Fatal injuries among Hispanic workers in the U.S. construction industry: Findings from FACE investigation reports

IntroductionIdentifying and understanding the characteristics of workplace accidents can provide vital information required to clarify their causes and prevent similar accidents from happening in the future. The Hispanic workforce represents a significant segment of the U.S. construction labor force that is projected to continue increasing in population. The government statistical data show higher rates of fatalities among Hispanic workers when compared to other ethnic groups.MethodThis study aims to provide details about the trends of fatal injuries among Hispanic workers. The study examined 92 government investigation reports to reveal the general trends, then an examination of fatal fall injuries within the study sample was conducted since falling is the predominant cause of fatal injuries.ResultsThe findings suggest differences in accident characteristics between Hispanic workers and all workers, which could indicate a need for different interventions to improve the overall site safety. The study also revealed the dire need to propose revised investigation procedures that would help identify the root causes of accidents, which in turn leads to better recommendations and interventions.     

Tractor rollover fatalities,analyzing accident scenario

IntroductionIn many countries, traditional data sources for collecting injuries of workers covered by compulsory accident insurance have recently been integrated by new observatories whose results may differ. A comparative analysis of the Italian data collection systems related to fatal tractor accidents in agriculture was performed focusing on tractor rollover fatalities with the aim of analyzing the accident scenario.MethodData from the Operational Archives of the Italian Workers Compensation Authority (INAIL), which collects injuries of workers covered by compulsory accident insurance and those of the National Surveillance System (INAIL_ASL), which provides narrative text reports of work-related fatal accidents have been analyzed and compared to the information collected by the INAIL Observatory. The INAL Observatory was recently set up to complement the collection of fatal accidents involving agricultural machinery. Italian data were then compared to data available at an international level. Fatal tractor accidents vary considerably with respect to fatal accidents in agriculture, being 10.6 and 43.7% for the Operational Archives and Surveillance System, respectively. National Surveillance System records, implemented with narrative texts allowed the accident scenario to be defined.Results71.7% of fatal tractor-related accidents refer to non-ROPS equipped vehicles and of these, 26.5% involved machines originally mounted with a ROPS that had been removed or was inoperative in the folded-down position during the rollover event. Just one fatal event from a collapsed ROPS on the overturned tractor was recorded. It is interesting that 16.6% of fatal accidents involved a clear environmental factor.Practical applicationA campaign to train tractor drivers on the correct use of the combination ROPS and seatbelt can contribute to decreasing rollover events with fatal outcomes. Contemporarily a strict requirement to install ROPS and a seatbelt on tractors, combined to an official inspection at the farm level, can increase the chance of survival in a rollover accident.     

Analysis of work related accidents in the Spanish mining sector from 1982-2006

Introduction

The rate for work related accidents in the Spanish mining sector is notably higher than in other countries such as the United States. It produces a very negative impact on the mining industry. This paper is the report of a study on serious and fatal accidents in Spanish mining from 1982-2006. It is based on the reports of 212 accidents (serious or fatal) carried out by the General Management of Energy and Mining of Catalonia (Spain). Method: The high work-related accident rate in the Spanish mining sector makes it necessary to carry out an analysis and research that can shed light on the causes of this high rate; this is the only way that a solution can be found. The study is based on Feyer and Williamson's analysis of accident causes, as they apply to 212 accidents. The types and causes of the accidents are coded according to the coding system used by the Spanish National Institute for Safety and Hygiene in the Workplace, which allows us to identify a series of direct causes and contributing factors in different accidents. Results If all the causes and factors that are present in the accidents are known, we are able to look for appropriate solutions to reduce them as much as possible. In short, we are able to come up with a series of conclusions that expose the weak links in the management of accident prevention in companies. This is helpful in the struggle to reduce work injuries in the Spanish mining sector.     

Understanding factors associated with misclassification of fatigue-related accidents in police record

IntroductionFatigue is one of the riskiest causes of traffic accidents threatening road safety. Due to lack of proper criteria, the identification of fatigue-related accidents by police officers largely depends on inferential evidence and their own experience. As a result, many fatigue-related accidents are misclassified and the harmfulness of fatigue on road safety is misestimated.MethodIn this paper, a joint model framework is introduced to analyze factors contributing to misclassification of a fatigue-related accident in police reports. Association rule data mining technique is employed to identify the potential interactions of factors, and logistic regression models are applied to analyze factors that hinder police officers' identification of fatigue-related accidents. Using the fatigue-related crash records from Guangdong Province during 2005–2014, factors contributing to the false positive and false negative detection of the fatigue-related accident have been identified and compared.ResultsSome variables and interactions were identified to have significant impacts on fatigue-related accident detection.ConclusionsBased on the results, it can be inferred that the stereotype of certain groups of drivers, crash types, and roadway conditions affects police officers' judgment on fatigue-related accidents.Practical applicationsThis finding can provide useful information for training police officers and build better criteria for fatigue identification.     

