Changes in the way they walk can predict which elders are at greatest risk for frailty, disability, and death, researchers say.
“This study indicates that multiscale characteristics derived from spontaneous daily movement can be useful for health monitoring in older adults,” write Peng Li, PhD, of Brigham and Women’s Hospital, Boston, Massachusetts, and colleagues in an article published online October 30 in Science Translational Medicine.
The use of wristwatch-like actimetry sensors affixed to the wrists and ankles of research participants have allowed researchers to collect a great deal of objective data on motor activity.
In analyzing these data, researchers discovered that many complex physiologic networks fluctuate along fractal patterns, meaning that the fluctuations have similar temporal, structural, and statistical properties across a wide time scale. These patterns have been shown to indicate the ability of these systems to adapt and interact.
Li and colleagues wanted to know whether these fractal regulation patterns could be used to predict frailty and death. In 2005, they began asking elderly persons to wear wristwatch-like activity monitors on their nondominant wrists for up to 10 days as they went about their routine daily movements. These devices mostly measured the participants’ acceleration in a direction parallel to the face of the device.
After taking these baseline measurements, the researchers followed study participants until 2018. They analyzed measurements for 1275 of these individuals. At baseline, the participants’ mean age was 81 years. The mean duration of the follow-up was 6 years, and it ranged from 1 to 13 years.
Random fluctuations in walking acceleration measured at baseline corresponded with frailty, disability, and death from all causes. For every 1 standard deviation increase in the randomness of fluctuations in the way the elders walked, the risk for frailty increased by 31%, the risk for disability increased by 15% to 25%, and the risk for death increased by 26%.
These incidences occurred on average 4.7 years after baseline for frailty, 3 to 4.2 years for disability, and 5.8 years for death. The observations were independent of age, sex, education, chronic health conditions, depressive symptoms, cognition, motor function, and total daily activity.
The researchers speculate that fractal regulation is so closely tied to other measures of health because “fractal regulation reflects the complexity of physiological control,” Li and colleagues write. “Conversely, the degradation suggests a reduced complexity in the system; thus, the system becomes less adaptive to perturbations and more vulnerable to catastrophic events.”
Wrist- and ankle-worn actimetry sensors are a convenient, cost-effective, and unobtrusive form of home monitoring, the researchers say. Clinicians could use this finding to assess the risk for frailty and death among their patients and to prescribe early interventions, the researchers explain.
In addition to analytic tools, fractal physiology opens up new methods for neurologic physical therapy, they note.
For instance, one pilot study found that sleep and memory can be enhanced with acoustic stimulations using “pink noise” — a sound with similar fractal temporal correlations to those observed in such physiologic signals as motor activity, heartbeat, and brain activity.
Another study found that increasing light exposure for elderly patients could reduce or eliminate degradation in fractal regulation.
More work is needed to establish the exact mechanisms by which fractal regulation operates in physiologic networks, but Li and colleagues are hopeful that an increased understanding of fractal regulations will assist clinicians to “identify targets for interventions with the aim to improve physical well-being and longevity.”
The study was funded by the National Institutes of Health and by the International Postdoctoral Exchange Fellowship. The authors have disclosed no relevant financial relationships.
Sci Transl Med. Published online October 30, 2019. Abstract