The project examines the complex relationships between human mobility patterns, individual exposures to environmental stressors, neighborhood quality, and individual health. It seeks to understand how the neighborhoods people live in and visit in their daily life affect their health and wellbeing through comparative studies of several cities in China and the U.S., including Beijing, Shanghai, Guangzhou, and Chicago. It focuses on the noise and air quality that people are exposed to over their whole day – not just at their residence, but also as they undertake their daily activities (e.g., travel to work and pick up kids from school). Data have been collected in both cities using surveys, GPS-equipped mobile phones, and portable noise and air pollutant sensors. The project will provide insight into the complex interactions between environmental influences (e.g., air pollutants and noise), human mobility, and individual health. It helps build greater community knowledge of noise and air pollutants, empower the participants and their communities with such knowledge, promote policy changes, and improve urban environments and health outcomes.

Because human health is influenced by both genetic and non-genetic factors, we study the environment interacting with the genome to influence individual health. The exposome comprises aspects of the built environment (characteristics of where we live), the social environment (with whom we interact, social networks and income); the physicochemical environment (chemical substances we are exposed to) and the lifestyle/food environment (what we eat, how much we exercise). 

It is very important that research can be replicated, because it means that other researchers can test the findings of the research and give readers confidence in research. In order for the replicability of scientific research, sharing research data are is necessary. Given the uniquity of geospatial data, this research develops the GVDE, which is an integrated approach for accessing, sharing, and building on research involving confidential geospatial data. It allows researchers to access and analyze geo-referenced data while protecting the confidentiality of subjects.