IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i3p2220-d1047480.html
   My bibliography  Save this article

Intersectionality-Informed Sex/Gender-Sensitivity in Public Health Monitoring and Reporting (PHMR): A Case Study Assessing Stratification on an “Intersectional Gender-Score”

Author

Listed:
  • Emily Mena

    (Department of Social Epidemiology, Institute of Public Health and Nursing Research, Faculty of Human and Health Sciences, University of Bremen, 28359 Bremen, Germany
    Health Sciences Bremen, University of Bremen, 28359 Bremen, Germany)

  • Katharina Stahlmann

    (Department of Social Epidemiology, Institute of Public Health and Nursing Research, Faculty of Human and Health Sciences, University of Bremen, 28359 Bremen, Germany
    Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany)

  • Klaus Telkmann

    (Department of Social Epidemiology, Institute of Public Health and Nursing Research, Faculty of Human and Health Sciences, University of Bremen, 28359 Bremen, Germany
    Health Sciences Bremen, University of Bremen, 28359 Bremen, Germany)

  • Gabriele Bolte

    (Department of Social Epidemiology, Institute of Public Health and Nursing Research, Faculty of Human and Health Sciences, University of Bremen, 28359 Bremen, Germany
    Health Sciences Bremen, University of Bremen, 28359 Bremen, Germany)

  • on behalf of the AdvanceGender Study Group

    (Advance Gender Study Group are listed in acknowledgments.)

Abstract

To date, PHMR has often relied on male/female stratification, but rarely considers the complex, intersecting social positions of men and women in describing the prevalence of health and disease. Stratification on an Intersectional Gender-Score (IG-Score), which is based on a variety of social covariables, would allow comparison of the prevalence of individuals who share the same complex intersectional profile (IG-Score). The cross-sectional case study was based on the German Socio-Economic Panel 2017 (n = 23,269 age 18+). After stratification, covariable-balance within the total sample and IG-Score-subgroups was assessed by standardized mean differences. Prevalence of self-rated health, mental distress, depression and hypertension was compared in men and women. In the IG-Score-subgroup with highest proportion of males and lowest probability of falling into the ‘woman’-category, most individuals were in full-time employment. The IG-Score-subgroup with highest proportion of women and highest probability of falling into the ‘woman’-category was characterized by part-time/occasional employment, housewife/-husband, and maternity/parental leave. Gender differences in prevalence of health indicators remained within the male-dominated IG-Score-subgroup, whereas the same prevalence of depression and self-rated health was observed for men and women constituting the female-dominated IG-Score-subgroup. These results might indicate that sex/gender differences of depression and self-rated health could be interpreted against the background of gender associated processes. In summary, the proposed procedure allows comparison of prevalence of health indicators conditional on men and women sharing the same complex intersectional profile.

