Evidence for Dependence Among Diseases

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

Chapter Chapter 4 in Biodemography of Aging, 2016, pp 95-111 from Springer

Abstract: Abstract Demographic calculations evaluating the role of chronic diseases in life expectancy use the assumption that diseases are independent. Disease independence was a plausible hypothesis in the era of infectious diseases. However, the health problems of modern populations are closely connected with diseases of the elderly i.e., with chronic non-communicable diseases that often have common risk factors. The existence of such common genetic and non-genetic risk factors makes chronic diseases mutually dependent. In this chapter, we provide evidence of trade-offs between cancer and other diseases as well as between cancer and aging changes. The Multiple Cause of Death data are used to evaluate correlations among mortality rules from cancer and other major health disorders, including heart disease, stroke, diabetes, Alzheimer’s and Parkinson’s diseases, and asthma. Significant negative correlations between cancer and some of the selected diseases are detected. These correlations show regular patterns of change over time. The chapter describes possible mechanisms of disease dependence including pleiotropic effects of genetic factors and discusses appropriate methods of statistical analysis of disease dependence.

Keywords: Coronary Heart Disease; Death Certificate; Markov Chain Model; Coronary Heart Disease Mortality; Maximal Life Span (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_4

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DOI: 10.1007/978-94-017-7587-8_4

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