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Finding causation in occupational fatalities: A latent class analysis
Author(s) -
Farina Elena,
Bianco Selene,
Bena Antonella,
Pasqualini Osvaldo
Publication year - 2019
Publication title -
american journal of industrial medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.7
H-Index - 104
eISSN - 1097-0274
pISSN - 0271-3586
DOI - 10.1002/ajim.22936
Subject(s) - causation , latent class model , medicine , occupational accident , occupational safety and health , environmental health , class (philosophy) , rollover (web design) , poison control , injury prevention , forensic engineering , statistics , engineering , artificial intelligence , computer science , mathematics , pathology , world wide web , political science , law
Background The method “Learning by mistakes” was developed in Italy to conduct occupational injury investigations and to collect information on the genesis of injuries. The aim is to analyze data classified with this method in order to identify patterns among the factors contributing to injury dynamics. Methods Data regarding 673 factors, corresponding to 354 occupational fatalities that occurred in the Piedmont region (north‐west of Italy) during 2005‐2014 were considered. Latent Class Analysis (LCA) was applied to find patterns among these factors. Results The eight‐class model was selected. Most of the factors fell in the class “Fall from height or vehicle rollover due to incorrect practice” (40.56%) while the remaining factors where heterogeneously distributed in the other classes. Conclusions All the classes found allow for a logical interpretation. Systematic use of LCA could aid in uncovering new, unexpected patterns of factors not otherwise detectable by analysis of the single fatal accident.