Maintaining physiological state for exceptional survival: What is the normal level of blood glucose and does it change with age?

Pubmed ID: 19635493

Pubmed Central ID: PMC2764411

Journal: Mechanisms of ageing and development

Publication Date: Sept. 1, 2009

MeSH Terms: Humans, Male, Adult, Female, Cardiovascular Diseases, Risk Factors, United States, Aging, Age Factors, Middle Aged, Longitudinal Studies, Data Interpretation, Statistical, Models, Statistical, Time Factors, Health Surveys, Blood Glucose, Statistics as Topic

Grants: 5P01AG008761, R01 AG028259, R01 AG028259-05, R01AG028259, R01 AG027019, R01 AG027019-04, R01AG027019, P01 AG008761, P01 AG008761-190005

Authors: Yashin AI, Arbeev KG, Ukraintseva SV, Akushevich I, Kulminski AM, Arbeeva LS

Cite As: Yashin AI, Ukraintseva SV, Arbeev KG, Akushevich I, Arbeeva LS, Kulminski AM. Maintaining physiological state for exceptional survival: What is the normal level of blood glucose and does it change with age? Mech Ageing Dev 2009 Sep;130(9):611-8. Epub 2009 Jul 25.

Studies:

Abstract

The levels of blood glucose (BG) in humans tend to increase with age deviating from the norm specified for the young adults. Such elevation is often considered as a factor contributing to an increase in risks of disease and death. The proper use of intervention strategies coping with or preventing consequences of BG elevation requires understanding the roles of external forces and intrinsic senescence in this process. To address these issues, we performed analyses of longitudinal data on BG collected in the Framingham Heart Study using methods of descriptive statistics and statistical modeling. The approach allows us to separate effects of persistent external disturbances from "normal" aging-related changes due to the senescence process. We found that the BG level corresponding to the lowest mortality risk tends to increase with age. The changes in the shape of the mortality risk with age indicate the aging-related decline in resistance to stresses affecting the BG level. The results show that analyzing longitudinal data using advanced methods may substantially increase our knowledge on factors and mechanisms responsible for aging-related changes in humans.