The role of interaction-based effects on fatal accidents using logic regression

Abstract

Background and Objectives: Road traffic accidents (RTAs) were estimated to be the eighth major cause of death worldwide in 2016. Investigation of various factors alone can distort the results. Thus, it is important to consider interactions among the various factors associated with RTAs. Logic regression was used to investigate the important combinations among traffic accident variables. Methods: In this analytical study, the existing 1-year data from the police accident database in 2014 were examined. The Legal Medicine Organization database was also used to correct death after 30 days. Logic regression, a generalized regression model, was used to explore the interactions among different factors of the accident. Results: Cross-validation results showed the best model in the form of three trees and eight leaves. Being a professional driver and exposure to a heavy vehicle on sandy or earthy road double the chance of death. Operating an unsafe car on a road with curve increases the odds of a fatal crash by 1.65 times. Driver error on a nonresidential road without any shoulders adds 90% to the odds of having a deadly crash. Conclusions: The significance of the interactions between the road and driver factors shows that roads with poor design can cause a driver to make mistakes and increase fatal accidents. Therefore, politicians must consider constructing structures alongside nonresidential roads and proper shoulders, install signs at curves, and repair pavement in order to reduce the fatality of accidents. It is also recommended that manufacturers of commercial vehicles install proper safeguards in all heavy vehicles to reduce fatal accidents.

Keywords

• interactions
• logic regression
• road traffic accidents