English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Recent literature reviews have shown that studies analyzing racial/ethnic disparities in Brazil are still scarce. Multilevel approaches are necessary, since race is a socially constructed concept and can vary by area of residence. The analysis included 2,697 individuals from 145 Brazilian municipalities (counties), classified by race (white, black, or mixed). Multilevel models were fitted using Bayesian inference with Markov Chain Monte Carlo methods. After including demographic, socioeconomic, and health access variables, black and mixed-race individuals showed higher odds of negative self-rated health (OR = 1.71; 95%CI: 1.24; 2.37 and OR = 1.37; 95%CI: 1.10; 1.71, respectively). Characteristics of the area of residence did not significantly affect the association between race and self-rated health. Racial/ethnic disparities lost their statistical significance after re-categorization of the dependent variable. The results indicate that racial/ ethnic disparities in health in Brazil may be deeper and more complex than expected.

Disparidades étnico-raciais em saúde autoavaliada: análise multinível de 2.697 indivíduos residentes em 145 municípios brasileiros