[Role of the occupational medicine in the prevention of diseases and accidents]. / Rôle de la Médecine du travail dans la prévention des maladies et des accidents.

Occupational medicine is an essential branch of preventive medicine that aims to protect the health of workers in the workplace. Any work situation exposes the worker to occupational hazards. The three levels of prevention applied in occupational medicine make it possible, together, to control risks. Primary prevention aims to prevent the occurrence of damage related to occupational risks, secondary prevention aims to early detect work-related health problems and in tertiary prevention, the objective is to limit the consequences of occupational risks or diseases already developed. It is not always possible to completely eliminate an occupational hazard. Regular medical examinations, at a frequency appropriate to the risks identified, meet this objective and therefore make it possible to detect work-related health problems or problems that could influence work. A proactive approach focused on prevention helps to reduce occupational risks, prevent work-related diseases, and to promote a healthy and safe work environment for all.

La médecine du travail est une branche essentielle de la médecine préventive qui vise à protéger la santé des travailleurs sur leur lieu de travail. Toute situation de travail expose le travailleur à des dangers professionnels. Les trois niveaux de prévention appliqués en médecine du travail permettent, ensemble, de maîtriser les risques. La prévention primaire vise à empêcher l'apparition des dommages liés aux risques professionnels, la prévention secondaire vise à détecter précocement les problèmes de santé liés au travail et en prévention tertiaire, l'objectif est de limiter les conséquences des risques professionnels ou des maladies déjà développées. Il n'est pas toujours possible de supprimer complètement un risque professionnel. Les examens médicaux réguliers, à une périodicité adaptée aux risques identifiés, répondent à cet objectif et permettent donc de détecter les éventuels problèmes de santé liés au travail ou qui pourraient influencer le travail. Une approche proactive axée sur la prévention contribue à réduire les risques professionnels, à prévenir les maladies liées au travail, et à promouvoir un environnement de travail sain et sécurisé pour tous.

Work-related crashes in rideshare drivers in the United States.

INTRODUCTION: Motor vehicle crashes (MVCs) are the leading cause of work-related deaths in the United States. The increasing popularity of the competitive rideshare market and the lack of oversight over workforce health and safety limits understanding of the current occupational hazards and associated risk factors faced by this precarious workforce. The objective of this analysis was to determine what the personal, social and occupational risk factors for work-related crashes in rideshare drivers are in the United States and suggest further research required to understand occupational health risks and opportunities for interventions. MATERIAL AND METHODS: We conducted a survey of a convenience sample of rideshare and taxi drivers using an online questionnaire. Rideshare respondents (n = 277) were recruited through an email that was distributed to people who subscribe to TheRideshareGuy.com. We examined the general characteristics of rideshare drivers by history of work-related MVCs and logistic regression models were used to determine major predictors of MVCs. RESULTS: Of 276 rideshare drivers that reported their crash history, one-third (n = 91, 33%) reported being involved in a work-related crash. Results from a multivariable logistic regression model showed rideshare MVCs were more likely in older drivers (aOR for 10 year increases in age, 1.55, p = 0.001), if drivers undertook 10 or more rideshare trips per day (aOR 1.84, p = 0.041), frequently or very frequently were driving on unfamiliar roads (aOR 1.72, p = 0.048) and driving whilst tired (aOR 3.03, p = 0.003). CONCLUSION: Precarious workers and health and safety is emerging as a major area of research focus. There is a unique opportunity to explore the occupational health risks in rideshare drivers to provide interventions that encourage growth of a healthy and fit rideshare workforce and promote work practices and future regulations aimed at improving safe work practices. PRACTICAL APPLICATIONS: This analysis paints a complex picture of personal and occupational factors that are associated with MVCs in rideshare drivers suggesting that additional policy development related to occupational health and safety of rideshare drivers could be constructive.

A prospective cohort study of perceived organizational support and occupational accidents and near-miss events among Japanese workers.

