Data from the Fatality Analysis Reporting System (FARS), maintained by the National Highway Traffic Safety Administration (NHTSA), have shown a consistent relationship between rural and urban crashes, with approximately 55 percent of fatal crashes on rural roads each year. Figure 1 shows the number of rural and urban fatal crashes reported in FARS from 1986 through 1993.
The advent of market research tools that combine geographic, demographic, and life-style information (now termed "geodemographics") makes it possible to determine the relative involvement of rural and urban dwellers in fatal crashes at the national level. Geodemographic software permits researchers to use individuals' postal zip codes to characterize the urbanization of their residence location. In 1988, FARS began recording drivers' residence zip codes obtained from the drivers' license recorded on the police accident report.
NHTSA recently conducted several independent studies of different population subgroups using geodemographic methods to facilitate development of safety programs tailored specially for each subgroup (Bradbard, S.L. & Lisboa-Farrow, E., 1995; Graham, J.D., Isaac, N.E., Kennedy, B., & Winsten, J., 1995; Bradbard, S.L., Panlener, J.C., & Lisboa-Farrow, E.,1996). These analyses revealed that, in each subgroup examined, residents of rural areas and small towns were consistently over-represented in fatal crashes relative to their numbers in the population.
This report augments and presents the data from these analyses and investigates the extent to which rural and urban residents were involved in crashes on rural or urban roadways.
We used the 1995 update of Compass Prizm geodemographic software by Claritas Corporation to place each driver's residence location into one of five levels of population density: Rural, Town, 2nd City, Suburban, Urban. Rural and Town represent the most sparsely-populated areas. Second City locations include places larger than towns but not major metropolitan areas, such as Youngstown, OH, or Fresno, CA. They might also be "edge" cities, located on the exurban fringe of a major metropolitan area, such as Reston, VA or Frederick, MD, on the outskirts of Washington, DC. Suburban and Urban zip codes represent the most densely populated areas (Claritas, 1995a, 1995b, 1996).
In geodemographic analyses, the primary measure of a population's level of involvement is the "index of concentration." This index is obtained by dividing the percentage of a population sub-group involved in an activity by the percentage of the sub-group population in the whole population and multiplying by 100. If the characteristic of interest is distributed evenly throughout the population, then the index of concentration would be 100.
For example, if 20 percent of the male drivers involved in fatal crashes lived in small towns and 20 percent of the male population lived in small towns, the index of concentration would be 100 (100 x 20% involved ÷ 20% resident). If 40 percent of male drivers involved in fatal crashes lived in small towns, the index would be 200 (100 x 40% involved ÷ 20% resident), indicating that twice as many were involved as would be expected if everyone in the whole population had the same tendency toward involvement in fatal crashes. Values below 100 indicate lower- than-expected involvement.
We conducted separate analyses of several sub-populations, including (a) drivers involved in crashes resulting in the death of a child; (b) drivers involved in crashes in which alcohol was detected in the drivers' blood (at three levels of BAC); and (c) young drivers in two age groups according to legal drinking age (15-20 and 21-25). In addition, we analyzed the whole population of drivers involved in fatal crashes by gender.
The analyses of each subpopulation compared the percentage of drivers in fatal crashes in each social cluster to the percentage of the base population of that social cluster. In general, the base population represents the number and percent of the U.S. population age 15 and older residing in the areas included in each social cluster. Because the age categories used by Compass PRIZM did not correspond exactly to age categories for the youth crash analyses, we used the PRIZM breakdown of 18-24 as a base for both.
|Group||Total Population 15+||Drivers in Crashes involving Child Fatalities||Drivers in Crashes where Restraint Used||Drivers in Crashes where No Restraint Used|
|* Table 1 does not include 197 child fatalities for which restraint use was unknown.|
|Group||Population 15+||Drivers in Fatal Crashes where BAC = .08 to .09||Drivers in Fatal Crashes where BAC = .10 to .14||Drivers in Fatal Crashes where BAC = .15 & above|
Figure 2 presents graphically the indexes of concentration for drivers involved in alcohol-related fatalities for each cluster. For all BAC levels, the Rural residents' index of concentration was about 200, twice the expected ratio of 100.
|Group||18-24 YO Population||15-20 YO Fatalities||21-25 YO Fatalities|
|GROUP||Total Population 15+||Drivers 15+ Involved in Fatal Crashes||INDEX|
Table 5 shows the over-involvement in fatal crashes of Rural male drivers. The majority of males (63 percent) resided in Urban, Suburban, and 2nd City cluster locations but were involved in only 36 percent of male-driver fatal crashes (index=57). The majority of fatal crashes (44 percent) involved Rural males. However, only 18 percent of the male population resided in the Rural cluster, resulting in an index of concentration of 252.
|GROUP||Males in Population||Male Drivers involved in Fatal Crashes||INDEX|
Table 6 shows that 31 percent of female-driver fatal crashes involved Rural females with only 17 percent of the female population residing in that cluster location, yielding an index of concentration of 180. Although 54 percent of female-driver fatal crashes involved Rural and Small Town residents, these females made up only 37 percent of the female population. Sixty- three percent lived in Suburban, Urban, and Second City locations but these females were involved in only 46% of the fatal crashes.
|GROUP||Females in Population||Female Drivers Involved in Fatal Crashes||INDEX|
Figure 3 summarizes the results of the preceding analyses, showing the index of concentration for each population subgroup by the residence location of drivers involved in fatal crashes. These results show that rural residents were heavily over- involved in fatal crashes, while residents of small towns were slightly over-involved. Drivers residing in more urbanized areas were generally under-involved in fatal crashes.
