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Identifying typologies of diurnal patterns in desk-based workers' sedentary time
- Source :
- PLoS ONE, Vol 16, Iss 4, p e0248304 (2021), PLoS ONE
- Publication Year :
- 2021
- Publisher :
- Public Library of Science (PLoS), 2021.
-
Abstract
- 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.
- Subjects :
- Male
Physiology
Economics
Social Sciences
Electronics Engineering
Mathematical and Statistical Techniques
0302 clinical medicine
Sociology
Japan
Accelerometry
Medicine and Health Sciences
Psychology
Cluster Analysis
Public and Occupational Health
030212 general & internal medicine
Workplace
Morning
Sitting Position
Multidisciplinary
Statistics
Sedentary behavior
Middle Aged
Circadian Rhythm
Geography
Physical Sciences
Standing Position
Social Systems
Engineering and Technology
Educational Status
Medicine
Female
Research Article
Sleep duration
Employment
Adult
Evening
Science
Physical activity
Research and Analysis Methods
Education
03 medical and health sciences
Humans
Statistical Methods
Exercise
Educational Attainment
Desk
Sedentary time
Behavior
Analysis of Variance
Biology and Life Sciences
Physical Activity
030229 sport sciences
Cross-Sectional Studies
Labor Economics
Sedentary Behavior
Electronics
Accelerometers
Physiological Processes
Sleep
Mathematics
Demography
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 16
- Issue :
- 4
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....eb43472a93bbe1f607cfeca8552cb8ab