INTRODUCTION: Preventing occupational accidents is a major global challenge, and employee safety practices play a crucial role in accident prevention. Although perceived organizational support (POS) is related to safety practices, there is currently insufficient evidence supporting a relationship between POS and occupational accidents. We investigated the relationships between POS and both occupational accidents and near-miss events that can lead to accidents in the following year among workers in various industries in Japan. METHOD: This prospective cohort study was conducted from March 2022 to March 2023 using a questionnaire survey. In total, 9916 participants who completed the follow-up survey and met our inclusion criteria were analyzed. The follow-up survey asked participants about both occupational accidents and near-miss events experienced in the year following the baseline assessment. POS was evaluated at baseline using the eight-item version of the Survey of Perceived Organizational Support. Odds ratios (ORs) for the relationships between POS and occupational accidents and near-miss events were estimated using multilevel logistic regression analyses nested by industries. RESULTS: The ORs for self-reported occupational accidents were significantly higher for the moderate (OR = 1.41, 95% confidence interval [CI]: 1.10-1.82), low (OR = 1.49, 95%CI: 1.18-1.89), and very low (OR = 2.03, 95%CI: 1.61-2.56) POS groups compared with the very high group. The ORs for self-reported near-miss events were also significantly higher for the moderate (OR = 1.21, 95%CI: 1.03-1.43), low (OR = 1.20, 95%CI: 1.03-1.40), and very low (OR = 1.56, 95%CI: 1.34-1.82) groups than the very high group. CONCLUSIONS: Our findings suggest lower POS is related to a higher occurrence of occupational accidents and near-miss events in the following year. Organizations should consider enhancing employees' POS to reduce occupational accidents and near-miss events. PRACTICAL APPLICATIONS: To enhance employees' POS, organizations should address identified antecedents of POS (e.g., fairness, supervisor support, rewards, favorable job conditions, and human resource practices).

Evolution of work conditions for employees driving for work in France based on data from the 2003, 2010 and 2017 SUMER surveys (Surveillance Médicale des expositions aux risques Professionnels).

INTRODUCTION: The occupational road-accident risk on public roads and the work conditions for professional driving is still an important issue in occupational health despite lower road-accident rates. This study presents the evolution over time of the work-related constraints for these employees based on the Sumer surveys carried out in 2003, 2010 and 2017. METHOD: Data from the 2010 and 2017 surveys were restricted to match the scope of the 2003 survey in order to enable prevalence data to be compared in equivalent populations. The main variable of interest was "driving (car, truck, bus, and other vehicles) on public thoroughfares" for work (during the last week of work: yes/no). Work time characteristics, work rhythm, autonomy and scope for initiative, collective work group, standards and evaluations variables were completed by the occupational health physicians. A self-administered questionnaire was also provided to employees and contained the Job Content Questionnaire, which assesses decision latitude, social support and psychological demands, the reward scale of Siegrist questionnaire, the hostile behaviour with inspired questions for Leymann, sick leave and work accidents during the past 12 months and job satisfaction. Finally, prevention in the workplace was also completed by the occupational health physicians. RESULTS: About 25% of employees in France were exposed to work-related driving in 2017, which was stable in comparison with 2003 and 2010. However, the population was older and there were more females, more often from the clerical staff/middle manager category and working in companies with fewer than 10 employees. Employees exposed to work-related driving were also more frequently exposed to sustained work schedules and physical constraints, but less exposed to psychosocial risks. CONCLUSIONS: The percentage of employees exposed to occupational road accident risk, i.e., exposure to work-related driving, remained stable at about 25% in 2017 compared with previous surveys. These employees were also more frequently exposed to sustained work schedules and physical constraints, but less exposed to psychosocial risks. PRACTICAL APPLICATIONS: Prevention campaigns on work-related road accident risk should be provided to all employees in all companies since all jobs can be concerned.

From unstructured accident reports to a hybrid decision support system for occupational risk management: The consensus converging approach.

INTRODUCTION: Workplace accidents in the petroleum industry can cause catastrophic damage to people, property, and the environment. Earlier studies in this domain indicate that the majority of the accident report information is available in unstructured text format. Conventional techniques for the analysis of accident data are time-consuming and heavily dependent on experts' subject knowledge, experience, and judgment. There is a need to develop a machine learning-based decision support system to analyze the vast amounts of unstructured text data that are frequently overlooked due to a lack of appropriate methodology. METHOD: To address this gap in the literature, we propose a hybrid methodology that uses improved text-mining techniques combined with an un-bias group decision-making framework to combine the output of objective weights (based on text mining) and subjective weights (based on expert opinion) of risk factors to prioritize them. Based on the contextual word embedding models and term frequencies, we extracted five important clusters of risk factors comprising more than 32 risk sub-factors. A heterogeneous group of experts and employees in the petroleum industry were contacted to obtain their opinions on the extracted risk factors, and the best-worst method was used to convert their opinions to weights. CONCLUSIONS AND PRACTICAL APPLICATIONS: The applicability of our proposed framework was tested on the data compiled from the accident data released by the petroleum industries in India. Our framework can be extended to accident data from any industry, to reduce analysis time and improve the accuracy in classifying and prioritizing risk factors.