Analysis of injury mechanism of the elderly and non-elderly groups in minor motor vehicle accidents

Abstract

Objective: The purpose of this study is to investigate the injury patterns of noncatastrophic accidents by individual age groups.

Methods: Data were collected from the Korean In-Depth Accident Study database based on actual accident investigation. The noncatastrophic criteria were classified according to U.S. experts from the Centers for Disease Control and Prevention’s recommendations for field triage guidelines of high-risk automobile crash criteria by vehicle intrusions more than 12 in. on occupant sites (including the roof) and more than 18 in. on any site. The Abbreviated Injury Scale (AIS) was used to determine injury patterns for each body region. Severely injured patients were classified as Maximum Abbreviated Injury Scale (MAIS) 3 or higher.

Results: In this study, the most significant injury regions were the head and neck, extremities, and thorax. In addition, the incidence of severe injury among elderly patients was nearly 1.6 times higher than that of non-elderly patients. According to age group, injured body regions among the elderly were the thorax, head and neck, and extremities, in that order. For the non-elderly groups, these were head and neck, extremities, and thorax. Severe injury rates were slightly different for the elderly group (head and neck, abdomen) and non-elderly group (thorax, head and neck).

Conclusions: In both age groups, the rate of severe injury is proportional to an increase in crush extent zone. Front airbag deployment may have a relatively significant relationship to severe injuries.     

Exploring bicyclist injury severity in bicycle-vehicle crashes using latent class clustering analysis and partial proportional odds models

Introduction: Bicyclists are more vulnerable compared to other road users. Therefore, it is critical to investigate the contributing factors to bicyclist injury severity to help provide better biking environment and improve biking safety. According to the data provided by National Highway Traffic Safety Administration (NHTSA), a total of 8,028 bicyclists were killed in bicycle-vehicle crashes from 2007 to 2017. The number of fatal bicyclists had increased rapidly by approximately 11.70% during the past 10 years (NHTSA, 2019). Methods: This paper conducts a latent class clustering analysis based on the police reported bicycle-vehicle crash data collected from 2007 to 2014 in North Carolina to identify the heterogeneity inherent in the crash data. First, the most appropriate number of clusters is determined in which each cluster has been characterized by the distribution of the featured variables. Then, partial proportional odds models are developed for each cluster to further analyze the impacts on bicyclist injury severity for specific crash patterns. Results: Marginal effects are calculated and used to evaluate and interpret the effect of each significant explanatory variable. The model results reveal that variables could have different influence on the bicyclist injury severity between clusters, and that some variables only have significant impacts on particular clusters. Conclusions: The results clearly indicate that it is essential to conduct latent class clustering analysis to investigate the impact of explanatory variables on bicyclist injury severity considering unobserved or latent features. In addition, the latent class clustering is found to be able to provide more accurate and insightful information on the bicyclist injury severity analysis. Practical Applications: In order to improve biking safety, regulations need to be established to prevent drinking and lights need to be provided since alcohol and lighting condition are significant factors in severe injuries according to the modeling results.     

Acute injuries resulting from accidents involving powered mobility devices (PMDs)—Development and outcomes of PMD-related accidents in Sweden

Objective: Powered mobility devices (PMDs) are commonly used as aids for older people and people with disabilities, subgroups of vulnarable road users (VRUs) who are rarely noted in traffic safety contexts. However, the problem of accidents involving PMD drivers has been reported in many countries where these vehicles have become increasingly popular.

The aim of this study is to extract and analyze national PMD-related accident and injury data reported to the Swedish Traffic Accident Data Acquisition (STRADA) database. The results will provide valuable insight into the risks and obstacles that PMD drivers are exposed to in the traffic environment and may contribute to improving the mobility of this group in the long term.

Methods: The current study is based on data from 743 accidents and 998 persons. An analysis was performed on a subset of data (N?=?301) in order to investigate the development of accidents over a period of 10 years. Thereafter, each accident in the whole data set was registered as either single (N?=?427) or collision (N?=?315).

Results: The results show that there was a 3-fold increase in the number of PMD-related accidents reported to STRADA during the period 2007–2016.

With regard to single accidents, collisions, as well as fatalities, the injury statistics were dominated by males. Single accidents were more common than collisions (N?=?427 and N?=?316, respectively) and the level of injury sustained in each type of accident is on par.

