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Spatial Association Between Urban Neighbourhood Characteristics ‎‎and ‎‎‎Child Pedestrian–Motor Vehicle Collision‎s

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Abstract

This study examined the relationship between environmental and socioeconomic factors and the number of motor vehicle collisions involving young pedestrians. The research encompassed urban neighbourhoods as well as an entire metropolitan area and analyzed data from 7,028 motor vehicle collisions that involved pedestrians aged 18 years or younger, occurring between 2015 and 2019 in the city of Mashhad, Iran. Thirteen indices related to socioeconomic and built environmental factors were quantified at the neighbourhood level. To model the relationship between these explanatory factors and the number of collisions investigated, Poisson and negative binomial models were developed using the geographically weighted regression (GWR) technique. The GWR was used to account for the impact of location on the association between explanatory factors and the count of collisions. The study found that the population of young people, road area ratio, main road intersection ratio, average maximum speed limit, non-motorized travels, sidewalk area ratio, sidewalk disconnections, number of schools, unemployment ratio, illiteracy rate, and open space ratio were significantly associated with child pedestrian-motor vehicle collisions. However, these associations were not uniform across the entire study area. It is possible that unknown factors or an unknown interaction of known factors in different parts of the urban area may have influenced the observed associations.

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Data Availability

The data is available by request from the corresponding author.

References

  • Almasi, S. A., Behnood, H. R., & Arvin, R. (2021). Pedestrian crash exposure analysis using alternative geographically weighted regression models. Journal of Advanced Transportation, 2021, 1–13.

  • Asare, I. O., & Mensah, A. C. (2020). Crash severity modelling using ordinal logistic regression approach. International Journal of Injury Control and Safety Promotion, 27(4), 412–419.

    Article  Google Scholar 

  • Behzadnia, S., & Shahmohammadi, S. (2016). Road traffic injuries among iranian children and adolescents: An epidemiological review. Journal of Pediatrics Review, 4(1), 0.

    Article  Google Scholar 

  • Bennet, S. A., & Yiannakoulias, N. (2015). Motor-vehicle collisions involving child pedestrians at intersection and mid-block locations. Accident Analysis & Prevention, 78, 94–103.

    Article  Google Scholar 

  • Peden, M., Oyegbite, K., Ozanne-Smith, J., Hyder, A. A., Branche, C., Rahman, A. K. M. F., Rivara, F., Bartolomeos, K., editors. World Report on Child Injury Prevention. Geneva: World Health Organization; 2008. PMID: 26269872.

  • Briz-Redón, Á, Martínez-Ruiz, F., & Montes, F. (2019). Estimating the occurrence of traffic accidents near school locations: A case study from Valencia (Spain) including several approaches. Accident Analysis & Prevention, 132, 105237.

    Article  Google Scholar 

  • Chakravarthy, B., Anderson, C. L., Ludlow, J., Lotfipour, S., & Vaca, F. E. (2010). The relationship of pedestrian injuries to socioeconomic characteristics in a large Southern California County. Traffic Injury Prevention, 11(5), 508–513.

    Article  Google Scholar 

  • Clifton, K. J., Burnier, C. V., & Akar, G. (2009). Severity of injury resulting from pedestrian–vehicle crashes: What can we learn from examining the built environment? Transportation Research Part D: Transport and Environment, 14(6), 425–436.

    Article  Google Scholar 

  • Congiu, T., Sotgiu, G., Castiglia, P., Azara, A., Piana, A., Saderi, L., & Dettori, M. (2019). Built environment features and pedestrian accidents: An italian retrospective study. Sustainability, 11(4), 1064.

    Article  Google Scholar 

  • Cottrill, C. D., & Thakuriah, P. V. (2010). Evaluating pedestrian crashes in areas with high low-income or minority populations. Accident Analysis & Prevention, 42(6), 1718–1728.

