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. 2017 Aug;18(5):913-922.
doi: 10.5811/westjem.2017.6.34404. Epub 2017 Jul 25.

Using Geospatial Mapping to Determine the Impact of All-Terrain Vehicle Crashes on Both Rural and Urban Communities

Evelyn S Qin  1 , Charles A Jennissen  1 , Caroline A Wadman  1 , Gerene M Denning  1
Affiliations

Using Geospatial Mapping to Determine the Impact of All-Terrain Vehicle Crashes on Both Rural and Urban Communities

Evelyn S Qin et al. West J Emerg Med. 2017 Aug.

Abstract

Introduction: Deaths and injuries from all-terrain vehicle (ATV) crashes result in approximately 700 deaths each year and more than 100,000 emergency department (ED) visits. Common misconceptions about ATV crashes are a significant barrier to injury prevention efforts, as is the lack of key information about where and how crashes occur. The purpose of this study was to determine ATV crash patterns within a state, and to compare and contrast characteristics of these crashes as a function of crash-site rurality.

Methods: We performed descriptive, comparative, and regression analyses using a statewide off-road vehicle crash and injury database (2002-2013). Comparisons were performed by rurality as defined using the Rural Urban Commuting Area (RUCA) coding system, and we used geographic information system (GIS) software to map crash patterns at the zip code and county levels.

Results: ATV crashes occurred throughout the state; 46% occurred in urban and 54% in rural zip code areas. Comparisons of rider and crash characteristics by rurality showed similarities by sex, age, seating position, on vs. off the road, and crash mechanism. Conversely, helmet use was significantly lower among victims of isolated rural crashes as compared to other victims (p=0.004). Crashes in isolated rural and small rural areas accounted for only 39% of all crashes but resulted in 62% of fatalities. In both rural and urban areas, less than one-quarter of roadway injuries were traffic related. Relative crash rates varied by county, and unique patterns were observed for crashes involving youth and roadway riders. During the study period, 10% and 50% of all crashes occurred in 2% and 20% of the state's counties, respectively.

Conclusion: This study suggests that ATV crashes are a public health concern for both rural and urban communities. However, isolated rural ATV crash victims were less likely to be helmeted, and rural victims were over-represented among fatalities. Traffic was not the major factor in roadway crashes in either rural or urban areas. Unique crash patterns for different riding populations suggest that injury prevention experts and public policy makers should consider the potential impact of geographical location when developing injury prevention interventions.

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Conflict of interest statement

Conflicts of Interest: By the WestJEM article submission agreement, all authors are required to disclose all affiliations, funding sources and financial or management relationships that could be perceived as potential sources of bias. The University of Iowa Department of Emergency Medicine provided the majority of funding for this project. Pilot grant funding for original creation of the database was awarded to Dr. Christopher Buresh and Dr. Charles Jennissen by the Iowa Injury Prevention Research Center (IPRC). The IPRC is supported by the National Center for Injury Prevention and Control (Grant # 1R49CE001167-05). Evelyn Qin was supported through an NIH T35 training grant (T35 HL 7485-36) awarded to the Carver College of Medicine Medical Student Summer Research Program. Caroline Wadman was supported by the Iowa Center for Research by Undergraduates (ICRU).

Figures

Figure 1
Figure 1
Zip code pattern of all-terrain vehicle (ATV) crashes in Iowa recorded in the Off-Road Vehicle Crash and Injury Database for the years 2002–2013 (n=1,832 crashes). Map shows zip code location of crashes with shading based on the Rural Urban Commuting Area (RUCA) coding system.
Figure 2
Figure 2
Patterns of all-terrain vehicle (ATV) crashes in the Off-Road Vehicle Crash and Injury Database for the years 2002–2013 by county (n=1,832 crashes). Values in the indicated ranges (automatically selected by ArcGIS for optimal grouping of crashes) are represented using a shaded scale. Crash rates were based on an estimated number of registered vehicles per county and are expressed as crashes per 100 registered ATVs. Panel a, b: Maps show crash number and crash rate for all crashes in each county. Stars represent the largest cities with the larger star representing four cities in the Des Moines metropolitan area. Panel c, d: Maps show crash number and crash rate for crashes in each county involving youth <16 years old. Panel e, f: Maps show crash number and crash rate for roadway crashes in each county.
See this image and copyright information in PMC

References

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