Luis Miguel Martín-de-Los Reyes1, Virginia Martínez-Ruiz2, Pablo Lardelli-Claret3, Elena Moreno-Roldán3, Daniel Molina-Soberanes1, Eladio Jiménez-Mejías3. 1. Departamento de Medicina Preventiva y Salud Pública, Facultad de Medicina, Universidad de Granada, Granada, España; Programa de Doctorado en Medicina Clínica y Salud Pública, Universidad de Granada, Granada, España. 2. Departamento de Medicina Preventiva y Salud Pública, Facultad de Medicina, Universidad de Granada, Granada, España; CIBER de Epidemiología y Salud Pública (CIBERESP), España; Instituto de Investigación Biosanitaria de Granada, Granada, España. Electronic address: virmruiz@ugr.es. 3. Departamento de Medicina Preventiva y Salud Pública, Facultad de Medicina, Universidad de Granada, Granada, España; CIBER de Epidemiología y Salud Pública (CIBERESP), España; Instituto de Investigación Biosanitaria de Granada, Granada, España.
Abstract
OBJECTIVE: To quantify the magnitude of the association between the type of vehicle and the probability of being responsible for a collision between two or more vehicles. METHOD: From the registry of road crashes with victims maintained by the Spanish Traffic General Directorate (2014 and 2015), a matched case-control study was designed. Cases were offending drivers involved in the 27,630 collisions between two or more vehicles in which only one of the drivers had committed a driving mistake or offence. Each case was matched with the non-offending drivers of the vehicles involved in the same crash: in all, 31,219 controls were included. Apart from the commission of offences and the type of vehicle involved, we got information about other characteristics of the driver (age, sex, etc.) and about the vehicle (age). Odds ratios (OR) were calculated in order to quantify the association between each type of vehicle and the odds of being responsible for the collision, crude and adjusted (by conditioned logistic regression) by the rest of collected variables. RESULTS: In comparison with private cars, bicycles had a lower risk of causing a collision (adjusted OR: .30), and also mopeds (aOR: .52) and buses (aOR: .63). Vans (aOR: 1.19) and four-wheel vehicles (aOR: 1.33) increased the risk. CONCLUSION: Two-wheeled vehicles and buses had a lower risk of causing collisions than private cars. This association is independent of some of the characteristics of the driver, as well as the age of the vehicle.
OBJECTIVE: To quantify the magnitude of the association between the type of vehicle and the probability of being responsible for a collision between two or more vehicles. METHOD: From the registry of road crashes with victims maintained by the Spanish Traffic General Directorate (2014 and 2015), a matched case-control study was designed. Cases were offending drivers involved in the 27,630 collisions between two or more vehicles in which only one of the drivers had committed a driving mistake or offence. Each case was matched with the non-offending drivers of the vehicles involved in the same crash: in all, 31,219 controls were included. Apart from the commission of offences and the type of vehicle involved, we got information about other characteristics of the driver (age, sex, etc.) and about the vehicle (age). Odds ratios (OR) were calculated in order to quantify the association between each type of vehicle and the odds of being responsible for the collision, crude and adjusted (by conditioned logistic regression) by the rest of collected variables. RESULTS: In comparison with private cars, bicycles had a lower risk of causing a collision (adjusted OR: .30), and also mopeds (aOR: .52) and buses (aOR: .63). Vans (aOR: 1.19) and four-wheel vehicles (aOR: 1.33) increased the risk. CONCLUSION: Two-wheeled vehicles and buses had a lower risk of causing collisions than private cars. This association is independent of some of the characteristics of the driver, as well as the age of the vehicle.
Keywords:
Accidente de tráfico; Case-control studies; Estudio de casos y controles; Factores de riesgo; Motocicletas; Motor vehicles; Motorcycles; Risk factors; Traffic accident; Vehículos a motor
Authors: Luis Miguel Martín-delosReyes; Virginia Martínez-Ruiz; Mario Rivera-Izquierdo; José Pulido-Manzanero; Eladio Jiménez-Mejías; Pablo Lardelli-Claret Journal: Int J Environ Res Public Health Date: 2021-12-23 Impact factor: 3.390