Table 1 - uploaded by Corinne Peek-Asa
Content may be subject to copyright.
Fatal crash incidence density, injury fatality rate, crash injury rate, and crash incidence density
Source publication
Motor vehicle crash fatality rates have been consistently higher in rural areas than in urban areas. However, the explanations for these differences are less clear. In this study the decomposition method was used to explore the factors associated with increased fatal crash involvement rates in rural communities.
Using national databases, the fatal...
Context in source publication
Context 1
... we repeated the decomposition restricting the analysis to crashes that caused severe vehicular damage. Table 1 summarizes the data used in this study: the number of fatal crashes, the number of crashes with injuries, the total number of crashes, and the number of miles driven. As expected, the fatal crash incidence density, the injury fatality rate, and the crash injury rate were all higher in rural than in urban areas, but the crash incidence density was lower in rural than in urban areas. ...
Similar publications
To assess the secondary health impacts of a traffic calming scheme on a community.
Prospective cohort study of a randomly selected sample of the local community using postal questionnaires and pedestrian counts on the affected road six months before and six months after the implementation of the scheme. The setting was a community in which a traffi...
Weak linkages between health providers and slum communities hinder the improvement of health services for India's urban poor. To address this issue, an urban health programme is implementing two approaches in Indore city, Madhya Pradesh, the demand–supply linkage approach and ward coordination approach. The former is based on the premise that build...
Objective
National data have shown worse endometrial cancer (EC) outcomes among racial and ethnic minorities. We aimed to analyze EC patient outcomes within a large urban academic health system, with a focus on patterns of care and recurrence rates.
Methods
This was a retrospective chart review of EC patients at three system hospitals from 1/1/07–...
Poor air quality, especially in urban regions among low-and middle-income countries such as India poses a significant healthcare challenge. Amongst urban areas, metropolitan cities garner the utmost importance for air quality related policies and studies with limited studies from tier II cities which are thought to be relatively immune to air pollu...
This article describes the effective use of telemedicine for the urban adult patient. A successful pediatric telemedicine program was expanded to include care for adults. The pilot program resulted in high levels of patient satisfaction, decreased loss of work time, and decrease in inappropriate use of the emergency department.
Citations
... Levinson et al. 11 calculated crash costs per vehicle-kilometertraveled (vkt), reporting $0.04/vkt for rural highways and $0.02/vkt for urban highways. This supports previous observations that rural areas suffer a higher crash costs 12,13 . Parry 14 examined external costs borne by others, finding an average of 2.2-6.6 cents per mile annually for crashes with and without fatalities during 1998-2000. ...
Crash cost estimates are essential for evaluating road safety management policies and assessing the economic benefits of safety improvements. Existing studies often rely on aggregated crash data, assuming an even distribution of incidents, which overlooks significant spatial variations influenced by road characteristics and traffic conditions. This research presents a methodological framework for link-based crash cost analysis that considers both internal and external costs, enabling detailed quantification at a localized level. By employing safety performance functions and ordered probit models, we estimate on-road crash rates by crash type and injury severity, distinguishing between internal costs borne by individuals involved in crashes and external costs that impact victims, insurers, and government agencies. This framework is applied to the Minneapolis-St. Paul metropolitan area for a proof-of-concept. Our findings reveal that the costs incurred by drivers are higher than those imposed on others, and that highways are generally safer than surface streets. However, these crash costs are too low compared to the value of travel time to significantly influence route choices, even when drivers are aware of these costs. To enhance effective decision-making, related policies should consider offering incentives for safe driving practices. Future research on the practical applications of this framework is encouraged to maintain a dynamic dataset that reflects ongoing changes in road safety conditions.
... In academia, the HPMS dataset is a vital publicly available resource for researching a variety of transportation-related topics. It provides essential data for assessing infrastructure conditions, analyzing traffic speed and congestion, and studying road safety and factors contributing to accidents [11][12][13][14][15][16] . Additionally, researchers use it to evaluate the sustainability and resiliency of the U.S. transportation systems in the face of climate change, air pollution exposure, and extreme weather events [17][18][19][20][21][22] . ...
The Highway Performance Monitoring System, managed by the Federal Highway Administration, provides essential data on average annual daily traffic across U.S. roadways, but it has limited representation of medium- and heavy-duty vehicles on non-interstate roads. This gap limits research and policy analysis on the impacts of truck traffic, especially concerning air quality and public health. To address this, we use random forest regression to estimate medium- and heavy-duty vehicle traffic volumes in areas with sparse data. This results in a more comprehensive dataset, which enables the estimation of traffic density at the census block level as a proxy for traffic-related air pollution exposure. Our high-resolution spatial data products, rigorously validated, provide a more accurate representation of truck traffic and its environmental and health impacts. These datasets are valuable for transportation planning, public health research, and policy decisions aimed at mitigating the effects of truck traffic on vulnerable communities exposed to air pollution.
