Do gender, disability, and morbidity affect aging rate in the LLFS? Application of indices of cumulative deficits.

Abstract

We used an approach of cumulative deficits to evaluate the rate of aging in 4954 participants of the Long-Life Family Study (LLFS) recruited in the U.S. (Boston, New York, and Pittsburgh) and Denmark. We used an array of 85 health-related deficits covering major health dimensions including depression, cognition, morbidity, physical performance, and disability to construct several deficit indices (DIs) with overlapping and complementary sets of deficits to test robustness of the estimates. Our study shows that the DIs robustly characterize accelerated rates of aging irrespective of specific of deficits. When a wider spectrum of health dimensions is considered these rates are better approximated by quadratic law. Exponential rates are more characteristic for more severe health dimensions. The aging rates are the same for males and females. Individuals who contracted major diseases and those who were free of them exhibited the same aging rates as characterized by the DI constructed using mild deficits. Unlike health, disability can qualitatively alter the aging patterns of the LLFS participants. We report on systemic differences in health among the LLFS centenarians residing in New York and Boston. This study highlights importance of aggregated approaches to better understand systemic mechanisms of health deterioration in long-living individuals.

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Published Version (Please cite this version)

10.1016/j.mad.2011.03.006

Publication Info

Kulminski, Alexander M, Konstantin G Arbeev, Kaare Christensen, Richard Mayeux, Anne B Newman, Michael A Province, Evan C Hadley, Winifred Rossi, et al. (2011). Do gender, disability, and morbidity affect aging rate in the LLFS? Application of indices of cumulative deficits. Mech Ageing Dev, 132(4). pp. 195–201. 10.1016/j.mad.2011.03.006 Retrieved from https://hdl.handle.net/10161/14878.

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Scholars@Duke

Arbeev

Konstantin Arbeev

Associate Research Professor in the Social Science Research Institute

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.

Yashin

Anatoli I. Yashin

Research Professor in the Social Science Research Institute

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