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

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 ass...

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Autores principales: Winters, Meghan, Teschke, Kay, Brauer, Michael, Fuller, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751700/
https://www.ncbi.nlm.nih.gov/pubmed/26867585
http://dx.doi.org/10.1186/s12966-016-0339-0
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author Winters, Meghan
Teschke, Kay
Brauer, Michael
Fuller, Daniel
author_facet Winters, Meghan
Teschke, Kay
Brauer, Michael
Fuller, Daniel
author_sort Winters, Meghan
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12966-016-0339-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-47517002016-02-13 Bike Score®: Associations between urban bikeability and cycling behavior in 24 cities Winters, Meghan Teschke, Kay Brauer, Michael Fuller, Daniel Int J Behav Nutr Phys Act Research 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12966-016-0339-0) contains supplementary material, which is available to authorized users. BioMed Central 2016-02-11 /pmc/articles/PMC4751700/ /pubmed/26867585 http://dx.doi.org/10.1186/s12966-016-0339-0 Text en © Winters et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Winters, Meghan
Teschke, Kay
Brauer, Michael
Fuller, Daniel
Bike Score®: Associations between urban bikeability and cycling behavior in 24 cities
title Bike Score®: Associations between urban bikeability and cycling behavior in 24 cities
title_full Bike Score®: Associations between urban bikeability and cycling behavior in 24 cities
title_fullStr Bike Score®: Associations between urban bikeability and cycling behavior in 24 cities
title_full_unstemmed Bike Score®: Associations between urban bikeability and cycling behavior in 24 cities
title_short Bike Score®: Associations between urban bikeability and cycling behavior in 24 cities
title_sort bike score®: associations between urban bikeability and cycling behavior in 24 cities
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751700/
https://www.ncbi.nlm.nih.gov/pubmed/26867585
http://dx.doi.org/10.1186/s12966-016-0339-0
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