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Bicycling crash circumstances vary by route type: a cross-sectional analysis Teschke, Kay; Frendo, Theresa; Shen, Hui; Anne Harris, M; Reynolds, Conor C; Cripton, Peter A; Brubacher, Jeff; Cusimano, Michael D; Friedman, Steven M; Hunte, Garth; Monro, Melody; Vernich, Lee; Babul, Shelina; Chipman, Mary; Winters, Meghan Nov 22, 2014

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RESEARCH ARTICLEBicycling crash circumstans25,There is renewed interest in promoting bicycling around this evidence has grown, many cities have begun toTeschke et al. BMC Public Health 2014, 14:1205http://www.biomedcentral.com/1471-2458/14/1205or objects) and falls [12,14,16-19]. There is considerableEast Mall, Vancouver, BC, CanadaFull list of author information is available at the end of the articlethe world – to increase physical activity in the popula-tion, promote city vitality, and reduce traffic congestion,air pollution and greenhouse gases [1]. Evidence showsthat the safety and motivators of utilitarian and leisurecycling are influenced by route infrastructure [2-10].Bike-specific facilities that reduce interactions withmotor vehicle traffic have lower crash risk for cyclistsbuild new facilities that offer dedicated space for cy-clists [1,11]. Crashes may occur on any route type, butthe circumstances (e.g., falls, collisions) may differ.Understanding these differences will help plannersand engineers select and design cycling routes in away that maximizes safety.A number of cycling injury studies have reported crashcircumstances. Most report whether a crash was a colli-sion with a motor vehicle or not [12-18]. Many reportother collisions (e.g., with pedestrians, cyclists, animals,* Correspondence: kay.teschke@ubc.ca1School of Population and Public Health, University of British Columbia, 2206BackgroundAbstractBackground: Widely varying crash circumstances have been reported for bicycling injuries, likely because ofdiffering bicycling populations and environments. We used data from the Bicyclists’ Injuries and the CyclingEnvironment Study in Vancouver and Toronto, Canada, to describe the crash circumstances of people injured whilecycling for utilitarian and leisure purposes. We examined the association of crash circumstances with route type.Methods: Adult cyclists injured and treated in a hospital emergency department described their crashcircumstances. These were classified into major categories (collision vs. fall, motor vehicle involved vs. not) andsubcategories. The distribution of circumstances was tallied for each of 14 route types defined in an earlier analysis.Ratios of observed vs. expected were tallied for each circumstance and route type combination.Results: Of 690 crashes, 683 could be characterized for this analysis. Most (74%) were collisions. Collisions includedthose with motor vehicles (34%), streetcar (tram) or train tracks (14%), other surface features (10%), infrastructure(10%), and pedestrians, cyclists, or animals (6%). The remainder of the crashes were falls (26%), many as a result ofcollision avoidance manoeuvres. Motor vehicles were involved directly or indirectly with 48% of crashes. Crashcircumstances were distributed differently by route type, for example, collisions with motor vehicles, including“doorings”, were overrepresented on major streets with parked cars. Collisions involving streetcar tracks wereoverrepresented on major streets. Collisions involving infrastructure (curbs, posts, bollards, street furniture) wereoverrepresented on multiuse paths and bike paths.Conclusions: These data supplement our previous analyses of relative risks by route type by indicating the types ofcrashes that occur on each route type. This information can guide municipal engineers and planners towardsimprovements that would make cycling safer.Keywords: Bicycling injuries, Bike lanes, Traffic accidents[2-6]. Such facilities also encourage cycling [7-10]. Asa cross-sectional analysisKay Teschke1*, Theresa Frendo1, Hui Shen1, M Anne HarriMichael D Cusimano6, Steven M Friedman7, Garth HunteMary Chipman6 and Meghan Winters9© 2014 Teschke et al.; licensee BioMed CentraCommons Attribution License (http://creativecreproduction in any medium, provided the orDedication waiver (http://creativecommons.orunless otherwise stated.Open Accessces vary by route type:, Conor CO Reynolds3, Peter A Cripton4, Jeff Brubacher5,Melody Monro1, Lee Vernich6, Shelina Babul8,l Ltd. This is an Open Access article distributed under the terms of the Creativeommons.org/licenses/by/4.0), which permits unrestricted use, distribution, andiginal work is properly credited. The Creative Commons Public Domaing/publicdomain/zero/1.0/) applies to the data made available in this article,Teschke et al. BMC Public Health 2014, 14:1205 Page 2 of 10http://www.biomedcentral.com/1471-2458/14/1205variance in the proportions of various crash circum-stances reported from study to study. This may be a re-sult of different cycling infrastructure in the locationsstudied, but this has rarely been investigated or de-scribed [18,20].Differences in crash circumstances may also be relatedto study design, for example the population or mode ofcycling being investigated. Bicycling is a term that repre-sents an array of activities that includes not only cyclingas a mode of utilitarian or leisure travel where safety isdesired and expected, but also as a sport (e.g., road ra-cing, mountain biking, cyclo-cross, BMX, trick riding)where risk-taking is intentional and part of the challenge[21]. Crashes that occur during these very differentactivities are best examined separately. Unfortunatelymost administrative data on bicycling injuries offer twoextremes: a narrow focus on motor vehicle crashes or abreadth that includes all types of cycling together.Transportation data typically only count collisions withmotor vehicles [13,22]. Hospitalization data usually cap-tures all cyclist crashes, including injuries incurred indeliberately risky cycling sports and in utilitarian or leis-ure cycling [15,23]. Studies using primary data collectionmay also mix these [2,16].We previously conducted a study of 690 cyclistsinjured in two of Canada’s largest cities, Torontoand Vancouver: the Bicyclists’ Injuries and the CyclingEnvironment Study [3,4]. Its primary purpose was toexamine the relative risks of cycling injury by route typeand other infrastructure features. Data were collectedfrom cyclists who were injured seriously enough to betreated in a hospital emergency department. We ex-cluded crashes incurred in mountain biking, racing andtrick riding, so the study focused on cycling as a modeof utilitarian and leisure travel using urban transporta-tion infrastructure designed by planners and transportengineers. The relative risk results are outlined in detailelsewhere [3,4], but in brief, we found that injury riskswere highest on major streets with car parking and nobike infrastructure, and were lower on cycle tracks, bikelanes, local streets and bike paths.To understand how the injuries occurred, here we de-scribe elements of the crash circumstances observed inthe study and examine whether the circumstances dif-fered on 14 route types defined in the main study ana-lysis [3].MethodsThe study methods were reviewed and approved by thehuman subjects ethics review boards of the University ofBritish Columbia, the University of Toronto, St. Paul’sHospital, Vancouver General Hospital, St. Michael’sHospital, and the University Health Network (TorontoGeneral Hospital and Toronto Western Hospital). Allparticipants gave written informed consent before takingpart in the study.Study procedures have been described in detail else-where [3,24]; the following is a summary. The studypopulation consisted of adult (≥19 years) residents ofToronto and Vancouver who were injured while riding abicycle in the city and treated within 24 hours in theemergency departments of the hospitals listed abovebetween May 18, 2008 and November 30, 2009. Allhospitals were located in central business districts, andone in each city was a regional trauma centre.Eligible participants were interviewed in person bytrained interviewers, using a structured questionnaire(http://cyclingincities.spph.ubc.ca/files/2011/10/InterviewFormFinal.pdf) as soon as possible after the injury tomaximize recall. Crash circumstances were derived fromparticipants’ answers to the following questions: In your own words, please describe thecircumstances of the injury incident. (responseopen-ended) Was this a collision between you and a motorvehicle, person, animal or object (including holes inthe road)? (response options: yes, no) If yes, what did you collide with? (response options:car, SUV, pick-up truck, or van; motorcycle orscooter; large truck; bus or streetcar; pedestrian;cyclist; animal; other non-motorized wheeledtransport; pot hole or other hole; streetcar or traintrack; other (specify))A classification system for the crash circumstances(Figure 1) was developed based on a review of other sys-tems in the injury literature [12-19] and the range ofresponses to the questions above. Each participant’s an-swers to the questions were reviewed and classified bytwo study investigators (TF, KT), blind to route type.Differences in initial classifications were reviewed andadjudicated (KT).We determined features of the crash site and of a ran-domly selected control site located along the route ofthe trip during which the injury occurred. The probabil-ity that specific route types would be selected as controlswas proportional to their relative lengths on the trips(e.g., on a 4-km trip, there would be a 25% chance ofselecting a control site on a 1-km section that was on abike path). Cumulated over all trips, the control sitesprovide an estimate of study participants’ exposure tothe various route types.Data were collected at every injury and control site viastructured observations by trained personnel blinded tosite status (http://cyclingincities.spph.ubc.ca/files/2011/10/SiteObservationFormFinal.pdf ). These observationswere used to classify the sites into 14 route typesbyTeschke et al. BMC Public Health 2014, 14:1205 Page 