    Article  Google Scholar 

  • Currie, J., & Hotz, V. J. (2004). Accidents will happen?: Unintentional childhood injuries and the effects of child care regulations. Journal of Health Economics, 23(1), 25–59.

    Article  Google Scholar 

  • Curtis, J. W. (2017). Spatial distribution of child pedestrian injuries along census tract boundaries: Implications for identifying area-based correlates. PLoS One, 12(6), e0179331.

  • Da Silva, A. R., & Rodrigues, T. C. V. (2014). Geographically weighted negative binomial regression—incorporating overdispersion. Statistics and Computing, 24, 769–783.

    Google Scholar 

  • Egorov, A. I., Mudu, P., Braubach, M., & Martuzzi, M. (2016). Urban green spaces and health-A review of evidence. WHO Regional Office for Europe.

    Google Scholar 

  • Elias, W., & Shiftan, Y. (2014). Analyzing and modeling risk exposure of pedestrian children to involvement in car crashes. Accident Analysis & Prevention, 62, 397–405.

    Article  Google Scholar 

  • Graham, D. J., McCoy, E. J., & Stephens, D. A. (2013). Quantifying the effect of area deprivation on child pedestrian casualties by using longitudinal mixed models to adjust for confounding, interference and spatial dependence. Journal of the Royal Statistical Society: Series A (Statistics in Society), 176(4), 931–950.

    Article  Google Scholar 

  • Hagel, B. E., Macpherson, A., Howard, A., Fuselli, P., Cloutier, M. S., Winters, M., Richmond, S. A., Rothman, L., Belton, K., & Buliung, R. (2019). The built environment and active transportation safety in children and youth: A study protocol. BMC Public Health, 19, 1–13.

    Article  Google Scholar 

  • Hwang, J., Joh, K., & Woo, A. (2017). Social inequalities in child pedestrian traffic injuries: Differences in neighborhood built environments near schools in Austin, TX, USA. Journal of Transport & Health, 6, 40–49.

    Article  Google Scholar 

  • Jamshidi, E., Moradi, A., & Majdzadeh, R. (2017). Environmental risk factors contributing to traffic accidents in children: A case-control study. International Journal of Injury Control and Safety Promotion, 24(3), 338–344.

    Article  Google Scholar 

  • Kendrick, D. (1993). Prevention of pedestrian accidents. Archives of Disease in Childhood, 68(5), 669–672.

    Article  Google Scholar 

  • Kim, D. (2019). The transportation safety of elderly pedestrians: Modeling contributing factors to elderly pedestrian collisions. Accident Analysis & Prevention, 131, 268–274.

    Article  Google Scholar 

  • Kuşkapan, E., Sahraei, M. A., Çodur, M. K., & Çodur, M. Y. (2022). Pedestrian safety at signalized intersections: Spatial and machine learning approaches. Journal of Transport & Health, 24, 101322.

    Article  Google Scholar 

  • Li, Q., Alonge, O., & Hyder, A. A. (2016). Children and road traffic injuries: Can’t the world do better? Archives of Disease in Childhood, 101(11), 1063–1070.

    Article  Google Scholar 

  • Litman, T. (2012). Evaluating non-motorized transportation benefits and costs. Victoria Transport Policy Institute Victoria.

  • Ma, C., Hao, W., Xiang, W., & Yan, W. (2018). The impact of aggressive driving behavior on driver-injury severity at highway-rail grade crossings accidents. Journal of Advanced Transportation, 2018. https://doi.org/10.1155/2018/9841498

  • Mashhad Traffic and Transportation organisation (2020). Annual Reports of Transportation- Annual Report 2020. Retrieved from Mashha. https://traffic.mashhad.ir/. Accessed on 1 March 2023.

  • Miranda-Moreno, L. F., Morency, P., & El-Geneidy, A. M. (2011). The link between built environment, pedestrian activity and pedestrian–vehicle collision occurrence at signalized intersections. Accident Analysis & Prevention, 43(5), 1624–1634.

