Kim Youngwon, Lee Jung-Min, Peters Bradley P, Gaesser Glenn A, Welk Gregory J
Department of Kinesiology, Iowa State University, Ames, Iowa, United States of America.
School of Health, Physical Education and Recreation College of Education, University of Nebraska, Omaha, Nebraska, United States of America.
PLoS One. 2014 Apr 3;9(4):e90630. doi: 10.1371/journal.pone.0090630. eCollection 2014.
Public health research on sedentary behavior (SB) in youth has heavily relied on accelerometers. However, it has been limited by the lack of consensus on the most accurate accelerometer cut-points as well as by unknown effects caused by accelerometer position (wrist vs. hip) and output (single axis vs. multiple axes). The present study systematically evaluates classification accuracy of different Actigraph cut-points for classifying SB using hip and wrist-worn monitors and establishes new cut-points to enable use of the 3-dimensional vector magnitude data (for both hip and wrist placement).
A total of 125 children ages 7-13 yrs performed 12 randomly selected activities (from a set of 24 different activities) for 5 min each while wearing tri-axial Actigraph accelerometers on both the hip and wrist. The accelerometer data were categorized as either sedentary or non-sedentary minutes using six previously studied cut-points: 100 counts-per-minute (CPM), 200 CPM, 300 CPM, 500 CPM, 800 CPM and 1100 CPM. Classification accuracy was evaluated with Cohen's Kappa (κ) and new cut-points were identified from Receiver Operating Characteristic (ROC).
Of the six cut-points, the 100 CPM value yielded the highest classification accuracy (κ = 0.81) for hip placement. For wrist placement, all of the cut-points produced low classification accuracy (ranges of κ from 0.44 to 0.67). Optimal sedentary cut-points derived from ROC were 554.3 CPM (ROC-AUC of 0.99) for vector magnitude for hip, 1756 CPM (ROC-AUC of 0.94) for vertical axis for wrist, and 3958.3 CPM (ROC-AUC of 0.93) for vector magnitude for wrist placement.
The 100 CPM was supported for use with vertical axis for hip placement, but not for wrist placement. The ROC-derived cut-points can be used to classify youth SB with the wrist and with vector magnitude data.
青少年久坐行为（SB）的公共卫生研究严重依赖于加速度计。然而，它受到以下限制：对于最准确的加速度计切点缺乏共识，以及加速度计位置（手腕与臀部）和输出（单轴与多轴）所产生的未知影响。本研究系统地评估了使用臀部和手腕佩戴式监测器对不同Actigraph切点进行久坐行为分类的准确性，并建立了新的切点，以便能够使用三维向量大小数据（用于臀部和手腕放置）。
共有125名7至13岁的儿童，在臀部和手腕上佩戴三轴Actigraph加速度计，同时从一组24种不同活动中随机选择12种活动，每种活动持续5分钟。使用六个先前研究的切点将加速度计数据分类为久坐或非久坐分钟：每分钟100计数（CPM）、200 CPM、300 CPM、500 CPM、800 CPM和1100 CPM。使用科恩kappa系数（κ）评估分类准确性，并从受试者工作特征（ROC）中确定新的切点。
在六个切点中，100 CPM值在臀部放置时产生了最高的分类准确性（κ = 0.81）。对于手腕放置，所有切点的分类准确性都较低（κ范围为0.44至0.67）。从ROC得出的最佳久坐切点为：臀部向量大小为554.3 CPM（ROC曲线下面积为0.99），手腕垂直轴为1756 CPM（ROC曲线下面积为0.94），手腕放置向量大小为3958.3 CPM（ROC曲线下面积为0.93）。
支持将100 CPM用于臀部放置的垂直轴，但不用于手腕放置。从ROC得出的切点可用于通过手腕和向量大小数据对青少年久坐行为进行分类。
