How do the definitions of urban and rural matter for transportation safety? Re-interpreting transportation fatalities as an outcome of regional development processes

"Dengue fever is not just urban or rural: Reframing its spatial categorization."

Infectious diseases exploit niches that are often spatially defined as urban and/or rural. Yet spatial research on infectious diseases often fails to define "urban" and "rural" and how these contexts might influence their epidemiology. We use dengue fever, thought to be mostly an urban disease with rural foci, as a device to explore local definitions of urban and rural spaces and the impact of these spaces on dengue risk in the province of Esmeraldas, Ecuador. Ecuador, like many countries, only uses population size and administrative function to define urban and rural locales. Interviews conducted from 2019 to 2021 with 71 residents and 23 health personnel found that they identified the availability of basic services, extent of their control over their environment, and presence of underbrush and weeds (known in Ecuador as monte and maleza and conceptualized in this paper as natural disorder) as important links to their conceptions of space and dengue risk. This broader conceptualization of space articulated by local residents and professionals reflects a more sophisticated approach to characterizing dengue risk than using categories of urban and rural employed by the national census and government. Rather than this dichotomous category of space, dengue fever can be better framed for health interventions in terms of specific environmental features and assemblages of high-risk spaces. An understanding of how community members perceive risk enhances our ability to collaborate with them to develop optimal mitigation strategies.

Urban-rural disparities in childhood obesogenic environments in the United States: Application of differing rural definitions

BACKGROUND

Research is needed that identifies environmental resource disparities and applies multiple rural definitions. Therefore, this study aims to examine urban-rural differences in food and physical activity (PA) environment resource availability by applying several commonly used rural definitions. We also examine differences in resource availability within urban-rural categories that are typically aggregated.

METHODS

Six food environment variables (access to grocery/superstores, farmers' markets, fast food, full-service restaurants, convenience stores, and breastfeeding-friendly facilities) and 4 PA environment variables (access to exercise opportunities and schools, walkability, and violent crimes) were included in the childhood obesogenic environment index (COEI). Total COEI, PA environment, and food environment index scores were generated by calculating the average percentile for related variables. US Department of Agriculture Urban Influence Codes, Office of Management and Budget codes, Rural-Urban Continuum Codes, Census Bureau Population Estimates for percent rural, and Rural Urban Commuting Area Codes were used. One-way ANOVA was used to detect urban-rural differences.

RESULTS

The greatest urban-rural disparities in COEI (F=310.2, P<.0001) and PA environment (F=562.5, P<.0001) were seen using RUCC codes. For food environments, the greatest urban-rural disparities were seen using Census Bureau percent rural categories (food: F=24.9, P<.0001). Comparing remote rural categories, differences were seen for food environments (F=3.1, P=.0270) and PA environments (F=10.2, P<.0001). Comparing metro-adjacent rural categories, differences were seen for PA environment (F=4.7, P=.0090).

CONCLUSION

Findings inform future research on urban and rural environments by outlining major differences between urban-rural classifications in identifying disparities in access to health-promoting resources.

Capturing long-memory properties in road fatality rate series by an autoregressive fractionally integrated moving average model with generalized autoregressive conditional heteroscedasticity: A case study of Florida, the United States, 1975-2018

INTRODUCTION

Time series models play an important role in monitoring and understanding the serial dynamics of road crash exposures, risks, outcomes, and safety performance indicators. The time-series methods applied in previous studies on crash time series analysis assume that the serial dependency decays rapidly or even exponentially. However, this assumption is violated in most cases because of the existence of long-memory properties in the crash time series data. Ignoring the long-memory dependency could result in biased understanding of the dynamics of road traffic crashes.

METHOD

To fill this research gap, this study proposes an autoregressive fractionally integrated moving average model with generalized autoregressive conditional heteroscedasticity (ARFIMA-GARCH) to capture and accommodate the long-memory decencies in the road fatality rate time series. To further investigate how the factors influencing the fatality risks play a role in the long-memory dependence, the effects of exogenous variables are examined in this study. The analysis is conducted based on the road crash fatality data in Florida, USA over 44 years. Results' Conclusions: The case analysis confirmed the existence of long-memory property in the crash fatality time series data by both the joint tests of Augmented Dickey-Fuller and the Phillips-Perron, and the integer order of differencing (≤0.5) in the proposed models. The model results reveal that gasoline price and alcohol consumption per capita is positively associated with road fatality risks, whereas unemployment rate and rural/urban road mileage are negatively related to the road fatality risks.

