Pillion riders' cloth related injuries and helmet wearing patterns: a study of Lahore, Pakistan

The prevalence of helmet use in motorcyclists around the world: a systematic review and meta-analysis of 5,006,476 participants

Road traffic injuries present a significant public health burden, especially in developing countries. This systematic review and meta-analysis synthesized global evidence on motorcycle helmet use prevalence by including 299 records across 249 articles involving 5,006,476 participants from 1982 to 2022. The findings revealed a declining trend in helmet use prevalence over the past four decades, with an overall prevalence of 48.71%. The meta-regression analysis did not find any statistically significant change in the overall prevalence. Subgroup analysis showed higher helmet use prevalence in observation/survey records (54.29%) compared to crashed patient records (44.84%). Riders/Motorcyclists demonstrated a higher likelihood of wearing helmets than passengers in both observation/survey records (62.61 vs. 28.23%) and crashed patient records (47.76 vs. 26.61%). Countries with mandatory helmet use laws had higher helmet usage prevalence compared to those without (52.26 vs. 37.21%). The African continent had the lowest helmet use rates, while Latin America and the Caribbean regions had higher rates. This study provides a comprehensive overview of global helmet use prevalence, emphasizing disparities between high and low-income countries, variations in law enforcement, and trends over four decades. Targeted interventions are necessary to improve helmet-wearing habits, especially among passengers and regions with low usage rates. Effective legislation and awareness campaigns are crucial for promoting helmet use and reducing road traffic injuries burden.

Evaluating helmet-wearing of single-vehicle overspeeding motorcycle crashes: Insights from temporal instability in parsimonious pooled framework

OBJECTIVE

A lower helmet-wearing rate and overspeeding in Pakistan are critical risk behaviors of motorcyclists, causing severe injuries. To explore the differences in the determinants affecting the injury severities among helmeted and non-helmeted motorcyclists in motorcycle crashes caused by overspeeding behavior, single-vehicle motorcycle crash data in Rawalpindi city for 2017-2019 is collected. Considering three possible crash injury severity outcomes of motorcyclists: fatal injury, severe injury and minor injury, the rider, roadway, environmental, and temporal characteristics are estimated.

METHODS

To provide a mathematically simpler framework, the current study introduces parsimonious pooled random parameters logit models. Then, the standard pooled random parameters logit models without considering temporal effects are also simulated for comparison. By comparing the goodness of fit measure and estimation results, the parsimonious pooled random parameters logit model is suitable for capturing the temporal instability. Then, the non-transferability among helmeted and non-helmeted overspeeding motorcycle crashes is illustrated by likelihood ratio tests and out-of-sample prediction, and two types of models provide robust results. The marginal effects are also calculated.

RESULTS

Several variables, such as age, cloudy and weekday indicators illustrate temporal instability. Moreover, several variables are observed to only show significance in non-helmeted models, showing non-transferability across helmeted and non-helmeted models.

CONCLUSIONS

More educational campaigns, regulation and enforcement, and management countermeasures should be organized for non-helmeted motorcyclists and overspeeding behavior. Such findings also provide research reference for the risk-compensating behavior and self-selected group issues under overspeeding riding considering the usage of helmets.

Factors affecting injury severity in motorcycle crashes: Different age groups analysis using Catboost and SHAP techniques

OBJECTIVE

Motorcycle crashes often result in severe injuries on roads that affect people's lives physically, financially, and psychologically. These injuries could be notably harmful to drivers of all age groups. The main objective of this study is to investigate the risk factors contributing to the severity of crash injuries in different age groups.

METHODS

This Objective is achieved by developing accurate machine learning (ML) based prediction models. This research examines the relationship between potential risk factors of motorcycle-associated crashes using (ML) and Shapley Additive explanations (SHAP) technique. The SHAP technique further helped interpreting ML methods for traffic injury severity prediction. It indicates the significant non-linear interactions between dependent and independent variables. The data for this study was collected from the Provincial Emergency Response Service RESCUE 1122 for the Rawalpindi region (Pakistan) over three years (from 2017 to 2020). The Synthetic Minority Oversampling Technique (SMOTE) is employed to balance injury severity classes in the pre-processing phase.

