Document Type

Article

Publication Date

2-2025

Publication Title

Journal of Racial and Ethnic Health Disparities

Abstract

South Asians are a fast-growing, heterogeneous ethnic group in the United States. However, they remain understudied in health equity research despite experiencing a high burden of cardiovascular disease. Biased assumptions, such as the model minority myth, obscure their unique experiences of discrimination—a known contributor to cardiovascular disease–related health inequities. The form and pattern of everyday discrimination among South Asians has been largely unexamined. We addressed this gap by examining the dimensionality of the everyday discrimination scale (EDS) and its potential predic- tors among South Asians. Data are from the Mediators of Atherosclerosis in South Asians Living in America (MASALA; 2010–2018), a cross-sectional community sample (N=1164, 52% male, Mage=56.73, SDage=9.41). Structural equation modeling (SEM) analysis was used to conduct confrmatory factor analyses to estimate a measurement model for the latent variable of everyday discrimination and a structural model to examine associations between hypothesized predictors and the latent everyday discrimination variable. Confrmatory factor analyses revealed that a six-item, unidimensional version of the EDS ft the data best. SEM analyses showed that everyday discrimination was socially patterned across individual-, health-, community-, and cultural characteristics. Findings highlight the importance of considering how social positionali- ties and context may shape exposure to everyday discrimination. Importantly, our results have implications for identifying South Asian individuals at an increased risk of experiencing everyday discrimination and its associated health inequities, including cardiovascular disease–related outcomes.

Keywords

Unfair treatment, Social positionality, Socio-ecological factors, South Asians, Intersectionality

DOI

https://doi.org/10.1007/s40615-025-02380-2

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Rights

Licensed to Smith College and distributed CC-BY 4.0 under the Smith College Faculty Open Access Policy.

Comments

Peer reviewed accepted manuscript.

Available for download on Sunday, February 01, 2026

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