Impact of the Built Environment on Active Travel: A Longitudinal Study of 12 U.S. Metropolitan Areas

摘要

Background: Increasing walking and bicycling rates is a common goal for cities to improve community health through physical activity and reduced emissions. Previous studies employed bicycle and pedestrian traffic count data to model spatial patterns of active travel; however, temporal trends have rarely been included in these studies since longitudinal traffic counts do not exist in most jurisdictions. We aim to address this limitation by examining the temporal trends and spatial patterns of active travel in 12 US metropolitan areas (MSA) across 12 years. Methods: We processed pedestrian and bicycle traffic count data from 2004 to 2016 (n=4,773 count locations; 12,832 observations) in the 12 MSAs. At each count location, we tabulated transportation, land use, and socio-demographic variables at three buffer sizes (300m, 500m, and 750m). We used two-level mixed-effect models to examine the multi-year trend and spatial patterns in bicycling and walking during morning and afternoon peak periods. Results: Our models suggest that active travel increased at a rate of 1-6% (bicycle) and 2-3% (pedestrian) per year. Built environment features were significant across models. Close proximity to university campuses, green space, water, and high density employment areas had a positive impact on active travel. The presence of bicycle facilities (e.g., bicycle lanes; off-street trails) were positively associated with higher levels of bicycle traffic. Inclusion of interaction terms suggests that locations with an off-street bicycle facility had a higher rate of increase in bicycle traffic over time. Conclusions: Our study provides evidence for the role of the built environment and transportation network in promoting active travel to increase physical activity and reduce emissions. Health researchers and practitioners could use our model results to quantify health impacts associated with how changes in the built environment and infrastructure influence rates of active travel.