Investigating Sedentary Time In Aging: New Directions Using Technology (iSTAND)

描述（由申请人提供）：老年人每天坐着的时间超过8小时，比任何其他年龄组都多。久坐时间长现在与身体活动之外的不良健康影响（如糖尿病、心血管疾病相关死亡率）有关。这表明明确关注久坐行为的研究是有道理的。为了进一步研究肥胖、糖尿病和心血管疾病老年人的久坐行为，需要解决以下三个问题：1)利用基于先进技术的方法改善久坐时间的测量（由于自我报告和传统加速度计数据处理技术的局限性）；2)了解久坐时间与心脏代谢生物标志物和健康状况之间的关系；3)开发基于技术的干预措施以减少久坐时间。iSTAND（调查久坐时间在老龄化中的作用：利用技术的新方向）项目旨在利用来自三个丰富来源的数据来解决这些差距（成功老龄化评估[SAGE]研究，妇女健康倡议[WHI]长寿研究，以及来自大型综合医疗保健系统的参与者池）。在第一个研究目标中，探索了久坐时间的客观测量技术（例如加速度计、SenseCam、机器学习算法）（aim 1a），并将加速度计数据的机器学习算法应用于WHI样本，以检查老年妇女久坐时间与健康风险因素之间的关系（aim 1b）。在目标2中，将进行焦点小组讨论，为针对肥胖、糖尿病和/或心血管疾病的老年人制定基于技术的减少久坐时间计划提供信息。在一项试点干预中，将对来自大型综合医疗保健系统的40名患有肥胖症、糖尿病和/或心血管疾病的老年人进行干预的可行性和可接受性测试。这项研究计划与罗森博格博士的培训计划相吻合，以获得她所缺乏的两个关键领域的必要技能和知识：1)更准确地测量久坐时间的无线技术；2)在老年人中应用无线技术减少久坐时间的干预措施。该项目将由一个多学科专家导师团队（生物信息学、技术与测量、老年病学、统计学）和通过培训经验、课程和会议获得的知识指导。这项为期4年的以患者为导向的研究职业发展奖的支持，将使罗森伯格博士领导一个独立的研究项目，利用技术减少患有慢性疾病的老年人的久坐时间。

DESCRIPTION (provided by applicant): Older adults spend over 8 hours per day sitting, more than any other age group. High sedentary time has now been associated with adverse health impacts (e.g. diabetes, cardiovascular disease related mortality) independent from physical activity. This suggests that research explicitly focusing on sedentary behavior is warranted. To further the field of sedentary behavior research among older adults with obesity, diabetes, and cardiovascular disease, three gaps will be addressed: 1) improving measures of sedentary time using advanced technology-based methods (due to limitations of self-reports and traditional accelerometer data processing techniques); 2) understanding relationships between sedentary time and cardio-metabolic biomarkers and health conditions; and, 3) developing technology-based interventions to reduce sedentary time. The iSTAND (Investigating Sedentary Time in Aging: New Directions using technology) Project aims to address these gaps using data from 3 rich sources (Successful Aging Evaluation [SAGE] Study, the Women's Health Initiative [WHI] Long Life Study, and a participant pool from a large integrated health care system). In the first research aim, objective measurement techniques for sedentary time (e.g. accelerometers, SenseCam, machine learning algorithms) are explored (Aim 1a), and machine learning algorithms for accelerometer data are applied to the WHI sample to examine relationships between sedentary time and health risk factors among older women (Aim 1b). In Aim 2, focus groups will be conducted to inform development of a technology-based sedentary time reduction program targeting older adults with obesity, diabetes, and/or cardiovascular disease. In a pilot intervention, the feasibility and acceptability of the intervention will be tested in 40 older aduls with obesity, diabetes, and/or cardiovascular disease from a large integrated health care system. The research plans dovetail with training plans for Dr. Rosenberg to obtain necessary skills and knowledge in 2 key areas where she has deficits: 1) wireless technologies to measure sedentary time more accurately, and, 2) application of wireless technologies to sedentary time reduction interventions among older adults. The project will be guided by a multidisciplinary team of expert mentors (bioinformatics, technology and measurement, geriatrics, statistics) and knowledge obtained through training experiences, coursework, and conferences. Support from this 4-year patient-oriented research career development award will position Dr. Rosenberg to lead an independent research program in using technology decrease sedentary time among older adults with chronic health conditions.