Chapitre 4. L'accident du travail chez soi.

The widespread use of teleworking during the health crisis reduced the flow of occupational accident claims by 20%. This applies to commuting accidents, as well as claims related to « immediate » or “deferred” risks (Rapp. annuel 2020 de l’Assurance maladie - Risques professionnels : Eléments statistiques et financiers, déc. 2021, p. 2 and 113). On the basis of these figures, working at home could be analyzed as a means of preventing occupational risks and improving workers’ health. In reality, however, these figures should not obscure the fact that telecommuting is a major occupational hazard. This is all the more the case given that, while telecommuting was not very widespread before the pandemic, it is now popular with employees and is being developed by many companies as a source of productivity (Rapp. CNP, May 16 2022). We therefore need to keep a close eye on the development of workplace accident legislation in this area, its adaptability to the specific claims experience of teleworkers and its perfectibility, not forgetting the thorny question of the possible recognition of the employer’s inexcusable fault in the event of the accident being covered by professional legislation.

Developing a risk framework for assembly construction based on stakeholder theory and structural equation modelling.

Occupational injuries in the construction industry have plagued many countries, and many cases have shown that accidents often occur because of a combination of project participants. Assembled construction (AC) projects have received extensive attention from Chinese scholars as a future trend, but few studies have explored the interrelationships and potential risks of various stakeholders in depth. This study fills this research gap by proposing a multi-stakeholder AC risk framework. The study surveyed 396 stakeholders, then analyzed the collected data and created a risk framework based on Structural Equation Modelling (SEM) and the CRITIC weighting method. The results revealed that factors like "regular supervision is a formality," "blindly approving the wrong safety measures," and "failure to organize effective safety education and training." are vital risks in AC of China. Finally, the study validates the risk factors and the framework with 180 real-life cases, which shows that the proposed framework is theoretically grounded and realistic. The study also suggests multi-level strategies such as introducing AI-based automated risk monitoring, improving the adaptability of normative provisions to technological advances, and advancing the culture of project communities of interest to ensure AC's safe practices.

Research on the evolutionary control of unsafe behavior of construction personnel based on multi-field coupled-homogeneous analysis model.

Unsafe behavior among construction personnel poses significant risks in petroleum engineering construction projects. This study addresses this issue through the application of a multi-field coupled homogeneous analysis model. By conducting case analyses of petroleum engineering construction accidents and utilizing the WSR methodology, the influencing factors of unsafe behaviors among construction personnel are systematically categorized into organizational system factors, equipment management factors, and construction personnel factors. Subsequently, employing Risk coupling theory, the study delves into the analysis of these influencing factors, discussing their coupling mechanisms and classifications, and utilizing the N-K model to elucidate the coupling effect among them. Furthermore, a novel approach integrating coupling analysis and multi-agent modeling is employed to establish an evolutionary model of construction personnel's unsafe behavior. The findings reveal that a two-factor control method, concurrently reinforcing equipment and construction personnel management, significantly mitigates unsafe behavior. This study provides valuable insights into the evolution of unsafe behavior among construction personnel and offers a robust theoretical framework for targeted interventions. Significantly, it bears practical implications for guiding safety management practices within petroleum engineering construction enterprises. By effectively controlling unsafe behaviors and implementing targeted safety interventions, it contributes to fostering sustainable development within the petroleum engineering construction industry.

Development of Quick Response (QR) Training of Tractor Component Identification, Function, Maintenance, and Safety.

Given the high variability of secondary agricultural teacher background and facility constraints, the instruction of tractor (and similar agricultural machinery) component identification, function, maintenance, and corresponding safety precautions oftentimes prove difficult and/or inconsistent. This study focused on the development and plausible application of quick response codes, commonly referred to as QR codes, placed on a demonstration tractor or machine to be used as a self-guided student learning experience for training the next generation of safe operators. This review documents a novel self-guided instruction methodology utilizing "gamification" learning theory. Content materials were derived from the nationally disseminated, open source, Gearing Up for Safety Production Agriculture Safety Training for Youth curriculum. Specifically, QR code learning modules were recommended to supplement Gearing Up for Safety, Lesson 16: Hands-On Tractor Operation of the youth worker certification component of the Pre-Operational Skills Exam.

