Risk Factors For Accidents Research Articles

Analysis of coal mining accident risk factors based on text mining

Frequently occurring coal mine safety accidents have caused great casualties and economic losses. Coal mine intelligence is the core technical support for the high-quality development of the coal industry. The deep integration of coal mining safety production management and Artificial Intelligence (AI) technology is practically significant to achieve accident prevention. To efficiently identify mining accident risk factors and explore mechanism of coupling between risk factors, this study mined 400 reported cases of mining accidents in Shanxi Province and identified 64 accident risk factors through custom, stopword, synonym dictionary construction, keyword extraction and keyword correlation analysis. Then, this study constructed association rules and a Bayesian causal network. The major risk factors are identified using a comprehensive high-frequency, sensitivity, strength and key path analysis of the Bayesian causal network. The following seven risk factors are found to play a major role in the occurrence of mine accidents: inadequate safety supervision, disordered safety management, illegal organization of production, inadequate staff safety education and training, operation against rules, command against rules and weak safety consciousness among the staff. Finally, a case study is conducted to validate the reliability of the results. This study solves the problem of incomplete extraction of key feature information in coal mine reports and the lack of analyses of coupling mechanisms between coal mine risk factors in traditional accident analysis methods, providing the methodological support for the effective use of unstructured coal mine safety production data for risk analysis.

Awareness of Domestic Accidents Among Mothers of Children Aged Less than 10 Years in an Urban Locality of South Karnataka: A Cross-Sectional Study

Introduction: Domestic accidents are one of the five leading causes of death due to injuries in industrialised and developed countries. Awareness about domestic accidents and their prevention can help in eliminating risk factors of accidents. Since children are vulnerable to accidents, the immediate caregivers must have adequate knowledge regarding the causes and prevention to reduce the morbidity and mortality due to accidents. Objective: To study the socio-demographic profile of the study subjects; To assess the knowledge on prevention of domestic accidents among mothers of children aged less than 10 years. Methods: A cross-sectional study was undertaken in the urban field practice area of a medical college in Southern Karnataka among mothers of children aged less than 10 years using a pre-structured proforma. Data was analysed using descriptive and inferential statistics. Results: A total of 385 mothers were part of the study. 51.4% had good knowledge regarding domestic accidents and their prevention. There was a statistically significant association between the level of awareness of domestic accidents with maternal age, educational status, occupation, religion, type of family and standard of living. Conclusion: The knowledge of domestic accidents and their prevention was 51.4%.

Variable selection methods for Log-Gaussian Cox processes: A case-study on accident data

In order to prevent and/or forecast road accidents, the statistical modeling of spatial dependence and potential risk factors is a major asset. The main goal of this article is to predict the number of accidents on a certain area by considering georeferenced accident locations crossed with variables characterizing the studied geographical area such as road characteristics as well as sociodemographic and global infrastructure variables. We model the accident point pattern by a spatial log-Gaussian Cox process (LGCP). To reduce the computation burden of LGCP models in this high-dimensional setting, we suggest a two-step procedure: to perform first automatic variable selection methods based on Poisson regression, Poisson aggregation and random forest and in a second step, to use the selected variables and perform LGCP model analysis. The dataset consists in road accidents occurred between 2017 and 2019 in the CAGB (urban community of Besançon), France. Based on LGCP analysis, we are able to identify the principal risk factors of road accidents and risky areas from CAGB region.

Real-time risk assessment of multi-parameter induced fall accidents at construction sites

