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Life course epidemiology of chronic diseases has been dominated so far by theenvironmental approach. Whether it focuses on early life exposures and eventsor later lifestyle behaviors, this approach assumes that previous lifeexperiences interact at each stage of life and shape subsequent healthtrajectories. Inspired by the analysis of social trajectories, focusing ontransitions between multiple states, in multiple dimensions of the socialexperience, we propose in this paper a novel empirical approach to multipletime-to-event health data, denoted as multiple state analysis. Alike theso-called state sequence analysis, the aim of multiple state analysis is tocreate typologies of the main life course trajectories. This approach isillustrated by the analysis of records from a south London general practiceelectronic health record from which multiple long term conditions associatedwith myocardial infarction were considered. Among expected results such as therecurrent role of hypertension, multiple state analysis shows that differentpatterns of long term conditions including physical and mental healthconditions, are associated with the onset timing of myocardial infarction butalso with socio-demographics such as sex and ethnicity.

Multiple State Analysis, a Multidimentional Approach to Multiple  Time-to-Event Data and Life Course Health Trajectories: Application to  Patients with Myocardial Infarction