Equating accelerometer estimates among youth: The Rosetta Stone 2
Equating accelerometer estimates among youth: The Rosetta Stone 2
复制标题
DOI：
10.1016/j.jsams.2015.02.006
复制
发表时间：
2016-03-01
影响因子：
4
通讯作者：
van sluijs, Esther M. F.
中科院分区：
文献类型：
--
作者：
Brazendale, Keith;Beets, Michael W.;van sluijs, Esther M. F.
目的：不同的研究人员使用不同的加速度计切割点，往往会产生非常不同的估计中度到剧烈强度的身体活动（MVPA）。这被认为是临界点非等效性（CNE），这降低了准确比较不同研究中青年MVPA的能力。本研究的目标是开发一个分界点转换系统，该系统可以标准化六组不同的已发布分界点的MVPA分钟数。设计：二级数据分析。方法：来自国际儿童加速度计数据库的数据（ICAD; 2014年春季），包括来自21项全球研究的43，112个Actigraph加速度计数据文件（3-18岁儿童，61.5%女性）用于开发六组已发表临界点的预测方程。使用留一交叉验证技术进行线性和非线性建模，以开发将MVPA从一组临界点转换为另一组临界点的方程。Bland Altman图显示了实际MVPA和预测MVPA值之间的一致性。结果：在总样本中，平均MVPA范围为29.7 MVPA min d（-1）（Puyau）至126.1 MVPA min d（-1）（Freedson 3 MET）。在转换方程中，中位绝对百分比误差为12.6%（范围：1.3 - 30.1），解释的方差比例范围为66.7%-99.8%。最佳预测方程（VC与EV）的平均差为0.110 min d（-1）（一致性限（LOA），-2.623至2.402）。表现最差的预测方程（FR 3从PY）的平均差异为34.76 min d（-1）（LOA，-60.392至129.910）。结论：对于六组不同的已发表的临界点，使用该等化系统可以帮助个人尝试综合越来越多的关于Actigraph、加速度计衍生MVPA的文献。(C)2015年澳大利亚运动医学。由爱思唯尔有限公司出版。保留所有权利。
Objectives: Different accelerometer cutpoints used by different researchers often yields vastly different estimates of moderate-to-vigorous intensity physical activity (MVPA). This is recognized as cutpoint non-equivalence (CNE), which reduces the ability to accurately compare youth MVPA across studies. The objective of this research is to develop a cutpoint conversion system that standardizes minutes of MVPA for six different sets of published cutpoints.Design: Secondary data analysis.Methods: Data from the International Children's Accelerometer Database (ICAD; Spring 2014) consisting of 43,112 Actigraph accelerometer data files from 21 worldwide studies (children 3-18 years, 61.5% female) were used to develop prediction equations for six sets of published cutpoints. Linear and non-linear modeling, using a leave one out cross-validation technique, was employed to develop equations to convert MVPA from one set of cutpoints into another. Bland Altman plots illustrate the agreement between actual MVPA and predicted MVPA values.Results: Across the total sample, mean MVPA ranged from 29.7 MVPA min d(-1) (Puyau) to 126.1 MVPA min d(-1) (Freedson 3 METs). Across conversion equations, median absolute percent error was 12.6% (range: 1.3 to 30.1) and the proportion of variance explained ranged from 66.7% to 99.8%. Mean difference for the best performing prediction equation (VC from EV) was 0.110 min d(-1) (limits of agreement (LOA), -2.623 to 2.402). The mean difference for the worst performing prediction equation (FR3 from PY) was 34.76 min d(-1) (LOA, -60.392 to 129.910).Conclusions: For six different sets of published cutpoints, the use of this equating system can assist individuals attempting to synthesize the growing body of literature on Actigraph, accelerometry-derived MVPA. (C) 2015 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.