OBJECTIVES:To compare how well frailty measures based on a phenotypic frailty approach proposed in the Cardiovascular Health Study (CHS) and a cumulative deficits approach predict mortality. DESIGN: Cohort study.Corresponding Author: A. Kulminski Center for Population Health and Aging, Duke University Trent Hall, Room 002, Box 90408, Durham, NC 27708. Fax: (919) 684-3861 E-mail: E-mail: Alexander.Kulminski@duke.edu. Alternate Corresponding Author: A. Yashin E-mail: E-mail: aiy@duke.edu. Author contributions: Drs. Kulminski and Yashin are responsible for study design, the accuracy of the analyses, and interpretation of the results. Drs. Kulminski, Ukraintseva, Kulminskaya, Arbeev, and Yashin take responsibility for the data integrity, and drafting the manuscript. Drs. Ukraintseva and Kulminskaya participated in elaboration of the phenotypic frailty and cumulative deficits indices. Dr. Kulminski was responsible for statistical analyses.Financial Disclosure: The research reported in this paper was supported by the grants 1R01 AG028259, 1R01-AG-027019 and 5P01-AG-008761 from the National Institute on Aging (NIA). Conflict of Interest MEASUREMENTS:A phenotypic frailty index (PFI) was defined in the same way as proposed in the CHS: assessing weight loss, exhaustion, low physical activity, slowness, and poor grip strength. A cumulative deficit index (DI) was defined based on 48 elderly deficits (signs, symptoms, impairments, diseases) included in the index, with equal weights. RESULTS:Of the 1,073 frailest individuals with the lowest survival, the PFI, categorized as proposed in the CHS into robust, prefrail, and frail categories, underestimated the risk of death for 720 persons, whereas the DI categorized into the same three frailty categories underestimated the mortality risk for 134 persons. The higher power of the DI for discriminating frail individuals in their susceptibility to death also followed from comparison of quasi-instantaneous values of both indices. The three-level DI identified 219 individuals as frail of 361 individuals identified as frail according to the three-level PFI. CONCLUSIONS:The DI can more precisely evaluate chances of death because it assesses a broader spectrum of disorders than the PFI. Both indices appear to be frailty related. Integration of both approaches is highly promising for increasing the precision of discrimination of the risk of death and especially for identification of the most vulnerable elderly people.

The FI: (i) can be considered as an adequate sex-specific indicator of the aging-associated processes in the elderly, (ii) can characterize these processes independently of age, and (iii) is a better characteristic of the aging phenotype than chronological age.

Aging-related changes in a human organism follow dynamic regularities, which contribute to the observed age patterns of incidence and mortality curves. An organism's "optimal" (normal) physiological state changes with age, affecting the values of risks of disease and death. The resistance to stresses, as well as adaptive capacity, declines with age. An exposure to improper environment results in persisting deviation of individuals' physiological (and biological) indices from their normal state (due to allostatic adaptation), which, in turn, increases chances of disease and death. Despite numerous studies investigating these effects, there is no conceptual framework, which would allow for putting all these findings together, and analyze longitudinal data taking all these dynamic connections into account. In this paper we suggest such a framework, using a new version of stochastic process model of aging and mortality. Using this model, we elaborated a statistical method for analyses of longitudinal data on aging, health and longevity and tested it using different simulated data sets. The results show that the model may characterize complicated interplay among different components of aging-related changes in humans and that the model parameters are identifiable from the data.

The accelerated FI age patterns suggest that FI can be considered as a systemic measure of aging process. Convergence of the (sex-specific) FI age patterns for low and high FI groups by extreme ages might reflect the limit of the FI-specific (or systemic) age as well as the limit of adaptation capacity in aging individuals.

An ongoing debate in demography has focused on whether the human lifespan has a maximal natural limit. Taking a mechanistic perspective, and knowing that short telomeres are associated with diminished longevity, we examined whether telomere length dynamics during adult life could set a maximal natural lifespan limit. We define leukocyte telomere length of 5 kb as the ‘telomeric brink’, which denotes a high risk of imminent death. We show that a subset of adults may reach the telomeric brink within the current life expectancy and more so for a 100-year life expectancy. Thus, secular trends in life expectancy should confront a biological limit due to crossing the telomeric brink.