3 of 10http://www.biomedcentral.com/1471-2458/14/1205(Figure 2) and provide contextual information such astraffic volumes and speeds [3]. Observations were con-ducted at a time that conformed as closely as possible tothe time of the crash (i.e., season; weekday vs weekend;morning rush, midday, afternoon rush, evening, night).Data analyses were performed using JMP 10 (SASInstitute, Cary, NC) and R (http://www.r-project.org).We tallied the crash circumstances and cross-tabulatedthem with route type. We examined associations be-tween crash circumstances and route type by calculatingthe ratio of observed to expected injury events for eachcrash circumstance and route type combination. Ex-Figure 1 Crash circumstances, stratified by collisions and falls, andpected events were calculated two ways: 1) using the dis-tribution of controls sites (reflecting exposure) by routeFigure 2 Route types where the 683 injury events occurred, stratifiedtype, and 2) using the distribution of injury sites byroute type:Expected1 = all control sites with that route type * allinjury events with that crash circumstance/all injuryeventsExpected2 = all injury sites with that route type * allinjury events with that crash circumstance/all injuryeventsConfidence intervals (95%) for the ratio of observedto expected events were calculated using the R functionmotor vehicle involvement or not.prop.test. Since there were zero injury events for somecircumstances and route types, the commonly usedby broad crash circumstance categories. MV =motor vehicle.normal approximation was not appropriate. Instead, theWilson score with continuity correction was used to obtainthe 95% CI for each proportion [25,26].ResultsThe study recruited 690 injured cyclists (414 in Vancouver,276 in Toronto). Most participants were men (59%), youn-ger than 40 years (62%), well-educated (75% with a post-secondary diploma or degree), employed full time (69%),regular cyclists (88% cycled ≥52 times per year). Most ofthe trips during which the injuries occurred were utilitar-ian in nature (74%), on weekdays (77%), during daylighthours (78%), and short (68% <5 km) [3].Seven of the 690 injured cyclists could not recallenough about their crash to classify it for this analysis.Of the available 683 crashes, 506 were classified ascollisions and 177 as falls. Figure 1 lists 16 detailedcrash circumstance categories, and further stratifiesthem according to whether a motor vehicle was in-volved. Motor vehicles were involved directly in 231(33.8%) collisions, with cars, buses, trucks or vehicledoors. They were also involved indirectly when cycliststook avoidance manoeuvres that resulted in othercollisions or falls (99 additional crashes, 14.5%). Thetop crash circumstances were collisions with cars(22.1% of crashes), streetcar (tram) tracks (14.2%),other surfaces (10.1%), infrastructure (10.1%), vehicledoors (9.2%), and falls to avoid collisions (10.1%).Crashes with other cyclists, pedestrians or animals wererare (total = 5.9%).Figure 2 and Table 1 list the 14 route types where the683 injury events occurred. To describe these routetypes, we measured traffic and speeds. Median motor ve-hicle traffic and median speeds were higher on majorstreets than local streets (~900 vs. 50 vehicles/hour and~40 vs. 30 km/h, respectively). Median bike traffic washighest on cycle tracks (114/h), then bike lanes andmulti-use paths (60-78/h), then shared lanes, local streetbikeways and bike paths (36-48/h), and lowest on streetswith no bike infrastructure (0-24/h).The dominant route types where crashes occurredwere major streets with no bike infrastructure (with orwithout parked cars, 22.5% and 16.4% respectively), resi-dential streets with no bike infrastructure (12.9%), andoff-street multiuse paths (9.1%). Note that the distribu-tion of injury events by route type was influenced bothTable 1 Observed injury events classified by crash circumstance and route typeInjurysitesMotor vehicle(excluding door)MotorvehicledoorPedestrian,cyclist oranimalStreetcar (tram)or train tracksOthersurfaceInfrastructure Fall to avoidcollisionOtherfall683 168 63 40 97 69 69 69 1082-1521412212161Teschke et al. BMC Public Health 2014, 14:1205 Page 4 of 10http://www.biomedcentral.com/1471-2458/14/1205Major street, with parked carsNo bike infrastructure 155 42 31AShared lane 9 3 2Bike lane 24 8 4Major street, no parked carsNo bike infrastructure 112 24 12AShared lane 13 1 2Bike lane 35 14 1Local street (mainly residential)No bike infrastructure 88 24 5Bike route 51 18 4Bike route, with trafficcalming48 19 2Separated from trafficSidewalk or otherpedestrian path52 12 -Multiuse paths, paved 61 3 -Multiuse paths, unpaved 12 - -Bike path 21 - -BCycle track 2 - -- no injury events with this crash circumstance on this route type.AShared lanes include traffic lanes marked with sharrows or shared HOV lanes.BCycle tracks run alongside major streets but are physically separated from them, ebike lanes”.49 6 3 8 14- - 1 2 12 4 2 2 128 9 12 4 182 2 1 3 -5 2 5 2 55 13 6 5 261 7 6 5 9- 2 1 12 102 7 9 9 113 9 13 13 8- 7 2 1 1- - 8 3 4- 1 - - -xcept at