Mortality inequalities measured by socioeconomic indicators in Brazil: a scoping review

OBJECTIVE Summarize the literature on the relationship between composite socioeconomic indicators and mortality in different geographical areas of Brazil. METHODS This scoping review included articles published between January 1, 2000, and August 31, 2020, retrieved by means of a bibliographic search carried out in the Medline, Scopus, Web of Science, and Lilacs databases. Studies reporting on the association between composite socioeconomic indicators and all-cause, or specific cause of death in any age group in different geographical areas were selected. The review summarized the measures constructed, their associations with the outcomes, and potential study limitations. RESULTS Of the 77 full texts that met the inclusion criteria, the study reviewed 24. The area level of composite socioeconomic indicators analyzed comprised municipalities (n = 6), districts (n = 5), census tracts (n = 4), state (n = 2), country (n = 2), and other areas (n = 5). Six studies used composite socioeconomic indicators such as the Human Development Index, Gross Domestic Product, and the Gini Index; the remaining 18 papers created their own socioeconomic measures based on sociodemographic and health indicators. Socioeconomic status was inversely associated with higher rates of all-cause mortality, external cause mortality, suicide, homicide, fetal and infant mortality, respiratory and circulatory diseases, stroke, infectious and parasitic diseases, malnutrition, gastroenteritis, and oropharyngeal cancer. Higher mortality rates due to colorectal cancer, leukemia, a general group of neoplasms, traffic accident, and suicide, in turn, were observed in less deprived areas and/or those with more significant socioeconomic development. Underreporting of death and differences in mortality coverage in Brazilian areas were cited as the main limitation. CONCLUSIONS Studies analyzed mortality inequalities in different geographical areas by means of composite socioeconomic indicators, showing that the association directions vary according to the mortality outcome. But studies on all-cause mortality and at the census tract level remain scarce. The results may guide the development of new composite socioeconomic indicators for use in mortality inequality analysis

Differentials in death count records by databases in Brazil in 2010

OBJECTIVE To compare the death counts from three sources of information on mortality available in Brazil in 2010, the Mortality Information System (SIM - Sistema de Informações sobre Mortalidade ), Civil Registration Statistic System (RC - Sistema de Estatísticas de Resgistro Civil ), and the 2010 Demographic Census at various geographical levels, and to confirm the association between municipal socioeconomic characteristics and the source which showed the highest death count. METHODS This is a descriptive and comparative study of raw data on deaths in the SIM, RC and 2010 Census databases, the latter held in Brazilian states and municipalities between August 2009 and July 2010. The percentage of municipalities was confirmed by the database showing the highest death count. The association between the source of the highest death count and socioeconomic indicators - the Índice de Privação Brasileiro (IBP – Brazilian Deprivation Index) and Índice de Desenvolvimento Humano Municipal (IHDM – Municipal Human Development Index) - was performed by bivariate choropleth and Moran Local Index of Spatial Association (LISA) cluster maps. RESULTS Confirmed that the SIM is the database with the highest number of deaths counted for all Brazilian macroregions, except the North, in which the highest coverage was from the 2010 Census. Based on the indicators proposed, in general, the Census showed a higher coverage of deaths than the SIM and the RC in the most deprived (highest IBP values) and less developed municipalities (lowest IDHM values) in the country. CONCLUSION The results highlight regional inequalities in how the databases chosen for this study cover death records, and the importance of maintaining the issue of mortality on the basic census questionnaire

Mortality inequalities measured by socioeconomic indicators in Brazil: a scoping review