Establishment-level safety analytics: a scoping review.

The use of data analytics has seen widespread application in fields such as medicine and supply chain management, but their application in occupational safety has only recently become more common. The purpose of this scoping review was to summarize studies that employed analytics within establishments to reveal insights about work-related injuries or fatalities. Over 300 articles were reviewed to survey the objectives, scope and methods used in this emerging field. We conclude that the promise of analytics for providing actionable insights to address occupational safety concerns is still in its infancy. Our review shows that most articles were focused on method development and validation, including studies that tested novel methods or compared the utility of multiple methods. Many of the studies cited various challenges in overcoming barriers caused by inadequate or inefficient technical infrastructures and unsupportive data cultures that threaten the accuracy and quality of insights revealed by the analytics.

Demeter - a Risk Mitigation Tool for Agriculture Workers.

The agriculture industry lacks novel techniques for analyzing risks facing its workers. Although injuries are common in this field, existing datasets and tools are insufficient for risk assessment and mitigation for two primary reasons: they provide neither immediate nor long-term risk mitigation advice, and they do not account for hazards which fluctuate daily. The purpose of Demeter is to collect safety data about hazards on farms and produce risk analysis and mitigation reports. This application uses a combination of formula-based risk calculations and state-of-the-art graph neural networks (GNNs) to perform risk analysis and reduction. The formula-based risk calculations had a mean absolute error (MAE) of 0.2110, and the GNN had an accuracy of 94.9%, a precision of 0.3521, and a recall of 0.8333. Demeter has the potential to reduce the number of injuries and fatalities among agriculture workers by alerting them to risks present in their daily workflow and suggesting safety precautions.

24Model-based comparative analysis of two catastrophic hazardous chemical pipeline accidents.

Objectives. This study conducted a comparative analysis of two catastrophic pipeline accidents in China in order to identify some common mistakes and lessons learned to prevent similar accidents. Methods. The 24Model was used in this study, which provides a universal pathway for accident analysis from the individual level to the organizational level. Results. There were similarities between the two cases in the aspects of the occurrence, development, emergency and causation at different levels: both were caused by leaks of pipelines and evolved into multiple explosions during emergency response; both leaks were caused by the corrosion of pipelines in the confined space of a damp or salt-spray environment; both were classified as 'responsibility accidents', and unsafe acts, such as the failure to identify hidden hazards of pipelines that were the direct cause of accidents, reflected the shortcomings of individual safety habitual behaviour in terms of knowledge, awareness, habits and psychology; weaknesses in the organizational management mainly concerned hazard identification, pipeline maintenance, emergency disposal, etc.; and there is not a good safety climate within the organization. Conclusions. Organizations should develop a closed-loop management system and strengthen the construction of safety culture, and the government should supervise the implementation of procedures.

Risk self-perception and occupational accidents.

INTRODUCTION: This study analyzes the relationship between measures of occupational accidents and workers' perception of risk in the workplace using nationally representative data on workers' characteristics and a complete record of occupational accidents. METHODS: Regression analyzes addressing both the ordinal nature of the dependent variable and causality were conducted to control for different sociodemographic factors influencing workers' perceptions of occupational risks. Special attention was paid to the risk level of the worker's workgroup, existence of family responsibilities, organizational safety culture, and measures of accident rates. RESULTS: Individuals showed different perceptions of risk based on their personal and work characteristics. Significant associations were observed between each variable of interest and risk perception. Overall, the results remain robust across specifications addressing both simultaneity and ordinality. CONCLUSIONS: Employees' "reading" of hazards was not fully aligned with objective information on occupational accidents but depended on individual characteristics. Having family responsibilities or being unionized increased workers' risk perception, whereas belonging to a workgroup with higher accident rates reduced it. PRACTICAL APPLICATIONS: Knowing how workers perceive risk and how this perception deviates from statistical information on accidents are essential for management to accurately design safety measures. In this regard, specific characteristics such as age, having dependents in the family, or the typology of the workers' workgroup should be taken into account. Greater knowledge of preventive measures will improve the way workers perceive risk, and ultimately contribute to reducing the likelihood of occupational accidents.

Safety: A collective and embedded competency. An ethnographic study of safety practices at an industrial workplace in the Netherlands.

