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Review
. 2021 Nov 20:16:100977.
doi: 10.1016/j.ssmph.2021.100977. eCollection 2021 Dec.

An investigation of quantitative methods for assessing intersectionality in health research: A systematic review

Alice Guan  1 , Marilyn Thomas  1   2 , Eric Vittinghoff  1 , Lisa Bowleg  3 , Christina Mangurian  1   2   4 , Paul Wesson  1
Affiliations
Review

An investigation of quantitative methods for assessing intersectionality in health research: A systematic review

Alice Guan et al. SSM Popul Health. .

Abstract

Intersectionality is a theoretical framework that investigates how interlocking systems of power and oppression at the societal level influence the lived experiences of historically and socially marginalized groups. Currently, there are no consistent or widely adopted quantitative methods to investigate research questions informed by intersectionality theory. The objective of this systematic review is to describe the current landscape of quantitative methods used to assess intersectionality and to provide recommendations on analytic best practices for future research. We searched PubMed, EMBASE, and the Web of Science in December 2019 to identify studies using analytic quantitative intersectionality approaches published up to December 2019 (PROSPERO CRD42020162686). To be included in the study, articles had to: (1) be empirical research, (2) use a quantitative statistical method, (3) be published in English, and (4) incorporate intersectionality. Our initial search yielded 1889 articles. After screening by title/abstract, methods, and full text review, our final analytic sample included 153 papers. Eight unique classes of quantitative methods were identified, with the majority of studies employing regression with an interaction term. We additionally identified several methods which appear to be at odds with the key tenets of intersectionality. As quantitative intersectionality continues to expand, careful attention is needed to avoid the dilution of the core tenets. Specifically, emphasis on social power is needed as methods continue to be adopted and developed. Additionally, clear explanation of the selection of statistical approaches is needed and, when using regression with interaction terms, researchers should opt for use of the additive scale. Finally, use of methods that are potentially at odds with the tenets of intersectionality should be avoided.

Keywords: Epidemiology; Intersectionality; Research methods; Statistics; Systematic review.

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Conflict of interest statement

The authors have no conflicts of interest to declare.

Figures

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Fig. 1
Study flow diagram for systematic review process.
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