Age patterns of incidence of geriatric disease in the U.S. elderly population: Medicare-based analysis

美国老年人群老年疾病发病率的年龄模式:基于医疗保险的分析

阅读:1

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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。