PI: Edmund Seto and Glen Duncan
Project number: 5R21ES024715
Project dates: 3/1/2015–2/28/2017
This research addresses the mission of the National Institutes of Environmental Health Sciences by increasing our understanding of how the environment influences human health through validation of a new wearable device that measures multiple environmental toxicants in real-time and space, called the Portable University of Washington Particle Monitor (PUWPM), and application in a genetically informed sample of adult twins from the community-based UW Twin Registry (UWTR). The use of twins is unique in environment-based research because it will allow us to assess the associations between environmental exposures and health outcomes while controlling for genetic and shared environmental (familial) influences that might otherwise introduce selection biases into the choice of living environments that contribute to differential levels of exposures, and thus confound similar studies in unrelated individuals. Furthermore, our innovative methods will allow us to link environmental exposures with accelerometer and GPS-based measures of movement through space. Using GIS, we will capture spatially continuous variables relevant to the built environment at the same scale as the exposures and movement patterns.
In the first phase the study (R21 phase), the design-feedback iterative cycle will be used to assess the feasibility and usability of the integrated PUWP monitor to assess multiple aspects of behavior and toxic exposures in 15 pairs of twins. Based on qualitative data obtained from focus groups and quantitative data from usability surveys, we will improve the design and ease of use of the PUWP through 2 or 3 iterative cycles. Concurrently, the validity of the PUWP will be established in these same 15 pairs compared to gold standard methods.
In the second phase of the study (R33 phase), we will collect clinical measures including blood pressure, body mass index, waist circumference, and lung function (spirometry), as well as biologic measures including inflammatory cytokines and cortisol in a larger sample of 150 twin pairs. Using these measures, we will first compare associations between clinical/biological outcomes with PM 2.5 measures from the PUWP against their associations with exposure estimates based on ambient air quality models that are standard in the field. Next, we will determine the associations among air pollution, noise, and other environmental exposures from the integrated PUWP system, lifestyle behaviors including physical activity and diet, and psychosocial stress with the various clinical and biologic outcomes. Ultimately, our unique sample and methods will lead to new and important insights linking environmental, behavioral, and genetic aspects of chronic disease.