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: 10617201
• 负责人: Tarik Benmarhnia
• 金额: $ 44.67万
• 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/10617201
• 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; Cessation of life; Characteristics; Cluster Analysis; Communities; Cues; Data; Data Analyses; Disparity; Elderly; Environment; Environmental Exposure; Environmental Risk Factor; Equity; Exposure to; Food; Funding; Future; Glucose; Goals; Government; Green space; Health; Health Food; Home; Home environment; Individual; Individual Adjustment; 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; Recommendation; 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; behavior change; behavior influence; behavior prediction; built environment; cancer biomarkers; cancer prevention; cancer risk; connected care; data integration; demographics; design; environmental change; food environment; frailty; health assessment; 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 group; 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266120例浸润性乳腺癌新发病例。乳腺癌和环境