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Mapping disparities in homicide trends across Brazil: 2000–2014
BackgroundHomicides are a major problem in Brazil. Drugs and arms trafficking, and land conflicts are three of the many factors driving homicide rates in Brazil. Understanding long-term spatiotemporal trends and social structural factors associated with homicides in Brazil would be useful for design...
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Published in: | Injury epidemiology 2020-09, Vol.7 (1), p.47-47, Article 47 |
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description | BackgroundHomicides are a major problem in Brazil. Drugs and arms trafficking, and land conflicts are three of the many factors driving homicide rates in Brazil. Understanding long-term spatiotemporal trends and social structural factors associated with homicides in Brazil would be useful for designing policies aimed at reducing homicide rates.MethodsWe obtained data from 2000 to 2014 from the Brazil Ministry of Health (MOH) Mortality Information System and sociodemographic data from the Brazil Institute of Geography and Statistics (IBGE). First, we quantified the rate of change in homicides at the municipality and state levels. Second, we used principal component regression and k-medoids clustering to examine differences in temporal trends across municipalities. Lastly, we used Bayesian hierarchical space-time models to describe spatio-temporal patterns and to assess the contribution of structural factors.ResultsThere were significant variations in homicide rates across states and municipalities. We noted the largest decrease in homicide rates in the western and southeastern states of Sao Paulo, Rio de Janeiro and Espirito Santo, which coincided with an increase in homicide rates in the northeastern states of Ceará, Alagoas, Paraiba, Rio Grande Norte, Sergipe and Bahia during the fifteen-year period. The decrease in homicides in municipalities with populations of at least 250,000 coincided with an increase in municipalities with 25,000 people or less. Structural factors that predicted municipality-level homicide rates included crude domestic product, urbanization, border with neighboring countries and proportion of population aged fifteen to twenty-nine.ConclusionsOur findings support both a dissemination hypothesis and an interiorization hypothesis. These findings should be considered when designing interventions to curb homicide rates. |
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Drugs and arms trafficking, and land conflicts are three of the many factors driving homicide rates in Brazil. Understanding long-term spatiotemporal trends and social structural factors associated with homicides in Brazil would be useful for designing policies aimed at reducing homicide rates.MethodsWe obtained data from 2000 to 2014 from the Brazil Ministry of Health (MOH) Mortality Information System and sociodemographic data from the Brazil Institute of Geography and Statistics (IBGE). First, we quantified the rate of change in homicides at the municipality and state levels. Second, we used principal component regression and k-medoids clustering to examine differences in temporal trends across municipalities. Lastly, we used Bayesian hierarchical space-time models to describe spatio-temporal patterns and to assess the contribution of structural factors.ResultsThere were significant variations in homicide rates across states and municipalities. We noted the largest decrease in homicide rates in the western and southeastern states of Sao Paulo, Rio de Janeiro and Espirito Santo, which coincided with an increase in homicide rates in the northeastern states of Ceará, Alagoas, Paraiba, Rio Grande Norte, Sergipe and Bahia during the fifteen-year period. The decrease in homicides in municipalities with populations of at least 250,000 coincided with an increase in municipalities with 25,000 people or less. Structural factors that predicted municipality-level homicide rates included crude domestic product, urbanization, border with neighboring countries and proportion of population aged fifteen to twenty-nine.ConclusionsOur findings support both a dissemination hypothesis and an interiorization hypothesis. These findings should be considered when designing interventions to curb homicide rates.