Cardiovascular mortality in Brazil during the COVID-19 pandemic: a comparison between underlying and multiple causes of death

Data de publicação

Novembro de 2023

Periódico

Public Health

Resumo

Objetives – The COVID-19 pandemic has differentially impacted cardiovascular disease (CVD) mortality worldwide. Causes of death misclassification may be one of the reasons. We evaluated the impact of the pandemic on CVD mortality in Brazil, comparing underlying causes (UCs) and multiple causes (MCs) of death.

Study design – Ecological time-series study.

Methods – An ecological, time-series study was conducted analysing age-standardised death rates for CVD, from epidemiological week (EW) 10/2020 to 39/2021, using data from the Mortality Information System, Brazil. CVD was defined using the International Classification of Diseases (ICD-10) coding, if reported as UC or MC of death. Observed and expected data (mean for the same EW, 2017–2019) were compared. Risk ratios (RiRs) were analysed, and 95% confidence intervals (CIs) were calculated.

Results – Age-standardised mortality rate for CVD as UC of death was 165.8 (95%CI: 165.4–166.3) per 100,000 inhabitants, similar to what was expected (165.6/100,000, 95%CI: 165.2–166.1, RiR = 1.00). There was increased out-of-hospital mortality (RiR = 1.18; 95%CI: 1.17–1.19) and deaths of ill-defined causes (RiR = 1.43; 95%CI: 1.42–1.44). The increase in out-of-hospital deaths was more pronounced in the North (RiR = 1.33; 95%CI 1.30–1.36) region, with a less resilient health system. Conversely, as MCs of death, there was a 10% increase in CVD mortality (observed: 243.2 [95%CI: 242.7–243.7], expected: 221.6 [95%CI: 221.1–222.1] per 100,000). An increase also occurred in the North and Central West regions (RiR = 1.16; 95%CI: 1.15–1.18), among men (RiR = 1.11; 95%CI: 1.11–1.12) and individuals aged ≥60 years (RiR = 1.11; 95%CI: 1.10–1.11).

Conclusions – During the pandemic, mortality rates for CVD as MCs of death increased in Brazil, whereas as UC mortality rates did not change. Higher out-of-hospital mortality, misclassification, and competing causes of death may explain this pattern.

DOI/link

https://doi.org/10.1590/S1679-49742021000100017

Autoria

Vínculo institucional

Lattes

Orcid

Luísa Campos Caldeira Brant

School of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil and Telehealth Center, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

Pedro Cisalpino Pinheiro

School of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

Luiz Guilherme Passaglia

School of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

Maria De Fátima Marinho de Souza

School of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

Deborah Carvalho Malta

School of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil and Nursing School, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

Amitava Banerjee

Institute of Health Informatics, University College London, London, UK

Antonio Luiz Pinho Ribeiro

Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

Bruno Ramos Nascimento

School of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil and Telehealth Center, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil and Serviço de Hemodinâmica do Hospital Madre Teresa, Belo Horizonte, MG, Brazil