Abstract
Purpose: To examine rural–urban differences in motor vehicle fatality (MVF) risk factors.Methods: We used 2017 County Health Rankings data to run stratified regression models to estimate county-level correlates of motor vehicle fatalities (MVFs) by rural and urban location.Results: Rural counties have higher rates of MVFs than urban counties (22 vs. 14 per 100,000, p<0.001). Physical inactivity and uninsurance were associated with higher rates of MVFs, as was having a more racially or ethnically concentrated population and larger percentages of younger or older adults.Conclusion: Interventions to reduce MVFs should take geographic location and population composition into account.
Highlights
IntroductionMortality rates from all five leading causes of death, including motor vehicle fatality (MVF), are higher in rural areas than in urban areas.[1,2] the overall rate of Motor vehicle fatalities (MVFs) is declining, it remains higher in rural areas than in urban areas.[3] In addition to geography, MVF rates are associated with sociodemographic characteristics, including race, ethnicity, age, and gender, which differ between rural and urban communities.[2,4,5,6] For example, MVF rates are highest among American Indian/
Motor vehicle fatalities (MVFs), combined with other types of unintentional injuries, are one of the five leading causes of death in the United States, and the leading cause of death among people of ages 1–44 years.[1,2]Mortality rates from all five leading causes of death, including motor vehicle fatality (MVF), are higher in rural areas than in urban areas.[1,2] the overall rate of MVFs is declining, it remains higher in rural areas than in urban areas.[3]
This study addresses that gap and its results will be useful in tailoring interventions by geographic location to reduce MVFs risk
Summary
Mortality rates from all five leading causes of death, including MVFs, are higher in rural areas than in urban areas.[1,2] the overall rate of MVFs is declining, it remains higher in rural areas than in urban areas.[3] In addition to geography, MVF rates are associated with sociodemographic characteristics, including race, ethnicity, age, and gender, which differ between rural and urban communities.[2,4,5,6] For example, MVF rates are highest among American Indian/. This study addresses that gap and its results will be useful in tailoring interventions by geographic location to reduce MVFs risk
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