Table of Contents
ISRN Geriatrics
Volume 2013 (2013), Article ID 943418, 15 pages
Research Article

Population-Based Analysis of Incidence Rates of Cancer and Noncancer Chronic Diseases in the US Elderly Using NLTCS/Medicare-Linked Database

1Center for Population Health and Aging, Duke University, P.O. Box 90408, Durham, NC 27708, USA
2Division of Surgical Sciences, Department of Surgery, Duke University Medical Center, Durham, NC 27705, USA

Received 19 November 2012; Accepted 22 January 2013

Academic Editors: S. Vieira, Å. Wahlin, and R. Wirth

Copyright © 2013 I. Akushevich et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The age, disability, and comorbidity patterns of incidence rates of cancer and chronic noncancer diseases such as heart failure, diabetes mellitus, asthma, Parkinson's disease, Alzheimer's disease, skin melanoma, and cancers of breast, prostate, lung, and colon were studied for the US elderly population (aged 65+) using the National Long-Term Care Survey (NLTCS) data linked to Medicare records for 1991–2005. Opposite to breast cancer and asthma, incidence rates of heart failure and Alzheimer's diseases were increasing with age. Higher incidence rates of heart failure, diabetes, asthma, and Parkinson's and Alzheimer's diseases were observed among individuals with severe disabilities or/and comorbidities, while rates of breast and prostate cancers were higher among those with minor disabilities or fewer comorbidities. Our results were in agreement with those obtained from other epidemiological datasets, thus suggesting that Medicare administrative records can provide nationally representative incidence rates. Detailed sensitivity analysis that focused on the effects of alternative onset definitions, latent censoring, study design, and other procedural uncertainties showed the stability of reconstructed incidence rates. This Medicare-linked dataset can be used for studying highly debated effects of new medical technologies on aging-related diseases burden and future Medicare costs.