Agreement Between Apple Watch and Actical Step Counts in a Community Setting: Cross-Sectional Investigation From the Framingham Heart Study.

Nicole L Spartano, Yuankai Zhang, Chunyu Liu, Ariel Chernofsky, Honghuang Lin, Ludovic Trinquart, Belinda Borrelli, Chathurangi H Pathiravasan, Vik Kheterpal, Christopher Nowak, Ramachandran S Vasan, Emelia J Benjamin, David D McManus, Joanne M Murabito
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Abstract

Background: Step counting is comparable among many research-grade and consumer-grade accelerometers in laboratory settings.

Objective: The purpose of this study was to compare the agreement between Actical and Apple Watch step-counting in a community setting.

Methods: Among Third Generation Framingham Heart Study participants (N=3486), we examined the agreement of step-counting between those who wore a consumer-grade accelerometer (Apple Watch Series 0) and a research-grade accelerometer (Actical) on the same days. Secondarily, we examined the agreement during each hour when both devices were worn to account for differences in wear time between devices.

Results: We studied 523 participants (n=3223 person-days, mean age 51.7, SD 8.9 years; women: n=298, 57.0%). Between devices, we observed modest correlation (intraclass correlation [ICC] 0.56, 95% CI 0.54-0.59), poor continuous agreement (29.7%, n=957 of days having steps counts with ≤15% difference), a mean difference of 499 steps per day higher count by Actical, and wide limits of agreement, roughly ±9000 steps per day. However, devices showed stronger agreement in identifying who meets various steps per day thresholds (eg, at 8000 steps per day, kappa coefficient=0.49), for which devices were concordant for 74.8% (n=391) of participants. In secondary analyses, in the hours during which both devices were worn (n=456 participants, n=18,760 person-hours), the correlation was much stronger (ICC 0.86, 95% CI 0.85-0.86), but continuous agreement remained poor (27.3%, n=5115 of hours having step counts with ≤15% difference) between devices and was slightly worse for those with mobility limitations or obesity.

Conclusions: Our investigation suggests poor overall agreement between steps counted by the Actical device and those counted by the Apple Watch device, with stronger agreement in discriminating who meets certain step thresholds. The impact of these challenges may be minimized if accelerometers are used by individuals to determine whether they are meeting physical activity guidelines or tracking step counts. It is also possible that some of the limitations of these older accelerometers may be improved in newer devices.

社区环境中 Apple Watch 和 Actical 步数的一致性:来自弗雷明汉心脏研究的横断面调查
背景:在实验室环境中,许多研究级和消费级加速度计的计步性能相当:在实验室环境中,许多研究级和消费级加速度计的计步结果具有可比性:本研究旨在比较 Actical 和 Apple Watch 在社区环境中计步的一致性:在第三代弗雷明汉心脏研究参与者(N=3486)中,我们检查了在同一天佩戴消费级加速度计(Apple Watch Series 0)和研究级加速度计(Actical)的参与者的计步一致性。其次,我们还考察了在佩戴两种设备的每个小时内的一致性,以考虑设备之间佩戴时间的差异:我们研究了 523 名参与者(n=3223 人天,平均年龄 51.7 岁,SD 8.9 岁;女性:n=298,57.0%)。在不同设备之间,我们观察到了适度的相关性(类内相关性 [ICC] 0.56,95% CI 0.54-0.59)、较差的连续一致性(29.7%,n=957 天的步数差异≤15%)、Actical 每天平均高出 499 步的差异以及较宽的一致性范围(大约为每天 ±9000 步)。不过,设备在识别哪些人达到了不同的日步数阈值(例如,在日步数为 8000 步时,卡帕系数=0.49)时表现出了更强的一致性,在这一点上,74.8% 的参与者(人数=391)的设备是一致的。在二次分析中,在佩戴两种设备的小时数中(456 名参与者,18760 人时),设备间的相关性更强(ICC 0.86,95% CI 0.85-0.86),但设备间的连续一致性仍然较差(27.3%,5115 个小时的步数差异≤15%),对于行动不便或肥胖者,设备间的一致性略差:我们的调查表明,Actical 设备计算的步数与 Apple Watch 设备计算的步数之间的整体一致性较差,而在区分哪些人达到特定步数阈值方面的一致性较强。如果个人使用加速度计来确定自己是否符合体育锻炼指南或跟踪步数,这些挑战的影响可能会降到最低。此外,这些老式加速度计的一些局限性也有可能在更新的设备中得到改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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