Brage Søren, Ekelund Ulf, Brage Niels, Hennings Mark A, Froberg Karsten, Franks Paul W, Wareham Nicholas J
MRC Epidemiology Unit, Cambridge CB1 9NL, UK.
J Appl Physiol (1985). 2007 Aug;103(2):682-92. doi: 10.1152/japplphysiol.00092.2006. Epub 2007 Apr 26.
Combining accelerometry with heart rate (HR) monitoring may improve precision of physical activity measurement. Considerable variation exists in the relationships between physical activity intensity (PAI) and HR and accelerometry, which may be reduced by individual calibration. However, individual calibration limits feasibility of these techniques in population studies, and less burdensome, yet valid, methods of calibration are required. We aimed to evaluate the precision of different individual calibration procedures against a reference calibration procedure: a ramped treadmill walking-running test with continuous measurement of PAI by indirect calorimetry in 26 women and 25 men [mean (SD): 35 (9) yr, 1.69 (0.10) m, 70 (14) kg]. Acceleration (along the longitudinal axis of the trunk) and HR were measured simultaneously. Alternative calibration procedures included treadmill testing without calorimetry, submaximal step and walk tests with and without calorimetry, and nonexercise calibration using sleeping HR and gender. Reference accelerometry and HR models explained >95% of the between-individual variance in PAI (P < 0.001). This fraction dropped to 73 and 81%, respectively, for accelerometry and HR models calibrated with treadmill tests without calorimetry. Step-test calibration captured 62-64% (accelerometry) and 68% (HR) of the variance between individuals. Corresponding values were 63-76% and 59-61% for walk-test calibration. There was only little benefit of including calorimetry during step and walk calibration for HR models. Nonexercise calibration procedures explained 54% (accelerometry) and 30% (HR) of the between-individual variance. In conclusion, a substantial proportion of the between-individual variance in relationships between PAI, accelerometry, and HR is captured with simple calibration procedures, feasible for use in epidemiological studies.
将加速度测量与心率(HR)监测相结合可能会提高身体活动测量的精度。身体活动强度(PAI)与心率和加速度测量之间的关系存在相当大的差异,个体校准可能会减少这种差异。然而,个体校准限制了这些技术在人群研究中的可行性,因此需要更简便且有效的校准方法。我们旨在针对一种参考校准程序评估不同个体校准程序的精度:对26名女性和25名男性[平均(标准差):35(9)岁,身高1.69(0.10)米,体重70(14)千克]进行斜坡式跑步机行走 - 跑步测试,通过间接量热法连续测量PAI。同时测量加速度(沿躯干纵轴)和心率。替代校准程序包括不使用量热法的跑步机测试、有和没有量热法的次最大阶梯和步行测试,以及使用静息心率和性别的非运动校准。参考加速度测量和心率模型解释了PAI个体间差异的>95%(P<0.001)。对于未使用量热法的跑步机测试校准的加速度测量和心率模型,这一比例分别降至73%和81%。阶梯测试校准捕获了个体间差异的62 - 64%(加速度测量)和68%(心率)。步行测试校准的相应值为63 - 76%和59 - 61%。在阶梯和步行校准中,对于心率模型,使用量热法的益处不大。非运动校准程序解释了个体间差异的54%(加速度测量)和30%(心率)。总之,通过简单的校准程序可以捕获PAI、加速度测量和心率之间关系中相当一部分的个体间差异,这些程序在流行病学研究中使用是可行的。