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Intersectional MAIHDA

What is Intersectional MAIHDA?

Intersectional MAIHDA is a recently proposed approach to analysing sociodemographic inequalities in individual outcomes. The approach gives elevated attention to the way such characteristics intersect and potentially interact to advantage and disadvantage different individuals. The approach extends naturally to the study of sociodemographic intersectionality in the measured relationships between outcomes and exposures.

From a multilevel modelling perspective, the individual outcome is regressed on individual exposures in the usual way. The key novelty is that intersectional MAIHDA treats individuals (level-1) as nested within sociodemographic strata (level-2) formed by combinations of the key individual sociodemographic characterises of research focus. The regression intercept and slope coefficients are then modelled as varying across these strata.

Interest lies in assessing the general importance of strata, predicting and ranking mean outcomes, and understanding the extent to which this variation is attributable to the additive main effects vs. complex interactions between the stratum characteristics, drawing attention to otherwise hidden marginalised subpopulations

The approach was proposed by Evans et al. (2018) and has been subsequently developed and disseminated Evans and others and is increasingly applied in social epidemiology and related fields.

A Tutorial on to Intersectional MAIHDA

A key reading for those wishing to learn more about Intersectional MAIHDA is the following tutorial paper

We provide Stata and R scripts and datasets to replicate all results presented in this article.

The Intersectional Health Website

The Intersectional Health Website provides a dedicated research hub for understanding, exploring, and engaging with intersectional health research. It provides a resource for those interested in intersectional health research, whether theoretically, methodologically, or from a policy and practice perspective. It also a source of information for those wishing to understand and apply the MAIHDA approach to quantitative intersectionality.

CMM contributions to Intersectional MAIHDA

CMM Co-Director Leckie has collaborated with Evans, Merlo, Subramanian, Bell, Holman, and other key researchers in this area in both further developing the Intersectional MAIHDA approach and in disseminating applications. This joint work has been funded by two grants

Collectively, these collaborations have led to a growing number of journal articles on Intersectional MAIHDA, including:

  • Bell, A., Evans, C., Holman, D., & Leckie, G. (2023). Extending intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) for longitudinal data, with application to mental health trajectories in the UK.
  • Evans, C., Leckie, G. B., Bell, A., & Merlo, J. (2024). A Tutorial for Conducting Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). SSM-Population Health.
  • Evans, C. R., Leckie, G., & Merlo, J. (2020). Multilevel versus single-level regression for the analysis of multilevel information: the case of quantitative intersectional analysis. Social Science & Medicine, 245, 112499.
  • Fisk, S. A., Mulinari, S., Wemrell, M., Leckie, G., Vicente, R. P., & Merlo, J. (2018). Chronic obstructive pulmonary disease in Sweden: an intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy. SSM-Population Health, 4, 334-346.
  • Hernández-Yumar, A., Wemrell, M., Abasolo Alesson, I., González López-Valcárcel, B., Leckie, G., & Merlo, J. (2018). Socioeconomic differences in body mass index in Spain: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy. PloS one, 13(12), e0208624.
  • Khalaf, K., Axelsson Fisk, S., Ekberg-Jansson, A., Leckie, G., Perez-Vicente, R., & Merlo, J. (2020). Geographical and sociodemographic differences in discontinuation of medication for chronic obstructive pulmonary disease–a cross-classified multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). Clinical Epidemiology, 783-796.
  • Ljungman, H., Wemrell, M., Khalaf, K., Perez-Vicente, R., Leckie, G., & Merlo, J. (2022). Antidepressant use in Sweden: an intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). Scandinavian journal of public health, 50(3), 395-403.
  • Mattsson, H., Gustafsson, J., Prada, S., Jaramillo-Otoya, L., Leckie, G., Merlo, J., & Rodriguez-Lopez, M. (2024). Mapping socio-geographical disparities in the occurrence of teenage maternity in Colombia using multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). International Journal for Equity in Health, 23(1), 36.
  • Merlo, J., Öberg, J., Khalaf, K., Perez-Vicente, R., & Leckie, G. (2023). Geographical and sociodemographic differences in statin dispensation after acute myocardial infarction in Sweden: a register-based prospective cohort study applying analysis of individual heterogeneity and discriminatory accuracy (AIHDA) for basic comparisons of healthcare quality. BMJ open, 13(9), e063117.
  • Merlo, J., Wagner, P., & Leckie, G. (2019). A simple multilevel approach for analysing geographical inequalities in public health reports: the case of municipality differences in obesity. Health & place, 58, 102145.
  • Persmark, A., Wemrell, M., Evans, C. R., Subramanian, S., Leckie, G., & Merlo, J. (2020). Intersectional inequalities and the US opioid crisis: challenging dominant narratives and revealing heterogeneities. Critical Public Health, 30(4), 398-414.
  • Persmark, A., Wemrell, M., Zettermark, S., Leckie, G., Subramanian, S., & Merlo, J. (2019). Correction: Precision public health: Mapping socioeconomic disparities in opioid dispensations at Swedish pharmacies by Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). PloS one, 14(10), e0224008.
  • Persmark, A., Wemrell, M., Zettermark, S., Leckie, G., Subramanian, S., & Merlo, J. (2019). Precision public health: Mapping socioeconomic disparities in opioid dispensations at Swedish pharmacies by Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). PloS one, 14(8), e0220322.
  • Prior, L., Evans, C., Merlo, J., & Leckie, G. (2022). Sociodemographic inequalities in student achievement: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) with application to students in London, England. arXiv preprint arXiv:2211.06321.
  • Rodriguez‐Lopez, M., Leckie, G., Kaufman, J. S., & Merlo, J. (2023). Multilevel modelling for measuring interaction of effects between multiple categorical variables: An illustrative application using risk factors for preeclampsia. Paediatric and Perinatal Epidemiology, 37(2), 154-164.
  • Rodriguez-Lopez, M., Merlo, J., Perez-Vicente, R., Austin, P., & Leckie, G. (2020). Cross-classified Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to evaluate hospital performance: the case of hospital differences in patient survival after acute myocardial infarction. BMJ open, 10(10), e036130.
  • Zettermark, S., Khalaf, K., Perez-Vicente, R., Leckie, G., Mulinari, D., & Merlo, J. (2021). Population heterogeneity in associations between hormonal contraception and antidepressant use in Sweden: a prospective cohort study applying intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). BMJ open, 11(10), e049553.

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