PI: Glen Duncan
Project Number: 7R01AG042176
Project Dates: 9/30/2011–5/31/2016
The goal of this research is to determine how the built environment in which individuals live, work, and play in on a daily basis influences their lifestyle behaviors and health. We couple advanced methods in geospatial data management and analysis with cutting-edge technology, the multisensor board (MSB), to gather objective information about the built environment and lifestyle behaviors in real time and space. The MSB is a small wearable device with multiple sensing capabilities, including accelerometry, barometric pressure, and location, connected wirelessly to a WiFi enabled mobile telephone. Outdoor and indoor activities are monitored using GPS and WiFi signals to obtain data with high spatial resolution. The mobile phone has been adapted for use as an automated food intake program. We will use this integrated tool in a study of environmental influences on lifestyle behaviors and health in a community-based sample of adult monozygotic twins who were reared together but now live apart.
With these tools and methods, we will create a unique and rich dataset linking rigorous measures of physical activity and eating in real time and space relative to locations in the built environment. This approach will build upon and extend our knowledge by measuring lifestyle behaviors in continuous time and space within and beyond the individual residential locations (neighborhoods) of twins.
Using a co-twin control design, we will examine monozygotic pairs who live apart and determine how the home built environment influences levels of both walking and total physical activity, free of genetic and familial influences. Next, we will measure and compare location-based activity and eating episodes in real-time to investigate how often the twins use features of their home built environment that are associated with activity and eating. By measuring how many activity and eating episodes occur in the home built environment versus in distal built environments, including work, transit, and recreation-related settings, we will be able to determine whether proximity to features of the home built environment are associated with their use. Finally, we will measure associations among the built environment, lifestyle behaviors, and body mass index in twins who live apart by linking weight status with physical activity levels and food intake to determine if body mass index is associated with the built environment through these behaviors.
Our scientific approach integrates conceptual models from the behavioral and social sciences with biological, computational, and physical measures in a genetically informative research design. This effort lays the critical groundwork to use an existing repository of phenotypic data and biological samples, including DNA, in future research to determine how specific genes interact with the environment to influence behaviors and health. Ultimately, our unique sample and scientific methods will lead to new and important insights linking environmental, behavioral, and genetic aspects of obesity and chronic disease.