Abstract

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.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
3R01AG032319-04S1
Application #
8331020
Study Section
Neurological, Aging and Musculoskeletal Epidemiology (NAME)
Program Officer
Patmios, Georgeanne E
Project Start
2008-09-01
Project End
2013-08-31
Budget Start
2011-09-30
Budget End
2012-08-31
Support Year
4
Fiscal Year
2011
Total Cost
$137,868
Indirect Cost

  Institution

Name
Duke University
Department
Social Sciences
Type
Schools of Arts and Sciences
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705

  Publications

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
Stallard, Eric (2016) Compression of Morbidity and Mortality: New Perspectives. N Am Actuar J 20:341-354
An, Ping; Miljkovic, Iva; Thyagarajan, Bharat et al. (2014) Genome-wide association study identifies common loci influencing circulating glycated hemoglobin (HbA1c) levels in non-diabetic subjects: the Long Life Family Study (LLFS). Metabolism 63:461-8
Akushevich, Igor; Kravchenko, Julia; Ukraintseva, Svetlana et al. (2013) Morbidity risks among older adults with pre-existing age-related diseases. Exp Gerontol 48:1395-401
Akushevich, Igor; Kravchenko, Julia; Ukraintseva, Svetlana et al. (2013) Recovery and survival from aging-associated diseases. Exp Gerontol 48:824-30
Akushevich, Igor; Kravchenko, Julia; Ukraintseva, Svetlana et al. (2013) Time trends of incidence of age-associated diseases in the US elderly population: Medicare-based analysis. Age Ageing 42:494-500
Akushevich, Igor; Kravchenko, Julia; Ukraintseva, Svetlana et al. (2013) Circulatory Diseases in the U.S. Elderly in the Linked National Long-Term Care Survey-Medicare Database: Population-Based Analysis of Incidence, Comorbidity, and Disability. Res Aging 35:437-458
Yashin, A I; Arbeev, K G; Akushevich, I et al. (2012) The quadratic hazard model for analyzing longitudinal data on aging, health, and the life span. Phys Life Rev 9:177-88; discussion 195-7
Akushevich, Igor; Kravchenko, Julia; Ukraintseva, Svetlana et al. (2012) Age patterns of incidence of geriatric disease in the U.S. elderly population: Medicare-based analysis. J Am Geriatr Soc 60:323-7
Arbeev, Konstantin G; Ukraintseva, Svetlana V; Kulminski, Alexander M et al. (2012) Effect of the APOE Polymorphism and Age Trajectories of Physiological Variables on Mortality: Application of Genetic Stochastic Process Model of Aging. Scientifica (Cairo) 2012:

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