Center for Injury Research and Prevention

Disparities in Motor Vehicle Crash Death Rates

December 3, 2015

An interesting study exploring the trends in inequalities in motor vehicle crash death rates came across my desk yesterday. Mortality data from the National Center for Health Statistics, along with data from the Current Population Survey and National Household Travel Survey, were used to estimate mortality rates among adults aged 25 years or older from 1995-2010. Overall death rates from motor vehicle crashes declined over the study period, but differences in mortality based on educational levels persisted or worsened during the time. Adjusted death rates were higher among the bottom of the education distributuion, and that disparity increased from 15.3 per 100,000 (which is about twice the risk of death when compared to death rates at the higher end of the education distribution) to 17.9 per 100,000 in 2010 (about 4 times the risk of death when compared to death rates at the higher end of the education distribution). It should be noted that the number of vehicle miles traveled may have been underestimated due to differences in reporting or interpolation, and potentially could have overestimated the risk of crash among those in the lower education brackets. Furthermore, the study examined trends at a large population level, and not at a community or individual level.

As for why this disparity increased over time, the study authors suggest that there may be multiple factors, such as poor infrastructure in neighborhoods (traffic signs, etc), or reduced access to high quality health care in the event of a crash. This study certainly suggests that risk factors based on education level should be further explored at a community level. I think it is safe to assume that adults are frequently driving their children and youth, so this disparity is likely to affect both adults and children as well. These findings remind us that we may need to customize outreach education and infrastructure improvements to target those with lower education levels (for instance, targeting poor signage and road improvements in lower income neighborhoods). 

Click here to read the study abstract.

 

 

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