A multivariate analysis of social security costs of occupational accidents and diseases - Jesus, Liandra dos Santos; Freitas, Eliél Batistão; Ciorlia, Marcelo Coelho; Ferrari, Guilherme; Galdamez, Edwin Vladimir Cardoza; Leal, Gislaine Camila Lapasini; Ossani, Paulo César (Brazilian Journal of Production Engineering, 2026)
The objective of this study is to identify and characterize patterns in granting social security benefits related to occupational accidents and diseases in Brazil. A quantitative approach was adopted, analyzing a comprehensive dataset of 185,238 occupational accident benefits granted by the INSS between 2019 and 2020. The methodology combined hierarchical and non-hierarchical clustering techniques to identify distinct beneficiary groups, followed by Multiple Correspondence Analysis (MCA) to explore associations among categorical variables. The results revealed three clusters with distinct profiles regarding injury types, wage levels, and demographic characteristics. Cluster 1 is characterized by repetitive strain and manual injuries among low-wage workers; Cluster 2 features musculoskeletal and psychological disorders in higher-wage groups; and traumatic injuries among the lowest wage earners dominate Cluster 3. The MCA highlighted cohesive and isolated associations among benefit types, diseases, and geographic regions. This research provides a robust, data-driven profile of the social security costs of occupational accidents in Brazil, offering valuable insights for policymakers and OSH professionals. The identification of distinct risk groups and the mapping of associated factors support the development of more targeted and equitable prevention and compensation policies.