Dataset Information

Analysis of the Characteristics of Fatal Accidents in the Construction Industry in China Based on Statistical Data.

ABSTRACT: Background: Construction activities not only provide the necessary conditions for citizens to live, but also cause fatal accidents. Methods: This study aimed to reveal the characteristics of fatal accidents in the construction industry in China based on statistical data. From 2010 to 2019, there were 6005 fatal accidents in China's construction industry causing 7275 deaths. The important features of these fatal accidents, such as the type, time of occurrence, site location, severity, and geographical region of the accident, were carefully analyzed. Results: There were 258 major and severe construction accidents causing 1037 deaths, accounting for 4.3% and 14.25% of the total number of construction accidents and deaths in this period, respectively. As an important finding, more deaths occurred in August and on Mondays. The greatest number of construction accidents took place along openings and edges, accounting for 22.9% of all fatal accidents. Taking into account their economic development level and number of employees, Qinghai and Hainan experienced a higher mortality rate than Jiangsu. Falls from a high place were the dominant type of construction accident, accounting for 51.66% of all accidents. However, collapses were the primary type of major and severe construction accident, accounting for 60.09% of such accidents. The predicted number of construction deaths in 2020 is 887 according to the GM(1,1) model. Corresponding safety measures should be adopted to improve the working environment of the construction industry. Implications: The implications of these results with respect to the characteristics of construction accidents can be regarded as the foundation for accident prevention in practice.

SUBMITTER: Xu Q

PROVIDER: S-EPMC7926821 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Analysis of the Characteristics of Fatal Accidents in the Construction Industry in China Based on Statistical Data.

Xu Qingwei Q Xu Kaili K

International journal of environmental research and public health 20210223 4

<i>Background</i>: Construction activities not only provide the necessary conditions for citizens to live, but also cause fatal accidents. <i>Methods:</i> This study aimed to reveal the characteristics of fatal accidents in the construction industry in China based on statistical data. From 2010 to 2019, there were 6005 fatal accidents in China's construction industry causing 7275 deaths. The important features of these fatal accidents, such as the type, time of occurrence, site location, severit ...[more]

PMID: 33672141

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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: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.

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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.

Dataset Information

Analysis of the Characteristics of Fatal Accidents in the Construction Industry in China Based on Statistical Data.

Publications

Analysis of the Characteristics of Fatal Accidents in the Construction Industry in China Based on Statistical Data.

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