A mortalidade feminina por acidentes de motocicleta nos municípios brasileiros, 2005, 2010 e 2015

Pinheiro, Pedro Cisalpino; Queiroz, Bernardo Lanza; Teixeira, Renato Azeredo; Ribeiro, Antônio Luiz Pinho; Malta, Déborah Carvalho

doi:10.1590/1980-549720200010.supl.1

Cited by 5 publications

(3 citation statements)

References 37 publications

(79 reference statements)

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“…Mortality from motorcycle accidents, for example, has increased significantly in North, Northeast, and Center-West regions in recent decades (19,37,39). Pinheiro et al (40) found that, between 2005 and 2015, several municipalities in the western portion of Paraná, passing through the Center-West and Northeast regions, presented a high concentration of high motorcycle mortality rates among women. To some extent, this spatial pattern can also be observed in our findings.…”

Section: Discussionmentioning

confidence: 99%

Regional Distribution of Causes of Death for Small Areas in Brazil, 1998–2017

Baptista

Queiroz

Pinheiro

2021

Front. Public Health

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Background: What is the spatial pattern of mortality by cause and sex in Brazil? Even considering the main causes of death, such as neoplasms, cardiovascular diseases, external causes, respiratory diseases, and infectious diseases, there are still important debate regarding the spatial pattern of mortality by causes in Brazil. Evidence shows that there is an overlap in transitional health states, due to the persistence of infectious diseases (e.g., dengue, cholera, malaria, etc.,) in parallel with the increase in chronic degenerative diseases. The main objective of this paper is to analyze the spatio-temporal evolution of three groups of causes of death in Brazil across small areas from 1998 to 2017, by sex.Methods: We use publicly available data from the System Data Mortality Information (SIM-DATASUS) from 1998 to 2017. We focus on this period due to the better quality of information, in addition to all deaths are registered following the Tenth Revision of the International Classification of Diseases (ICD-10). We estimate standardized mortality rates by sex and cause aggregated into three main groups. We use a ternary color scheme to maximize all the information in a three-dimensional array of compositional data.Results: We find improvements in mortality from chronic degenerative diseases; faster declines are observed in the Southern regions of the country; but the persistence of high levels of mortality due to infectious diseases remained in the northern parts of the country. We also find impressive differences in external causes of deaths between males and females and an increase in mortality from these causes in the interior part of the country.Conclusions: This study provides useful information for policy makers in establishing effective measures for the prevention of deaths and public health planning for deaths from external and non-communicable causes. We observed how the distribution of causes of death varies across regions and how the patterns of mortality also vary by gender.

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Section: Discussionmentioning

confidence: 99%

Regional Distribution of Causes of Death for Small Areas in Brazil, 1998–2017

Baptista

Queiroz

Pinheiro

2021

Front. Public Health

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“…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 .…”

Section: Treatment Of Mortality Datamentioning

confidence: 99%

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

Cardoso

Teixeira

Ribeiro

et al. 2021

Rev. bras. epidemiol.

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Objective: To estimate premature mortality due to noncommunicable diseases (NCDs) in Brazilian municipalities. Methods: This ecological study estimated premature mortality rates due to cardiovascular diseases, chronic respiratory diseases, cancer and diabetes in Brazilian municipalities, for the three-year periods of 2010 to 2012 and 2015 to 2017, and it analyzed the spatial and temporal distribution of these rates. Data treatment combined proportional redistribution of the missing data and ill-defined causes, and the application of coefficients for under-registration correction. The local empirical Bayesian estimator was used to calculate municipal mortality rates. Results: Rates for the set of chronic diseases decreased in Brazil between the three-year periods. The mean rates for total NCDs declined in the South, Southeast and Central-West regions, remained stable in the North and increased in the Northeast. Mortality rates due to cardiovascular diseases were the highest in all regions but showed the greatest declines between the periods. Cancers were the second leading cause of death. The North and Northeast regions stood out as having increased mean rates of cancer between the periods analyzed and showing the highest mean premature mortality rates due to diabetes in the 2015 to 2017 period. Conclusion: Spatial and temporal distribution of premature mortality rates due to NCDs differed between Brazilian municipalities and regions in the three-year periods evaluated. The South and Southeast had decreased rates of deaths due to cardiovascular and chronic respiratory diseases, as well as diabetes. The North and Northeast had increased rates of deaths due to cancer. There was an increase in the rate of deaths due to diabetes in the Central-West.

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“…Considering that, of the 5,570 municipalities in the country, 88% had a population of less than 50 thousand inhabitants in 2010 10 , it is a great challenge to directly calculate mortality rates in these locations due to instability and great variability in the estimates. Thus, as an alternative, some authors have been using Bayesian methods, such as the Empirical Bayesian Estimator, in order to estimate mortality rates in municipalities 11,12 .…”

Section: Introductionmentioning

confidence: 99%

Mortality due to garbage codes in Brazilian municipalities: differences in rate estimates by the direct and Bayesian methods from 2015 to 2017

Teixeira

Ishitani

França

et al. 2021

Rev. bras. epidemiol.

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Objective: To generate estimates of mortality rates due to garbage codes (GC) for Brazilian municipalities by comparing the direct and the Bayesian methods, based on deaths registered in the Mortality Information System (SIM) between 2015 and 2017. Methods: Data from the SIM were used. The analysis was performed in groups of GC levels 1 and 2, levels 3 and 4, and total GC. Mortality rates were estimated directly and also according to the Bayesian method by applying the Empirical Bayesian Estimator. Results: About 38% of GC were estimated and regional differences in mortality rates were observed, higher in the Northeast and Southeast and lower in the South and Midwest regions. The Southeast presented similar rates for the two analyzed groups of GC. The smallest differences between direct and Bayesian method estimates were observed in large cities with a population over 500 thousand inhabitants. Municipalities in the north of the state of Minas Gerais and those in the states of Rio de Janeiro, São Paulo, and Bahia presented high rates at levels 1 and 2. Conclusion: There are differences in the quality of the definition of the underlying causes of death, even with the use of Bayesian methodology, which assists in smoothing the rates. The quality of the definition of causes of death is important, as they are associated with the access to and quality of healthcare services and support health planning.

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A mortalidade feminina por acidentes de motocicleta nos municípios brasileiros, 2005, 2010 e 2015

Cited by 5 publications

References 37 publications

Regional Distribution of Causes of Death for Small Areas in Brazil, 1998–2017

Regional Distribution of Causes of Death for Small Areas in Brazil, 1998–2017

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

Mortality due to garbage codes in Brazilian municipalities: differences in rate estimates by the direct and Bayesian methods from 2015 to 2017

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