Association between Daily Living Walking Speed and Walking Speed in Laboratory Settings in Healthy Older Adults

Abstract

Although there is evidence on the predictors of adverse health outcomes in older individuals, walking speed has typically been measured in laboratory settings (LWS); LWS may be distinct from individuals' actual walking speed in their daily lives (DWS). We examined whether DWS differs from LWS among older adults, and its association with physical frailty. Participants were 90 community-dwelling older adults. A five-meter normal (LWS nor ) and maximum (LWS max ) walking speed was measured with a stopwatch. DWS was measured using a global positioning system-related smartphone application for one month during their daily lives. DWS avr , DWS max , and DWS sd were defined as the average, maximum, and standard deviation of walking speed for one month. Participants' mean DWS avr and DWS max were 1.28 m/s and 2.14 m/s, respectively, significantly slower than the mean LWS nor (1.42 m/s) and LWS max (2.24 m/s); the intraclass correlation coefficient between DWS and LWS were 0.188 to 0.341. DWS was significantly correlated with grip strength, one-legged stance, and LWS. The area under the receiver operating characteristic curve of DWS sd concerning pre-frailty was largest among DWSs, at 0.615, while that of LWS nor was 0.643. The findings suggest that DWS differs from LWS and is associated with physical function and pre-frailty.

Intra-day variation in daily outdoor walking speed among community-dwelling older adults

“…In our previous study [19], we defined daily living walking speed (DWS) as the average of multiple walking speed measurements taken during daily life using a smartphone with a built-in global positioning system (GPS) and showed its re-test reliability. Moreover, we presented age-related changes in DWS [20] and the association between DWS and physical function and pre-frailty [15]. Those studies indicated that DWS declines with age, like walking speed measured in the laboratory, and that discriminability of prefrailty is comparable to laboratory walking speed, suggesting that DWS can be utilized for physical health assessment.…”

“…1). At the survey location, participants were asked whether they would participate in DWS measurement using a smartphone app for 1 month; 106 participants expressed interest [15]. Reasons for non-participation included being unwilling to use a smartphone or choosing not to take part.…”

“…For example, the discretization of laboratory-type measures can cause artificial increases in walking speeds [10]; in addition, the presence of the experimenters during data collection also increases the walking speed [11]. While this may have a small effect on maximum performance (i.e., walking a relatively short distance as fast as possible), normal walking speed (i.e., walking at a comfortable pace) measured in this way may somewhat differ from daily life walking speed, and several studies have indicated such differences [12][13][14][15][16][17]. Measuring the walking speed remotely (without an examiner) in daily life could be a better tool for the long-term assessment of older individuals' health conditions, because it can evaluate the natural walking speed in daily life and can be measured continuously.…”

“…Studies that have measured daily life gait have employed technologies including wearable accelerometer sensors and smartphone apps [12][13][14][15][16][17][18][19][20][21]. Recent developments in sensor technology enable the measurement of daily life walking speed.…”

Association between Daily Living Walking Speed and Lifestyle and Physiological Factors in Older, Female Pokémon GO Players

“…In addition, many studies evaluating walking speed are based on self-reported data or use data measured on an artificial walkway in laboratory settings where people may intentionally alter their walking speed. Walking speed measured in the laboratory is known to be different from the true walking speed in daily life [6].…”