title: The predictive value of gait speed and maximum step length for falling in community-dwelling older persons.
abstract: BACKGROUND
  Falling is a major health problem.
  
  
  OBJECTIVE
  To investigate the predictive value for falls of the maximum step length and gait speed.
  
  
  METHODS
  A prospective cohort study.
  
  
  METHODS
  Geriatric outpatient clinic.
  
  
  METHODS
  Three hundred and fifty-two community-dwelling older persons screened by their general practitioner.
  
  
  METHODS
  Maximum step length and gait speed were recorded as part of a comprehensive geriatric assessment. One-year follow-up was performed using the fall telephone system.
  
  
  RESULTS
  One hundred and thirty-six (39%) of all subjects (mean age: 76.2 years, standard deviation: 4.3, 55% female), fell at least once, of whom 96 were injured. Predictive values for any falls of both maximum step length and gait speed were low (area under the curve (AUC): 0.53 and 0.50) and slightly better for recurrent falls (maximum step length AUC: 0.64 and gait speed AUC: 0.59). After adding age, gender and fall history to the prediction model, the AUC was 0.63 for maximum step length and 0.64 for gait speed, and for recurrent falls, the AUC was 0.69 both for maximum step length and gait speed. The prediction of fall-related injuries showed similar results. A higher maximum step length score indicated a lower likelihood for falls (hazards ratio 0.36; 95% confidence interval 0.17-0.78).
  
  
  CONCLUSIONS
  Maximum step length and gait speed as single-item tools do not have sufficient power to predict future falls in community-dwelling older persons.
authors.affiliation: Department of Geriatric Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
authors.forename: Kim T J
authors.initials: KT
authors.lastname: Bongers
authors.affiliation: Department of Geriatric Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
authors.forename: Yvonne
authors.initials: Y
authors.lastname: Schoon
authors.affiliation: Department of Geriatric Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
authors.forename: Maartje J
authors.initials: MJ
authors.lastname: Graauwmans
authors.affiliation: Department of Primary and Community Care, Radboud University Medical Center, Nijmegen, The Netherlands.
authors.forename: Henk J
authors.initials: HJ
authors.lastname: Schers
authors.affiliation: Department of Geriatric Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
authors.forename: René J
authors.initials: RJ
authors.lastname: Melis
authors.affiliation: Department of Geriatric Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
authors.forename: Marcel G M
authors.initials: MG
authors.lastname: Olde Rikkert
mesh_terms: D000058:Accidental Falls; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005684:Gait; D058006:General Practice; D015577:Geriatric Assessment / Q000379:methods*; D006801:Humans; D057187:Independent Living; D008297:Male; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012008:Recurrence; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors
keywords: fall prediction; gait speed; maximum step length; mobility; older people