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.
Type
Journal articleSubject
AgedAged, 80 and over
Aging
Attitude to Health
Cohort Studies
Depression
Disabled Persons
Disease
Female
Health Status
Humans
Longevity
Male
Sex Factors
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https://hdl.handle.net/10161/14878Published Version (Please cite this version)
10.1016/j.mad.2011.03.006Publication Info
Kulminski, Alexander M; Arbeev, Konstantin G; Christensen, Kaare; Mayeux, Richard;
Newman, Anne B; Province, Michael A; ... Yashin, Anatoli I (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.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
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 Resea
Alexander Kulminski
Research Professor in the Social Science Research Institute
Anatoli I. Yashin
Research Professor in the Social Science Research Institute
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