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Socioeconomic and racial/ethnic inequalities in depression prevalence and the treatment gap in Brazil: A decomposition analysis

Depression is a major global health burden and there are stark socioeconomic inequalities in both the prevalence of depression and access to treatment for depression. In Brazil, racial/ethnic inequalities are of particular concern, but the factors contributing to these inequalities remain mostly unk...

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Autores principales: Mrejen, Matías, Hone, Thomas, Rocha, Rudi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9587003/
https://www.ncbi.nlm.nih.gov/pubmed/36281244
http://dx.doi.org/10.1016/j.ssmph.2022.101266
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author Mrejen, Matías
Hone, Thomas
Rocha, Rudi
author_facet Mrejen, Matías
Hone, Thomas
Rocha, Rudi
author_sort Mrejen, Matías
collection PubMed
description Depression is a major global health burden and there are stark socioeconomic inequalities in both the prevalence of depression and access to treatment for depression. In Brazil, racial/ethnic inequalities are of particular concern, but the factors contributing to these inequalities remain mostly unknown. This paper firstly explores determinants of depression and the treatment gap (i.e., untreated afflicted individuals) in Brazil and identifies if socio-economic and health system factors explain changes over time. Secondly, it analyses income and racial/ethnic inequalities in depression and the treatment gap and identifies factors explaining inequalities through decomposition methods. Data from two waves (2013 and 2019) of a representative household-based survey are used. In 2019, 10.8% of adults were depressed, but over 70% of depressed adults did not receive care. Black or brown/mixed Brazilians were more likely to have untreated depression, and region of residence was the most important determinant of these racial/ethnic inequalities. Notably, 44.6% of the difference in the treatment gap between white individuals and black and brown/mixed individuals was not explained by differences in observables, which could potentially be due to discrimination or difficulties in accessing treatment due to other non-observable characteristics. Employment, age, exposure to violence and physical activity are the main contributing factors to income inequalities in depression. These results suggest that policies aimed at improving the levels of exposure of lower-income individuals to risk factors may positively impact mental health and mental health inequalities, while addressing inequalities in service provision and resourcing for mental health and tackling barriers to access stemming from discrimination are essential to bridge the treatment gap equitably.
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spelling pubmed-95870032022-10-23 Socioeconomic and racial/ethnic inequalities in depression prevalence and the treatment gap in Brazil: A decomposition analysis Mrejen, Matías Hone, Thomas Rocha, Rudi SSM Popul Health Regular Article Depression is a major global health burden and there are stark socioeconomic inequalities in both the prevalence of depression and access to treatment for depression. In Brazil, racial/ethnic inequalities are of particular concern, but the factors contributing to these inequalities remain mostly unknown. This paper firstly explores determinants of depression and the treatment gap (i.e., untreated afflicted individuals) in Brazil and identifies if socio-economic and health system factors explain changes over time. Secondly, it analyses income and racial/ethnic inequalities in depression and the treatment gap and identifies factors explaining inequalities through decomposition methods. Data from two waves (2013 and 2019) of a representative household-based survey are used. In 2019, 10.8% of adults were depressed, but over 70% of depressed adults did not receive care. Black or brown/mixed Brazilians were more likely to have untreated depression, and region of residence was the most important determinant of these racial/ethnic inequalities. Notably, 44.6% of the difference in the treatment gap between white individuals and black and brown/mixed individuals was not explained by differences in observables, which could potentially be due to discrimination or difficulties in accessing treatment due to other non-observable characteristics. Employment, age, exposure to violence and physical activity are the main contributing factors to income inequalities in depression. These results suggest that policies aimed at improving the levels of exposure of lower-income individuals to risk factors may positively impact mental health and mental health inequalities, while addressing inequalities in service provision and resourcing for mental health and tackling barriers to access stemming from discrimination are essential to bridge the treatment gap equitably. Elsevier 2022-10-11 /pmc/articles/PMC9587003/ /pubmed/36281244 http://dx.doi.org/10.1016/j.ssmph.2022.101266 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Regular Article
Mrejen, Matías
Hone, Thomas
Rocha, Rudi
Socioeconomic and racial/ethnic inequalities in depression prevalence and the treatment gap in Brazil: A decomposition analysis
title Socioeconomic and racial/ethnic inequalities in depression prevalence and the treatment gap in Brazil: A decomposition analysis
title_full Socioeconomic and racial/ethnic inequalities in depression prevalence and the treatment gap in Brazil: A decomposition analysis
title_fullStr Socioeconomic and racial/ethnic inequalities in depression prevalence and the treatment gap in Brazil: A decomposition analysis
title_full_unstemmed Socioeconomic and racial/ethnic inequalities in depression prevalence and the treatment gap in Brazil: A decomposition analysis
title_short Socioeconomic and racial/ethnic inequalities in depression prevalence and the treatment gap in Brazil: A decomposition analysis
title_sort socioeconomic and racial/ethnic inequalities in depression prevalence and the treatment gap in brazil: a decomposition analysis
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9587003/
https://www.ncbi.nlm.nih.gov/pubmed/36281244
http://dx.doi.org/10.1016/j.ssmph.2022.101266
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