ArticlePaediatric and perinatal epidemiology2023
Multilevel modelling for measuring interaction of effects between multiple categorical variables: An illustrative application using risk factors for preeclampsia.
Article in Paediatric and perinatal epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- From Averages to Heterogeneity: A Plain-Language Guide to MAIHDA in Epidemiology.International journal of social determinants of health and health services · 2026Review
- Association between cold climates and in-hospital mortality of acute heart failure: An observational study using multilevel analysis.Medicine · 2026Observational
- Socio-geographical disparities in cardiometabolic multimorbidity in Sweden: an Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (I-MAIHDA).International journal for equity in health · 2025Article
- Competing demands on adult children: How do they shape their provision of informal care?SSM - population health · 2025Article
- An overview of modern machine learning methods for effect measure modification analyses in high-dimensional settings.SSM - population health · 2025Article
- Trust in healthcare and perceived discrimination in Sweden: a fixed effects analysis of individual heterogeneity and discriminatory accuracy.Frontiers in public health · 2025Article
- Depression at the intersection of race/ethnicity, sex/gender, and sexual orientation in a nationally representative sample of US adults: a design-weighted intersectional MAIHDA.American journal of epidemiology · 2024Article
- An analysis of intersectional disparities in alcohol consumption in the US.Social science & medicine (1982) · 2024Article
- Onset of Type 2 diabetes in adults aged 50 and older in Europe: an intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy.Diabetology & metabolic syndrome · 2024Article
- A tutorial for conducting intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA).SSM - population health · 2024Article
- 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 · 2024Article
- Multilevel modelling for measuring interaction of effects between multiple categorical variables: An illustrative application using risk factors for preeclampsia.Paediatric and perinatal epidemiology · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
backgroundMeasuring multiple and higher-order interaction effects between multiple categorical variables proves challenging.
objectivesTo illustrate a multilevel modelling approach to studying complex interactions.
methodsWe apply a two-level random-intercept linear regression to a binary outcome for individuals (level-1) nested within strata (level-2) defined by all observed combinations of multiple categorical exposure variables. As a pedagogic application, we analyse 36 strata defined by five risk factors of preeclampsia (parity, previous preeclampsia, chronic hypertension, multiple pregnancies, body mass index category) among 652,603 women in the Swedish Medical Birth Registry between 2002 and 2010.
resultsThe absolute risk of preeclampsia was 4% but was predicted to vary from 1% to 44% across strata. The stratum discriminatory accuracy was 30% according to the variance partition coefficient (VPC) and 0.73 according to the area under the receiver operating characteristic curve (AUC). While the risk heterogeneity across strata was primarily due to the main effects of the categories defining the strata, 5% of the variation was attributable to their two- and higher-way interaction effects. One stratum presented a positive interaction, and two strata presented negative interaction.
conclusionsMultilevel modelling is an innovative tool for identifying and analysing higher-order interaction effects. Further work is needed to explore how this approach can best be applied to making causal inferences.
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