en Occupational Health Original Article <h2 style="text-align:justify; margin-top:16px; margin-bottom:4px"><span style="font-size:10pt"><span style="line-height:150%"><span style="font-family:&quot;Courier New&quot;"><span style="color:black"><b><span style="font-size:11.0pt"><span style="line-height:150%"><span style="font-family:&quot;Times New Roman&quot;,&quot;serif&quot;">Background:</span></span></span></b> <a name="_Hlk229985910"><span style="font-size:11.0pt"><span style="line-height:150%"><span style="font-family:&quot;Times New Roman&quot;,&quot;serif&quot;">The causes of occupational accidents have been widely examined from different perspectives; however, little is known about the specifics of such accidents in the Russian industry. Therefore, this study aimed to identify these specifics and compare them with global patterns.</span></span></span></a></span></span></span></span><br> <span style="font-size:10pt"><span style="line-height:150%"><span style="font-family:&quot;Courier New&quot;"><span style="color:black"><b><span style="font-size:11.0pt"><span style="line-height:150%"><span style="font-family:&quot;Times New Roman&quot;,&quot;serif&quot;">Materials and Methods:</span></span></span></b><span style="font-size:11.0pt"><span style="line-height:150%"><span style="font-family:&quot;Times New Roman&quot;,&quot;serif&quot;"> This study analysed 165 officially documented cases of severe and fatal occupational accidents that occurred in the utilities, manufacturing, and construction industries in a Russian industrial city between 2018 and 2021. Structural analysis, cross-tabulation analysis, and binary regression models were used to identify potentially high-risk groups, focusing on two main categories of accident causes: employee-related and employer-related. Sociodemographic and accident characteristics were also analysed.</span></span></span></span></span></span></span><br> <span style="font-size:10pt"><span style="line-height:150%"><span style="font-family:&quot;Courier New&quot;"><span style="color:black"><b><span style="font-size:11.0pt"><span style="line-height:150%"><span style="font-family:&quot;Times New Roman&quot;,&quot;serif&quot;">Results:</span></span></span></b><span style="font-size:11.0pt"><span style="line-height:150%"><span style="font-family:&quot;Times New Roman&quot;,&quot;serif&quot;"> The general distribution of injury mechanisms (collapses, contacts, and falls) and factors associated with accident severity (night and Saturday shifts and occupations in energy provision) were consistent with international patterns. Night and weekend shifts, as well as energy-provision occupations, significantly increased the odds of fatal accidents. Technical causes were statistically associated with fatal accidents in both the industrial sector overall and the manufacturing industry. Workers with &ge;15 years of experience had higher odds of employer-related injuries, whereas accidents involving employees aged &ge;61 years were more often attributed to employee behaviour.</span></span></span></span></span></span></span><br> <span style="font-size:10pt"><span style="line-height:150%"><span style="font-family:&quot;Courier New&quot;"><span style="color:black"><b><span style="font-size:11.0pt"><span style="line-height:150%"><span style="font-family:&quot;Times New Roman&quot;,&quot;serif&quot;">Conclusions: </span></span></span></b><span style="font-size:11.0pt"><span style="line-height:150%"><span style="font-family:&quot;Times New Roman&quot;,&quot;serif&quot;">The findings identify high-risk worker groups and may help improve occupational safety practices in Russian industry. Closer supervision of high-risk groups (core-age workers, night/weekend shifts, and workers with >15 years of experience), mandatory training for new employees, and proactive safety measures for an aging workforce are recommended.</span></span></span></span></span></span></span></h2> Occupational Accidents, Severe and Fatal Accidents, Industrial Sector, Statistical Survey, Binary Logistic Regression, Accident Causes 56 66 http://johe.rums.ac.ir/browse.php?a_code=A-10-1033-1&slc_lang=en&sid=1 Irina Pylaeva irenpylaeva74@gmail.com 22400319475328460013645 22400319475328460013645 Yes Ph.D. in Economics, Freelance researcher, Chelyabinsk, Russia. Mariya Podshivalova podshivalovamv@susu.ru 22400319475328460013646 22400319475328460013646 No Ph.D. in Economics, Department of Economics and Finance, South Ural State University, Chelyabinsk, Russia. South Ural State University,