[Violence clusters in Pernambuco, Brazil]. / Conglomerados de violência em Pernambuco, Brasil.

OBJECTIVES: To analyze the spatial distribution of homicide mortality rates among males 15 to 49 years old in the state of Pernambuco, Brazil, for the periods of 1980 to 1984 and 1995 to 1998, and to identify violence clusters. METHODS: Mortality data were obtained from the Brazilian Ministry of Health's Mortality Information System. The mean homicide mortality rate was estimated for each municipality in the state for the two periods. The Moran coefficient was calculated to determine spatial autocorrelation. (The Moran coefficient ranges from -1 to +1, with a positive coefficient indicating a cluster of similar values, and a negative coefficient indicating adjacent dissimilar values.) To identify clusters of municipalities with either high or low homicide mortality rates, the local indicator of spatial association (LISA) was used. Finally, a Moran map was constructed to identify municipalities with statistically significant LISA values and to identify clusters of municipalities with either high or low homicide mortality rates. RESULTS: The Moran coefficient for 1980-1984 was 0.392, and for 1995-1998 it was 0.291 (P < 0.001). In the 1980-1984 period, one cluster of high homicide mortality rates was found in the Mata Sul region of the state, close to the metropolitan region of the state capital, Recife. In the 1995-1998 period, two violence clusters were identified: a predominantly urban one in the Recife metropolitan region, and the other in the state interior, in an area known as the "Marijuana Polygon" (Polígono da Maconha). CONCLUSION: This study suggests that the violence clusters are not the result of the socioeconomic conditions per se, but rather the consequence of the interaction between poor economic conditions and drug trafficking.

[Spatial analysis of socioeconomic determinants of homicide in Brazil]. / Análise espacial dos determinantes socioeconômicos dos homicídios no Estado de Pernambuco.

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.

[Homicide progression per geographical area in the State of Pernambuco, Brazil, 1980-1998]. / Evolução de homicídios por área geográfica em Pernambuco entre 1980 e 1998.

OBJECTIVE: To analyze the magnitude and growth of homicides among male population according to the geopolitical areas. METHODS: An ecological study including a time series analysis was carried out among 15 to 49 year-old males living in the state of Pernambuco, Brazil. Mortality data was collected from the Ministry of Health's Mortality Information System. Data on population was from the 1980 and 1991 censuses and the 1996 Brazilian Institute of Geography and Statistics' census. For inter-census years, the population size was estimated by interpolation, and for the period 1997-1998 it was estimated by projection, using the geometric method. Statistical analysis was performed using mobile mean and regression analysis techniques. RESULTS: In the 1980s, the greatest increase in homicide rates was in the state capital (390%). In the 1990s, the greatest increase occurred in the metropolitan region (68.5%) suggesting violence spread from the capital to other municipalities of greater Recife. Homicide rates tended to grow linearly in the interior, whilst there was an exponential growth in the capital and metropolitan region. A striking feature is the high rates of homicides with firearms in the three areas. CONCLUSIONS: The progression of homicides in the three areas of study shows a characteristic increase. It should be stressed that even though it is the same phenomenon - male homicides -, the generating dynamic of this process has geographical particularities between more urban and interior areas and they should be taken into account while developing local policies for supporting victims and preventing these events.