Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/52461
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJing Daien_US
dc.contributor.authorCheng Zien_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.contributor.authorZhanqiong Heen_US
dc.date.accessioned2018-09-04T09:25:35Z-
dc.date.available2018-09-04T09:25:35Z-
dc.date.issued2013-01-01en_US
dc.identifier.issn21945357en_US
dc.identifier.other2-s2.0-84872796130en_US
dc.identifier.other10.1007/978-3-642-35443-4-22en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84872796130&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/52461-
dc.description.abstractChina's economy has experienced remarkable growth in past 20 years. With rapid economic growth, Chinese people have enjoyed significant nutritional improvements. Meanwhile, with the changes in lifestyle, dietary behavior and other aspects, the prevalence of obesity and high blood pressure has also increased quickly. The relationship between obesity, high blood pressure and risk of chronic noncommunicable diseases is continuous and consistent. The higher BMI and blood pressure, the greater the chance of heart attack, stroke, kidney disease and etc. The objective of this paper is to analyze how socio-demographic and socioeconomic factors affect the prevelance of obesity and high blood pressure, and find the dependence structure between obesity and high blood pressure (HBP) with the help of copula functions. Computational results were obtained by R programme, and the results show that Frank copula model provides a better estimation than others. The empirical findings of this paper provide useful insights which can be expected to be of interest to public health sectors and local government in the formulation of health management policies especially on obesity, high blood pressure, and related chronic non-communicable disease. © 2013 Springer-Verlag Berlin Heidelberg.en_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titleAnalyzing dependence structure of obesity and high blood pressure: A copula approachen_US
dc.typeBook Seriesen_US
article.title.sourcetitleAdvances in Intelligent Systems and Computingen_US
article.volume200 AISCen_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsKunming University of Science and Technologyen_US
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.