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

Research output: Working paper/PreprintPreprint

Original languageUndefined/Unknown
Published22 Sep 2022

Bibliographical note

16 pages, 4 figures and 2 tables

Documents

  • 2209.11084v2

    2209.11084v2.pdf, 328 KB, application/pdf

    Uploaded date:29 Sep 2022

King's Authors

Abstract

Life course epidemiology of chronic diseases has been dominated so far by the environmental approach. Whether it focuses on early life exposures and events or later lifestyle behaviors, this approach assumes that previous life experiences interact at each stage of life and shape subsequent health trajectories. Inspired by the analysis of social trajectories, focusing on transitions between multiple states, in multiple dimensions of the social experience, we propose in this paper a novel empirical approach to multiple time-to-event health data, denoted as multiple state analysis. Alike the so-called state sequence analysis, the aim of multiple state analysis is to create typologies of the main life course trajectories. This approach is illustrated by the analysis of records from a south London general practice electronic health record from which multiple long term conditions associated with myocardial infarction were considered. Among expected results such as the recurrent role of hypertension, multiple state analysis shows that different patterns of long term conditions including physical and mental health conditions, are associated with the onset timing of myocardial infarction but also with socio-demographics such as sex and ethnicity.

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