Abstract:
From a life-course perspective, the occurrence and development of chronic diseases, as well as risk exposures, are understood to be dynamic processes. The innovative theories of life course epidemiology include the critical period model, the accumulation risk model, and the life-course causal model. A key challenge lies inutilizing longitudinal data from life course cohorts, which capture the dynamic longitudinal risk factors of chronic diseases across the lifecourse or disease progression, to uncover the trajectory changing patterns, identify critical period for prevention and control, assess cumulative risk effects, and elucidate causal pathways. Additionally,constructing dynamic prediction models is crucial. This presentation will introduce the theoretical models of life course epidemiology, trajectory analysis, causal models, and dynamic prediction methods. Using examples from cardiovascular disease longitudinal cohorts and longitudinal clinical cohorts for gastrointestinal tumors, it will also highlight the advancements in life course cohort research.
About the Speaker:
张涛,山东大学生物统计学教授,博士生导师,国家优秀青年科学基金获得者,山东大学杰出中青年学者。现任山东大学公共卫生学院院长助理,生命历程理论方法创新团队PI,兼任中华预防医学会健康大数据与人工智能应用专业委员会常务委员、中华预防医学会生物统计分会委员、中国抗癌协会肿瘤流行病学分会委员等职。长期从事生命历程纵向队列统计方法与应用研究,聚焦心血管病与恶性肿瘤等重大慢性病全生命周期防控,开展危险因素轨迹分析、因果图模型、多组学标志物和动态预测模型的统计方法和转化应用。近年来,主持国家自然科学基金5项,在国际学术期刊发表论文100余篇,其中以第一/通讯作者在CirculationResearch、Hypertension、Nat Commun 、Science Bulletin、BMCMedicine和EBioMedicine等国际权威期刊发表学术论文50余篇,被引用3000余次。

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