Crouter S E, Bassett D R
Division of Nutritional Sciences, Cornell University, Ithaca, NY,USA.
Br J Sports Med. 2008 Mar;42(3):217-24. doi: 10.1136/bjsm.2006.033399. Epub 2007 Aug 30.
The objective of this study was to develop a new 2-regression model relating Actical activity counts to METs.
Forty-eight participants (mean (SD) age 35 (11.4) years) performed 10 min bouts of various activities ranging from sedentary behaviours to vigorous physical activities. Eighteen activities were split into three routines with each routine being performed by 20 individuals. Forty-five routines were randomly selected for the development of a new 2-regression model and 15 tests were used to cross-validate the new 2-regression model and compare it against existing equations. During each routine, the participant wore an Actical accelerometer on the hip and oxygen consumption was simultaneously measured by a portable metabolic system. The coefficient of variation (CV) of four consecutive 15 s epochs was calculated for each minute. For each activity, the average CV and the counts min(-1) were calculated for minutes 4-9. If the CV was < or =13% a walk/run regression equation was used and if the CV was >13% a lifestyle/leisure time physical activity regression was used.
An exponential regression line (R(2) = 0.912; standard error of the estimate (SEE) = 0.149) was used for activities with a CV< or =13%, and a cubic regression line (R(2) = 0.884, SEE = 0.804) was used for activities with a CV>13%. In the cross-validation group the mean estimates, using the new 2-regression model with an inactivity threshold, were within 0.56 METs of measured METs for each of the activities performed (p> or =0.05), except cycling (p<0.05).
For most activities examined the new 2-regression model predicted METs more accurately than currently available equations for the Actical accelerometer.
本研究的目的是开发一种新的二元回归模型,将Actical活动计数与代谢当量(METs)相关联。
48名参与者(平均(标准差)年龄35(11.4)岁)进行了10分钟的各种活动,范围从久坐行为到剧烈体育活动。18种活动被分成三个常规,每个常规由20个人进行。随机选择45个常规用于开发新的二元回归模型,并使用15次测试对新的二元回归模型进行交叉验证,并将其与现有方程进行比较。在每个常规期间,参与者在髋部佩戴Actical加速度计,并通过便携式代谢系统同时测量耗氧量。计算每分钟四个连续15秒时段的变异系数(CV)。对于每种活动,计算第4 - 9分钟的平均CV和每分钟计数(min⁻¹)。如果CV≤13%,则使用步行/跑步回归方程;如果CV>13%,则使用生活方式/休闲时间体育活动回归方程。
对于CV≤13%的活动,使用指数回归线(R² = 0.912;估计标准误差(SEE) = 0.149),对于CV>13%的活动,使用三次回归线(R² = 0.884,SEE = 0.804)。在交叉验证组中,使用具有不活动阈值的新二元回归模型,除了骑自行车(p<0.05)外,每种进行的活动的平均估计值与测量的代谢当量相差在0.56代谢当量以内(p≥0.05)。
对于大多数所检查的活动,新的二元回归模型比目前Actical加速度计可用的方程更准确地预测代谢当量。