In this research, a risk assessment model was developed that concurrently considers the location and physiological risk factors for fall accidents in workers at construction sites. In terms of location risk, data on 1683 occupational fall accidents involving 1718 worker casualties in the construction industry were collected for the period 1996–2016 from the Institute of Labor, Occupational Safety and Health (ILOSH), Taiwan. Next, the locations of these fall accidents were identified and defined as hazardous areas, with each area assigned a fall-risk level based on the average number of occupational accidents per year. In terms of physiological risk, the thermal hazard evaluation model, Recommended Alert Limits/Recommended Exposure Limits (RALs/RELs), developed by the National Institute for Occupational Safety and Health (NIOSH), USA was used in this study. This model uses metabolic heat and wet bulb globe temperature (WBGT) to recommend hourly rest/work times for workers. Using WBGT and one hour as the basic unit of time, varying degrees of metabolic heat, defined as metabolic heat loading severity (MHLS), were obtained. An optical heart rate (HR) sensor was applied in this study to measure HR, which was subsequently converted to a metabolic heat value using the Malchaire J metabolic heat evaluation model. Next, metabolic heat loading risk level was evaluated based on the MHLS. Finally, the location-based fall-risk level was multiplied by the MHLS, generating a risk evaluation model for fall accidents. The evaluation results identify the real-time fall-risk level of each worker and, if needed, suggest actions to be taken to mitigate the elevated risks of fall accidents identified by the model.

A Mini Review (PRISMA) on Causes of Incidents and Injuries Occurring in Agricultural Workplaces

Agriculture, alongside construction and mining, is one of the three most hazardous industries, and is characterized by numerous risk factors for occupational accidents. Unlike other industries, agriculture faces significant safety concerns related to the natural environment. Determining the causes of accidents is therefore imperative for accident prevention. However, the difficulty in investigating accidents owing to inadequate reporting and management systems among self-employed farmers hampers the determination of their causes. This study aims to determine the factors influencing agricultural accidents through a literature review. A systematic literature search was conducted according to the PRISMA guidelines. The initial search yielded 165 articles of which 34 papers were selected after removing those by applying the selection criteria. The selected papers were categorized into three domains: work accidents, machinery accidents, and farmer safety promotion. Accident causes were classified using the 4M technique: machine, media, man, and management. The results were visualized with a heat map. The main causes of accidents thus identified were insufficient operation/management, inappropriate work situation, and insufficient education/training. The findings of this study can serve as foundational data for developing measures to improve working environments not only in agriculture but also in other high-hazard industries.

Therapeutic role of yoga in hypertension.

Systemic hypertension is an established risk factor for coronary artery disease and cerebrovascular accident and control of blood pressure reduces the risk of a major cardiovascular event. Both non-pharmacological and pharmacological treatment options are available to treat hypertension. Yoga, recently received more attention as a treatment modality for various lifestyle disorders, even though practiced in India since ancient times. In this review, we are analyzing the role of yoga in the treatment of systemic hypertension.

Identifying excessive chronic alcohol use with phosphatidylethanol in patients with suspected severe injury-results from the IDART study.

Acute and chronic alcohol use are well-known risk factors for accidents and injuries, and concurrent psychoactive drug use can increase injury risk further. Phosphatidylethanol (PEth) 16:0/18:1 is a biomarker used to determine alcohol consumption the previous 3-4 weeks. The aim was to investigate the prevalence of chronic alcohol use in trauma patients, as determined by PEth 16:0/18:1 concentrations, and how excessive chronic alcohol use relate to demographic variables, injury mechanisms and drug use. Patients received at Norwegian trauma hospitals from March 2019 to February 2020. The study is part of the Impairing Drugs and Alcohol as Risk factors for Traumatic Injuries study. All patients aged ≥ 16 years received with trauma team were included in the study. Data on injury date and mechanism, gender and age was registered. Blood samples were analyzed for 22 psychoactive medicinal and illicit drugs, ethanol and phosphatidylethanol 16:0/18:1. Regression analyses were conducted to assess associations between alcohol use and gender, age, injury mechanism and drug use. Of the 4845 patients included in the study, 10% had PEth 16:0/18:1 concentration ≥ 600 nM (~430 ng/mL), indicative of excessive chronic alcohol use. Being male, between 44-61 years old, involved in violence, and testing positive for medicinal drugs was associated with excessive chronic alcohol use.Excessive chronic alcohol use was common among males, middle-aged, patients with violence as injury mechanism and those with medicinal drug use. These findings emphasize the need to detect and treat excessive chronic alcohol use among trauma patients.

