Spatial modeling of homicide mortality in the Northeast region of Brazil
To analyze the spatiotemporal distribution of homicide mortality and association with social determinants of health in the Northeast Region of Brazil. Ecological study with spatiotemporal modeling of homicide deaths between 2000 and 2019. Temporal trends were analyzed by segmented linear regression....
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| Veröffentlicht in: | Revista Brasileira de Enfermagem 2023-01, Vol.76 (2), p.e20220182-8 |
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| creator | Silva, Carlos Carvalho da Souza, Katyucia Oliveira Crispim de Paz, Wandklebson Silva da Santos, Antônio Pedro Santana Melo, Luís Ricardo Santos de Sousa, Álvaro Francisco Lopes de Araújo, Damião da Conceição Santos, Allan Dantas Dos |
| description | To analyze the spatiotemporal distribution of homicide mortality and association with social determinants of health in the Northeast Region of Brazil.
Ecological study with spatiotemporal modeling of homicide deaths between 2000 and 2019. Temporal trends were analyzed by segmented linear regression. Crude mortality was calculated and adjusted by smoothing the local empirical Bayesian method and analyzed by the Global/Local Moran Index and spatiotemporal scan statistics. The association between social determinants of health and homicide mortality was performed using multiple linear regression and autoregressive spatial models.
353,089 deaths were recorded. Mortality increased from 2000 to 2019, with an annual increase of 4.37 in males and 3.57 in females. High risk spatial and spatiotemporal clusters were identified in the coastal region of the states. The spatial regression model showed an association with socioeconomic inequalities.
High risk areas for homicides associated with socioeconomic inequality, which should be considered as a priority for designing and investing in public health policies were investigated. |
| doi_str_mv | 10.1590/0034-7167-2022-0182 |
| format | Article |
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Ecological study with spatiotemporal modeling of homicide deaths between 2000 and 2019. Temporal trends were analyzed by segmented linear regression. Crude mortality was calculated and adjusted by smoothing the local empirical Bayesian method and analyzed by the Global/Local Moran Index and spatiotemporal scan statistics. The association between social determinants of health and homicide mortality was performed using multiple linear regression and autoregressive spatial models.
353,089 deaths were recorded. Mortality increased from 2000 to 2019, with an annual increase of 4.37 in males and 3.57 in females. High risk spatial and spatiotemporal clusters were identified in the coastal region of the states. The spatial regression model showed an association with socioeconomic inequalities.
High risk areas for homicides associated with socioeconomic inequality, which should be considered as a priority for designing and investing in public health policies were investigated.</description><identifier>ISSN: 0034-7167</identifier><identifier>ISSN: 1984-0446</identifier><identifier>EISSN: 1984-0446</identifier><identifier>DOI: 10.1590/0034-7167-2022-0182</identifier><identifier>PMID: 36753255</identifier><language>eng</language><publisher>Brazil: Associação Brasileira de Enfermagem</publisher><subject>Bayes Theorem ; Brazil - epidemiology ; Domestic violence ; Ecological Studies ; Epidemiology ; Female ; Homicide ; Humans ; Inequality ; Male ; Mortality ; Multivariate Analysis ; Murders & murder attempts ; NURSING ; Original ; Population ; Public health ; Regression analysis ; Social Determinants of Health ; Socioeconomic Factors ; Spatial Analysis</subject><ispartof>Revista Brasileira de Enfermagem, 2023-01, Vol.76 (2), p.e20220182-8</ispartof><rights>2023. This work is published under https://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>This work is licensed under a Creative Commons Attribution 4.0 International License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-1645-4459 ; 0000-0002-6771-1961 ; 0000-0003-1116-170X ; 0000-0002-2898-2646 ; 0000-0002-6529-1887 ; 0000-0003-2710-2122 ; 0000-0003-0232-137X ; 0000-0001-7768-7005</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901349/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901349/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,728,781,785,865,886,27926,27927,53793,53795</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36753255$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Silva, Carlos Carvalho da</creatorcontrib><creatorcontrib>Souza, Katyucia Oliveira Crispim de</creatorcontrib><creatorcontrib>Paz, Wandklebson Silva da</creatorcontrib><creatorcontrib>Santos, Antônio Pedro Santana</creatorcontrib><creatorcontrib>Melo, Luís Ricardo Santos de</creatorcontrib><creatorcontrib>Sousa, Álvaro Francisco Lopes de</creatorcontrib><creatorcontrib>Araújo, Damião da Conceição</creatorcontrib><creatorcontrib>Santos, Allan Dantas Dos</creatorcontrib><title>Spatial modeling of homicide mortality in the Northeast region of Brazil</title><title>Revista Brasileira de Enfermagem</title><addtitle>Rev Bras Enferm</addtitle><description>To analyze the spatiotemporal distribution of homicide mortality and association with social determinants of health in the Northeast Region of Brazil.
Ecological study with spatiotemporal modeling of homicide deaths between 2000 and 2019. Temporal trends were analyzed by segmented linear regression. Crude mortality was calculated and adjusted by smoothing the local empirical Bayesian method and analyzed by the Global/Local Moran Index and spatiotemporal scan statistics. The association between social determinants of health and homicide mortality was performed using multiple linear regression and autoregressive spatial models.
353,089 deaths were recorded. Mortality increased from 2000 to 2019, with an annual increase of 4.37 in males and 3.57 in females. High risk spatial and spatiotemporal clusters were identified in the coastal region of the states. The spatial regression model showed an association with socioeconomic inequalities.
