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.
