4.7 Article

Causal factors and risk assessment of fall accidents in the US construction industry: A comprehensive data analysis (2000-2020)

期刊

SAFETY SCIENCE
卷 146, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.ssci.2021.105537

关键词

Fall accidents; Accident prevention; Trends analysis; Logistic regression; Project management; Safety monitoring; Risk assessment

资金

  1. Department of Science and Technology of Sichuan Province [2019YJ0221]
  2. Natural Science Foundation of China [51808455]

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This study examines the leading factors of 23,057 fall accidents in the US construction industry over 20 years, finding that there are significant correlations under certain conditions. It also establishes a predictive model that can accurately diagnose the injury severity of accidents, providing technical support and recommendations for reducing fall accidents.
This study delves into investigating the leading factors of occurring 23,057 fall accidents in the United States construction industry over 20 years (1/2000-8/2020) recorded in the Occupational Safety and Health Administration (OSHA) database. Additionally, the contributions are elicited in terms of diverse dimensions of fall accident, such as project type, construction end-use, work activity, worker's occupation and age, fall location and height, accident time, injury degree, and fall protection. The data is analysed using frequency analysis to obtain the trends of fall accidents, correlation analysis between the accident factors and the injury degree, and logistic regression analysis to establish a prediction model that can diagnose fatal and nonfatal accidents. The results emphasized that the proportion of fall accidents increased substantially, and there was egregious evidence that the usage of fall protection has no considerable improvement. Besides, most of the fall accidents were (1) from heights<9.15 m, (2) among the roofers, (3) occurring on new commercial buildings and residential projects with low cost, (4) during the time intervals 10:00-12:00 and 13:00-15:00, (5) among older workers which alert that the experience might not be enough to diminish the accident. The correlation analysis revealed the fall factors that were significantly associated with the injury degree. Subsequently, a logistic regression model was done to predict the injury outcome (fatal/nonfatal). It was found that the prediction model could correctly diagnose the injury degree outcome by 77.7% depending on the selected predictors of the fall accident. Furthermore, the odds of reporting fatal or nonfatal accidents from the prominent factors of fall were calculated, enhancing the risk assessment to avoid the implications of falls. This study might encourage the safety managers to apply proactive and preparedness procedures for reducing fall accidents and prioritize risks according to the likelihood of fall risk and injury characteristics by applying appropriate safety regulations.

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