Acidentes de transporte terrestre com motociclistas: fatores das vias urbanas modeladores de risco

• Ano de defesa: 2015
• Autor(a) principal: Eugênio Paceli Hatem Diniz
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; Brasil; MED - DEPARTAMENTO DE MEDICINA PREVENTIVA SOCIAL; Programa de Pós-Graduação em Saúde Pública; UFMG
• Palavras-chave em Português: motocicletas; acidentes; razão de chances; acidentes de trânsito; análise espacial; Motocicletas; Acidentes; Razão de Chances; Análise Espacial
• Link de acesso: http://hdl.handle.net/1843/35350; https://orcid.org/0000-0003-0789-0416

Urban streets factors participating in the traffic accident risk modelling involving motorcycles Introduction: In Brazil, motorcyclists take the lead in the number of traffic deaths with 34% while motorcycles are only 26% of all vehicles. In Belo Horizonte (Minas Gerais state, Brazil), in 2012, they were 24% (129) over the total of deaths for a fleet of 13% for the total. After all, the urban streets factors of this city were in some way associated with that event? Objective: to identify the most dangerous cluster sites for five years and the urban road features that can increase motorcycle accidents in Belo Horizonte. Methods: Data were provided by the Military Police’s (13,209 accidents) and from SAMU (Emergency Services) (22,334 accidents). Two techniques were used to analyze the accident clusters: Kernel Analysis and Scan Statistics (Continuous Poisson Model) (Paper 1). A case-control study associated with Systematic Observation was conducted to identify and characterize road features by comparing links (n=100) and intersections (n=72) with and without motorcycle accident occurrences. (Paper 2). Results: Ten main clusters of risk were found in the downtown area and on major thoroughfares. Surprisingly, the highest risk of accidents and death occurred between intersections, not in them. The final model of the multivariate analysis showed the following accident variables for links: access for incoming traffic from the opposite side of the road (OR: 4.38; CI 95% 1.40-13.74), speed control by radar (OR: 4.32; CI 95% 0.81-23.11), area use with commercial buildings (OR: 3.03; CI 95% 0.88-10.39) and residential buildings (OR: 2.51; CI 95% 0.88-7.21). Regarding intersection accidents, the following variables were identified: traffic volume (OR: 0.95; CI 95% 0.92-0.99), median strip (OR: 6.92; CI 95% 1.13-42.32) and intersection with no traffic light, bump or roundabout (OR: 0.21; CI 95% 0.04-1.06). Conclusion: The study justifies the need to improve routes for motorcycles and public transportation. Furthermore, it is important that the social actors involved in the process, use the product of this research to support their actions and public policies in order to intervene in the identified urban situations.