Biomedical subjects

A Kulminski

Publications and source records attributed to A Kulminski.

3 recordsLinked to original sources

PubMed2006

Cumulative index of health disorders as an indicator of aging-associated processes in the elderly: results from analyses of the National Long Term Care Survey.

BACKGROUND: We employ an approach based on the elaborated frailty index (FI), which is capable of taking into account variables with mild effect on the aging, health and survival outcomes, and investigate the connections between the FI, chronological age and the aging-associated outcomes in the elderly. METHODS: Cross-sectional analysis of pooled data from the National Long Term Care Survey (NLTCS) assessing health and functioning of the U.S. elderly in 1982, 1984, 1989, 1994, and 1999. RESULTS: Distributions of frequency, residual life span, mortality rate, and relative risk of death are remarkably similar over age and FI. Coefficients of correlation between FI and age are low both for males (0.127, p<.01) and females (0.221, p<.01). The FI-specific age patterns show deceleration at advanced ages. The FI can provide order of magnitude better resolution in estimating mean remaining life span compared to age. Males have smaller FI than females while males' mortality risks are higher. For short-time horizons, the FI and age are largely independently associated with mortality risks. CONCLUSIONS: 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.

Age Factors↗

PubMed2004

Demographic analysis and modeling of human populations exposed to ionizing radiation.

The health effects of ionizing radiation on human populations are often analyzed using epidemiological statistical methods. Because of the complexity of the health consequences of ionizing radiation and the prolonged period during which the consequences emerge, we propose to evaluate these health effects using mathematical models that are based on the best theoretical reasoning and prior biological evidence about disease mechanisms. We believe this will improve the ability of the model to identify health effects and reduce erroneous inferences.

Demography↗

PubMed2004

Modeling nonlinear effects in longitudinal survival data: implications for the physiological dynamics of biological systems.

Despite the wealth of longitudinal data on the health dynamics of human populations, information on covariates (risk factors) changes in those studies has not been systematically and fully exploited. In this work we use the 46-year follow-up of the Framingham Heart Study to analyze dynamics of these risk factors in survival models that go far beyond the standard linear dynamic formulation. We focus on improving the inferences about the physiology of human aging processes and its plasticity and on modeling state trajectories for individuals considering the effect of nonlinear interactions among covariates. We find that using standard statistical methods to construct models describing the age dependence of health status might give rise to surprising results with highly "diluted" dynamics, but with significantly improved statistical criteria. It is found that problems with the dynamics are a consequence of the intrinsic nonlinear nature of these models. We show that evolution of the risk factors measured in the Framingham study is more complicated for females than for males (i.e., female health status is more sensitive to nonlinear interactions among risk factors). We suggest that this is due to the rapid rate of decline of estrogen production after menopause.

Aging↗