Biodemographic Analyses of Longitudinal Data on Aging, Health, and Longevity: Recent Advances and Future Perspectives.

Konstantin G Arbeev, Igor Akushevich, Alexander M Kulminski, Svetlana V Ukraintseva, Anatoliy I Yashin
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Abstract

Biodemography became one of the most innovative and fastest growing areas in demography. This progress is fueled by the growing variability and amount of relevant data available for analyses as well as by methodological developments allowing for addressing new research questions using new approaches that can better utilize the potential of these data. In this review paper, we summarize recent methodological advances in biodemography and their diverse practical applications. Three major topics are covered: (1) computational approaches to reconstruction of age patterns of incidence of geriatric diseases and other characteristics such as recovery rates at the population level using Medicare claims data; (2) methodological advances in genetic and genomic biodemography and applications to research on genetic determinants of longevity and health; and (3) biodemographic models for joint analyses of time-to-event data and longitudinal measurements of biomarkers collected in longitudinal studies on aging. We discuss how such data and methodology can be used in a comprehensive prediction model for joint analyses of incomplete datasets that take into account the wide spectrum of factors affecting health and mortality transitions including genetic factors and hidden mechanisms of aging-related changes in physiological variables in their dynamic connection with health and survival.

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老龄化、健康和长寿纵向数据的生物统计学分析:最新进展与未来展望》。
生物人口学已成为人口学中最具创新性和发展最快的领域之一。可用于分析的相关数据的变异性和数量不断增加,方法学的发展也推动了这一进展,新方法可以更好地利用这些数据的潜力,从而解决新的研究问题。在这篇综述论文中,我们总结了生物水文方法学的最新进展及其各种实际应用。论文涉及三大主题:(1) 利用医疗保险报销数据重建老年病发病年龄模式和其他特征(如人口层面的康复率)的计算方法;(2) 基因和基因组生物测量学的方法学进展以及在长寿和健康的基因决定因素研究中的应用;(3) 在老龄化纵向研究中收集的时间到事件数据和生物标志物纵向测量数据的联合分析生物人口学模型。我们讨论了如何将这些数据和方法用于综合预测模型,以联合分析不完整的数据集,这些数据集考虑到了影响健康和死亡率转变的广泛因素,包括遗传因素以及生理变量与健康和生存动态关联中与衰老相关的隐性变化机制。
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Biodemographic Analyses of Longitudinal Data on Aging, Health, and Longevity: Recent Advances and Future Perspectives.
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