Metabolic Costs of Daily Activities in Older Adults

描述（由申请人提供）：美国人将超过90%的与活动相关的能量消耗用于日常活动。卫生保健专业人员使用规范性数据作为指导，为患者和客户规定适当的活动。此外，科学家利用这些资源计划体育活动或营养干预，并将这些估计应用于流行病学研究。然而，虽然规范数据已经存在了20多年，并且在年轻人中似乎是准确的，但它们可能导致对老年人日常活动代谢成本的错误估计。这不是一个微不足道的问题，因为体育活动是唯一已知的改善老年人身体功能的方式之一，在调节体重方面起着关键作用。然而，关于日常活动代谢成本的潜在年龄相关差异的信息严重缺乏。这给心肺和骨科损伤风险较高的人群合理开具体育锻炼处方留下了很大的知识空白。该项目的主要目标是验证衰老与运动和生活方式活动的代谢成本差异有关的假设。我们将在进行38项日常活动时佩戴便携式间接热量计，评估210名20至80岁以上的成年人的肺气体交换。我们将检查每项任务的代谢当量（代谢当量作为3.5毫升“min-1”kg-1的函数）、代谢经济性（给定工作速率下的能量消耗）和相对代谢成本（作为静息和峰值耗氧量的函数）作为年龄的函数。其次，我们将通过对另外90名患有功能障碍的老年人（60岁以上）进行测试，研究日常活动的代谢成本是如何受到功能障碍的影响的。第三，由于科学家和公共卫生官员都依赖于基于感知的运动来监测身体活动的强度，我们将解决这个问题——“衰老是否与自我测量感知运动的不准确性有关？”解决这个问题将有助于更好地为老年人推荐运动强度。最后，所提出的设计和综合代谢测量将为验证用于估计身体活动类型和强度的加速度计提供前所未有的机会。使用应用机器学习方法的新数学技术（随机森林、支持向量和多核学习技术），我们将评估在估计体育活动类型和强度时减少误差的潜力

DESCRIPTION (provided by applicant): Americans spend over 90% of their activity related energy expenditure performing common daily activities. Health care professionals use normative data as a guide to prescribe appropriate activities for patients and clients. Additionally, scientists use this resource to plan physical activity or nutritional interventions ad apply these estimates to epidemiological research. However, while normative data have existed for over 20 years and are seemingly accurate in young adults, they can lead to misguided estimates of the metabolic cost of daily activities in older adults. This is not a trivial issue sice physical activity is one of the only known modalities to improve physical function in older adults and plays a critical role in regulating body weight. However, there is a serious lack of information pertaining to potential age-related differences in the metabolic cost of daily activitis. This leaves a major gap in knowledge for properly prescribing physical activity for a population that has elevated risk cardiopulmonary and orthopedic impairments. The primary goal of this project is to test the hypothesis that aging is associated with a difference in the metabolic cost f doing exercise and lifestyle activities. We will assess pulmonary gas exchange in 210 adults aged 20 to 80+ years with a portable indirect calorimeter worn while performing 38 daily activities. We will examine the metabolic equivalent (MET as a function of 3.5 milliliter" min-1"kg-1), metabolic economy (energy expended for a given work rate) and relative metabolic cost (as a function of resting and peak oxygen consumption) for each task as a function of age. Secondly, we will address how metabolic costs of daily activities are affected by having functional impairments by testing an additional 90 older adults (60+ years) with functional impairment. Thirdly, because scientists and public health officials alike rely on perception-based exertion to monitor intensity of physical activity, we will address the question- "Is aging associated with inaccuracies for self-gauging perceived exertion?" Addressing this question will gain insight into a better delivery system for recommending physical intensity to older adults. Lastly, the design and comprehensive metabolic measurements being proposed will provide an unprecedented opportunity to validate accelerometers for estimating the type and intensity of physical activity. Using new mathematical techniques that apply machine learning approaches (random forests, support vector and multiple kernel learning techniques), we will assess the potential to reduce the error in estimating the type and intensity of physical activity as compared to traditional methods. There are many end products of this research. First, the work will produce the largest dataset of metabolic cost for daily activities in 60+ years old. Second, an age-correction factor for metabolic costs will be created to apply to hundreds of tasks that fall into similar categories as those being evaluated. Finally, the work will refine the tools needed to feasibly assess physical activity in young and old adults. These accomplishments will directly impact the fields of epidemiology, geriatric medicine, rehabilitation, and nutritional sciences.