This paper raises the issue of the optimum utilization of information from accident registers for the achievement of one main goal: the facilitation of safety planning.
It proposes a non-traditional way of analyzing accident data that provides a condensed and comprehensive overview of the most common accident problems encountered by a target group.
A description of typical accident patterns is obtained by the simultaneous treatment of the entire body of information compiled.
Two statistical methods complement one another:
The Factorial Analysis of Correspondence (FAC) and the Hierarchical Ascendant Classification (HAC).
The target group comprised blue-collar workers at the engine workshops of a large automobile and truck factory in Sweden.
As well as the identification and characterization of the main accident patterns, the study was also designed estimate the risk of accidents for six occupational groups and to establish whether levels of risk were similar between workshops for each occupational group.
Mots-clés Pascal : Europe, Accident travail, Poste travail, Industrie automobile, Statut professionnel, Sécurité travail, Planification, Analyse statistique, Homme, Suède, Médecine travail
Mots-clés Pascal anglais : Europe, Occupational accident, Workplace layout, Automobile industry, Professional status, Work safety, Planning, Statistical analysis, Human, Sweden, Occupational medicine
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 91-0574329
Code Inist : 002B30. Création : 199406.