PRACTICAL APPLICATIONS

The significant influential factors are also found to account for the long-memory serial correlations between road traffic fatalities to some extent.

Study of Design and Construction of Transit Facilities in Rural Areas in USA

The United States rural transit facilities have a considerable impact on annual transportation expenditures as there are many of them and they are geographically dispersed. It is challenging to estimate the design and construction costs of the facilities, as the historical and documented cost database is insufficient; therefore, the ultimate aim of this study was to establish a baseline estimate for design and construction costs. Additionally, the key information associated with the different aspects of rural transit facility projects was also provided in this study. Interviews were conducted with professional managers of different departments of transportation (DOTs) who were involved in rural transit projects. A structured survey was then developed and distributed to various DOT representatives, and 26 of them were completed and returned. Two regression models were generated by utilizing the survey data to predict the design and construction costs of rural transit facilities, based on the size of the projects. Furthermore, the results revealed that issues arising from soil conditions and unexpected underground conditions are frequently risk factors for construction of transit facilities. It was also concluded that the popular approach to estimating the cost of the design and construction phases associated with transit facility projects is to use the data from similar projects. These findings support the need for additional literature to provide a baseline estimate for design and construction costs and key information of different important aspects of rural transit facilities.

Characteristics of crashes and injuries among 14 and 15 year old drivers, by rurality

PURPOSE

Motor-vehicle crashes continue to be the leading cause of death for teenagers in the United States. The United States has some of the youngest legal driving ages worldwide. The objective of this study was to determine rates and factors associated with injury crashes among 14- and 15-year-old drivers and how these varied by rurality.

METHODS

Data for this cross-sectional study of 14- and 15-year-old drivers were obtained from the Iowa Department of Transportation from 2001 to 2013. Crash and injury crash rates were calculated by rurality. The relationship between crash and driver factors and injury was assessed using logistic regression.

FINDINGS

Teen drivers, aged 14 and 15 years, had a statewide crash rate of 8 per 1,000 drivers from 2001 to 2013. The majority of crashes occurred in urban areas (51%), followed by in town (29%), remote rural areas (13%), and suburban areas (7%). Crash and injury crash rates increased as level of rurality increased. The odds of an injury crash increased more than 10-fold with the presence of multiple other teens as passengers, compared to no passengers (OR = 10.7, 95% CI: 7.1-16.2).

CONCLUSIONS

Although 14- and 15-year-old drivers in Iowa have either limited unsupervised (school permits) or supervised only driving restrictions, they are overrepresented in terms of crashes and injury crashes. Rural roads and multiple teen passengers are particularly problematic in terms of injury outcomes. Practical applications: Results from this study support passenger restrictions and teen driving interventions designed with a rural focus.

Geoclinical analyses for areas at high risk for motorcycle-related road traffic injury in a district in Malaysia

Objective:

The goal of this prospective cross-sectional study was particularly to collect data on the epidemiology, the pattern of injury among motorcyclists and to relate with spatial data in a local district.

Methods:

It involved data collection from prehospital care and inhospital care record. In addition, it utilized geospatial ARCGIS® version 10.1 software in the identification of hotspot location of road traffic injury. Written informed consent was obtained from patient(s) or relatives for their anonymized information to be published in any article.

Results:

A total of 439 cases were recruited over 10 months. The mean age (standard deviation) of the motorvehicle crash victims was 26.04 (15.26) years. Male comprised 302 (73.3%) of the cases. A total of 176 (42.7%) of the victims were between the ages of 20–40 years. A total of 176 (42.7%) of the motorcyclists admitted were wearing the safety helmets either from the history taking or from the witness. A total of 117 (28.4%) and 28 (6.8%) of the victims were admitted to the general wards and critical care units, respectively for further management. The mean (standard deviation) length of hospital stays was 7.19 (6.94) days. Based on hotspot mapping using ARCGIS 10.1, most of the motorvehicle crash cases occurred mainly within the specific borough. This finding concurred with the locations of the state roads involved that traversed mainly within the same borough. Further geospatial and temporal analysis showed that most of the motorvehicle crash that occurred during the weekend were located within the suburban areas.