Suggested Citation

  • Emily Mena & Katharina Stahlmann & Klaus Telkmann & Gabriele Bolte & on behalf of the AdvanceGender Study Group, 2023. "Intersectionality-Informed Sex/Gender-Sensitivity in Public Health Monitoring and Reporting (PHMR): A Case Study Assessing Stratification on an “Intersectional Gender-Score”," IJERPH, MDPI, vol. 20(3), pages 1-15, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:3:p:2220-:d:1047480
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/3/2220/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/20/3/2220/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    2. Friedrich Scheller, 2011. "Bestimmung der Herkunftsnationen von Teilnehmern des Sozio-oekonomischen Panels (SOEP) mit Migrationshintergrund," SOEPpapers on Multidisciplinary Panel Data Research 407, DIW Berlin, The German Socio-Economic Panel (SOEP).
    3. Scheim, Ayden I. & Bauer, Greta R., 2019. "The Intersectional Discrimination Index: Development and validation of measures of self-reported enacted and anticipated discrimination for intercategorical analysis," Social Science & Medicine, Elsevier, vol. 226(C), pages 225-235.
    4. Bauer, Greta R., 2014. "Incorporating intersectionality theory into population health research methodology: Challenges and the potential to advance health equity," Social Science & Medicine, Elsevier, vol. 110(C), pages 10-17.
    5. Goebel Jan & Grabka Markus M. & Liebig Stefan & Kroh Martin & Richter David & Schröder Carsten & Schupp Jürgen, 2019. "The German Socio-Economic Panel (SOEP)," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(2), pages 345-360, April.
    6. Daniele Bottigliengo & Giulia Lorenzoni & Honoria Ocagli & Matteo Martinato & Paola Berchialla & Dario Gregori, 2021. "Propensity Score Analysis with Partially Observed Baseline Covariates: A Practical Comparison of Methods for Handling Missing Data," IJERPH, MDPI, vol. 18(13), pages 1-17, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sabine Zinn & Michael Bayer, 2021. "Time Spent on School-Related Activities at Home during the Pandemic: A Longitudinal Analysis of Social Group Inequality among Secondary School Students," SOEPpapers on Multidisciplinary Panel Data Research 1132, DIW Berlin, The German Socio-Economic Panel (SOEP).
    2. Katja Möhring & Sabine Zinn & Ulrike Ehrlich, 2023. "Family care during the first COVID-19 lockdown in Germany: longitudinal evidence on consequences for the well-being of caregivers," European Journal of Ageing, Springer, vol. 20(1), pages 1-11, December.
    3. Kline, Nolan, 2022. "Syndemic statuses: Intersectionality and mobilizing for LGBTQ+ Latinx health equity after the Pulse shooting," Social Science & Medicine, Elsevier, vol. 295(C).
    4. Harari, Lexi & Lee, Chioun, 2021. "Intersectionality in quantitative health disparities research: A systematic review of challenges and limitations in empirical studies," Social Science & Medicine, Elsevier, vol. 277(C).
    5. Noémi Kreif & Richard Grieve & Iván Díaz & David Harrison, 2015. "Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1213-1228, September.
    6. Aksoy, Cevat Giray & Poutvaara, Panu & Schikora, Felicitas, 2023. "First time around: Local conditions and multi-dimensional integration of refugees," Journal of Urban Economics, Elsevier, vol. 137(C).
    7. Abhilash Bandam & Eedris Busari & Chloi Syranidou & Jochen Linssen & Detlef Stolten, 2022. "Classification of Building Types in Germany: A Data-Driven Modeling Approach," Data, MDPI, vol. 7(4), pages 1-23, April.
    8. Boonstra Philip S. & Little Roderick J.A. & West Brady T. & Andridge Rebecca R. & Alvarado-Leiton Fernanda, 2021. "A Simulation Study of Diagnostics for Selection Bias," Journal of Official Statistics, Sciendo, vol. 37(3), pages 751-769, September.
    9. Daniel Demant & Oscar Oviedo-Trespalacios & Julie-Anne Carroll & Jason A. Ferris & Larissa Maier & Monica J. Barratt & Adam R. Winstock, 2018. "Do people with intersecting identities report more high-risk alcohol use and lifetime substance use?," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 63(5), pages 621-630, June.
    10. Alvarez, Camila H. & Evans, Clare Rosenfeld, 2021. "Intersectional environmental justice and population health inequalities: A novel approach," Social Science & Medicine, Elsevier, vol. 269(C).
    11. Silvia Loi & Peng Li & Mikko Myrskylä, 2022. "At the intersection of adverse life course pathways: the effects on health by nativity," MPIDR Working Papers WP-2022-018, Max Planck Institute for Demographic Research, Rostock, Germany.
    12. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    13. Liangyuan Hu & Lihua Li, 2022. "Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series," IJERPH, MDPI, vol. 19(23), pages 1-13, December.
    14. Norah Alyabs & Sy Han Chiou, 2022. "The Missing Indicator Approach for Accelerated Failure Time Model with Covariates Subject to Limits of Detection," Stats, MDPI, vol. 5(2), pages 1-13, May.
    15. Feldkircher, Martin, 2014. "The determinants of vulnerability to the global financial crisis 2008 to 2009: Credit growth and other sources of risk," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 19-49.
    16. Panarello, Demetrio, 2021. "Economic insecurity, conservatism, and the crisis of environmentalism: 30 years of evidence," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    17. Ida Kubiszewski & Kenneth Mulder & Diane Jarvis & Robert Costanza, 2022. "Toward better measurement of sustainable development and wellbeing: A small number of SDG indicators reliably predict life satisfaction," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 139-148, February.
    18. Georges Steffgen & Philipp E. Sischka & Martha Fernandez de Henestrosa, 2020. "The Quality of Work Index and the Quality of Employment Index: A Multidimensional Approach of Job Quality and Its Links to Well-Being at Work," IJERPH, MDPI, vol. 17(21), pages 1-31, October.
    19. Layland, Eric K. & Maggs, Jennifer L. & Kipke, Michele D. & Bray, Bethany C., 2022. "Intersecting racism and homonegativism among sexual minority men of color: Latent class analysis of multidimensional stigma with subgroup differences in health and sociostructural burdens," Social Science & Medicine, Elsevier, vol. 293(C).
    20. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:20:y:2023:i:3:p:2220-:d:1047480. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.