Spatial analysis of socioeconomic determinants of homicide in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2005 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por eng |
Título da fonte: | Revista de Saúde Pública |
Texto Completo: | https://www.revistas.usp.br/rsp/article/view/31850 |
Resumo: | 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. |
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Spatial analysis of socioeconomic determinants of homicide in Brazil Análise espacial dos determinantes socioeconômicos dos homicídios no Estado de Pernambuco HomicídioDistribuição espacialFatores socioeconômicosAnálise espacialHomicideResidence characteristicsSocioeconomic factorsSpatial analysis 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. OBJETIVO: Investigar a associação entre variáveis socioeconômicas e taxas de homicídio, considerando a localização espacial dos indicadores. MÉTODOS: Utilizou-se o método de estudo ecológico. A variável dependente foi taxa de homicídio da população masculina de 15 a 49 anos, residente nos municípios do Estado de Pernambuco, em 1995 a 1998. As variáveis independentes referem-se a: índice de condições de vida, renda familiar per capita, desigualdade de Theil, índice de Gini, renda média do chefe de família, índice de pobreza, taxa de analfabetismo, densidade demográfica.Utilizou-se teste de correlação espacial determinado pelo Índice de Moran, regressão múltipla, Conditional Auto Regressive (CAR) e a função Loess, como modelo de detecção de tendência especial. RESULTADOS: Os indicadores taxa de analfabetismo e índice de pobreza explicaram 24,6% da variabilidade total das taxas de homicídio, cuja associação foi inversa. O índice de Moran revelou autocorrelação espacial entre os municípios. O modelo de regressão espacial que melhor se adequou ao estudo foi o CAR, que confirmou a associação entre índice de pobreza, analfabetismo e homicídio. CONCLUSÕES: A relação inversa observada entre os indicadores socioeconômicos e homicídios pode expressar determinado processo que propicia melhoria das condições de vida, e está atrelado predominantemente a condições geradoras de violência, como a do tráfico de drogas. Universidade de São Paulo. Faculdade de Saúde Pública2005-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://www.revistas.usp.br/rsp/article/view/3185010.1590/S0034-89102005000200006Revista de Saúde Pública; Vol. 39 No. 2 (2005); 176-182 Revista de Saúde Pública; Vol. 39 Núm. 2 (2005); 176-182 Revista de Saúde Pública; v. 39 n. 2 (2005); 176-182 1518-87870034-8910reponame:Revista de Saúde Públicainstname:Universidade de São Paulo (USP)instacron:USPporenghttps://www.revistas.usp.br/rsp/article/view/31850/33803https://www.revistas.usp.br/rsp/article/view/31850/33804Copyright (c) 2017 Revista de Saúde Públicainfo:eu-repo/semantics/openAccessLima, Maria Luiza C deXimenes, Ricardo A de ASouza, Edinilsa Ramos deLuna, Carlos FeitosaAlbuquerque, Maria de Fátima P Militão de2012-07-08T22:34:04Zoai:revistas.usp.br:article/31850Revistahttps://www.revistas.usp.br/rsp/indexONGhttps://www.revistas.usp.br/rsp/oairevsp@org.usp.br||revsp1@usp.br1518-87870034-8910opendoar:2012-07-08T22:34:04Revista de Saúde Pública - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Spatial analysis of socioeconomic determinants of homicide in Brazil Análise espacial dos determinantes socioeconômicos dos homicídios no Estado de Pernambuco |
title |
Spatial analysis of socioeconomic determinants of homicide in Brazil |
spellingShingle |
Spatial analysis of socioeconomic determinants of homicide in Brazil Lima, Maria Luiza C de Homicídio Distribuição espacial Fatores socioeconômicos Análise espacial Homicide Residence characteristics Socioeconomic factors Spatial analysis |
title_short |
Spatial analysis of socioeconomic determinants of homicide in Brazil |
title_full |
Spatial analysis of socioeconomic determinants of homicide in Brazil |
title_fullStr |
Spatial analysis of socioeconomic determinants of homicide in Brazil |
title_full_unstemmed |
Spatial analysis of socioeconomic determinants of homicide in Brazil |
title_sort |
Spatial analysis of socioeconomic determinants of homicide in Brazil |
author |
Lima, Maria Luiza C de |
author_facet |
Lima, Maria Luiza C de Ximenes, Ricardo A de A Souza, Edinilsa Ramos de Luna, Carlos Feitosa Albuquerque, Maria de Fátima P Militão de |
author_role |
author |
author2 |
Ximenes, Ricardo A de A Souza, Edinilsa Ramos de Luna, Carlos Feitosa Albuquerque, Maria de Fátima P Militão de |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Lima, Maria Luiza C de Ximenes, Ricardo A de A Souza, Edinilsa Ramos de Luna, Carlos Feitosa Albuquerque, Maria de Fátima P Militão de |
dc.subject.por.fl_str_mv |
Homicídio Distribuição espacial Fatores socioeconômicos Análise espacial Homicide Residence characteristics Socioeconomic factors Spatial analysis |
topic |
Homicídio Distribuição espacial Fatores socioeconômicos Análise espacial Homicide Residence characteristics Socioeconomic factors Spatial analysis |
description |
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. |
publishDate |
2005 |
dc.date.none.fl_str_mv |
2005-04-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.revistas.usp.br/rsp/article/view/31850 10.1590/S0034-89102005000200006 |
url |
https://www.revistas.usp.br/rsp/article/view/31850 |
identifier_str_mv |
10.1590/S0034-89102005000200006 |
dc.language.iso.fl_str_mv |
por eng |
language |
por eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/rsp/article/view/31850/33803 https://www.revistas.usp.br/rsp/article/view/31850/33804 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2017 Revista de Saúde Pública info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2017 Revista de Saúde Pública |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Universidade de São Paulo. Faculdade de Saúde Pública |
publisher.none.fl_str_mv |
Universidade de São Paulo. Faculdade de Saúde Pública |
dc.source.none.fl_str_mv |
Revista de Saúde Pública; Vol. 39 No. 2 (2005); 176-182 Revista de Saúde Pública; Vol. 39 Núm. 2 (2005); 176-182 Revista de Saúde Pública; v. 39 n. 2 (2005); 176-182 1518-8787 0034-8910 reponame:Revista de Saúde Pública instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Revista de Saúde Pública |
collection |
Revista de Saúde Pública |
repository.name.fl_str_mv |
Revista de Saúde Pública - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
revsp@org.usp.br||revsp1@usp.br |
_version_ |
1800221783078469632 |