Inequalities in infant mortality in Brazil at subnational levels in Brazil, 1990 to 2015.

BACKGROUND: In this study, infant mortality rate (IMR) inequalities are analyzed from 1990 to 2015 in different geographic scales. METHODS: The Ministry of Health (MoH) IMR estimates by Federative Units (FU) were compared to those obtained by the Global Burden of Disease (GBD) group. In order to measure the inequalities of the IMR by FU, the ratios from highest to lowest from 1990 to 2015 were calculated. Maps were elaborated in 2000, 2010, and 2015 at the municipality level. To analyze the effect of income, IMR inequalities by GDP per capita were analyzed, comparing Brazil and the FU to other same-income level countries in 2015, and the IMR municipal estimates were analyzed by income deciles, in 2000 and 2010. RESULTS: IMR decreased from 47.1 to 13.4 per 1000 live births (LB) from 1990 to 2015, with an annual decrease rate of 4.9%. The decline was less pronounced for the early neonatal annual rate (3.5%). The Northeast region showed the most significant annual decline (6.2%). The IMR estimates carried out by the GBD were about 20% higher than those obtained by the MoH, but in terms of their inequalities, the ratio from the highest to the lowest IMR among the 27 FU decreased from 4 to 2, for both methods. The percentage of municipalities with IMR higher than 40 per 1000 LB decreased from 23% to 2%, between 2000 and 2015. Comparing the IMR distribution by income deciles, all inequality measures of the IMR decreased markedly from 2000 to 2010. CONCLUSION: The results showed a marked decrease in the IMR inequalities in Brazil, regardless of the geographic breakdown and the calculation method. Despite clear signs of progress in curbing infant mortality, there are still challenges in reducing its level, such as the concentration of deaths in the early neonatal period, and the specific increases of post neonatal mortality in 2016, after the recent cuts in social investments.

GeoSES: A socioeconomic index for health and social research in Brazil.

The individual's socioeconomic conditions are the most relevant to predict the quality of someone's health. However, such information is not usually found in medical records, making studies in the area difficult. Therefore, it is common to use composite indices that characterize a region socioeconomically, such as the Human Development Index (HDI). The main advantage of the HDI is its understanding and adoption on a global scale. However, its applicability is limited for health studies since its longevity dimension presents mathematical redundancy in regression models. Here we introduce the GeoSES, a composite index that summarizes the main dimensions of the Brazilian socioeconomic context for research purposes. We created the index from the 2010 Brazilian Census, whose variables selection was guided by theoretical references for health studies. The proposed index incorporates seven socioeconomic dimensions: education, mobility, poverty, wealth, income, segregation, and deprivation of resources and services. We developed the GeoSES using Principal Component Analysis and evaluated its construct, content, and applicability. GeoSES is defined at three scales: national (GeoSES-BR), Federative Unit (GeoSES-FU), and intra-municipal (GeoSES-IM). GeoSES-BR dimensions showed a good association with HDI-M (correlation above 0.85). The model with the poverty dimension best explained the relative risk of avoidable cause mortality in Brazil. In the intra-municipal scale, the model with GeoSES-IM was the one that best explained the relative risk of mortality from circulatory system diseases. By applying spatial regressions, we demonstrated that GeoSES shows significant explanatory potential in the studied scales, being a compelling complement for future researches in public health.