intersections. They are also called “separated bike lanes” or “protectedTeschke et al. BMC Public Health 2014, 14:1205 Page 5 of 10http://www.biomedcentral.com/1471-2458/14/1205by where people cycled and the risk of a specific routetype (relative risks by route type are described in detailin our earlier paper and reported in brief in Table 2here) [3]. Motor vehicle involvement in collisions andfalls featured most prominently on major streets withparked cars, and almost not at all on routes separatedfrom traffic. A minority of all crashes occurred at inter-sections (31%), though a higher proportion of motorvehicle collisions were at intersections (53%) (data notshown).Table 1 shows a cross-tabulation of crash circumstancesby route type. To ensure numbers for subsequent analyses,some circumstances shown in Figure 1 were grouped intolarger categories (circumstances with <5% of crashes).There were no collisions involving motor vehicle doors onany of the route types separated from traffic. There wereno collisions with motor vehicles or with streetcar or traintracks on unpaved multiuse paths, bike paths, or cycletracks.Table 2 reports associations between crash circum-stance and route type via the ratio of observed to ex-pected injury events, using the distribution of controlssites (reflecting exposure) by route type (Expected1). Allcrash circumstances except “other fall” were associatedwith route type. Collisions involving motor vehicles, in-cluding motor vehicle doors, were consistently higherthan expected for all major street route types withparked cars, significantly so where there was no infra-structure for bikes. This excess was not observed onmajor streets without parked cars. Streetcar and traintrack collisions were significantly higher than expectedon major streets without bike infrastructure, whether ornot there were parked cars. Local street bike routes withtraffic calming had significantly more motor vehiclecollisions and falls to avoid collisions than expected.Paved multi-use paths and bike paths had more colli-sions than expected involving infrastructure and pedes-trians, cyclists or animals. Paved multi-use paths hadmore falls to avoid collisions than expected. Unpavedmulti-use paths had more collisions involving surfacesthan expected.We also calculated observed to expected injury eventsusing the distribution of injury sites by route type (Ex-pected2, data not shown). Using this method, associa-tions between crash circumstance and route type did notdiffer substantively from those described above.DiscussionIn this study, we examined a large number of crash cir-cumstances and considered their distributions across 14route types. Of the 683 crashes characterized, 34% weredirect collisions with motor vehicles, 6% were collisionswith pedestrians, cyclists, or animals, 34% were colli-sions with infrastructure or surface features, and 26%were falls. Crash circumstances were distributed differ-ently by route type, for example, motor vehicle and tramtrack collisions were overrepresented on major streets,and infrastructure or other surface collisions were over-represented on off-street routes. Below, our results foreach circumstance type is considered in light of otherresearch.Crashes involving motor vehiclesUnderstanding collisions with motor vehicles is particu-larly important because they typically result in more se-vere injuries [2,15,27] and concern about collisions withmotor vehicles deters cycling [8,9]. In this study, 34% ofthe injury events were direct crashes with motor vehi-cles. Studies of hospital visits in comparable jurisdictionswith little specialized bicycling infrastructure have foundsimilar proportions: 27% in the US [15]; 31% in France[12]; and 34% in New Zealand [17]. Others have re-ported lower proportions of collisions with motor vehi-cles: 9% in Sweden [14]; 14% in Australia [16]; 18% inthe Netherlands [19]; and 21% in South Korea [18].These lower proportions may result from different casedefinitions (inclusion of less serious injuries and sportscycling injuries, as in the Australian study) [16] or thebicycling facilities available in the area (routes that separatecyclists from motor vehicles, as in Sweden, the Netherlandsand Korea) [14,18,19].The potential for cycling infrastructure to reducecrashes between cyclists and motor vehicles is observedin our results. Collisions with motor vehicles repre-sented 40% of all crashes on streets. Major streets withparked cars had more crashes with vehicles than ex-pected, including those with vehicle doors. In contrast,collisions with motor vehicles on routes separated fromtraffic were rare (10%). There has been concern thatcycle tracks and other separated infrastructure mightpose a special risk to cyclists when they eventually meettraffic at intersections [5]. Our results show that even ifthat were the case, the overall benefit of separation ismaintained. Other studies found similar benefits to sepa-rated infrastructure. A study in South Korea [18] foundthat 40% of bike crashes on regular roadways were withmotor vehicles, compared to only 4.4% of those