1
|
Garber MD, Watkins KE, Flanders WD, Kramer MR, Lobelo RF, Mooney SJ, Ederer DJ, McCullough LE. Bicycle infrastructure and the incidence rate of crashes with cars: A case-control study with Strava data in Atlanta. JOURNAL OF TRANSPORT & HEALTH 2023; 32:101669. [PMID: 38196814 PMCID: PMC10773466 DOI: 10.1016/j.jth.2023.101669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Introduction Bicycling has individual and collective health benefits. Safety concerns are a deterrent to bicycling. Incomplete data on bicycling volumes has limited epidemiologic research investigating safety impacts of bicycle infrastructure, such as protected bike lanes. Methods In this case-control study, set in Atlanta, Georgia, USA between 2016-10-01 and 2018-08-31, we estimated the incidence rate of police-reported crashes between bicyclists and motor vehicles (n = 124) on several types of infrastructure (off-street paved trails, protected bike lanes, buffered bike lanes, conventional bike lanes, and sharrows) per distance ridden and per intersection entered. To estimate underlying bicycling (the control series), we used a sample of high-resolution bicycling data from Strava, an app, combined with data from 15 on-the-ground bicycle counters to adjust for possible selection bias in the Strava data. We used model-based standardization to estimate effects of treatment on the treated. Results After adjustment for selection bias and confounding, estimated ratio effects on segments (excluding intersections) with protected bike lanes (incidence rate ratio [IRR] = 0.5 [95% confidence interval: 0.0, 2.5]) and buffered bike lanes (IRR = 0 [0,0]) were below 1, but were above 1 on conventional bike lanes (IRR = 2.8 [1.2, 6.0]) and near null on sharrows (IRR = 1.1 [0.2, 2.9]). Per intersection entry, estimated ratio effects were above 1 for entries originating from protected bike lanes (incidence proportion ratio [IPR] = 3.0 [0.0, 10.8]), buffered bike lanes (IPR = 16.2 [0.0, 53.1]), and conventional bike lanes (IPR = 3.2 [1.8, 6.0]), and were near 1 and below 1, respectively, for those originating from sharrows (IPR = 0.9 [0.2, 2.1]) and off-street paved trails (IPR = 0.7 [0.0, 2.9]). Conclusions Protected bike lanes and buffered bike lanes had estimated protective effects on segments between intersections but estimated harmful effects at intersections. Conventional bike lanes had estimated harmful effects along segments and at intersections.
Collapse
Affiliation(s)
- Michael D. Garber
- Department of Epidemiology, Rollins School of Public
Health, Emory University, Atlanta, GA, USA
- Department of Environmental and Radiological Health
Sciences, Colorado State University, Fort Collins, CO, USA
- Herbert Wertheim School of Public Health and Human
Longevity Science & Scripps Institution of Oceanography, UC San Diego, San
Diego, CA, USA
| | - Kari E. Watkins
- Civil and Environmental Engineering, University of
California, Davis, Davis, CA, USA
| | - W. Dana Flanders
- Department of Epidemiology, Rollins School of Public
Health, Emory University, Atlanta, GA, USA
- Department of Biostatistics and Bioinformatics, Rollins
School of Public Health, Emory University, Atlanta, GA, USA
| | - Michael R. Kramer
- Department of Epidemiology, Rollins School of Public
Health, Emory University, Atlanta, GA, USA
| | - R.L. Felipe Lobelo
- Hubert Department of Global Health, Rollins School of
Public Health, Emory University, Atlanta, GA, USA
| | - Stephen J. Mooney
- Department of Epidemiology, University of Washington School
of Public Health, USA
- Harborview Injury Prevention & Research Center,
University of Washington, Seattle, WA, USA
| | - David J. Ederer
- Civil and Environmental Engineering, Georgia Institute of
Technology, Atlanta, GA, USA
| | - Lauren E. McCullough
- Department of Epidemiology, Rollins School of Public
Health, Emory University, Atlanta, GA, USA
| |
Collapse
|
2
|
Garber MD, Flanders WD, Watkins KE, Lobelo RF, Kramer MR, McCullough LE. Have Paved Trails and Protected Bike Lanes Led to More Bicycling in Atlanta?: A Generalized Synthetic-Control Analysis. Epidemiology 2022; 33:493-504. [PMID: 35439778 PMCID: PMC9211442 DOI: 10.1097/ede.0000000000001483] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
BACKGROUND Bicycling is an important form of physical activity in populations. Research assessing the effect of infrastructure on bicycling with high-resolution smartphone data is emerging in several places, but it remains limited in low-bicycling US settings, including the Southeastern US. The Atlanta area has been expanding its bicycle infrastructure, including off-street paved trails such as the Atlanta BeltLine and some protected bike lanes. METHODS Using the generalized synthetic-control method, we estimated effects of five groups of off-street paved trails and protected bike lanes on bicycle ridership in their corresponding areas. To measure bicycling, we used 2 years (October 1, 2016 to September 30, 2018) of monthly Strava data in Atlanta's urban core along with data from 15 on-the-ground counters to adjust for spatiotemporal variation in app use. RESULTS Considering all infrastructure as one joint intervention, an estimated 1.10 (95% confidence interval [CI]: 0.99, 1.18) times more bicycle-distance was ridden than would have been expected in the same areas had the infrastructure not been built, when defining treatment areas by the narrower of two definitions (defined in text). The Atlanta BeltLine Westside Trail and Proctor Creek Greenway had especially strong effect estimates, e.g., ratios of 1.45 (95% CI: 1.12, 1.86) and 1.55 (1.10, 2.14) under each treatment-area definition, respectively. We estimated that other infrastructure had weaker positive or no effects on bicycle-distance ridden. CONCLUSIONS This study advances research on the topic because of its setting in the US Southeast, simultaneous assessment of several infrastructure groups, and data-driven approach to estimating effects. See video abstract at, http://links.lww.com/EDE/B936.
Collapse
Affiliation(s)
- Michael D. Garber
- Department of Epidemiology, Rollins School of Public
Health, Emory University, Atlanta, GA
| | - W. Dana Flanders
- Department of Epidemiology, Rollins School of Public
Health, Emory University, Atlanta, GA
- Department of Biostatistics and Bioinformatics, Rollins
School of Public Health, Emory University, Atlanta, GA
| | - Kari E. Watkins
- School of Civil and Environmental Engineering, Georgia
Institute of Technology, Atlanta, GA
| | - R.L. Felipe Lobelo
- Hubert Department of Global Health, Rollins School of
Public Health, Emory University, Atlanta, GA
| | - Michael R. Kramer
- Department of Epidemiology, Rollins School of Public
Health, Emory University, Atlanta, GA
| | - Lauren E. McCullough
- Department of Epidemiology, Rollins School of Public
Health, Emory University, Atlanta, GA
| |
Collapse
|