Abstract
To describe the scenarios of typical occupational injuries in lumber industry. All occupational injuries reported to a INSS (National Institute of Social Security) center in Lages, SC, Brazil from January 1997 to January 1999 were identified. A descriptive cross-sectional study was carried out and 254 injury report forms were analyzed. Multivariate analysis was conducted using Factorial Analysis of Correspondence (FAC), Hierarchical Ascendant Classification (HAC) and Partition to identify the scenarios of typical occupational injuries. There were identified five scenarios of occupational injuries: 1) workers' falls (40 reports); 2) overexertion in lifting or pushing objects (5 reports); 3) objects or machine parts falling or being ejected from running machines (76 reports); 4) crushing of soft tissue body parts (56 reports); and 5) body contact with running saw machines (77 reports). Multivariate analysis allowed describing the most typical injuries related to specific types of accidents, and provided a better understanding of the circumstances for their occurrence.
Highlights
Multivariate analysis allowed describing the most typical injuries related to specific types of accidents, and provided a better understanding of the circumstances for their occurrence
O objetivo do presente estudo é descrever os cenários decorrentes de acidentes de trabalho na indústria madeireira por meio do agrupamento das características e dos fatores mais típicos associados às lesões entre os trabalhadores no setor
13 eram menores de 18 anos (5,1%), 109 tinham idade entre 18 e 29 anos (42,9%), 99 entre 30 e 49 anos (39%) e 33 tinham 50 anos ou mais (13%)
Summary
All occupational injuries reported to a INSS (National Institute of Social Security) center in Lages, SC, Brazil from January 1997 to January 1999 were identified. A descriptive cross-sectional study was carried out and 254 injury report forms were analyzed. Multivariate analysis was conducted using Factorial Analysis of Correspondence (FAC), Hierarchical Ascendant Classification (HAC) and Partition to identify the scenarios of typical occupational injuries. Baseado na dissertação de mestrado apresentada ao Programa de Pós-Graduação em Saúde Pública do Centro de Ciências da Saúde da Universidade Federal de Santa Catarina, 2000. Apresentado no VI Congresso Brasileiro de Saúde Coletiva, Salvador, Bahia, 2000.
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