Tyler Mason, MD

Understanding the effects of air pollution exposure on obesogenic and cardio-metabolic outcomes has been an important research focus of the USC Preventive Medicine department. Recent advances in mobile phone and geolocation tracking technologies have created opportunities for environmental health researchers to capture real-time relevant geospatial contexts of air pollution exposure and investigate their interactive effects on biobehavioral responses on a within-daily or daily basis. Despite these advances, several methodological challenges remain in processing raw GPs data and defining the temporal and spatial parameters of interest for generating the relevant geospatial contexts, before they can be linked it to environmental exposures and health outcomes to study their covariations.

Our application proposes to develop a novel geospatial context construction toolkit to facilitate and streamline the GPS data processing, contextual neighborhood generation and built/social environment contexts extraction processes using high spatiotemporal-resolved data from a study of air pollution, stress and obesity as a use case. Our ArcGIS and R based toolkit will be applicable for use in a variety of environmental health investigations collecting time-resolved GPS data and can be extended to other environmental exposures (e.g., noise, UV radiation) and outcomes (e.g., asthma symptoms). Also, our toolkit can be utilized to conduct research that will inform future ecological momentary and just-in-time adaptive interventions, which are intervention frameworks that can use information about momentary environment exposures and mobility patterns to provide targeted intervention material at the times and locations it is most needed. At the end of the CTSI project period, we will apply for NIH R01 funding to extend our methodological framework to large-scale environmental health and epidemiological studies with bigger datasets in real studies to answer research questions.