... This study finds that, when crashes occur in rural areas, there is an increased possibility of severe outcomes, which concurs with the earlier literature [36]. Extreme terrain, lower rates of seatbelt use, the propensity to drive at higher speed and under the influence of alcohol or drugs [63] and longer response time to conduct rescue operations can be possible contributing factors to the higher number of severe crashes in rural areas [64][65][66]. Meanwhile, crashes in residential areas are associated with a reduced possibility of a severe injury outcome, likely because physically impaired drivers might not be driving at very high speeds in residential areas. ...
Drivers with physical and/or mental impairments face many driving challenges. However, not many studies have been carried out to understand the factors that contribute to crashes involving these drivers and how these factors influence their crash outcomes. This study aims to address this gap in the road safety literature. The study uses historical crash data from the State of Alabama for at-fault physically impaired drivers and utilizes a random parameter with heterogeneity in a mean modeling approach to account for unobserved heterogeneity. The model estimation results reveal that in rural areas, driving over the speed limit, the time of crash being between 6.00 p.m. and 11.59 p.m., younger drivers, employed and distracted drivers were associated with severe injuries. Minor injury crashes are found to be associated with female drivers, state roads and residential areas. Finally, property-damage-only crashes are more associated with weekdays, driving under the influence of alcohol or drugs, a road with left curvature, driving too fast for the road conditions and intersections. The results obtained provide a foundation for the adoption of targeted countermeasures to improve highway safety for physically impaired drivers and all road users in general.
... 4 The fatal crash rate in rural regions exceeds twice that of urban areas, which is generally attributed to lower safety measures adoption, leading to more severe crashes, delayed medical attention, and varying medical response quality. 5 Delayed on-scene access to care in rural settings and prehospital time exceeding 60 min have been associated with higher odds of mortality. 2,6,7 Moreover, limited access to trauma care facilities, particularly in remote areas, increases the emergency department mortality rates. ...
Keywords: Access to health care Delay in care Riyadh region Rural healthcare Standardized trauma systems Trauma activation criteria Trauma burden Trauma care a b s t r a c t Introduction: Trauma is a major cause of death and disability among young adults in Saudi Arabia, with a road traffic fatality rate three times higher than other high-income countries. The vast expanse of the Riyadh region comprises 21 governorates over 156,078 square miles, most of which is rural. Although delays in access to trauma care pose a significant mortality and economic burden, regions at highest risk of delays have not been previously studied. This paper aims to identify the trauma center distribution, trauma burden, and areas with delayed access to trauma care in the rural governorates of the Riyadh region. Methods: We conducted a retrospective review of 24,268 reports from 17 rural governorates in the Riyadh region from the official data registry of the Red Crescent of Saudi Arabia from January 2021 to March 2023. Higher severity cases were classified under the red criteria (for age 15-64 ys: systolic blood pressure (SBP) < 90 mmHg or heart rate > SBP); for age 65 ys: SBP <110 mmHg or heart rate > SBP) based on established trauma activation criteria. We geospatially mapped all level 1-3 trauma centers in the rural governorates of the Riyadh region with an overlay of trauma burden, and identified red criteria cases and those that had delayed access to trauma centers in each of the governorates. Data were mapped using Quantum Geographic Information System, and analysis was performed using R statistics. Results: Rural Riyadh lacks level 1 trauma centers, with level 3 facilities primarily delivering trauma care. Among the reported trauma cases, majority were classified under the red criteria (67.7%, n ¼ 16,433). Al-Kharj emerged as a hotspot for trauma cases, reporting the highest number of cases (21.4%, n ¼ 5202) and red criteria cases (21.4%, n ¼ 3512), followed by Al-Quwayiyah (14.4%, n ¼ 3490) and Al-Majma'ah (9.8%, n ¼ 2369). Blunt trauma predominated (79.4%, n ¼ 19,280), with a substantial portion meeting the red criteria (62.4%, ScienceDirect jo urnal homepage: www.J ou rn alofS urgicalR esearch.com j o u r n a l o f s u r g i c a l r e s e a r c h d e c e m b e r 2 0 2 4 (3 0 4) 2 5 2 e2 5 8
... Earlier studies have reported that low-income areas experience worse injury severity compared to high-income areas [11,12], and the higher the educational level, the lower the risk of fatal and nonfatal crash injuries [13,14]. Also, fatal crash injury rates are significantly higher in rural areas compared to urban areas [15]; road users who live in rural areas experience longer emergency medical service response times and are more likely to experience fatal crash injuries without resuscitation [16][17][18]. The built (such as intersections, highways, ramps, and work zones) and natural (such as rain, fog, and snow) road environments are associated with fatal crash injuries, and the impact of the built and natural road environment on fatal crash injury differs in rurality/urbanicity [19,20]. ...
