Mortalidade por Doenças Cardiovasculares Segundo o Sistema de Informação sobre Mortalidade e as Estimativas do Estudo Carga Global de Doenças no Brasil, 2000-2017

Abstract

Background: The Brazilian Information System on Mortality (SIM) is of vital importance in monitoring the trends of cardiovascular diseases (CVDs) and is aimed at supporting public policies. Objective: To compare historical series of CVD mortality based on data from the SIM, with and without correction, and from the Brazil Global Burden of Disease (GBD) Study 2017, in the 2000-2017 period. Methods: Analysis of CVD mortality in Brazil between 2000 and 2017. Three CVD mortality estimates were compared: Crude SIM, Corrected SIM, and GBD 2017. Absolute numbers and age-standardized rates were used to compare the estimates for Brazil, its states and the Federal District. Results: In the SIM, the total of deaths ranged from 261,000, in 2000, to 359,000, in 2017. In the GBD 2017, the total of deaths ranged from 292,000 to 388,000, for the same years, respectively. A high proportion of the causes of death from CVD corresponded to garbage codes, classified according to the GBD 2017, reaching 42% in 2017. The rates estimated by GBD ranged from 248.8 (1990) to 178.0 (2017) deaths per 100,000 inhabitants. The rates of the Crude SIM and Corrected SIM also showed a reduction for the whole series analyzed, the Crude SIM showing lower rates: 204.9 (1990) and 155.1 (2017) deaths per 100 thousand inhabitants. When analyzing by the states and Federal District, the Crude SIM trends reversed, with an increase in mortality rates in the Northern and Northeastern states. Conclusion: This study shows the decrease in CVD mortality rates in Brazil in the period analyzed. Conversely, when analyzing by the states and Federal District, the Crude SIM showed an increase in those rates for the Northern and Northeastern states. The use of crude data from the SIM can result in interpretation errors, indicating an increase in rates, due to the increase in death data capture and the improvement in the definition of the underlying causes of death in the past decade, especially in the Northern and Northeastern regions, justifying the use of corrected data in mortality analyses.

Premature mortality due to non-communicable diseases in Brazilian municipalities estimated for the three-year periods of 2010 to 2012 and 2015 to 2017

“…These differences would be explained by the heterogeneity of the quality of information on mortality between Brazilian states and macro-regions 32 . It should be noted that SIM coverage and the quality of information on causes of death have progressed over the last decades in Brazil 33 as a result of the implementation of coordinated government interventions between the levels of municipal, state and federal government 19 , which will contribute to the greater reliability of estimates in the future.…”

“…The data provided by the SIM received treatment to minimize potential biases related to the local quality of the data 19 , since the quality of the SIM is heterogeneous in the country 20 . The empirical Bayesian estimator technique was used to generate mortality rates, a specific methodological approach for estimates in small areas 21 .…”

“…Proportional redistribution of data without information, missing and blank, was carried out each year, for the variables age, sex and municipality of residence 19 . It is noteworthy that the state of residence has always been filled in the DC.…”

Epidemiologia das Doenças Cardiovasculares no Brasil: A Verdade Escondida nos Números

“…4,5 Through data from multiple sources (health records, cohorts and prospective trials, administrative data, verbal analysis and others) and applying complex statistical models, the initiative has provided data by sex, age and country, to more than 310 diseases and conditions, with continuous methodological improvement. 6 The importance of these new metrics is pointed out in the article by Malta et al 7 The authors compared historical series of CVD mortality between 2000 and 2017, based on three estimates: gross data from the Mortality Information System (SIM), corrected for ill-defined causes and underreporting, and those applied by the GBD. Over this period, on all databases, there was a reduction in mortality from CVD mortality in Brazil, by 27% in the gross SIM and 28% by the GBD.…”

“…How can the estimates of prevalence, incidence DOI: https://doi.org/10.36660/abc.20200793 and risk factors for cardiovascular diseases be used by managers and politicians in their decision-making efforts? 4,7 The first step, taken by Malta et al, 7 is to transform existing records into relevant and valid information that can guide objective actions to control CVD. Accepting that local gross records are insufficient for this purpose is extremely relevant.…”