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Transcending the Male–Female Binary in Biomedical Research: Constellations, Heterogeneity, and Mechanism When Considering Sex and Gender

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  • Stacey A. Ritz

    (Department of Pathology & Molecular Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON L8S 4K1, Canada)

  • Lorraine Greaves

    (Centre of Excellence for Women’s Health, Vancouver, BC V6H 3N1, Canada
    School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada)

Abstract

Accounting for the influences of sex- and gender-related factors on health is one of the most interesting and important challenges in contemporary health research. In biomedical research, models, experimental designs, and statistical analyses create particular challenges in attempting to incorporate the complex, dynamic, and context-dependent constructs of sex and gender. Here, we offer conceptual elaborations of the constructs of sex and gender and discuss their application in biomedical research, including a more mechanism-oriented and context-driven approach to experimental design integrating sex and gender. We highlight how practices of data visualization, statistical analysis, and rhetoric can be valuable tools in expanding the operationalization of sex and gender biomedical science and reducing reliance on a male–female binary approach.

Suggested Citation

  • Stacey A. Ritz & Lorraine Greaves, 2022. "Transcending the Male–Female Binary in Biomedical Research: Constellations, Heterogeneity, and Mechanism When Considering Sex and Gender," IJERPH, MDPI, vol. 19(7), pages 1-11, March.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:7:p:4083-:d:782888
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    References listed on IDEAS

    as
    1. Lorraine Greaves & Stacey A. Ritz, 2022. "Sex, Gender and Health: Mapping the Landscape of Research and Policy," IJERPH, MDPI, vol. 19(5), pages 1-13, February.
    2. Tiffany Jones, 2018. "Intersex Studies: A Systematic Review of International Health Literature," SAGE Open, , vol. 8(2), pages 21582440177, May.
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    Cited by:

    1. Valérie Lederer & Karen Messing & Hélène Sultan-Taïeb, 2022. "How Can Quantitative Analysis Be Used to Improve Occupational Health without Reinforcing Social Inequalities? An Examination of Statistical Methods," IJERPH, MDPI, vol. 20(1), pages 1-19, December.

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