Age Trajectories of Physiological Indices: Which Factors Influence Them?

Anatoliy I. Yashin (), Liubov S. Arbeeva (), Konstantin G. Arbeev (), Igor Akushevich (), Alexander M. Kulminski (), Eric Stallard () and Svetlana V. Ukraintseva ()
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Anatoliy I. Yashin: Duke Population Research Institute & Social Science Research Institute at Duke University, Biodemography of Aging Research Unit, Center for Population Health and Aging
Liubov S. Arbeeva: Duke Population Research Institute & Social Science Research Institute at Duke University, Biodemography of Aging Research Unit, Center for Population Health and Aging
Konstantin G. Arbeev: Duke Population Research Institute & Social Science Research Institute at Duke University, Biodemography of Aging Research Unit, Center for Population Health and Aging
Igor Akushevich: Duke Population Research Institute & Social Science Research Institute at Duke University, Biodemography of Aging Research Unit, Center for Population Health and Aging
Alexander M. Kulminski: Duke Population Research Institute & Social Science Research Institute at Duke University, Biodemography of Aging Research Unit, Center for Population Health and Aging
Eric Stallard: Duke Population Research Institute & Social Science Research Institute at Duke University, Biodemography of Aging Research Unit, Center for Population Health and Aging
Svetlana V. Ukraintseva: Duke Population Research Institute & Social Science Research Institute at Duke University, Biodemography of Aging Research Unit, Center for Population Health and Aging

Chapter Chapter 2 in Biodemography of Aging, 2016, pp 21-45 from Springer

Abstract: Abstract Longitudinal data on aging, health, and longevity provide researchers with a unique opportunity to observe aging-related changes in biomarkers that describe the functioning of individual organisms during people’s life courses. In this chapter, empirical estimates of the mean values of eight physiological variables are calculated for several groups of individuals using longitudinal data on participants of the original cohort from the Framingham Heart Study. These variables include: diastolic blood pressure, systolic blood pressure, pulse pressure, body mass index, serum cholesterol, blood glucose, hematocrit, and ventricular rate. The results of analyses of age trajectories of these variables show that they depend on various genetic and non-genetic factors affecting human lifespan. The patterns of physiological aging changes differ between the shorter-lived and the longest-lived individuals, as well as between individuals with shorter and longer healthspans. A particularly notable finding was that health and extreme longevity were associated with different patterns of aging changes in physiological variables indicating that longevity can be linked to a postponement of the aging changes in physiological variables rather than to their “healthier” values. To further uncover mechanisms responsible for the dynamic behavior of physiological variables from analysis of longitudinal human data, one needs appropriate statistical models that link aging-related changes in these variables with health and survival outcomes.

Keywords: Diastolic Blood Pressure; Pulse Pressure; Physiological Variable; Framingham Heart Study; Ventricular Rate (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-94-017-7587-8_2

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DOI: 10.1007/978-94-017-7587-8_2

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