Physical Activity Energy Expenditure and Adolescent Obesity

描述(由申请人提供)： 体力活动所消耗的能量(EEAcr)是能量平衡的主要因素。由于随着时间的推移，微小的能量过剩(摄入和消耗)是导致人类体重增加和肥胖的最常见原因，因此测量EEACT的精确度对于病因学和干预性研究至关重要。青少年患肥胖症的风险很高，但他们间歇性的体力活动(PA)和更高的代谢效率使得测量EEAcr更具挑战性。现有的加速度计技术仅限于使用粗略的时间平均信号和过于简化的线性回归算法，这导致了EEAcr预测的不准确。以前对这些技术的验证研究经常有不精确的EE测量，缺乏自发的和较低强度的PA，并且样本容量不足。在我们提出的研究中，我们将测试这一假设，即与目前用于青少年的现有设备和算法相比，测量来自不同身体部分的详细运动和姿势信号将显著改善我们对EEACr的预测。在具体目标1中，我们将获得与PA同步的黄金标准EE测量，使用当前可用的定制设计的加速度计设备进行测量。我们将使用24小时的全房间间接量热计和3小时自由生活期的便携式热量计来测量分钟到分钟的EEACr。专门为这项研究开发的新的加速度计将在32个样本/秒、16个通道和10个不同的身体位置同步测量加速度。在具体目标2中，我们建议开发先进的建模方法来转换身体加速度和姿势来预测EEACr-我们将利用强大的人工神经网络和传统的生物统计学方法进行建模。在具体目标3中，我们将在使用无线设备和双标记水的自由生活青少年中验证这些EE预测模型。然后，我们将在具体目标4中定义PA在瘦、超重和肥胖青少年能量平衡中的作用。在这项研究中，我们将把生物工程设备和分析模型的最新进展应用于青少年肥胖的临床研究。这也将指导未来PA监测仪的设计，以针对这一脆弱群体的准确能源支出评估。此外，我们将利用我们的综合测量来验证和改进现有加速度计预测青少年能量消耗的能力，从而直接为现场研究人员带来好处。

DESCRIPTION (provided by applicant): The energy expended in physical activity (EEAcr) is a major factor in energy balance. Since small energy excess (intake>expenditure) over time is the most common cause for weight gain and obesity in humans, the precision in measuring EEACT is crucial for etiological and interventional studies. Adolescents are at high risk for obesity, yet the intermittent nature of their physical activity (PA) and their greater metabolic efficiency make measuring EEAcr more challenging. The existing technologies in accelerometry are restricted to using crude time-averaged signals and over-simplified linear regression algorithms, which lead to inaccuracies in EEAcr predictions. Previous validation studies of these technologies often had imprecise measures of EE, lacked spontaneous and lower intensity PA's, and suffered from insufficient sample sizes. In our proposed study, we will test this hypothesis that measurements of detailed motion and postural signals from different body segments will significantly improve our predictions of EEACr as compared to the existing devices and algorithms used currently for adolescents. In Specific Aim 1, we will obtain goldstandard EE measurements synchronously with PA measured using currently-available and custom designed accelerometry devices. We will measure minute-to-minute EEACr using a whole-room indirect calorimeter for a 24-hour period, and a portable calorimeter for a 3-hour free-living period. The new accelerometry device specifically developed for this study will synchronously measure accelerations at 32 samples/second, 16 channels, and 10 different body locations. In Specific Aim 2, we propose to develop advanced modeling approaches to transform body accelerations and postures to predict EEACr- We will utilize powerful Artificial Neural Network and traditional biostatistical approaches for modeling. In Specific Aim 3, we will validate these EE predictive models in free-living adolescents using wireless devices and doubly-labeled water. We will then, in Specific Aim 4, define the role of PA in energy balance for lean, overweight, and obese adolescents. In this study, we will apply the latest advances in bioengineering devices and analytical modeling in clinical investigations of adolescent obesity. This will also guide the design of future PA monitors targeting accurate energy expenditure assessments in this vulnerable population. Moreover, we will utilize our comprehensive measurements to validate and improve the ability of existing accelerometers to predict energy expenditure in adolescents, thus providing directly benefits to the field researchers.