Free-Living Gait Cadence Measured by Wearable Accelerometer: A Promising Alternative to Traditional Measures of Mobility for Assessing Fall Risk

Background Wearable devices have become widespread in research applications, yet evidence on whether they are superior to structured clinic-based assessments is sparse. In this manuscript, we compare traditional, laboratory-based metrics of mobility with a novel accelerometry-based measure of free-living gait cadence for predicting fall rates. Methods Using negative binomial regression, we compared traditional in-clinic measures of mobility (6-minute gait cadence, speed, and distance, and 4-m gait speed) with free-living gait cadence from wearable accelerometers in predicting fall rates. Accelerometry data were collected with wrist-worn Actigraphs (GT9X) over 7 days in 432 community-dwelling older adults (aged 77.29 +/- 5.46 years, 59.1% men, 80.2% White) participating in the Study to Understand Fall Reduction and Vitamin D in You. Falls were ascertained using monthly calendars, quarterly contacts, and ad hoc telephone reports. Accelerometry-based free-living gait cadence was estimated with the Adaptive Empirical Pattern Transformation algorithm. Results Across all participants, free-living cadence was significantly related to fall rates; every 10 steps per minute higher cadence was associated with a 13.2% lower fall rate (p = .036). Clinic-based measures of mobility were not related to falls (p > .05). Among higher-functioning participants (cadence >= 100 steps/minute), every 10 steps per minute higher free-living cadence was associated with a 27.7% lower fall rate (p = .01). In participants with slow baseline gait (gait speed <0.8 m/s), all metrics were significantly associated with fall rates. Conclusion Data collected from biosensors in the free-living environment may provide a more sensitive indicator of fall risk than in-clinic tests, especially among higher-functioning older adults who may be more responsive to intervention.

Automated summary

This study compared traditional laboratory-based measures of mobility with free-living gait cadence in predicting fall rates. The results showed that free-living cadence was significantly related to fall rates, while clinic-based measures of mobility were not. This suggests that data collected from biosensors in the free-living environment may provide a more sensitive indicator of fall risk.