ArticleInternational journal for equity in health2025
Depressive symptoms, education, gender and history of migration - an intersectional analysis using data from the German National Cohort (NAKO).
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. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Intersectional inequalities in depressive symptoms according to gender, migration, and education in 30 European countries.BMC public health · 2026Article
- Antidepressant discontinuation in France from an intersectional perspective: a discrete-time survival analysis within the MAIHDA framework.BMC public health · 2026Article
- Redesigning medicine: integrating sex and gender for better health outcomes.Naunyn-Schmiedeberg's archives of pharmacology · 2026Review
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26 authors.
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Abstract
backgroundThe 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.
methodsThe 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.
resultsThe 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.
conclusionsWe 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.
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