Citation

Palazón-Bru A, Prieto-Castelló MJ, Folgado-de la Rosa DM, Macanás-Martínez A, Mares-García E, Carbonell-Torregrosa ML, Gil-Guillén VF, Cardona-Llorens A, Marhuenda-Amorós D. Int. J. Environ. Res. Public Health 2020; 17(24): e9518.

Copyright

(Copyright © 2020, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/ijerph17249518

PMID

unavailable

Abstract

Predictive factors for fatal traffic accidents have been determined, but not addressed collectively through a predictive model to help determine the probability of mortality and thereby ascertain key points for intervening and decreasing that probability. Data on all road traffic accidents with victims involving a private car or van occurring in Spain in 2015 (164,790 subjects and 79,664 accidents) were analyzed, evaluating 30-day mortality following the accident. As candidate predictors of mortality, variables associated with the accident (weekend, time, number of vehicles, road, brightness, and weather) associated with the vehicle (type and age of vehicle, and other types of vehicles in the accident) and associated with individuals (gender, age, seat belt, and position in the vehicle) were examined. The sample was divided into two groups. In one group, a logistic regression model adapted to a points system was constructed and internally validated, and in the other group the model was externally validated. The points system obtained good discrimination and calibration in both the internal and the external validation. Consequently, a simple tool is available to determine the risk of mortality following a traffic accident, which could be validated in other countries.

Language: en

Keywords

accidents; mortality; death; traffic; models; statistical