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Intersectionality-based quantitative health research and sex/gender sensitivity: a scoping review
Emily Mena1,2, Gabriele Bolte3,4,
1Institute of Public Health and Nursing Research, Department of Social Epidemiology, Faculty of Human and Health Sciences, University of Bremen, Grazer Straße 4, 28359, Bremen, Germany. e.mena@uni-bremen.de.
International Journal for Equity in Health
|December 23, 2019
Summary
Intersectionality in health research primarily examines sex/gender and race/ethnicity in U.S. studies. Integrating modifiable factors can enhance quantitative analysis and sex/gender sensitivity in health disparities research.
Area of Science:
- Public Health and Epidemiology
- Sociology of Health
- Quantitative Health Research Methods
Background:
- Intersectionality framework gaining traction in quantitative health research.
- Originates from Black feminist scholarship advocating for integrated analysis of sex/gender and race/ethnicity.
- Crucial for understanding complex health disparities beyond single social dimensions.
Purpose of the Study:
- To conduct a scoping review on intersectionality in epidemiological research, focusing on sex/gender.
- Assess how different social dimensions are incorporated in multivariable and multivariate analyses.
- Evaluate sex/gender sensitivity in operationalization and theoretical application within studies.
Main Methods:
- Literature review following PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines.
- Searched PubMed for studies in diabetes, smoking, and physical activity research.
- Compared operationalization of sex/gender, theoretical frameworks, and analytical approaches for intersectional analyses.
Main Results:
- Intersectionality analyses predominantly in U.S. studies, focusing on sex/gender and race/ethnicity intersections.
- Commonly used as subgrouping variables or in interaction terms in regression analyses.
- Sex/gender operationalized binarily; solution-linked variables rarely incorporated, limiting nuanced analysis.
Conclusions:
- Current intersectionality analyses in health research often use binary sex/gender and focus on race/ethnicity.
- Limited use of advanced interaction methods and solution-linked variables restricts depth of analysis.
- Integrating modifiable, solution-linked variables can improve sex/gender sensitivity in quantitative health research.
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