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Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance

the benefits of physical activity (PA) and sleep for health, accurate and objective population-based surveillance is important. Monitor-based surveillance has potential, but the main challenge is the need for replicable outcomes from different monitors. This study investigated the agreement of movem...

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Autores principales: Migueles, Jairo H., Molina-Garcia, Pablo, Torres-Lopez, Lucia V., Cadenas-Sanchez, Cristina, Rowlands, Alex V., Ebner-Priemer, Ulrich W., Koch, Elena D., Reif, Andreas, Ortega, Francisco B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8975935/
https://www.ncbi.nlm.nih.gov/pubmed/35365696
http://dx.doi.org/10.1038/s41598-022-09469-2
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author Migueles, Jairo H.
Molina-Garcia, Pablo
Torres-Lopez, Lucia V.
Cadenas-Sanchez, Cristina
Rowlands, Alex V.
Ebner-Priemer, Ulrich W.
Koch, Elena D.
Reif, Andreas
Ortega, Francisco B.
author_facet Migueles, Jairo H.
Molina-Garcia, Pablo
Torres-Lopez, Lucia V.
Cadenas-Sanchez, Cristina
Rowlands, Alex V.
Ebner-Priemer, Ulrich W.
Koch, Elena D.
Reif, Andreas
Ortega, Francisco B.
author_sort Migueles, Jairo H.
collection PubMed
description the benefits of physical activity (PA) and sleep for health, accurate and objective population-based surveillance is important. Monitor-based surveillance has potential, but the main challenge is the need for replicable outcomes from different monitors. This study investigated the agreement of movement behavior outcomes assessed with four research-grade activity monitors (i.e., Movisens Move4, ActiGraph GT3X+, GENEActiv, and Axivity AX3) in adults. Twenty-three participants wore four monitors on the non-dominant wrist simultaneously for seven days. Open-source software (GGIR) was used to estimate the daily time in sedentary, light, moderate-to-vigorous PA (MVPA), and sleep (movement behaviors). The prevalence of participants meeting the PA and sleep recommendations were calculated from each monitor’s data. Outcomes were deemed equivalent between monitors if the absolute standardized difference and its 95% confidence intervals (CI(95%)) fell within ± 0.2 standard deviations (SD) of the mean of the differences. The participants were mostly men (n = 14, 61%) and aged 36 (SD = 14) years. Pairwise confusion matrices showed that 83–87% of the daily time was equally classified into the movement categories by the different pairs of monitors. The between-monitor difference in MVPA ranged from 1 (CI(95%): − 6, 7) to 8 (CI(95%): 1, 15) min/day. Most of the PA and sleep metrics could be considered equivalent. The prevalence of participants meeting the PA and the sleep guidelines was 100% consistent across monitors (22 and 5 participants out of the 23, respectively). Our findings indicate that the various research-grade activity monitors investigated show high inter-instrument reliability with respect to sedentary, PA and sleep-related estimates when their raw data are processed in an identical manner. These findings may have important implications for advancement towards monitor-based PA and sleep surveillance systems.
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spelling pubmed-89759352022-04-05 Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance Migueles, Jairo H. Molina-Garcia, Pablo Torres-Lopez, Lucia V. Cadenas-Sanchez, Cristina Rowlands, Alex V. Ebner-Priemer, Ulrich W. Koch, Elena D. Reif, Andreas Ortega, Francisco B. Sci Rep Article the benefits of physical activity (PA) and sleep for health, accurate and objective population-based surveillance is important. Monitor-based surveillance has potential, but the main challenge is the need for replicable outcomes from different monitors. This study investigated the agreement of movement behavior outcomes assessed with four research-grade activity monitors (i.e., Movisens Move4, ActiGraph GT3X+, GENEActiv, and Axivity AX3) in adults. Twenty-three participants wore four monitors on the non-dominant wrist simultaneously for seven days. Open-source software (GGIR) was used to estimate the daily time in sedentary, light, moderate-to-vigorous PA (MVPA), and sleep (movement behaviors). The prevalence of participants meeting the PA and sleep recommendations were calculated from each monitor’s data. Outcomes were deemed equivalent between monitors if the absolute standardized difference and its 95% confidence intervals (CI(95%)) fell within ± 0.2 standard deviations (SD) of the mean of the differences. The participants were mostly men (n = 14, 61%) and aged 36 (SD = 14) years. Pairwise confusion matrices showed that 83–87% of the daily time was equally classified into the movement categories by the different pairs of monitors. The between-monitor difference in MVPA ranged from 1 (CI(95%): − 6, 7) to 8 (CI(95%): 1, 15) min/day. Most of the PA and sleep metrics could be considered equivalent. The prevalence of participants meeting the PA and the sleep guidelines was 100% consistent across monitors (22 and 5 participants out of the 23, respectively). Our findings indicate that the various research-grade activity monitors investigated show high inter-instrument reliability with respect to sedentary, PA and sleep-related estimates when their raw data are processed in an identical manner. These findings may have important implications for advancement towards monitor-based PA and sleep surveillance systems. Nature Publishing Group UK 2022-04-01 /pmc/articles/PMC8975935/ /pubmed/35365696 http://dx.doi.org/10.1038/s41598-022-09469-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Migueles, Jairo H.
Molina-Garcia, Pablo
Torres-Lopez, Lucia V.
Cadenas-Sanchez, Cristina
Rowlands, Alex V.
Ebner-Priemer, Ulrich W.
Koch, Elena D.
Reif, Andreas
Ortega, Francisco B.
Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance
title Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance
title_full Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance
title_fullStr Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance
title_full_unstemmed Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance
title_short Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance
title_sort equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8975935/
https://www.ncbi.nlm.nih.gov/pubmed/35365696
http://dx.doi.org/10.1038/s41598-022-09469-2
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