title: The Physical Performance Test as a predictor of frequent fallers: a prospective community-based cohort study.
abstract: OBJECTIVE
  To construct a risk model in order to identify elderly individuals at risk of frequent falling.
  
  
  METHODS
  Prospective community-based cohort study over 12 months.
  
  
  METHODS
  Baseline measures were performed at a local community centre.
  
  
  METHODS
  Two hundred and sixty-three community-dwelling elderly people (mean age 72 years).
  
  
  METHODS
  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< 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Belgium. Kim.Delbaere@UGent.be
authors.forename: Kim
authors.initials: K
authors.lastname: Delbaere
authors.forename: Nele
authors.initials: N
authors.lastname: Van den Noortgate
authors.forename: Jan
authors.initials: J
authors.lastname: Bourgois
authors.forename: Guy
authors.initials: G
authors.lastname: Vanderstraeten
authors.forename: Willems
authors.initials: W
authors.lastname: Tine
authors.forename: Dirk
authors.initials: D
authors.lastname: Cambier
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control* / Q000706:statistics & numerical data; D000368:Aged; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D016015:Logistic Models; D008297:Male; D008403:Mass Screening; D008962:Models, Theoretical; D011446:Prospective Studies; D011597:Psychomotor Performance; D018570:Risk Assessment