Analysis of the evolution of infant mortality rates of children residing in the state of rio grande do sul, brazil
Autor(a) principal: | |
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Data de Publicação: | 2024 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Saúde (Santa Maria) |
Texto Completo: | https://periodicos.ufsm.br/revistasaude/article/view/69170 |
Resumo: | Objective: This study aims to highlight the main characteristics and compare the evolution of infant mortality rates in the state of Rio Grande do Sul (RS) through the ARIMA and ARMA methodologies. Method The monthly infant mortality rates of the period of 2000 to 2017 were obtained from the Unified Health System (SUS) Department of Informatics (DATASUS). A descriptive analysis and time series modelling using the ARIMA and ARMA methodologies were carried out and discussed. Results: Cacique Doble, Alto Alegre, and São Valério do Sul were the cities of residence with the highest infant mortality rates for the state of RS in the period. Based on the residual analysis and the AIC and BIC penalizing criteria, a better quality of fit was observed in the ARMA(4,6) model. Conclusion Although the ARMA model presented better quality of fit, the accuracy measurements were lower in the SARIMA model. The proposed methodologies can guide the planning of preventive and educational policies aimed at the risk of a born alive dying during its first year of life. |
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Analysis of the evolution of infant mortality rates of children residing in the state of rio grande do sul, brazilAnálise da evolução das taxas de mortalidade de crianças com até um ano de idade residentes no estado do rio grande do sulInfant mortalityChild mortalityARIMAβARMAForecastingMortalidade infantilSéries temporaisARIMAARMA PrevisãoObjective: This study aims to highlight the main characteristics and compare the evolution of infant mortality rates in the state of Rio Grande do Sul (RS) through the ARIMA and ARMA methodologies. Method The monthly infant mortality rates of the period of 2000 to 2017 were obtained from the Unified Health System (SUS) Department of Informatics (DATASUS). A descriptive analysis and time series modelling using the ARIMA and ARMA methodologies were carried out and discussed. Results: Cacique Doble, Alto Alegre, and São Valério do Sul were the cities of residence with the highest infant mortality rates for the state of RS in the period. Based on the residual analysis and the AIC and BIC penalizing criteria, a better quality of fit was observed in the ARMA(4,6) model. Conclusion Although the ARMA model presented better quality of fit, the accuracy measurements were lower in the SARIMA model. The proposed methodologies can guide the planning of preventive and educational policies aimed at the risk of a born alive dying during its first year of life.Este estudo tem por objetivo destacar as principais características e comparar a evolução das taxas de mortalidade infantil no Estado do Rio Grande do Sul (RS) por meio das metodologias ARIMA e ARMA. Método: As taxas mensais de mortalidade infantil do período de 2000 a 2017 foram obtidas do Departamento de Informática do Sistema Único de Saúde (SUS) (DATASUS). Foi realizada e discutida uma análise descritiva e modelagem de séries temporais utilizando as metodologias ARIMA e ARMA. Resultados: Cacique Doble, Alto Alegre e São Valério do Sul foram as cidades de residência com as taxas de mortalidade infantil mais elevadas para o estado do RS no período. Com base na análise dos resíduos e nos critérios penalizadores de AIC e BIC, foi observada uma melhor qualidade de ajuste no modelo ARMA(4,6). Conclusão: Embora o modelo ARMA apresentasse melhor qualidade ajuste, as medidas de acuracidade foram inferiores no modelo SARIMA. As metodologias propostas podem orientar no planejamento de políticas preventivas e educativas voltadas ao risco de um nascido vivo morrer durante o seu primeiro ano de vida.Universidade Federal de Santa Maria2024-05-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/revistasaude/article/view/6917010.5902/2236583469170Saúde (Santa Maria); Vol. 50 No. 1 (2024): Revista Saúde (Santa Maria) | Fluxo contínuoSaúde (Santa Maria); v. 50 n. 1 (2024): Revista Saúde (Santa Maria) | Fluxo contínuo2236-58340103-4499reponame:Saúde (Santa Maria)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMporhttps://periodicos.ufsm.br/revistasaude/article/view/69170/63830Copyright (c) 2024 Cristiane Melchior, Roselaine Ruviaro Zanini, Mírianhttps://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessMelchior, CristianeZanini, Roselaine RuviaroMírian2024-05-21T18:26:29Zoai:ojs.pkp.sfu.ca:article/69170Revistahttps://periodicos.ufsm.br/revistasaudePUBhttps://periodicos.ufsm.br/revistasaude/oairevistasaude.ufsm@gmail.com || amanda.revsaude@gmail.com || beatriz.revsaude@gmail.com2236-58342236-5834opendoar:2024-05-21T18:26:29Saúde (Santa Maria) - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Analysis of the evolution of infant mortality rates of children residing in the state of rio grande do sul, brazil Análise da evolução das taxas de mortalidade de crianças com até um ano de idade residentes no estado do rio grande do sul |
