scholarly journals Exploring the Determinants of the Severity of Pedestrian Injuries by Pedestrian Age: A Case Study of Daegu Metropolitan City, South Korea

2020 ◽  
Vol 17 (7) ◽  
pp. 2358 ◽  
Author(s):  
Seung-Hoon Park ◽  
Min-Kyung Bae
Keyword(s):  
Land Use ◽  
Injury Severity ◽  
Binary Logistic Regression ◽  
Vehicle Crashes ◽  
Pedestrian Injury ◽  
Moving Vehicles ◽  
Pedestrian Injuries ◽  
Serious Injury ◽  
Pedestrian Crashes ◽  
Age Range

Pedestrian-vehicle crashes can result in serious injury to pedestrians, who are exposed to danger when in close proximity to moving vehicles. Furthermore, these injuries can be considerably serious and even lead to death in a manner that varies depending on the pedestrian’s age. This is because the pedestrian’s physical characteristics and behaviors, particularly in relation to roads with moving vehicles, differ depending on the pedestrian’s age. This study examines the determinants of pedestrian injury severity by pedestrian age using binary logistic regression. Factors in the built environment, such as road characteristics and land use of the places where pedestrian crashes occurred, were considered, as were the accident characteristics of the pedestrians and drivers. The analysis determined that the accident characteristics of drivers and pedestrians are more influential in pedestrian-vehicle crashes than the factors of the built environmental characteristics. However, there are substantial differences in injury severity relative to the pedestrian’s age. Young pedestrians (aged under 20 years old) are more likely to suffer serious injury in school zones; however, no association between silver zones and injury severity is found for elderly pedestrians. For people in the age range of 20–39 years old, the severity of pedestrian injuries is lower in areas with more crosswalks and speed cameras. People in the age range of 40–64 years old are more likely to be injured in areas with more neighborhood streets and industrial land use. Elderly pedestrians are likely to suffer fatal injuries in areas with more traffic signals. This study finds that there are differences in the factors of pedestrian injury severity according to the age of pedestrians. Therefore, it is suggested that concrete and efficient policies related to pedestrian age are required to improve pedestrian safety and reduce pedestrian-vehicle crashes.

scholarly journals A Multilevel Model Approach for Investigating Individual Accident Characteristics and Neighborhood Environment Characteristics Affecting Pedestrian-Vehicle Crashes

2020 ◽  
Vol 17 (9) ◽  
pp. 3107 ◽  
Author(s):  
Seunghoon Park ◽  
Dongwon Ko
Keyword(s):  
South Korea ◽  
Multilevel Model ◽  
Injury Severity ◽  
Traffic Signals ◽  
Individual Characteristics ◽  
Neighborhood Environment ◽  
Vehicle Crashes ◽  
Pedestrian Injuries ◽  
Pedestrian Crashes ◽  
The Individual

Walking is the most basic movement of humans and the most fundamental mode of transportation. To promote walking, it is necessary to create a safe environment for pedestrians. However, pedestrian-vehicle crashes still remain relatively high in South Korea. This study employs a multilevel model to examine the differences between the lower-level individual characteristics of pedestrian crashes and the upper-level neighborhood environmental characteristics in Seoul, South Korea. The main results of this study are as follows. The individual characteristics of pedestrian-vehicle crashes are better at explaining pedestrian injury severity than built environment characteristics at the neighborhood level. Older pedestrians and drivers suffer more severe pedestrian injuries. Larger vehicles such as trucks and vans are more likely to result in a high severity of pedestrian injuries. Pedestrian injuries increase during inclement weather and at night. The severity of pedestrian injuries is lower at intersections and crosswalks without traffic signals than at crosswalks and intersections with traffic signals. Finally, school zones and silver zones, which are representative policies for pedestrian safety in South Korea, fail to play a significant role in reducing the severity of pedestrian injuries. The results of this study can guide policymakers and planners when making decisions on how to build neighborhoods that are safer for pedestrians.

Age and pedestrian injury severity in motor-vehicle crashes: A heteroskedastic logit analysis

2008 ◽  
Vol 40 (5) ◽  
pp. 1695-1702 ◽  
Author(s):  
Joon-Ki Kim ◽  
Gudmundur F. Ulfarsson ◽  
Venkataraman N. Shankar ◽  
Sungyop Kim
Keyword(s):  
Injury Severity ◽  
Motor Vehicle ◽  
Motor Vehicle Crashes ◽  
Logit Analysis ◽  
Vehicle Crashes ◽  
Pedestrian Injury

scholarly journals Understanding Victim Cooperation in Cases of Nonfatal Gun Assaults

2019 ◽  
Vol 46 (12) ◽  
pp. 1793-1811 ◽  
Author(s):  
Natalie Kroovand Hipple ◽  
Kristina J. Thompson ◽  
Beth M. Huebner ◽  
Lauren A. Magee
Keyword(s):  
Injury Severity ◽  
Binary Logistic Regression ◽  
Case Processing ◽  
Firearm Violence ◽  
Police Investigation ◽  
Race Conditions ◽  
Serious Injury ◽  
The Relationship ◽  
Criminal Case Processing ◽  
Willingness To Cooperate

Victims play a central role in criminal case processing, but research suggests many victims do not report crimes to police or cooperate in a police investigation. This study extends the literature on victim cooperation by examining the effect of incident-level variables and neighborhood characteristics on victim cooperation in nonfatal shooting incidents. The sample includes 1,054 nonfatal shooting victims from two Midwestern cities. Results using binary logistic regression suggest that incident and victim characteristics are significantly associated with cooperation, but race conditions the effect of injury severity and motive on cooperation. The willingness to cooperate among Whites is contingent on injury severity while non-White victims do not become markedly more cooperative when confronted with serious injury. Race also moderates the relationship between crime motive and cooperation. This work demonstrates the need to incorporate nonfatal firearm violence into studies of victim cooperation and gun crime more broadly.

