Perception of risks and victimization of inmates in the state of Rio de Janeiro

• Autor(a) principal: Melo, Paulo Henrique Mauricio de
• Data de Publicação: 2021
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/24751
• topic: Riesgo; Victimización; Prisión; Modelo Logístico; Muestra Compleja.; Risco; Vitimização; Presídio; Modelo Logístico; Amostra Complexa.; Risk; Victimization; Prison; Logistic Model; Complex Sample.

This article aims to investigate the health and life conditions related to the perception of risk and victimization of sentenced inmates in custody of the prison system in the State of Rio de Janeiro. The methodology was based on information from the Study of the Health Conditions and Quality of Life of Prisoners and the Environmental Conditions of Prison Units in the State of Rio de Janeiro, developed by the Department of Violence and Health Studies Jorge Careli, of the Escola Nacional de Saúde Pública Sergio Arouca, from the Oswaldo Cruz Foundation, held in 2012. Perception of risk and victimization were defined as dichotomous variables. To study the factors associated with risk and victimization, logistic models were used and the sampling design used in the study was incorporated. The final model for the outcome on the feeling of being at risk was composed of the variables: color/race, frequency of visits, being treated inferiorly by prison employees because of their social status, having children, marital status and age range . The final model for the outcome of having suffered some type of aggression inside the prison had the following variables: gender, education, age, being treated in a lesser way by prison employees because of their condition of inmate, being treated in a way lower by other prison inmates on account of the type of crime committed and color/race. Therefore, it is concluded that there is a difference between the variables that compose and are decisive for the two models.