Bike Score®: Associations between urban bikeability and cycling behavior in 24 cities

International Journal of Behavioral Nutrition and Physical Activity

Research

Daniel Fuller¹  Meghan Winters²  Kay Teschke³  Michael Brauer³ 

[1] Department of Community Health and Epidemiology, University of Saskatchewan, Health Science Building, 107 Wiggins Road, S7N 5E5, Saskatoon, Saskatchewan, Canada;Faculty of Health Sciences, Simon Fraser University, Blusson Hall Rm 11522, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada;School of Population and Public Health, University of British Columbia, 2206 East Mall, V6T 1Z3, Vancouver, BC, Canada;

关键词: Active transport;    Cycling;    Built environment;    Multi-level modeling;    Bike Score;   

DOI  :  10.1186/s12966-016-0339-0

 received in 2015-08-12, accepted in 2016-01-30,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundThere is growing interest in designing cities that support not only walking, but also cycling. Bike Score® is a metric capturing environmental characteristics associated with cycling that is now available for over 160 US and Canadian cities. Our aim was to determine if Bike Score was associated with between and within-city variability in cycling behavior.MethodsWe used linear regression to model associations between Bike Score and journey to work cycling mode share (US: American Community Survey, 2013 or 2012 5-year estimates; Canada: 2011 National Household Survey) for 5664 census tracts in 24 US and Canadian cities.ResultsAt the city level, the correlation between mean Bike Score and mean journey to work cycling mode share was moderate (r = 0.52). At the census tract level, the correlation was 0.35; a ten-unit increase in Bike Score was associated with a 0.5 % (95 % CI: 0.5 to 0.6) increase in the proportion of population cycling to work, a meaningful difference given the low modal shares (mean = 1.9 %) in many North American cities. Census tracts with the highest Bike Scores (>90 to 100) had mode shares 4.0 % higher (β = 4.0, 95 % CI: 2.9 to 5.0) than the lowest Bike Score areas (0–25). City specific analyses indicated between-city variability in associations, with regression estimates between Bike Score and mode share ranging from 0.2 to 3.5 %.ConclusionsThe Bike Score metric was associated bicycle mode share between and within cities, suggesting its utility for planning bicycle infrastructure.

【 授权许可】

CC BY   
© Winters et al. 2016