A novel approach to study the health consequences of road crashes
Artikel i vetenskaplig tidskrift, 2017
While an association between road crashes and health impairments is well documented, few studies have analysed impairments in relation to crash parameters. The aim of this paper is to describe a novel approach for studying the full complexity of road crashes which allows an analysis of the relationship between crash factors and longer-term health consequences.
A multidisciplinary team investigated road crashes sampled in a Swedish region. The course of events, road environment and crash configuration were studied at the scene and telephone interviews were conducted with drivers. Road users were queried about their health status 1, 6, and 12 months after the crash. To illustrate a potential use of the collected data, the relationship between crash factors and impairments for car occupants after one month was explored using multiple logistic regression.
The sampled data included 176 crashes, 310 vehicles and 430 people. The most common crash characteristics were: multiple vehicle crashes (62%); posted speed limit of ≥ 70km/h (65%); passenger cars (88%); driver age 25–54 years (60%); male drivers/riders (70%). The example analysis of passenger car occupants showed that having an injury with ISS ≥ 1 at the time of crash was a statistically significant predictor for impairment at one month (p < 0.001, OR = 25.42, 95% CI: 8.30, 77.81).
The methodology described in this paper provides information about the full spectrum of road crashes and enables novel analyses of unexplored research questions. Based on the data collected so far and the example analysis presented in the paper, recommendations have been made about future data collection. The proposed data collection methodology enables characterisation of crash factors that are associated with long-term health consequences. The ability to timely identify those at risk provides important opportunities for early intervention to reduce long-term health outcomes also from low severity crashes.