Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21218, USA.
Sensors (Basel). 2021 Feb 23;21(4):1545. doi: 10.3390/s21041545.
The ability of individuals to engage in physical activity is a critical component of overall health and quality of life. However, there is a natural decline in physical activity associated with the aging process. Establishing normative trends of physical activity in aging populations is essential to developing public health guidelines and informing clinical perspectives regarding individuals' levels of physical activity. Beyond overall quantity of physical activity, patterns regarding the timing of activity provide additional insights into latent health status. Wearable accelerometers, paired with statistical methods from functional data analysis, provide the means to estimate diurnal patterns in physical activity. To date, these methods have been only applied to study aging trends in populations based in the United States. Here, we apply curve registration and functional regression to 24 h activity profiles for 88,793 men (N = 39,255) and women (N = 49,538) ages 42-78 from the UK Biobank accelerometer study to understand how physical activity patterns vary across ages and by gender. Our analysis finds that daily patterns in both the volume of physical activity and probability of being active change with age, and that there are marked gender differences in these trends. This work represents the largest-ever population analyzed using tools of this kind, and suggest that aging trends in physical activity are reproducible in different populations across countries.
个体参与身体活动的能力是整体健康和生活质量的关键组成部分。然而,随着年龄的增长,身体活动会自然减少。建立老龄化人口身体活动的规范趋势对于制定公共卫生指南和告知临床医生关于个体身体活动水平的观点至关重要。除了身体活动的总体数量外,活动时间的模式还提供了对潜在健康状况的更多了解。可穿戴式加速度计与功能数据分析中的统计方法相结合,为估计身体活动的昼夜模式提供了手段。迄今为止,这些方法仅应用于研究美国人群的老龄化趋势。在这里,我们将曲线配准和功能回归应用于来自英国生物银行加速度计研究的 88793 名男性(N=39255)和女性(N=49538)的 24 小时活动记录,以了解身体活动模式如何随年龄和性别而变化。我们的分析发现,身体活动量和活动概率的日常模式随年龄而变化,而且这些趋势在性别上存在明显差异。这项工作代表了迄今为止使用这种工具分析的最大人群,表明身体活动的老龄化趋势在不同国家的不同人群中是可复制的。