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Measuring Perceived Discrimination and Its Consequences for Latino Health.

Giovani Burgos1, Alex Trillo2

  • 1Department of Sociology, College of Arts and Sciences, Adelphi University, Garden City, NY 11530, USA.

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Summary

Discrimination negatively impacts health, but research often overlooks Latino ethnic variations. A refined measurement of discrimination reveals stronger links to health outcomes, highlighting the need to disaggregate ethnic groups.

Keywords:
CES-DLatinoschronic healthdepressiondiscriminationethnicityracismstructural equation modeling

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Area of Science:

  • Health Disparities
  • Sociology of Health
  • Psychological Measurement

Background:

  • Discrimination is a known social determinant of health.
  • Existing research often uses unidimensional scales, masking ethnic differences and the multidimensional nature of discrimination.
  • The Latino population is diverse, yet often treated as a monolithic group in research.

Purpose of the Study:

  • To examine ethnic differences in perceived discrimination among Latino groups using the Everyday Discrimination Scale (EDS).
  • To assess the fit and dimensionality of the EDS across different Latino ethnic groups via confirmatory factor analysis.
  • To evaluate how different scaling methods for discrimination influence its relationship with depression and chronic health conditions.

Main Methods:

  • Utilized data from the National Latino and Asian American Study.
  • Conducted confirmatory factor analysis (CFA) on the EDS for distinct Latino ethnic groups.
  • Compared the association between discrimination (using various scaling approaches) and health outcomes (depression, chronic conditions).

Main Results:

  • Significant ethnic variations in perceived discrimination were found among Latino groups.
  • A second-order factor model, comprising subtle and overt discrimination, demonstrated good fit across all examined Latino ethnic groups.
  • The association between discrimination and health was stronger when discrimination was measured using the second-order factor model.

Conclusions:

  • Alternative scaling approaches, beyond traditional alpha scales, are more appropriate for measuring discrimination.
  • Precise measurement of discrimination, acknowledging its multidimensionality, is crucial for accurately assessing its health impacts.
  • Disaggregating panethnic categories like "Latino" is essential for understanding ethnic stratification and its influence on health.