Integrating novel GIS and GPS data to assess the impact of built environments on changes in BMI, physical activity and cancer-related biomarkers in two successful weight loss interventions in women at

整合新颖的 GIS 和 GPS 数据，评估建筑环境对 BMI、体力活动和癌症相关生物标志物变化的影响，在两项成功的女性减肥干预措施中

• 批准号: 10378748
• 负责人: Tarik Benmarhnia
• 金额: $ 39.15万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-09 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10378748
• 关键词: Accelerometer; Address; Advocacy; Affect; Age; Aging; Air Pollution; Automobile Driving; Behavior; Behavioral; Big Data Methods; Biological Markers; Body Weight decreased; Body mass index; Breast Cancer Risk Factor; Breast Cancer survivor; Businesses; Cancer Center; Cancer Patient; Cancer Survivor; Centers for Disease Control and Prevention (U.S.); Cessation of life; Characteristics; Cluster Analysis; Communities; Cues; Data; Data Analyses; Elderly; Environment; Environmental Exposure; Environmental Risk Factor; Exposure to; Food; Funding; Future; Glucose; Goals; Government; Green space; Health; Health Food; Home; Home environment; Individual; Inflammation; Insulin; Intervention; Learning; Malignant Neoplasms; Measurement; Measures; Methods; Modeling; Monte Carlo Method; Movement; National Institute of Environmental Health Sciences; Neighborhoods; Obesity; Outcome; Oxidative Stress; Pathway interactions; Pattern; Physical activity; Policies; Pollution; Population; Population Group; Psychosocial Factor; Recording of previous events; Research; Resources; Risk; Sampling; Source; Standardization; Surgeon; Surveys; Techniques; Technology; Testing; Time; Transportation; Vitamin D; Walking; Woman; active lifestyle; adaptive intervention; base; behavior change; behavior influence; built environment; cancer biomarkers; cancer prevention; cancer risk; connected care; demographics; design; environmental change; food environment; frailty; hospital readmission; improved; intervention participants; lifestyle intervention; mHealth; malignant breast neoplasm; mortality; multilevel analysis; novel; personalized approach; personalized medicine; prediction algorithm; predictive modeling; prevent; programs; remote location; social media; unsupervised learning; walkability; weight loss intervention

In 2018, 266,120 new cases of invasive breast cancer are expected. The Breast Cancer and Environment Research Program, funded by NIEHS and NCI, identified a need to better understand environmental exposures to inform cancer prevention efforts. Further, Just in Time Adaptive Interventions (JITAIs) employ temporal and spatial cues to prompt behavior change, but little is known about spatial predictors of behaviors at the minute level and beyond home neighborhoods. Two successful weight loss trials in women at risk for breast cancer, conducted in harmony under the NCI-funded Transdisciplinary Research and Energetics in Cancer Center, offer a unique opportunity to examine the health impacts of changing environmental exposures in a heterogeneous sample. One trial focused on older breast cancer survivors, the other on women across the age range at increased breast cancer risk due to their obesity status. The studies included numerous identical measures at baseline and 6 months, including biomarkers, GPS and accelerometer measurements, and perceived environment surveys. We propose to investigate the relationship between minute level objective GIS measured walkability, greenspace, pollution and food environments and changes in BMI, physical activity (PA), and cancer related biomarkers. Few studies have assessed the impact of the built environment on weight loss interventions using objective daily measures, and none included biomarkers of cancer risk. Further, no studies have employed novel GPS measures of total environment exposure that can change as behaviors change in an intervention. Assessing the effects of built environments on intervention outcomes and investigating changes in exposure over time will provide more causal evidence to inform the policy agenda. Most data on built environment and health are cross sectional. We need longitudinal, causal evidence to support policy changes in urban design that will have lasting impact on large population groups and those at risk, recommended by the WHO, IOM and CDC. In addition, we will use estimates of exposure change from the current study to simulate the potential impact of JITAIs and to identify decision points, decision rules and tailoring variables for future interventions. The current study will geocode each GPS coordinate (42 million), integrate built environment data on walkability, greenspace, pollution and food environments in GIS using validated integrated data analysis techniques, and investigate whether the environment influences changes in biomarkers, BMI and PA. The Ecological model posits that factors at the individual, interpersonal, and community level can influence behavior and health. These analyses will assess the multi-level predictors, while adjusting for interpersonal and individual covariates. Results will be disseminated to existing community partners from cancer, aging and transportation planning to inform local advocacy efforts. This study will also inform future RCTs controlling for individual and environmental predictors at baseline and inform JITAIs by developing and testing minute level spatial, temporal and behavioral rules.

2018年，预计将有266,120例新发浸润性乳腺癌病例。乳腺癌与环境 由 NIEHS 和 NCI 资助的研究计划确定了需要更好地了解环境 暴露为癌症预防工作提供信息。此外，及时适应性干预 (JITAI) 采用 促进行为改变的时间和空间线索，但对行为的空间预测因素知之甚少 在分钟级别并超越家庭社区。两项针对有以下风险的女性的成功减肥试验 乳腺癌，在 NCI 资助的跨学科研究和能量学下协调进行 癌症中心提供了一个独特的机会来检查不断变化的环境暴露对健康的影响 在异质样本中。一项试验针对的是老年乳腺癌幸存者，另一项试验针对的是女性 由于肥胖状况而导致乳腺癌风险增加的年龄范围。这些研究包括许多 基线和 6 个月的测量结果相同，包括生物标记、GPS 和加速计测量， 和感知环境调查。我们建议研究分钟级目标之间的关系 GIS 测量了步行适宜性、绿地、污染和食物环境以及 BMI、体力活动的变化 （PA）和癌症相关的生物标志物。很少有研究评估建筑环境对体重的影响 使用客观的日常测量进行损失干预，但没有一项包括癌症风险的生物标志物。此外，不 研究采用了新的 GPS 测量方法来测量总体环境暴露情况，这种测量方法会随着行为的变化而改变 干预措施的改变。评估建筑环境对干预结果的影响和 调查暴露随时间的变化将为政策议程提供更多因果证据。 大多数关于建筑环境和健康的数据都是横截面的。我们需要纵向的因果证据 支持城市设计方面的政策变化，这将对大量人口群体和居住在城市中的人口产生持久影响。 世界卫生组织、国际移民组织和疾病预防控制中心推荐的风险。此外，我们将使用对暴露变化的估计 当前的研究旨在模拟 JITAI 的潜在影响并确定决策点、决策规则和 为未来的干预措施定制变量。当前的研究将对每个 GPS 坐标（4200 万）进行地理编码， 使用 GIS 将步行性、绿地、污染和食品环境的建筑环境数据集成到 GIS 中 验证综合数据分析技术，并调查环境是否影响变化 生物标志物、BMI 和 PA。生态模型假设个体、人际和 社区水平可以影响行为和健康。这些分析将评估多级预测变量，同时 调整人际关系和个人协变量。结果将传播给现有社区 来自癌症、老龄化和交通规划领域的合作伙伴为当地的宣传工作提供信息。这项研究还将 为未来控制个人和环境预测因子的随机对照试验提供信息，并通过以下方式向 JITAI 提供信息： 开发和测试分钟级的空间、时间和行为规则。