on bikelanes (typically separated). A study in Australia foundthat 35% of bike crashes in traffic involved motor vehi-cles, compared to only 11% of those on other facilities(bike lanes, shared paths, footpaths) [20].A number of studies have tallied collisions with open-ing doors of parked vehicles (“doorings”). In a Swedishstudy, “doorings” accounted for 4.3% of collisions withmotor vehicles [22], in a Dutch study, 3% of single partycrashes [19] and in Australian studies, 2.2% of surveyedcyclists, 3.1% of hospital presentations, and 8.1% of po-lice reported crashes [16,28]. These proportions are allTable 2 Ratio of observed to expected injury events for each crash circumstance and route type combinationOdds Ratio (relativerisk of injury) byroute type [3]ARatios of observed to expected1 injury events (and 95% confidence intervals)BControl sites Motor vehicle(excluding door)Motor vehicle door Pedestrian,cyclist oranimalStreetcar (tram)or train trackOthersurfaceInfrastructure Fall to avoidcollisionOther fall683 168 63 40 97 69 69 69 108Major street, with parked carsNo bike infrastructure 1.0 reference 114 1.5 B(1.1-1.9) 3.0 (2.1-4.0) 0.3 (0.1-1.2) 3.0 (2.4-3.7) 0.5 (0.2-1.2) 0.3 (0.1-0.8) 0.7 (0.3-1.4) 0.8 (0.5-1.3)CShared lane 0.78 7 1.7 (0.5-3.2) 3.1 (0.6-7.6) 0 (0–7.5) 0 (0–3.1) 0 (0–4.4) 1.4 (0.1-5.7) 2.8 (0.5-6.9) 0.9 (0.1-3.7)Bike lane 0.53 27 1.2 (0.6-2.1) 1.6 (0.5-3.8) 0.6 (0–3.6) 0.5 (0.1-1.8) 1.5 (0.5-3.4) 0.7 (0.1-2.6) 0.7 (0.1-2.6) 0.2 (0–1.3)Major street, no parked carsNo bike infrastructure *0.65 116 0.8 (0.6-1.2) 1.1 (0.6-1.9) 0.7 (0.3-1.8) 1.7 (1.2-2.3) 0.8 (0.4-1.5) 1.0 (0.6-1.8) 0.3 (0.1-0.9) 1.0 (0.6-1.5)CShared lane 0.66 12 0.3 (0–1.6) 1.8 (0.3-5.3) 2.9 (0.5-8.4) 1.2 (0.2-3.5) 1.7 (0.3-4.9) 0.8 (0–4.0) 2.5 (0.7-5.7) 0 (0–1.9)Bike lane *0.47 46 1.2 (0.7-1.9) 0.2 (0–1.4) 0.4 (0–2.2) 0.8 (0.3-1.7) 0.4 (0.1-1.6) 1.1 (0.4-2.4) 0.4 (0.1-1.6) 0.7 (0.3-1.5)Local street (mainly residential)No bike infrastructure *0.44 115 0.9 (0.6-1.2) 0.5 (0.2-1.1) 0.6 (0.2-1.6) 0.3 (0.1-0.7) 1.1 (0.6-1.9) 0.5 (0.2-1.1) 0.4 (0.2-1.0) 1.4 (0.9-2.0)Bike route *0.53 56 1.3 (0.8-1.9) 0.8 (0.3-2.0) 0.3 (0–1.9) 0.1 (0–0.8) 1.2 (0.6-2.4) 1.1 (0.4-2.2) 0.9 (0.3-2.0) 1.0 (0.5-1.8)Bike route, with traffic calming 0.59 46 1.7 (1.1-2.3) 0.5 (0.1-1.7) 0.7 (0.1-2.7) 0 (0–0.7) 0.4 (0.1-1.6) 0.2 (0–1.3) 2.6 (1.5-4.1) 1.4 (0.7-2.3)Separated from trafficSidewalk, pedestrian path 0.73 47 1.0 (0.6-1.7) 0 (0–1.0) 0.7 (0.1-2.7) 0.3 (0.1-1.1) 1.5 (0.7-2.9) 1.9 (1.0-3.3) 1.9 (1.0-3.3) 1.5 (0.8-2.4)Multiuse paths, paved 0.75 55 0.2 (0.1-0.7) 0 (0–0.9) 3.7 (2.1-6.0) 0.4 (0.1-1.1) 1.6 (0.8-2.9) 2.3 (1.4-3.7) 2.3 (1.4-3.7) 0.9 (0.4-1.7)Multiuse paths, unpaved 0.63 11 0 (0–1.3) 0 (0–3.5) 1.6 (0.1-7.3) 0 (0–2.3) 6.3 (3.1-8.7) 1.8 (0.3-5.2) 0.9 (0.1-4.2) 0.6 (0–2.7)Bike path 0.54 21 0 (0–0.8) 0 (0–2.1) 4.9 (2.1-8.9) 0 (0–1.4) 0 (0–1.9) 3.8 (1.9-6.1) 1.4 (0.4-3.7) 1.2 (0.4-2.7)DCycle track *0.12 10 0 (0–1.4) 0 (0–3.7) 1.7 (0.1-7.8) 0 (0–2.4) 1.0 (0.1-4.5) 0 (0–3.4) 0 (0–3.4) 0 (0–2.2)AOdds ratios (relative risks of injury) by route type are from a previous analysis [3] and are provided for reference only. Asterisks indicate risk of injury for this route type was significantly lower than on major streetswith parked cars and no bike infrastructure (the reference category).BRatios of observed to expected1 injury events and confidence intervals in bold when statistically significantly different from 1.0. Expected1 based on exposure to route type, estimated via randomly selected controlsites on the trip route.CShared lanes include traffic lanes marked with sharrows or shared HOV lanes.DCycle tracks run alongside major streets but are physically separated from them, except at intersections. They are also called “separated bike lanes” or “protected bike lanes”.Statistical significance, p ≤ 0.05.Teschkeetal.BMCPublicHealth2014,14:1205Page6of10http://www.biomedcentral.com/1471-2458/14/1205Teschke et al. BMC Public Health 2014, 14:1205 Page 7 of 10http://www.biomedcentral.com/1471-2458/14/1205considerably lower than we found (10% of all crashes,27% of motor vehicle collisions). The Australian studyincluded mountain biking and racing injuries, likely in-fluencing the low proportion there [16]. In Sweden andthe Netherlands, the prevalence of well designed, usuallyseparated facilities on major streets likely made colli-sions with vehicle doors rare.