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@ARTICLE{Vonneilich:300632,
      author       = {N. Vonneilich and H. Becher and K. Berger and P. Bohmann
                      and H. Brenner$^*$ and S. Castell and N. Dragano and V.
                      Harth and S. Jaskulski and A. Karch and T. Keil and L. Krist
                      and B. Lange and M. Leitzmann and J. Massag and C.
                      Meinke-Franze and R. Mikolajczyk and N. Obi and T. Pischon
                      and M. Reuter and B. Schmidt and I. M. Velásquez and H.
                      Völzke and C. Wiessner and O. von dem Knesebeck and D.
                      Lüdecke},
      title        = {{D}epressive symptoms, education, gender and history of
                      migration - an intersectional analysis using data from the
                      {G}erman {N}ational {C}ohort ({NAKO}).},
      journal      = {International journal for equity in health},
      volume       = {24},
      number       = {1},
      issn         = {1475-9276},
      address      = {London},
      publisher    = {BioMed Central},
      reportid     = {DKFZ-2025-00846},
      pages        = {108},
      year         = {2025},
      abstract     = {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.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.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.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.},
      keywords     = {Humans / Germany: epidemiology / Male / Female /
                      Educational Status / Depression: epidemiology / Adult /
                      Middle Aged / Cohort Studies / Sex Factors / Socioeconomic
                      Factors / Aged / Health Status Disparities / Depression
                      (Other) / Educational inequalities (Other) / Gender (Other)
                      / German national cohort (Other) / History of migration
                      (Other) / Intersectional analysis (Other) / MAIHDA (Other) /
                      NAKO (Other)},
      cin          = {C070},
      ddc          = {610},
      cid          = {I:(DE-He78)C070-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40259268},
      doi          = {10.1186/s12939-025-02479-2},
      url          = {https://inrepo02.dkfz.de/record/300632},
}