TY - JOUR
T1 - Spatial Association Between Urban Neighbourhood Characteristics and Child Pedestrian–Motor Vehicle Collisions
AU - Soroori, Emad
AU - Kiani, Behzad
AU - Ghasemi, Soraya
AU - Mohammadi, Alireza
AU - Shabanikiya, Hamidreza
AU - Bergquist, Robert
AU - Kiani, Fatemeh
AU - Tabatabaei Jafari, Hossein
N1 - Funding Information:
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.
Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature B.V.
PY - 2023/5/24
Y1 - 2023/5/24
N2 - 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.
AB - 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.
KW - Built environment · Geographically Weighted Negative Binomial Regression · Geographically Weighted Poisson Regression · Child pedestrian · Socioeconomic · Trafc safety
UR - http://www.scopus.com/inward/record.url?scp=85160233544&partnerID=8YFLogxK
U2 - 10.1007/s12061-023-09519-w
DO - 10.1007/s12061-023-09519-w
M3 - Article
AN - SCOPUS:85160233544
SN - 1874-4621
VL - 16
SP - 1443
EP - 1462
JO - Applied Spatial Analysis and Policy
JF - Applied Spatial Analysis and Policy
IS - 4
ER -