Comparing Cadence vs. Machine Learning Based Physical Activity Intensity Classifications: Variations in the Associations of Physical Activity With Mortality

IF 3.5 2区 医学 Q1 SPORT SCIENCES Scandinavian Journal of Medicine & Science in Sports Pub Date : 2024-09-10 DOI:10.1111/sms.14719
Le Wei, Matthew N. Ahmadi, Raaj Kishore Biswas, Stewart G. Trost, Emmanuel Stamatakis
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Abstract

Step cadence‐based and machine‐learning (ML) methods have been used to classify physical activity (PA) intensity in health‐related research. This study examined the association of intensity‐specific PA duration with all‐cause (ACM) and CVD mortality using the cadence‐based and ML methods in 68 561 UK Biobank participants wearing wrist‐worn accelerometers. The two‐stage‐ML method categorized activity type and then intensity. The one‐level‐cadence‐method (1LC) derived intensity‐specific duration using all detected steps (including standing utilitarian steps) and cadence thresholds of ≥100 steps/min (moderate intensity) and ≥130 steps/min (vigorous intensity). The two‐level‐cadence‐method (2LC) detected ambulatory steps (i.e., walking and running) and then applied the same cadence thresholds. The 2LC exhibited the most pronounced association at the lower end of duration spectrum. For example, the 2LC showed the smallest minimum moderate‐to‐vigorous‐PA (MVPA) duration (amount associated with 50% of optimal risk reduction) with similar corresponding ACM hazard ratio (HR) to other methods (2LC: 2.8 min/day [95% CI: 2.6, 2.8], HR: 0.83 [95% CI: 0.78, 0.88]; 1LC, 11.1[10.8, 11.4], 0.80 [0.76, 0.85]; ML, 14.9 [14.6, 15.2], 0.82 [0.76, 0.87]). The ML elicited the greatest mortality risk reduction. For example, the medians and corresponding HR in VPA‐ACM association: 2LC, 2.0 min/day [95% CI: 2.0, 2.0], HR, 0.69 [95% CI: 0.61, 0.79]; 1LC, 6.9 [6.9, 7.0], 0.68 [0.60, 0.77]; ML, 3.2 [3.2, 3.2], 0.53 [0.44, 0.64]. After standardizing durations, the ML exhibited the most pronounced associations. For example, the standardized minimum durations in MPA‐CVD mortality association were: 2LC, −0.77; 1LC, −0.85; ML, −0.94; with corresponding HR of 0.82 [0.72, 0.92], 0.79 [0.69, 0.90], and 0.77 [0.69, 0.85], respectively. The 2LC exhibited the most pronounced association with all‐cause and CVD mortality at the lower end of the duration spectrum. The ML method provided the most pronounced association with all‐cause and CVD mortality, thus might be appropriate for estimating health benefits of moderate and vigorous intensity PA in observational studies.
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比较步调与基于机器学习的体育锻炼强度分类:体育锻炼与死亡率关系的变化
在与健康相关的研究中,基于步频的方法和机器学习(ML)方法已被用于对身体活动(PA)强度进行分类。本研究采用基于步频的方法和机器学习方法,对佩戴腕戴式加速度计的 68 561 名英国生物库参与者进行了研究,探讨了特定强度的体力活动持续时间与全因(ACM)死亡率和心血管疾病死亡率之间的关系。两阶段 ML 法先对活动类型进行分类,然后再对活动强度进行分类。单级步速法(1LC)使用所有检测到的步数(包括站立的功利性步数)和≥100步/分钟(中等强度)和≥130步/分钟(剧烈强度)的步速阈值,得出特定强度的持续时间。两级步速法(2LC)检测移动步数(即步行和跑步),然后应用相同的步速阈值。2LC 在持续时间频谱的低端表现出最明显的关联性。例如,2LC 显示出最小的中度到剧烈运动(MVPA)持续时间(与 50% 最佳风险降低相关的量),其相应的 ACM 危险比(HR)与其他方法相似(2LC:2.8分钟/天 [95% CI:2.6,2.8],HR:0.83 [95% CI:0.78,0.88];1LC,11.1 [10.8,11.4],0.80 [0.76,0.85];ML,14.9 [14.6,15.2],0.82 [0.76,0.87])。ML 降低的死亡率风险最大。例如,VPA-ACM 关联的中位数和相应 HR:2LC,2.0 分钟/天 [95% CI:2.0,2.0],HR,0.69 [95% CI:0.61,0.79];1LC,6.9 [6.9,7.0],0.68 [0.60,0.77];ML,3.2 [3.2,3.2],0.53 [0.44,0.64]。在标准化持续时间后,ML 表现出最明显的关联。例如,MPA-心血管疾病死亡率关联的标准化最小持续时间为2LC,-0.77;1LC,-0.85;ML,-0.94;相应的 HR 分别为 0.82 [0.72,0.92]、0.79 [0.69,0.90] 和 0.77 [0.69,0.85]。在持续时间频谱的低端,2LC 与全因死亡率和心血管疾病死亡率的关系最为明显。ML 方法与全因死亡率和心血管疾病死亡率的关系最为明显,因此可能适合在观察性研究中估算中等强度和剧烈强度体育锻炼对健康的益处。
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来源期刊
CiteScore
7.90
自引率
4.90%
发文量
162
审稿时长
3 months
期刊介绍: The Scandinavian Journal of Medicine & Science in Sports is a multidisciplinary journal published 12 times per year under the auspices of the Scandinavian Foundation of Medicine and Science in Sports. It aims to publish high quality and impactful articles in the fields of orthopaedics, rehabilitation and sports medicine, exercise physiology and biochemistry, biomechanics and motor control, health and disease relating to sport, exercise and physical activity, as well as on the social and behavioural aspects of sport and exercise.
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