To determine the approximate magnitude of this bias, we adjusted the population base by the proportion of licensed drivers in the place-of-residence categories reported in the 1990 Nationwide Personal Transportation Survey (NPTS)(Hu & Young, 1993). The 1990 NPTS uses only three categories for population density: MSA, central city; MSA, non-central city; and non-MSA. The licensing rates for these categories were 85.0%, 92.1%, and 90.5%, respectively. Table 7 shows the original and adjusted bases and the resulting concentration indexes.
|GROUP||Total Population 15+||Drivers 15+ Involved in
|% Lic Drivers||Estimated Licensed Drivers|
Using the estimated distribution of licensed drivers as the comparison base has only a small effect on the index of concentration across the five groups. The bias introduced by using the population distribution was one to three points on the index of concentration. The different methods produced less than one percent difference for the small town and rural categories.
|MSA* Central City||MSA Non Central City||Non MSA|
|Personal Miles Traveled (PMT) (millions)||705,454||1,072,689||537,130|
|% PMT by Personal Vehicle||84.1||87.9||93.8|
|Miles Traveled by Personal Vehicle (millions)||593,287||942,894||503,828|
|Number of Licensed Drivers (thousands)||56,180||70,103||36,742|
|Personal Vehicle Miles per Licensed Driver (thousands)||10.56||13.45||13.71|
|*MSA=Metropolitan Statistical Area|
While the number of crashes was smaller, the pattern of involvement of urban residents in urban crashes was the mirror image of the rural pattern: About 3 out of 4 fatal crashes on urban roads involved drivers residing in Suburban, Urban, or 2nd City clusters.
|FARS Crash Location||Rural & Small-Town Residents||Suburban, Urban, 2nd City Residents||TOTAL|
|Rural||114,709 (41.2)||43,070 (15.5)||157,779 (56.7)|
|Urban||33,071 (11.9)||87,273 (31.4)||120,344 (43.3)|
|TOTAL||147,780 (53.1)||130,343 (46.9)||278,123 (100.0)|
The analysis shows, conversely, that urban residents are primarily involved in urban crashes. By and large, people have crashes where they live, and by implication, where they drive: Rural residents crash on rural roads and urban residents crash on urban roads.
Highway safety researchers suggest a number of reasons for increased risk of fatal crashes on rural roads. Design elements (e.g., two lane highways, narrow or nonexistent shoulders, and limited sight distance due to hills and curves) contribute to this risk. A majority of all fatal crashes occur on two-lane, two-way highways, with a large percentage of these highways located in rural areas. Higher speeds are also a contributing factor. For example, speed limit and land use data show that 40 percent of all 1992 fatal crashes occurred on rural roads posted at 55 mph or higher (NHTSA, 1994a).
Economic and behavioral factors also influence crash outcomes. Lower rates of seat belt and child safety seat use, both of which characterize rural residents, contribute to increasing seriousness of injuries (NHTSA, 1995). Delays in discovery and extended Emergency Medical Services (EMS) response times (often a 10 to 30 minute delay in ambulance response and 30 to 60 minute additional travel time to hospitals), and lack of nearby emergency and trauma care facilities decrease the likelihood of surviving serious crashes in remote areas.
In order to address the unique needs of rural residents, NHTSA has adopted the techniques of social marketing, using geodemographics to help locate potential target populations and focus-group interviews and surveys to assist in developing and testing thematic messages and communication channels.
NHTSA has developed an integrated injury-control approach involving partnerships among health care, government, businesses, and community groups. While the rural motor-vehicle injury problem is too complex and resources are too limited for any one group to solve alone, rural community partnerships involving government, police, fire, EMS, schools, businesses, community groups, health care providers, and public health agencies may hold the key to reducing the personal, emotional, and financial impacts on rural residents due to motor-vehicle crashes.
Bradbard, S.L., Panlener, J.C., & Lisboa-Farrow, (1996) Program strategies for increasing safety belt usage in rural areas, DOT- HS-808-505, U.S. Department of Transportation, National Highway Traffic Safety Administration, Washington, D.C.
Claritas, Inc., (1995a) Cluster Snapshots: Getting to Know the 62 Clusters, Arlington, VA.
Claritas, Inc., (1995b) PRIZM Lifestyle Segmentation, Arlington, VA.
Claritas, Inc., (1996) Cluster Narratives: Summary Lifestyle Descriptions, Arlington, VA.
Graham, J.D., Isaac, N.E., Kennedy, B., & Winsten, J., (1996) Strategic advertising plans to deter drunk driving. DOT-HS-806- 611, U.S. Department of Transportation, National Highway Traffic Safety Administration, Washington, D.C.
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NHTSA, (1995) National Occupant Protection Use Survey: Controlled Intersection Study, Research Note, U.S. Department of Transportation, National Highway Traffic Safety Administration, National Center for Statistics and Analysis, Washington, D.C.
NHTSA (1996) Rural and Urban Crashes: a Comparative Analysis, DOT-HS-808-450, U.S. Department of Transportation, National Highway Traffic Safety Administration, Washington, D.C.