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

基于 GPS/GIS 的新型前瞻性暴露测量方法的开发和验证

• 批准号: 8542802
• 负责人: Jacqueline Kerr
• 金额: $ 9.13万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-10 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8542802
• 关键词: Address; Affect; Age; Animals; Behavior; Buffers; Cities; Code; Communities; Country; Criminology; Data; Data Set; Data Sources; Databases; Destinations; Development; Devices; Dietary intake; Eating; Environment; Environmental Exposure; Exposure to; Food; Forestry; Future; Geography; Goals; Health; Health Food; Health behavior; Health behavior change; Health behavior outcomes; Home Ranges; Individual; International; Intervention Studies; Intervention Trial; Lead; Life; Light; Location; Low income; Measurement; Measures; Methods; Modeling; Monitor; Neighborhoods; Outcome; Participant; Physical activity; Pollution; Population Study; Research; Research Personnel; Restaurants; Retirement; Role; Route; Sampling; Sampling Studies; Sociology; Speed; Techniques; Time; Transportation; Travel; Validation; Walking; Weight; Work; base; behavior measurement; cost; density; energy balance; fast food; follow-up; food environment; improved; insulin sensitivity; land use; multidisciplinary; novel; obesity prevention; prospective; residence; sedentary

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).

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方面的作用的理解取得了进展。然而，大部分研究都集中在居住地址周围的建筑环境与体育活动 (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以及通往目的地的路线沿线。专注于一个位置（例如居住地址）会低估对多种环境的暴露程度。此外，健康行为通常以汇总方式评估，例如全天的总 PA。将一个位置与总体行为联系起来会导致效应大小被低估，特别是当该行为主要不是发生在该位置时。轻便、低成本且精确的 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 GIS 数据已与 GPS 数据结合使用，但迄今为止仅采用静态方法；即使用 GIS 来确定某些位置的时间，但不探索路线缓冲区或每日暴露于多个 跨越时间和空间的土地利用。在包含近 500 名 GPS 和加速计数据的参与者的两项研究样本中，我们将开发基于日常暴露于支持 PA 的环境（例如公园、连通街道、公共交通和多个目的地）和健康饮食的新颖、动态 GIS 变量（例如杂货店）。借助 GPS 轨迹，我们可以在多个位置周围创建“暴露区”、调查时间关联并估计沿线的环境暴露。我们可以按模式和速度对暴露进行加权，并根据 GPS 轨迹“查看”基于 GIS 的土地使用情况。将开发总结环境暴露的新技术，以避免因一天中不同的暴露而回归到平均值。一组数据包括来自 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“居住范围”（人们出行的范围）的变化。只有 16 个社区，我们也可以切实观察和编码当地的土地利用，以评估 GIS 数据库的有效性。随着行为测量更加精细，GIS 数据的不准确问题变得更加严重。另一个数据集包括住宅地址的更大变异性，提高了我们研究结果的普遍性，并改进了与传统的基于静态位置的 GIS 缓冲区与我们全天动态暴露测量的比较。此外，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在食物环境中对健康饮食的影响，这可能是一个重大改进。我们的多学科专家团队将使用溢出的一半方法来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个 R01 应用：1) 多国 GPS 研究 2) 将新方法应用于现有 GPS 样本 (N=2850)。