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April 16, 2026Journal of Racial and Ethnic Health Disparities0 citationsOpen Access

Developing an Intergenerational Model of Structural Racism Exposure among Women in Black Families in South Carolina, 1989–2020

ARAnnie RoYXYanmei XieWLWoo Jung Lee

Key Points

  • The research aims to develop an intergenerational model to measure structural racism exposure among Black families in South Carolina from 1989 to 2020.
  • Developed a multigenerational dataset linking birth certificates along the maternal line from 1989–2020.
  • Applied a lifecourse perspective to identify indicators of structural racism across generations.
  • Employed confirmatory factor analysis (CFA) to assess latent variables in structural racism.
  • Conducted measurement invariance testing to evaluate consistency of indicators across generations.
  • The model showed good fit for criminal justice, economic opportunity, educational resources, and residential segregation domains.
  • Political participation was excluded due to poor fit in the model.
  • Significant generational shifts were observed, with economic opportunity indicators relevant for mothers but not grandmothers.
  • The study found four key dimensions of structural racism affecting Black families in South Carolina.

Abstract

Structural racism is a key driver of health inequities among Black Americans, yet its measurement remains inconsistent. This study introduces a multigenerational model of exposure to structural racism across five domains—criminal justice, economic opportunity, educational resources, political participation, and residential segregation—among Black women in South Carolina from 1989 to 2020. It addresses key gaps by applying a lifecourse perspective, identifying consistent indicators over time and space, and using latent variables for assessment across two generations. We developed a multigenerational dataset by linking South Carolina birth certificates along the maternal line (1989–2020), focusing on first births among Black mothers with complete structural racism data (n = 75,088 births; 37,544 family trees). Twenty-two indicators were drawn from national and state sources, merged at the county level. Confirmatory factor analysis (CFA) was used to construct latent variables representing structural racism. Measurement invariance testing assessed consistency across generations. The model showed good fit for four domains—criminal justice, economic opportunity, educational resources, and residential segregation. Political participation was excluded due to poor fit. Economic opportunity indicators were significant for mothers but not grandmothers, highlighting generational shifts in indicator relevance. Four key dimensions of structural racism were observed across two generations in Black families in South Carolina, though indicator relevance varied. These findings emphasize the importance of context-specific, temporally aware measures. Future research should link these models to health outcomes to deepen understanding of how structural racism shapes health over time.

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Cite This Study

Ro et al. (2026) studied this question.

synapsesocial.com/papers/69e07e3b2f7e8953b7cbf49fhttps://doi.org/10.1007/s40615-026-02879-2
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Measuring Structural Racism to Advance Health Equity: A Scoping Review of Quantitative Approaches2026
  2. 2Abstract A109: The development of racial and ethnic-specific composite measures of structural racism for cancer inequities research: The Multiethnic Cohort Study2025
  3. 3Toward the Development of a Multilevel Measure of Structural Racism: Theory and Methods2026
  4. 4Understanding the Structural, Social, and Interpersonal Mechanisms of Racism in Maternal Health Care Experiences in Southeastern United States: A Conceptual Framework2026
  5. 5Judge Me Not: Exploring Black Mothers’ Perceptions of Maternal Health Care Services and Structural Racism in South Carolina2026