ABC | Volume 115, Nº2, August 2020

Original Article Malta et al. Cardiovascular Disease Mortality in SIM and GBD Arq Bras Cardiol. 2020; 115(2):152-160 between corrected estimates and crude ones. Level 1 and level 2 GC, those with little specification of the real cause of death, correspond to 12% of the SIM records. When level 3 and level 4 GC are considered to be redistributed in the same group of causes, that is, with better specification of the cause of death, the GC can reach 40%, which can lead to differences in the estimates between the SIM and the GBD. 6,8 This study indicates that the Crude SIM analyses are biased, especially for the Northern and Northeastern states. Therefore, its adoption is not recommended, especially for the definition of regional policies, because the rates are subject to estimation errors, such as those due to underreporting and excessive proportion of ill- defined causes. Methodological adjustments to coverage and redistribution of ill-defined causes are necessary, even more when it comes to the analysis of historical series, involving a period in which the quality of SIM was impaired. In 2015, the United Nations Assembly approved the Sustainable Development Goals, representing 17 global challenges to achieve a better and more sustainable future for all. One of the goals is to ensure good health and well- being for all, at all ages. It includes the indicator “a 30% reduction in premature mortality from CNCDs by 2030”, whose calculation involves a reduction in CVDs. Reducing CNCDs and CVDs is a global challenge. 21-23 To meet the goal to prevent and control CNCDs, the World Health Organization has issued a document recommending the adoption of interventions for health promotion, with the implementation of public policies within and across sectors that promote healthy practices, such as healthy diets, low-sodium food products, open public spaces and adequate infrastructure to support physical activity, smoke-free environments, and alcohol advertising regulation. 24 In addition, it is worth noting the importance of investing in primary care and access to medium and high complexity technologies, when necessary, aimed at the whole care of patients with CNCDs. 25 This study shows an increase (GBD 2017) or stability (Corrected SIM) in the mortality rates due the CVD from 2015 onwards. These data need to be revised because of the short period analyzed. However, other studies have reported worsening of health indicators in Brazil, which has been attributed to the economic crisis, the increase in poverty, and the cuts in health and social policies resulting from the Constitutional Amendment 95/2016 and the freeze on public expenses, health included, for 20 years. 22-25 This study has limitations. The use of secondary databases can add biases, such as underreporting and inconsistencies in death certificate completion. In addition, the Brazilian population estimates may be subject to errors, as the last available census in Brazil dates back to 2010. Moreover, the GBD estimates might have limitations because of its sources, adjustments, and algorithms used. Conclusion This study shows the decline in the CVD mortality rates in the period analyzed, except for the last two years. The comparison of the estimates shows similarities between the Corrected SIM and the GBD Study 2017. However, the use of the Crude SIM data is not recommended, especially for subnational analyses, because it can result in interpretation errors. In this study, the increase in mortality rates might have reflected the improvement in death data capture and in the definition of the underlying causes of death in the past decade, especially in the Northern and Northeastern regions. This justifies the recommendation to always use corrected data for mortality analyses. Author contributions Conception and design of the research, Analysis and interpretation of the data and Critical revision of the manuscript for intellectual content: Malta DC, Teixeira R, Oliveira GMM, Ribeiro AL; Acquisition of data and Writing of the manuscript: Malta DC, Teixeira R; Statistical analysis: Teixeira R; Obtaining financing: Malta DC, Ribeiro AL. Potential Conflict of Interest No potential conflict of interest relevant to this article was reported. Sources of Funding Ministerio da Saúde – Fundo Nacional de Saúde – TED 148/2018. Dr. Ribeiro was supported in part by CNPq (Bolsa de produtividade em pesquisa, 310679/2016-8 and IATS, project: 465518/2014-1) and by FAPEMIG (Programa Pesquisador Mineiro, PPM-00428-17). Malta DC was supported in part by CNPq (Bolsa de produtividade em pesquisa) and by FAPEMIG (Programa Pesquisador Mineiro). Study Association This study is not associated with any thesis or dissertation work. 1. Brasil.MinistériodaSaúde.Departamentode InformáticadoSUS–DATASUS. InformaçõesdeSaúde,EpidemiológicaseMorbidade:bancodedados.[Acesso em 12fev2018].Disponívelem :http://www2.datasus.gov.br/DATASUS/index. php?area=0501. 2. Brasil.MinistériodaSaúde.SaúdeBrasil2018umaanálisedesituaçãodesaúde edasdoençaseagravoscr ônicos:desafioseperspectivas.Brasília ;2019. 3. Mello Jorge MHP, Laurenti R, Gotlieb SL. Análise da qualidade das estatísticas vitaisb rasileiras:aexperiênciadeimplantaçãodoSIMedoSINASC.CiêncSaúde Coletiva.2007;12(3):643-54. 4. Saltarelli RMF, Prado RR, Monteiro RA, Malta DC. Tendência da mortalidade porcausasevitáveisnainfância:contribuiçõesparaaavaliaçãodedesempenho dos serviços públicos de saúde da Região Sudeste do Brasil. Rev Bras. Epidemiol.2019;22:e190020. References 159