[19,22] In Vancouver andToronto at the time of our study, cycling betweenparked and moving cars was often the only option onmajor roads, even where there were painted bike lanesor shared lanes.Tallying direct collisions with motor vehicles may notprovide a complete picture of motor vehicles’ influenceon cycling injuries. In the Australian survey, cyclists re-ported that 5% of crashes involved motor vehicle colli-sion avoidance [16]. In our study, 15% of cases involvedcrashes to avoid a motor vehicle, so in total, motor ve-hicle interactions were responsible for half the crashes.Separated routes prevent these interactions (except at in-tersections) and can prevent whole classes of crashessuch as doorings [3,5].Crashes involving people or animalsA common concern with separated and off-street bikefacilities is collisions with other cyclists, pedestrians, oranimals. Only 5.9% of the injury events in this studyinvolved such collisions. Similar low proportions wereidentified in France and New Zealand [12,17], but inSouth Korea where cycle lanes were more common, 15%of crashes were with other cyclists and 3% with pedes-trians [18]. An Australian survey also reported a higherproportion of crashes between cyclists (11%), thoughone-quarter of their survey cohort were racing cyclistswho may collide during training and races [16].We found more crashes involving people or animalsthan expected on multi-use paths. Multi-use paths aredesignated for both pedestrians and cyclists, so thisresult is not a surprise. Multi-use paths also had morefalls to avoid collisions than expected, most to avoidother cyclists or pedestrians. Another study reportedhigher proportions of cyclist and pedestrian collisions orcollision-avoidance crashes on multi-use paths [20].Bike only paths also had more collisions than expectedwith cyclists and pedestrians (in equal numbers), sug-gesting that the delineation of the path for cyclists maynot have been clear or that heavy pedestrian traffic over-flowed to the cyclist side. Bike paths did not have aproblem with falls to avoid collisions, suggesting theydid function better than multi-use paths.Crashes with infrastructure and surface featuresMuch more common than collisions with people or ani-mals were those with infrastructure or surface features.These contributed 34% of injury events, the same asmotor vehicle collisions. This group comprised manycrash circumstances, most related to route type, andlikely preventable via design solutions.Crashes on streetcar (tram) or train tracks made up14% of all events, and were in excess on major streets.Toronto has an extensive streetcar system in its centralbusiness district, not separated from traffic along moststreets. In our previous analyses, we found greatly in-creased relative risk where streetcar tracks were present[3,4]. Streetcar track crashes involved wheels beingcaught in the slot or slipping on the rail surface. Two re-cent reports from Europe noted the issue of tram tracks[19,29]. Physically separated bike lanes or streetcar lanesare potential design changes that would greatly reducethis type of crash. Crossings would still be needed at in-tersections, but in our study two-thirds of the crashesinvolving tracks were not at intersections.While streetcar or train tracks were a problem onmajor city streets, other surfaces (10% of crash circum-stances) were involved in crashes across all route types,with unpaved multi-use paths showing a strong excess.Crashes with surfaces involved bumps, potholes, gravel,icy or wet surfaces, and vegetation such as roots orleaves, pointing to the importance of route maintenance.Some studies tallied surface feature crash circumstances:18% in Australia [16]; 23% (including tram rails) in theNetherlands [19]; and 21% (including tracks) in Belgium[29]. These proportions are similar to the total of street-car track and other surface crashes we found (24%).Infrastructure such as curbs, concrete barriers, walls,fences, railings, furniture, boulders, speed bumps, andstairs contributed 10% of crash circumstances, and wereoverrepresented particularly on paved multi-use paths andbike paths. In our previous analyses of relative risks byroute type, we found that multi-use and bike paths werenot as safe as cycle tracks and local street bikeways withtraffic diversion [4]. A reason may be that such paths wereoften designed to be interesting (e.g., with street furnitureand curves) and to direct traffic (using bollards, signage,curbs and fences to prevent motor vehicle ingress or toseparate pedestrians and cyclists). In measurements takenat injury and control sites, 5 to 10% of bike and multi-usepaths had poor forward visibility, but this was not a prob-lem on on-street routes. The crashes with infrastructuresuggest a rethink of multi-use and bike path design to pro-vide straight, wide and obstacle-free passage for cyclists.In other studies, infrastructure was involved in 8 to 31% ofcrashes [12,16,18,19]. A South Korean study tallied crasheswith obstacles by route type; it found similar proportions(~10%) on both bike lanes and roads [18].FallsFalls to avoid collisions contributed 10% of crash cir-cumstances. About half (N = 34) were to avoid motorTeschke et al. BMC Public Health 2014, 14:1205 Page 8 of 10http://www.biomedcentral.com/1471-2458/14/1205vehicles, 16 to avoid pedestrians, 8 to avoid other cy-clists, 10 to avoid infrastructure or surface features, and1 to avoid an animal. Excesses were observed on sharedfacilities (shared lanes on streets, multi-use paths) andsidewalks, reinforcing the importance of bike-specific in-frastructure [2-4].Collision avoidance falls were also in excess on localstreet bike routes with traffic calming, most to avoidmotor vehicles. Two types of traffic calming were ob-served in our study: traffic diversion (full or