title: Multiple modes of assessment of gait are better than one to predict incident falls.
abstract: BACKGROUND
  Though gait evaluation is recommended as a core component of fall risk assessments, a systematic examination of the predictive validity of different modes of gait assessments for falls is lacking.
  
  
  OBJECTIVE
  To compare three commonly employed gait assessments - self-reported walking difficulties, clinical evaluation, and quantitative gait - to predict incident falls.
  
  
  METHODS
  380 community-dwelling older adults (mean age 76.5 ± 6.8 y, 55.8% female) were evaluated with three independent gait assessment modes: patient-centered, quantitative, and clinician-diagnosed. The association of these three gait assessment modes with incident falls was examined using Cox proportional hazards models.
  
  
  RESULTS
  23.2% of participants self-reported walking difficulties, 15.5% had slow gait, and 48.4% clinical gait abnormalities. 30.3% had abnormalities on only one assessment, whereas only 6.3% had abnormalities on all three. Over a mean follow-up of 24.2 months, 137 participants (36.1%) fell. Those with at least two abnormal gait assessments presented an increased risk of incident falls (hazard ratio (HR): 1.61, 95% confidence interval (CI): 1.04-2.49) in comparison to the 169 participants without any abnormalities on any of the three assessments.
  
  
  CONCLUSIONS
  Multiple modes of gait evaluation provide a more comprehensive mobility assessment than only one assessment alone, and better identify incident falls in older adults.
authors.affiliation: Department of Neurology, Division of Cognitive & Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA; Department of Clinical Neurosciences, Geneva University Hospitals and University of Geneva, Geneva, Switzerland. Electronic address: gilles.allali@einstein.yu.edu.
authors.forename: Gilles
authors.initials: G
authors.lastname: Allali
authors.affiliation: Department of Neurology, Division of Cognitive & Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA.
authors.forename: Emmeline I
authors.initials: EI
authors.lastname: Ayers
authors.affiliation: Department of Neurology, Division of Cognitive & Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA.
authors.forename: Joe
authors.initials: J
authors.lastname: Verghese
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control*; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D005260:Female; D005684:Gait; D015577:Geriatric Assessment / Q000379:methods*; D006801:Humans; D015994:Incidence; D008297:Male; D051346:Mobility Limitation; D004856:Postural Balance; D011446:Prospective Studies; D012111:Residence Characteristics; D018570:Risk Assessment; D012307:Risk Factors
keywords: Aging; Clinical assessment; Falls; Gait disorders