</description><identifier>ISSN: 2197-1714</identifier><identifier>EISSN: 2197-1714</identifier><identifier>DOI: 10.1186/s40621-020-00273-y</identifier><identifier>PMID: 32892747</identifier><language>eng</language><publisher>Heideberg: Springer Nature B.V</publisher><subject>Brazil ; Homicide ; Hypotheses ; Original Contribution ; Trends ; Violent crimes</subject><ispartof>Injury epidemiology, 2020-09, Vol.7 (1), p.47-47, Article 47</ispartof><rights>The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c540t-d413ab050b08efe51a768d8ae1a3f3de552229eeaaee4da569617947ebf9cce3</citedby><cites>FETCH-LOGICAL-c540t-d413ab050b08efe51a768d8ae1a3f3de552229eeaaee4da569617947ebf9cce3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2440408803/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2440408803?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,74998</link.rule.ids></links><search><creatorcontrib>Nsoesie, Elaine Okanyene</creatorcontrib><creatorcontrib>Lima Neto, Antonio S.</creatorcontrib><creatorcontrib>Jay, Jonathan</creatorcontrib><creatorcontrib>Wang, Hailun</creatorcontrib><creatorcontrib>Zinszer, Kate</creatorcontrib><creatorcontrib>Saha, Sudipta</creatorcontrib><creatorcontrib>Maharana, Adyasha</creatorcontrib><creatorcontrib>Marinho, Fatima</creatorcontrib><creatorcontrib>Soares Filho, Adauto Martins</creatorcontrib><title>Mapping disparities in homicide trends across Brazil: 2000–2014</title><title>Injury epidemiology</title><description>BackgroundHomicides are a major problem in Brazil. Drugs and arms trafficking, and land conflicts are three of the many factors driving homicide rates in Brazil. Understanding long-term spatiotemporal trends and social structural factors associated with homicides in Brazil would be useful for designing policies aimed at reducing homicide rates.MethodsWe obtained data from 2000 to 2014 from the Brazil Ministry of Health (MOH) Mortality Information System and sociodemographic data from the Brazil Institute of Geography and Statistics (IBGE). First, we quantified the rate of change in homicides at the municipality and state levels. Second, we used principal component regression and k-medoids clustering to examine differences in temporal trends across municipalities. Lastly, we used Bayesian hierarchical space-time models to describe spatio-temporal patterns and to assess the contribution of structural factors.ResultsThere were significant variations in homicide rates across states and municipalities. We noted the largest decrease in homicide rates in the western and southeastern states of Sao Paulo, Rio de Janeiro and Espirito Santo, which coincided with an increase in homicide rates in the northeastern states of Ceará, Alagoas, Paraiba, Rio Grande Norte, Sergipe and Bahia during the fifteen-year period. The decrease in homicides in municipalities with populations of at least 250,000 coincided with an increase in municipalities with 25,000 people or less. Structural factors that predicted municipality-level homicide rates included crude domestic product, urbanization, border with neighboring countries and proportion of population aged fifteen to twenty-nine.ConclusionsOur findings support both a dissemination hypothesis and an interiorization hypothesis. These findings should be considered when designing interventions to curb homicide rates.</description><subject>Brazil</subject><subject>Homicide</subject><subject>Hypotheses</subject><subject>Original Contribution</subject><subject>Trends</subject><subject>Violent crimes</subject><issn>2197-1714</issn><issn>2197-1714</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkctq3DAUQEVpaEKSH-jK0E03TvWW3EUhDX0EErrJXlxL1xMNHsuVPIXpqv_QP8yXVJ0JpclKQvdwEPcQ8prRC8asflck1Zy1lNOWUm5Eu3tBTjjrTMsMky__ux-T81LWlFLGlTJWvSLHgtuOG2lOyOUtzHOcVk2IZYYcl4iliVNznzbRx4DNknEKpQGfUynNxww_4_i-4VX38Os3p0yekaMBxoLnj-cpufv86e7qa3vz7cv11eVN65WkSxskE9BTRXtqcUDFwGgbLCADMYiASnHOO0QARBlA6U4z00mD_dB5j-KUXB-0IcHazTluIO9cguj2DymvHOQl-hGdHbqq74WQwkpWlUprCzqYMPBB-lBdHw6uedtvMHiclgzjE-nTyRTv3Sr9cEZao1lXBW8fBTl932JZ3CYWj-MIE6ZtcVzWOlopRSv65hm6Tts81U3tKUmtpaJS_EDt15xx-PcZRt3f3u7Q29Xebt_b7cQfq_mcLw</recordid><startdate>20200907</startdate><enddate>20200907</enddate><creator>Nsoesie, Elaine Okanyene</creator><creator>Lima Neto, Antonio S.