INVESTIGATING THE RISK FACTORS AFFECTING THE OCCURRENCE, FREQUENCY, AND SEVERITY OF LARGE TRUCK ACCIDENTS IN AL-NAJAF GOVERNORATE, IRAQ

In spite of the established literature-based evidence regarding the consequences of large truck accidents, limited body of research has been done on the characteristics and risk factors of such road accidents in Iraqi cities and governorates. According to national statistics, there has been a steady increase in the number of trucks and truck-related crashes over the past ten years. This paper aims to investigate the characteristics and risk factors associated with accidents involving large trucks in Al-Najaf governorate. A sample of 400 truck drivers were randomly selected and interviewed to collect the needed accident data. Four generalized linear models have been built; ordinal regression model for total injuries, binary logistic model for fatal accident occurrence, multinomial logit model for accident frequency, and ordinal regression model for accident cost. The analysis results revealed several influential predictors including truck driver age, education level, type of collision, truck speed, truck type, and street lighting condition. The obtained findings should be enlightening and helpful for government organizations looking to promote safety measures for sustainable freight truck transport.

Analisis Faktor-Faktor Kinerja Sistem Keselamatan Kerja Konstruksi Proyek Bangunan Gedung Dinas Pendidikan Kota Sungai Penuh

The Indonesian government through the minister of Public Works and Public Housing has recently issued regulation Number 10 of 2021 concerning guidelines for construction safety management systems. The SMK3 Occupational Health and Safety Management System is part of the company's overall management system in order to control risks related to work activities in order to create a safe, efficient and productive workplace. The Construction Safety Management System is required to be implemented during construction because it is also part of the planning and control of the BPSDM PUPR project, 2021. In fact, in Sungai Full city in 2019-2021 experienced labor accidents, one of the projects was a school construction project at the Sungai Full City Education Office which could not be separated from the risk factors for accidents to its workers. Based on secondary data related to work accident information at the Sungai Full City education office School Building Construction Project, information was obtained that there had been 68 accident cases during 2019 – 2021. The purpose of this study is to identify the dominant factors and factors in the Implementation of Improving Performance Aspects of the Work Safety Management System of the Education Building Project in Sungai Full City, as well as providing solutions to improve the Performance of the Work Safety Management System. This study used quantitative methods by distributing questionnaires to respondents. The results of the research conducted there are 6 factors in the Work Safety Management System (SMKK) implemented in the implementation of the Education Building Project in Sungai Full City, consisting of Commitment factors, Project Managerial factors, K3 Regulations and Procedures factors, Worker Communication factors, Worker Competence factors, Work Environment factors, and Worker Involvement factors in K3.

The Influence of Unsafe Behavior and Workspace Arrangement on Occupational Accidents Among Workers at Pt Maruki International Indonesia Makassar

Objective: Workplace accidents are unplanned and uncontrolled incidents that occur during work due to unsafe actions and unsafe conditions, leading to the interruption of work activities. This study aims to investigate the influence of behavior and workspace layout on workplace acidentes.
 
 Method: This research employs a quantitative approach with a case-control study design. Questionnaires were distributed to 57 workers, comprising 19 cases of workplace accidents and 38 controls without workplace accidents at PT Maruki Internasional Indonesia. Collected data include gender, age, tenure, behavior, and workspace layout. The gathered data in Excel tables will be analyzed using chi-square tests and logistic regression analysis.
 
 Result: The most common type of workplace accident is found among male workers (OR=4.065 [CI 95%: 0.462-35.752]; p=0.247). Unsafe work behavior (OR=18.417 [CI 95%: 3.656-92.779]; p=0.000) and workspace layout (OR=5.385 [CI 95%: 1.587-18.264]; p=0.010) are significant factors. Further logistic regression analysis reveals that variables influencing workplace accidents at PT Maruki Internasional Indonesia are work behavior and workspace layout
 Conclussion: Behavior and workspace layout are the most influential risk factors for workplace accidents, with unsafe work behavior being the most significant risk fator.
 
