Zhang Yuankai, Wang Xuzhi, Pathiravasan Chathurangi H, Spartano Nicole L, Lin Honghuang, Borrelli Belinda, Benjamin Emelia J, McManus David D, Larson Martin G, Vasan Ramachandran S, Shah Ravi V, Lewis Gregory D, Liu Chunyu, Murabito Joanne M, Nayor Matthew
Department of Biostatistics, School of Public Health, Boston University, Boston, MA, United States.
Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States.
J Med Internet Res. 2024 Jun 13;26:e56676. doi: 10.2196/56676.
Resting heart rate (HR) and routine physical activity are associated with cardiorespiratory fitness levels. Commercial smartwatches permit remote HR monitoring and step count recording in real-world settings over long periods of time, but the relationship between smartwatch-measured HR and daily steps to cardiorespiratory fitness remains incompletely characterized in the community.
This study aimed to examine the association of nonactive HR and daily steps measured by a smartwatch with a multidimensional fitness assessment via cardiopulmonary exercise testing (CPET) among participants in the electronic Framingham Heart Study.
Electronic Framingham Heart Study participants were enrolled in a research examination (2016-2019) and provided with a study smartwatch that collected longitudinal HR and physical activity data for up to 3 years. At the same examination, the participants underwent CPET on a cycle ergometer. Multivariable linear models were used to test the association of CPET indices with nonactive HR and daily steps from the smartwatch.
We included 662 participants (mean age 53, SD 9 years; n=391, 59% women, n=599, 91% White; mean nonactive HR 73, SD 6 beats per minute) with a median of 1836 (IQR 889-3559) HR records and a median of 128 (IQR 65-227) watch-wearing days for each individual. In multivariable-adjusted models, lower nonactive HR and higher daily steps were associated with higher peak oxygen uptake (VO), % predicted peak VO, and VO at the ventilatory anaerobic threshold, with false discovery rate (FDR)-adjusted P values <.001 for all. Reductions of 2.4 beats per minute in nonactive HR, or increases of nearly 1000 daily steps, corresponded to a 1.3 mL/kg/min higher peak VO. In addition, ventilatory efficiency (V/VCO; FDR-adjusted P=.009), % predicted maximum HR (FDR-adjusted P<.001), and systolic blood pressure-to-workload slope (FDR-adjusted P=.01) were associated with nonactive HR but not associated with daily steps.
Our findings suggest that smartwatch-based assessments are associated with a broad array of cardiorespiratory fitness responses in the community, including measures of global fitness (peak VO), ventilatory efficiency, and blood pressure response to exercise. Metrics captured by wearable devices offer a valuable opportunity to use extensive data on health factors and behaviors to provide a window into individual cardiovascular fitness levels.
静息心率（HR）和日常身体活动与心肺适能水平相关。商用智能手表能够在现实环境中长时间进行远程心率监测和步数记录，但在社区中，智能手表测量的心率与日常步数和心肺适能之间的关系仍未完全明确。
本研究旨在探讨电子弗雷明汉心脏研究参与者中，智能手表测量的静息心率和日常步数与通过心肺运动试验（CPET）进行的多维适能评估之间的关联。
电子弗雷明汉心脏研究的参与者参加了一项研究检查（2016 - 2019年），并配备了一块研究用智能手表，该手表可收集长达3年的纵向心率和身体活动数据。在同一次检查中，参与者在自行车测力计上进行CPET。使用多变量线性模型来测试CPET指标与智能手表测量的静息心率和日常步数之间的关联。
我们纳入了662名参与者（平均年龄53岁，标准差9岁；n = 391名女性，占59%；n = 599名白人，占91%；平均静息心率73次/分钟，标准差6次/分钟），每位参与者的心率记录中位数为1836次（四分位间距889 - 3559次），佩戴手表天数中位数为128天（四分位间距65 - 227天）。在多变量调整模型中，较低的静息心率和较高的日常步数与较高的峰值摄氧量（VO）、预测峰值VO百分比以及通气无氧阈时的VO相关，所有这些的错误发现率（FDR）调整P值均<0.001。静息心率每降低2.4次/分钟，或日常步数增加近1000步，对应峰值VO升高1.3 mL/kg/min。此外，通气效率（V/VCO；FDR调整P = 0.009）、预测最大心率百分比（FDR调整P<0.001）以及收缩压与工作量斜率（FDR调整P = 0.01）与静息心率相关，但与日常步数无关。
我们的研究结果表明，基于智能手表的评估与社区中广泛的心肺适能反应相关，包括整体适能测量（峰值VO）、通气效率以及运动时的血压反应。可穿戴设备捕获的指标提供了一个宝贵的机会，利用关于健康因素和行为的大量数据，为了解个体心血管适能水平提供一个窗口。
