Research ArticleOpen AccessGoogle Scholar indexed
Power Law for the Rates of Different Numbers of Chronic Diseases among Elderly Chinese People
School of Systems Science, Beijing Normal University, Beijing, China
School of Systems Science, Beijing Normal University, Beijing, China
- 1 School of Systems Science, Beijing Normal University, Beijing, China
- 2 School of Systems Science, Beijing Normal University, Beijing, China
Open Journal of Statistics·Volume 06 (2016)·Pages 1155–1165·Published 14 November 2016·DOI10.4236/ojs.2016.66093
Copy link · social · email
Abstract
Chronic disease is an important factor that affect the health of elderly people. We analyzed the 2006 and 2010 data from the Chinese Urban and Rural Elderly Population Surveys, which are nationally representative surveys of elderly people aged 60 years and above. We found that there existed a typical power-law distribution for the rates of different numbers of chronic diseases among elderly Chinese people. A Kolmogorov-Smirnov test indicated that the result was robust, and the power exponents were approximately ?2.5. In addition, a paired t-test was conducted, which demonstrated that the rates of different numbers of chronic diseases did not have significant urban-rural differences, time differences or gender differences.
KeywordsChronic DiseasePower Law DistributionElderly PeopleKolmogorov-Smirnov Test (K-S Test)Paired T-Test
- Freedman, V.A. and Martin, L.G. (2000) Contribution of Chronic Conditions to Aggregate Changes in Old-Age Functioning. American Journal of Public Health, 90, 1755-1760. https://doi.org/10.2105/AJPH.90.11.1755
- Thorpe, K.E. and Howard, D.H. (2006) The Rise in Spending among Medicare Beneficiaries: The Role of Chronic Disease Prevalence and Changes in Treatment Intensity. Health Affairs, 25, 378-388. https://doi.org/10.1377/hlthaff.25.w378
- Wolff, J.L., Starfield, B. and Anderson, G. (2002) Prevalence, Expenditures and Complications of Multiple Chronic Conditions in the Elderly. Archives of Internal Medicine, 162, 2269-2276. https://doi.org/10.1001/archinte.162.20.2269
- Vogeli, C., Shields, A.E., Lee, T.A., Gibson, T.B., Marder, W.D., Weiss, K.B. and Blumenthal, D. (2007) Multiple Chronic Conditions: Prevalence, Health Consequences, and Implications for Quality, Care Management and Costs. JGIM, 22, 391-395. https://doi.org/10.1007/s11606-007-0322-1
- Vassilev, I., Rogers, A., Sanders, C., Cheraghi-Sohi, S., Blickem, C., Brooks, H., Kapadia, D., Reeves, D., Doran, T. and Kennedy, A. (2014) Social Status and Living with a Chronic Illness: An Exploration of Assessment and Meaning Attributed to Work and Employment. Chronic Illness, 10, 273-290. https://doi.org/10.1177/1742395314521641
- Zhang, W.J. and Wei, M. (2015) Disability Level of the Chinese Elderly: Comparison from Multiple Data Sources. Population Research, 39, 34-48.
- Li, S.X., Chen, C.X., Zhao, Y.N. and Ma, S.H. (2013) The Urban Elderly’s in Common Chronic Diseases Life Quality Survey. Modern Preventive Medicine, 40, 3435-3437.
- Shao, J.J. Li, D., Fan, L.J. and Shen, J.L. (2013) Chronic Mental Adaptation: Concepts, Models and Influencing Factors. Journal of Southwest University (Social Sciences Edition), 2, 83-90.
- Wu, D.W., Fan, H. and Xiao, X.Y. (2005) Domestic Present Situation, Trend, Coping Strategies of Chronic Diseases. Chinese Journal of Clinical Rehabilitation, 9, 126-128.
- Zhong, G.F. and Xiang, Y.Z. (2010) Chinese Hypertension Epidemiology and Its Influencing Factors. Chinese Journal of Public Health, 26, 301-302.
- Hu, J.F., Luo, F.J. and Kong, H.N. (2013) Chronic Disease Health Management Research Progress. Chronic Pathematology Journal, 14, 526-529.
- Visser, M. (2013) Zipf’s Law, Power Laws, and Maximum Entropy. New Journal of Physics, 15, 43021-43033. https://doi.org/10.1088/1367-2630/15/4/043021