Identifying typologies of diurnal patterns in desk-based workers’ sedentary time
Open Access
- 9 April 2021
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 16 (4), e0248304
- https://doi.org/10.1371/journal.pone.0248304
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.Funding Information
- Meiji Yasuda Life Foundation of Health and Welfare
- Japan Society for the Promotion of Science (18K10986, 20H04113)
- MEXT-Supported Program for the Strategic Research Foundation at Private Universities (S1511017)
This publication has 27 references indexed in Scilit:
- The contribution of office work to sedentary behaviour associated riskBMC Public Health, 2013
- Prolonged sedentary time and physical activity in workplace and non-work contexts: a cross-sectional study of office, customer service and call centre employeesInternational Journal of Behavioral Nutrition and Physical Activity, 2012
- Too much sitting – A health hazardDiabetes Research and Clinical Practice, 2012
- Measurement of Adults' Sedentary Time in Population-Based StudiesAmerican Journal of Preventive Medicine, 2011
- Real-time estimation of daily physical activity intensity by a triaxial accelerometer and a gravity-removal classification algorithmBritish Journal of Nutrition, 2011
- Sedentary time and cardio-metabolic biomarkers in US adults: NHANES 2003–06European Heart Journal, 2011
- Too Much SittingExercise and Sport Sciences Reviews, 2010
- Classifying household and locomotive activities using a triaxial accelerometerGait & Posture, 2010
- Daily physical activities in chronic lower back pain patients assessed with accelerometryEuropean Journal of Pain Supplements, 2009
- Theory and Method in Health Audience SegmentationJournal of Health Communication, 1996