Traffic Crash Characteristics in Shenzhen, China from 2014 to 2016

Li, Guofa; Liao, Yuan; Guo, Qiangqiang; Shen, Caixiong; Lai, Weijian

doi:10.3390/ijerph18031176

Cited by 28 publications

(13 citation statements)

References 63 publications

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“…7 However, another study on traffic crashes in China found lower correlation of road crashes with rainy weather, which they attributed to a possible tendency of drivers to be more careful during bad weathers. 17 According to this study, the median length of hospital stay for women is 5 days. The length of hospital stay usually corresponds to the severity of injuries sustained, but a study by Cullen et al ( 2021) 18 observed no difference in the severity of injuries sustained between men and women.…”

Section: Discussionmentioning

confidence: 83%

Road Traffic Injuries among Women Brought to the Largest Tertiary Hospital in the Philippines

2022

Acta Med Philipp

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Introduction. Road traffic accidents are a growing public health burden, especially in the low- and middle-income countries (LMICs). With resource scarcity, road traffic injuries may lead to poor quality of life among survivors, or deaths at worst. Victims of crashes involving transportations are gendered; therefore, there may be differences in the trends and characteristics of injuries sustained by men and women related to road crash. Objectives. This study aimed to determine the factors related to severity of road crashes among women road users in the Philippines from 2008 to 2017. Methods. We conducted a retrospective review of clinical records of women patients involved in road crash at the Trauma Division, Department of Surgery of the Philippine General Hospital (PGH) for the ten-year period, January 1, 2008 to December 31, 2017. Data were extracted from the electronic patient records in Integrated Surgical Information System (ISIS). Results. From 2008 to 2017, 926 of the road crash victims brought to PGH were women. There was an increasing trend, with the years 2015 to 2017 accounting for half of the total cases (55.62%). The highest cases of women patient admissions were also recorded during the months of June and July (5.61%). The CALABARZON region (11.23%) and National Capital Region (8.21%) had the highest admissions. The patients were most commonly pedestrians (12.20%) and involved in collisions (13.50%) or vehicle involvement (13.17%). The most common vehicle involved was a motorcycle (9.72%) followed by car and vans (1.62%). Only a small proportion of women patients used helmets (3.33%) and seatbelts (0.12%). The median length of hospital stay of women patients was 5 days. The most commonly sustained injuries among patients were multiple (83.65%), external (43.72%), extremity (33.15%), head and neck (23.47%), and face (21.58%) injuries. Among these, injuries to the extremity had the highest average length of hospital stay (16.04 ± 31.28 days) while external and head and neck injuries had the shortest (10.81 ± 33.42 days). Multinomial regression showed that women patients who suffered from head and neck, and abdominal injuries had increased odds of dying by 4.94 times (CI: 2.158-11.302, p < 0.05), and 3.33 times (CI:1.235-9.02, p < 0.05), respectively, compared to those who did not suffer said injuries. Conclusion. There is a significant number of women involved in road crashes in the Philippines, and therefore, there is a need for directed policies on female road users as vulnerable road users.

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Section: Discussionmentioning

confidence: 83%

Road Traffic Injuries among Women Brought to the Largest Tertiary Hospital in the Philippines

2022

Acta Med Philipp

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“…There were several reasons why accidents often happen in the morning. For example, high movement of motor vehicles, because there is more activity in the morning [19]. Majority of Indonesian people start their activities in the morning such as going to work or going to school.…”

Section: Resultsmentioning

confidence: 99%

Characteristics of Traffic Accidents Frequency on Connection Road Between 3 Cities in Riau - Indonesia

Fahmi

Arifin

2022

InternationalConferenceUNIKS

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The main cause of road accidents in outside of cities is the driver's lack of awareness about road safety. Efforts to reduce these accidents can be done if the characteristics and causes are known. The purpose of this study was to determine the characteristics of road accidents in three areas in Riau province. Analysis used a descriptive quantitative analysis. This study was done to identify the characteristics of traffic accidents occurred from 2014 to 2019 on the connection road between 3 cities in Riau, namely in the Kuantan Singingi, Kampar and Rokan Hulu areas of Riau Province, Indonesia. The analysis used is descriptive quantitative analysis. The greater accidents were occurred in 2018, in which 192 cases. The least accidents were occurred in 2017, in which 115 cases, the month of June had the highest number of accidents since it was a month of school holidays. The percentage of total deaths on traffic accidents reached 60%. Meanwhile, 75.6% of traffic accident victims were injured, with the most accidents occurring on flat and straight roads. The types of vehicles that are often involved are motorcycle, which occur from 06.00 to 11.59 pm.

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“…For instance, the drivers in crashes that took place on rainy days were in many cases young drivers or old drivers. Likewise, Li et al [20] studied the relationship between land-use patterns and vehicle crashes. However, this method does not provide a full understanding of driving behavior [21].…”

Section: Related Workmentioning

confidence: 99%

Individual Driver Crash Risk Classification Based on IoV Data and Offline Consumer Behavior Data

Zhao

Dai

2021

Mobile Information Systems

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With the development of big data technologies, usage-based insurance (UBI) has received considerable attention from insurance companies. UBI products focus on identifying the relationship between the individual driver’s risk and online channel behavior variables from Internet of Vehicles (IoV) data. Although omnichannel information integration has promoted the development of many industries, it has not been used to improve the accuracy of driver risk classification models in insurance industries. This paper investigates the role of combining different channel variables in improving the classification of driver’s risk. Specifically, several models, including logistic regression and three different data mining techniques (neural networks, random forests, and support vector machines), augmented with driving behavior data based on the IoV and offline consumer behavior data collected from 4S (Sale, Spare part, Service, Survey) dealers, are applied to the classification model of risk. The empirical results show that the inclusion of online and offline channel data improves the different risk assessments; results also demonstrate the importance of offline consumer behavior variables in different models. These insights have important implications for insurance companies on UBI pricing strategy and cost management.

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Traffic Crash Characteristics in Shenzhen, China from 2014 to 2016

Cited by 28 publications

References 63 publications

Road Traffic Injuries among Women Brought to the Largest Tertiary Hospital in the Philippines

Road Traffic Injuries among Women Brought to the Largest Tertiary Hospital in the Philippines

Characteristics of Traffic Accidents Frequency on Connection Road Between 3 Cities in Riau - Indonesia

Individual Driver Crash Risk Classification Based on IoV Data and Offline Consumer Behavior Data

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