The quadratic hazard model for analyzing longitudinal data on aging, health, and the life span.
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2012-06
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Abstract
A better understanding of processes and mechanisms linking human aging with changes in health status and survival requires methods capable of analyzing new data that take into account knowledge about these processes accumulated in the field. In this paper, we describe an approach to analyses of longitudinal data based on the use of stochastic process models of human aging, health, and longevity which allows for incorporating state of the art advances in aging research into the model structure. In particular, the model incorporates the notions of resistance to stresses, adaptive capacity, and "optimal" (normal) physiological states. To capture the effects of exposure to persistent external disturbances, the notions of allostatic adaptation and allostatic load are introduced. These notions facilitate the description and explanation of deviations of individuals' physiological indices from their normal states, which increase the chances of disease development and death. The model provides a convenient conceptual framework for comprehensive systemic analyses of aging-related changes in humans using longitudinal data and linking these changes with genotyping profiles, morbidity, and mortality risks. The model is used for developing new statistical methods for analyzing longitudinal data on aging, health, and longevity.
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Yashin, AI, KG Arbeev, I Akushevich, A Kulminski, SV Ukraintseva, E Stallard and KC Land (2012). The quadratic hazard model for analyzing longitudinal data on aging, health, and the life span. Phys Life Rev, 9(2). pp. 177–188. 10.1016/j.plrev.2012.05.002 Retrieved from https://hdl.handle.net/10161/14845.
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Scholars@Duke
Anatoli I. Yashin
Konstantin Arbeev
Konstantin G. Arbeev received the M.S. degree in Applied Mathematics from Moscow State University (branch in Ulyanovsk, Russia) in 1995 and the Ph.D. degree in Mathematics and Physics (specialization in Theoretical Foundations of Mathematical Modeling, Numerical Methods and Programming) from Ulyanovsk State University (Russia) in 1999. He was a post-doctoral fellow in Max Planck Institute for Demographic Research in Rostock (Germany) before moving to Duke University in 2004 to work as a Research Scientist and a Senior Research Scientist in the Department of Sociology and the Social Science Research Institute (SSRI). He is currently an Associate Research Professor in SSRI. Dr. Arbeev's major research interests are related to three interconnected fields of biodemography, biostatistics and genetic epidemiology as pertains to research on aging. The focus of his research is on discovering genetic and non-genetic factors that can affect the process of aging and determine longevity and healthy lifespan. He is interested in both methodological advances in this research area as well as their practical applications to analyses of large-scale longitudinal studies with phenotypic, genetic and, recently, genomic information. Dr. Arbeev authored and co-authored more than 150 peer-reviewed publications in these areas.
Igor Akushevich
Alexander Kulminski
Svetlana Ukraintseva
Dr. Ukraintseva studies the causes of human aging and the associated decline in whole-body resilience, with the goal of identifying genetic and other factors that drive this decline and contribute to the age-related increase in all-cause mortality risk, ultimately limiting longevity even in individuals without major diseases. She also investigates the “multi-hit” mechanism of Alzheimer’s disease and the complex, including trade‑off–like, relationships between Alzheimer’s disease and cancer. She actively explores the role of infectious diseases and compromised immunity in Alzheimer’s development, as well as the interplay between vaccines and genetic factors, to advance personalized vaccine repurposing for AD prevention. To address these questions, Dr. Ukraintseva and her team analyze large human datasets containing comprehensive information on millions of individuals. She is a PI and key investigator on several NIH-funded grants and has authored more than 150 peer‑reviewed publications, including in major journals such as JAMA, Nature group journals, Stroke, Alzheimer’s & Dementia, and others.
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Kenneth C. Land
I received my Ph.D. in sociology and mathematics from the University of Texas at Austin in 1969. After a year of postdoctoral study in mathematical statistics at Columbia University in New York City, I taught there and was a member of the staff of the Russell Sage Foundation for three years. I then was successively a member of the faculties of the University of Illinois at Urbana Champaign and the University of Texas at Austin before joining the Duke Sociology Department as Chairman in 1986. I served as Chair of Sociology from January 1986 to August 1997. My main research interests are contemporary social trends and quality-of-life measurement, social problems, demography, criminology, organizations, and mathematical and statistical models and methods for the study of social and demographic processes. I have done extensive research in each of these areas and have been elected a Fellow of the American Statistical Association (1978), the Sociological Research Association (1981), the American Association for the Advancement of Science (1992), the International Society for Quality-of-Life Studies (1997), and the American Society of Criminology (2004). I teach Contemporary Social Problems (SOCIOL 111), Advanced Methods of Demographic Analysis, and the Demography of Aging Proseminar (SOCIOL 750S). My other interests include tennis, jogging (10 kilometers), and music.
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