Dataset Information

Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China.

ABSTRACT: The metallurgical industry is a significant component of the national economy. The main purpose of this study was to establish a composite risk analysis method for fatal accidents in the metallurgical industry. We collected 152 fatal accidents in the Chinese metallurgical industry from 2001 to 2018, including 141 major accidents, 10 severe accidents, and 1 extraordinarily severe accident, together resulting in 731 deaths. Different from traffic or chemical industry accidents, most of the accidents in the metallurgical industry are poisoning and asphyxiation accidents, which account for 40% of the total number of fatal accidents. As the original statistical data of fatal accidents in the metallurgical industry have irregular fluctuations, the traditional prediction methods, such as linear or quadratic regression models, cannot be used to predict their future characteristics. To overcome this issue, the grey interval predicting method and the GM(1,1) model of grey system theory are introduced to predict the future characteristics of fatal accidents in the metallurgical industry. Different from a fault tree analysis or event tree analysis, the bow tie model integrates the basic causes, possible consequences, and corresponding safety measures of an accident in a transparent diagram. In this study, the bow tie model was used to identify the causes and consequences of fatal accidents in the metallurgical industry; then, corresponding safety measures were adopted to reduce the risk.

SUBMITTER: Xu Q

PROVIDER: S-EPMC7312879 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China.

Xu Qingwei Q Xu Kaili K

International journal of environmental research and public health 20200527 11

The metallurgical industry is a significant component of the national economy. The main purpose of this study was to establish a composite risk analysis method for fatal accidents in the metallurgical industry. We collected 152 fatal accidents in the Chinese metallurgical industry from 2001 to 2018, including 141 major accidents, 10 severe accidents, and 1 extraordinarily severe accident, together resulting in 731 deaths. Different from traffic or chemical industry accidents, most of the acciden ...[more]

PMID: 32471060

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Project description:IntroductionThis research aims to estimate the relative risks of responsibility for a fatal accident linked to driving under the influence of cannabis or alcohol, the prevalence of these influences among drivers and the corresponding attributable risk ratios. A secondary goal is to estimate the same items for three other groups of illicit drugs (amphetamines, cocaine and opiates), and to compare the results to a similar study carried out in France between 2001 and 2003.MethodologyPolice procedures for fatal accidents in Metropolitan France during 2011 were analyzed and 300 characteristics encoded to provide a database of 4,059 drivers. Information on alcohol and four groups of illicit drugs derived from tests for positivity and potential confirmation through blood analysis. The study compares drivers responsible for causing the accident, that is to say having directly contributed to its occurrence, to drivers involved in an accident for which they were not responsible, and who can be assimilated to drivers in general.ResultsThe proportion of persons driving under the influence of alcohol is estimated at 2.1% (95% CI: 1.4-2.8) and under the influence of cannabis at 3.4% (2.9%-3.9%). Drivers under the influence of alcohol are 17.8 times (12.1-26.1) more likely to be responsible for a fatal accident, and the proportion of fatal accidents which would be prevented if no drivers ever exceeded the legal limit for alcohol is estimated at 27.7% (26.0%-29.4%). Drivers under the influence of cannabis multiply their risk of being responsible for causing a fatal accident by 1.65 (1.16-2.34), and the proportion of fatal accidents which would be prevented if no drivers ever drove under the influence of cannabis is estimated at 4.2% (3.7%-4.8%). An increased risk linked to opiate use has also been found to be significant, but with low prevalence, requiring caution in interpreting this finding. Other groups of narcotics have even lower prevalence, and the associated extra risks cannot be assessed.ConclusionAlmost a decade separates the present study from a similar one previously conducted in France, and there have been numerous developments in the intervening years. Even so, the prevalence of drivers responsible for causing fatal accidents under the influence of alcohol or narcotics has stayed remarkably stable, as have the proportion of fatal accidents which could in theory be prevented if no drivers ever exceeded the legal limits. The overall number of deaths from traffic accidents has dropped sharply during this period, and the number of victims attributable to alcohol and/or cannabis declined proportionally. Alcohol remains the main problem in France. It is just as important to note that one in two drivers considered to be under the influence of cannabis was also under the influence of alcohol. With risks cumulating between the two, it is particularly important to point out the danger of consuming them together.