 Implication of the research: This research can contribute to raising public awareness about the importance of workplace accident impacts and encourage people to be more cautious while working.

Evaluation of Traffic Accidents in the Province of Albay: Basis for Sustainable Traffic Management Framework

The traffic safety situation around the world is still not optimistic. Accidents occur due to a combination of factors and are rarely caused by a specific reason. Risk factors are a better explanation for why traffic accidents occur. This study determined the traffic accidents in the province of Albay. It identified the number of reported traffic accidents in the Province of Albay covering Calendar Year 2020 to 2022. It also determined the causes and risk factors of traffic accidents regarding driver's behaviors, road conditions, vehicle conditions, traffic signs, and traffic management. Moreover, it inferred a significant agreement among the ranks regarding the causes and risk factors of traffic accidents. It proposed a traffic management framework to prevent traffic accidents in the province of Albay. The respondents of this study are 60 personnel from the three CPS in Albay, 30 from the Local Government Unit, and 47 community, representing the riders and commuters in the Poblacion area. The study revealed a concerning prevalence of traffic accidents, underscoring a pressing public concern due to the high number of casualties and severity of outcomes. Despite this, road safety has not received sufficient attention, attributed to a lack of awareness regarding the problem's extent, associated costs, and effective interventions. Implementing a comprehensive traffic management framework involving collaboration among stakeholders is crucial for understanding and addressing the multifaceted causes of accidents, emphasizing the importance of community-wide initiatives and cooperation among various entities to enhance public awareness and promote responsible driving behavior.

A New Screening Tool (BAMSA) for Sleep Apnea in Male Professional Truck Drivers.

Obstructive sleep apnea (OSA) is common in professional truck drivers. It is important that OSA is recognized since undiagnosed and/or untreated sleep apnea is a risk factor for sleepiness-related traffic accidents. In this study, we developed a new simple tool to screen for obstructive sleep apnea (OSA) in this population. Altogether, 2066 professional truck drivers received a structured questionnaire. A total of 175 drivers had a clinical examination and were invited to participate in sleep laboratory studies, including cardiorespiratory polygraphy. We studied associations of different risk factors with the presence of sleep apnea. We established a new simple screening tool for obstructive sleep apnea (OSA) that was compared to other existing screening tools. A total of 1095 drivers completed the questionnaire. Successful cardiorespiratory polygraphy was obtained for 172 drivers. Full data were available for 160 male drivers included in the analyses. The following five risk factors for sleep apnea formed the BAMSA score (0 to 5): BMI > 30 kgm-2, age > 50 years, male gender, snoring at least one night per week, and the presence of apnea at least sometimes. BAMSA showed a sensitivity of 85.7% and a specificity of 78.8% in detecting AHI ≥ 15 when using a cut-off point of 4, and the ROC area was 0.823. BAMSA is a sensitive and easy-to-use tool in predicting obstructive sleep apnea in male professional drivers.

Analysis of Accidents in Petroleum and Chemical Industries

This study determined the critical risk factors that influence the risk of major accidents in petroleum and chemical industries. The retrospective study assessed five iconic accidents using the tripod beta analysis methodology. These failures were aggregated into critical risk factors for these major accidents. The findings of this study revealed empirically that there are broadly five critical risk factors that influence the risk of major accidents: (i) design flaws, (ii) site process safety management, (iii) barrier management / control, (iv) operating procedures, and (v) process safety culture. These findings highlight that major accident risks can accumulate “dangerous” from the impairment of safety-critical barriers and that the operators of petroleum and chemical facilities may be blind-sided to the cumulative risk of the impairments. The findings also highlight the need for a proactive risk assessment tool with the capability to check the health of safety-critical barriers on a real time basis, in an operating plant. The use of Tripod Beta as a tool in accident causation analysis is recommended

Risk factors as causes of accidents: Criterion of causality, logical structure of relationship to accidents and completeness of explanations