INTRODUCTION: Organizations place strong emphasis on the standardized occupational health and safety procedures to reduce work-related illnesses and workplace accidents. However, standardized procedures are not always followed up in daily work practices. Organizations must cope with the differences between standardized procedures and local adaptation by employees. METHODS: This ethnographic field study at an industrial workplace in the Netherlands provides insights into employees' everyday work practices, how these work practices are shaped, and how they relate to local occupational health and safety procedures. Acknowledging safety as a competency embedded in work practices, as introduced by Gherardi and Nicolini (2002), offers a theoretical point of view for looking beyond the dichotomy of standardization and local adaptations. RESULTS: The results show that a standardized and noncontextualized occupational health and safety management system that focuses on accident-free days and compliance actually leads to ignorance of practical and tacit competences of workers and no learning and improvement of safety procedures can take place. However, our findings also illustrate how employees in their informal everyday work practices reduce the risks produced by the safety system itself. CONCLUSION: Overall, the results indicate that social interactions among employees, leaders, and management within the organization play an important role in workplace safety. The analysis highlights the value of vulnerability and trust in relationships at work to be able to learn and develop safety procedures that align with local demands. PRACTICAL APPLICATIONS: This study emphasizes the need for participatory approaches in creating safer and healthier workplaces. The cocreation of occupational health and safety (OHS) rules and procedures, however, can only function if they are combined with a responsive leadership style.

Descriptive summary of fatal work-related injuries, Western States, 2011-2017.

Work-related deaths are a persistent occupational health issue that can be prevented. However, prevention opportunities can be hampered by a lack of adequate public health resources. The Western States Occupational Network (WestON) is a network of federal, state, and local occupational health professionals that includes a 19-state region of the United States. To encourage public health collaboration, WestON partners examined work-related fatalities within the region. Fatality counts (numerators) were obtained from the U.S. Bureau of Labor Statistics (BLS) Census of Fatal Occupational Injuries restricted-access research files for all workers ages ≥15 years and fatally injured in WestON states from 2011 through 2017. Estimates of full-time equivalent hours worked (FTE) (denominators) were retrieved from the BLS Current Population Survey. Annual average fatality rates were calculated as number of fatalities per 100,000 FTE over the study period. Rates were stratified by state, select demographics, industry sector, and event/exposure types. Pearson chi-squared tests and rate ratios with 95% confidence probability limits were used to assess rate differences. All analyses were conducted using SAS v.9.4. From 2011 through 2017, the annual average overall occupational fatality rate for the WestON region was 3.5 fatalities per 100,000 FTE, comparable to the overall U.S. fatality rate. Male workers had a fatality rate almost 10 times higher than female workers in the region. Fatality rates increased with successive age groups. Alaska and New Mexico had significantly higher fatality rates for all racial/ethnic groups compared to respective regional rates. Wyoming, North Dakota, and Montana had the three highest occupational fatality rates among foreign-born workers. Agriculture/forestry/fishing, mining/oil/gas extraction, and transportation/warehousing/utilities were industry sector groups with the three highest fatality rates regionally. Transportation-related incidents were the most frequent event type associated with occupational fatalities for all 19 states. Work-related fatalities are a crosscutting occupational public health priority. This analysis can be an impetus for collaborative multistate initiatives among a dynamic and varied occupational public health network to better meet the needs of a rapidly changing workforce.

Correlational analysis of occupational accidents and the safety policies in the Chinese coal mining industry from 2008 to 2021.

This study investigates the correlation between previous coal mine safety policies and accidents in China. Data on coal mine accidents and government regulatory information from 2008 to 2021 are collected. The characteristics of coal mine accidents are analyzed, and safety policy indexes are identified. An ordinary least squares (OLS) regression model is established to quantitatively analyze the correlation between accidents and safety policy. The study finds that safety policies have some impact on accident occurrence in coal mines. Although there has been a decrease in accidents and deaths over time, higher mortality rates are observed during periods of increased production intensity and on weekends. Gas accidents are the most common, followed by roof and flood accidents. The study concludes that national safety policies with wider coverage and a stronger system are effective in preventing accidents, but caution should be exercised to avoid reduced vigilance with decreasing death rates.

Research on the decision-making of work safety investment in industrial park enterprises: evidence from behavioral experiments.

