Chia-Yuan Yu1. 1. Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station, TX, USA.
Abstract
OBJECTIVE: The present study investigates the influence of income, ethnicity, and built environmental characteristics on the percentages of workers who walk/bike as well as on pedestrian/cyclist crash rates. Furthermore, income and ethnicity disparities are also explored. METHODS: This study chose 162 census tracts in Austin as the unit of analysis. To explore income and ethnicity differences in built environments, this study examined the associations of the poverty rate, the percentage of white population, and the percentage of Hispanic population to each built environmental variable. Path models were applied to examine environmental supports of walking/biking and pedestrian/cyclist safety. RESULTS: Areas with high poverty rates had more biking trips and experienced more cyclist crashes, while areas with a high percentage of white population generated more walking trips and fewer pedestrian crashes. Sidewalk completeness and mixed land uses promoted walking to work but increased the crash risk for pedestrians as well. In terms of biking behaviors, road density and transit stop density both increased biking trips and cyclist crashes. CONCLUSIONS: Environmental designs that both encourage walking/biking trips and generate more safety threats should attract more attention from policy makers. Policies should also be more devoted to enhancing the mobility and health for areas with high poverty rates.
OBJECTIVE: The present study investigates the influence of income, ethnicity, and built environmental characteristics on the percentages of workers who walk/bike as well as on pedestrian/cyclist crash rates. Furthermore, income and ethnicity disparities are also explored. METHODS: This study chose 162 census tracts in Austin as the unit of analysis. To explore income and ethnicity differences in built environments, this study examined the associations of the poverty rate, the percentage of white population, and the percentage of Hispanic population to each built environmental variable. Path models were applied to examine environmental supports of walking/biking and pedestrian/cyclist safety. RESULTS: Areas with high poverty rates had more biking trips and experienced more cyclist crashes, while areas with a high percentage of white population generated more walking trips and fewer pedestrian crashes. Sidewalk completeness and mixed land uses promoted walking to work but increased the crash risk for pedestrians as well. In terms of biking behaviors, road density and transit stop density both increased biking trips and cyclist crashes. CONCLUSIONS: Environmental designs that both encourage walking/biking trips and generate more safety threats should attract more attention from policy makers. Policies should also be more devoted to enhancing the mobility and health for areas with high poverty rates.
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