Homicide mortality is a worldwide concern and has occupied the agenda of researchers and public managers. In Brazil, homicide is the third leading cause of death in the general population and the first in the 15-39 age group. In South America, Brazil has the third highest homicide mortality, behind Venezuela and Colombia. To measure the impacts of violence it is important to assess health systems and criminal justice, as well as other areas. In this paper, we analyze the spatial distribution of homicide mortality in the state of Goias, Center-West of Brazil, since the homicide rate increased from 24.5 per 100,000 in 2002 to 42.6 per 100,000 in 2014 in this location. Moreover, this state had the fifth position of homicides in Brazil in 2014. We considered socio-demographic variables for the state, performed analysis about correlation and employed three clustering algorithms: K-means, Density-based and Hierarchical. The results indicate the homicide rates are higher in cities neighbors of large urban centers, although these cities have the best socioeconomic indicators.
This study demonstrate that the empirical literature on the structural convariates of homicide rates contains inconsistent findings across different time periods and different geographical units. This apparent variance of findings may be due to statistical or methodological artifacts of particular studies, such as different time periods covered, units of analysis, samples, model specification, and problems of statistical analysis and inference. A baseline regression model using 11 structural covariates is estimated for cities, metropolitan areas, and states in 1960, 1970, and 1980. The empirical estimates of this model exhibit instability because of high levels of collinearity among several regressors. Principal components analysis is applied to simplify the dimensionally of the structural covariate space. Reestimation of the regression model then indicates that the apparent inconsistencies across time and social space are greatly reduced. The theoretical significance of the findings for substantive theor... As the 20-year mark since the publication of an article by Kenneth C. Land, Patricia L. McCall, and Lawrence Cohen, “Structural Covariates of Homicide Rates: Are There Any Invariances Across Time and Social Space?” approaches, the question that these scholars originally posed is raised again: Have researchers been able to identify a set of robust structural covariates that consistently predict crime rates? Subsequent to the publication of this piece, numerous scholars have replicated and extended its conceptual, methodological, and empirical work in various ways—with more than 500 citations to date. In response to this attention, the authors first review the advances made by the article. This is followed by a review of findings from studies published over the past 20 years to determine which structural predictors identified in the piece continue to be prominent in the study of homicide and which structural predictors have surfaced in recent years as influential to crime rates. Usin...