</creator><creator>Jay, Jonathan</creator><creator>Wang, Hailun</creator><creator>Zinszer, Kate</creator><creator>Saha, Sudipta</creator><creator>Maharana, Adyasha</creator><creator>Marinho, Fatima</creator><creator>Soares Filho, Adauto Martins</creator><general>Springer Nature B.V</general><general>BioMed Central</general><general>BMC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20200907</creationdate><title>Mapping disparities in homicide trends across Brazil: 2000–2014</title><author>Nsoesie, Elaine Okanyene ; Lima Neto, Antonio S. ; Jay, Jonathan ; Wang, Hailun ; Zinszer, Kate ; Saha, Sudipta ; Maharana, Adyasha ; Marinho, Fatima ; Soares Filho, Adauto Martins</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c540t-d413ab050b08efe51a768d8ae1a3f3de552229eeaaee4da569617947ebf9cce3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Brazil</topic><topic>Homicide</topic><topic>Hypotheses</topic><topic>Original Contribution</topic><topic>Trends</topic><topic>Violent crimes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nsoesie, Elaine Okanyene</creatorcontrib><creatorcontrib>Lima Neto, Antonio S.</creatorcontrib><creatorcontrib>Jay, Jonathan</creatorcontrib><creatorcontrib>Wang, Hailun</creatorcontrib><creatorcontrib>Zinszer, Kate</creatorcontrib><creatorcontrib>Saha, Sudipta</creatorcontrib><creatorcontrib>Maharana, Adyasha</creatorcontrib><creatorcontrib>Marinho, Fatima</creatorcontrib><creatorcontrib>Soares Filho, Adauto Martins</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection (Proquest)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Injury epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nsoesie, Elaine Okanyene</au><au>Lima Neto, Antonio S.</au><au>Jay, Jonathan</au><au>Wang, Hailun</au><au>Zinszer, Kate</au><au>Saha, Sudipta</au><au>Maharana, Adyasha</au><au>Marinho, Fatima</au><au>Soares Filho, Adauto Martins</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mapping disparities in homicide trends across Brazil: 2000–2014</atitle><jtitle>Injury epidemiology</jtitle><date>2020-09-07</date><risdate>2020</risdate><volume>7</volume><issue>1</issue><spage>47</spage><epage>47</epage><pages>47-47</pages><artnum>47</artnum><issn>2197-1714</issn><eissn>2197-1714</eissn><abstract>BackgroundHomicides are a major problem in Brazil. Drugs and arms trafficking, and land conflicts are three of the many factors driving homicide rates in Brazil. Understanding long-term spatiotemporal trends and social structural factors associated with homicides in Brazil would be useful for designing policies aimed at reducing homicide rates.MethodsWe obtained data from 2000 to 2014 from the Brazil Ministry of Health (MOH) Mortality Information System and sociodemographic data from the Brazil Institute of Geography and Statistics (IBGE). First, we quantified the rate of change in homicides at the municipality and state levels. Second, we used principal component regression and k-medoids clustering to examine differences in temporal trends across municipalities. Lastly, we used Bayesian hierarchical space-time models to describe spatio-temporal patterns and to assess the contribution of structural factors.ResultsThere were significant variations in homicide rates across states and municipalities. We noted the largest decrease in homicide rates in the western and southeastern states of Sao Paulo, Rio de Janeiro and Espirito Santo, which coincided with an increase in homicide rates in the northeastern states of Ceará, Alagoas, Paraiba, Rio Grande Norte, Sergipe and Bahia during the fifteen-year period. The decrease in homicides in municipalities with populations of at least 250,000 coincided with an increase in municipalities with 25,000 people or less. Structural factors that predicted municipality-level homicide rates included crude domestic product, urbanization, border with neighboring countries and proportion of population aged fifteen to twenty-nine.ConclusionsOur findings support both a dissemination hypothesis and an interiorization hypothesis. These findings should be considered when designing interventions to curb homicide rates.</abstract><cop>Heideberg</cop><pub>Springer Nature B.V</pub><pmid>32892747</pmid><doi>10.1186/s40621-020-00273-y</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Brazil Homicide Hypotheses Original Contribution Trends Violent crimes |
title | Mapping disparities in homicide trends across Brazil: 2000–2014 |
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