Department of Epidemiology and Biostatistics, University of South Carolina, USA.
Department of Biostatistics, Harvard University T. H. Chan School of Public Health, Boston, MA, USA.
Ann Epidemiol. 2024 Nov;99:24-31. doi: 10.1016/j.annepidem.2024.10.001. Epub 2024 Oct 3.
Cardiovascular disease (CVD) is one of the leading causes of death worldwide. Physical activity (PA) has previously been shown to be a prominent risk factor for CVD mortality. Traditionally, measurements of PA have been self-reported and based on various summary metrics. However, recent advances in wearable technology provide continuously monitored and objectively measured physical activity data. This facilitates a more comprehensive interpretation of the implications of PA in the context of CVD mortality by considering its daily patterns and compositions.
This study utilized accelerometer data from the 2003-2006 National Health and Nutrition Examination Survey (NHANES) on 2816 older adults aged 50-85 and mortality data from the National Death Index (NDI) in December 2019. A novel partially functional distributional analysis method was used to quantify and understand the association between daily distributional patterns of physical activity and cardiovascular mortality risk through a multivariable functional Cox model.
A higher mean intensity of daily PA during the day was associated with a reduced hazard of CVD mortality after adjusting for other higher order distributional summaries of PA and age, gender, race, body mass index (BMI), smoking and coronary heart disease (CHD). A higher daily variability of PA during afternoon was associated with a reduced hazard of CVD mortality, after adjusting for the other predictors, particularly on weekdays. The subjects with a lower variability of PA, despite having same mean PA throughout the day, could have a lower reserve of PA and hence could be at increased risk for CVD mortality.
Our results demonstrate that not only the mean intensity of daily PA during daytime, but also the variability of PA during afternoon could be an important protective factor against the risk of CVD-mortality. Considering circadian rhythm of PA as well as its daily compositions can be useful for designing time-of-day and intensity-specific PA interventions to protect against the risk of CVD mortality.
心血管疾病（CVD）是全球主要死因之一。身体活动（PA）先前被证明是 CVD 死亡率的主要危险因素。传统上，PA 的测量是基于自我报告和各种综合指标。然而，可穿戴技术的最新进展提供了持续监测和客观测量的身体活动数据。这使得通过考虑 PA 的日常模式和组成，更全面地解释其在 CVD 死亡率方面的意义成为可能。
本研究利用了 2003-2006 年国家健康与营养调查（NHANES）中 2816 名年龄在 50-85 岁的成年人的加速度计数据，以及 2019 年 12 月国家死亡指数（NDI）的死亡率数据。采用一种新的部分功能分布分析方法，通过多变量功能 Cox 模型，量化和理解 PA 日常分布模式与心血管死亡率风险之间的关联。
在调整其他更高阶的 PA 分布总结和年龄、性别、种族、体重指数（BMI）、吸烟和冠心病（CHD）等因素后，白天 PA 平均强度较高与 CVD 死亡率风险降低相关。下午 PA 日常变异性较高与 CVD 死亡率风险降低相关，在调整其他预测因素后，尤其是在工作日。尽管全天 PA 的平均值相同，但 PA 变异性较低的受试者可能 PA 储备较低，因此 CVD 死亡率风险增加。
我们的结果表明，不仅白天 PA 的平均强度，而且下午 PA 的变异性也可能是降低 CVD 死亡率风险的重要保护因素。考虑 PA 的昼夜节律及其日常组成，对于设计针对特定时间和强度的 PA 干预措施以预防 CVD 死亡率风险可能是有用的。
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