Conclusion:

Motorcyclists, being male and young age are the vulnerable group of road users commonly injured on our road. The initial geospatial analysis of injury-related motorvehicle crash cases has shown common hotspot trending along certain roads and borough within the district. This new knowledge can be used in the future for preventive and road safety programs in high-risk areas.

Rural and Urban Differences in Passenger-Vehicle-Occupant Deaths and Seat Belt Use Among Adults - United States, 2014

PROBLEM/CONDITION

Motor-vehicle crashes are a leading cause of death in the United States. Compared with urban residents, rural residents are at an increased risk for death from crashes and are less likely to wear seat belts. These differences have not been well described by levels of rurality.

REPORTING PERIOD

2014.

DESCRIPTION OF SYSTEMS

Data from the Fatality Analysis Reporting System (FARS) and the Behavioral Risk Factor Surveillance System (BRFSS) were used to identify passenger-vehicle-occupant deaths from motor-vehicle crashes and estimate the prevalence of seat belt use. FARS, a census of U.S. motor-vehicle crashes involving one or more deaths, was used to identify passenger-vehicle-occupant deaths among adults aged ≥18 years. Passenger-vehicle occupants were defined as persons driving or riding in passenger cars, light trucks, vans, or sport utility vehicles. Death rates per 100,000 population, age-adjusted to the 2000 U.S. standard population and the proportion of occupants who were unrestrained at the time of the fatal crash, were calculated. BRFSS, an annual, state-based, random-digit-dialed telephone survey of the noninstitutionalized U.S. civilian population aged ≥18 years, was used to estimate prevalence of seat belt use. FARS and BRFSS data were analyzed by a six-level rural-urban designation, based on the U.S. Department of Agriculture 2013 rural-urban continuum codes, and stratified by census region and type of state seat belt enforcement law (primary or secondary).

RESULTS

Within each census region, age-adjusted passenger-vehicle-occupant death rates per 100,000 population increased with increasing rurality, from the most urban to the most rural counties: South, 6.8 to 29.2; Midwest, 5.3 to 25.8; West, 3.9 to 40.0; and Northeast, 3.5 to 10.8. (For the Northeast, data for the most rural counties were not reported because of suppression criteria; comparison is for the most urban to the second-most rural counties.) Similarly, the proportion of occupants who were unrestrained at the time of the fatal crash increased as rurality increased. Self-reported seat belt use in the United States decreased with increasing rurality, ranging from 88.8% in the most urban counties to 74.7% in the most rural counties. Similar differences in age-adjusted death rates and seat belt use were observed in states with primary and secondary seat belt enforcement laws.

INTERPRETATION

Rurality was associated with higher age-adjusted passenger-vehicle-occupant death rates, a higher proportion of unrestrained passenger-vehicle-occupant deaths, and lower seat belt use among adults in all census regions and regardless of state seat belt enforcement type.

PUBLIC HEALTH ACTIONS

Seat belt use decreases and age-adjusted passenger-vehicle-occupant death rates increase with increasing levels of rurality. Improving seat belt use remains a critical strategy to reduce crash-related deaths in the United States, especially in rural areas where seat belt use is lower and age-adjusted death rates are higher than in urban areas. States and communities can consider using evidence-based interventions to reduce rural-urban disparities in seat belt use and passenger-vehicle-occupant death rates.

Are rural places less safe for motorists? Definitions of urban and rural to understand road safety disparities

The objectives of the study are to understand road safety within the context of regional development processes and to assess how urban-rural categories represent differences in motor vehicle occupant fatality risk. We analysed 2015 motor vehicle occupant deaths in Wisconsin from 2010 to 2014, using three definitions of urban-rural continua and negative binomial regression to adjust for population density, travel exposure and the proportion of teen residents. Rural-Urban Commuting Area codes, Beale codes and the Census definition of urban and rural places do not explain differences in urban and rural transportation fatality rates when controlling for population density. Although it is widely believed that rural places are uniquely dangerous for motorised travel, this understanding may be an artefact of inaccurate constructs. Instead, population density is a more helpful way to represent transportation hazards across different types of settlement patterns, including commuter suburbs and exurbs.