The causes of accidents are studied in the belief that by finding causes, accidents can be prevented by removing or controlling their causes. It follows that the risk factors that have traditionally been regarded as contributing to accidents can only be regarded as causes if it is possible to alter them by means of one or more road safety measures. Risk factors are causes if their relationship to accidents can be changed by implementing one or more road safety measures influencing the risk factors. Hence, road safety measures that could have been implemented to change risk factors identified as contributing to an accident, but have not, are also causes of accidents. Many of the human factors that have traditionally been identified as risk factors for accidents, like age, gender, driving experience, expectations or involuntary inattention are not causes of accidents, because they cannot be changed by means of any realistic road safety measure. What cannot be changed (could not have been different) is not a cause. It is possible, both in case studies and in statistical analyses, to determine when a set of factors precipitating or contributing to accidents is complete. A list of road safety measures that could have been implemented is only limited by our creativity and imagination and will therefore never be complete.

Coupling analysis of crane accident risks based on Bayesian network and the N-K model

Crane usage is pervasive on construction sites, however, it is associated with a notably high accident rate. The analyzing of crane accident risks is essential for accident prevention, control, and ensuring the safety of lifting operations. Hence, significant emphasis should be placed on understanding the interaction among various risk factors. This paper proposes a quantitative coupling method for human, machine, management, and environmental risk factors in crane accidents, leveraging Bayesian networks (BN) and the N-K model. Firstly, text mining technology and fault tree analysis are employed to analyze the causes of crane accidents and categorize the associate risk factors. Secondly, the types of risk coupling resulting from human, machine, management, and environmental risk factors are defined. Thirdly, the BN model is developed based on the analysis of crane accident risksand its N-K model. Fourthly, the parameters of the risk coupling nodes in the developed BN are determined based on the calculation results of the N-K model. Finally, for the risk coupling types with high coupling values and the first-level node and second-level node, the failure probability is analyzed through posterior probability and sensitivity analysis. The results indicate that factors related to man and management significantly impact crane accidents and warrant enhanced attention. The interplay among multiple risk factors significantly influences the probability of crane accidents, necessitating careful attention.

Biosafety knowledge and perception among medical laboratory students: a cross-sectional study at a medical university in Vietnam

Introduction: Medical students have to deal with biohazards in laboratories during undergraduate studies and intensive practice in hospitals. Unsafe operators can result in an outbreak of biohazardous pathogens to healthcare workers, the community, and the environment. However, the most common risk factors for laboratory accidents are a lack of perception and knowledge of biosafety and laboratory safety management. This study aimed to assess knowledge and factors influencing the biosafety practices of medical students at Hanoi Public Health University, Vietnam Methods: A cross-sectional study was conducted to assess the biosafety knowledge of all 286 students majoring in a medical laboratory at HUPH from December 2021 to February 2022. Ethical clearance was obtained from the Ethics Committee of Hanoi University of Public Health. The questionnaire has been created based on WHO biosafety guidelines with some modifications according to the local context. The data were collected by face-to-face interviews Results:: Out of the 286 students invited to complete a biosafety questionnaire, 68.6% of students recognized the fundamental principles of biosafety. Additionally, 76.2% and 91% of students correctly identified risk factors and danger signs in the laboratory, respectively. Furthermore, 79.8% of students provided accurate answers to biosafety laboratory troubleshooting questions. Notably, academic performance, students’ year of study, and average scores in biosafety courses had significantly related to the biosafety knowledge. Gender factors and academic performance were related to the rate of obtaining precise knowledge about incident handling and preventing risk factors in the laboratory. Conclusion: The passed rate of biosafety knowledge among medical laboratory students at the University of Public Health was 68.6%. Factors such as the student's school year, academic performance, average score in the biosafety course number of internships in hospitals significantly affected their biosafety and troubleshooting knowledge in the laboratory.

