Spatial distribution of diabetes mortality in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Saúde e Desenvolvimento Humano |
Texto Completo: | https://revistas.unilasalle.edu.br/index.php/saude_desenvolvimento/article/view/6135 |
Resumo: | Objective: To analyze the spatial distribution of mortality rates from diabetes in Brazil.Methods: Ecological study nationwide, based on secondary mortality data from the Mortality Information System (SIM) from 2012 to 2016. Spatial distribution, intensity and significance were analyzed using the Moran Global index, MoranMap, as well as the occurrence of high-risk clusters through LisaMap and BoxMap.Results: During the study period, there were 293,752 deaths from Diabetes, of which 162,743 (55.40%) were female; 237,428 deaths (80.83%) aged 60 years and over; 49.56% for whites and yellows; 36.32% are married; 67.77% occurred in the hospital. The municipalities with the highest average standardized mortality rates were: Junco do Maranhão - MA (142.14 deaths/100 thousand inhab.), Brejinho - PE (128.88), Brejo de Areia - MA (127.64), Xexéu - PE (123.96), Malhada dos Bois - SE (118.41), Jaqueira - PE (115.96) and Arara - PB (104.78). The value of the Global Moran Index was positive and with statistical significance (p-value = 0.01). High-risk (high/high) cluster formation was evidenced in municipalities in the north, northeast, southeast and central-west regions, while the presence oflow-risk (low/low) clusters was verified in the southern region of the country. Conclusions: There is a pattern of spatial dependence in Brazil in the distribution of mortality rates due to Diabetes. |
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Spatial distribution of diabetes mortality in BrazilDistribuição espacial da mortalidade por diabetes no BrasilMortality; Diabetes; Spatial DistributionEnfermagem; Saúde Coletiva; Saúde Pública; Ciências da Saúde; Demografia.Mortalidade; Diabetes; Distribuição EspacialObjective: To analyze the spatial distribution of mortality rates from diabetes in Brazil.Methods: Ecological study nationwide, based on secondary mortality data from the Mortality Information System (SIM) from 2012 to 2016. Spatial distribution, intensity and significance were analyzed using the Moran Global index, MoranMap, as well as the occurrence of high-risk clusters through LisaMap and BoxMap.Results: During the study period, there were 293,752 deaths from Diabetes, of which 162,743 (55.40%) were female; 237,428 deaths (80.83%) aged 60 years and over; 49.56% for whites and yellows; 36.32% are married; 67.77% occurred in the hospital. The municipalities with the highest average standardized mortality rates were: Junco do Maranhão - MA (142.14 deaths/100 thousand inhab.), Brejinho - PE (128.88), Brejo de Areia - MA (127.64), Xexéu - PE (123.96), Malhada dos Bois - SE (118.41), Jaqueira - PE (115.96) and Arara - PB (104.78). The value of the Global Moran Index was positive and with statistical significance (p-value = 0.01). High-risk (high/high) cluster formation was evidenced in municipalities in the north, northeast, southeast and central-west regions, while the presence oflow-risk (low/low) clusters was verified in the southern region of the country. Conclusions: There is a pattern of spatial dependence in Brazil in the distribution of mortality rates due to Diabetes.Objetivo: Analisar a distribuição espacial das taxas de mortalidade por diabetes no Brasil.Métodos: Estudo ecológico com municípios do Brasil, no período de 2012 a 2016. Analisou-se a distribuição espacial, a intensidade e a significância através do índice de Moran Global, MoranMap, LisaMap e BoxMap.Resultados: No período estudado houve 293.752 óbitos por Diabetes, destes 162.743 (55,40%) são do sexo feminino; 237.428 óbitos (80,83%) com idade de 60 anos e mais; 49,56% para brancos e amarelos; 36,32% são casados; 67,77% ocorreram no hospital. Os municípios que apresentaram as maiores taxas médias de mortalidade padronizadas foram: Junco do Maranhão – MA (142,14 óbitos/100 mil hab.), Brejinho – PE (128,88), Brejo de Areia – MA (127,64), Xexéu – PE (123,96), Malhada dos Bois – SE (118,41), Jaqueira – PE (115,96) e Arara – PB (104,78). O valor do Índice de Moran Global foi positivo e com significância estatística (p-valor=0.01). Evidenciou-se formação de clúster de alto/alto em municípios das regiões norte, nordeste, sudeste e centro-oeste, enquanto que foi verificada a presença de clúster de baixo/baixo na região sul país.Conclusões: Existe no Brasil um padrão de dependência espacial na distribuição das taxas de mortalidade por Diabetes.Universidade LaSalle - Unilasalle CanoasMarques, Marilane VilelaSantos, Samara Sybelle de Araújo NobreLima, Mirna Vasconcelos deMatos, Marisa Karina de MirandaPereira, Sônia MariaAmador, Ana Edimilda2020-08-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.unilasalle.edu.br/index.php/saude_desenvolvimento/article/view/613510.18316/sdh.v8i3.6135Saúde e Desenvolvimento Humano; v. 8, n. 3 (2020); p. 113-122Saúde e Desenvolvimento Humano; v. 8, n. 3 (2020); p. 113-1222317-8582reponame:Saúde e Desenvolvimento Humanoinstname:Universidade La Salle (UNILASALLE)instacron:UNILASALLEporhttps://revistas.unilasalle.edu.br/index.php/saude_desenvolvimento/article/view/6135/pdfhttps://revistas.unilasalle.edu.br/index.php/saude_desenvolvimento/article/downloadSuppFile/6135/1247Direitos autorais 2020 Saúde e Desenvolvimento Humanoinfo:eu-repo/semantics/openAccess2022-03-29T14:31:53Zoai:ojs.revistas.unilasalle.edu.br:article/6135Revistahttp://www.revistas.unilasalle.edu.br/index.php/saude_desenvolvimentohttps://revistas.unilasalle.edu.br/index.php/saude_desenvolvimento/oaisdh@unilasalle.edu.br2317-85822317-8582opendoar:2022-03-29T14:31:53Saúde e Desenvolvimento Humano - Universidade La Salle (UNILASALLE)false |
