Age patterns of incidence of geriatric disease in the U.S. elderly population: Medicare-based analysis.
Abstract
OBJECTIVES: To use the Medicare Files of Service Use (MFSU) to evaluate patterns in
the incidence of aging-related diseases in the U.S. elderly population. DESIGN: Age-specific
incidence rates of 19 aging-related diseases were evaluated using the National Long
Term Care Survey (NLTCS) and the Surveillance, Epidemiology, and End Results (SEER)
Registry data, both linked to MFSU (NLTCS-M and SEER-M, respectively), using an algorithm
developed for individual date at onset evaluation. SETTING: A random sample from the
entire U.S. elderly population (Medicare beneficiaries) was used in NLTCS, and the
SEER Registry data covers 26% of the U.S. population. PARTICIPANTS: Thirty-four thousand
seventy-seven individuals from NLTCS-M and 2,154,598 from SEER-M. MEASUREMENTS: Individual
medical histories were reconstructed using information on diagnoses coded in MFSU,
dates of medical services and procedures, and Medicare enrollment and disenrollment.
RESULTS: The majority of diseases (e.g., prostate cancer, asthma, and diabetes mellitus)
had a monotonic decline (or decline after a short period of increase) in incidence
with age. A monotonic increase in incidence with age with a subsequent leveling off
and decline was observed for myocardial infarction, stroke, heart failure, ulcer,
and Alzheimer's disease. An inverted U-shaped age pattern was detected for lung and
colon carcinomas, Parkinson's disease, and renal failure. The results obtained from
the NLTCS-M and SEER-M were in agreement (excluding an excess for circulatory diseases
in the NLTCS-M). A sensitivity analysis proved the stability of the incidence rates
evaluated. CONCLUSION: The developed computational approaches applied to the nationally
representative Medicare-based data sets allow reconstruction of age patterns of disease
incidence in the U.S. elderly population at the national level with unprecedented
statistical accuracy and stability with respect to systematic biases.
Type
Journal articleSubject
Age DistributionAge Factors
Aged
Aged, 80 and over
Female
Geriatrics
Humans
Incidence
Male
Medicare
United States
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https://hdl.handle.net/10161/14851Published Version (Please cite this version)
10.1111/j.1532-5415.2011.03786.xPublication Info
Akushevich, Igor; Kravchenko, Julia; Ukraintseva, Svetlana; Arbeev, Konstantin; &
Yashin, Anatoliy I (2012). Age patterns of incidence of geriatric disease in the U.S. elderly population: Medicare-based
analysis. J Am Geriatr Soc, 60(2). pp. 323-327. 10.1111/j.1532-5415.2011.03786.x. Retrieved from https://hdl.handle.net/10161/14851.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Igor Akushevich
Research Professor in the Social Science Research Institute
Konstantin Arbeev
Associate Research Professor in the Social Science Research Institute
Konstantin G. Arbeev received the M.S. degree in Applied Mathematics from Moscow State
University (branch in Ulyanovsk, Russia) in 1995 and the Ph.D. degree in Mathematics
and Physics (specialization in Theoretical Foundations of Mathematical Modeling, Numerical
Methods and Programming) from Ulyanovsk State University (Russia) in 1999. He was
a post-doctoral fellow in Max Planck Institute for Demographic Research in Rostock
(Germany) before moving to Duke University in 2004 to work as a Resea
Svetlana Ukraintseva
Research Professor in the Social Science Research Institute
Dr. Ukraintseva studies causes of human aging and related decline in resilience, to
identify genetic and other factors responsible for the increase in mortality risk
with age eventually limiting longevity. She explores complex relationships, including
trade-offs, between physiological aging-changes and risks of major diseases (with
emphasis on Alzheimer’s and cancer), as well as survival, to find new genetic and
other targets for anti-aging interventions and disease prevention. S
Anatoli I. Yashin
Research Professor in the Social Science Research Institute
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