Objective: Summarize the literature on the relationship between composite socioeconomic indicators and mortality in different geographical areas of Brazil. Methods: This scoping review included articles published between January 1, 2000, and August 31, 2020, retrieved by means of a bibliographic search carried out in the Medline, Scopus, Web of Science, and Lilacs databases. Studies reporting on the association between composite socioeconomic indicators and all-cause, or specific cause of death in any age group in different geographical areas were selected. The review summarized the measures constructed, their associations with the outcomes, and potential study limitations. Results: Of the 77 full texts that met the inclusion criteria, the study reviewed 24. The area level of composite socioeconomic indicators analyzed comprised municipalities (n = 6), districts (n = 5), census tracts (n = 4), state (n = 2), country (n = 2), and other areas (n = 5). Six studies used composite socioeconomic indicators such as the Human Development Index, Gross Domestic Product, and the Gini Index; the remaining 18 papers created their own socioeconomic measures based on sociodemographic and health indicators. Socioeconomic status was inversely associated with higher rates of all-cause mortality, external cause mortality, suicide, homicide, fetal and infant mortality, respiratory and circulatory diseases, stroke, infectious and parasitic diseases, malnutrition, gastroenteritis, and oropharyngeal cancer. Higher mortality rates due to colorectal cancer, leukemia, a general group of neoplasms, traffic accident, and suicide, in turn, were observed in less deprived areas and/or those with more significant socioeconomic development. Underreporting of death and differences in mortality coverage in Brazilian areas were cited as the main limitation. Conclusions: Studies analyzed mortality inequalities in different geographical areas by means of composite socioeconomic indicators, showing that the association directions vary according to the mortality outcome. But studies on all-cause mortality and at the census tract level remain scarce. The results may guide the development of new composite socioeconomic indicators for use in mortality inequality analysis

Differentials in death count records by databases in Brazil in 2010

Objective: To compare the death counts from three sources of information on mortality available in Brazil in 2010, the Mortality Information System (SIM – Sistema de Informações sobre Mortalidade ), Civil Registration Statistic System (RC – Sistema de Estatísticas de Resgistro Civil ), and the 2010 Demographic Census at various geographical levels, and to confirm the association between municipal socioeconomic characteristics and the source which showed the highest death count. Methods: This is a descriptive and comparative study of raw data on deaths in the SIM, RC and 2010 Census databases, the latter held in Brazilian states and municipalities between August 2009 and July 2010. The percentage of municipalities was confirmed by the database showing the highest death count. The association between the source of the highest death count and socioeconomic indicators – the Índice de Privação Brasileiro (IBP – Brazilian Deprivation Index) and Índice de Desenvolvimento Humano Municipal (IHDM – Municipal Human Development Index) – was performed by bivariate choropleth and Moran Local Index of Spatial Association (LISA) cluster maps. Results: Confirmed that the SIM is the database with the highest number of deaths counted for all Brazilian macroregions, except the North, in which the highest coverage was from the 2010 Census. Based on the indicators proposed, in general, the Census showed a higher coverage of deaths than the SIM and the RC in the most deprived (highest IBP values) and less developed municipalities (lowest IDHM values) in the country. Conclusion: The results highlight regional inequalities in how the databases chosen for this study cover death records, and the importance of maintaining the issue of mortality on the basic census questionnaire