Project description:The objective of this work is to advance the understanding of helicopter accidents by examining and quantifying the association between helicopter-specific configurations (number of main rotor blades, number of engines, rotor diameter, and takeoff weight) and the likelihood of accidents. We leverage a dataset of 8,338 turboshaft helicopters in the U.S. civil fleet and 825 accidents from 2005 to 2015. We use the dataset to develop a logistic regression model using the method of purposeful selection, which we exploit for inferential purposes and highlight the novel insights it reveals. For example, one important question for the design and acquisition of helicopters is whether twin-engine turboshaft helicopters exhibit a smaller likelihood of accidents than their single-engine counterparts, all else being equal. The evidence-based result we derive indicates that the answer is contingent on other covariates, and that a tipping point exists in terms of the rotor diameter beyond which the likelihood of accidents of twin-engines is higher (worse) than that of their single-engine counterparts. Another important result derived here is the association between the number of main rotor blades and likelihood of accidents. We found that for single-engine turboshaft helicopters, the four-bladed ones are associated with the lowest likelihood of accidents. We also identified a clear coupling between the number of engines and the rotor diameter in terms of likelihood of accidents. In summary, we establish important relationships between the different helicopter configurations here considered and the likelihood of accident, but these are associations, not causal in nature. The causal pathway, if it exists, may be confounded or mediated by other variables not accounted for here. The results provided here lend themselves to a rich set of interpretive possibilities, and because of their significant safety implications they deserve careful attention from the rotorcraft community.

Project description:Maritime search and rescue (SAR) remains a great global challenge because of the long distances, harsh environment and complicated trauma. A systematic investigation and analysis of China Maritime Search and Rescue Center (CMSRC) data has been lacking. This study aimed to provide more insightful information for future development of a better maritime and aquatic SAR system in China. This retrospective study retrieved and analyzed data on the water traffic volume from The Ministry of Transportation, People's Republic of China website and SAR data on ship accidents between January 1, 2008 and December 31, 2019. Spearman's correlation test was performed to analyze the data for the number of ship accidents, number of persons in distress, number of rescued persons, SAR success rate, and SAR forces. The χ2 test was used to assess significant changes in the proportion of ship accident locations, categories, dispatched SAR forces, and location of deaths annually. The Cox Stuart test was applied to determine the trends in the data from 2008 to 2019. Between 2008 and 2019, a total of 24,013 ship accidents were reported and recorded by the CMSRC surveillance system; 209,948 persons in distress because of ship accidents were reported; 8,051 individual deaths from ship accidents. Water traffic volume and ship carrying capacity increased while the annual number of persons in distress, ship collisions, and ship collision-related deaths decreased. The SAR success rate (96.17%±0.92%) did not improve despite an increase in the number of rescue ships dispatched during this period. Helicopters (92.40±20.58 min) arrived faster than rescue ships (283.75±40.96 min) but the dispatched number of helicopters did not increase during this period. The average arrival time of nearby passing ships (41.90±7.98 min) was the shortest. CMSRC efforts mitigated the growth of ship accidents despite increasing traffic volume. More dispatched rescue ships did not improve the SAR success rate without saving arrival time. Future SAR protocols may need to increase and strengthen the role of helicopters and nearby passing ships to improve the SAR success rate.

Project description:BackgroundAnger is associated with dysfunction following potentially traumatic events. It is still unclear to what extent different types of anger are differentially related to poor outcomes. To advance knowledge in this area, the Posttraumatic Anger Questionnaire (PAQ) was designed, measuring anger directed at (i) the justice system, (ii) other people, (iii) the self, (iv) people held accountable for the potential traumatic event, and (v) a desire for revenge to those held responsible. Preliminary evidence shows that these types of anger are distinguishable and differentially associated with posttraumatic stress (PTS). No studies have yet examined whether such findings can be generalized to victims of non-fatal traffic accidents, one of the most common potentially traumatic events.ObjectiveThis study's aims were (i) to establish if the five-factor structure of the PAQ found in prior studies could be replicated, (ii) to explore whether the intensity of emerging types of anger differed, and (iii) to explore the associations of anger-types with levels of PTS, depression, and functional impairment.MethodTwo-hundred and fifty adults who experienced a traffic accident completed the PAQ and instruments measuring PTS, depression, and functional impairment. They also answered questions about their socio-demographic characteristics and features of the accident.ResultsConfirmatory factor analysis confirmed that the PAQ measures five types of anger. Levels of anger at people held accountable were the highest. Structural equation modelling showed that both anger at others and anger at the self, but not the other three anger types, were associated with PTS, depression, and functional impairment, when controlling for the shared variance between the anger types, socio-demographic variables, and features of the accident.ConclusionsFindings illustrate the potential importance of considering different types of anger when assessing and treating PTS following traffic accidents.HighlightsBased on data from people confronted with a traffic accident, we found the Posttraumatic Anger Questionnaire (PAQ) to represent distinguishable dimensions of anger.Anger dimensions were: anger directed at (i) the justice system, (ii) other people, (iii) the self, (iv) people held accountable for the event, and (v) a desire for revenge to those held responsible.Scores on items measuring anger at people held accountable for the event were significantly higher than scores on items measuring other anger types.Anger at the self and other people were most strongly associated with posttraumatic stress, depression, and functional impairment.

Dataset Information

Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China.

Publications

Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China.

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