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Extending intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to study individual longitudinal trajectories, with application to mental health in the UK

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  • Bell, Andrew
  • Evans, Clare
  • Holman, Dan
  • Leckie, George

Abstract

The intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) approach is gaining prominence in health sciences and beyond, as a robust quantitative method for identifying intersectional inequalities in a range of individual outcomes. However, it has so far not been applied to longitudinal data, despite the availability of such data, and growing recognition that intersectional social processes and determinants are not static, unchanging phenomena. Drawing on intersectionality and life course theories, we develop a longitudinal version of the intersectional MAIHDA approach, allowing the analysis not just of intersectional inequalities in static individual differences, but also of life course trajectories. We discuss the conceptualization of intersectional groups in this context: how they are changeable over the life course, appropriate treatment of generational differences, and relevance of the age-period-cohort identification problem. We illustrate the approach with a study of mental health using United Kingdom Household Longitudinal Study data (2009–2021). The results reveal important differences in trajectories between generations and intersectional strata, and show that trajectories are partly multiplicative but mostly additive in their intersectional inequalities. This article provides an important and much needed methodological contribution, enabling rigorous quantitative, longitudinal, intersectional analyses in social epidemiology and beyond.

Suggested Citation

  • Bell, Andrew & Evans, Clare & Holman, Dan & Leckie, George, 2024. "Extending intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to study individual longitudinal trajectories, with application to mental health in the UK," Social Science & Medicine, Elsevier, vol. 351(C).
    • Handle: RePEc:eee:socmed:v:351:y:2024:i:c:s027795362400399x
    DOI: 10.1016/j.socscimed.2024.116955
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    References listed on IDEAS

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    1. Daniel Holman & Alan Walker, 2021. "Understanding unequal ageing: towards a synthesis of intersectionality and life course analyses," European Journal of Ageing, Springer, vol. 18(2), pages 239-255, June.
    2. Evans, Clare R. & Erickson, Natasha, 2019. "Intersectionality and depression in adolescence and early adulthood: A MAIHDA analysis of the national longitudinal study of adolescent to adult health, 1995–2008," Social Science & Medicine, Elsevier, vol. 220(C), pages 1-11.
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    5. Johannes Beller, 2022. "Age-period-cohort analysis of depression trends: are depressive symptoms increasing across generations in Germany?," European Journal of Ageing, Springer, vol. 19(4), pages 1493-1505, December.
    6. Evans, Clare & Leckie, George & Subramanian, SV & Bell, Andrew & Merlo, Juan, 2024. "A Tutorial for Conducting Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)," SocArXiv 635hx, Center for Open Science.
    7. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    8. Evans, Clare R. & Nieves, Christina I. & Erickson, Natasha & Borrell, Luisa N., 2023. "Intersectional inequities in the birthweight gap between twin and singleton births: A random effects MAIHDA analysis of 2012–2018 New York City birth data," Social Science & Medicine, Elsevier, vol. 331(C).
    9. Alvarez, Camila H. & Evans, Clare Rosenfeld, 2021. "Intersectional environmental justice and population health inequalities: A novel approach," Social Science & Medicine, Elsevier, vol. 269(C).
    10. Zubizarreta, Dougie & Beccia, Ariel L. & Trinh, Mai-Han & Reynolds, Colleen A. & Reisner, Sari L. & Charlton, Brittany M., 2022. "Human papillomavirus vaccination disparities among U.S. college students: An intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)," Social Science & Medicine, Elsevier, vol. 301(C).
    11. Evans, Clare R. & Williams, David R. & Onnela, Jukka-Pekka & Subramanian, S.V., 2018. "A multilevel approach to modeling health inequalities at the intersection of multiple social identities," Social Science & Medicine, Elsevier, vol. 203(C), pages 64-73.
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