Abstract
Standing postural control is complex, meaning that it is dependent upon numerous inputs interacting across multiple temporal-spatial scales. Diminished physiologic complexity of postural sway has been linked to reduced ability to adapt to stressors. We hypothesized that older adults with lower postural sway complexity would experience more falls in the future. 738 adults aged ≥70 years completed the Short Physical Performance Battery test (SPPB) test and assessments of single and dual-task standing postural control. Postural sway complexity was quantified using multiscale entropy. Falls were subsequently tracked for 48 months. Negative binomial regression demonstrated that older adults with lower postural sway complexity in both single and dual-task conditions had higher future fall rate (incident rate ratio (IRR) = 0.98, p = 0.02, 95% Confidence Limits (CL) = 0.96–0.99). Notably, participants in the lowest quintile of complexity during dual-task standing suffered 48% more falls during the four-year follow-up as compared to those in the highest quintile (IRR = 1.48, p = 0.01, 95% CL = 1.09–1.99). Conversely, traditional postural sway metrics or SPPB performance did not associate with future falls. As compared to traditional metrics, the degree of multi-scale complexity contained within standing postural sway-particularly during dual task conditions- appears to be a better predictor of future falls in older adults.
Highlights
System, the relationship between these inputs and related muscular outputs is continuously modulated over time; the system dynamically “re-weights” the relative influence of each type of feedback on postural muscle activation in order to optimize performance in a given situation[9, 10]
We hypothesized that as opposed to traditional metrics, those metrics aimed at capturing the physiologic “complexity” of postural sway will more accurately reflect the integrity of the postural control system and better identify those at risk of suffering falls in the future
When comparing the postural sway metrics, fallers exhibited lower postural sway complexity in both ST and DT conditions (p < 0.007) at baseline than non-fallers, while the traditional parameters (i.e., sway speed, sway area and anterioposterior (AP) path length) or Short Physical Performance Battery test (SPPB) score did not differ between fallers and non-fallers
Summary
System, the relationship between these inputs and related muscular outputs is continuously modulated over time; the system dynamically “re-weights” the relative influence of each type of feedback on postural muscle activation in order to optimize performance in a given situation[9, 10]. We chose to quantify the degree of postural sway complexity during single- and dual-task standing using a technique called multiscale entropy (MSE)[18]. MSE is one of numerous non-linear time-series analytical techniques that have been used to estimate postural sway complexity[19]. This approach quantifies the degree of re-occurrence of repetitive patterns within sway fluctuations. We hypothesized that that those with lower MSE-derived complexity of postural sway during single or dual task standing at baseline would suffer more falls in the future
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