Social determinants of health (SDoH) are nonmedical factors impacting health outcomes. We evaluated the relationship between the county-level measure of SDoH and county-level fatal crash counts among geriatric and non-geriatric road users. We pooled data from the Fatality Analysis Reporting System and limited our analyses to the 3108 contiguous US counties. The outcome measures were county-level fatal crash counts involving (1) geriatric (65 years and older), (2) non-geriatric, and (3) all road users. The predictor variable was the multidimensional deprivation index (MDI), a composite measure of SDoH, measured as a three-level categorical variable defined as very highly deprived, highly deprived, and average-to-low deprived. We performed a Bayesian spatial Poisson regression analysis using integrated nested Laplace approximations and reported the adjusted crash fatality rate ratios (plus 95% credible intervals (CrI)). The median (Q1, Q3) standardized mortality rate ratios among geriatric and non-geriatric road users were 1.3 (0.6, 2.5) and 1.6 (0.9, 2.7), respectively. Counties classified as very highly deprived had 23% (95% CrI: 1.10–1.38) and 20% (95% CI: 1.08–1.32) increased geriatric and non-geriatric fatality crash rate ratios. In conclusion, improving county-level SDoH may reduce the county-level fatal rate ratios equally among geriatric and non-geriatric road users.
... Some studies, as Clark and Cushing [22], provide evidence that increased distance between people and/or medical facilities is a determinant of mortality from vehicle collisions. In fact, many studies have shown that the risk of crash depends on the distance driven [10,25] and the severity of traffic crashes is higher on low-density areas than in urban areas [6,56,75]. In Spain, over 52% of all road traffic fatalities in 2021 occurred on rural roads [26]. ...
... In our study we have analyzed the effect of the population density of both the crash location and the driver's residence on the injury outcome. We found that more crashes with injured victims occur in more densely populated areas,however, the ratio of serious injuries and fatalities to total injury crashes rises as the population density of the area falls, a finding that is consistent with previous studies [8,39,75]. The literature review of Keeves et al. [35] concluded that of the studies reporting injury-related mortality, there were a greater risk of fatality following an injury in rural areas. ...
The concentration of population in cities and processes of rural depopulation coupled with the generational shift to older societies represent new challenges in road safety. Here, we examine the severity of injuries suffered by the occupants of motor vehicles involved in a crash based on the population density of the area in which the crash occurs, the driver’s age and the density of their place of residence. We conduct the study in Spain, a country with one of the highest levels of elderly population concentrated in rural areas in Europe. Relational methods are used to match Eurostat’s urbanization classifications with the accident database of Spain’s Directorate General of Traffic so as to correlate each crash with the population density of the place where it occurred. A set of generalized linear models with random effects is fitted to analyze the relationship between population density and the bodily injury severity of the occupants of the vehicle(s) involved in a crash, measuring the effect of drivers’ relocation and aging by geographical area. Independence of injury severity and the degree of urbanization was rejected at the 5% significance level. While 53.8% of the Spanish population is living in densely populated areas and only 13.5% in rural areas, the latter concentrates most crashes with fatalities: 2.3 times more than in urban areas (43.5 and 18.6%, respectively). Drivers living in rural areas are more likely to be associated with serious or fatal injuries when involved in a crash in urban and intermediate areas. Moreover, drivers aged over 75 are significantly more likely to be associated with serious and fatal injuries, especially when the crash occurred in urban areas. Recent research alerts on the implications for rural (often elderly) residents of concentrating public services, particularly healthcare, in densely populated areas. Our study shows that motor crashes in more densely populated areas are also a rural health concern. Policy decision-makers need to address this issue to reduce the number of victims and their bodily injury severity.
... Despite greater reliance of driving in rural areas, there is a greater risk of fatalities on rural roads, as US-based studies have shown that older adults are over two-times more likely to have fatal road traffic incidents on rural roads than urban roads (Zwerling et al., 2005). ...
