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      The Complexity of Standing Postural Sway Associates with Future Falls in Community-Dwelling Older Adults: The MOBILIZE Boston Study

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          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.

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          Risk factors for falls among elderly persons living in the community.

          To study risk factors for falling, we conducted a one-year prospective investigation, using a sample of 336 persons at least 75 years of age who were living in the community. All subjects underwent detailed clinical evaluation, including standardized measures of mental status, strength, reflexes, balance, and gait; in addition, we inspected their homes for environmental hazards. Falls and their circumstances were identified during bimonthly telephone calls. During one year of follow-up, 108 subjects (32 percent) fell at least once; 24 percent of those who fell had serious injuries and 6 percent had fractures. Predisposing factors for falls were identified in linear-logistic models. The adjusted odds ratio for sedative use was 28.3; for cognitive impairment, 5.0; for disability of the lower extremities, 3.8; for palmomental reflex, 3.0; for abnormalities of balance and gait, 1.9; and for foot problems, 1.8; the lower bounds of the 95 percent confidence intervals were 1 or more for all variables. The risk of falling increased linearly with the number of risk factors, from 8 percent with none to 78 percent with four or more risk factors (P less than 0.0001). About 10 percent of the falls occurred during acute illness, 5 percent during hazardous activity, and 44 percent in the presence of environmental hazards. We conclude that falls among older persons living in the community are common and that a simple clinical assessment can identify the elderly persons who are at the greatest risk of falling.
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            Approximate entropy as a measure of system complexity.

            Techniques to determine changing system complexity from data are evaluated. Convergence of a frequently used correlation dimension algorithm to a finite value does not necessarily imply an underlying deterministic model or chaos. Analysis of a recently developed family of formulas and statistics, approximate entropy (ApEn), suggests that ApEn can classify complex systems, given at least 1000 data values in diverse settings that include both deterministic chaotic and stochastic processes. The capability to discern changing complexity from such a relatively small amount of data holds promise for applications of ApEn in a variety of contexts.
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              Multiscale entropy analysis of biological signals

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                Author and article information

                Contributors
                junhongzhou@hsl.harvard.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                7 June 2017
                7 June 2017
                2017
                : 7
                : 2924
                Affiliations
                [1 ]ISNI 000000041936754X, GRID grid.38142.3c, , Hebrew SeniorLife Institute for Aging Research, ; Roslindale, MA USA
                [2 ]ISNI 0000 0000 9011 8547, GRID grid.239395.7, , Beth Israel Deaconess Medical Center, ; Boston, MA USA
                [3 ]ISNI 000000041936754X, GRID grid.38142.3c, , Harvard Medical School, ; Boston, MA USA
                Article
                3422
                10.1038/s41598-017-03422-4
                5462759
                28127054
                39a9c28d-47d9-4031-be60-e49f962213f7
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 26 August 2016
                : 28 April 2017
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