Comparability of accelerometer signal aggregation metrics across placements and dominant wrist cut points for the assessment of physical activity in adults
Comparability of accelerometer signal aggregation metrics across placements and dominant wrist cut points for the assessment of physical activity in adults
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DOI：
10.1038/s41598-019-54267-y
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发表时间：
2019-12-03
影响因子：
4.6
通讯作者：
Ortega, Francisco B.
中科院分区：
文献类型：
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作者：
Migueles, Jairo H.;Cadenas-Sanchez, Cristina;Ortega, Francisco B.
使用加速计进行身体行为和睡眠评估的大型流行病学研究在加速计附件的位置和所选的信号聚合度量上有所不同。本研究旨在评估常用的24小时身体附着点、清醒和睡眠时间的加速度指标的可比性，并测试优势腕和非优势腕的PA切割点的可比性。研究对象为45名青壮年(23名女性，18-41岁)，将GT3X+加速度计(美国佛罗里达州彭萨科拉Actigraph公司生产)放置在他们的右髋腕、优势腕和非优势腕上7天。我们从原始加速度得到了欧几里德范数减1g(Enmo)、低通滤波Enmo(LFENMO)、平均幅度偏差(MAD)和活动图活动计数。使用相关性分析和按一天中的不同时间绘制差异图来比较度量值。在一个可能的阈值网格中，以非优势腕关节的估计值为参考，使用Lin的协和相关系数优化得到了优势腕关节的切点。他们在一个单独的样本中交叉验证(N=36，10名女性，22-30岁)。加速指标对之间的共同差异因站点和指标对而异(r(2)范围：0.19-0.97，均为p<；0.01)，这表明某些站点和指标是关联的，而其他站点和指标不是关联的。我们观察到优势腕比非优势腕有更高的度量值，因此，我们根据Enmo开发了优势腕的切割点来分类久坐时间(=440毫克)。我们的发现表明优势腕和非优势腕之间的差异，我们提出了新的切割点来减弱这些差异。Enmo和LFENMO是最相似的指标，与MAD具有较好的可比性。然而，计数与Enmo、LFENMO和MAD不可同日而语。
Large epidemiological studies that use accelerometers for physical behavior and sleep assessment differ in the location of the accelerometer attachment and the signal aggregation metric chosen. This study aimed to assess the comparability of acceleration metrics between commonly-used body-attachment locations for 24 hours, waking and sleeping hours, and to test comparability of PA cut points between dominant and non-dominant wrist. Forty-five young adults (23 women, 18-41 years) were included and GT3X + accelerometers (ActiGraph, Pensacola, FL, USA) were placed on their right hip, dominant, and non-dominant wrist for 7 days. We derived Euclidean Norm Minus One g (ENMO), Low-pass filtered ENMO (LFENMO), Mean Amplitude Deviation (MAD) and ActiGraph activity counts over 5-second epochs from the raw accelerations. Metric values were compared using a correlation analysis, and by plotting the differences by time of the day. Cut points for the dominant wrist were derived using Lin's concordance correlation coefficient optimization in a grid of possible thresholds, using the nondominant wrist estimates as reference. They were cross-validated in a separate sample (N = 36, 10 women, 22-30 years). Shared variances between pairs of acceleration metrics varied across sites and metric pairs (range in r(2) : 0.19-0.97, all p < 0.01), suggesting that some sites and metrics are associated, and others are not. We observed higher metric values in dominant vs. non-dominant wrist, thus, we developed cut points for dominant wrist based on ENMO to classify sedentary time (= 440 mg). Our findings suggest differences between dominant and non-dominant wrist, and we proposed new cut points to attenuate these differences. ENMO and LFENMO were the most similar metrics, and they showed good comparability with MAD. However, counts were not comparable with ENMO, LFENMO and MAD.