MEMOTEF Department, Sapienza University of Rome, Rome, Italy.
Stat Med. 2023 Feb 20;42(4):579-595. doi: 10.1002/sim.9633. Epub 2022 Dec 23.
Accelerometers are commonly used in human medical and public health research to measure physical movement, which is relevant in a wide range of studies, from physical activity and sleep behaviours studies, to identification of movement patterns in people affected by diseases of the locomotor system and prediction of risk of injury in high performance sports. The accelerometer output provides the intensity (activity count) and timing (timestamp) of the movement, which can be used to define bouts of activity (periods of sustained movement of a given intensity). In some contexts, it may be important to include both dimensions to obtain a broader and deeper understanding of the phenomenon under study. Such is the case of a large-scale epidemiological investigation on the daily and weekly physical activity behaviours of school-aged children enrolled in the UK Millennium Cohort Study, which has motivated the present article. I present a statistical approach to joint modelling of intensity and timing of activity bouts that takes advantage of the circular nature of the timing. The model, which accounts for the longitudinal structure of the observations, is remarkably simple to implement using standard statistical software.
加速度计常用于人类医学和公共卫生研究中,以测量身体活动,这在广泛的研究中具有相关性,从体育活动和睡眠行为研究,到识别运动系统疾病患者的运动模式以及预测高性能运动中的受伤风险。加速度计的输出提供了运动的强度(活动计数)和时间(时间戳),可用于定义活动的爆发(给定强度的持续运动期)。在某些情况下,为了更广泛和深入地了解研究中的现象,包含这两个维度可能很重要。英国千禧年队列研究对学龄儿童的日常和每周身体活动行为进行的大规模流行病学调查就是这种情况,这促使本文进行了研究。我提出了一种联合建模强度和活动爆发时间的统计方法,该方法利用了时间的循环性质。该模型考虑了观察的纵向结构,使用标准统计软件实现起来非常简单。