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Identifying typologies of diurnal patterns in desk-based workers’ sedentary time

The purpose of this study was to identify typologies of diurnal sedentary behavior patterns and sociodemographic characteristics of desk-based workers. The sedentary time of 229 desk-based workers was measured using accelerometer devices. The within individual diurnal variations in sedentary time wa...

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Autores principales: Kurosawa, Sayaka, Shibata, Ai, Ishii, Kaori, Koohsari, Mohammad Javad, Oka, Koichiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034739/
https://www.ncbi.nlm.nih.gov/pubmed/33836010
http://dx.doi.org/10.1371/journal.pone.0248304
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author Kurosawa, Sayaka
Shibata, Ai
Ishii, Kaori
Koohsari, Mohammad Javad
Oka, Koichiro
author_facet Kurosawa, Sayaka
Shibata, Ai
Ishii, Kaori
Koohsari, Mohammad Javad
Oka, Koichiro
author_sort Kurosawa, Sayaka
collection PubMed
description The purpose of this study was to identify typologies of diurnal sedentary behavior patterns and sociodemographic characteristics of desk-based workers. The sedentary time of 229 desk-based workers was measured using accelerometer devices. The within individual diurnal variations in sedentary time was calculated for both workdays and non-workdays. Diurnal variations in sedentary time during each time period (morning, afternoon, and evening) was calculated as the percentage of sedentary time during each time period divided by the percentage of the total sedentary time. A hierarchical cluster analysis (Ward’s method) was used to identify the optimal number of clusters. To refine the initial clusters, a non-hierarchical cluster analysis (k-means method) was performed. Four clusters were identified: stable sedentary cluster (46.7%), off-morning break cluster (26.6%), off-afternoon break cluster (8.3%), and evening sedentary cluster (18.3%). The stable sedentary cluster had the lowest variations in sedentary time throughout the day and the highest amount of total sedentary time. Participants in the off-morning and off-afternoon break clusters had nearly the same sedentary patterns but took short-term breaks during non-workday mornings or afternoons. The evening sedentary cluster had a completely different pattern, with a longer sedentary time during the evening both on workdays and non-workdays. Sociodemographic attributes such as sex, household income, educational attainment, employment status, sleep duration, and residential area, differed significantly between groups. Initiatives to address desk-based workers’ sedentary behavior need to focus not only on the workplace but also on the appropriate timing for reducing excessive sedentary time in non-work contexts depending on the characteristics and diurnal patterns of target subgroups.
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spelling pubmed-80347392021-04-15 Identifying typologies of diurnal patterns in desk-based workers’ sedentary time Kurosawa, Sayaka Shibata, Ai Ishii, Kaori Koohsari, Mohammad Javad Oka, Koichiro PLoS One Research Article The purpose of this study was to identify typologies of diurnal sedentary behavior patterns and sociodemographic characteristics of desk-based workers. The sedentary time of 229 desk-based workers was measured using accelerometer devices. The within individual diurnal variations in sedentary time was calculated for both workdays and non-workdays. Diurnal variations in sedentary time during each time period (morning, afternoon, and evening) was calculated as the percentage of sedentary time during each time period divided by the percentage of the total sedentary time. A hierarchical cluster analysis (Ward’s method) was used to identify the optimal number of clusters. To refine the initial clusters, a non-hierarchical cluster analysis (k-means method) was performed. Four clusters were identified: stable sedentary cluster (46.7%), off-morning break cluster (26.6%), off-afternoon break cluster (8.3%), and evening sedentary cluster (18.3%). The stable sedentary cluster had the lowest variations in sedentary time throughout the day and the highest amount of total sedentary time. Participants in the off-morning and off-afternoon break clusters had nearly the same sedentary patterns but took short-term breaks during non-workday mornings or afternoons. The evening sedentary cluster had a completely different pattern, with a longer sedentary time during the evening both on workdays and non-workdays. Sociodemographic attributes such as sex, household income, educational attainment, employment status, sleep duration, and residential area, differed significantly between groups. Initiatives to address desk-based workers’ sedentary behavior need to focus not only on the workplace but also on the appropriate timing for reducing excessive sedentary time in non-work contexts depending on the characteristics and diurnal patterns of target subgroups. Public Library of Science 2021-04-09 /pmc/articles/PMC8034739/ /pubmed/33836010 http://dx.doi.org/10.1371/journal.pone.0248304 Text en © 2021 Kurosawa et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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
Kurosawa, Sayaka
Shibata, Ai
Ishii, Kaori
Koohsari, Mohammad Javad
Oka, Koichiro
Identifying typologies of diurnal patterns in desk-based workers’ sedentary time
title Identifying typologies of diurnal patterns in desk-based workers’ sedentary time
title_full Identifying typologies of diurnal patterns in desk-based workers’ sedentary time
title_fullStr Identifying typologies of diurnal patterns in desk-based workers’ sedentary time
title_full_unstemmed Identifying typologies of diurnal patterns in desk-based workers’ sedentary time
title_short Identifying typologies of diurnal patterns in desk-based workers’ sedentary time
title_sort identifying typologies of diurnal patterns in desk-based workers’ sedentary time
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034739/
https://www.ncbi.nlm.nih.gov/pubmed/33836010
http://dx.doi.org/10.1371/journal.pone.0248304
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