Leveraging cell phone location data to measure interactions with the food environment and associated health outcomes

利用手机位置数据来衡量与食品环境的相互作用以及相关的健康结果

• 批准号: 10707905
• 负责人: Pablo Monsivais
• 金额: $ 19.13万
• 依托单位: WASHINGTON STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-22 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10707905
• 关键词: Acceleration; Address; Adult; Algorithms; American; Behavior; Behavioral; Big Data; Body Weight; Body Weight Changes; Cardiovascular Diseases; Cellular Phone; Characteristics; Chronic Disease; Classification; Communities; Consumption; Cross-Sectional Studies; Data; Development; Devices; Diet; Dietary intake; Environment; Error Sources; Food; Food Access; Food Patterns; Frequencies; Funding; Geographic Locations; Geography; Grant; Health; Health Food; Health behavior; Home; Human; Individual; Location; Malignant Neoplasms; Measurement; Measures; Methods; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Outcome; Participant; Patient Self-Report; Pattern; Persons; Population; Population Research; Positioning Attribute; Questionnaires; Recording of previous events; Registries; Research; Research Personnel; Resolution; Restaurants; Risk; Risk Factors; Sampling; Services; Shapes; Source; Surveys; Time; Travel; Twin Multiple Birth; Unhealthy Diet; United States National Institutes of Health; Washington; Weight; Weight Gain; Work; behavior measurement; built environment; cohort; data space; design; diaries; dietary; epidemiology study; fast food; food consumption; food environment; health data; insight; longitudinal analysis; novel; novel strategies; patient engagement; sociodemographics; timeline; tool

Project Summary Unhealthy diet is a key behavioral risk factor for several chronic diseases, particularly type-2 diabetes, cardiovascular disease, and some cancers. Long-term measures of diet are typically self-reported and subject to known sources of error and bias. A recognized population-level determinant of diet is access to and use of food retailing, particularly consuming food away from home (FAFH) from quick-service or “fast food” outlets. Currently, there are few methods to objectively measure long-term patterns of FAFH in health research or to understand how built environments shape these behaviors. However, the pervasive use of smartphones provides an emerging opportunity to address these questions. We will use Google Location History Timeline (GTL) data, which includes high-resolution geographic location data collected passively on smartphones with Google Apps, to develop new measures of long-term patterns of food retailer utilization, especially use of FAFH outlets. We will use data from 500 adults from the Washington State Twin Registry who are contributing their GTL data for another NIH-funded study on built environments and active travel (R21 ES031226-01A1). These data include daily time-activity patterns from 2012 to present. We will evaluate these measures against objective measures of contemporaneous food outlet utilization and detailed dietary intake measures in a subset of twins who have previously completed additional surveys, including food frequency questionnaires and travel diaries. Finally, we will measure how metrics of FAFH use relate to health outcomes, particularly weight status, weight change, and self-rated overall health, both cross-sectionally and longitudinally. New measures of food access behaviors associated with diet and health outcomes can be used in epidemiological research and advance the field of built environment influences on human health.

项目摘要 不健康的饮食是几种慢性疾病的关键行为风险因素，特别是2型糖尿病， 心血管疾病和一些癌症。长期的饮食测量通常是自我报告的， 错误和偏见的来源。一个公认的人口水平的饮食决定因素是获得和使用 食品零售业，特别是从快餐店或“快餐”店消费食品。 目前，在健康研究中，很少有方法客观地测量FAFH的长期模式， 了解建筑环境如何塑造这些行为。然而，智能手机的普及提供了 一个解决这些问题的新机会。我们将使用Google位置历史时间轴（GTL）数据， 其中包括在智能手机上通过Google Apps被动收集的高分辨率地理位置数据， 制定新的措施，长期模式的食品零售商的利用，特别是使用FAFH网点。我们 将使用来自华盛顿州双胞胎登记处的500名成年人的数据，这些人将他们的GTL数据贡献给 另一项由NIH资助的关于建筑环境和主动旅行的研究（R21 ES 031226 - 01 A1）。这些数据包括 2012年至今的日常时间活动模式。我们将根据客观标准评估这些措施 在一组双胞胎中， 以前完成的额外调查，包括食物频率问卷和旅行日记。最后我们 将衡量FAFH使用的指标与健康结果的关系，特别是体重状况、体重变化， 自我评定的整体健康状况，包括横截面和纵向。食品获取行为的新措施 与饮食和健康结果相关的研究可以用于流行病学研究，并推进建筑领域 环境对人类健康的影响。