Description: The conventional methods for genetic analyses of data on aging and longevity-related traits underutilize available information on aging, health and life span and treat the limited data set as the only source of information about the traits. We show that the power and biological relevance of GWAS can be enhanced by incorporating the biological and demographic principles of trait formation into the backbone of genetic analyses, through appropriate mathematical models and statistical functions, and by incorporating genetic questions into a comprehensive framework of dynamic analyses of longitudinal data. In this paper we use Framingham Heart Study data from the original cohort to show how genetic factors are associated with age trajectories of physiological variables and other biomarkers. The approach allows for incorporating hidden biomarkers of aging into the stochastic process model of aging and mortality and evaluate age their age patterns fr om the data for individuals with different genetic background.

Description: Abstract for How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Lessons from Biodemographic Analyses of Longitudinal Data

Description: This report estimates sex-specific trends in HIPAA ADL disability between 1984 and 2004 using the National Long Term Care Survey (NLTCS); estimates age-standardized 20-year changes in ADL and cognitive impairment (CI) among the U.S. elderly using the HIPAA CI trigger; estimates the joint distribution of cognitive impairment (CI) and ADL disability among aged Medicare enrollees using the HIPAA disability triggers.

Description: Presented at Living to 100 symposium, January 2011. This paper investigates dynamic properties of age trajectories of physiological indices and their effects on mortality risk and longevity using longitudinal data on more than 5,000 individuals collected in biannual examinations of the Framingham Heart Study original age group during about 50 subsequent years of follow up.