scholarly journals Spatial Equity Analysis of Nighttime Pedestrian Safety: Role of Land Use and Alcohol Establishments in Albuquerque, NM

2021 ◽  
pp. 036119812110302
Author(s):  
Benson Long ◽  
Nicholas N. Ferenchak
Keyword(s):  
Land Use ◽  
Past Research ◽  
The United States ◽  
Sociodemographic Factors ◽  
Severe Injury ◽  
Severe Injuries ◽  
Lighting Condition ◽  
Crash Data ◽  
Pedestrian Crashes ◽  
Pedestrian Collisions

The United States experienced a 53% increase in pedestrian fatalities between 2009 and 2018, with 2018 having a 3.4% increase from 2017. Of the 2018 pedestrian fatalities with known lighting conditions, 76% occurred in dark/nighttime conditions, with 50% occurring between 6:00 and 11:59 p.m. Despite past research exploring several contributing characteristics for nighttime pedestrian crashes, there is limited research that investigates the spatial aspects of land use attributes and sociodemographic factors. Have these nighttime pedestrian collisions been concentrated in certain land uses? Could an establishment with the capacity to serve alcohol invoke a greater risk of pedestrian crashes? Does sociodemographic status correlate with clustering for fatal crashes, severe crashes, or both? To better understand the spatial characteristics of the recent increase in pedestrian collisions, we analyzed crash data from Albuquerque, New Mexico for pedestrian fatalities and severe injuries from 2013 to 2018 relative to lighting condition, land use (with a focus on alcohol establishments), and race/ethnicity on the block group level. We used confidence intervals and Getis-Ord Gi* statistics to verify the statistical integrity of the trends. Findings suggested that pedestrian fatality and severe injury rates were higher within a quarter mile of bars at night and in areas with elevated concentrations of minority populations. Pedestrian fatality and severe injury hot spots appeared to have higher percentages of non-white residents, coupled with lower sidewalk coverage and more arterials or collectors.

scholarly journals Analysis of Severe Injuries in Crashes Involving Large Trucks Using K-Prototypes Clustering-Based GBDT Model

Safety ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 32
Author(s):  
Syed As-Sadeq Tahfim ◽  
Chen Yan
Keyword(s):  
Injury Severity ◽  
Unobserved Heterogeneity ◽  
The United States ◽  
Clustering Methods ◽  
Severe Injuries ◽  
Traffic Crash ◽  
Crash Data ◽  
Boosted Decision Trees ◽  
The Individual ◽  
Crash Characteristics

The unobserved heterogeneity in traffic crash data hides certain relationships between the contributory factors and injury severity. The literature has been limited in exploring different types of clustering methods for the analysis of the injury severity in crashes involving large trucks. Additionally, the variability of data type in traffic crash data has rarely been addressed. This study explored the application of the k-prototypes clustering method to countermeasure the unobserved heterogeneity in large truck-involved crashes that had occurred in the United States between the period of 2016 to 2019. The study segmented the entire dataset (EDS) into three homogeneous clusters. Four gradient boosted decision trees (GBDT) models were developed on the EDS and individual clusters to predict the injury severity in crashes involving large trucks. The list of input features included crash characteristics, truck characteristics, roadway attributes, time and location of the crash, and environmental factors. Each cluster-based GBDT model was compared with the EDS-based model. Two of the three cluster-based models showed significant improvement in their predicting performances. Additionally, feature analysis using the SHAP (Shapley additive explanations) method identified few new important features in each cluster and showed that some features have a different degree of effects on severe injuries in the individual clusters. The current study concluded that the k-prototypes clustering-based GBDT model is a promising approach to reveal hidden insights, which can be used to improve safety measures, roadway conditions and policies for the prevention of severe injuries in crashes involving large trucks.

Evaluating Factors Influencing the Severity of Three-Plus Multiple-Vehicle Crashes using Real-Time Traffic Data

2018 ◽  
Vol 2672 (38) ◽  
pp. 128-137 ◽  
Author(s):  
Angela E. Kitali ◽  
Emmanuel Kidando ◽  
Paige Martz ◽  
Priyanka Alluri ◽  
Thobias Sando ◽  
...  
Keyword(s):  
Real Time ◽  
Random Effect ◽  
Random Effect Model ◽  
Probit Model ◽  
Severe Injury ◽  
Traffic Data ◽  
Vehicle Crashes ◽  
Lighting Condition ◽  
Crash Data ◽  
Real Time Traffic