The vast majority of single accidents resulted in the PMD driver impacting the ground (87%), due to either PMD turnover (71%) or the driver falling out of the PMD (16%). The reason for many of the single accidents was a difference in ground level (34%, typically a curb).

Cars, trucks, or buses were involved in 67% of collision events; these occured predominantly at junctions or intersections (70%).

Abbreviated Injury Scale (AIS) 3+ injuries were dominated by hip and head injuries in both single accidents and collision events.

Conclusions: The present study shows that further research on PMD accidents is required, with regard to both single accidents and collision events. To ensure that appropriate decisions are made, future work should follow up on injury trends and further improve the quality of PDM-related accident data. Improved vehicle stability and design, increased usage of safety equipment, proper training programs, effective maintenance services, and development of a supporting infrastructure would contribute to increased safety for PMD drivers.     

Applying Hierarchical Loglinear Models to Nonfatal Underground Coal Mine Accidents for Safety Management

Underground mining is considered to be one of the most dangerous industries and mining remains the most hazardous occupation. Categorical analysis of accident records may present valuable information for preventing accidents. In this study, hierarchical loglinear analysis was applied to occupational injuries that occurred in an underground coal mine. The main factors affecting the accidents were defined as occupation, area, reason, accident time and part of body affected. By considering subfactors of the main factors, multiway contingency tables were prepared and, thus, the probabilities that might affect nonfatal injuries were investigated. At the end of the study, important accident risk factors and job groups with a high probability of being exposed to those risk factors were determined. This article presents important information on decreasing the number accidents in underground coal mines.     

The analysis of influence of individual and environmental factors on 2-wheeled users’ injuries

Objective: Powered 2-wheeled motor vehicles (PTWs) are one of the most vulnerable categories of road users. Bearing that fact in mind, we have researched the effects of individual and environmental factors on the severity and type of injuries of PTW users. The aim was to recognize the circumstances that cause these accidents and take some preventive actions that would improve the level of road safety for PTWs.

Methods: In the period from 2001 to 2010, an analysis of 139 road accidents involving PTWs was made by the Faculty of Transport and Traffic Engineering in Belgrade. The effects of both individual (age, gender, etc.) and environmental factors (place of an accident, time of day, etc.) on the cause of accidents and severity and type of injuries of PTWs are reported in this article. Analyses of these effects were conducted using logistic regression, chi-square tests, and Pearson's correlation.

Results: Factors such as categories of road users, pavement conditions, place of accident, age, and time of day have a statistically significant effect on PTW injuries, whereas other factors (gender, road type; that is, straight or curvy) do not. The article also defines the interdependence of the occurrence of particular injuries at certain speeds. The results show that if PTW users died of a head injury, these were usually concurrent with chest injuries, injuries to internal organs, and limb injuries.

Conclusions: It has been shown that there is a high degree of influence of individual factors on the occurrence of accidents involving 2-wheelers (PTWs/bicycles) but with no statistically significant relation. Establishing the existence of such conditionalities enables identifying and defining factors that have an impact on the occurrence of traffic accidents involving bicyclists or PTWs. Such a link between individual factors and the occurrence of accidents makes it possible for system managers to take appropriate actions aimed at certain categories of 2-wheelers in order to reduce casualties in a particular area. The analysis showed that most of the road factors do not have a statistically significant effect on either category of 2-wheeler. Namely, the logistic regression analysis showed that there is a statistically significant effect of the place of accident on the occurrence of accidents involving bicyclists.     

The role of behavioral factors on safety management in underground mines

Traditional approaches on the prevention of accidents/injuries in mines reached its limit of effectiveness in improving safety performance and a fresh approach is utmost required. Behavioral safety analysis has been identified as an effective alternative in many industries. This paper is therefore sought to examine the role of behavioral factors on the occurrence of mine accidents and injuries through a case study. Data were collected from two neighboring underground coalmines operating under a large public sector organization of India. High–low plots and t-test were done to explore the differences between behavioral characteristics of accident involved (case) and non-involved (control) workers. How these differences could cause accidents/injuries in mines was estimated through structural equation modeling. The case study results show that accident group of workers (cases) are more job dissatisfied, negatively affected, and highly risk taking compared to the non-accident group of workers (controls). The accident model path analysis shows that negative affectivity, job dissatisfaction, and risk taking behaviors predict an increased number of injuries in mines. Apart from direct influences to work injuries, negative affectivity and job dissatisfaction make workers to take more risks and behave unsafely. These findings contribute to the design of safety programs including safety training, which should be behaviorally motivated. Mine safety management of the case study mines should outskirt their age old belief that accidents/injuries are due to hazardous nature of mining and only engineering control and regulatory monitoring are sufficient for improving safety of the mines. The multivariate analysis also shows that experience bears no relationships with work injury indicating that a less experienced worker is equally likely to be injured as an experienced worker. It implies that experience though helps workers in understanding the physical hazards, however, avoiding the imminent danger is much more behavioral. The variables negative affectivity, job dissatisfaction, and risk taking behaviors are therefore crucial in avoiding accident/injuries in mines.     

