Changes in Environmental Exposures in Two Randomized Control Weight Loss Trials for Women at Risk of Breast Cancer

Authors: Marta Jankowska*, University of California San Diego, Nana Luo, University of California San Diego, Tarik Benmarhnia, University of California San Diego, Atsushi Nara, San Diego State University, Loki Natarajan, University of California San Diego, Dorothy Sears, University of California San Diego, Jiue-An Yang, University of California San Diego, Steven Zamora, University of California San Diego
Topics: Medical and Health Geography, Spatial Analysis & Modeling, Temporal GIS
Keywords: dynamic exposure; GPS; cancer; built environment; randomized control trial
Session Type: Virtual Paper
Day: 4/10/2021
Start / End Time: 11:10 AM / 12:25 PM
Room: Virtual 8
Presentation File: No File Uploaded


Ecological models posit that disease risk health behaviors are impacted by individual, interpersonal and environmental factors. Most evidence to support these theories remains cross sectional and providing causal evidence for improving environmental policies remains challenging. Stronger causal evidence can be generated with randomized control trials that include environmental exposure data at several timepoints. In this study we take advantage of two existing and successful weight loss trials in women at increased risk for breast cancer to test if intervention participants engaged in behaviors that result in increased daily exposure to healthy food, green space, walkability, and cleaner air environments than controls. Two trials completed in 2015 were pooled together to create a data set of 578 women with 7,395 days of objective accelerometer and global positioning system (GPS) data across two timepoints (baseline and 6-month follow up). Mean weight loss in the intervention groups was 7.5kg and there was an increase in physical activity of up to 135 minutes per week. Exposure at baseline to four built environment features – healthy food, green space, walkability, and air pollution – was calculated using GPS data with kernel density estimation and compared to exposure at 6-month follow up in the intervention and control groups. Linear mixed effects models with each daily GPS derived exposure at baseline and 6 months with random subject-specific intercepts to account for hierarchical design will be performed. We hypothesize that intervention participants will engage in behaviors that result in greater changes in daily exposure to health promoting environment.

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