Mortality due to garbage codes in Brazilian municipalities: differences in rate estimates by the direct and Bayesian methods from 2015 to 2017

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...

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Main Authors: Renato Azeredo Teixeira (Author), Lenice Harumi Ishitani (Author), Elisabeth França (Author), Pedro Cisalpino Pinheiro (Author), Marina Martins Lobato (Author), Deborah Carvalho Malta (Author)
Format: Book
Published: Associação Brasileira de Pós-Graduação em Saúde Coletiva.
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100 1 0 |a Renato Azeredo Teixeira  |e author 
700 1 0 |a Lenice Harumi Ishitani  |e author 
700 1 0 |a Elisabeth França  |e author 
700 1 0 |a Pedro Cisalpino Pinheiro  |e author 
700 1 0 |a Marina Martins Lobato  |e author 
700 1 0 |a Deborah Carvalho Malta  |e author 
245 0 0 |a Mortality due to garbage codes in Brazilian municipalities: differences in rate estimates by the direct and Bayesian methods from 2015 to 2017 
260 |b Associação Brasileira de Pós-Graduação em Saúde Coletiva. 
500 |a 1980-5497 
500 |a 10.1590/1980-549720210003.supl.1 
520 |a 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. 
546 |a EN 
546 |a PT 
690 |a Data accuracy 
690 |a Mortality registries 
690 |a Cause of death 
690 |a Small-area analysis 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n Revista Brasileira de Epidemiologia 
787 0 |n http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2021000200414&tlng=pt 
787 0 |n http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2021000200414&tlng=en 
787 0 |n http://www.scielo.br/pdf/rbepid/v24s1/pt_1980-5497-rbepid-24-supl1-e210003.pdf 
787 0 |n http://www.scielo.br/pdf/rbepid/v24s1/1980-5497-rbepid-24-supl1-e210003.pdf 
787 0 |n https://doaj.org/toc/1980-5497 
856 4 1 |u https://doaj.org/article/4d16c991db9a45e8a65a7da169a0e6a3  |z Connect to this object online.