dc.title.none.fl_str_mv |
Spatial distribution of diabetes mortality in Brazil Distribuição espacial da mortalidade por diabetes no Brasil |
title |
Spatial distribution of diabetes mortality in Brazil |
spellingShingle |
Spatial distribution of diabetes mortality in Brazil Marques, Marilane Vilela Mortality; Diabetes; Spatial Distribution Enfermagem; Saúde Coletiva; Saúde Pública; Ciências da Saúde; Demografia. Mortalidade; Diabetes; Distribuição Espacial |
title_short |
Spatial distribution of diabetes mortality in Brazil |
title_full |
Spatial distribution of diabetes mortality in Brazil |
title_fullStr |
Spatial distribution of diabetes mortality in Brazil |
title_full_unstemmed |
Spatial distribution of diabetes mortality in Brazil |
title_sort |
Spatial distribution of diabetes mortality in Brazil |
author |
Marques, Marilane Vilela |
author_facet |
Marques, Marilane Vilela Santos, Samara Sybelle de Araújo Nobre Lima, Mirna Vasconcelos de Matos, Marisa Karina de Miranda Pereira, Sônia Maria Amador, Ana Edimilda |
author_role |
author |
author2 |
Santos, Samara Sybelle de Araújo Nobre Lima, Mirna Vasconcelos de Matos, Marisa Karina de Miranda Pereira, Sônia Maria Amador, Ana Edimilda |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
|
dc.contributor.author.fl_str_mv |
Marques, Marilane Vilela Santos, Samara Sybelle de Araújo Nobre Lima, Mirna Vasconcelos de Matos, Marisa Karina de Miranda Pereira, Sônia Maria Amador, Ana Edimilda |
dc.subject.none.fl_str_mv |
|
dc.subject.por.fl_str_mv |
Mortality; Diabetes; Spatial Distribution Enfermagem; Saúde Coletiva; Saúde Pública; Ciências da Saúde; Demografia. Mortalidade; Diabetes; Distribuição Espacial |
topic |
Mortality; Diabetes; Spatial Distribution Enfermagem; Saúde Coletiva; Saúde Pública; Ciências da Saúde; Demografia. Mortalidade; Diabetes; Distribuição Espacial |
description |
Objective: To analyze the spatial distribution of mortality rates from diabetes in Brazil.Methods: Ecological study nationwide, based on secondary mortality data from the Mortality Information System (SIM) from 2012 to 2016. Spatial distribution, intensity and significance were analyzed using the Moran Global index, MoranMap, as well as the occurrence of high-risk clusters through LisaMap and BoxMap.Results: During the study period, there were 293,752 deaths from Diabetes, of which 162,743 (55.40%) were female; 237,428 deaths (80.83%) aged 60 years and over; 49.56% for whites and yellows; 36.32% are married; 67.77% occurred in the hospital. The municipalities with the highest average standardized mortality rates were: Junco do Maranhão - MA (142.14 deaths/100 thousand inhab.), Brejinho - PE (128.88), Brejo de Areia - MA (127.64), Xexéu - PE (123.96), Malhada dos Bois - SE (118.41), Jaqueira - PE (115.96) and Arara - PB (104.78). The value of the Global Moran Index was positive and with statistical significance (p-value = 0.01). High-risk (high/high) cluster formation was evidenced in municipalities in the north, northeast, southeast and central-west regions, while the presence oflow-risk (low/low) clusters was verified in the southern region of the country. Conclusions: There is a pattern of spatial dependence in Brazil in the distribution of mortality rates due to Diabetes. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-08-14 |
dc.type.none.fl_str_mv |
|
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://revistas.unilasalle.edu.br/index.php/saude_desenvolvimento/article/view/6135 10.18316/sdh.v8i3.6135 |
url |
https://revistas.unilasalle.edu.br/index.php/saude_desenvolvimento/article/view/6135 |
identifier_str_mv |
10.18316/sdh.v8i3.6135 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://revistas.unilasalle.edu.br/index.php/saude_desenvolvimento/article/view/6135/pdf https://revistas.unilasalle.edu.br/index.php/saude_desenvolvimento/article/downloadSuppFile/6135/1247 |
dc.rights.driver.fl_str_mv |
Direitos autorais 2020 Saúde e Desenvolvimento Humano info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Direitos autorais 2020 Saúde e Desenvolvimento Humano |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade LaSalle - Unilasalle Canoas |
publisher.none.fl_str_mv |
Universidade LaSalle - Unilasalle Canoas |
dc.source.none.fl_str_mv |
Saúde e Desenvolvimento Humano; v. 8, n. 3 (2020); p. 113-122 Saúde e Desenvolvimento Humano; v. 8, n. 3 (2020); p. 113-122 2317-8582 reponame:Saúde e Desenvolvimento Humano instname:Universidade La Salle (UNILASALLE) instacron:UNILASALLE |
instname_str |
Universidade La Salle (UNILASALLE) |
instacron_str |
UNILASALLE |
institution |
UNILASALLE |
reponame_str |
Saúde e Desenvolvimento Humano |
collection |
Saúde e Desenvolvimento Humano |
repository.name.fl_str_mv |
Saúde e Desenvolvimento Humano - Universidade La Salle (UNILASALLE) |
repository.mail.fl_str_mv |
sdh@unilasalle.edu.br |
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1749120543955615744 |