Exceptional survivors have lower age trajectories of blood glucose: lessons from longitudinal data
- 159 Downloads
Exceptional survival results from complicated interplay between genetic and environmental factors. The effects of these factors on survival are mediated by the biological and physiological variables, which affect mortality risk. In this paper, we evaluated the role of blood glucose (BG) in exceptional survival using the Framingham heart study data for the main (FHS) and offspring (FHSO) cohorts. We found that: (1) the average cross-sectional age patterns of BG change over time; (2) the values of BG level among the longest lived individuals in this study differ for different sub-cohorts; (3) the longitudinal age patterns of BG differ from those of cross-sectional ones. We investigated mechanisms forming average age trajectories of BG in the FHS cohort. We found that the two curves: one, characterizing the average effects of allostatic adaptation, and another, minimizing mortality risk for any given age, play the central role in this process. We found that the average BG age trajectories for exceptional survivors are closer to the curve minimizing mortality risk than those of individuals having shorter life spans. We concluded that individuals whose age trajectories of BG are located around the curve minimizing chances of premature death at each given age have highest chances of reaching exceptional longevity.
KeywordsMortality risk Stochastic process model of aging Allostatic adaptation Age-specific physiological norm Blood glucose Framingham heart study
The research reported in this paper was supported by the National Institute on Aging grants R01AG027019, R01AG028259, and 5P01AG008761. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Aging or the National Institutes of Health. The Framingham Heart Study (FHS) is conducted and supported by the NHLBI in collaboration with the FHS Investigators. This manuscript was prepared using a limited access dataset obtained from the NHLBI and does not necessarily reflect the opinions or views of the FHS or the NHLBI.
- Bagdonavicius V, Nikulin M (2002) Accelerated life models. Chapman and Hall/CRC, Boca RatonGoogle Scholar
- Bagdonavicius V, Nikulin M (2004) Semiparametric analysis of degradation and failure time data with covariates. In: Nikulin MS, Balakrishnan N, Mesbah M, Limnios N (eds) Parametric and semiparametric models with applications to reliability, survival analysis, and quality of life. Birkhauser, Boston, pp 41–65Google Scholar
- Bagdonavicius V, Nikuline M (2005) Analysis of survival data with non-proportional hazards and crossings of survival functions. In: Edler L, Kitsos C (eds) Recent advances in quantitative methods in cancer and human health risk assessment. Wiley, New York, pp 197–210Google Scholar
- Dawber TR (1980) The Framingham study: the epidemiology of atherosclerotic disease. Harvard University Press, Cambridge, MAGoogle Scholar
- Paolisso G, Gambardella A, Ammendola S, Damore A, Balbi V, Varricchio M, Donofrio F (1996) Glucose tolerance and insulin action in healthy centenarians. Am J Physiol Endocrinol Metab 270:E890–E894Google Scholar
- Sterling P, Eyer J (1988) Allostasis: a new paradigm to explain arousal pathology. In: Fisher S, Reason J (eds) Handbook of life stress, cognition and health. Wiley, New York, pp 629–649Google Scholar