    Article  Google Scholar 

  • Muazir, S., & Hsieh, H. C. (2019). Urban network in strategic areas in Indonesia case study: Sambas Regency, West Kalimantan. Journal of Design and Built Environment, 19(2), 14–29.

    Article  Google Scholar 

  • Nakaya, T., Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2005). Geographically weighted poisson regression for disease association mapping. Statistics in Medicine, 24(17), 2695–2717.

    Article  Google Scholar 

  • Oluwajana, S. D., Park, P. Y., & Cavalho, T. (2022). Macro-level collision prediction using geographically weighted negative binomial regression. Journal of Transportation Safety & Security, 14(7), 1085–1120.

    Article  Google Scholar 

  • Part, D. (2010). Highway safety manual (p. 19192). American Association of State Highway and Transportation Officials.

    Google Scholar 

  • Peera, K. M., Shekhawat, R. S., & Prasad, C. (2019). Traffic analysis zone level road traffic accident prediction models based on land use characteristics. International Journal for Traffic and Transport Engineering (Belgrade), 9(4), 376–386.

    Google Scholar 

  • Pernica, J. M., LeBlanc, J. C., Soto-Castellares, G., Donroe, J., Carhuancho-Meza, B. A., Rainham, D. G. C., & Gilman, R. H. (2012). Risk factors predisposing to pedestrian road traffic injury in children living in Lima, Peru: A case–control study. Archives of Disease in Childhood, 97(8), 709–713.

    Article  Google Scholar 

  • QGIS software (2020). QGIS: A Free and Open Source Geographic Information System. https://qgis.org/en/site/. Accessed on 10 December 2022.

  • Rothman, L., Howard, A., Buliung, R., Macarthur, C., Richmond, S. A., & Macpherson, A. (2017). School environments and social risk factors for child pedestrian-motor vehicle collisions: A case-control study. Accident Analysis & Prevention, 98, 252–258.

    Article  Google Scholar 

  • Rothman, L., Cloutier, M. S., Manaugh, K., Howard, A. W., Macpherson, A. K., & Macarthur, C. (2020). Spatial distribution of roadway environment features related to child pedestrian safety by census tract income in Toronto, Canada. Injury Prevention, 26(3), 229–233.

    Article  Google Scholar 

  • Rothman, L., Schwartz, N., Cloutier, M. S., Winters, M., Macarthur, C., Hagel, B. E., Macpherson, A. K., El Amiri, N., Fuselli, P., & Howard, A. W. (2022). Child pedestrian and cyclist injuries, and the built and social environment across canadian cities: The child active transportation safety and the Environment Study (CHASE). Injury Prevention, 28(4), 311–317.

    Article  Google Scholar 

  • Rus, M., Tasențe, T., & Rus, C. V. (2020). Preventive Behaviors and Attitudes of the Children as Active Participants in Road Traffic: Array. Acta Universitatis Danubius. Administratio, 11(1). Retrieved from https://dj.univ-danubius.ro/index.php/AUDA/article/view/138

  • Schuurman, N., Walker, B. B., Swanlund, D., Amram, O., & Yanchar, N. L. (2020). Qualitative field observation of pedestrian injury hotspots: a mixed-methods approach for developing built-and socioeconomic-environmental risk signatures. International Journal of Environmental Research and Public Health, 17(6), 2066.

  • Shabanikiya, H., Hashtarkhani, S., Bergquist, R., Bagheri, N., VafaeiNejad, R., Amiri-Gholanlou, M., Akbari, T., & Kiani, B. (2020). Multiple-scale spatial analysis of paediatric, pedestrian road traffic injuries in a major city in North-Eastern Iran 2015–2019. BMC Public Health, 20(1), 1–11.

    Article  Google Scholar 

  • Silverman, J. D., Hutchison, M. G., & Cusimano, M. D. (2013). Association between neighbourhood marginalization and pedestrian and cyclist collisions in Toronto intersections. Canadian Journal of Public Health, 104, e405–e409.

