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The Physical Performance Test as a predictor of frequent fallers: a prospective community-based cohort study

Department of Rehabilitation Sciences and Physiotherapy, Ghent, Belgium

Nele Van den Noortgate

Department of Geriatrics and Gerontology, Ghent, Belgium

Jan Bourgois

Guy Vanderstraeten

Willems Tine

Dirk Cambier

Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium

Objective: To construct a risk model in order to identify elderly individuals at risk of frequent falling.

Design: Prospective community-based cohort study over 12 months.

Setting: Baseline measures were performed at a local community centre.

Subjects: Two hundred and sixty-three community-dwelling elderly people (mean age 72 years).

Measurements: A variety of variables were evaluated, including medical, psychological, sensory, physical and postural control measurements. Fall incidence was monitored retrospectively and during one-year follow-up.

Results: Logistic regression analysis showed that polypharmacia was the most prominent medical fall predictor with an odds ratio (OR) of 1.29 (P =0.005), poor visual acuity the best sensory predictor (OR=0.84; P =0.009) and general fear of falling the most crucial psychological predictor (OR=3.25; P B=0.001). Increased postural sway in near-tandem stance with eyes open was selected as the best balance predictor for falls (OR=5.60; P =0.010), followed by delayed anteroposterior movement velocity during rhythmic weight shifts (OR=0.42; P =0.004). The best physical predictor was a low score on the Physical Performance Test (OR=4.16; P <0.001), followed by decreased maximal handgrip strength (OR=0.87; P <0.001) and increased timed chair-stands (OR=1.13; P <0.003). Step-by-step regression analysis revealed a risk model for the prediction of future falls, as a combination of the Physical Performance Test and maximal handgrip strength.

Conclusion: This study confirms the multicausality of falls, since medical, psychological, sensory, postural control as well as physical variables provides a predictive value. The composed fall risk model was mainly physically oriented.

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