Desigualdades na mortalidade e a composição do índice de iniquidade em saúde em uma capital brasileira

Abstract

Differences in health outcomes among different population groups are revealed by several academic studies and government reports, and are not new. Nevertheless, the theme of social inequalities is the object of a recurrent study in the different areas of knowledge, perhaps due to the expansion of these inequalities over the years. Brazil, despite the reduction in inequalities in the last decades, still sustains one of the greatest social inequalities in the world. The creation of an index that aggregates socioeconomic and health indicators can contribute to actions that reduce or eliminate iniquities within the country. In view of this, this study proposes the creation of the Health Inequity Index (IIS) composed of health indicators - the average number of years lived and the average number of years of life lost (PYLL) - and socioeconomic indicators of income, schooling and population in conditions of poverty for the city of Natal, state of Rio Grande do Norte. Mortality variables were calculated from the mortality records of the Mortality Information System (SIM) database of the Ministry of Health and the socioeconomic variables obtained from the Demographic Census-2010, from the Brazilian Institute of Geography and Statistics (IBGE). In addition to the descriptive analyzes of mortality and socioeconomic conditions among the neighborhoods, a probabilistic linkage was made between the databases to capture the census tracts of residences with death records between 2007-2013. With the internal homogeneity of the census tracts it is possible to discriminate even better the inequality between the areas of the city. For the calculation of the index, the principal components factorial analysis was used. The index was validated through a factorial analysis in the sector sample and by the cluster analysis, whereas the Spearman correlation was used for the consistency analysis. The index data was spatially represented using the QGIS software. The results show that the difference in the average of the years lived between the neighborhoods of Natal-RN reaches 25 years, with the worst neighborhood showing comparable mortality conditions to poor countries in Africa, whereas the neighborhood with the highest average of years lived is similar to the Brazilian average. Mortality was strongly correlated with socioeconomic variables, with a significant relationship between the mean number of PYLL in non-communicable chronic diseases and the proportion of low-income households (ρ = 0.913). The Health Inequity Index presented consistency with the other models (ρ> 0.800) and may reveal areas with worse socioeconomic and health conditions located peripherally in the city, especially in the western and northern zones of the city. These data help public policy makers prioritize actions aimed at reducing or eliminating health inequities.