Validation of Objective Measures of Place-Based Physical Activity

描述（由申请人提供）：我们建议实地测试和验证PALMS (Physical Activity Location Measurement System)，这是我们在基因环境倡议（GEI）的支持下开发的一种行为测量工具。我们将在圣地亚哥县的拉丁裔教会中进行R01研究。palm使用同时佩戴的全球定位系统（GPS）设备和加速度计的数据来确定位置、时间和体育活动（PA）类型，基本上是连续的。到这个项目开始时，我们将在一项由GEI机会基金资助的高度受控研究中验证PALMS中的处理算法。我们还处理了来自2000多名参与者（700名成年人、800名青少年和500名儿童）的7天GPS和加速度计数据，使我们能够从统计上证明除了加速度计数据外，收集GPS数据的价值。然而，我们尚未在正在进行的队列（或前瞻性）研究中评估PALMS，因此没有关于“现实世界”使用中工作人员或参与者负担的信息。我们在此提出的基于实地的验证研究将是合乎逻辑的下一步，以确保palm在典型的研究环境中可以被研究人员和研究参与者使用，并且它提供了有关其意图测量的内容的有效信息：身体活动的地理空间和时间特征。重要的是，我们选择与Elva Arredondo博士合作进行这项研究，Elva Arredondo博士是R01的PI，该R01研究了圣地亚哥拉丁裔人中基于地点的体育活动干预。Arredondo博士是nhlbi资助的一项多地点前瞻性队列研究——西班牙裔社区健康研究/拉丁美洲人研究（HCHS/SOL）的联合研究者，这是一项主要的全国性研究，其四个地点之一在圣地亚哥（其他地点在迈阿密、纽约和芝加哥）。圣地亚哥HCHS/SOL的PI是Greg Talavera博士他是我们提议的项目的合作研究员。因此，该项目将有助于为HCHS/SOL研究人员将PALMS纳入HCHS/SOL奠定基础。此外，基于地点的干预措施，如Arredondo博士的R01，旨在改善个人行为环境，并在最有利的环境中鼓励个人行为，可以从时间和空间上更精确的个人行为测量中获益。在本研究中，我们将：a)通过对参与者和研究人员的两轮评估，在基于社区的R01试验中展示PALMS的可用性；b)证明，与目前的调查方法相比，palm可以收集更精确和有效的连续组合测量体力活动（通过加速度计）和x-time位置（通过GPS）的数据；c)这些数据为研究人员提供了附加价值，因为它们比当前的GIS或基于调查的方法更有能力预测位置-x- pa关系。

DESCRIPTION (provided by applicant): We propose to field test and validate PALMS (Physical Activity Location Measurement System), a behavioral measurement tool that we have developed with support from the Gene-Environment Initiative (GEI). We will do this in an ongoing R01 study among church going Latinas in San Diego County. PALMS uses data from concurrently worn Global Positioning System (GPS) devices and accelerometers to ascertain location, time and type of physical activity (PA) on an essentially continuous basis. By the time this proposed project begins we will have validated the processing algorithms in PALMS in a highly controlled study supported by a GEI Opportunity Fund Grant. We have also processed 7-day GPS and accelerometer data from over 2000 participants (700 adults; 800 adolescents; and 500 children) enabling us to statistically demonstrate the value of collecting GPS data in addition to accelerometer data. However, we have not yet assessed PALMS in an ongoing cohort (or prospective) study and thus have no information on staff or participant burden in "real world" use. The field based validation study we propose herein will be the logical next step to ensure that PALMS is feasible to use-by both research staff and research participants-in typical research settings, and that it provides valid information about what it is intended to measure: the geospatial and temporal characteristics of physical activity. Importantly, we have selected to perform this research in collaboration with Dr. Elva Arredondo, PI of an R01 examining a place based physical activity intervention among Latinos in San Diego. Dr. Arredondo is a Co-investigator on a multi-site NHLBI-funded prospective cohort study, the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a major national study with one of its four sites in San Diego (others are in Miami, New York and Chicago). The PI of the San Diego HCHS/SOL is Dr. Greg Talavera and he is a proposed co-investigator on the project we propose. Thus, this project will help set the stage for HCHS/SOL investigators to incorporate PALMS into the HCHS/SOL. In addition, place based interventions like Dr. Arredondo's R01, that are designed to improve PA environments and encourage PA in the most supportive environments, can greatly benefit from more precise measures of PA in time and space. In this study we will: a) Demonstrate the usability of PALMS in a community-based R01 trial through two rounds of assessment with participants and research staff; b) Demonstrate that PALMS can collect more precise and valid data on continuous combined measures of physical activity (via accelerometer) and location- x-time (via GPS) than current survey methods; and c) that these data provide added value to researchers as they have greater ability to predict location-x-PA relationships than current GIS or survey based methods. PUBLIC HEALTH RELEVANCE: This project will field test and validate a new behavioral measurement tool that will help exposure biology researchers better understand the relationships between physical activity and the environment. PALMS uses data from concurrently worn Global Positioning System (GPS) devices and accelerometers to ascertain location, time and type of physical activity (PA) on an essentially continuous basis, collect and integrate data on physical activity. The science of integrating GPS and PA data is new but, when linked to increasingly sophisticated Geographical Information Systems (GIS), has the potential to deepen our understanding of the relationships between health and the environment.