Due to the clustering of risk factors, industrial park safety accidents can easily trigger a domino effect. Work safety investment is the foundation of enterprise work safety in industrial parks. Therefore, increasing the work safety investment of enterprises in industrial parks is the key condition to prevent accidents. However, due to the typical negative externalities of industrial park work safety accidents, the decision-making process of work safety in park enterprises is influenced by other enterprises within the park, including imitation behaviors. This makes the decision-making of work safety in park enterprises very specific. In order to clarify the influencing factors and effects of work safety investment in industrial park enterprises, this study uses a behavioral experiment method and conducts decision-making experiments using the experimental platform O-Tree. The study recruits 76 participants who play the role of decision-makers in park enterprises. This study uses a lottery price experiment and a dictator experiment to measure the risk preference and altruism preference of the participants, respectively. The study introduces the real background of work safety investment in industrial park enterprises and collects data on work safety investment by the participants in different experimental scenarios. The research results show that the safety attitudes of decision-makers, altruism preference, accident experience, government work safety supervision, park management measures, and safety benefits positively influence work safety investment in park enterprises. The risk preference of decision-makers and the resource capability of work safety negatively influence work safety investment in park enterprises. Work safety investment in park enterprises is influenced by the work safety investment of other enterprises within the park.

A model based on PDCA and data mining approach for the prevention of occupational accidents in the plumbing activity in the construction sector.

BACKGROUND: Occupational accidents in the plumbing activity in the construction sector in developing countries have high rates of work absenteeism. The productivity of enterprises is heavily influenced by it. OBJECTIVE: To propose a model based on the Plan, Do, Check, and Act cycle and data mining for the prevention of occupational accidents in the plumbing activity in the construction sector. METHODS: This cross-sectional study was administered on a total of 200 male technical workers in plumbing. It considers biological, biomechanical, chemical, and, physical risk factors. Three data mining algorithms were compared: Logistic Regression, Naive Bayes, and Decision Trees, classifying the occurrences occupational accident. The model was validated considering 20% of the data collected, maintaining the same proportion between accidents and non-accidents. The model was applied to data collected from the last 17 years of occupational accidents in the plumbing activity in a Colombian construction company. RESULTS: The results showed that, in 90.5% of the cases, the decision tree classifier (J48) correctly identified the possible cases of occupational accidents with the biological, chemical, and, biomechanical, risk factors training variables applied in the model. CONCLUSION: The results of this study are promising in that the model is efficient in predicting the occurrence of an occupational accident in the plumbing activity in the construction sector. For the accidents identified and the associated causes, a plan of measures to mitigate the risk of occupational accidents is proposed.

Enhancing safety of construction workers in Korea: an integrated text mining and machine learning framework for predicting accident types.

Construction workers face a high risk of various occupational accidents, many of which can result in fatalities. This study aims to develop a prediction model for nine prevalent types of construction accidents, utilizing construction tasks, activities, and tools/materials as input features, through the application of machine learning-based multi-class classification algorithms. 152,867 construction accident summary reports, composed of both structured (construction task, construction activity, accident type) and unstructured data (tools/materials) were used for the study. The study employed several data processing techniques, including keyword extraction through text mining, Boruta feature selection, and SMOTE data resampling enhance model accuracy. Three performance metrics (Multi-class area under the receiver operating characteristic curve (MAUC), Multi-class Matthews Correlation Coefficient (MMCC), Geometric-mean (G-mean)) were used to compare the predictive performance of four machine learning algorithms, including Decision tree, Random forest, Naïve bayes, and XGBoost. Of the four algorithms, XGBoost showed the highest performance in predicting accident type (MAUC: 0.8603, MMCC: 0.3523, G-mean: 0.5009). Furthermore, a Shapley additive explanation (SHAP) analysis was conducted to visualize feature importance. The findings of this study make a valuable contribution to improving construction safety by presenting a prediction model for accident types derived from real-world big data.

Tractors, Trees, and Rollover Protective Structures: A Cause for Concern.

Injury and fatality events that are caused by tree work and tractor-related activities contribute to the already elevated rates of work-related injuries in the agriculture and logging sectors. This brief report highlights the circumstances surrounding these events, as well as a number of surveillance sources that identify the extent to which they contribute to the injury burden in these hazardous industries. These data sources include fatality investigations, agricultural injury news reports, consumer product injury data captured from emergency rooms and near-miss reporting data captured from individuals participating in the National Rollover Protective Structure Rebate Program (NRRP). Several recommendations for further research and interventional efforts are outlined, with particular consideration of the manner in which rollbars have been involved in falling object incidents.