Use of a Two-Regression Model for Estimating Energy Expenditure in Children
Use of a Two-Regression Model for Estimating Energy Expenditure in Children
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DOI：
10.1249/mss.0b013e3182447825
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发表时间：
2012-06-01
期刊：
影响因子：
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通讯作者：
Bassett, David R., Jr.
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文献类型：
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作者：
Crouter, Scott E.;Horton, Magdalene;Bassett, David R., Jr.
克鲁特E、M. HORTON，和D. R.小巴塞特使用双回归模型估计儿童的能量消耗。医学科学体育锻炼，第44卷，第6期，第100页。1177-1185，2012。目的：本研究的目的是开发两种新的双回归模型（2 RM），用于儿童，使用ActiGraph GT 3X估计能量消耗（EE）：1）平均向量幅度（VM）计数或2）垂直轴（VA）计数。还将新的2 RM与现有的儿童ActiGraph方程进行了比较。研究方法：57名男孩和52名女孩（平均值+/- SD：年龄= 11 +/- 1.7岁，体重指数= 21.4 +/- 5.5 kg.m（-2））进行了30分钟仰卧休息和8分钟的6种不同活动，从久坐行为到剧烈的体力活动。18项活动分为三个常规，每个常规由38-39名参与者进行。77名参与者用于开发组，39名参与者用于交叉验证组。在所有测试过程中，使用佩戴在右髋的ActiGraph GT 3X收集活动数据，并使用Cosmed K4 b（2）测量耗氧量。所有能量消耗值表示为METRMR（活动（V）对dotO（2）/休息（V）对dotO（2））。结果如下：对于每项活动，使用VA和VM的10-s时间点计算变异系数，以确定活动是连续步行/跑步还是间歇性生活方式活动。独立的回归方程，步行/跑步和间歇性生活方式的活动。在交叉验证组中，除运动墙和跑步外，所有活动的VM和VA 2 RM均在测量METRMR的0.8METRMR范围内（均P > 0.05）。其他现有ActiGraph方程的活动平均误差范围为0.0至2.6 METRMR。结论：与目前可用的其他预测公式相比，ActiGraph GT 3X用于儿童的新2 RM提供了更接近平均测量METRMR的估计值。此外，它们改善了各种活动强度下的个体预测误差。
CROUTER, S. E., M. HORTON, and D. R. BASSETT Jr. Use of a Two-Regression Model for Estimating Energy Expenditure in Children. Med. Sci. Sports Exerc., Vol. 44, No. 6, pp. 1177-1185, 2012. Purpose: The purpose of this study was to develop two new two-regression models (2RM), for use in children, that estimate energy expenditure (EE) using the ActiGraph GT3X: 1) mean vector magnitude (VM) counts or 2) vertical axis (VA) counts. The new 2RMs were also compared with existing ActiGraph equations for children. Methods: Fifty-seven boys and 52 girls (mean +/- SD: age = 11 +/- 1.7 yr, body mass index = 21.4 +/- 5.5 kg.m(-2)) performed 30-min supine rest and 8 min of six different activities ranging from sedentary behaviors to vigorous physical activity. Eighteen activities were split into three routines with each routine performed by 38-39 participants. Seventy-seven participants were used for the development group, and 39 participants were used for the cross-validation group. During all testing, activity data were collected using an ActiGraph GT3X, worn on the right hip, and oxygen consumption was measured using a Cosmed K4b(2). All energy expenditure valises are expressed as METRMR (activity (V) over dotO(2)/resting (V) over dotO(2)). Results: For each activity, a coefficient of variation was calculated using 10-s epochs for the VA and VM to determine whether the activity was continuous walking/running or an intermittent lifestyle activity. Separate regression equations were developed for walking/running and intermittent lifestyle activity. In the cross-validation group, the VM and VA 2RMs were within 0.8 METRMR of measured METRMR for all activities except Sportwall and running (all P > 0.05). The other existing ActiGraph equations had mean errors ranging from 0.0 to 2.6 METRMR for the activities. Conclusions: The new 2RMs for use in children with the ActiGraph GT3X provide a closer estimate of mean measured METRMR than other currently available prediction equations. In addition, they improve the individual prediction errors across a wide range of activity intensities.