Weber Kyle S, Godkin F Elizabeth, Cornish Benjamin F, McIlroy William E, Van Ooteghem Karen
Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.
JMIR Form Res. 2023 Mar 15;7:e41685. doi: 10.2196/41685.
Accurate measurement of daily physical activity (PA) is important as PA is linked to health outcomes in older adults and people living with complex health conditions. Wrist-worn accelerometers are widely used to estimate PA intensity, including walking, which composes much of daily PA. However, there is concern that wrist-derived PA data in these cohorts is unreliable due to slow gait speed, mobility aid use, disease-related symptoms that impact arm movement, and transient activities of daily living. Despite the potential for error in wrist-derived PA intensity estimates, their use has become ubiquitous in research and clinical application.
The goals of this work were to (1) determine the accuracy of wrist-based estimates of PA intensity during known walking periods in older adults and people living with cerebrovascular disease (CVD) or neurodegenerative disease (NDD) and (2) explore factors that influence wrist-derived intensity estimates.
A total of 35 older adults (n=23 with CVD or NDD) wore an accelerometer on the dominant wrist and ankle for 7 to 10 days of continuous monitoring. Stepping was detected using the ankle accelerometer. Analyses were restricted to gait bouts ≥60 seconds long with a cadence ≥80 steps per minute (LONG walks) to identify periods of purposeful, continuous walking likely to reflect moderate-intensity activity. Wrist accelerometer data were analyzed within LONG walks using 15-second epochs, and published intensity thresholds were applied to classify epochs as sedentary, light, or moderate-to-vigorous physical activity (MVPA). Participants were stratified into quartiles based on the percent of walking epochs classified as sedentary, and the data were examined for differences in behavioral or demographic traits between the top and bottom quartiles. A case series was performed to illustrate factors and behaviors that can affect wrist-derived intensity estimates during walking.
Participants averaged 107.7 (SD 55.8) LONG walks with a median cadence of 107.3 (SD 10.8) steps per minute. Across participants, wrist-derived intensity classification was 22.9% (SD 15.8) sedentary, 27.7% (SD 14.6) light, and 49.3% (SD 25.5) MVPA during LONG walks. All participants measured a statistically lower proportion of wrist-derived activity during LONG walks than expected (all P<.001), and 80% (n=28) of participants had at least 20 minutes of LONG walking time misclassified as sedentary based on wrist-derived intensity estimates. Participants in the highest quartile of wrist-derived sedentary classification during LONG walks were significantly older (t=4.24, P<.001) and had more variable wrist movement (t=2.13, P=.049) compared to those in the lowest quartile.
The current best practice wrist accelerometer method is prone to misclassifying activity intensity during walking in older adults and people living with complex health conditions. A multidevice approach may be warranted to advance methods for accurately assessing PA in these groups.
准确测量日常身体活动(PA)很重要,因为PA与老年人和患有复杂健康状况的人群的健康结果相关。腕部佩戴的加速度计被广泛用于估计PA强度,包括步行,而步行占日常PA的很大一部分。然而,人们担心这些队列中源自手腕的PA数据由于步态速度慢、使用移动辅助工具、影响手臂运动的疾病相关症状以及日常生活中的短暂活动而不可靠。尽管源自手腕的PA强度估计可能存在误差,但它们在研究和临床应用中已变得无处不在。
这项工作的目标是(1)确定老年人以及患有脑血管疾病(CVD)或神经退行性疾病(NDD)的人群在已知步行期间基于手腕的PA强度估计的准确性,以及(2)探索影响源自手腕的强度估计的因素。
共有35名老年人(n = 23名患有CVD或NDD)在优势手腕和脚踝上佩戴加速度计,持续监测7至10天。使用脚踝加速度计检测步数。分析仅限于时长≥60秒且步频≥每分钟80步的步态周期(长距离步行),以识别可能反映中等强度活动的有目的、持续步行的时间段。在长距离步行期间,使用15秒的时间段对腕部加速度计数据进行分析,并应用已发表的强度阈值将时间段分类为久坐、轻度或中度至剧烈身体活动(MVPA)。参与者根据被分类为久坐的步行时间段百分比被分层为四分位数,并检查最高和最低四分位数之间行为或人口统计学特征的差异。进行了一个病例系列研究,以说明在步行期间可能影响源自手腕的强度估计的因素和行为。
参与者平均有107.7次(标准差55.8)长距离步行,步频中位数为每分钟107.3步(标准差10.8)。在所有参与者中,长距离步行期间源自手腕的强度分类为22.9%(标准差15.8)久坐、27.7%(标准差14.6)轻度和49.3%(标准差25.5)MVPA。所有参与者在长距离步行期间测量的源自手腕的活动比例在统计学上低于预期(所有P <.001),并且80%(n = 28)的参与者根据源自手腕的强度估计至少有20分钟的长距离步行时间被错误分类为久坐。与最低四分位数的参与者相比,长距离步行期间源自手腕的久坐分类处于最高四分位数的参与者年龄显著更大(t = 4.24,P <.001)且手腕运动变化更大(t = 2.13,P =.049)。
当前最佳实践的腕部加速度计方法在老年人和患有复杂健康状况的人群步行期间容易错误分类活动强度。可能需要采用多设备方法来改进这些人群中准确评估PA的方法。