Who rides and who is left behind: a multilevel analysis of new cycling infrastructure use in three Canadian cities
Year: 2026
Type: article
Study design: Observational Study
Abstract: Despite ongoing expansions of cycling infrastructure in cities across the western world, few studies have examined how people engage with multiple new cycling facilities across cities. Using an online travel survey (n = 2,690) in Vancouver, Toronto, and Montréal linked to 46 cycling facilities built between 2020 and 2022, we assess how residential proximity shapes the probability of using these facilities, and together with proximity, how the attributes of facilities as well as individual sociodemographic characteristics associate with use, including differences across gender and income. Logistic and Bayesian cross-classified multilevel models show strong distance decay that each additional kilometre is associated with 24% lower odds of use. Distance decay is steeper for lower-income riders and for women and gender-diverse respondents than for higher-income riders and men, indicating that proximity is a stronger barrier for groups historically underrepresented in cycling. Odds of use are lower for older adults, women and gender-diverse respondents; higher for non-single households, newcomers, and those working from home less frequently. New facilities with network connectivity of multiple nodes see higher use. The odds of use is higher in urban than suburban areas for middle-income respondents. Among higher-income respondents, protected cycle tracks are linked to greater use, whereas more nearby existing cycling infrastructure within 1 km is correlated with lower use, suggesting substitution in infrastructure-mature contexts. Findings suggest that comparable amount of new infrastructure may not translate into comparable usage across populations. Accounting for proximity, facility attributes, and sociodemographic differences can support more equitable, demand-responsive infrastructure planning.
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,270
Award: G4784418763
OpenAlex ID: W7166549886
