prevent risk of falling, promoting well-being and increase quality of their life.
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