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.

Figure 1

Age-specific rates of total mortality and disease incidence calculated using NLTCS-Medicare (open dots) and SEER-Medicare (close dots). Rates for different diseases are rescaled to use the same scale on all plots to compare rates for different diseases: the original rate (per 100,000) can be calculated by multiplying the values obtained from plot by the rescaled factor. Upper panel represents diseases with age patterns of the first and second types (i.e., a monotonic increase of incidence with age with subsequent leveling off and decline) and lower panel represents the results of the age pattern of third type (a monotonic decline in incidence with age or decline following short period of increase)