Evidence map›Paper›PMID 40420085›Full record

ArticleInternational journal for equity in health2025

What can we learn from an intersectionality-informed description of study participants? Results from the German National Cohort.

Philipp Jaehn, Stefan Rach, Gabriele Bolte, Rafael Mikolajczyk, Sibille Merz, Paula Sofia Herrera-Espejel, Tilman Brand, Amand Führer, Klaus Berger, Henning Teismann and 29 more

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Article in International journal for equity in health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

39 authors.

Philipp JaehnInstitute of Social Medicine and Epidemiology, Brandenburg Medical School Theodor Fontane, Hochstraße 15, Brandenburg an der Havel, 14770, Germany. philipp.jaehn@mhb-fontane.de.
Stefan RachLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Gabriele BolteDepartment of Social Epidemiology, Institute of Public Health and Nursing Research, University of Bremen, Bremen, Germany.
Rafael MikolajczykInstitute for Medical Epidemiology, Biometrics and Informatics, Martin Luther University Halle-Wittenberg, Halle, Germany.
Sibille MerzInstitute of Social Medicine and Epidemiology, Brandenburg Medical School Theodor Fontane, Hochstraße 15, Brandenburg an der Havel, 14770, Germany.
Paula Sofia Herrera-EspejelLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Tilman BrandLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Amand FührerInstitute for Medical Epidemiology, Biometrics and Informatics, Martin Luther University Halle-Wittenberg, Halle, Germany.
Klaus BergerInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.
Henning TeismannInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.
Barbara BohnNAKO e.V., Heidelberg, Germany.
Lena Koch-GallenkampDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Hermann BrennerDivision of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Carolina J Klett-TammenDepartment for Epidemiology, Helmholtz Centre for Infection Research, Brunswick, Germany.
Stefanie CastellDepartment for Epidemiology, Helmholtz Centre for Infection Research, Brunswick, Germany.
Nina EbertInstitute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
Carina EmmelInstitute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
Börge SchmidtInstitute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
Sylvia GastellNAKO Study Center, German Institute of Human Nutrition Potsdam-Rehbruecke, Potsdam, Germany.
Matthias B SchulzeDepartment of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Potsdam, Germany.
Nadia ObiInstitute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Volker HarthInstitute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Bernd HolleczekSaarland Cancer Registry, Saarbrücken, Germany.
Stefanie JaskulskiInstitute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
Verena KatzkeDivision of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Rudolf KaaksDivision of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Stefan N WillichInstitute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Thomas KeilInstitute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Andrea WeberInstitute for Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany.
Michael LeitzmannInstitute for Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany.
Kerstin WirknerLeipzig Research Centre for Civilization Diseases (LIFE), University of Leipzig, Leipzig, Germany.
Claudia Meinke-FranzeInstitute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.
Sabine SchipfInstitute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.
Tamara SchikowskiIUF - Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany.
Alexandra SchneiderInstitute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
S Claire SlesinskiInstitute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
Ilais Moreno-VelásquezMolecular Epidemiology Research Group, Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany.
Tobias PischonMolecular Epidemiology Research Group, Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany.
Christine HolmbergInstitute of Social Medicine and Epidemiology, Brandenburg Medical School Theodor Fontane, Hochstraße 15, Brandenburg an der Havel, 14770, Germany.

Funding

Bundesministerium für Bildung und Forschung 01ER1301A/B/C, 01ER1511D, 01ER1801A/B/C/D, and 01ER2301A/B/CBundesministerium für Bildung und Forschung 01GL1710A
6 · The paper itself

Abstract

backgroundIntersectionality has contributed to novel insights in epidemiology. However, participants of epidemiological studies have rarely been characterised from an intersectional perspective. We aimed to show the gained insights of an intersectionality-informed approach to describing a study population by comparing it to a conventional approach.

methodsWe used data of the German National Cohort (NAKO), which recruited 205,415 participants between 2014 and 2019. In the conventional approach, marginal proportions of educational level, cohabitation status, and country of birth were compared between the study populations of the NAKO and the German census survey (MZ) of 2014. In the intersectionality-informed approach, so-called intersectional population strata were constructed by cross-classifying educational level, cohabitation status, and country of birth. Proportions of these strata were also compared between NAKO and MZ. All analyses were stratified by sex and age group.

resultsThe conventional approach showed that the proportion of people with low education was lower in the NAKO compared to the MZ in all sex and age strata. Similarly, proportions of all intersectional population strata with low education were lower in the NAKO. Concerning cohabitation, the conventional approach showed that the proportion of those living without a partner was lower in the NAKO than in the MZ for women under 60 and men. The intersectionality-informed approach revealed that the proportions of some subgroups of those living without a partner were higher in the NAKO than in the MZ. These were intersectional population strata who lived without a partner, had a high level of education and were born in Germany. The intersectionality-informed approach revealed similar within-group heterogeneity for country of birth, showing that not all proportions of foreign-born people were lower in the NAKO compared to the MZ. Proportions of foreign-born with high education who lived with a partner were higher.

conclusionsOur results showed that heterogeneity within social categories can be revealed by applying the concept of intersectionality when comparing study participants with an external population. This way, an intersectionality-informed approach contributes to describing social complexity among study participants more precisely. Furthermore, results can be used to reduce participation barriers in a more targeted way.

Indexed as

Educational StatusSocioeconomic FactorsAdolescentAdultAgedCohort StudiesFemaleGermanyHumansMaleMiddle AgedSurveys and QuestionnairesCohort studyIntersectionalitySocial inequalityStudy participants

Identifiers

PMID40420085
PMCPMC12107990

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