Methods for analytic intercategorical intersectionality in quantitative research: Discrimination as a mediator of health inequalities

Greta R. Bauer, Ayden I. Scheim

Research output: Contribution to journalArticlepeer-review

151 Scopus citations

Abstract

Rationale: Intersectionality as a theoretical framework has gained prominence in qualitative research on social inequity. Intercategorical quantitative applications have focused primarily on describing health or social inequalities across intersectional groups, coded using cross-classified categories or interaction terms. This descriptive intersectionality omits consideration of the mediating processes (e.g., discrimination) through which intersectional positions impact outcome inequalities, which offer opportunities for intervention. Objective: We argue for the importance of a quantitative analytic intersectionality. We identify methodological challenges and potential solutions in structuring studies to allow for both intersectional heterogeneity in outcomes and in the ways that processes such as discrimination may cause these outcomes for those at different intersections. Method: To incorporate both mediation and exposure-mediator interaction, we use VanderWeele's three-way decomposition methodology, adapt the interpretation for application to analytic intersectionality studies, and present a step-by-step analytic approach. Using online panel data collected from Canada and the United States in 2016 (N = 2542), we illustrate this approach with a statistical analysis of whether and to what extent observed inequalities in psychological distress across intersections of ethnoracial group and sexual or gender minority (SGM) status may be explained by past-year experiences of day-to-day discrimination, assessed using the Intersectional Discrimination Index (InDI). Results and conclusions: We describe actual and adjusted intersectional inequalities in psychological distress and decompose them to identify three component effects for each of 11 intersectional comparison groups (e.g., Indigenous SGM), versus the reference intersectional group that experienced the lowest levels of discrimination (white non-SGM). These reflect the expected inequality in outcome: 1) due to membership in the more discriminated-against group, if its members had experienced the same lower levels of discrimination as the reference intersection; 2) due to unequal levels of discrimination; and 3), due to unequal effects of discrimination. We present considerations for use and interpretation of these methods.

Original languageEnglish (US)
Pages (from-to)236-245
Number of pages10
JournalSocial Science and Medicine
Volume226
DOIs
StatePublished - Apr 2019
Externally publishedYes

Bibliographical note

Funding Information:
This research was funded by the Canadian Institutes of Health Research (CIHR, funding reference 130489 ) and Research Western. The funders played no role in study design, data collection, analysis or interpretation. Ayden Scheim was supported by a Vanier Canada Graduate Scholarship , the Pierre Elliott Trudeau Foundation , and a CIHR Fellowship . The authors wish to thank Siobhan Churchill for assistance with literature searches. We thank the following people for valuable feedback on an earlier draft: Lisa Bowleg, Siobhan Churchill, Ana Maria del Río-González, Dan Lizotte, Alex Ratzki-Leewing, Chantel Walwyn, and Guangyong Zou.

Publisher Copyright:
© 2018 The Authors

Keywords

  • Discrimination
  • Gender
  • Health equity
  • Intersectionality
  • Race
  • Research design methods
  • Social determinants of health
  • Statistics

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