title: Income inequality and homicide rates in Rio de Janeiro, Brazil.
abstract: OBJECTIVE
  This study determined the effect of income inequality on homicide rates in the state of Rio de Janeiro, Brazil.
  
  
  METHODS
  We conducted an ecological study at 2 geographical levels, municipalities in the state of Rio de Janeiro and administrative regions in the municipality of Rio de Janeiro. The association between homicide and income inequality was tested by multiple regression procedures, with adjustment for other socioeconomic indicators.
  
  
  RESULTS
  For the municipalities of Rio de Janeiro State, no association between homicide and income concentration was found an outcome that can be explained by the municipalities' different degrees of urbanization. However, for the administrative regions in the city of Rio de Janeiro, the 2 income inequality indicators were strongly correlated with the outcome variable (P < .01). Higher homicide rates were found precisely in the sector of the city that has the greatest concentration of slum residents and the highest degree of income inequality.
  
  
  CONCLUSIONS
  The findings suggest that social policies specifically aimed at low-income urban youth, particularly programs to reduce the harmful effects of relative deprivation, may have an important impact on the homicide rate.
authors.affiliation: Department of Information on Health, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.
authors.forename: C L
authors.initials: CL
authors.lastname: Szwarcwald
authors.forename: F I
authors.initials: FI
authors.lastname: Bastos
authors.forename: F
authors.initials: F
authors.lastname: Viacava
authors.forename: C L
authors.initials: CL
authors.lastname: de Andrade
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D001938:Brazil / Q000453:epidemiology; D004522:Educational Status; D005260:Female; D006708:Homicide / Q000517:prevention & control / Q000706:statistics & numerical data*; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D008297:Male; D015999:Multivariate Analysis; D011156:Population Density; D011159:Population Surveillance; D011203:Poverty / Q000517:prevention & control / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012111:Residence Characteristics / Q000706:statistics & numerical data; D017678:Sex Distribution; D014504:Urban Health; D014507:Urbanization