{"title":"Comprehensive analysis of traumatic rupture of the aorta in road traffic crashes: incorporating epidemiological insights and K-prototype clustering.","authors":"Zhengwei Ma, Liming Zhang, Changren Qiu, Gang Xu, Ziyang Liang, Wei Wei","doi":"10.1080/15389588.2024.2398669","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>The identification of crash characteristics associated with traumatic rupture of the aorta (TRA) can significantly enhance countermeasures against TRA. Conventional epidemiological approaches struggle to adequately handle the substantial variability of traffic crash data. Consequently, this study aims to integrate conventional epidemiological analysis with data-driven cluster analysis to more comprehensively analyze TRA-related crash characteristics.</p><p><strong>Methods: </strong>A total of 350 unweighted TRA crashes were extracted from traffic crash databases including comprehensive crash details and injury descriptions. Initially, a selection was made of 11 continuous variables and 9 categorical variables, describing crash characteristics. After correlation analysis and principal component analysis were applied to the dataset, K-prototype clustering was finally conducted using 6retained categorical variables and 6 principal components derived from the continuous variables.</p><p><strong>Results: </strong>This study found significant age and gender disparities among TRA victims, with 50% falling within the age range of 25-59 years and an overwhelming majority (62.2%) being males. Side impacts emerged as the primary cause of TRA-related crashes (37.2%), followed by collisions with off-road objects (28.6%) and head-on collisions (24.8%). Cluster analyses revealed 6 distinct clusters within the TRA-related crash dataset. These clusters were characterized by factors such as vehicle model year, curb weight, collision dynamics, and seatbelt usage, providing a deeper understanding of the heterogeneity in TRA incidents and their associated factors.</p><p><strong>Conclusions: </strong>Although limitations related to available data sources and factors such as accompanying injuries and vehicle weight warrant further comprehensive investigations in the future, this study contributes valuable insights into TRA analysis to enhance understanding and prevention strategies.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-10"},"PeriodicalIF":1.6000,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Traffic Injury Prevention","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/15389588.2024.2398669","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: The identification of crash characteristics associated with traumatic rupture of the aorta (TRA) can significantly enhance countermeasures against TRA. Conventional epidemiological approaches struggle to adequately handle the substantial variability of traffic crash data. Consequently, this study aims to integrate conventional epidemiological analysis with data-driven cluster analysis to more comprehensively analyze TRA-related crash characteristics.
Methods: A total of 350 unweighted TRA crashes were extracted from traffic crash databases including comprehensive crash details and injury descriptions. Initially, a selection was made of 11 continuous variables and 9 categorical variables, describing crash characteristics. After correlation analysis and principal component analysis were applied to the dataset, K-prototype clustering was finally conducted using 6retained categorical variables and 6 principal components derived from the continuous variables.
Results: This study found significant age and gender disparities among TRA victims, with 50% falling within the age range of 25-59 years and an overwhelming majority (62.2%) being males. Side impacts emerged as the primary cause of TRA-related crashes (37.2%), followed by collisions with off-road objects (28.6%) and head-on collisions (24.8%). Cluster analyses revealed 6 distinct clusters within the TRA-related crash dataset. These clusters were characterized by factors such as vehicle model year, curb weight, collision dynamics, and seatbelt usage, providing a deeper understanding of the heterogeneity in TRA incidents and their associated factors.
Conclusions: Although limitations related to available data sources and factors such as accompanying injuries and vehicle weight warrant further comprehensive investigations in the future, this study contributes valuable insights into TRA analysis to enhance understanding and prevention strategies.
目标：确定与主动脉外伤性破裂（TRA）相关的交通事故特征可以大大加强针对 TRA 的对策。传统的流行病学方法难以充分处理交通事故数据的巨大变异性。因此，本研究旨在将传统的流行病学分析与数据驱动的聚类分析相结合，更全面地分析与 TRA 相关的碰撞特征：方法：从交通事故数据库中提取了 350 起未加权的 TRA 事故，其中包括全面的事故细节和伤害描述。初步选择了 11 个连续变量和 9 个分类变量来描述碰撞特征。在对数据集进行相关性分析和主成分分析后，最后利用从连续变量中提取的 6 个分类变量和 6 个主成分进行了 K 原型聚类：研究发现，TRA 受害者在年龄和性别上存在明显差异，50%的受害者年龄在 25-59 岁之间，绝大多数（62.2%）为男性。侧面碰撞是与 TRA 有关的车祸的主要原因（37.2%），其次是与越野物体的碰撞（28.6%）和正面碰撞（24.8%）。聚类分析显示，与 TRA 相关的碰撞数据集中有 6 个不同的聚类。这些聚类的特征包括车型年份、整备质量、碰撞动力学和安全带使用情况等因素，从而加深了对TRA事故的异质性及其相关因素的理解：尽管现有数据源以及伴随伤害和车辆重量等因素存在局限性，但本研究为 TRA 分析提供了宝贵的见解，有助于加深理解和制定预防策略。
期刊介绍：
The purpose of Traffic Injury Prevention is to bridge the disciplines of medicine, engineering, public health and traffic safety in order to foster the science of traffic injury prevention. The archival journal focuses on research, interventions and evaluations within the areas of traffic safety, crash causation, injury prevention and treatment.
General topics within the journal''s scope are driver behavior, road infrastructure, emerging crash avoidance technologies, crash and injury epidemiology, alcohol and drugs, impact injury biomechanics, vehicle crashworthiness, occupant restraints, pedestrian safety, evaluation of interventions, economic consequences and emergency and clinical care with specific application to traffic injury prevention. The journal includes full length papers, review articles, case studies, brief technical notes and commentaries.
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