, Volume 17, Issue 1, pp 89–107 | Cite as

How the effects of aging and stresses of life are integrated in mortality rates: insights for genetic studies of human health and longevity

  • Anatoliy I. Yashin
  • Konstantin G. Arbeev
  • Liubov S. Arbeeva
  • Deqing Wu
  • Igor Akushevich
  • Mikhail Kovtun
  • Arseniy Yashkin
  • Alexander Kulminski
  • Irina Culminskaya
  • Eric Stallard
  • Miaozhu Li
  • Svetlana V. Ukraintseva
Review Article


Increasing proportions of elderly individuals in developed countries combined with substantial increases in related medical expenditures make the improvement of the health of the elderly a high priority today. If the process of aging by individuals is a major cause of age related health declines then postponing aging could be an efficient strategy for improving the health of the elderly. Implementing this strategy requires a better understanding of genetic and non-genetic connections among aging, health, and longevity. We review progress and problems in research areas whose development may contribute to analyses of such connections. These include genetic studies of human aging and longevity, the heterogeneity of populations with respect to their susceptibility to disease and death, forces that shape age patterns of human mortality, secular trends in mortality decline, and integrative mortality modeling using longitudinal data. The dynamic involvement of genetic factors in (i) morbidity/mortality risks, (ii) responses to stresses of life, (iii) multi-morbidities of many elderly individuals, (iv) trade-offs for diseases, (v) genetic heterogeneity, and (vi) other relevant aging-related health declines, underscores the need for a comprehensive, integrated approach to analyze the genetic connections for all of the above aspects of aging-related changes. The dynamic relationships among aging, health, and longevity traits would be better understood if one linked several research fields within one conceptual framework that allowed for efficient analyses of available longitudinal data using the wealth of available knowledge about aging, health, and longevity already accumulated in the research field.


Longitudinal data Genetic heterogeneity Pleiotropy Population aging Quadratic hazard Health of the elderly 



Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Numbers R01AG046860, P01AG043352, and P30AG034424. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with Boston University (Contract No. N01-HC-25195). This manuscript was not prepared in collaboration with investigators of the Framingham Heart Study and does not necessarily reflect the opinions or views of the Framingham Heart Study, Boston University, or NHLBI. Funding for SHARe Affymetrix genotyping was provided by NHLBI Contract N02-HL-64278. SHARe Illumina genotyping was provided under an agreement between Illumina and Boston University. The authors thank Debra Fincham for help in preparing this paper for publication.


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Anatoliy I. Yashin
    • 1
    • 3
  • Konstantin G. Arbeev
    • 1
  • Liubov S. Arbeeva
    • 1
  • Deqing Wu
    • 1
  • Igor Akushevich
    • 1
  • Mikhail Kovtun
    • 1
  • Arseniy Yashkin
    • 1
  • Alexander Kulminski
    • 1
  • Irina Culminskaya
    • 1
  • Eric Stallard
    • 1
  • Miaozhu Li
    • 1
  • Svetlana V. Ukraintseva
    • 1
    • 2
  1. 1.The Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamUSA
  2. 2.The Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamUSA
  3. 3.The Biodemography of Aging Research Unit, Social Science Research InstituteDuke UniversityDurhamUSA

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