论文标题
多个状态分析，一种多维的方法，用于多个事件数据和生活课程健康轨迹：对心肌梗塞患者的应用
Multiple State Analysis, a Multidimentional Approach to Multiple Time-to-Event Data and Life Course Health Trajectories: Application to Patients with Myocardial Infarction
论文作者
论文摘要
到目前为止，慢性疾病的生命课程流行病学已经由环境方法主导。无论是专注于早期生活的暴露和事件，还是以后的生活方式行为，这种方法都假设前一个生活经历在生活的每个阶段和随后的健康轨迹上都相互作用。受社会轨迹分析的启发，重点关注多个状态之间的过渡，在社会经验的多个维度上，我们在本文中提出了一种新颖的经验方法，用于多个事实上的健康数据，称为多个状态分析。就像所谓的状态序列分析一样，多种状态分析的目的是创建主要生命过程轨迹的类型。通过对南伦敦一家通用电子健康记录的记录的分析来说明这种方法，从中考虑了与心肌梗塞相关的多个长期条件。在预期的结果（例如高血压的复发作用）中，多个状态分析表明，包括身心健康的长期状况的不同模式与心肌梗死的发作时间有关，也与社会人口统计学（例如性别和种族）有关。
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.
