Intraindividual Variability of Neuromotor Function Predicts Falls Risk in Older Adults and those with Type 2 Diabetes

Abstract

This study was designed to examine the effect of increasing age and type 2 diabetes on the average responses and inter- and intraindividual variability of falls risk, reaction time, strength, and walking speed for healthy older adults and older persons with type 2 diabetes (T2DM). Seventy-five older individuals (controls) and 75 persons with T2DM aged between 50 and 79 years participated in the study. Assessments of falls risk, reaction time (RT), knee extension strength, and walking speed were conducted. The results revealed that advancing age for both control and T2DM groups was reflected by a progressive increase in falls risk, decreased leg strength and a decline (i.e., slowing) of reactions and gait speed. Conversely, the level of intraindividual variability for the RT, strength and gait measures increased with increasing age for both groups, with T2DM persons tending to be more variable compared to the healthy controls of similar age. In contrast to the intraindividual changes, measures of interindividual variability revealed few differences between the healthy elderly and T2DM individuals. Taken together, the findings support the proposition that intraindividual variability of neuromotor measures may be useful as a biomarker for the early detection of decline in physiological function due to age or disease.

A Wearable Biofeedback Device to Increase Gait Swing Time Could Have Positive Effects on Gait among Older Adults

“…If the Shapiro–Wilks tests indicated that normality of data could not be assumed, the Wilcoxon test was used instead. The level of significance α was established as 0.05 [ 48 , 49 ]. We hypothesized that the smart insoles significantly changed the four primary outcome variables: swing time, hip flexion angle, stride length and cadence.…”

The Dynamic Motor Control Index as a Marker of Age-Related Neuromuscular Impairment

“…During adult aging, physiological changes lead to impaired muscle strength (Janssen et al, 2002;Doherty, 2003;Lauretani et al, 2003;Goodpaster et al, 2006;King et al, 2016;Morrison and Newell, 2019), increased muscular atrophy (Janssen et al, 2002;Doherty, 2003;Lauretani et al, 2003;Goodpaster et al, 2006), and reduced neuromuscular control (i.e., impaired muscle recruitment and coordination) (Clark et al, 2010;Dingwell et al, 2017;Morrison and Newell, 2019;Kara et al, 2020). As a result, older adults tend to have poorer balance (King et al, 2016;Cruz-Jimenez, 2017), walk at slower speeds (Menz et al, 2003;Kim and Kim, 2014;Cruz-Jimenez, 2017), and take fewer steps per day (Bassett et al, 2010) than younger adults.…”

“…As a result, older adults tend to have poorer balance (King et al, 2016;Cruz-Jimenez, 2017), walk at slower speeds (Menz et al, 2003;Kim and Kim, 2014;Cruz-Jimenez, 2017), and take fewer steps per day (Bassett et al, 2010) than younger adults. These deficits continue to progress with further aging; endurance (Gardener et al, 2006;Schrack et al, 2016), walking speed (Xie et al, 2017;Morrison and Newell, 2019), balance (Xie et al, 2017), and muscle mass (Doherty, 2003;Castell et al, 2013;Rong et al, 2020) significantly decrease with increasing age from 50 to 80+ years old. Untreated, these impairments can lead to significantly reduced participation in the community (Allison et al, 2013;Warren et al, 2016) and an increased risk of falling (Verghese et al, 2009;Toebes et al, 2012;Ambrose et al, 2013;Lusardi et al, 2017), one of the leading causes of morbidity among older adults (Burns and Kakara, 2018).…”