ArticleSN social sciences2022
Inequality and income segregation in Brazilian cities: a nationwide analysis.
Article in SN social sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed.
- Machine Learning for Predicting Colorectal Cancer-Specific Mortality: The Role of Socioeconomic Inequalities in Public Policy.ANZ journal of surgery · 2026Article
- Article
- Co-production of informal settlement health: a community based participatory research program for building healthy communities in urban informal settlements of Salvador, Brazil.Frontiers in public health · 2026Article
- The association between residential segregation and stillbirths in Brazil-a cross-sectional study.BMC pregnancy and childbirth · 2025Article
- Associations of municipality-level income and racial segregation with individual-level tuberculosis treatment outcomes in Brazil: a nationwide cohort study (2010-2019).Journal of epidemiology and community health · 2025Article
- What Is There to Buy? An Analysis of the Food Environment in Public and Private Schools in the Federal District.International journal of environmental research and public health · 2025Article
- Cardiovascular diseaseLancet regional health. Americas · 2025Article
- Socioeconomic Urban Environment in Latin America: Towards a Typology of Cities.Sustainability · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Residential segregation has brought significant challenges to cities worldwide and has important implications for health. This study aimed to assess income segregation in the 152 largest Brazilian cities in the SALURBAL Project. We identify specific socioeconomic characteristics related to residential segregation by income using the Brazilian demographic census of 2010 and calculated the income dissimilarity index (IDI) at the census tract level for each city, subsequently comparing it with Gini and other local socioeconomic variables. We evaluated our results' robustness using a bootstrap correction to the IDI to examine the consequences of using different income cut-offs in substantial urban and regional inequalities. We identified a two minimum wage cut-off as the most appropriate. We found little evidence of upward bias in the calculation of the IDI regardless of the cut-off used. Among the ten most segregated cities, nine are in the Northeast region, with Brazil's highest income inequality and poverty. Our results indicate that the Gini index and poverty are the main variables associated with residential segregation. Supplementary Information: The online version contains supplementary material available at 10.1007/s43545-022-00491-9.
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