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Titel: Depressive symptoms, education, gender and history of migration - an intersectional analysis using data from the German National Cohort (NAKO)
Autor(en): Becher, HeikoIn der Gemeinsamen Normdatei der DNB nachschlagen
Berger, KlausIn der Gemeinsamen Normdatei der DNB nachschlagen
Bohmann, Patricia
Brenner, HermannIn der Gemeinsamen Normdatei der DNB nachschlagen
Castell, StefanieIn der Gemeinsamen Normdatei der DNB nachschlagen
Dragano, NicoIn der Gemeinsamen Normdatei der DNB nachschlagen
Harth, VolkerIn der Gemeinsamen Normdatei der DNB nachschlagen
Jaskulski, StefanieIn der Gemeinsamen Normdatei der DNB nachschlagen
Karch, AndréIn der Gemeinsamen Normdatei der DNB nachschlagen
Keil, ThomasIn der Gemeinsamen Normdatei der DNB nachschlagen
Krist, LilianIn der Gemeinsamen Normdatei der DNB nachschlagen
Lange, BeritIn der Gemeinsamen Normdatei der DNB nachschlagen
Leitzmann, MichaelIn der Gemeinsamen Normdatei der DNB nachschlagen
Massag, Janka
Meinke-Franze, Claudia
Mikolajczyk, RafaelIn der Gemeinsamen Normdatei der DNB nachschlagen
Erscheinungsdatum: 2025
Art: Artikel
Sprache: Englisch
Zusammenfassung: Background: The educational gradient in depressive symptoms is well documented. Gender and history of migration have also been found to be associated with depressive symptoms. Intersectional approaches enable the analysis of the interplay of different social factors at a time to gain a deeper understanding of inequalities in depressive symptoms. In this study, intersectional inequalities in depressive symptoms according to education, gender and history of migration are analysed. Methods: The German National Cohort (NAKO, N = 204,783) collected information on depressive symptoms (PHQ-9), which was used as an outcome variable. Educational attainment (ISCED-97), gender, and history of migration constituted the different social strata in the analyses. The predicted probabilities of depressive symptoms for 30 social strata were calculated. Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) was applied, using logistic regression and social strata were introduced as higher-level unit interaction terms. Results: The analyses revealed an educational gradient in depressive symptoms, with differences within each educational group when gender and history of migration were introduced to the models. The predicted probabilities of depressive symptoms varied between the most advantaged and the most disadvantaged social strata by more than 20% points. Among the three studied variables, education contributed the most to the variance explained by the MAIHDA models. The between-strata differences were largely explained by additive effects. Conclusions: We observed a robust educational gradient in depressive symptoms, but gender and history of migration had substantial contribution on the magnitude of educational inequalities. An intersectional perspective on inequalities in depressive symptoms enhances current knowledge by showing that different social dimensions may intersect and contribute to inequalities in depressive symptoms. Future studies on inequalities in depression may greatly benefit from an intersectional approach, as it reflects lived inequalities in their diversity.
URI: https://opendata.uni-halle.de//handle/1981185920/121080
http://dx.doi.org/10.25673/119124
Open-Access: Open-Access-Publikation
Nutzungslizenz: (CC BY 4.0) Creative Commons Namensnennung 4.0 International(CC BY 4.0) Creative Commons Namensnennung 4.0 International
Journal Titel: International journal for equity in health
Verlag: BioMed Central
Verlagsort: London
Band: 24
Originalveröffentlichung: 10.1186/s12939-025-02479-2
Enthalten in den Sammlungen:Open Access Publikationen der MLU

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