Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3216, Australia.
Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC 3053, Australia.
J Sport Health Sci. 2022 Mar;11(2):234-243. doi: 10.1016/j.jshs.2021.03.004. Epub 2021 Mar 15.
The study aimed to describe youth time-use compositions, focusing on time spent in shorter and longer bouts of sedentary behavior and physical activity (PA), and to examine associations of these time-use compositions with cardiometabolic biomarkers.
Accelerometer and cardiometabolic biomarker data from 2 Australian studies involving youths 7-13 years old were pooled (complete cases with accelerometry and adiposity marker data, n = 782). A 9-component time-use composition was formed using compositional data analysis: time in shorter and longer bouts of sedentary behavior; time in shorter and longer bouts of light-, moderate-, or vigorous-intensity PA; and "other time" (i.e., non-wear/sleep). Shorter and longer bouts of sedentary time were defined as <5 min and ≥5 min, respectively. Shorter bouts of light-, moderate-, and vigorous-intensity PA were defined as <1 min; longer bouts were defined as ≥1 min. Regression models examined associations between overall time-use composition and cardiometabolic biomarkers. Then, associations were derived between ratios of longer activity patterns relative to shorter activity patterns, and of each intensity level relative to the other intensity levels and "other time", and cardiometabolic biomarkers.
Confounder-adjusted models showed that the overall time-use composition was associated with adiposity, blood pressure, lipids, and the summary score. Specifically, more time in longer bouts of light-intensity PA relative to shorter bouts of light-intensity PA was significantly associated with greater body mass index z-score (zBMI) (β = 1.79; SE = 0.68) and waist circumference (β = 18.35, SE = 4.78). When each activity intensity was considered relative to all higher intensities and "other time", more time in light- and vigorous-intensity PA, and less time in sedentary behavior and moderate-intensity PA, were associated with lower waist circumference.
Accumulating PA, particularly light-intensity PA, in frequent short bursts may be more beneficial for limiting adiposity compared to accumulating the same amount of PA at these intensities in longer bouts.
本研究旨在描述青少年的时间利用情况,重点关注短时间和长时间久坐行为和身体活动(PA)的时间分配,并探讨这些时间利用情况与心血管代谢生物标志物之间的关联。
对 2 项涉及 7-13 岁青少年的澳大利亚研究中的加速度计和心血管代谢生物标志物数据进行了汇总(具有加速度计和肥胖标志物数据的完整案例,n=782)。使用成分数据分析形成了 9 个成分的时间利用情况组成部分:短时间和长时间久坐时间;短时间和长时间轻、中、高强度 PA 时间;以及“其他时间”(即非穿戴/睡眠时间)。久坐时间的短时间和长时间分别定义为<5 分钟和≥5 分钟。短时间的轻、中、高强度 PA 定义为<1 分钟;长时间的定义为≥1 分钟。回归模型检验了整体时间利用情况组成与心血管代谢生物标志物之间的关联。然后,得出了较长活动模式与较短活动模式、每个强度水平与其他强度水平和“其他时间”的比值与心血管代谢生物标志物之间的关联。
在调整了混杂因素的模型中,整体时间利用情况组成与肥胖、血压、血脂和综合评分有关。具体而言,与短时间的轻强度 PA 相比,长时间的轻强度 PA 时间与更高的体重指数 z 分数(zBMI)(β=1.79;SE=0.68)和腰围(β=18.35,SE=4.78)显著相关。当考虑每个活动强度相对于所有更高强度和“其他时间”时,更多的时间进行轻强度和剧烈强度 PA,以及更少的时间进行久坐行为和中强度 PA,与较低的腰围有关。
与在较长时间内以这些强度积累相同量的 PA 相比,频繁进行短时间的 PA(特别是低强度 PA)可能更有利于限制肥胖。