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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 2.

Unadjusted conditional logistic regression models predicting bicycle crashes at intersections, Iowa, 2007-2010, N=294.

Predictor of bicycle crash Unadjusted OR 95% CI
On-road bicycle facility present (ref=none) 0.58 0.23-1.48
On-road bicycle facility type (ref=none)
 Pavement markings (bicycle lane or shared lane arrows) 0.42 0.10-1.80
 Bicycle-specific signage 1.14 0.30-4.33
 Pavement markings & signage 0.20 0.02-1.93
Sidewalks, index streeta,b (ref=none)
 Full 2.53 1.01-6.35
 Partial 1.78 0.71-4.44
Sidewalks, non-index streetc,d (ref=none)
 Full 1.57 0.62-3.95
 Partial 1.03 0.38-2.79
Traffic controls present, index streeta (ref=no) 1.36 0.63-2.97
Traffic controls present, non-index streetb (ref=no) 2.75 1.22-6.18
Bicycle volume (per 5) 1.09 0.76-1.56
Motor vehicle volume (per 5) 1.04 1.01-1.07
Curb to curb width (per 10ft) 1.48 1.15-1.91
Speed limit, index streeta (per 5mph) 0.94 0.60-1.48
Speed limit, non-index streetb (per 5mph) 0.89 0.49-1.63

Ref=reference

a

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

b

Cochran-Armitage trend test p=0.13

c

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

d

Cochran-Armitage trend test p=0.48