, Volume 39, Issue 2, pp 433–448 | Cite as

Spatial epidemiologic analysis of relative collision risk factors among urban bicyclists and pedestrians

  • Elizabeth Cahill Delmelle
  • Jean-Claude Thill
  • Hoe-Hun Ha


Pedestrians and bicyclists are the victims of countless car crashes in U.S. cities as well as around the world. Yet, many dimensions of their involvement in crashes remain rather poorly known. In this article, we follow a spatial epidemiologic approach to study the relative risk factors of bicycle and pedestrian crashes at the neighborhood level in the City of Buffalo, NY over a two-year period. The analysis examines physical road characteristics such as roadway and intersection functional classes, urban density and type of development—business or residential, as well as socio-economic and demographic variables to identify discriminating risk factors between the two non-motorized transportation modes. The analysis underscores significant differences tied to neighborhood ethnicity, educational attainment and land use, while physical characteristics of the road infrastructure register as marginally discriminating factors. Income related socio-economic status is not found to play a prominent role.


Bicyclists Pedestrians Crash analysis Spatial statistics Urban traffic safety Spatial analysis 



The authors wish to thank the referees of an earlier version of the manuscript for their insightful comments. Their critical input enhanced the quality of our work.


  1. Agran, P.F., Winn, D.G., Anderson, C.L., Valle, C.D.: Family, social, and cultural factors in pedestrian injuries among Hispanic children. Injury Prev. 4, 188–193 (1998)CrossRefGoogle Scholar
  2. Anselin, L., Bera, A.K.: Spatial dependence in linear regression models with an Introduction to spatial econometrics. In: Ullah, A., Giles, D.E.A. (eds.) Handbook of Applied Economic Statistics, pp. 237–289. Marcel Dekker, New York (1998)Google Scholar
  3. Beck, L., Dellinger, A., O’Neil, M.: Motor vehicle crash injury rates by mode of travel, United States: using exposure-based methods to quantify differences. Am. J. Epidemiol. 166, 212–218 (2007)CrossRefGoogle Scholar
  4. Braddock, M., Lapidus, G., Gregorio, D., Kapp, M., Banco, L.: Population, income, and ecological correlates of child pedestrian injury. Pediatrics 88, 1242–1247 (1991)Google Scholar
  5. Cervero, R., Duncan, M.: Walking, bicycling, and urban landscapes: evidence from the San Francisco Bay area. Am. J. Public Health 93(9), 1478–1483 (2003)CrossRefGoogle Scholar
  6. Clifton, K., Kreamer-Fults, K.: Examination of environmental attributes associated with pedestrian-vehicular crashes near public schools. Accid. Anal. Prev. 39, 709–715 (2007)CrossRefGoogle Scholar
  7. Delmelle, E.C., Thill, J.-C.: Urban bicyclists: spatial analysis of adult and youth traffic hazard intensity. Transp. Res. Rec. 2074, 31–39 (2008)CrossRefGoogle Scholar
  8. Dissanayake, D., Aryaija, J., Priyantha Wedagama, D.M.: Modelling the effects of land use and temporal factors on child pedestrian casualties. Accid. Anal. Prev. 41(5), 1016–1024 (2009)CrossRefGoogle Scholar
  9. Dumbaugh, E., Frank, L.: Traffic safety and safe routes to schools. Synthesizing the empirical evidence. Transp. Res. Rec. 2009, 89–97 (2007)CrossRefGoogle Scholar
  10. Epperson, B.: Demographic and economic characteristics of bicyclists involved in bicycle–motor vehicle accidents. Transp. Res. Rec. 1502, 58–64 (1995)Google Scholar
  11. Ewing, R., Dumbaugh, E.: The built environment and traffic safety. J. Plan. Lit. 23(4), 347–367 (2009)CrossRefGoogle Scholar
  12. Garder, P.E.: The impact of speed and other variables on pedestrian safety in Maine. Accid. Anal. Prev. 36(4), 533–542 (2004)CrossRefGoogle Scholar
  13. Ha, H.H., Thill, J.-C.: Analysis of traffic hazard intensity: a spatial epidemiology case study of urban pedestrians. Comput. Environ. Urban Syst. 35, 230–240 (2011)Google Scholar
  14. Hayes, J., Groner, J.: Minority status and the risk of serious childhood injury and death. J. Natl. Med. Assoc. 97(3), 362–369 (2005)Google Scholar
  15. Hoque, M., Andreassen, D.C.: Pedestrian accidents: an examination by road class with special reference to accident ‘cluster’. Traffic Eng. Control 27, 391–397 (1986)Google Scholar
  16. Jacobsen, P.L.: Safety in numbers: more walkers and bicyclists, safer walking and bicycling. Injury Prev. 9, 205–209 (2003)CrossRefGoogle Scholar
  17. Kelejian, H.H., Prucha, I.R.: Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances. J. Econom. 157, 53–67 (2010)CrossRefGoogle Scholar
