Graduate School of Sport Sciences, Waseda University, Tokorozawa, Saitama, Japan.
Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan.
PLoS One. 2021 Apr 9;16(4):e0248304. doi: 10.1371/journal.pone.0248304. eCollection 2021.
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.
本研究旨在确定基于办公桌的工作人员的日间久坐行为模式和社会人口特征的类型。使用加速度计设备测量了 229 名基于办公桌的工作人员的久坐时间。计算了工作日和非工作日的个体内日间久坐时间变化。在每个时间段（早晨、下午和晚上）内计算了久坐时间的日间变化，方法是将每个时间段的久坐时间百分比除以总久坐时间的百分比。使用层次聚类分析（Ward 法）确定最佳聚类数。为了细化初始聚类，进行了非层次聚类分析（k-均值法）。确定了四个聚类：稳定久坐聚类（46.7%）、上午休息后聚类（26.6%）、下午休息后聚类（8.3%）和傍晚久坐聚类（18.3%）。稳定久坐聚类在一天中久坐时间变化最小，总久坐时间最高。上午休息和下午休息后聚类的参与者具有几乎相同的久坐模式，但在非工作日的早晨或下午进行短暂休息。傍晚久坐聚类具有完全不同的模式，在工作日和非工作日的晚上久坐时间都更长。性别、家庭收入、教育程度、就业状况、睡眠时间和居住区域等社会人口特征在组间存在显著差异。解决基于办公桌的工作人员久坐行为的措施不仅需要关注工作场所，还需要根据目标亚组的特征和日间模式，在适当的时间减少非工作环境下的过度久坐时间。
