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Estimating the possibility of workday loss accidents in road construction
Worksite hazards and occupational accidents in road construction pose significant risks to worker safety and productivity, necessitating a comprehensive understanding of the factors contributing to workday loss. This study aimed to determine the probability of workday loss owing to occupational accidents among road workers based on individual and occupational characteristics. Univariate statistical analysis, cross-tabulation, and binary logistic regression were used for data analysis. A binary logistic regression analysis was conducted using data from 5,519 occupational accidents during road construction between 2013 and 2016. The independent variables included the workers’ age, sex, marital status, occupational health and safety (OHS) training, experience, education, occupation, accident season, accident location, and material causing the accident. An equation was derived to estimate the probability of workday loss given a worker’s experience, OHS education, season, location, and the material involved. In conclusion, this study demonstrated the applicability of logistic regression analysis in determining the probability of workday loss owing to occupational accidents. This approach can be used across different sectors, reducing workday loss accidents and associated costs while promoting worker health and sustainable production policies.
Estimating the possibility of workday loss accidents in road construction
Worksite hazards and occupational accidents in road construction pose significant risks to worker safety and productivity, necessitating a comprehensive understanding of the factors contributing to workday loss. This study aimed to determine the probability of workday loss owing to occupational accidents among road workers based on individual and occupational characteristics. Univariate statistical analysis, cross-tabulation, and binary logistic regression were used for data analysis. A binary logistic regression analysis was conducted using data from 5,519 occupational accidents during road construction between 2013 and 2016. The independent variables included the workers’ age, sex, marital status, occupational health and safety (OHS) training, experience, education, occupation, accident season, accident location, and material causing the accident. An equation was derived to estimate the probability of workday loss given a worker’s experience, OHS education, season, location, and the material involved. In conclusion, this study demonstrated the applicability of logistic regression analysis in determining the probability of workday loss owing to occupational accidents. This approach can be used across different sectors, reducing workday loss accidents and associated costs while promoting worker health and sustainable production policies.
Estimating the possibility of workday loss accidents in road construction
Atiye Bilim (Autor:in) / Osman Nuri Çelik (Autor:in)
2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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