  18. Kerr, J., Frank, L., Sallis, J., Chapman, J.: Urban form correlates of pedestrian travel in youth: differences by gender, race-ethnicity, and household attributes. Transp. Res. D 12, 177–182 (2007)CrossRefGoogle Scholar
  19. Laflamme, L., Diderichesen, F.: Social differences in traffic injury risks in childhood and youth—a literature review and a research agenda. Injury Prev. 6, 293–298 (2000)CrossRefGoogle Scholar
  20. LaScala, E., Gerber, D., Gruenewald, P.: Demographic and environmental correlates of pedestrian injury collisions: a spatial analysis. Accid. Anal. Prev. 32, 651–658 (2000)CrossRefGoogle Scholar
  21. LaScala, E., Gruenewald, P., Johnson, F.: An ecological study of the locations of schools and child pedestrian injury collisions. Accid. Anal. Prev. 36, 569–576 (2004)CrossRefGoogle Scholar
  22. Leden, L.: Pedestrian risk decrease with pedestrian flow. A case study based on data from signalized intersections in Hamilton, Ontario. Accid. Anal. Prev. 34, 457–464 (2001)CrossRefGoogle Scholar
  23. Lee, C., Abdel-Aty, M.: Comprehensive analysis of vehicle-pedestrian crashes at intersections in Florida. Accid. Anal. Prev. 37(4), 775–786 (2005)CrossRefGoogle Scholar
  24. Lightstone, A.S., Dhillon, P.J., Peek-Asa, C., Kraus, J.F.: A geographic analysis of motor vehicle collisions with child pedestrians in Long Beach, California: comparing intersections and midblock incident locations. Injury Prev. 7, 155–160 (2001)Google Scholar
  25. Loukaitou-Sideris, A., Liggett, R., Sung, H.-G.: Death on the crosswalk: a study of pedestrian-automobile collisions in Los Angeles. J. Plan. Educ. Res. 26, 338–351 (2007)CrossRefGoogle Scholar
  26. Mitra, S., Washington, S.P., can Schalkwyk, I.: Important omitted spatial variables in safety models: understanding contributing crash causes at intersections. Transportation Research Board Annual Meeting, CD Rom (2007)Google Scholar
  27. Noland, R., Quddus, M.: Analysis of pedestrian and bicycle casualties with regional panel data. Transp. Res. Rec. 1897, 28–33 (2004)CrossRefGoogle Scholar
  28. Plaut, P.: Non-motorized commuting in the US. Transp. Res. D 10, 347–356 (2005)CrossRefGoogle Scholar
  29. Pless, I.B., Verreault, R., Tenina, S.: A case-control study of pedestrian and bicyclist injuries in childhood. Am. J. Public Health 79, 995–998 (1989)CrossRefGoogle Scholar
  30. Pucher, J., Dijkstra, L.: Making walking and cycling safer: lessons from Europe. Transp. Quart. 54, 25–50 (2000)Google Scholar
  31. Pucher, J., Dijkstra, L.: Promoting safe walking and cycling to improve public health: lessons from the Netherlands and Germany. Am. J. Public Health 93(9), 1509–1516 (2003)CrossRefGoogle Scholar
  32. Pucher, J., Renne, J.: Socio-economics of urban travel–evidence from the 2001 NHTS. Transp. Quart. 57(3), 49–77 (2003)Google Scholar
  33. Ryb, G., Dischinger, P., Kufera, J., Soderstrom, C.: Social, behavioral and driving characteristics of injured pedestrians: a comparison with other unintentional trauma patients. Accid. Anal. Prev. 39, 313–318 (2007)CrossRefGoogle Scholar
  34. Sebert Kuhlmann, A.K., Brett, J., Thomas, D., Sain, S.: Environmental characteristics associated with pedestrian–motor vehicle collisions in Denver, Colorado. Am. J. Public Health 99(9), 1632–1637 (2009)CrossRefGoogle Scholar
  35. Targa, F., Clifton, K.J.: The built environment and trip generation for non-motorized travel. J. Transp. Stat. 8, 55–70 (2005)Google Scholar
  36. US Department of Transportation: The pedestrian and bicyclist highway safety problem as it relates to the Hispanic population in the United States. (Report No. DTFH61-03-D-00324), US Department of Transportation, Federal Highway Administration, Washington (2004)Google Scholar
  37. White, H.: A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48(4), 817–838 (1980)CrossRefGoogle Scholar
  38. Wier, M., Weintraub, J., Humphreys, E., Seto, E., Bhatia, R.: An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning. Accid. Anal. Prev. 41, 137–145 (2009)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2011

Authors and Affiliations

  • Elizabeth Cahill Delmelle
    • 1
  • Jean-Claude Thill
    • 1
  • Hoe-Hun Ha
    • 2
  1. 1.Department of Geography & Earth SciencesThe University of North Carolina at CharlotteCharlotteUSA
  2. 2.Department of GeographyUniversity at Buffalo – The State University of New YorkAmherstUSA

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