Distribuição espacial dos homicídios e a sua relação com os fatores socioeconômico no município de Fortaleza no triênio 2004-2006 - Sousa, Geziel dos Santos de (2009)
The violence has become a public health problem in Brazil, is the third leading cause of deaths. In the Group of the violence, murders are the main causes of death. The main objective of this study was to analyze the spatial distribution of the homicides in the triennium 2004 fortress to 2006 related to socioeconomic factors. The technique was used for linkage to rescue the place of occurrence of the contained in the records of the IML to the database of Mortality Information System (SIM). Was created a model of multivariate linear regression analysis that allowed the identification of a statistical relationship between homicides and socioeconomic indicators. We recorded 35,266 thousand deaths in residents in Fortaleza, this 1,815 were victims of homicide. The use of the linkage procedure allowed an improvement of the information contained on the SIM, with 93.6% recovery of information places of occurrence of death at the place of occurrence of the violent event. For effect of spatial analysis were only considered 1,699 deaths with neighborhood of occurrence identified. The main risk group to death for murder is that of young males between 15 and 29 years, in which the risk is 15.5 times greater than the drab female, unmarried and with low schooling. Spatial statistical analysis was performed by smoothing the rate variations using the Bayesian method and empirical observation of Spatial autocorrelation through I of Moran. As for the spatial distribution of the homicide, understand-if relevant contrasts between worst areas and better living conditions, where 9.65% of districts have low IDH, also have high rates of homicide. The spatial distribution had an irregular pattern, was held anti-aliasing of the homicide rate that began to behave less fragmented. Spatial autocorrelation was not detected, being evaluated through the global index of Moran (I=0.0425). The proposed regression model with five variables proved to be appropriate to the claims of this work by obtaining a significant coefficient of determination (R² = 0.4567).