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Background The Global Burden of Disease (GBD) does not produce estimates of heart failure (HF) since this condition is considered the common end to several diseases (i.e., garbage code). This study aims to analyze the interactions between underlying and multiple causes of death related to HF in Brazil and its geographic regions, by sex, from 2006 to 2016. Methods Descriptive study of a historical series of death certificates (DCs) related to deaths that occurred in Brazil between 2006 and 2016, including both sexes and all age groups. To identify HF as the underlying cause of death or as a multiple cause of death, we considered the International Classification of Diseases (ICD) code I50 followed by any digit. We evaluated the deaths and constructed graphs by geographic region to compare with national data. Results We included 1,074,038 DCs issued between 2006 and 2016 that included code I50 in Parts I or II of the certificate. The frequency of HF as the multiple cause of death in both sexes was nearly three times higher than the frequency of HF as an underlying cause of death; this observation remained consistent over the years. The Southeast region had the highest number of deaths in all years (about 40,000 records) and approximately double the number in the Northeast region and more than four times the number in the North region. Codes of diseases clinically unrelated to HF, such as diabetes mellitus, chronic obstructive pulmonary disease, and stroke, were mentioned in 3.11, 2.62, and 1.49% of the DCs, respectively. Conclusions When we consider HF as the underlying cause of death, we observed an important underestimation of its impact on mortality, since when analyzed as a multiple cause of death, HF is present in almost three times more deaths recorded in Brazil from 2006 to 2016. The mentioning of conditions with little association with HF at the time of the death highlights the importance of HF as a complex syndrome with multiple components that must be considered in the analysis of mortality trends for implementation of public health management programs.

ObjectiveThis study aimed to analyze the chain of events and contributing causes associated with COVID-19 adult mortality (30–69 years old), based on qualified data on CoD from three Brazilian capitals cities, Belo Horizonte, Salvador, and Natal, in 2020.MethodsData of all deaths among residents in the three capitals in 2020 were provided by these municipalities' routine Mortality Information System (SIM). Mentions B34.2 with the markers U07.1 and U07.2 in the death certificate identified COVID-19 deaths. We used a multiple-cause-of-death approach better to understand the complexity of the morbid process of COVID-19. Conditions that appeared more frequently in the same line or above the COVID-19 mentions in the death certificate were considered a chain-of-event. Conditions that occurred more often after the codes for COVID-19 were considered as contributing.ResultsIn 2020, 7,029 records from COVID-19 as the underlying cause of death were registered in SIM in the three capitals. Among these, 2,921 (41.6%) were deceased between 30 and 69 years old, representing 17.0% of deaths in this age group. As chain-of-events, the most frequent conditions mentioned were sepsis (33.4%), SARS (32.0%), acute respiratory failure (31.9%), unspecified lower respiratory infections (unspecified pneumonia) (20.1%), and other specified respiratory disorders (14.1%). Hypertension (33.3%), diabetes unspecified type (21.7%), renal failure (12.7%), obesity (9.8%), other chronic kidney diseases (4.9%), and diabetes mellitus type 2 (4.7%) were the most frequent contributing conditions. On average, 3.04 conditions were mentioned in the death certificate besides COVID-19. This average varied according to age, place of death, and capital.ConclusionThe multiple-cause analysis is a powerful tool to better understand the morbid process due to COVID-19 and highlight the importance of chronic non-communicable diseases as contributing conditions.

In response to the growing concern over diabetes, state-mandated health insurance benefits for diabetes have become popular since the late 1990s. However, little is known about whether these mandates improve the health of people with diabetes. In this paper, I use data from the Vital Statistics Multiple Cause of Death Mortality and the Behavioral Risk Factor Surveillance System to investigate the effects of these mandates on diabetes-related mortality rates, along with underlying mechanisms behind the estimated effects. Using a difference-in-differences framework that leverages variation in the enactment of mandates both across states and over time, I find that about 3.2 fewer diabetes-related deaths per 100,000 occur annually in mandate states than in non-mandate states. The mechanism analysis suggests higher utilization of the mandated medical benefits caused these mortality improvements.