Algoritmo Wang-Landau e agrupamento de dados superparamagnético

O método de agrupamento de dados não supervisionado proposto por Domany e colaboradores baseia-se no mapeamento do problema em um sistema magnético granular não homogêneo, cujas propriedades são investigadas através de algum método de Monte Carlo. A matriz que contém os dados é composta por n atributos de valor numérico e corresponde a um ponto em um espaço euclidiano n-dimensional. A cada item de dado é associado um spin de Potts. A interação entre tais spins decai exponencialmente com o aumento da distância entre eles. Isto favorece o alinhamento dos spins associados a objetos similares. O sistema físico corresponde a um ferromagneto desordenado que, por sua vez, é descrito por um hamiltoniano de Potts de q estados. Espera-se que o sistema magnético exiba três regimes quando sua temperatura seja variada. Para temperaturas muito baixas o sistema está completamente ordenado. No outro extremo, em altas temperaturas, o sistema não apresenta qualquer ordem magnética. Numa faixa intermediária de temperaturas, spins dentro de certas regiões permanecem fortemente acoplados, formando grãos. Porém, um grão não influencie o comportamento de outro grão. Ou seja, os grãos estão não correlacionados. Este estado intermediário caracteriza um estado superparamagnético. A transição de um regime para outro pode ser identificada por picos na curva de calor específico versus temperatura. Aplicamos o método aos conjuntos de dados reais da planta íris e de dados médicos, conhecido por BUPA, aos dados sintéticos conhecidos por Ruspini e a um conjunto de dados, gerado por nós, que consiste de duas figuras tridimensionais sobrepostas, um esfera e um toro. Procedemos a classificação dos dados através da correlação spin-spin em diversas temperaturas. O principal resultado foi a verificação que nem sempre o agrupamento realizado na fase superparamagnética é o ideal.The method of unsupervised data classification proposed by Domany and coworkers is based on mapping the problem onto an inhomogeneous granular magnetic system whose properties can be investigated through some Monte Carlo Method. The array containing the data consists of n numeric attributes corresponding to points in an n-dimensional Euclidean space. Each data item is associated with a Potts spin. The interaction between such spins decays exponentially with the distance. This favors the alignment of the spins associated with similar objects. The physical system corresponds to a disordered ferromagnet which, in turn, is described by a Hamiltonian of a q-states Potts model. It is expected that the magnetic system exhibits three temperature-dependent regimes. For very low temperatures the system is completely ordered. At the other extreme, high temperatures, the system shows no magnetic order. In an intermediate range of temperatures, the spins within certain regions remain tightly coupled, forming grains. However, a grain does not influence the behavior of another grain. That is, the grains are non-correlated and this intermediate state is named a superparamagnetic phase. The transition from one regime to another can be identified by peaks in the specific heat versus temperature curve. We apply the method to several artificial and real-life data sets, such as classification of flowers, summary medical data and identification of images. We measure the spin-spin correlation at several temperatures to classify the data. In disagreement with the Domany and coworkers claims we found that the best classification of the data occurred outside the superparagnetic phase.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPE

Estudo de séries temporais de preços de petróleo, etanol e açúcar através da Transfer Entropy