RESULTS

The results demonstrate that age, gender, posted speed limit, the number of lanes, and month of the year are positively associated with severe and fatal injuries. This research also assesses how the modeling framework varies between the ML and classical statistical methods. The predictive performance of proposed ML models was assessed using several evaluation metrics, and it is found that Catboost outperformed the XGBoost, Random Forest (RF) and Multinomial Logit (MNL) model.

CONCLUSION

The findings of this study will assist road users, road safety authorities, stakeholders, policymakers, and decision-makers in obtaining substantial and essential guidance for reducing the severity of crash injuries in Pakistan and other countries with prevailing conditions.

Factors affecting motorcyclists' injury severities: An empirical assessment using random parameters logit model with heterogeneity in means and variances

Motorcycles constitute 61% of the total registered vehicles in Pakistan and there has been a 371% growth in motorcycles in the country from year 2005-2015. Motorcycle is an essential and popular mode of transportation in Pakistan, therefore, the present study estimated a random parameters logit model to investigate the factors influencing the motorcycle injury severity using motorcycle crash data of Rawalpindi city collected by the Provincial Emergency Response Service. No injury, minor injury, severe injury and fatal injury are used as four categories of motorcyclist injury severity levels to calibrate the model. Mainly the effects of speed limits, crash-specific factors, rider attributes, roadway characteristics, weather and socio-demographics factors are considered for motorcycle-injury severity analysis. It was revealed that probability of fatal/severe injury increases for crashes: involving middle-aged riders (25-50 years) and riders with no education, occurring on roads with posted speed limit of 70 kms per hour or higher, crashes involving a motorcycle and a heavy vehicle, involving collision of a motorcycle with a fixed object and occurring during dry weather conditions. Also, the probability of minor injury increases for crashes: occurring on divided streets and road segments with a posted speed limit of less than 50 kms per hour, involving Chinese brand motorcycles, involving registered motorcycles, and where at least one motorcycle and auto rickshaw is involved. The research findings suggest that besides measures to control/ reduce the risky motorcyclists behavior there is a need to lower speed limits on roads with a higher motorcycle proportion, separate motorcycles from heavy vehicles and removal of fixed objects from the roadside. Besides data limitations, results are expected to generate more discussion and interest in motorcycle safety in the country and can be used by the enforcement agencies to improve/ enhance the current state of motorcycle safety in the country.

Cerebral Contusion: An Investigation of Etiology, Risk Factors, Related Diagnoses, and the Surgical Management at a Major Government Hospital in Cambodia

Introduction

Cerebral contusions are a common type of injury among the Cambodian population, mostly due to road traffic accidents. This article aims to assess various aspects around brain contusion focusing on the condition at admission, residing province, mechanism and time of injury, age and sex distribution with differing helmet wearing, and alcohol consumption patterns. Hospitalization-related data such as treatment and outcome were analyzed.

Methods

This was a retrospective analysis of 406 cases who have been admitted during the period between May 2013 and May 2016.

Results

Two hundred and ninety-five (75.51%) of the patients came from rural areas, 312 (76.84%) were male (mean age 31.17 ± 12.90 years for males and 38.5 ± 16.29 years for females). The average hospital stay amounted to 10.51 ± 6.67 days. One hundred and eight two cases (52.29%) happened between 4.00 and 11.00 p.m. Three hundred and nineteen (79%) of the injured patients were motorcycle drivers and 18% pedestrians. Male patients had an alcohol involvement in 135 (49.45%) (females in 5 [6.25%]) cases and 26 (10%) wore a helmet (females in 5 [6.25%]). Surgery was performed in 82 cases, specifically craniotomy and craniectomy +/- elevation of a depressed skull fracture. Two hundred and ninety-six (73.09%) patients showed related second diagnosis, mostly subdural hematoma in 96 (32.43%) and epidural hematoma in 63 (21.28%) cases. Fifty patients (13.16%) had a Glasgow Coma Scale of 3-8. 92 (24.21%) of 9-12 and 238 (62.63%) of 13-15 on admission. Most of the patients were discharged with an improved status 324 (91.52%) according to the Glasgow Outcome Scale 4 or 5.

Conclusion

The severity and resulting neurologic impairment of cerebral contusions show the importance of more in-depth research and prevention programs.