[Spatial analysis of socioeconomic determinants of homicide in Brazil].
OBJECTIVE
To investigate the association between homicide rates and socio-economic variables taking into account the spatial site of the indicators.


METHODS
An ecological study was conducted. The dependent variable was the rate of homicides among the male population aged 15 to 49 years, residing in the districts of the State of Pernambuco from 1995 to 1998. The independent variables were an index of the living conditions, per capita family income, Theil inequality index, Gini index, average income of the head of the family, poverty index, rate of illiteracy, and demographic density. The following techniques were used in the analysis: a spatial autocorrelation test determined by the Moran index, multiple linear regression, a spatial regression model (CAR) and a generalized additive model for the detection of spatial trend (LOESS).


RESULTS
The illiteracy and the poverty index explained 24.6% of the total variability of the homicide rates and there was an inverse relationship. Moran's I statistics indicated spatial autocorrelation between municipalities. The multiple linear regression model best fitted for the purposes of this study was the Conditional Auto Regressive (CAR) model. The latter confirmed the association between the poverty index, illiteracy and homicide rates.


CONCLUSIONS
The inverse association observed between socio-economic indicators and homicides may be expressing a process that propitiates improvement in living conditions and that is linked predominantly to conditions that generate violence, such as drug traffic.
de Lima
Maria Luiza C
ML
Faculdade de Ciências Médicas, Universidade de Pernambuco, Recife, PE, Brazil.
Ximenes
Ricardo A de A
RA
de Souza
Edinilsa Ramos
ER
Luna
Carlos Feitosa
CF
de Albuquerque
Maria de Fátima P Militão
Mde F
D000293:Adolescent; D000328:Adult; D001938:Brazil / Q000453:epidemiology; D004522:Educational Status; D006708:Homicide / Q000706:statistics & numerical data*; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011156:Population Density; D012959:Socioeconomic Factors