School of Nursing, University of Mississippi Medical Center, Jackson, Mississippi, USA.
Department of Population Health Science, the John D. Bower School of Population Health, University of Mississippi Medical Center, Jackson, Mississippi, USA.
J Spec Pediatr Nurs. 2022 Apr;27(2):e12364. doi: 10.1111/jspn.12364. Epub 2021 Dec 8.
The objectives of this paper are (1) to examine patterns of physical activity (PA) and sedentary behavior; (2) to describe development of a method to quantify movement dispersion; and (3) to determine the relationship between variables of movement (i.e., volume, intensity, and dispersion), volume of sedentary behavior, and estimated cardiorespiratory capacity in school-aged children.
A secondary analysis of an existing data set with raw accelerometer data identified PA patterns of movement dispersion in school-aged children. Bar graphs visually depicted each participant's daily vector magnitude counts. The research team developed a dispersion variable-movement dispersion-and formula to provide a new quantification of daily PA patterns. Total movement dispersion represents both intensity and distribution of movement, whereas pure movement dispersion refers to the distribution of movement during the wear time, independent of intensity. Kendall's tau examined the relationship between several variables: body mass index percentile, average minutes of sedentary behavior, average minutes of light PA, average minutes of moderate-vigorous PA (MVPA), derived VO max, total movement dispersion, and pure movement dispersion.
Three participants' activity graphs were presented as examples: (1) active, (2) inactive, and (3) mixed. The more active participant had the highest values for pure and total movement dispersion. The inactive participant had much lower pure and total movement dispersion values compared to the active participant. The mixed participant had high average minutes of MVPA yet lower pure and total movement dispersion values. Total movement dispersion had a significant correlation with average minutes of light PA (r = .406, p = .016) and average minutes of MVPA (r = .686, p < .001). Pure movement dispersion was significantly correlated with average minutes of light PA (r = .448, p = .008) and average minutes of MVPA (r = .599, p < .001). Average minutes of sedentary behavior (SB) were not significantly correlated with total (r = .041, p = .806) or pure movement dispersion (r = .165, p = .326).
Movement dispersion may provide another tool to advance knowledge of PA, potentially leading to improved health outcomes. Raw accelerometer data, such as that gathered at the elementary school in this study, offer opportunities to identify school-aged children at risk for obesity, SB, and lack of PA.
本文的目的是:(1) 研究体力活动(PA)和久坐行为的模式;(2) 描述一种量化运动分散的方法;(3) 确定运动变量(即量、强度和分散度)、久坐行为量和学龄儿童估计心肺能力之间的关系。
对现有数据集的二次分析,确定了学龄儿童运动分散的 PA 模式。条形图直观地显示了每个参与者的日常向量幅度计数。研究小组开发了一个分散变量——运动分散度,并制定了一个公式,为日常 PA 模式提供了一种新的量化方法。总运动分散度既代表运动的强度,也代表运动的分布,而纯运动分散度则指的是佩戴时间内运动的分布,与强度无关。肯德尔的 tau 检验了几个变量之间的关系:体重指数百分位数、平均久坐时间、平均低强度 PA 时间、平均中高强度 PA (MVPA)时间、衍生 VO max、总运动分散度和纯运动分散度。
作为示例,展示了三个参与者的活动图:(1)活跃,(2)不活跃,(3)混合。更活跃的参与者具有最高的纯运动和总运动分散度值。不活跃的参与者的纯运动和总运动分散度值比活跃的参与者低得多。混合参与者的中高强度 PA 时间较高,但纯运动和总运动分散度值较低。总运动分散度与低强度 PA 时间的平均分钟(r=0.406,p=0.016)和中高强度 PA 时间的平均分钟(r=0.686,p<0.001)显著相关。纯运动分散度与低强度 PA 时间的平均分钟(r=0.448,p=0.008)和中高强度 PA 时间的平均分钟(r=0.599,p<0.001)显著相关。平均久坐时间与总运动分散度(r=0.041,p=0.806)和纯运动分散度(r=0.165,p=0.326)均无显著相关性。
运动分散度可能为 PA 知识的发展提供另一种工具,从而可能带来更好的健康结果。像本研究中在小学收集的原始加速度计数据为识别肥胖、久坐行为和缺乏 PA 的学龄儿童提供了机会。