The enduring effects of racism on health: Understanding direct and indirect effects over time.


Journal

SSM - population health
ISSN: 2352-8273
Titre abrégé: SSM Popul Health
Pays: England
ID NLM: 101678841

Informations de publication

Date de publication:
Sep 2022
Historique:
received: 05 07 2022
revised: 27 07 2022
accepted: 22 08 2022
entrez: 12 9 2022
pubmed: 13 9 2022
medline: 13 9 2022
Statut: epublish

Résumé

Experiences of racism and racial discrimination are associated with poorer mental and physical health outcomes for people from minoritised ethnic groups. One mechanism by which racism leads to poor health is through reduced socio-economic resources, but the evidence documenting the direct and indirect effects of racism on health via socio-economic inequality over time is under-developed. The central aims of this paper are to better understand how racism affects health over time, by age, and via the key mechanism of socio-economic inequality. This paper analyses large-scale, nationally representative data from the UK Household Longitudinal Study (Understanding Society) 2009-2019. Findings from longitudinal structural equation models clearly indicate the enduring effects of racism on health, which operate over time both directly and indirectly through lower income and poorer prior health. Repeated exposure to racism severely and negatively impacts the health of people from minoritised ethnic groups. These findings make an important contribution to the existing evidence base, demonstrating the enduring effects of racism on health over time and across age groups.

Identifiants

pubmed: 36091297
doi: 10.1016/j.ssmph.2022.101217
pii: S2352-8273(22)00196-3
pmc: PMC9450139
doi:

Types de publication

Journal Article

Langues

eng

Pagination

101217

Informations de copyright

© 2022 Published by Elsevier Ltd.

Déclaration de conflit d'intérêts

None.

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Auteurs

Sarah Stopforth (S)

King's College London, UK.

Dharmi Kapadia (D)

University of Manchester, UK.

James Nazroo (J)

University of Manchester, UK.

Laia Bécares (L)

King's College London, UK.

Classifications MeSH