A infraestrutura energética brasileira no setor de transportes tem características únicas, com uma grande participação de bioenergia. O governo brasileiro obriga a adição de etanol na gasolina e esse percentual varia como um mecanismo político de estabilização dos preços, aumentando ou diminuindo a depender da capacidade industrial de produzir etanol e do preço do petróleo. O preço da cana-de-açúcar também tem um papel fundamental nesta tomada de decisão. O mercado interno alterna o destino da cana-de-açúcar para produção de etanol ou de açúcar dependendo dos preços do mercado. Grande parte da produção de etanol é destinada ao mercado interno. Enquanto o açúcar, além de ser um produto da cesta básica brasileira, é um forte produto de exportações. Dessa forma, as commodities açúcar, etanol e petróleo possuem uma correlação muito grande com relação aos preços no mercado financeiro brasileiro. A correlação existente entre os preços do etanol, açúcar e petróleo leva a necessidade de estudar esta troca de informações e avaliar a direcionalidade desse fluxo de informação. Para estudar a transferência de informações nas séries de preço destas commodities utilizamos a Transfer Entropy que permite, além de medir a intensidade de acoplamento entre as séries, identificar a direcionalidade do acoplamento. Como essas commodities são altamente influenciadas pelo mercado internacional, analisamos o comportamento de suas séries temporais de preços diante da crise financeira mundial que acarretou a quebra do Banco Lehman Brothers. Dessa forma, estudamos essas commodities para os períodos antes, durante e após a Crise Subprime. Nosso principal objetivo neste estudo foi investigar séries temporais de preço de etanol, petróleo e açúcar utilizando o método Transfer Entropy. Os resultados obtidos mostram que a crise financeira afetou a relação entre os preços das commodities açúcar, etanol e petróleo. ATransfer Entropy se mostrou eficiente para quantificar o fluxo de informações entre as séries temporais de preços dessas commodities e elucidar a direcionalidade da transferência. Destacamos algumas inversões observadas na intensidade do fluxo de informações, por exemplo, entre açúcar e petróleo, nos períodos durante e após a crise o comportamento da Transfer Entropy inverteu e o sentido petróleo - açúcar se tornou maior que o outro sentido. Entre açúcar e etanol e entre petróleo e etanol também houve inversão no comportamento da transferência de informações no período durante a crise. No geral, o método detectou a alteração no comportamento dos preços ocasionada pela crise financeira. Avantagem da técnica é, além de medir a intensidade entre esses acoplamentos, indicar a direcionalidade das interações. Entre os resultados obtidos com o método Multiscale Transfer Entropy destacamos que entre o petróleo e o etanol, ao analisar as diferentes escalas de tempo, não pudemos concluir qual sentido transfere mais informação. Essa característica pode ser relacionada com as intervenções políticas que baixam o preço da gasolina artificialmente, alteram o percentual de etanol na gasolina, fazendo com que a relação entre os preços do etanol e petróleo não ocorram naturalmente.The Brazilian energy infrastructure in the transportation sector has unique characteristics, with a large participation of bioenergy. The Brazilian government obliges the addition of ethanol in gasoline and this percentage varies as a political mechanism of price stabilization, increasing or decreasing depending on the industrial capacity to produce ethanol, the price of oil. The price of sugar cane also has a role in this decision-making. The domestic market switches the destination of sugarcane to ethanol or sugar production depending on market prices. Much of the ethanol production is destined for the domestic market. While sugar, besides being a product of the Brazilian basic food basket, is a strong product of exports. Thus, sugar, ethanol and petroleum commodities have a very large price correlation in the Brazilian financial market. The correlation between the prices of ethanol, sugar and oil leads to the need to study this exchange of information and to evaluate the directionality of this flow of information. In the analysis of multivariate time series, a common subject of interest is the coupling between the variables. In order to study the transfer of information in the series of prices of these commodities we use the Transfer Entropy that allows, in addition to measuring the coupling force between the series, to identify the directionality of the coupling. As these commodities are highly influenced by the international market, we analyze the behavior of their time series of prices in the face of the global financial crisis that led to the collapse of Lehman Brothers Bank. In this way, we study these commodities for the periods before, during and after the Subprime Crisis. Our main objective in this study was to investigate time series of ethanol, oil and sugar prices using the Transfer Entropy method. The results show that the financial crisis affected the relationship between sugar, ethanol and oil commodity prices. Transfer Entropy was efficient in quantifying the flow of information between the time series of prices of these commodities and elucidating the directionality of the transfer. We highlight some inversions observed in the intensity of the flow of information, for example between sugar and oil, during the periods during and after the crisis, the behavior of Transfer Entropy reversed and the direction of oil sugar became bigger than the other direction. Between sugar and ethanol and between oil and ethanol there was also an inversion in the behavior of information transfer during the period during the crisis. Overall, the method detected the change in price behavior caused by the financial crisis. The advantage of the technique is, besides measuring the intensity between these couplings, to indicate the directionality of the interactions. Among the results obtained with the Multiscale Transfer Entropy method we highlight that between oil and ethanol, when analyzing the different time scales, we could not conclude which direction transfers more information. This feature may be related to policy interventions that lower the price of gasoline artificially, change the percentage of ethanol in gasoline, causing the relationship between ethanol and oil prices not to occur naturally.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPE

Mortalit y inequalities measured by socioeconomic indicators in Brazil: A scoping review

Our study is the first review among the references consulted so far to map the construction of composite socioeconomic indicators and their association with mortality outcomes at different geographic levels in Brazil. It was possible to address more specific research questions to analyze inequalities in mortality, reporting important evidence for public health