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Compositional data analysis of 24-hour movement behaviors and mental health in workers
This cross-sectional study investigated the relationship between 24-hour movement behaviors and mental health among Japanese workers, accounting for the co-dependence of time spent in different behaviors during a single day. This research is part of a prospective cohort study called the Meiji Yasuda...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648171/ https://www.ncbi.nlm.nih.gov/pubmed/33204604 http://dx.doi.org/10.1016/j.pmedr.2020.101213 |
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author | Kitano, Naruki Kai, Yuko Jindo, Takashi Tsunoda, Kenji Arao, Takashi |
author_facet | Kitano, Naruki Kai, Yuko Jindo, Takashi Tsunoda, Kenji Arao, Takashi |
author_sort | Kitano, Naruki |
collection | PubMed |
description | This cross-sectional study investigated the relationship between 24-hour movement behaviors and mental health among Japanese workers, accounting for the co-dependence of time spent in different behaviors during a single day. This research is part of a prospective cohort study called the Meiji Yasuda LifeStyle study. Participants were 1095 workers in Tokyo, Japan, who underwent annual health check-ups between 2017 and 2018. Time use during workdays and non-workdays was separately evaluated. Behaviors included sleep (self-reported duration), sedentary behavior (SB), light-intensity physical activity (LPA), and moderate- to vigorous-intensity physical activity (assessed with a tri-axial accelerometer). We used the six-item Kessler Psychological Distress scale to evaluate psychological distress and the Utrecht Work Engagement Scale to assess work engagement as indicators for negative and positive mental health, respectively. We performed compositional logistic regression and compositional isotemporal substitution to examine associations between 24-hour movement behaviors and mental health. After controlling for potential confounders, time spent in workdays was significantly associated with higher psychological distress and lower work engagement (p < 0.05), respectively. Time spent sleeping was positively correlated with both mental health indicators, whereas time spent in SB or LPA was negatively correlated (p < 0.05). During workdays, higher psychological distress and lower work engagement were predicted to be 11.4–26.6% lower when 60 min/day of time spent sleeping were reallocated to SB or LPA. Reallocating time spent on SB or LPA to sleep during workdays may minimize psychological distress and optimize work engagement. Thus, proper time management focused on encouraging sleep may help improve workers’ mental health. |
format | Online Article Text |
id | pubmed-7648171 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-76481712020-11-16 Compositional data analysis of 24-hour movement behaviors and mental health in workers Kitano, Naruki Kai, Yuko Jindo, Takashi Tsunoda, Kenji Arao, Takashi Prev Med Rep Regular Article This cross-sectional study investigated the relationship between 24-hour movement behaviors and mental health among Japanese workers, accounting for the co-dependence of time spent in different behaviors during a single day. This research is part of a prospective cohort study called the Meiji Yasuda LifeStyle study. Participants were 1095 workers in Tokyo, Japan, who underwent annual health check-ups between 2017 and 2018. Time use during workdays and non-workdays was separately evaluated. Behaviors included sleep (self-reported duration), sedentary behavior (SB), light-intensity physical activity (LPA), and moderate- to vigorous-intensity physical activity (assessed with a tri-axial accelerometer). We used the six-item Kessler Psychological Distress scale to evaluate psychological distress and the Utrecht Work Engagement Scale to assess work engagement as indicators for negative and positive mental health, respectively. We performed compositional logistic regression and compositional isotemporal substitution to examine associations between 24-hour movement behaviors and mental health. After controlling for potential confounders, time spent in workdays was significantly associated with higher psychological distress and lower work engagement (p < 0.05), respectively. Time spent sleeping was positively correlated with both mental health indicators, whereas time spent in SB or LPA was negatively correlated (p < 0.05). During workdays, higher psychological distress and lower work engagement were predicted to be 11.4–26.6% lower when 60 min/day of time spent sleeping were reallocated to SB or LPA. Reallocating time spent on SB or LPA to sleep during workdays may minimize psychological distress and optimize work engagement. Thus, proper time management focused on encouraging sleep may help improve workers’ mental health. 2020-09-29 /pmc/articles/PMC7648171/ /pubmed/33204604 http://dx.doi.org/10.1016/j.pmedr.2020.101213 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Regular Article Kitano, Naruki Kai, Yuko Jindo, Takashi Tsunoda, Kenji Arao, Takashi Compositional data analysis of 24-hour movement behaviors and mental health in workers |
title | Compositional data analysis of 24-hour movement behaviors and mental health in workers |
title_full | Compositional data analysis of 24-hour movement behaviors and mental health in workers |
title_fullStr | Compositional data analysis of 24-hour movement behaviors and mental health in workers |
title_full_unstemmed | Compositional data analysis of 24-hour movement behaviors and mental health in workers |
title_short | Compositional data analysis of 24-hour movement behaviors and mental health in workers |
title_sort | compositional data analysis of 24-hour movement behaviors and mental health in workers |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648171/ https://www.ncbi.nlm.nih.gov/pubmed/33204604 http://dx.doi.org/10.1016/j.pmedr.2020.101213 |
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