Associations between Built Environment, Air Quality, and Quality of Life in Xi’an, China

Abstract

Associations between Built Environment, Air Quality, and Quality of Life in Xi’an, ChinaAbstract Number:2669 Meiling Gao*, Junji Cao, Edmund Seto, and Catherine Koshland Meiling Gao* University of California Berkeley, United States, E-mail Address: [email protected] Search for more papers by this author , Junji Cao Institute for Earth Environment Chinese Academy of Sciences, China, E-mail Address: [email protected] Search for more papers by this author , Edmund Seto University of Washington, United States, E-mail Address: [email protected] Search for more papers by this author , and Catherine Koshland University of California Berkeley, United States, E-mail Address: [email protected] Search for more papers by this author AbstractRapid economic development has led to dramatic changes in the physical environments of Chinese cities as they grow to accommodate a growing population. Changes in the urban environment has important public health implications by affecting how people live, travel, and access goods and services but this process is not well understood. This study examines the associations between built environment characteristics, air quality and quality of life in an urban Chinese population to inform how cities can be designed to promote health. Measures of neighborhood quality and quality of life were collected in a cross-sectional study of 1602 adults in 20 neighborhoods of Xi’an, China in 2013. Self-reported measures using the NEWS-A survey evaluated a neighborhood’s walkability, ease of access, safety, aesthetics and resources. Health-related quality of life using the SF-12 Health Survey included mental (MCS) and physical (PCS) component scales. Objective measures of walkability and accessibility were also assessed using Asian Development Bank’s Walkability survey and geographic information systems methods. Short-term deployments of 19 filter-based (MiniVol) and 34 passive monitors (Ogawa) in the heating and non-heating periods measured ambient PM2.5, NO2, SO2, and O3 concentrations. Using remote sensing, land-use regression, and principal components analysis, exposures to ambient pollution were estimated for the surveyed population. Preliminary analyses using population averaged models suggest self-reported measures of neighborhoods are more closely associated with the two components of health-related quality of life. Improving the pedestrian infrastructure and increasing access to resources within shorter walking distances is significantly associated with increases in both the MCS and PCS across the population.Results from this study can be used to inform how neighborhoods can be redesigned to improve health-related quality of life.