Pedestrian Injury Severities in Pedestrian-Vehicle Crashes and the Partial Proportional Odds Logit Model: Accounting for Age Difference

2019 ◽  
Vol 2673 (5) ◽  
pp. 731-746 ◽  
Author(s):  
Yang Li ◽  
Wei (David) Fan
Keyword(s):  
Logit Model ◽  
Injury Severity ◽  
Parameter Estimates ◽  
Age Difference ◽  
Age Group ◽  
Vehicle Crashes ◽  
Ordered Logit ◽  
Proportional Odds ◽  
Pedestrian Injury ◽  
Injury Severities

This study investigates factors that significantly contribute to the severity of pedestrian injuries resulting from pedestrian-vehicle crashes. Multinomial logit (MNL) models, mixed logit (ML) models, and ordered logit/probit models have been widely used in modeling crash injury severity, including pedestrian injury severity in pedestrian-vehicle crashes. However, both MNL and ML models treat injury severity levels as non-ordered, ignoring the inherent hierarchical nature of crash injury severities, and the data used in ordered logit models need to be strictly subjected to the proportional odds (PO) assumption. In this study, a partial proportional odds (PPO) logit model approach is employed to explore the issues of pedestrian safety associated with each age group: young (aged under 24), middle-aged (aged 25–55), and older pedestrians (aged over 55). Data used in this study are police-reported pedestrian crash data collected from 2007 to 2014 in North Carolina. A variety of motorist, pedestrian, environmental, and roadway characteristics are inspected. Results from likelihood ratio tests statistically show the better performance of developing separate injury severity models for each age group compared with estimating a single model utilizing all data. Relevant parameter estimates and associated marginal effects are used to interpret the results, followed by recommendations made in the concluding section.

scholarly journals Analysis of Pedestrian–Motor Vehicle Crashes in San Antonio, Texas

2021 ◽  
Vol 13 (12) ◽  
pp. 6610
Author(s):  
Khondoker Billah ◽  
Hatim O. Sharif ◽  
Samer Dessouky
Keyword(s):  
High Risk ◽  
San Antonio ◽  
Speed Limit ◽  
Vehicle Crashes ◽  
Contributing Factors ◽  
Hotspot Analysis ◽  
Lighting Condition ◽  
Downtown Area ◽  
Pedestrian Injury ◽  
Pedestrian Crashes

Pedestrian safety is becoming a global concern and an understanding of the contributing factors to severe pedestrian crashes is crucial. This study analyzed crash data for San Antonio, TX, over a six-year period to understand the effects of pedestrian–vehicle crash-related variables on pedestrian injury severity based on the party at fault and to identify high-risk locations. Bivariate analysis and logistic regression were used to identify the most significant predictors of severe pedestrian crashes. High-risk locations were identified through heat maps and hotspot analysis. A failure to yield the right of way and driver inattention were the primary contributing factors to pedestrian–vehicle crashes. Fatal and incapacitating injury risk increased substantially when the pedestrian was at fault. The strongest predictors of severe pedestrian injury include the lighting condition, the road class, the speed limit, traffic control, collision type, the age of the pedestrian, and the gender of the pedestrian. The downtown area had the highest crash density, but crash severity hotspots were identified outside of the downtown area. Resource allocation to high-risk locations, a reduction in the speed limit, an upgrade of the lighting facilities in high pedestrian activity areas, educational campaigns for targeted audiences, the implementation of more crosswalks, pedestrian refuge islands, raised medians, and the use of leading pedestrian interval and hybrid beacons are recommended.

A note on modeling pedestrian-injury severity in motor-vehicle crashes with the mixed logit model

2010 ◽  
Vol 42 (6) ◽  
pp. 1751-1758 ◽  
Author(s):  
Joon-Ki Kim ◽  
Gudmundur F. Ulfarsson ◽  
Venkataraman N. Shankar ◽  
Fred L. Mannering
Keyword(s):  
Logit Model ◽  
Injury Severity ◽  
Motor Vehicle ◽  
Mixed Logit ◽  
Motor Vehicle Crashes ◽  
Mixed Logit Model ◽  
Vehicle Crashes ◽  
Pedestrian Injury

Analysis of Inpatient Hospital Falls with Serious Injury

2020 ◽  
pp. 105477382097340
Author(s):  
Eileen Costantinou ◽  
Julie A. Spencer
Keyword(s):  
Injury Severity ◽  
Healthcare Organizations ◽  
Chi Square ◽  
Service Line ◽  
Major Injury ◽  
Key Variables ◽  
Serious Injury ◽  
Serious Injuries ◽  
Age Range ◽  
Hospital Study

Fall-related serious injuries pose risks to patients and healthcare organizations. This retrospective, single-hospital study used a 38 variable instrument to understand characteristics of those who sustained a fall with serious injury. Analyses included descriptive statistics, frequency, and Chi-square tests of associations between key variables and outcomes of moderate versus major injury. Age range 25–91 years, predominantly 60–69 years (23.3%), and mostly male (50.9%). Highest percentage occurred between 0:00 and 06:59 (39.6%), and on Oncology service (28.3%). Fallers were in the room, (81.1%), sustained major injury (73.6%), fractured a major bone (43.4%), had altered mobility prior to the fall (67.9%), and had received at least one narcotic dose within 24 hours before the fall (43.2%). The associations between injury severity and age, gender, altered mobility, fall risk assessment pre-fall, and unit service line are not statistically significant, however have small-to-moderate clinical significance. This study adds to the literature in identifying characteristics of patients who sustain a fall-related serious injury.

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