Spatial environmental risk factors for pedestrian injury collisions in Ciudad Juárez, Mexico (2008–2009): implications for urban planning

Abstract

The aim of this study is to examine the spatial distribution of pedestrian injury collisions and analyse the environmental (social and physical) risk factors in Ciudad Juarez, Mexico. More specifically, this study investigates the influence of land use, density, traffic and socio-economic characteristics. This cross sectional study is based on pedestrian injury collision data that were collected by the Municipal Transit Police during 2008–2009. This research presents an analysis of vehicle–pedestrian collisions and their spatial risk determinants using mixed methods that included (1) spatial/geographical information systems (GIS) analysis of pedestrian collision data and (2) ordinary least squares (OLS) regression analysis to explain the density of pedestrian collisions data. In our model, we found a higher probability for pedestrian collisions in census tracts with population and employment density, large concentration of commercial/retail land uses and older people (65 and more). Interventions to alleviate this situation including transportation planning such as decentralisation of municipal transport system, investment in road infrastructure – density of traffic lights, pedestrian crossing, road design, improves lane demarcation. Besides, land use planning interventions should be implemented in commercial/retail areas, in particular separating pedestrian and vehicular spaces.

Keywords:

• vehicle–pedestrians collisions
• environmental risks factors
• urban planning
• Ciudad Juárez
• México

Notes

1. The municipal traffic police collect information that included collisions resulting in pedestrian injuries and/or fatalities, hereafter referred to as vehicle–pedestrian collisions (Wier et al., 2009).

2. Its geographic location as a border city allows the residents to import used vehicles from aboard at a lower price than national vehicles, allowing wide sectors of the population to have access to them. This situation influences the high rate of motorisation.

3. The motorisation index is calculated dividing the number of motor vehicle and the population multiplied by 1000.