Multiple-vehicle crashes involving at least two vehicles constitute over 70% of fatal and injury crashes in the U.S. Moreover, multiple-vehicle crashes involving three or more vehicles (3+) are usually more severe compared with the crashes involving only two vehicles. This study focuses on developing 3+ multiple-vehicle crash severity models for a freeway section using real-time traffic data and crash data for the years 2014–2016. The study corridor is a 111-mile section on I-4 in Orlando, Florida. Crash injury severity was classified as a binary outcome (fatal/severe injury and minor/no injury crashes). For the purpose of identifying the reliable relationship between the 3+ severe multiple-vehicle crashes and the identified explanatory variables, a binary probit model with Dirichlet random effect parameter was used. More specifically, Dirichlet random effect model was introduced to account for unobserved heterogeneity in the crash data. The probit model was implemented using a Bayesian framework and the ratios of the Monte Carlo errors were monitored to achieve parameter estimation convergence. The following variables were found significant at the 95% Bayesian credible interval: logarithm of average vehicle speed, logarithm of average equivalent 10-minute hourly volume, alcohol involvement, lighting condition, and number of vehicles involved (3, or >3) in multiple-vehicle crashes. Further analysis involved analyzing the posterior probability distributions of these significant variables. The study findings can be used to associate certain traffic conditions with severe injury crashes involving 3+ multiple vehicles, and can help develop effective crash injury reduction strategies based on real-time traffic data.

scholarly journals Injury Severity of Bus–Pedestrian Crashes in South Korea Considering the Effects of Regional and Company Factors

2019 ◽  
Vol 11 (11) ◽  
pp. 3169 ◽  
Author(s):  
Ho-Chul Park ◽  
Yang-Jun Joo ◽  
Seung-Young Kho ◽  
Dong-Kyu Kim ◽  
Byung-Jung Park
Keyword(s):  
South Korea ◽  
Injury Severity ◽  
The Elderly ◽  
Type I ◽  
Severe Injuries ◽  
Crash Data ◽  
Level Model ◽  
Multi Level ◽  
Pedestrian Crashes ◽  
Upper Level

Bus–pedestrian crashes typically result in more severe injuries and deaths than any other type of bus crash. Thus, it is important to screen and improve the risk factors that affect bus–pedestrian crashes. However, bus–pedestrian crashes that are affected by a company’s and regional characteristics have a cross-classified hierarchical structure, which is difficult to address properly using a single-level model or even a two-level multi-level model. In this study, we used a cross-classified, multi-level model to consider simultaneously the unobserved heterogeneities at these two distinct levels. Using bus–pedestrian crash data in South Korea from 2011 through to 2015, in this study, we investigated the factors related to the injury severity of the crashes, including crash level, regional and company level factors. The results indicate that the company and regional effects are 16.8% and 5.1%, respectively, which justified the use of a multi-level model. We confirm that type I errors may arise when the effects of upper-level groups are ignored. We also identified the factors that are statistically significant, including three regional-level factors, i.e., the elderly ratio, the ratio of the transportation infrastructure budget, and the number of doctors, and 13 crash-level factors. This study provides useful insights concerning bus–pedestrian crashes, and a safety policy is suggested to enhance bus–pedestrian safety.

scholarly journals Risk Factors for Older Pedestrian Injuries and Fatalities Among Communities in Massachusetts

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 113-113
Author(s):  
Shuangshuang Wang ◽  
Nina Silverstein ◽  
Chae Man Lee ◽  
Frank Porell ◽  
Beth Dugan
Keyword(s):  
Risk Factors ◽  
Healthy Aging ◽  
Health And Safety ◽  
Pedestrian Safety ◽  
The United States ◽  
Time Of Day ◽  
Community Factors ◽  
Crash Data ◽  
The Road ◽  
Pedestrian Crashes

Abstract The number of pedestrian crashes in the United States has increased by 35 percent from 2008 to 2017. Among all pedestrian fatalities in 2017, 48% were pedestrians aged 50 and older, which suggests a disproportionate threat to older residents’ health and safety. Massachusetts has a large older population and is experiencing increased numbers of older pedestrian crashes. This research identified risk factors and community characteristics contributing to older pedestrian crashes and suggests leveraging the state’s age-friendly efforts to speed the implementation of countermeasures. Based on ten-year statewide crash data (2006-2015) and community indicators from the 2018 Massachusetts Healthy Aging Data Report, this study examined 4,472 crashes across Massachusetts that involved pedestrians age 55 and over. The leading reasons for crashes were driver’s inattention, driver’s failure to yield right of way, and driver’s issues with visibility. Older pedestrians were hit while walking in the road, often in crosswalks at intersections. Many factors were found to contribute to older pedestrian crashes: time of day (rush hour), time of year (winter), and community factors (higher rates of disabilities, higher percentage of racial minority residents, higher number of cultural amenities, and lack of dementia-friendly community efforts. Greater awareness of older pedestrian safety risks is needed. Communities highlighted in this research warrant priority attention from planning, health, aging services, and transportation authorities to improve older pedestrian safety.

