title: Good lateral harmonic stability combined with adequate gait speed is required for low fall risk in older people.
abstract: BACKGROUND
  Good lateral harmonic stability in gait may be important for minimising fall risk in older people because many falls occur during walking when the base of support is narrowest in the mediolateral (ML) direction. However, the traditional ML harmonic ratio (MLHR) may be a sub-optimal measure of gait quality because of insufficient frequency resolution.
  
  
  OBJECTIVE
  The primary objective was to investigate if a new measure of lateral harmonic stability, the 8-step MLHR, could discriminate older fallers from non-fallers while taking different walking speeds into account.
  
  
  METHODS
  Repeat walks over 20 m were completed by 96 older people (mean age 80, SD 4 years); 35 participants had a history of one or more falls in the past year. The traditional MLHR and the 8-step MLHR were obtained from an accelerometer attached to the sacrum.
  
  
  RESULTS
  Compared to the traditional MLHR, the 8-step MLHR demonstrated similar univariate ability to identify significant differences in fall risk based on age, walking speed and physiology (p ≤ 0.05). When differences in walking speed were taken into account, we observed that participants who walked both faster than average and had above-average lateral harmonic stability (by the 8-step MLHR) were 5.3 times less likely to be fallers than all other participants (relative risk: 0.19, 95% confidence interval: 0.06-0.57). For the traditional MLHR, however, no significant differences between the fallers and non-fallers were evident.
  
  
  CONCLUSIONS
  The findings indicate that good lateral harmonic stability interacts with adequate gait speed and, when coincident, are associated with reduced fall risk in older people. Future research could examine whether interventions focusing on enhancing both gait speed and lateral stability can reduce fall risk and whether these combined gait measures can remotely predict deteriorating health using wearable technology.
authors.affiliation: Falls and Balance Research Group, Neuroscience Research Australia, University of New South Wales, Sydney, N.S.W., Australia.
authors.forename: Matthew A D
authors.initials: MA
authors.lastname: Brodie
authors.forename: Hylton B
authors.initials: HB
authors.lastname: Menz
authors.forename: Stuart T
authors.initials: ST
authors.lastname: Smith
authors.forename: Kim
authors.initials: K
authors.lastname: Delbaere
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Lord
mesh_terms: D000058:Accidental Falls; D000368:Aged; D000369:Aged, 80 and over; D001696:Biomechanical Phenomena; D005080:Exercise Test; D005260:Female; D005684:Gait; D006801:Humans; D008297:Male; D004856:Postural Balance; D012306:Risk; D018570:Risk Assessment; D013997:Time Factors; D016138:Walking