title |
Analysis of the evolution of infant mortality rates of children residing in the state of rio grande do sul, brazil |
spellingShingle |
Analysis of the evolution of infant mortality rates of children residing in the state of rio grande do sul, brazil Melchior, Cristiane Infant mortality Child mortality ARIMA βARMA Forecasting Mortalidade infantil Séries temporais ARIMA ARMA Previsão |
title_short |
Analysis of the evolution of infant mortality rates of children residing in the state of rio grande do sul, brazil |
title_full |
Analysis of the evolution of infant mortality rates of children residing in the state of rio grande do sul, brazil |
title_fullStr |
Analysis of the evolution of infant mortality rates of children residing in the state of rio grande do sul, brazil |
title_full_unstemmed |
Analysis of the evolution of infant mortality rates of children residing in the state of rio grande do sul, brazil |
title_sort |
Analysis of the evolution of infant mortality rates of children residing in the state of rio grande do sul, brazil |
author |
Melchior, Cristiane |
author_facet |
Melchior, Cristiane Zanini, Roselaine Ruviaro Mírian |
author_role |
author |
author2 |
Zanini, Roselaine Ruviaro Mírian |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Melchior, Cristiane Zanini, Roselaine Ruviaro Mírian |
dc.subject.por.fl_str_mv |
Infant mortality Child mortality ARIMA βARMA Forecasting Mortalidade infantil Séries temporais ARIMA ARMA Previsão |
topic |
Infant mortality Child mortality ARIMA βARMA Forecasting Mortalidade infantil Séries temporais ARIMA ARMA Previsão |
description |
Objective: This study aims to highlight the main characteristics and compare the evolution of infant mortality rates in the state of Rio Grande do Sul (RS) through the ARIMA and ARMA methodologies. Method The monthly infant mortality rates of the period of 2000 to 2017 were obtained from the Unified Health System (SUS) Department of Informatics (DATASUS). A descriptive analysis and time series modelling using the ARIMA and ARMA methodologies were carried out and discussed. Results: Cacique Doble, Alto Alegre, and São Valério do Sul were the cities of residence with the highest infant mortality rates for the state of RS in the period. Based on the residual analysis and the AIC and BIC penalizing criteria, a better quality of fit was observed in the ARMA(4,6) model. Conclusion Although the ARMA model presented better quality of fit, the accuracy measurements were lower in the SARIMA model. The proposed methodologies can guide the planning of preventive and educational policies aimed at the risk of a born alive dying during its first year of life. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-05-21 |
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://periodicos.ufsm.br/revistasaude/article/view/69170 10.5902/2236583469170 |
url |
https://periodicos.ufsm.br/revistasaude/article/view/69170 |
identifier_str_mv |
10.5902/2236583469170 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://periodicos.ufsm.br/revistasaude/article/view/69170/63830 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2024 Cristiane Melchior, Roselaine Ruviaro Zanini, Mírian https://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2024 Cristiane Melchior, Roselaine Ruviaro Zanini, Mírian https://creativecommons.org/licenses/by-nc-nd/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
dc.source.none.fl_str_mv |
Saúde (Santa Maria); Vol. 50 No. 1 (2024): Revista Saúde (Santa Maria) | Fluxo contínuo Saúde (Santa Maria); v. 50 n. 1 (2024): Revista Saúde (Santa Maria) | Fluxo contínuo 2236-5834 0103-4499 reponame:Saúde (Santa Maria) instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Saúde (Santa Maria) |
collection |
Saúde (Santa Maria) |
repository.name.fl_str_mv |
Saúde (Santa Maria) - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
revistasaude.ufsm@gmail.com || amanda.revsaude@gmail.com || beatriz.revsaude@gmail.com |
_version_ |
1799943998372052992 |