Factors associated with urban non-fatal road-accident severity

Potoglou, Dimitris; Carlucci, Fabio; Cirà, Andrea; Restaino, Marialuisa

doi:10.1080/17457300.2018.1431945

Cited by 32 publications

(20 citation statements)

References 23 publications

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“…Collision between vehicles was the most frequent type of crash with 59.4% of all reported cases compared to 0.3% of cases for the vehicle-object-pedestrian type. These results are different from those found in Lubumbashi in 2011 and were more likely to be involved in a crash with a slight or serious injury than those aged 25-44 and 55 -64 years [16].…”

Section: Discussioncontrasting

confidence: 95%

Road Crashes: An Anthropic Pandemic, Case of the City of Lubumbashi

Kandolo¹,

Hardcastle²,

Matungulu³

et al. 2020

OALib

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Introduction: Road traffic crashes are a significant public health challenge in view of the high morbidity and mortality for which they are responsible. Objective: This study aims to describe the frequency and profile of road traffic crashes in the city of Lubumbashi. Methods: A retrospective descriptive study was conducted between January 1, 2015 and December 31, 2017. Included are all cases of vehicles registered with the road safety police, involved in a traffic crash. The data were processed using SPSS version 23 software (SPSS, Armonk, NY). Results: The study focused on 3495 cases of road traffic crashes registered with the road traffic police service from January 1, 2015 to December 31, 2017. These crashes were caused mainly by male drivers (98.6%). January had a large number of road crashes (9.2%) followed by that of October (9.1%); with 17.9% of the cases, crashes were on a Sunday. In 10% of road crashes there were fatalities recorded. Night driving; driving downtown; the use of public transport vehicles as well as the fact of driving on a long straight road predisposed to fatal road crashes in Lubumbashi (P < 0.05). Conclusions: Roads are designed to allow human movement; however there is major risk of injury and death particularly in holiday months and at night. Awareness campaigns can be used as a tool to reduce the pandemic of life-threatening traffic accidents. Some health education channels like schools, churches, political parties, socio-cultural associations, trade unions can be useful for this purpose (road prevention).

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Section: Discussioncontrasting

confidence: 95%

Road Crashes: An Anthropic Pandemic, Case of the City of Lubumbashi

Kandolo¹,

Hardcastle²,

Matungulu³

et al. 2020

OALib

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“…According to the results of previous studies conducted in India and Italy, the severity of accidents on rainy days is higher than sunny days (36). Moreover, compared to car accidents, the severity of injuries from motorcycle accidents is higher (37). Being severely injured reduces the QOL.…”

Section: Discussionmentioning

confidence: 99%

Quality of Life after Motorcycle Traffic Injuries: A Cohort Study in Northwest of Iran

Gheshlaghi

Sharifi²,

Noroozi³

et al. 2020

Preprint

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Background: The number of studies to address the Quality of life (QOL) after a motorcycle accident in the context of developing countries is low. In this study, we investigated the QOL of injured motorcyclists up to three months after their accident and determining the associated factors.Methods: In the present study, we included 190 injured motorcyclists who admitted at two referral specialized hospitals (Emam Reza and Shohada) in Tabriz, between June 2018 and January 2019, and agreed to participate. All injured motorcyclists were contacted through the telephone one and 171 of them (90%) three months after their accident to complete an EQ-5D-3L questionnaire. The baseline measurements were gathered by using face to face interviews in the hospitals. The QOL score could vary between 1-3. The higher score showed a lower QOL. The Generalized Estimating Equation (GEE) models were used to determine the factors affecting the motorcyclists’ QOL. Results: The injured motorcyclist’s QOL was relatively better three months after the accident (mean ± Standard Deviation: 2.15 ± 0.65) in comparison with their status a month after the accident (mean ± SD: 1.78 ± 0.51) (p<0.001). The multivariable model showed that individuals whose pelvis (Coef: 0.29, (95% Confidence Intervals [CI]: 0.16, 0.42), P= 0.001) and knee (Coef: 0.26, (95% CI: 0.10, 0.42), P= 0.001) were injured, experienced a lower QOL. Also, those whose accident had happened in rainy weather experienced lower QOL (Coef: 0.33, (95% CI: 0.12, 0.53), P= 0.001). Those who were in an accident with a vehicle experienced a better QOL than others (Coef: -0.26, (95% CI: -0.43, -0.09), P=0.002).Conclusion: The assessment of three-month post-discharge showed that the QOL of the motorcyclists was better. It is recommended that by designing multi-year cohort studies, the QOL of motorcyclists be assessed for a longer time to identify the practical factors that improve the QOL of injured motorcyclists. In hospital discharge victims (especially for those with lower limb injuries such as injury to pelvis and knee, victims with Post-traumatic stress disorder, depression, and anxiety problems), social support, psychological support, financial support, and rehabilitation should be considered to improve the QOL.

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“…This technique not only gives the measure of relevance of a feature but also gives its direction of the association, whether positive or negative. Logistic regression methods have been successfully used for reasonably accurate crash severity modeling in previous studies [41][42][43]. Crash severity was defined in two classes, these being whether a crash was fatal or non-fatal, given a list of explanatory variables at a selected confidence level.…”

Section: Crash Severity Modeling Using Logistic Regressionmentioning

confidence: 99%

The Dilemma of Road Safety in the Eastern Province of Saudi Arabia: Consequences and Prevention Strategies

Jamal

Rahman

Al-Ahmadi

et al. 2019

IJERPH

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Road traffic crashes (RTCs) are one of the most critical public health problems worldwide. The WHO Global Status Report on Road Safety suggests that the annual fatality rate (per 100,000 people) due to RTCs in the Kingdom of Saudi Arabia (KSA) has increased from 17.4 to 27.4 over the last decade, which is an alarming situation. This paper presents an overview of RTCs in the Eastern Province, KSA, from 2009 to 2016. Key descriptive statistics for spatial and temporal distribution of crashes are presented. Statistics from the present study suggest that the year 2012 witnessed the highest number of crashes, and that the region Al-Ahsa had a significantly higher proportion of total crashes. It was concluded that the fatality rate for the province was 25.6, and the mean accident to injury ratio was 8:4. These numbers are substantially higher compared to developed countries and the neighboring Gulf states. Spatial distribution of crashes indicated that a large proportion of severe crashes occurred outside the city centers along urban highways. Logistic regression models were developed to predict crash severity. Model estimation analysis revealed that crash severity can be attributed to several significant factors including driver attributes (such as sleep, distraction, overspeeding), crash characteristics (such as sudden deviation from the lane, or collisions with other moving vehicles, road fences, pedestrians, or motorcyclists), and rainy weather conditions. After critical analysis of existing safety and infrastructure situations, various suitable crash prevention and mitigation strategies, for example, traffic enforcement, traffic calming measures, safety education programs, and coordination of key stakeholders, have been proposed.

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Factors associated with urban non-fatal road-accident severity

Cited by 32 publications

References 23 publications

Road Crashes: An Anthropic Pandemic, Case of the City of Lubumbashi

Road Crashes: An Anthropic Pandemic, Case of the City of Lubumbashi

Quality of Life after Motorcycle Traffic Injuries: A Cohort Study in Northwest of Iran

The Dilemma of Road Safety in the Eastern Province of Saudi Arabia: Consequences and Prevention Strategies

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