All-cause mortality rates for indigenous in the states of Brazil and their (non) correlation with socioeconomic and health indicators in the years 2000 and 2010 - Arantes da Cunha, Arthur; Corona, Rodolfo Antonio; Carvalho Alves, Giovana; Tiyomi Sacata Tongu Nazima, Maira; Castilho-Martins, Emerson Augusto (O Mundo da Saúde, 2022)
In 2010, the indigenous population represented 0.2% of the Brazilian population and was mostly located in the Legal Amazon region. In Brazil, there are laws to protect the indigenous population, in addition to a National Health Care Policy for Indigenous Peoples. However, a large part of the indigenous population is considered under social and sanitary vulnerability, which are more pronounced in certain regions of the country. Therefore, this study aimed to calculate and evaluate the all-cause mortality rate in the Brazilian indigenous population and investigate correlations with socioeconomic and health indicators. This is an ecological study based on official data (2000 and 2010). The number of deaths were extracted from the Mortality Information System. Indigenous population data were extracted from Demographic Censuses of the Brazilian Institute of Geography and Statistics. The all-cause mortality rate were calculated by states and correlated, through Pearson's correlation test, with socioeconomic and health indicators extracted from the Atlas Brazil platform. In Brazil, an increase in the overall indigenous mortality rate was observed of 15.0% between 2000 and 2010. Among the regions, the Midwest had the highest rates in 2000 and 2010 (4.54 and 5.56 deaths/1,000 indigenous people, respectively). In 2000, the state with the highest all-cause mortality rate was Piauí (9.76/1,000) and in 2010 it was Mato Grosso do Sul (6.54/1,000). All-cause mortality rate did not present a significant correlation (p-value ≤0.05) with the analyzed indicators. The findings of this study indicated that the all-cause mortality rate in Brazil increased unevenly, according to regions/states, and without any correlation with the socioeconomic and health indicators analyzed.