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Mortality due to garbage codes in Brazilian municipalities: differences in rate estimates by the direct and Bayesian methods from 2015 to 2017 / Mortalidade por causas garbage nos municípios brasileiros: diferenças nas estimativas de taxas pelos métodos direto e Bayesiano de 2015 a 2017
Graduate Program in Public HealthTeixeira, Renato Azeredo; Ishitani, Lenice Harumi; Graduate Program in Public HealthFrança, Elisabeth; Pinheiro, Pedro Cisalpino; Lobato, Marina Martins; Graduate Program in Public HealthMalta, Deborah Carvalho.
  • Graduate Program in Public HealthTeixeira, Renato Azeredo; Universidade Federal de Minas Gerais. School of Medicine. Graduate Program in Public HealthTeixeira, Renato Azeredo. Belo Horizonte. BR
  • Ishitani, Lenice Harumi; Universidade Federal de Minas Gerais. Epidemiology and Health Assessment Research Group. Belo Horizonte. BR
  • Graduate Program in Public HealthFrança, Elisabeth; Universidade Federal de Minas Gerais. School of Medicine. Graduate Program in Public HealthFrança, Elisabeth. Belo Horizonte. BR
  • Pinheiro, Pedro Cisalpino; Universidade Federal de Minas Gerais. School of Medicine. Belo Horizonte. BR
  • Lobato, Marina Martins; Universidade Federal de Minas Gerais. Belo Horizonte. BR
  • Graduate Program in Public HealthMalta, Deborah Carvalho; Universidade Federal de Minas Gerais. School of Medicine. Graduate Program in Public HealthMalta, Deborah Carvalho. Belo Horizonte. BR
Rev. bras. epidemiol ; 24(supl.1): e210003, 2021. tab, graf
Article in English, Portuguese | LILACS | ID: biblio-1288495
ABSTRACT
ABSTRACT

Objective:

To generate estimates of mortality rates due to garbage codes (GC) for Brazilian municipalities by comparing the direct and the Bayesian methods, based on deaths registered in the Mortality Information System (SIM) between 2015 and 2017.

Methods:

Data from the SIM were used. The analysis was performed in groups of GC levels 1 and 2, levels 3 and 4, and total GC. Mortality rates were estimated directly and also according to the Bayesian method by applying the Empirical Bayesian Estimator.

Results:

About 38% of GC were estimated and regional differences in mortality rates were observed, higher in the Northeast and Southeast and lower in the South and Midwest regions. The Southeast presented similar rates for the two analyzed groups of GC. The smallest differences between direct and Bayesian method estimates were observed in large cities with a population over 500 thousand inhabitants. Municipalities in the north of the state of Minas Gerais and those in the states of Rio de Janeiro, São Paulo, and Bahia presented high rates at levels 1 and 2.

Conclusion:

There are differences in the quality of the definition of the underlying causes of death, even with the use of Bayesian methodology, which assists in smoothing the rates. The quality of the definition of causes of death is important, as they are associated with the access to and quality of healthcare services and support health planning.
RESUMO
RESUMO

Objetivo:

Gerar estimativas das taxas de mortalidade por causas garbage (CG) para os municípios do Brasil, fazendo a comparação entre o método direto e o Bayesiano, tendo como base os óbitos registrados no Sistema de Informações sobre Mortalidade (SIM) entre 2015 e 2017.

Métodos:

Os dados do SIM foram utilizados. A análise foi realizada com grupos de CG níveis 1 e 2, 3 e 4 e total de CG. As taxas de mortalidade foram estimadas de forma direta e bayesiana, aplicando o estimador Bayesianos Empírico Local.

Resultados:

Observaram-se 38% de CG e diferenças regionais nas taxas de mortalidade, maiores no Nordeste e Sudeste e menores no Sul e Centro-Oeste. O Sudeste apresentou taxas semelhantes para os dois grupos de CG analisados. As menores diferenças entre as estimativas diretas e bayesianas foram verificadas nas grandes cidades, acima de 500 mil habitantes. O norte de Minas Gerais e os estados do Rio de Janeiro, de São Paulo e da Bahia apresentaram municípios com altas taxas nos níveis 1 e 2.

Conclusão:

Existem diferenças na qualidade da definição das causas básicas de morte, mesmo com o uso de metodologia bayesiana, que auxilia na suavização das taxas. A qualidade da definição das causas de morte é importante, uma vez que se mostra associada ao acesso e à qualidade dos serviços de saúde e oferecem subsídios para o planejamento em saúde.
Subject(s)


Full text: Available Index: LILACS (Americas) Main subject: Information Systems / Mortality Type of study: Etiology study / Prognostic study Limits: Humans Country/Region as subject: South America / Brazil Language: English / Portuguese Journal: Rev. bras. epidemiol Journal subject: Epidemiology / Public Health Year: 2021 Type: Article Affiliation country: Brazil Institution/Affiliation country: Universidade Federal de Minas Gerais/BR

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Full text: Available Index: LILACS (Americas) Main subject: Information Systems / Mortality Type of study: Etiology study / Prognostic study Limits: Humans Country/Region as subject: South America / Brazil Language: English / Portuguese Journal: Rev. bras. epidemiol Journal subject: Epidemiology / Public Health Year: 2021 Type: Article Affiliation country: Brazil Institution/Affiliation country: Universidade Federal de Minas Gerais/BR