Bilim, NiyaziBilim, Atiye2021-12-132021-12-1320221080-35482376-9130https://doi.org/10.1080/10803548.2021.1990571https://hdl.handle.net/20.500.13091/270Coal mining has the most risk in all of the mining sectors. Hence, in this sector, most work accidents encountered are intensive. The demographic characteristics of workers affect the occurrence of occupational accidents. This study aims to develop an equation that predicts workday loss by analyzing the relationship between workers' demographic characteristics and having an accident with workday loss. In this study, work-related accidents between 2014 and 2019 in underground hard coal mines in Turkey were analyzed using logistic regression analysis. An equation is derived that estimates the workday loss with the characteristics of workers in hard coal mines. With the equation derived in this study, employers can determine the potential for work accidents according to the demographic characteristics of the workers and serious work accidents will be prevented. Therefore, proactive solutions can be produced by applying the methods used in this study to different industries.eninfo:eu-repo/semantics/closedAccessLogistic RegressionWork SafetyWork AccidentCoal Mine AccidentAccident AnalysesOccupational-Health HazardsStatistical-AnalysisSafety EvaluationMining SafetyInjuriesChinaExplosionsManagementLostExperienceArticle10.1080/10803548.2021.19905712-s2.0-85119359327