Citation

Winters M, Teschke K, Brauer M, Fuller D. Int. J. Behav. Nutr. Phys. Act. 2016; 13(1): 18.

Affiliation

Department of Community Health and Epidemiology, University of Saskatchewan, Health Science Building, 107 Wiggins Road, Saskatoon, Saskatchewan, S7N 5E5, Canada. daniel.fuller@usask.ca.

Copyright

(Copyright © 2016, Holtzbrinck Springer Nature Publishing Group - BMC)

DOI

10.1186/s12966-016-0339-0

PMID

26867585

PMCID

PMC4751700

Abstract

BACKGROUND: There 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.

METHODS: We 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.

RESULTS: At 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 %.

CONCLUSIONS: The Bike Score metric was associated bicycle mode share between and within cities, suggesting its utility for planning bicycle infrastructure.

Language: en