The long term objective of the proposed research is to evaluate current epidemiological trends in major geriatric disorders including cancer, acute coronary heart disease (ACHD), asthma, Alzheimer?s (AD) disease. We will evaluate current and prospective trends in the incidence rates and patients? survival, separately for each of the selected diseases as well as for their combinations, taking into account possible synergism/antagonism between the diseases in samples of aging individuals from the National Long Term Care Survey linked with Medicare Service Use Files (NLTCS-M) and the Surveillance Epidemiology and End Results (SEER) linked with Medicare Service Use Files along with 5% Medicare Service Use Files (SEER-M) as controls. Particular focus of the proposed research will be on evaluating these major epidemiological characteristics considering effects of dependence among diseases and possible recovery from certain diseases on disease free life span. The following specific aims will be addressed: 1) Evaluate cross-sectional age patterns and time trends in incidence, prevalence, recovery, and survival (i.e., mortality from the disease states) rates for elderly individuals of both sexes in the U.S. for four major geriatric conditions specified above using the NLTCS-M and SEER-M. 2) Develop versions of multistate cohort incidence/prevalence/survival models with parametric description of hazard rates. Using these models evaluate time trends for respective health characteristics listed above. 3) Examine the relationships between risks of disease onset in pairs of diseases listed above. Extend the elaborated multi-state models to describe development of co-morbidity. Apply extended models to the joint analyses of data on diseases showing highest connection.

Public Health Relevance

The results of this study will contribute to better understanding connection among major diseases of the elderly in the U.S. population and create an appropriate background for predicting health/well-being/survival characteristics of the U.S. elderly in 2020, 2025 and 2030.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Project (R01)
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Neurological, Aging and Musculoskeletal Epidemiology (NAME)
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Patmios, Georgeanne E
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Duke University
Social Sciences
Schools of Arts and Sciences
United States
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Yashin, Anatoliy I; Arbeev, Konstantin G; Wu, Deqing et al. (2016) How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data. N Am Actuar J 20:201-232
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