Background and objectives:
Older rural drivers are more dependent on driving than urban drivers to maintain community mobility due to reduced availability of transportation alternatives. Yet it is not understood how cognition impacts driving mobility and road safety across urban vs rural settings. The present study therefore aimed to establish whether cognitive changes impacted driving mobility and road safety differently across rural and urban older drivers.
Research Design and Methods:
969 older drivers (mean age: 71.01) were recruited for a prospective cohort study. Participants completed self-reported driving behaviour and road traffic incident (RTI) history questionnaires before completing an objective cognitive testing battery to establish global cognitive functioning; and were invited back to repeat the study procedure one-year later.
Results:
We find that older rural drivers have a greater driving mobility than older urban drivers and are less likely to reduce their driving mobility over time, as only urban residents with cognitive decline reduced their driving space. We further corroborate previous findings that RTI incidence is greater within urban areas and establish a distinct association between worse cognitive functioning and RTI risk solely in urban residents.
Discussion and implications:
Overall, we show for the first time how the interaction of age-related cognitive changes with geographical settings impact driving mobility and road safety in urban and rural areas. This paves the way for informed policymaking and future research directions to navigate driving cessation and improved road safety in ageing.
... Unlike purely statistical or machine learning-based models, which derive patterns from large datasets, the rule-based model method explicitly incorporates expert knowledge and domain-specific guidelines to interpret crash data [34], [35], [36]. In the context of crash analysis, these rules typically encompass a wide range of factors, including road geometry, traffic control devices, weather conditions, driver behaviors, and vehicle characteristics, among others [8], [37], [38]. By applying these rules to the details of individual crashes, the rule-based model method allows for a structured and comprehensive understanding of the contributing factors of each crash. ...
... These factors necessitate rural and remote residents travelling, sometimes large distances, to access healthcare services. However, travel can be influenced by limited public transport infrastructure (Dassah et al., 2018;Nolan-Isles et al., 2021), poor road quality and design, the age and reliability of private vehicles, and driver age (United States Transport Research Board, 2011;Zwerling et al., 2005). Some OECD member countries have introduced a range of policies designed to address these barriers including: locating primary health services in smaller population centres (OECD, 2020); utilising telehealth services to allow residents to remain in their rural or remote areas whilst accessing healthcare (Eze et al., 2020); implementing alternative models of service delivery (e.g. ...
... Several studies comparing prehospital trauma care in urban and rural areas have found higher mortality rates after trauma, fewer emergency medical health personnel per inhabitant, and longer distances from the incident scene to the trauma hospital in rural areas [6][7][8][19][20][21][22][23][24][25]. Some studies also observed that injuries were more severe in rural than in urban areas [19,20,22]. ...
... Several studies comparing prehospital trauma care in urban and rural areas have found higher mortality rates after trauma, fewer emergency medical health personnel per inhabitant, and longer distances from the incident scene to the trauma hospital in rural areas [6][7][8][19][20][21][22][23][24][25]. Some studies also observed that injuries were more severe in rural than in urban areas [19,20,22]. It is likely that the same challenges apply to rural areas in Norway. ...
Background
A severely injured patient needs fast transportation to a hospital that can provide definitive care. In Norway, approximately 20% of the population live in rural areas. Primary care doctors (PCDs) play an important role in prehospital trauma care. The aim of this study was to investigate how variations in PCD call-outs to severe trauma incidents in Norway were associated with rural-urban settings and time factors.
Methods
In this study on severe trauma patients admitted to Norwegian hospitals from 2012 to 2018, we linked data from four official Norwegian registries. Through this, we investigated the call-out responses of PCDs to severe trauma incidents. In multivariable log-binomial regression models, we investigated whether factors related to rural-urban settings and time factors were associated with PCD call-outs.
Results
There was a significantly higher probability of PCD call-outs to severe trauma incidents in the municipalities in the four most rural centrality categories compared to the most urban category. The largest difference in adjusted relative risk (95% confidence interval (CI)) was 2.08 (1.27–3.41) for centrality category four. PCDs had a significantly higher proportion of call-outs in the Western (RR = 1.46 (1.23–1.73)) and Central Norway (RR = 1.30 (1.08–1.58)) Regional Health Authority areas compared to in the South-Eastern area. We observed a large variation (0.47 to 4.71) in call-out rates to severe trauma incidents per 100,000 inhabitants per year across the 16 Emergency Medical Communication Centre areas in Norway.
Conclusions
Centrality affects the proportion of PCD call-outs to severe trauma incidents, and call-out rates were higher in rural than in urban areas. We found no significant difference in call-out rates according to time factors. Possible consequences of these findings should be further investigated.
