Connecting Fundamental Concepts of Human Aging: A Statistical Modeling Perspective

Anatoliy I. Yashin, Duke University
Konstantin G. Arbeev, Duke University
Igor Akushevich, Duke University
Aliaksandr Kulminski, Duke University
Lucy Akushevich, Duke University
Svetlana V. Ukraintseva, Duke University

Numerous studies of aging and longevity in humans have accumulated a substantial amount of data about aging-related decline in health/well-being/survival status. Despite substantial progress in studying selected areas of aging, the research potential of these data remains largely under-explored. This is because traditional studies ignore a large portion of related information that might be important for better understanding systemic regularities of the human aging processes. As a result, many important features the human of aging process remain disconnected. Important examples include: age dependence of physiological norm; allostatic adaptation, and allostatic load; resistance to stress, as well as regular and stochastic components of physiological age trajectories. In this paper we describe the new method of statistical modeling that allows us to connect these fundamental concepts of human aging. The properties of this approach and its application to the analysis of Framingham Heart Study data are discussed.

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Presented in Session 83: Statistical Modeling Issues in Population Research