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. Author manuscript; available in PMC: 2022 Jan 24.
Published in final edited form as: Accid Anal Prev. 2013 Jan 18;56:103–109. doi: 10.1016/j.aap.2012.12.031

Table 3.

Predictors of bicycle crashes, multivariable conditional logistic regression, Iowa, 2007-2010, N=294.

Model 1a Model 2b

Characteristic Any Facility Facility Type

Adjusted OR 95% CI Adjusted OR 95% CI
On-road bicycle facility present (ref=none) 0.48 0.18-1.36
On-road bicycle facility type (ref=none)
 Pavement markings (bicycle lane or shared lane arrows) 0.40 0.09-1.82
 Bicycle-specific signage 0.62 0.15-2.58
 Pavement markings & signage 0.36 0.03-4.32
Sidewalks, index street (ref=none) c
 Full 2.60 0.95-7.10 2.65 0.96-7.29
 Partial 1.66 0.61-4.49 1.66 0.61-4.54
Traffic controls present, non-index street (ref=no) d 1.97 0.80-4.84 1.91 0.77-4.73
Bicycle volume (per 5 bicycles) 1.10 0.73-1.66 1.10 0.73-1.67
Motor vehicle volume (per 10 vehicles) 1.02 0.99-1.05 1.02 0.99-1.05
Curb-to-curb width, index street (per 10 feet) c 1.38 1.06-1.79 1.37 1.05-1.79

Ref=reference

a

Model 1 includes: on-road bicycle facility present, sidewalks, traffic controls, bicycle volume, motor vehicle volume, and curb-to-curb width. Likelihood ratio test: Model 1 vs. Univariate model (χ2=23.42, df=6, p<0.001)

b

Model 2 includes: on-road bicycle facility type, sidewalks, traffic controls, bicycle volume, motor vehicle volume, and curb-to-curb width. Likelihood ratio test: Model 2 vs. Univariate model (χ2=21.46, df=6, p=0.002)

c

Index street = street motor vehicle was traveling on when crash occurred

d

Non-index street = street motor vehicle was not traveling on when crash occurred