partial bar-riers to motor vehicles at intersections with arterials)and traffic slowing (speed humps, traffic circles) [4].Traffic circles are small diameter (6–8 m) roundaboutsused at local street intersections. They had higher rela-tive risk of injury in our earlier analyses [4], in part be-cause drivers did not observe cyclists or did not knowwho had the right of way. Traffic circles also presented adifficult-to-negotiate obstacle to cyclists. In contrast,bike routes with traffic diversion had very low relativerisk of injury in our earlier analyses [4], suggesting thisis a better traffic calming method. A British study founda benefit to cyclists of traffic slowing; techniques used(speed humps, chicanes, raised junctions) only partlyoverlapped with those observed in our study, reinforcingthe importance of understanding the effects of specificelements [30]. Raised junctions have been shown togreatly reduce cycling injuries at intersections [19], butthese were not observed in our study.Our category “other falls” (16% of crash circum-stances) included loss of balance, braking too hard, bikemalfunctions, having an item caught in the wheel andcornering. This crash category was the only one not re-lated to route type. This is reasonable, since these fallsrepresented either problems with the bicycle itself orwith bicycling operations.Single party (bicyclist only) crashesSome studies classify crashes as multi-party vs. singleparty (bicyclist only) crashes. Single party is interpretedas any crash not involving a direct collision with a motorvehicle, pedestrian, cyclist or animal. By this standard,60% of the crashes in our study were single partycrashes. Schepers [19] reviewed data from several coun-tries and reported that 60 to 90% of crashes involvinghospital treatment were single cyclist crashes. Our studyis at the low end of these results, likely reflecting boththe case definition (urban cycling) and the types ofroutes available to cyclists in Toronto and Vancouver(typically on street mixed with motor vehicle traffic).The above definition of single party omits collisionavoidance crashes that do not result in direct collisionswith other parties. If we include collision avoidancecrashes as multi-party crashes, only 42% remain singleparty in our study. An Australian study [20] also foundthat single party crashes were considerably lower oncecollision avoidance was taken into account (52%).Strengths and limitationsThis study adds to the small base of evidence examiningthe distribution of crash circumstances in an urban cyc-ling context [12,18,20]. It is the first to report observedto expected crash circumstances by route type (control-ling for exposure). It examined 14 route types, manymore than previous studies, though this meant thatsome route types had small numbers of injury events, sothat confidence intervals were wide for observed to ex-pected ratios.We included injuries serious enough to require a hos-pital visit: treatment in an emergency department orhospital admission, but the most serious injuries (includ-ing deaths) were not included because routes and cir-cumstances could not be reported. Hospital-based caseidentification allowed a broad array of crash circum-stances to be captured beyond motor vehicle collisions.Others have reported injuries with hospital identifica-tion, providing a basis for comparison [12-15,17-19]. Werestricted cases to those injured while cycling for utili-tarian or leisure travel by excluding cases injured duringrisk-taking sports like mountain biking and racing. Thisrestriction provided a clear delineation of the focus: oncycling for which urban transportation engineers designroute infrastructure. Other studies did not have such re-strictions and sports injuries may have been substantial,particularly in countries such as the United States,Australia and New Zealand [13,15,16,23].We classified crash circumstances using classes similarto those in other studies, although each study had varia-tions [12-19]. Collisions with motor vehicles or not isthe most frequent basis for classification. We talliedcrashes with vehicle doors as a separate category andalso tallied motor vehicle involvement in crashes thatdid not end in a direct collision with a vehicle. Anothercommon basis for classification is collision vs. fall. Incollisions, we included crashes with surface features be-cause most of these crashes involved a dramatic changein motion after striking the feature. Some might con-sider these falls; our separate tally of streetcar track andother surface crashes allows others to do their owncalculations. There are other methods of classifyingcrashes, for example, based on travel movements or col-lision partner responsibility, but our data did not allowthese [31].Crash circumstances in this study were based on a de-scription of the event by the injured cyclist. This is trueof most studies classifying crashes, including surveys ofcyclists and studies using hospital coding of injuryevents [12,14-18]. The results therefore rely on the ac-curacy of participants’ recall. To minimize problemsTeschke