    Article  Google Scholar 

  • Song, C., Kwan, M. P., & Zhu, J. (2017). Modeling fire occurrence at the city scale: A comparison between geographically weighted regression and global linear regression. International Journal of Environmental Research and Public Health, 14(4), 396.

    Article  Google Scholar 

  • Soroori, E., Mohammadzadeh Moghaddam, A., & Salehi, M. (2021). Modeling spatial nonstationary and overdispersed crash data: Development and comparative analysis of global and geographically weighted regression models applied to macrolevel injury crash data. Journal of Transportation Safety and Security, 13(9), 1000–1024. https://doi.org/10.1080/19439962.2020.1712671

    Article  Google Scholar 

  • Stevenson, M. (2006). Building safer environments: Injury, safety, and our surroundings. Injury Prevention, 12(1), 1–3.

    Article  Google Scholar 

  • Sun, Z., Wang, J., Chen, Y., & Lu, H. (2018). Influence factors on injury severity of traffic accidents and differences in urban functional zones: The empirical analysis of Beijing. International Journal of Environmental Research and Public Health, 15(12), 2722.

    Article  Google Scholar 

  • Tetali, S., Edwards, P., Murthy, G. V. S., & Roberts, I. (2016). Road traffic injuries to children during the school commute in Hyderabad, India: Cross-sectional survey. Injury Prevention, 22(3), 171–175.

    Article  Google Scholar 

  • Tiwari, G. (1999). Towards a sustainable urban transport system: Planning for non-motorized vehicles in cities. Transport and Communications Bulletin for Asia and the Pacific, 68, 49–66.

    Google Scholar 

  • Wang, H., Schwebel, D. C., Tan, D., Shi, L., & Miao, L. (2018). Gender differences in children’s pedestrian behaviors: Developmental effects. Journal of Safety Research, 67, 127–133.

    Article  Google Scholar 

  • World Health Organization. (2018). Global status report on road safety 2018. available at https://www.who.int/publications/i/item/9789241565684. Accessed on 1 March 2023.

  • Xiao, D., Xu, X., & Duan, L. (2019). Spatial-temporal analysis of injury severity with geographically weighted panel logistic regression model. Journal of Advanced Transportation, 2019. https://doi.org/10.1155/2019/8521649

  • Xie, B., An, Z., Zheng, Y., & Li, Z. (2019). Incorporating transportation safety into land use planning: Pre-assessment of land use conversion effects on severe crashes in urban China. Applied Geography, 103, 1–11.

    Article  Google Scholar 

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Acknowledgements

We express our gratitude to Mashhad Municipality for their provision of spatial data. Additionally, we extend our appreciation to Mashhad University of Medical Sciences for their provision of data on Children Pedestrian Road Traffic Collisions.

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Authors and Affiliations

  1. Department of Civil Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

    Emad Soroori & Soraya Ghasemi

  2. School of Public Health, University of Montreal, Montreal, Canada

    Behzad Kiani

  3. Department of Geography and Urban Planning, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran

    Alireza Mohammadi

  4. Social Determinants of Health Research Centre, Mashhad University of Medical Sciences, Mashhad, Iran

    Hamidreza Shabanikiya

  5. Ingerod, Brastad, Sweden (formerly with the UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases, World Health Organization), Geneva, Switzerland

    Robert Bergquist

  6. Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Fatemeh Kiani

  7. Mental Health Policy Unit, Health Research Institute, The University of Canberra, Canberra, Australia

    Hossein Tabatabaei-Jafari

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  1. Emad Soroori
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Correspondence to Behzad Kiani.

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Soroori, E., Kiani, B., Ghasemi, S. et al. Spatial Association Between Urban Neighbourhood Characteristics ‎‎and ‎‎‎Child Pedestrian–Motor Vehicle Collision‎s. Appl. Spatial Analysis 16, 1443–1462 (2023). https://doi.org/10.1007/s12061-023-09519-w

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