Risk of repeat accidents by economic activity in Italy

RationaleThe phenomenon of repeat work-related accidents has not been sufficiently studied.ObjectivesTo evaluate the role of work-related factors in the occurrence of repeat accidents in Italy, using economic activity and the size of the enterprise as proxies and basing the analysis on available administrative data.MethodsThe data, provided by the Italian Workers’ Compensation Authority (INAIL), refer to accidents in the industry and artisan sectors and in the service industry between 1994 and 1999. We selected the data on accidents among 633,735 persons 25–55 years of age with a first accident in 1996–1997, and we determined the occurrence of further accidents within two years in the same economic activity, taking into account job mobility and factors associated with underreporting (geographic area, age, and size of the enterprise). The gender-specific relative risk was computed for each economic activity, given by the ratio between the risk of repeat accidents in a given economic activity and the risk in all of the other activities.ResultsIndividuals with a single accident differed from those with a repeat accident in terms of the distribution by gender, age-class, and severity of injury. The economic activities with the highest relative risk were generally those known to represent a risk of accidents in general: metal ore and coal mining, shipbuilding, the manufacturing of railroad equipment, building construction, road and railway construction, the primary iron and steel industry, foundry work, logging/wood manufacturing, slaughtering, and agriculture. However, certain activities not generally considered as hazardous showed a high risk of repeat accidents (e.g., public hygiene, and the manufacturing of bricks, pottery, and glass).ConclusionsThe epidemiological pattern of repeat accidents by economic activity reflects that of accidents in general, though with exceptions. Results suggest that factors associated with specific technical aspects and production processes are important determinants of safety. The differences between single accidents and repeat accidents by gender, age class, and severity of injury suggest that studying repeat accidents separately from first accidents is quite useful.     

基于灰关联度的事故聚类分析

事故是来自系统和环境的风险 ,危害人类的生产、生活和生存活动。对事故进行科学分类是安全管理和事故处理的重要基础。笔者针对现行事故等级分类标准的不足 ,分析了事故造成的人员伤亡和经济损失等多属性特征 ;通过灰关联度确定了各属性指标的不同权重 ,定义了事故间的加权欧氏距离 ;根据事故属性指标的相似度 ,利用聚类分析对事故进行了分类 ;以 2 0 0 3年全国发生的 14起特别重大事故为例进行了实证分析。提出的事故分类思想和方法 ,综合考虑了事故所造成的损失 ,理论严谨、方法实用有效 ,可作为政府有关部门进行事故分类和事故处理的决策依据。     

The effect of age and gender on motor vehicle driver injury severity at highway-rail grade crossings in the United States

IntroductionBased on the Federal Railway Administration (FRA) database, there were 25,945 highway-rail crossing accidents in the United States between 2002 and 2011. With an extensive database of highway-rail grade crossing accidents in the United States from 2002 to 2011, estimation results showed that there were substantial differences across age/gender groups for driver's injury severity.MethodThe study applied an ordered probit model to explore the determinants of driver injury severity for motor vehicle drivers at highway-rail grade crossings.ResultsThe analysis found that there are important behavioral and physical differences between male and female drivers given a highway-rail grade crossing accident happened.Practical applicationsOlder drivers have higher fatality probabilities when driving in open space under passive control especially during bad weather condition. Younger male drivers are found to be more likely to have severe injuries at rush hour with high vehicle speed passing unpaved highway-rail grade crossings under passive control. Synthesizing these results led to the conclusion that the primary problem with young is risk-taking and lack of vehicle handling skills. The strength of older drivers lies in their aversion to risk, but physical degradation issues which result in longer reaction/perception times and degradation in vision and hearing often counterbalance this attribute.     

Quantifying Vision Zero: Crash avoidance in rural and motorway accident scenarios by combination of ACC,AEB, and LKS projected to German accident occurrence

Abstract

Objective: The Vision Zero initiative pursues the goal of eliminating all traffic fatalities and severe injuries. Today’s advanced driver assistance systems (ADAS) are an important part of the strategy toward Vision Zero. In Germany in 2018 more than 26,000 people were killed or severely injured by traffic accidents on motorways and rural roads due to road accidents. Focusing on collision avoidance, a simulative evaluation can be the key to estimating the performance of state-of-the-art ADAS and identifying resulting potentials for system improvements and future systems.

