Análise espacial da mortalidade e das internações hospitalares por acidentes de motocicleta no Brasil

• Ano de defesa: 2016
• Autor(a) principal: Pedro Cisalpino Pinheiro
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Internações hospitalares; Motocicletas; Análise espacial; Municípios; Mortalidade; Pequenas áreas; Mortalidade Brasil; Motociclistas Mortalidade Brasil
• Link de acesso: http://hdl.handle.net/1843/BUBD-AKBRDZ

In the past few years, the mortality and the hospitalization related to motorcycle accidents in Brazil rose substantially and has been studied by some scholars. The consequences of this kind of accidents can be felt in individual, family and societal level. The analysis of the distribution of deaths and hospitalizations in Brazilian municipalities is fundamental to the development of policies focused in the prevention of their occurrence. Although, in small areas, some additional care is needed to estimate those rates. The main objective of this dissertation is to create estimates of the risk of dying and being hospitalized related by the use of a motorcycle in the Brazilian municipalities, as well as to analyse their distribution. Additionally, we intended to identify the presence of spatial patterns in the rates distribution and to investigate their association with income. The rates were constructed considering the mean number of deaths and hospitalization, for each sex, by municipality of residence, registered in the years of 2009, 2010 and 2011. The rates were age standardized and then we used the empirical bayes smoothing method. To the identification of spatial patterns we used local indicators of spatial association (LISAs). The association between income and the rates were analysed by multivariate spatial analyses tools. In general, the higher mortality and hospitalization rates were observed in municipalities located in the North-East and Central-West regions. The municipalities located in the North region were among those with higher mortality rates. The North, North-East and Central-West concentrated most of the high-high mortality and hospitalizations rate clusters. The analysis of the relation between mean income and the mortality and hospitalization rates showed different patterns for the North, North-East and Central-West and for the Southeast and South regions. The use of empirical bayes smoothing method were efficient to handle with extreme rates values, as well as the maps visualization were consistently improved by it use.