title: Database improvements for motor vehicle/bicycle crash analysis.
abstract: BACKGROUND
  Bicycling is healthy but needs to be safer for more to bike. Police crash templates are designed for reporting crashes between motor vehicles, but not between vehicles/bicycles. If written/drawn bicycle-crash-scene details exist, these are not entered into spreadsheets.
  
  
  OBJECTIVE
  To assess which bicycle-crash-scene data might be added to spreadsheets for analysis.
  
  
  METHODS
  Police crash templates from 50 states were analysed. Reports for 3350 motor vehicle/bicycle crashes (2011) were obtained for the New York City area and 300 cases selected (with drawings and on roads with sharrows, bike lanes, cycle tracks and no bike provisions). Crashes were redrawn and new bicycle-crash-scene details were coded and entered into the existing spreadsheet. The association between severity of injuries and bicycle-crash-scene codes was evaluated using multiple logistic regression.
  
  
  RESULTS
  Police templates only consistently include pedal-cyclist and helmet. Bicycle-crash-scene coded variables for templates could include: 4 bicycle environments, 18 vehicle impact-points (opened-doors and mirrors), 4 bicycle impact-points, motor vehicle/bicycle crash patterns, in/out of the bicycle environment and bike/relevant motor vehicle categories. A test of including these variables suggested that, with bicyclists who had minor injuries as the control group, bicyclists on roads with bike lanes riding outside the lane had lower likelihood of severe injuries (OR, 0.40, 95% CI 0.16 to 0.98) compared with bicyclists riding on roads without bicycle facilities.
  
  
  CONCLUSIONS
  Police templates should include additional bicycle-crash-scene codes for entry into spreadsheets. Crash analysis, including with big data, could then be conducted on bicycle environments, motor vehicle potential impact points/doors/mirrors, bicycle potential impact points, motor vehicle characteristics, location and injury.
authors.affiliation: Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA.
authors.forename: Anne C
authors.initials: AC
authors.lastname: Lusk
authors.affiliation: Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA.
authors.forename: Morteza
authors.identifier: http://orcid.org/0000-0002-3391-6918
authors.initials: M
authors.lastname: Asgarzadeh
authors.affiliation: Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA.
authors.forename: Maryam S
authors.identifier: http://orcid.org/0000-0003-1783-4186
authors.initials: MS
authors.lastname: Farvid
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control* / Q000706:statistics & numerical data; D001642:Bicycling / Q000293:injuries* / Q000706:statistics & numerical data; D003625:Data Collection / Q000379:methods* / Q000592:standards; D016208:Databases, Factual / Q000592:standards*; D006801:Humans; D016015:Logistic Models; D009519:New York City; D016495:Police; D012449:Safety; D015599:Trauma Severity Indices
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