Prediction of Energy Expenditure/Physical Activity in Children and Adolescents

儿童和青少年能量消耗/身体活动的预测

• 批准号: 7122480
• 负责人: NANCY F. BUTTE
• 金额: $ 29.66万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7122480
• 关键词: adolescence (12-20); basal metabolism; bioenergetics; body composition; body height; body physical activity; body weight; calorimetry; clinical research; heart rate; human subject; middle childhood (6-11); monitoring device; obesity; photon absorptiometry; physical fitness; statistics /biometry

DESCRIPTION (provided by applicant): In the proposed project, we will develop a model to predict minute-by-minute energy expenditure (EE) in children and adolescents using a new device called Actiheart, which simultaneously records heart rate (HR) and (PA). Total energy expenditure (TEE) will be derived from the summation of EE over a 24-h period and activity energy expenditure (AEE) will be computed from TEE using an estimate of resting metabolic rate (0.9 TEE-RMR). This method will be developed in a sample of 50 normal-weight and 50 overweight children and adolescents using 24-h room respiration calorimetry, and validated in an independent sample (n=46) using 24-h room respiration calorimetry and 7-day free-living measurements of TEE by the doubly labeled water (DLW) method. The overall goal will be to predict 24-h TEE and AEE of individuals from combined HR and PA within 10% of independently measured values by respiration calorimetry and DLW. Therefore, the specific aims of the proposed project are: 1. To develop multivariate adaptive regression splines (MARS) and cross-sectional time series models for the prediction of EE and hence 24-h TEE and AEE from HR in 50 normal-weight and 50 overweight children and adolescents using Actiheart and 24-h room respiration calorimetry. 2. To validate the MARS and cross-sectional time series models for the prediction of minute-by-minute EE and hence 24-h TEE and AEE from HR against 24-h room respiration calorimetry and DLW method in an independent sample of 23 normal-weight and 23 overweight children and adolescents. Public Health Relevance: Free-living measurements of 24-h TEE and AEE are required to better understand the metabolic, physiological, behavioral and environmental factors affecting energy balance and contributing to the global epidemic of childhood obesity. The two primary methods to measure EE (respiration calorimetry and DLW) are impractical for the large-scale epidemiological studies required to address this important public health problem. A new method based on direct ambulatory monitoring of HR and PA will be developed to accurately predict EE, and hence 24-h TEE and AEE in children and adolescents.

描述（由申请人提供）：在拟议的项目中，我们将开发一个模型，使用一种名为 Actiheart 的新设备来预测儿童和青少年每分钟的能量消耗 (EE)，该设备同时记录心率 (HR) 和 (宾夕法尼亚州）。总能量消耗 (TEE) 将根据 24 小时内 EE 的总和得出，活动能量消耗 (AEE) 将根据静息代谢率估计值 (0.9 TEE-RMR) 从 TEE 计算得出。该方法将使用 24 小时室内呼吸量热法在 50 名正常体重和 50 名超重儿童和青少年的样本中开发，并使用 24 小时室内呼吸量热法和 7 天自由呼吸量热法在独立样本 (n=46) 中进行验证。 - 通过双标记水 (DLW) 方法对 TEE 进行活体测量。总体目标是根据 HR 和 PA 的组合预测个体的 24 小时 TEE 和 AEE，误差在呼吸量热法和 DLW 独立测量值的 10% 范围内。因此，该项目的具体目标是： 1. 开发多元自适应回归样条 (MARS) 和横截面时间序列模型，用于预测 EE，从而预测 50 个正常体重和 HR 的 24 小时 TEE 和 AEE 50 名超重儿童和青少年使用 Actiheart 和 24 小时室内呼吸量热法。 2. 在 23 名正常人的独立样本中，根据 24 小时室内呼吸量热法和 DLW 方法验证 MARS 和横截面时间序列模型，用于预测每分钟 EE，从而预测来自 HR 的 24 小时 TEE 和 AEE -体重和23名超重儿童和青少年。公共健康相关性：需要对 24 小时 TEE 和 AEE 进行自由生活测量，以更好地了解影响能量平衡并导致全球儿童肥胖流行的代谢、生理、行为和环境因素。测量 EE 的两种主要方法（呼吸量热法和 DLW）对于解决这一重要公共卫生问题所需的大规模流行病学研究来说是不切实际的。将开发一种基于直接动态监测 HR 和 PA 的新方法，以准确预测 EE，从而准确预测儿童和青少年的 24 小时 TEE 和 AEE。