The effect of redistributions of garbage codes on the evolution of mortality from Chronic Diseases in Brazil, 2010 to 2019

Abstract This study aimed to estimate premature mortality (30-69 years) for four priority NCD groups in Brazil from 2010 to 2019, comparing crude data from the Mortality Information System (SIM), SIM data adjusted by GC redistribution and underreporting, and data extracted from the Global Burden of Disease (GBD) study. Premature mortality rates due to NCDs declined in the period analyzed. Although the adjustment methods hardly changed temporal trends, we observed that mortality rates calculated with adjusted data were significantly higher than those without adjustment. This variation was heterogeneous among the Federated Units. The rates estimated by the crude SIM method ranged from 322.0 to 276.1 deaths per 100 thousand inhabitants, while the redistributed SIM rates ranged from 340.4 to 296.8 deaths per 100 thousand inhabitants. The estimated rates for the GBD ranged from 371.6 to 323.0 deaths per 100 thousand inhabitants. In conclusion, this study highlights the importance of adopting methods that can be applied to achieve more reliable mortality statistics, which continuously improves the definition of death causes in the SIM.

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Publication Details

Journal
Ciência & Saúde Coletiva
Published
2025-03-01
DOI
https://doi.org/10.1590/1413-81232025303.00492024en
Citations
1
Primary Topic
Global Public Health Policies and Epidemiology
Type
article
Field-Weighted Citation Impact
2.76

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article

The effect of redistributions of garbage codes on the evolution of mortality from Chronic Diseases in Brazil, 2010 to 2019

Marli de Mesquita Silva Montenegro, Lenice Harumi Ishitani, Crizian Saar Gomes, Déborah Carvalho Malta et al.
1 citations
Ciência & Saúde Coletiva
Global Public Health Policies and Epidemiology
2.76
article

The effect of redistributions of garbage codes on the evolution of mortality from Chronic Diseases in Brazil, 2010 to 2019

Marli de Mesquita Silva Montenegro, Lenice Harumi Ishitani, Crizian Saar Gomes, Déborah Carvalho Malta, Valdelaine Etelvina Miranda de Araújo, Érika Carvalho de Aquino, Bruce Bartholow Duncan, Ana Maria Nogales Vasconcelos, Shirlei Moreira da Costa Faria, Elisabeth Barboza França, Juliana Bottoni de Souza, Renato Azeredo Teixeira, Ademar B. Dantas Júnior, Adauto Martins Soares Filho, Maria de Fátima Marinho de Souza, Antônio Luiz Pinho Ribeiro
article en
1 citations

Abstract

Abstract This study aimed to estimate premature mortality (30-69 years) for four priority NCD groups in Brazil from 2010 to 2019, comparing crude data from the Mortality Information System (SIM), SIM data adjusted by GC redistribution and underreporting, and data extracted from the Global Burden of Disease (GBD) study. Premature mortality rates due to NCDs declined in the period analyzed. Although the adjustment methods hardly changed temporal trends, we observed that mortality rates calculated with adjusted data were significantly higher than those without adjustment. This variation was heterogeneous among the Federated Units. The rates estimated by the crude SIM method ranged from 322.0 to 276.1 deaths per 100 thousand inhabitants, while the redistributed SIM rates ranged from 340.4 to 296.8 deaths per 100 thousand inhabitants. The estimated rates for the GBD ranged from 371.6 to 323.0 deaths per 100 thousand inhabitants. In conclusion, this study highlights the importance of adopting methods that can be applied to achieve more reliable mortality statistics, which continuously improves the definition of death causes in the SIM.

Ciência & Saúde ColetivaVol. 30(3)
Universidade Federal de Minas Gerais (BR), Universidade Federal do Rio Grande do Sul (BR), Universidade de Brasília (BR), Ministério da Saúde (ST), Vital Strategies (US), Secretaria Municipal de Saúde (BR), Universidade Federal de Goiás (BR)
Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado de Minas Gerais, Ministério da Saúde
Openalex Percentile: Top 12%
Global Public Health Policies and Epidemiology
2.76
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