A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Ciência & Saúde Coletiva (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-81232022000100287 |
Resumo: | Abstract Using five cause-specific mortality data sourced by the Brazilian Ministry of Health, and over 17 years period, we applied Bayesian spatio-temporal models on 644 municipalities of the state of São Paulo, using logistic model to the binary outcome that specifies whether or not the death was from a specific cause. We modeled the temporal mortality effects using B-splines, while the spatial components were considered through Gaussian and Markov random field, and inference was based on Markov chain Monte Carlo simulation. The results demonstrate consistent downward trend in mortality from infectious and parasitic diseases and external causes, while those from neoplasms and respiratory are rising. Cardiovascular is the only cause-specific death that is kept constant in time. All the causes of death considered show heterogeneous spatial and temporal variations among the municipalities, which sometimes change considerably within successive years. Mortality from infectious diseases clustered around the Northwestern municipalities in 2000, but changes to the Southeastern part in 2016, a similar development as external death causes. The study identifies areas with increased and decreased odds mortality and could be useful in disease monitoring, especially if we consider small spatial units. |
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A spatio-temporal analysis of cause-specific mortality in São Paulo State, BrazilCause of deathSmall areasSpatio-temporal analysisBrazilAbstract Using five cause-specific mortality data sourced by the Brazilian Ministry of Health, and over 17 years period, we applied Bayesian spatio-temporal models on 644 municipalities of the state of São Paulo, using logistic model to the binary outcome that specifies whether or not the death was from a specific cause. We modeled the temporal mortality effects using B-splines, while the spatial components were considered through Gaussian and Markov random field, and inference was based on Markov chain Monte Carlo simulation. The results demonstrate consistent downward trend in mortality from infectious and parasitic diseases and external causes, while those from neoplasms and respiratory are rising. Cardiovascular is the only cause-specific death that is kept constant in time. All the causes of death considered show heterogeneous spatial and temporal variations among the municipalities, which sometimes change considerably within successive years. Mortality from infectious diseases clustered around the Northwestern municipalities in 2000, but changes to the Southeastern part in 2016, a similar development as external death causes. The study identifies areas with increased and decreased odds mortality and could be useful in disease monitoring, especially if we consider small spatial units.ABRASCO - Associação Brasileira de Saúde Coletiva2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-81232022000100287Ciência & Saúde Coletiva v.27 n.1 2022reponame:Ciência & Saúde Coletiva (Online)instname:Associação Brasileira de Saúde Coletiva (ABRASCO)instacron:ABRASCO10.1590/1413-81232022271.32472020info:eu-repo/semantics/openAccessGayawan,EzraLima,Everton Emanuel Campos deeng2022-01-12T00:00:00Zoai:scielo:S1413-81232022000100287Revistahttp://www.cienciaesaudecoletiva.com.brhttps://old.scielo.br/oai/scielo-oai.php||cienciasaudecoletiva@fiocruz.br1678-45611413-8123opendoar:2022-01-12T00:00Ciência & Saúde Coletiva (Online) - Associação Brasileira de Saúde Coletiva (ABRASCO)false |
dc.title.none.fl_str_mv |
A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil |
title |
A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil |
spellingShingle |
A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil Gayawan,Ezra Cause of death Small areas Spatio-temporal analysis Brazil |
title_short |
A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil |
title_full |
A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil |
title_fullStr |
A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil |
title_full_unstemmed |
A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil |
title_sort |
A spatio-temporal analysis of cause-specific mortality in São Paulo State, Brazil |
author |
Gayawan,Ezra |
author_facet |
Gayawan,Ezra Lima,Everton Emanuel Campos de |
author_role |
author |
author2 |
Lima,Everton Emanuel Campos de |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Gayawan,Ezra Lima,Everton Emanuel Campos de |
dc.subject.por.fl_str_mv |
Cause of death Small areas Spatio-temporal analysis Brazil |
topic |
Cause of death Small areas Spatio-temporal analysis Brazil |
description |
Abstract Using five cause-specific mortality data sourced by the Brazilian Ministry of Health, and over 17 years period, we applied Bayesian spatio-temporal models on 644 municipalities of the state of São Paulo, using logistic model to the binary outcome that specifies whether or not the death was from a specific cause. We modeled the temporal mortality effects using B-splines, while the spatial components were considered through Gaussian and Markov random field, and inference was based on Markov chain Monte Carlo simulation. The results demonstrate consistent downward trend in mortality from infectious and parasitic diseases and external causes, while those from neoplasms and respiratory are rising. Cardiovascular is the only cause-specific death that is kept constant in time. All the causes of death considered show heterogeneous spatial and temporal variations among the municipalities, which sometimes change considerably within successive years. Mortality from infectious diseases clustered around the Northwestern municipalities in 2000, but changes to the Southeastern part in 2016, a similar development as external death causes. The study identifies areas with increased and decreased odds mortality and could be useful in disease monitoring, especially if we consider small spatial units. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-81232022000100287 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-81232022000100287 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1413-81232022271.32472020 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
ABRASCO - Associação Brasileira de Saúde Coletiva |
publisher.none.fl_str_mv |
ABRASCO - Associação Brasileira de Saúde Coletiva |
dc.source.none.fl_str_mv |
Ciência & Saúde Coletiva v.27 n.1 2022 reponame:Ciência & Saúde Coletiva (Online) instname:Associação Brasileira de Saúde Coletiva (ABRASCO) instacron:ABRASCO |
instname_str |
Associação Brasileira de Saúde Coletiva (ABRASCO) |
instacron_str |
ABRASCO |
institution |
ABRASCO |
reponame_str |
Ciência & Saúde Coletiva (Online) |
collection |
Ciência & Saúde Coletiva (Online) |
repository.name.fl_str_mv |
Ciência & Saúde Coletiva (Online) - Associação Brasileira de Saúde Coletiva (ABRASCO) |
repository.mail.fl_str_mv |
||cienciasaudecoletiva@fiocruz.br |
_version_ |
1754213049684721664 |