More random motor activity fluctuations predict incident frailty, disability, and mortality

Abstract

Mobile healthcare increasingly relies on analytical tools that can extract meaningful information from ambulatory physiological recordings. We tested whether a nonlinear tool of fractal physiology could predict long-term health consequences in a large, elderly cohort. Fractal physiology is an emerging field that aims to study how fractal temporal structures in physiological fluctuations generated by complex physiological networks can provide important information about system adaptability. We assessed fractal temporal correlations in the spontaneous fluctuations of ambulatory motor activity of 1275 older participants at baseline, with a follow-up period of up to 13 years. We found that people with reduced temporal correlations (more random activity fluctuations) at baseline had increased risk of frailty, disability, and all-cause death during follow-up. Specifically, for 1-SD decrease in the temporal activity correlations of this studied cohort, the risk of frailty increased by 31%, the risk of disability increased by 15 to 25%, and the risk of death increased by 26%. These incidences occurred on average 4.7 years (frailty), 3 to 4.2 years (disability), and 5.8 years (death) after baseline. These observations were independent of age, sex, education, chronic health conditions, depressive symptoms, cognition, motor function, and total daily activity. The temporal structures in daily motor activity fluctuations may contain unique prognostic information regarding wellness and health in the elderly population.

Physical Activity Intensity Cut-Points for Wrist-Worn GENEActiv in Older Adults

“…Overall, it is still unclear which of the dominant or non-dominant wrist provides better estimates of activity intensities. Finally, a recent study indicates that temporal patterns of PA are associated with health outcomes in older adults (Li et al, 2019 ); in this regard, obtaining cutpoints that allow good separation of PA levels is even more critical.…”

Assessing the Temporal Organization of Walking Variability: A Systematic Review and Consensus Guidelines on Detrended Fluctuation Analysis

“…This is plausibly attributable to the heterogeneity in population demographics of pooled studies. The source of this heterogeneity could be assigned to the severity of disease [the walking patterns of patients with PD with only mild symptoms seem to not deviate considerably from age-matched asymptomatic controls but still show slightly higher α values than patients with advanced PD (Bartsch et al, 2007;Ota et al, 2014)], levels of physical activity [physically active older adults might not differ greatly from healthy young adult performance (Stout et al, 2016;Ducharme et al, 2019)], or fall risk, as well as fear of falling status [older adults who have not experienced a fall vs. those who have fallen previously (Herman et al, 2005;Hausdorff, 2007;Li et al, 2019)]. These issues notwithstanding, a reduction in methodological inconsistencies could contribute to increasing the reliability of DFA analyses.…”

“…As a result, a scaling exponent α of ∼1 has traditionally been interpreted to represent healthy movement patterns (Hausdorff, 2007(Hausdorff, , 2009Gow et al, 2017). Movement disorders due to aging and neurological diseases, for example, Parkinson disease [PD (Frenkel-Toledo et al, 2005;Hausdorff, 2009;Marmelat et al, 2018), but also Huntington's disease (Hausdorff et al, 1997), as well as cognitive decline (Lamoth et al, 2011)], are associated with a loss of persistence (Damouras et al, 2010;Stergiou and Decker, 2011;Ota et al, 2014;Li et al, 2019) and hence lower scaling exponent α values (nearer to 0.5). The implication is that neural pathologies might adversely influence mechanisms that regulate the nature of long-range correlations in walking.…”

Classification of Actigraphy Records from Bipolar Disorder Patients Using Slope Entropy: A Feasibility Study

“…An actigraph is a wrist-worn device used for inexpensive evaluation of sleep and circadian rhythms [ 10 , 11 , 12 ] in common conditions (ambulatory patients mainly). In general, motor activity measurement or actigraphy can be used for a disparity of clinical purposes: to quantify physical activity, in chronobiology applications, to detect sleep patterns and stages, and many more that are related to health and diseases [ 10 ].…”