Development and Validation of Novel Prospective GPS/GIS Based Exposure Measures

描述（由申请人提供）：在过去的十年中，我们对社区在预防肥胖中的作用的理解取得了进展。然而，大部分的研究都集中在住宅周围的建筑环境和身体活动（PA）之间的关系。关注静态地址点周围的环境有几个缺点。健康行为发生在多个地点和沿着的目的地。集中在一个位置，如住宅地址，低估了暴露于多种环境。此外，健康行为通常以汇总的方式进行评估，例如，一天中的总PA。将一个位置与总体行为相关联会导致被低估的效应大小，特别是如果行为主要不是发生在该位置。重量轻、成本低且精确的GPS设备的出现使研究人员能够客观地跟踪个人的位置。虽然地理信息系统数据已与全球定位系统数据一起使用，但迄今为止只采用了静态方法;即使用地理信息系统确定某些地点的时间，但不探索路线缓冲区或每日暴露于多种环境的情况。 土地利用跨越时空。在两个研究样本中，近500名参与者使用GPS和加速度计数据，我们将开发新的，动态的基于GIS的变量，这些变量是日常暴露于支持PA的环境（例如公园，连接的街道，公共交通和多个目的地）和健康饮食（例如杂货店）。有了GPS轨迹，我们可以在多个地点周围创建“监控区”，调查时间关联，并估计沿着的环境暴露。我们可以根据模式和速度对暴露进行加权，并根据GPS轨迹调查基于GIS的土地利用。将开发总结环境暴露的新技术，以避免回归到一天中不同暴露的平均值。一个数据集包括来自16个退休社区的生态干预试验的前瞻性数据。这将使我们能够根据建筑环境评估“家庭范围”（人们旅行的范围）的变化。由于只有16个社区，我们也可以可行地观察和编码当地的土地利用，以评估GIS数据库的有效性。随着更精细的行为测量，GIS数据中的不准确性变得更成问题。另一个数据集包括住宅地址的更大变化，增加了我们发现的普遍性，并改善了与传统的基于静态位置的GIS缓冲区的比较，以对抗我们全天的动态暴露措施。此外，这第二个数据集包括饮食摄入量的测量，这将使我们能够评估全天暴露于食品环境对健康饮食的影响，这可能是一个重大的改进。我们的多学科专家团队将使用半分法开发和验证针对行为和健康结果的新措施。这项测量开发工作将支持两项R 01应用：1）多国GPS研究2）将新方法应用于现有GPS样本（N=2850）。 公共卫生相关性：我们才刚刚开始了解我们生活，工作和花费时间的地方如何影响我们的健康。这项研究将使用GPS数据，提供全天的人的踪迹，显示他们在哪里度过他们的时间，以及他们如何到达那里。了解人们活动和获取食物的地方的类型将有助于我们创造帮助人们活动和吃得更好的环境。

DESCRIPTION (provided by applicant): In the last decade, our understanding of neighborhoods' role in obesity prevention has progressed. However, much of the research has focused on the relationships between the built environment around a residential address and physical activity (PA). Focusing on the environment around static address points has several drawbacks. Health behaviors occur in multiple locations and along routes to destinations. Focusing on one location, such as residential address, underestimates the exposure to multiple environments. Further, health behaviors are usually assessed in an aggregate manner, for example, total PA across the day. Relating one location to total behavior results in underestimated effect sizes, especially if the behavior does not primarily occur at that location. The emergence of lightweight, low cost, and accurate GPS devices has enabled researchers to objectively track the location of an individual. While GIS data have been used in conjunction with GPS data, to date only a static approach has been employed; i.e. using the GIS to determine time in certain locations, but not exploring route buffers or daily exposures to multiple land uses across time and space. In two study samples of almost 500 participants with GPS and accelerometer data, we will develop novel, dynamic GIS based variables of daily exposure to environments that support PA (e.g. parks, connected streets, access to public transportation, and multiple destinations) and healthy eating (e.g. grocery stores). With the GPS traces, we can create "expozones" around multiple locations, investigate temporal associations, and estimate environmental exposures along routes. We can weight exposures by mode and speed and investigate GIS based land uses "in view" of the GPS traces. New techniques to summarize the environmental exposures will be developed to avoid regression to the mean from varying exposures across the day. One data set includes prospective data from an ecological intervention trial in 16 retirement communities. This will allow us to assess changes in "home range" (how widely people travel) based on the built environment. With only 16 communities, we can also feasibly observe and code the local land uses to assess the validity of the GIS databases. With more refined behavioral measures, inaccuracies in the GIS data become more problematic. The other dataset includes greater variability in residential addresses, increasing the generalizability of our findings and improving the comparison with traditional static location based GIS buffers against our dynamic exposure measures across the day. Further this second data set includes measures of dietary intake that will allow us to assess the impact of full-day exposure to food environments on healthy eating, which is likely to be a major improvement. Our multidisciplinary team of experts will develop and validate the new measures against behaviors and health outcomes using a spilt halves method. This measurement development work will support two R01 applications: 1) a multi-country GPS study 2) application of new methods to existing GPS samples (N=2850). PUBLIC HEALTH RELEVANCE: We are only just starting to understand how where we live, work and spend our time affects how healthy we are. This study will use GPS data that provides traces of people throughout the day, showing where they are spending their time and how they get there. Understanding the types of places where people are active and get their food will help us create environments that help people be active and eat better.