Department of Medicine, Stanford University, Stanford, California2Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California3Verily Life Sciences LLC, South San Francisco, California.
Department of Medicine, Stanford University, Stanford, California2Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California.
JAMA Cardiol. 2017 Jan 1;2(1):67-76. doi: 10.1001/jamacardio.2016.4395.
Studies have established the importance of physical activity and fitness, yet limited data exist on the associations between objective, real-world physical activity patterns, fitness, sleep, and cardiovascular health.
To assess the feasibility of obtaining measures of physical activity, fitness, and sleep from smartphones and to gain insights into activity patterns associated with life satisfaction and self-reported disease.
DESIGN, SETTING, AND PARTICIPANTS: The MyHeart Counts smartphone app was made available in March 2015, and prospective participants downloaded the free app between March and October 2015. In this smartphone-based study of cardiovascular health, participants recorded physical activity, filled out health questionnaires, and completed a 6-minute walk test. The app was available to download within the United States.
The feasibility of consent and data collection entirely on a smartphone, the use of machine learning to cluster participants, and the associations between activity patterns, life satisfaction, and self-reported disease.
From the launch to the time of the data freeze for this study (March to October 2015), the number of individuals (self-selected) who consented to participate was 48 968, representing all 50 states and the District of Columbia. Their median age was 36 years (interquartile range, 27-50 years), and 82.2% (30 338 male, 6556 female, 10 other, and 3115 unknown) were male. In total, 40 017 (81.7% of those who consented) uploaded data. Among those who consented, 20 345 individuals (41.5%) completed 4 of the 7 days of motion data collection, and 4552 individuals (9.3%) completed all 7 days. Among those who consented, 40 017 (81.7%) filled out some portion of the questionnaires, and 4990 (10.2%) completed the 6-minute walk test, made available only at the end of 7 days. The Heart Age Questionnaire, also available after 7 days, required entering lipid values and age 40 to 79 years (among 17 245 individuals, 43.1% of participants). Consequently, 1334 (2.7%) of those who consented completed all fields needed to compute heart age and a 10-year risk score. Physical activity was detected for a mean (SD) of 14.5% (8.0%) of individuals' total recorded time. Physical activity patterns were identified by cluster analysis. A pattern of lower overall activity but more frequent transitions between active and inactive states was associated with equivalent self-reported cardiovascular disease as a pattern of higher overall activity with fewer transitions. Individuals' perception of their activity and risk bore little relation to sensor-estimated activity or calculated cardiovascular risk.
A smartphone-based study of cardiovascular health is feasible, and improvements in participant diversity and engagement will maximize yield from consented participants. Large-scale, real-world assessment of physical activity, fitness, and sleep using mobile devices may be a useful addition to future population health studies.
已有研究证实了身体活动和健康的重要性，但关于客观的、现实世界中的身体活动模式、健康状况、睡眠与心血管健康之间的关联，目前仍缺乏相关数据。
评估从智能手机中获取身体活动、健康状况和睡眠测量值的可行性，并深入了解与生活满意度和自我报告疾病相关的活动模式。
设计、设置和参与者：MyHeart Counts 智能手机应用程序于 2015 年 3 月推出，2015 年 3 月至 10 月期间，有前瞻性的参与者下载了这款免费应用程序。在这项基于智能手机的心血管健康研究中，参与者记录身体活动、填写健康问卷并完成 6 分钟步行测试。该应用程序可在美国境内下载。
完全在智能手机上进行同意和数据收集的可行性、使用机器学习对参与者进行聚类、以及活动模式、生活满意度和自我报告疾病之间的关联。
从启动到本研究数据冻结时间（2015 年 3 月至 10 月），有 48968 名（自行选择）个人同意参与，代表了美国的所有 50 个州和哥伦比亚特区。他们的中位年龄为 36 岁（四分位距 27-50 岁），82.2%（30338 名男性、6556 名女性、10 名其他性别和 3115 名未知性别）为男性。共有 40017 人（同意者的 81.7%）上传了数据。在同意者中，有 20345 人（41.5%）完成了 7 天运动数据采集的 4 天，4552 人（9.3%）完成了所有 7 天。在同意者中，有 40017 人（81.7%）填写了部分问卷，有 4990 人（10.2%）完成了仅在 7 天后提供的 6 分钟步行测试。也可在 7 天后填写的 Heart Age Questionnaire 需要输入血脂值和 40-79 岁的年龄（在 17245 人中，43.1%的参与者）。因此，有 1334 名（2.7%）同意者完成了计算心脏年龄和 10 年风险评分所需的所有字段。检测到的身体活动占个人总记录时间的平均（SD）为 14.5%（8.0%）。通过聚类分析确定了身体活动模式。整体活动量较低但活跃和不活跃状态之间转换更频繁的模式与整体活动量较高但转换次数较少的模式具有相同的自我报告心血管疾病风险。个人对自身活动和风险的感知与传感器估计的活动或计算的心血管风险几乎没有关系。
基于智能手机的心血管健康研究是可行的，提高参与者的多样性和参与度将最大限度地提高同意者的收益。使用移动设备对身体活动、健康状况和睡眠进行大规模的、现实世界的评估可能是未来人群健康研究的有益补充。
