Association of domain‐specific physical activity and sedentary behavior with cardiometabolic health among office workers

医学 置信区间 上班族 久坐行为 体力活动 屏幕时间 老年学 环境卫生 物理疗法 人口学 内科学 运营管理 社会学 经济
作者
Naruki Kitano,Yuko Kai,Takashi Jindo,Yuya Fujii,Kenji Tsunoda,Takashi Arao
出处
期刊:Scandinavian Journal of Medicine & Science in Sports [Wiley]
卷期号:32 (8): 1224-1235 被引量:16
标识
DOI:10.1111/sms.14165
摘要

Previous studies have reported opposite effects of occupational or non-occupational physical activity (PA) and sedentary behavior (SB) on health outcomes. However, no study has investigated the relationship between domain-specific movement behaviors and cardiometabolic health (CMH) among office workers, considering the compositional nature of time-use data. We investigated the associations of accelerometer-measured PA and SB for each domain (working time, non-working time on workday, and non-workday) with CMH indicators among office workers, using compositional data analysis.This cross-sectional study included 1258 Japanese office workers. The time spent on SB, light-intensity PA (LPA), and moderate- to vigorous-intensity PA (MVPA) were assessed using an accelerometer. CMH indicators were retrieved from the annual health check-up data.Compositional multiple linear regression indicated that PA and SB during non-working time on workdays, but not working time or non-workdays, were significantly associated with CMH. In particular, during non-working time, time reallocations from SB to LPA and from SB to MVPA were associated with favorable changes in cardiometabolic risk score and lipid metabolism, respectively. Paradoxically, a greater proportion of LPA during non-working time was associated with favorable diastolic blood pressure (β = 1.61; 95% confidence interval [CI] = 0.02, 3.19), whereas occupational LPA was detrimental (β = -2.48; 95% CI = -4.87, -0.09).Our results suggested that reducing SB and increasing PA during non-working time on workdays may be effective for managing CMH among office workers. Future longitudinal studies using compositional data analysis are required to confirm our results.
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