Mobility in Old Age: Capacity Is Not Performance

Abstract

Background. Outcomes of laboratory-based tests for mobility are often used to infer about older adults' performance in real life; however, it is unclear whether such association exists. We hypothesized that mobility capacity, as measured in the laboratory, and mobility performance, as measured in real life, would be poorly linked. Methods. The sample consisted of 84 older adults (72.5 ± 5.9 years). Capacity was assessed via the iTUG and standard gait parameters (stride length, stride velocity, and cadence). Performance was assessed in real life over a period of 6.95 ± 1.99 days using smartphone technology to calculate following parameters: active and gait time, number of steps, life-space, mean action-range, and maximum action-range. Correlation analyses and stepwise multiple regression analyses were applied. Results. All laboratory measures demonstrated significant associations with the real-life measures (between r = .229 and r = .461). The multiple regression analyses indicated that the laboratory measures accounted for a significant but very low proportion of variance (between 5% and 21%) in real-life measures. Conclusion. In older adults without mobility impairments, capacity-related measures of mobility bear little significance for predicting real-life performance. Hence, other factors play a role in how older people manage their daily-life mobility. This should be considered for diagnosis and treatment of mobility deficits in older people.

Is a decrease of grip strength associated with community mobility restriction in dynapenic older women?

“…These results to suggest that grip strength should not be used to predict the risk of mobility limitation in real life settings. Also, our results imply that functional test performances are not readily translatable to community mobility, and as such agree with Giannouli and al (2016) who acknowledged the difference between capacityrelated measures and real-life performance [28]. In fact, an individual may have the physical capacity to move freely outside his/her home, but this does not imply that he or she will capitalize on this ability and have a higher level of community mobility.…”

Concern about Falling and Complexity of Free-Living Physical Activity Patterns in Well-Functioning Older Adults

“…the usual locomotion cadence (r = -0.38, p = 0.010), the number of locomotion periods with at least 30 steps and 100 steps/min (r = -0.50, p = 0.001), and PA complexity (PLZC metric, p = -0.35, p = 0.040). These weak to moderate correlations are in line with accumulated evidence suggesting that functional mobility assessed in the lab/clinic does not entirely reflect an individual's functioning in everyday life [34,35].…”

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“…The lack of association between volumes of activity and physical performance measures concurs with earlier reports (van Lummel et al, 2015;Weiss et al, 2013). Others have found associations between laboratory-based gait speed measures (Giannouli et al, 2016;Hall et al, 2017) (which we did not measure) and step count, although comparisons are limited due to methodological differences.…”

“…Together these features have been described as the 'macro' level of activity. A further advantage of wearable sensors is that detailed gait characteristics (features such as step length, step variability, step asymmetry) can be measured simultaneously, producing data with more ecological validity than that collected in the clinic or laboratory where assessments are independent of context and influenced by test protocol and attentional drive (Del Din, Godfrey, Galna, Lord, & Rochester, 2016;Giannouli, Bock, Mellone, & Zijlstra, 2016;Robles-García et al, 2015;Weiss et al, 2013). These detailed features comprise the 'micro' level of gait.…”