High risk areas for homicides associated with socioeconomic inequality, which should be considered as a priority for designing and investing in public health policies were investigated.</description><subject>Bayes Theorem</subject><subject>Brazil - epidemiology</subject><subject>Domestic violence</subject><subject>Ecological Studies</subject><subject>Epidemiology</subject><subject>Female</subject><subject>Homicide</subject><subject>Humans</subject><subject>Inequality</subject><subject>Male</subject><subject>Mortality</subject><subject>Multivariate Analysis</subject><subject>Murders & murder attempts</subject><subject>NURSING</subject><subject>Original</subject><subject>Population</subject><subject>Public health</subject><subject>Regression analysis</subject><subject>Social Determinants of Health</subject><subject>Socioeconomic Factors</subject><subject>Spatial Analysis</subject><issn>0034-7167</issn><issn>1984-0446</issn><issn>1984-0446</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>DOA</sourceid><recordid>eNpdUV1rFDEUDaLYpfYXCDLgiy9Tb74myYugRdtC0Yf2PSSZO7sp2cmamRXqrzfjtov16XJPzjn3cELIWwrnVBr4CMBFq2inWgaMtUA1e0FW1GjRghDdS7I6Mk7I2TRFDyAl5azTr8kJ75TkTMoVubrduTm61GxzjymO6yYPzSZvY4g9VrDMLsX5oYljM2-w-V6BDbppbgquYx4X9pfifsf0hrwaXJrw7HGekrtvX-8urtqbH5fXF59v2p4bM7cd4AAdd96AC0IyPwQlB-EMetQM-iAhOBg6OpigguJ1NQN4TzWi84qfkuuDbZ_dvd2VuHXlwWYX7V8gl7V1ZY4hoTVSC9ND6H1goqfUYed1UEglNTDg4nV-8JpCxJTtfd6XsWa3t0t3dumulssBgAFUVRV8Ogh2e7_FPuA4F5eepXj-MsaNXedf1higXJhq8OHRoOSfe5xmu41TwJTciHk_WaaUEEYbvdx6_x_1GI8pTRXnlVxZ7_5NdIzy9MH8D2V2pz4</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Silva, Carlos Carvalho da</creator><creator>Souza, Katyucia Oliveira Crispim de</creator><creator>Paz, Wandklebson Silva da</creator><creator>Santos, Antônio Pedro Santana</creator><creator>Melo, Luís Ricardo Santos de</creator><creator>Sousa, Álvaro Francisco Lopes de</creator><creator>Araújo, Damião da Conceição</creator><creator>Santos, Allan Dantas Dos</creator><general>Associação Brasileira de Enfermagem</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>CLZPN</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>GPN</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-1645-4459</orcidid><orcidid>https://orcid.org/0000-0002-6771-1961</orcidid><orcidid>https://orcid.org/0000-0003-1116-170X</orcidid><orcidid>https://orcid.org/0000-0002-2898-2646</orcidid><orcidid>https://orcid.org/0000-0002-6529-1887</orcidid><orcidid>https://orcid.org/0000-0003-2710-2122</orcidid><orcidid>https://orcid.org/0000-0003-0232-137X</orcidid><orcidid>https://orcid.org/0000-0001-7768-7005</orcidid></search><sort><creationdate>20230101</creationdate><title>Spatial modeling of homicide mortality in the Northeast region of Brazil</title><author>Silva, Carlos Carvalho da ; 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Ecological study with spatiotemporal modeling of homicide deaths between 2000 and 2019. Temporal trends were analyzed by segmented linear regression. Crude mortality was calculated and adjusted by smoothing the local empirical Bayesian method and analyzed by the Global/Local Moran Index and spatiotemporal scan statistics. The association between social determinants of health and homicide mortality was performed using multiple linear regression and autoregressive spatial models.
353,089 deaths were recorded. Mortality increased from 2000 to 2019, with an annual increase of 4.37 in males and 3.57 in females. High risk spatial and spatiotemporal clusters were identified in the coastal region of the states. The spatial regression model showed an association with socioeconomic inequalities.
High risk areas for homicides associated with socioeconomic inequality, which should be considered as a priority for designing and investing in public health policies were investigated.</abstract><cop>Brazil</cop><pub>Associação Brasileira de Enfermagem</pub><pmid>36753255</pmid><doi>10.1590/0034-7167-2022-0182</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-1645-4459</orcidid><orcidid>https://orcid.org/0000-0002-6771-1961</orcidid><orcidid>https://orcid.org/0000-0003-1116-170X</orcidid><orcidid>https://orcid.org/0000-0002-2898-2646</orcidid><orcidid>https://orcid.org/0000-0002-6529-1887</orcidid><orcidid>https://orcid.org/0000-0003-2710-2122</orcidid><orcidid>https://orcid.org/0000-0003-0232-137X</orcidid><orcidid>https://orcid.org/0000-0001-7768-7005</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Bayes Theorem Brazil - epidemiology Domestic violence Ecological Studies Epidemiology Female Homicide Humans Inequality Male Mortality Multivariate Analysis Murders & murder attempts NURSING Original Population Public health Regression analysis Social Determinants of Health Socioeconomic Factors Spatial Analysis |
| title | Spatial modeling of homicide mortality in the Northeast region of Brazil |
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