Unveiling the Link: Anemia as a Risk Factor for Cerebrovascular Accidents

Anemia, a prevalent hematological condition characterized by decreased red blood cell count or hemoglobin levels, has emerged as a significant risk factor for cerebrovascular accidents (CVAs) and commonly known as strokes. This review explores the intricate connection between anemia and the occurrence of CVAs, elucidating the underlying mechanisms and clinical implications. Anemia contributes to stroke risk through multiple pathways, including impaired oxygen delivery to the brain, alterations in cerebral hemodynamics, and disruption of neurovascular homeostasis. Furthermore, iron deficiency anemia’s predominant etiology-not only exacerbates hypoxia but also compromises neuronal integrity, predisposing individuals to ischemic and hemorrhagic stroke events. The hemodynamic consequences of anemia, including cerebral hypo-perfusion and increased thromboembolic risk, underscore its role as a silent culprit in stroke pathogenesis. Anemia-induced alterations in blood viscosity, endothelial dysfunction, and compensatory vasodilation contribute to the vulnerability of cerebral vasculature to ischemic insults. Moreover, iron deficiency exacerbates neurocognitive impairment and promotes neuro degeneration, exacerbating the risk of vascular cognitive decline and hemorrhagic stroke. Routine screening for anemia, particularly in highrisk populations, coupled with targeted interventions aimed at correcting underlying etiologies and optimizing hemoglobin levels, is essential for mitigating stroke risk and improving clinical outcomes.

Risk Factors associated with Stress-related Riding Behavior among Indonesian Motorcyclists

The risk of road accidents is influenced by various elements, particularly human factor. In Indonesia, motorcycles contribute significantly to accidents due to insufficient knowledge of traffic laws and a lack of awareness about safe riding practices. Stress-related riding behavior, which may lead to this incident, is closely linked to driving discipline. Therefore, this study aimed to examine stress-related behavior as the risk factor in road accidents among motorcyclists. To achieve this, a self-reported questionnaire was distributed to 300 motorcyclists in Banda Aceh City and surrounding areas in Aceh Province. Factor analysis was used to simplify the number of indicators included, after which they were prioritized in order of importance. The results showed the most influential indicators out of the 26 considered in this study. A total of 3 underlying factor were identified, comprising anxious riding, aggressive riding, and anger. By addressing the risk factor associated with stress-related riding behavior, road safety in Indonesia was enhanced.

Research on safety accident risk of construction engineering based on natural language processing technology and neural network technology

Abstract In recent years, China’s construction industry has achieved rapid development, while the problem of safety accident risks brought by construction projects has also arisen. In this paper, based on natural language processing technology, using a graph neural network algorithm, we constructed a graph data model of safety accident reports in construction engineering and generated a database of association rules of safety risk factors in construction engineering to identify and classify the risk of safety accidents in actual construction engineering. The pictures of safety risk behaviors at the construction site are processed with feature mapping and inputted into a convolutional neural network to build a construction engineering safety warning model. Through simulation experiments, the identification results of risk factors for the model constructed in this paper and the effective degree of safety warning are tested. The top five factors in the centrality ranking of risk factors of construction engineering safety accidents are S17, S6, S1, S9, and S8, with centrality levels of 1.9779, 1.8626, 1.8204, 1.6332 and 1.4534, and the factor attribute of S6 is the outcome factor. The warning model constructed in this paper is measured against the level of safety risk of the construction project under the non-adoption of the warning model. The safety risk is reduced by 35.8% after the adoption of the safety accident warning model, which shows that the model in this paper has a certain inhibition effect on the risk of safety accidents.

Coupling Study on Risk Factors of Safety Accidents in Chemical Enterprises Based on N-K Model

In order to study the risk coupling characteristics of chemical safety accidents, risk classification and risk factor identification of chemical safety accidents are carried out, the coupling mode of chemical safety accident risk factors is analyzed, and an N-K model based on complex network is constructed. Based on the data of major chemical safety accidents in China from 2010 to 2020, the probability and risk coupling values of different risk coupling forms are calculated and the coupling forms with strong coupling are analyzed. The results indicate that the more risk factors involved in the coupling, the greater the risk possibility of safety accidents. In the risk coupling, management and equipment technical factors are the key coupling factors, so management and equipment maintenance should be strengthened. The coupling form with strong coupling should be avoided as far as possible to reduce or eliminate the occurrence of chemical safety accidents.