Explaining regional disparities in traffic mortality by decomposing conditional probabilities

Abstract

Background In the United States, the mortality rate from traffic injury is higher in rural and in southern regions, for reasons that are not well understood. Methods For 1754 (56%) of the 3142 US counties, we obtained data allowing for separation of the deaths/population (D/P) rate into deaths/injury (D/I), injuries/crash (I/C), crashes/exposure (C/E), and exposure/population (E/P), with exposure measured as vehicle miles traveled. A “decomposition method” proposed by Li and Baker was extended to study how the contributions of these components were affected by three measures of rural location, as well as southern location. Results The method of Li and Baker extended without difficulty to include non-binary effects and multiple exposures. D/I was by far the most important determinant in the county-to-county variation in D/P, and accounted for the greatest portion of the rural/urban disparity. After controlling for the rural effect, I/C accounted for most of the southern/northern disparity. Conclusions The increased mortality rate from traffic injury in rural areas can be attributed to the increased probability of death given that a person has been injured, possibly due to challenges faced by emergency medical response systems. In southern areas, there is an increased probability of injury given that a person has crashed, possibly due to differences in vehicle, road, or driving conditions.

Evaluating adverse rural crash outcomes using the NHTSA State Data System

“…In all three of the models presented, the risk of an adverse outcome increased as rurality increased, as seen in previous research (Baker et al, 1987; Brown et al, 2000; Gedeborg et al, 2010; Goldstein et al, 2011; Muelleman et al, 2007). In particular, individuals with severe injuries were more likely to die in rural counties, validating previous studies (Brodsky and Hakkert, 1983; Brown, 1979; Muelleman et al, 2007; Travis et al, 2012).…”

“…While this disparity may be partly due to an increased incidence of severe crashes, it appears to be attributable more to the difference in outcome for persons who have been injured (Goldstein et al, 2011; Muelleman et al, 2007). This disparity in outcomes may raise questions about the quality of care delivered by emergency medical services (EMS) and emergency departments (ED), as well as the obvious problems of communication, transportation, and scarce resources in more remote locations (Cummings and O’Keefe, 2000).…”

Contribution of exposure, risk of crash and fatality to explain age- and sex-related differences in traffic-related cyclist mortality rates

“…As a result, decomposition methods provide a way to explain the differences in CCMR between age and sex subgroups in the target population. Although such methods have been widely used in analyses of other road users (Dellinger et al, 2002;Goldstein et al, 2011;Hermans et al, 2006;Zhu et al, 2013), we found only one study (Li and Baker, 1996) that applied this method to identify the determinants of differences in CCMR between males and females in the USA in 1990.…”

Distance matters

“…11 Motor vehicle collisions (MVC) have been shown to be particularly influenced by geographical factors, as several have shown that mortality from MVC is influenced by geographic region, population density, and vehicle miles traveled. 12–15 Further, MVC events are dispersed throughout a trauma system and have a wide range of injury severity that mobilizes the full range of prehospital and trauma center resources. 16 …”