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Disparities at the intersection of marginalized groups.

John W Jackson1, David R Williams2, Tyler J VanderWeele3,4

  • 1Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, USA. john.jackson@mail.harvard.edu.

Social Psychiatry and Psychiatric Epidemiology
|August 18, 2016
PubMed
Summary

This study introduces joint disparity analysis to understand how multiple social inequalities, like race and socioeconomic status (SES), impact mental health outcomes. Findings reveal significant disparities, highlighting the varying contributions of race, SES, and their intersection.

Keywords:
Attributable proportionDecompositionDisparitiesExcess intersectional disparityHeterogeneity of effectsInteractionIntersectionalityJoint disparityRatio of observed to expected joint effectsRelative excess risk for interactionSynergy index

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Area of Science:

  • Social Epidemiology
  • Health Disparities Research
  • Quantitative Social Science

Background:

  • Mental health disparities are prevalent across race/ethnicity, socioeconomic status (SES), and gender.
  • Traditional research often examines single dimensions of inequality, overlooking intersectional impacts.
  • There's a growing need for quantitative methods to study individuals facing multiple forms of marginalization.

Purpose of the Study:

  • To introduce and evaluate the concept of 'joint disparity' for analyzing intersecting social inequalities.
  • To illuminate outcome patterns for multiply marginalized social groups using a quantitative approach.
  • To compare the insights from joint disparity analysis with traditional measures of additive interaction.

Main Methods:

  • Utilized data from the National Longitudinal Survey of Youth cohort.
  • Examined disparities in unemployment, wages, and incarceration among young men.
  • Compared outcomes for Black men with low early-life SES against White men with high early-life SES.
  • Applied joint disparity analysis and compared it with additive interaction measures.

Main Results:

  • Observed significant disparities across all examined outcomes (unemployment, wages, incarceration).
  • Demonstrated that the influence of race, SES, and their intersection on these outcomes varies.
  • The joint disparity approach provided unique insights into patterned outcomes for multiply marginalized groups.

Conclusions:

  • Joint disparity analysis offers a valuable quantitative framework for understanding complex health disparities.
  • The interplay of race, SES, and their intersection significantly shapes mental health-related outcomes.
  • Future research should adopt intersectional quantitative methods to fully grasp health inequality.