Analysis of Factors Affecting Injury Severity in Traffic Crashes on Arizona Tribal Lands

2019 ◽  
Vol 2673 (9) ◽  
pp. 345-354
Author(s):  
Emmanuel James ◽  
Brendan J. Russo
Keyword(s):  
Traffic Safety ◽  
Injury Severity ◽  
The United States ◽  
The State ◽  
Severe Injury ◽  
Federal State ◽  
Severe Injuries ◽  
Traffic Crashes ◽  
Factors Affecting ◽  
Tribal Lands

Reducing fatal and serious injuries sustained in traffic crashes on tribal lands is a priority of federal, state, and local agencies in the United States. In the state of Arizona, the proportion of fatal and severe injury crashes on several areas of tribal land are 4.0% higher compared with statewide statistics. There is a need to investigate why higher proportions of fatal and severe injuries are occurring on tribal lands to plan effective countermeasures aimed at improving traffic safety in these areas. This study presents an analysis of factors affecting injury severity in crashes occurring within five tribal reservations in the state of Arizona. Crash data were obtained from the Arizona Department of Transportation, and the analysis included data for 9,597 persons involved in traffic crashes on these tribal lands for the years 2010–2016. An ordered logit model with random parameters was estimated using this data to identify factors significantly associated with severe injury outcomes in the event of a crash on tribal lands. Several person-, vehicle-, roadway-, and environmental-related variables were found to impact injury severity. For instance, alcohol and safety device usage were significantly associated with severity outcomes. The results of this study have the potential to aid transportation agencies effectively plan strategies to reduce traffic crash injuries and fatalities on tribal lands, and potential countermeasures considering the 4Es of traffic safety (engineering, education, enforcement, and emergency medical services) are discussed.

scholarly journals Vehicle-Pedestrian crashes at Intersections in Dhaka city

2017 ◽  
Vol 11 (1) ◽  
pp. 11-19 ◽  
Author(s):  
Shakil Mohammad Rifaat ◽  
Richard Tay ◽  
Shariar Mohammad Raihan ◽  
Abrar Fahim ◽  
Shah Mostofa Touhidduzzaman
Keyword(s):  
Developed Countries ◽  
Related Factors ◽  
Crash Data ◽  
Road Users ◽  
Safety Research ◽  
Commercial Area ◽  
Vulnerable Road Users ◽  
Pedestrian Crashes ◽  
Waste Deposit ◽  
Pedestrian Collisions

Background: Pedestrians are some of the most vulnerable road users, especially in large congested cities in developing countries. In order to develop appropriate countermeasures to improve safety, research has to be conducted to understand the factors contributing to vehicle-pedestrian collisions. Objective: This study aims to identify the factors contributing to intersection crashes in a developing country context. Method: A Poisson regression model was applied to police reported crash data from the capital of Bangladesh, Dhaka. Results: This study finds that an increase in vehicle traffic and the presence of police officer, footbridge, bus stop, solar panel and waste deposit facility were associated with an increase in the number of vehicle-pedestrian crashes, whereas an increase in pedestrian volume, roads with the same number of inbound and outbound lanes, roads with greater number of lanes, and the presence of traffic signal, commercial area or offices, speed breaker and rail crossing were associated with a reduction in the number of vehicle-pedestrian crashes. Conclusion: While the results of most traffic and engineering factors are consistent with those obtained in previous studies in developed countries, some of the results on human related factors and unusual road furniture are atypical and require more locally targeted countermeasures.

1496-P: Clinical Inertia in Relation to Sociodemographic Factors among Patients with Type 2 Diabetes (T2D) in the United States

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1496-P
Author(s):  
GAIL FERNANDES ◽  
BAANIE SAWHNEY ◽  
HAKIMA HANNACHI ◽  
TONGTONG WANG ◽  
ANN MARIE MCNEILL ◽  
...  
Keyword(s):  
United States ◽  
Type 2 Diabetes ◽  
The United States ◽  
Sociodemographic Factors ◽  
Clinical Inertia

The Oxford Handbook of Integrative Health Science

2018 ◽  
Keyword(s):  
Adult Life ◽  
The United States ◽  
Sociodemographic Factors ◽  
Population Based ◽  
Health Science ◽  
National Study ◽  
Integrative Health ◽  
Social Structural ◽  
Research Population ◽  
Psychosocial Influences

This handbook signals a paradigm shift in health research. Population-based disciplines have employed large national samples to examine how sociodemographic factors contour rates of morbidity and mortality. Behavioral and psychosocial disciplines have studied the factors that influence these domains using small, nonrepresentative samples in experimental or longitudinal contexts. Biomedical disciplines, drawing on diverse fields, have examined mechanistic processes implicated in disease outcomes. The collection of chapters in this handbook embraces all such prior approaches and, via targeted questions, illustrates how they can be woven together. Diverse contributions showcase how social structural influences work together with psychosocial influences or experiential factors to impact differing health outcomes, including profiles of biological risk across distinct physiological systems. These varied biopsychosocial advances have grown up around the Midlife in the United States (MIDUS) national study of health, begun over 20 years ago and now encompassing over 12,000 Americans followed through time. The overarching principle behind the MIDUS enterprise is that deeper understanding of why some individuals remain healthy and well as they move across the decades of adult life, while others succumb to differing varieties of disease, dysfunction, or disability, requires a commitment to comprehensiveness that attends to the interplay of multiple interacting influences. Put another way, all of the disciplines mentioned have reliably documented influences on health, but in and of themselves, each is inherently limited because it neglects factors known to matter for health outside the discipline’s purview. Integrative health science is the alternative seeking to overcome these limitations.

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