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Physical performance analysis: A new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations

BACKGROUND: Accurate measurement of physical performance in individuals with musculoskeletal pain is essential. Accelerometry is a powerful tool for this purpose, yet the current methods designed to evaluate energy expenditure are not optimized for this population. The goal of this study is to empir...

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Autores principales: Smuck, Matthew, Tomkins-Lane, Christy, Ith, Ma Agnes, Jarosz, Renata, Kao, Ming-Chih Jeffrey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5325560/
https://www.ncbi.nlm.nih.gov/pubmed/28235039
http://dx.doi.org/10.1371/journal.pone.0172804
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author Smuck, Matthew
Tomkins-Lane, Christy
Ith, Ma Agnes
Jarosz, Renata
Kao, Ming-Chih Jeffrey
author_facet Smuck, Matthew
Tomkins-Lane, Christy
Ith, Ma Agnes
Jarosz, Renata
Kao, Ming-Chih Jeffrey
author_sort Smuck, Matthew
collection PubMed
description BACKGROUND: Accurate measurement of physical performance in individuals with musculoskeletal pain is essential. Accelerometry is a powerful tool for this purpose, yet the current methods designed to evaluate energy expenditure are not optimized for this population. The goal of this study is to empirically derive a method of accelerometry analysis specifically for musculoskeletal pain populations. METHODS: We extracted data from 6,796 participants in the 2003–4 National Health and Nutrition Examination Survey (NHANES) including: 7-day accelerometry, health and pain questionnaires, and anthropomorphics. Custom macros were used for data processing, complex survey regression analyses, model selection, and statistical adjustment. After controlling for a multitude of variables that influence physical activity, we investigated whether distinct accelerometry profiles accompany pain in different locations of the body; and we identified the intensity intervals that best characterized these profiles. RESULTS: Unique accelerometry profiles were observed for pain in different body regions, logically clustering together based on proximity. Based on this, the following novel intervals (counts/minute) were identified and defined: Performance Sedentary (PSE) = 1–100, Performance Light 1 (PL1) = 101–350, Performance Light 2 (PL2) = 351–800, Performance Light 3 (PL3) = 801–2500, and Performance Moderate/Vigorous (PMV) = 2501–30000. The refinement of accelerometry signals into these new intervals, including 3 distinct ranges that fit inside the established light activity range, best captures alterations in real-life physical performance as a result of regional pain. DISCUSSION AND CONCLUSIONS: These new accelerometry intervals provide a model for objective measurement of real-life physical performance in people with pain and musculoskeletal disorders, with many potential uses. They may be used to better evaluate the relationship between pain and daily physical function, monitor musculoskeletal disease progression, gauge disease severity, inform exercise prescription, and quantify the functional impact of treatments. Based on these findings, we recommend that future studies of pain and musculoskeletal disorders analyze accelerometry output based on these new “physical performance” intervals.
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spelling pubmed-53255602017-03-09 Physical performance analysis: A new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations Smuck, Matthew Tomkins-Lane, Christy Ith, Ma Agnes Jarosz, Renata Kao, Ming-Chih Jeffrey PLoS One Research Article BACKGROUND: Accurate measurement of physical performance in individuals with musculoskeletal pain is essential. Accelerometry is a powerful tool for this purpose, yet the current methods designed to evaluate energy expenditure are not optimized for this population. The goal of this study is to empirically derive a method of accelerometry analysis specifically for musculoskeletal pain populations. METHODS: We extracted data from 6,796 participants in the 2003–4 National Health and Nutrition Examination Survey (NHANES) including: 7-day accelerometry, health and pain questionnaires, and anthropomorphics. Custom macros were used for data processing, complex survey regression analyses, model selection, and statistical adjustment. After controlling for a multitude of variables that influence physical activity, we investigated whether distinct accelerometry profiles accompany pain in different locations of the body; and we identified the intensity intervals that best characterized these profiles. RESULTS: Unique accelerometry profiles were observed for pain in different body regions, logically clustering together based on proximity. Based on this, the following novel intervals (counts/minute) were identified and defined: Performance Sedentary (PSE) = 1–100, Performance Light 1 (PL1) = 101–350, Performance Light 2 (PL2) = 351–800, Performance Light 3 (PL3) = 801–2500, and Performance Moderate/Vigorous (PMV) = 2501–30000. The refinement of accelerometry signals into these new intervals, including 3 distinct ranges that fit inside the established light activity range, best captures alterations in real-life physical performance as a result of regional pain. DISCUSSION AND CONCLUSIONS: These new accelerometry intervals provide a model for objective measurement of real-life physical performance in people with pain and musculoskeletal disorders, with many potential uses. They may be used to better evaluate the relationship between pain and daily physical function, monitor musculoskeletal disease progression, gauge disease severity, inform exercise prescription, and quantify the functional impact of treatments. Based on these findings, we recommend that future studies of pain and musculoskeletal disorders analyze accelerometry output based on these new “physical performance” intervals. Public Library of Science 2017-02-24 /pmc/articles/PMC5325560/ /pubmed/28235039 http://dx.doi.org/10.1371/journal.pone.0172804 Text en © 2017 Smuck et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Smuck, Matthew
Tomkins-Lane, Christy
Ith, Ma Agnes
Jarosz, Renata
Kao, Ming-Chih Jeffrey
Physical performance analysis: A new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations
title Physical performance analysis: A new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations
title_full Physical performance analysis: A new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations
title_fullStr Physical performance analysis: A new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations
title_full_unstemmed Physical performance analysis: A new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations
title_short Physical performance analysis: A new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations
title_sort physical performance analysis: a new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5325560/
https://www.ncbi.nlm.nih.gov/pubmed/28235039
http://dx.doi.org/10.1371/journal.pone.0172804
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