et al. BMC Public Health 2014, 14:1205 Page 9 of 10http://www.biomedcentral.com/1471-2458/14/1205related to recall, we excluded cyclists who could not re-member their injury event, we interviewed subjects as soonas possible after the crash (50% completed within 4.9 weeks,75% within 7.7), and we did not ask for comments aboutfault. Some injury data, particularly from police or transpor-tation agencies, may include reporting by all parties in thecrash, witnesses, and investigators [13,22].ConclusionsIn the Bicyclists’ Injuries and the Cycling Environmentstudy in Toronto and Vancouver, about one-third ofcrashes were collisions with motor vehicles (including“doorings”), one-third collisions with infrastructure andsurface features, and a small proportion collisions withcyclists, pedestrians and animals. All collision circum-stances, and falls to avoid collisions, were related toroute type. Our results reinforce the importance of pro-viding bicycle-specific facilities such as cycle tracksalongside major streets and bike paths off-street. Theydemonstrate the value of not placing cyclists betweenparked and moving vehicles on major streets to reducethe chance of being hit by a door. They show the valueof separation from streetcar (tram) tracks, via cycletracks or separated streetcar lanes. They shed light onproblems with off-street bike paths and multi-use paths,where collisions with infrastructure and surface featureswere elevated. Such facilities are very attractive to peopleof all ages and abilities; removing obstacles, providingclear sight lines and ensuring routine maintenanceshould improve their safety.Many cities are trying to encourage cycling, and safety isa key motivator [7,9]. Understanding crash circumstanceson the various routes types will help transportationplanners and engineers target improvements to make cyc-ling safer.Competing interestsKT, CCOR, PAC, MW have held consultancies to related to their transportationor injury biomechanics expertise. PAC has stock in a company developing ahelmet that he co-invented. All other authors have no financial or otherrelationships or activities that could appear to have influenced thesubmitted work.Authors’ contributionsKT, MAH, CCOR, and PAC were responsible for initial conception and designof the study. KT, MAH, CCOR, PAC, MW, MC, MDC, JB, GH, SB and SMF wereresponsible for the funding proposal. MAH, CCOR, MW, MM, MDC, LV and KTdesigned and tested data collection instruments. JB, GH, SMF, and MDCcontributed to identification of injured cyclists at the study hospitals. HS wasresponsible for data analyses. KT drafted the article. All authors contributedto study design and implementation, analysis decisions, interpretation ofresults, and critical revision of the article. All authors read and approved thefinal manuscript.AcknowledgementsWe thank the study participants for generously giving their time. Weappreciate the many contributions of study staff (Evan Beaupré, Niki Blakely,Jill Dalton, Vartouji Jazmaji, Martin Kang, Kevin McCurley, Andrew Thomas),hospital personnel (Barb Boychuk, Jan Buchanan, Doug Chisholm, NadaElfeki, Kishore Mulpuri), city personnel (Peter Stary, David Tomlinson, BarbaraWentworth) and community collaborators (Jack Becker, Bonnie Fenton,David Hay, Nancy Smith Lea, Fred Sztabinski). The study was funded by theHeart and Stroke Foundation of Canada and the Canadian Institutes ofHealth Research (Institute of Musculoskeletal Health and Arthritis, andInstitute of Nutrition, Metabolism and Diabetes). JRB, MAH, and MW weresupported by awards from the Michael Smith Foundation for HealthResearch. MAH, CCOR, and MW were supported by awards from theCanadian Institutes of Health Research.Author details1School of Population and Public Health, University of British Columbia, 2206East Mall, Vancouver, BC, Canada. 2School of Occupational and Public Health,Ryerson University, Toronto, ON, Canada. 3Institute for Resources,Environment and Sustainability, University of British Columbia, Vancouver, BC,Canada. 4Department of Mechanical Engineering, ICORD and the BrainResearch Centre, University of British Columbia, Vancouver, BC, Canada.5Department of Emergency Medicine, University of British Columbia,Vancouver, BC, Canada. 6School of Public Health, University of Toronto,Toronto, ON, Canada. 7Emergency Medicine, University Health Network,Toronto, ON, Canada. 8British Columbia Injury Research and Prevention Unit,Vancouver, BC, Canada. 9Faculty of Health Sciences, Simon Fraser University,Burnaby, BC, Canada.Received: 25 March 2014 Accepted: 6 November 2014Published: 22 November 2014References1. 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Tan C: Crash-Type Manual for Bicyclists. 1996. http://www.fhwa.dot.gov/publications/research/safety/pedbike/96104/ Accessed February 25, 2014.doi:10.1186/1471-2458-14-1205Cite this article as: Teschke et al.: Bicycling crash circumstances vary byroute type: a cross-sectional analysis. BMC Public Health 2014 14:1205.Submit your manuscript at www.biomedcentral.com/submit

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