This project deals with the effectiveness assessment of a combination of ADAS for longitudinal and lateral intervention based on German accident data. Considered systems are adaptive cruise control (ACC), autonomous emergency braking (AEB), and lane keeping support (LKS).

Methods: As an approach for benefit estimation of ADAS, the method of prospective effectiveness assessment is applied. Using the software rateEFFECT, a closed-loop simulation is performed on accident scenario data from the German In-Depth Accident Study (GIDAS) precrash matrix (PCM). To enable projection of results, the simulative assessment is amended with detailed single case studies of all treated cases without PCM data.

Results: Three categories among today’s accidents on German rural roads and motorways are reported in this study: Green, grey, and white spots.

Green spots identify accidents that can be avoided by state-of-the-art ADAS ACC, AEB, and LKS. Grey spots contain scenarios that require minor system modifications, such as reducing the activation speed or increasing the steering torque. Scenarios in the white category cannot be addressed by state-of-the-art ADAS. Thus, which situations demand future systems are shown. The proportions of green, grey, and white spots are determined related to the considered data set and projected to the entire GIDAS.

Conclusions: This article describes a systematic approach for assessing the effectiveness of ADAS using GIDAS PCM data to be able to project results to Germany. The closed-loop simulation run in rateEFFECT covers ACC, AEB, and LKS as well as relevant sensors for environment recognition and actuators for longitudinal and lateral vehicle control.

Identification of green spots evaluates safety benefits of state-of-the-art level 0–2 functions as a baseline for further system improvements to address grey spots. Knowing which accidents could be avoided by standard ADAS helps focus the evolution of future driving functions on white spots and thus aim for Vision Zero.     

非公路车辆翻车安全保护技术的研究

在我国农业、矿山、建筑、水利等行业中 ,非公路车辆保有量上千万台 ,使用者上亿人 ,由于车辆技术性能和操作使用水平参差不齐 ,非公路车辆作业工况恶劣 ,特别是车辆在承载时 ,重心上移 ,整车稳定性下降 ,加上车辆在边坡作业时 ,可能出现车辆翻滚现象 ,造成人员伤亡。笔者列举并分析了瑞典、德国、美国和中国等国家的非公路车辆翻车的人员伤亡统计数据 ;指出通过建立相应的保护法规 ,增设车辆翻车安全保护装置 (ROPS) ,一定程度上保护了工作人员安全 ;同时强调我国农业及工程车辆采用翻车保护装置的必要性 ,并给出了ROPS的设计选用原则。     

Agricultural accidents in north eastern region of India

An investigation was conducted to characterize the agricultural accidents, their magnitude, causes, severity and economic consequences in one of the states of north eastern region of India, Arunachal Pradesh. The accident data for 6 years between years 2000 and 2005 were collected by conducting a survey and personal interview of the victims in 42 selected villages of 4 districts. Agricultural accident incident rate was 6.39 per 1000 workers/year. All the accidents were non-fatal. Farm implement-related accidents accounted for 40% of the accidents. Slashing of shrubs accounted for one-third of the accidents causing cut and hit injuries of moderate severity. Twenty-five per cent of the accidents occurred on the way to or from the field leading to severe or serious injuries. Two-third of the accidents occurred within 4 h of start of work. Thirty-three per cent of the victims were 40–49 years of age. Based on the analysis, both passive and active measures have been suggested to minimize or prevent the occurrence of agricultural accidents.     

Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study

Objective: The main objective of this study is to identify the main factors associated with injury severity of vulnerable road users (VRUs) involved in accidents at highway railroad grade crossings (HRGCs) using data mining techniques.

Methods: This article applies an ordered probit model, association rules, and classification and regression tree (CART) algorithms to the U.S. Federal Railroad Administration's (FRA) HRGC accident database for the period 2007–2013 to identify VRU injury severity factors at HRGCs.

Results: The results show that train speed is a key factor influencing injury severity. Further analysis illustrated that the presence of illumination does not reduce the severity of accidents for high-speed trains. In addition, there is a greater propensity toward fatal accidents for elderly road users compared to younger individuals. Interestingly, at night, injury accidents involving female road users are more severe compared to those involving males.

Conclusions: The ordered probit model was the primary technique, and CART and association rules act as the supporter and identifier of interactions between variables. All 3 algorithms' results consistently show that the most influential accident factors are train speed, VRU age, and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGCs.