公共衛生學系Ching-Kuo WeiMING-CHIN YANGSyi SuMing-Chin Yang2018-09-102018-09-102012http://www.scopus.com/inward/record.url?eid=2-s2.0-84864027615&partnerID=MN8TOARShttp://scholars.lib.ntu.edu.tw/handle/123456789/373329This study used data mining techniques to investigate disease forms in various administrative areas and to analyze the differences among various administrative areas in order to further draw up a disease distribution map. It is hoped that may help formulate future public health strategies and to allocate medical resources more appropriately. The major disease forms for residents under the age of 60 were hypertension, hyperglycemia and hyperlipidemia. In regard to the neighboring areas, three neighboring areas, A1, A3, and B9, shared the same disease problems with A4, A5, and B3, while two mountain-area cities, B7 and C10, experienced higher instances of liver function impairment. In terms of the clustering phenomenon among municipally graded administrative areas, the major health problems in Grade A cities were hypertension, hyperglycemia, and hyperlipidemia. The health problems such as liver function impairment and renal dysfunction were more frequently observed in Grade B and Grade C cities. ? Springer Science+Business Media, LLC 2011.345808 bytesapplication/pdfCluster analysis; Data mining; Disease distribution map; Public health[SDGs]SDG3adult; aged; article; cluster analysis; community living; controlled study; data mining; female; geographic distribution; government; health care planning; human; hyperglycemia; hyperlipidemia; hypertension; kidney dysfunction; liver function; major clinical study; male; public health problem; resource allocation; screening; Taiwan; Adult; Aged; Cluster Analysis; Data Mining; Epidemiologic Methods; Female; Humans; Hypercholesterolemia; Hyperlipidemias; Liver Diseases; Male; Mass Screening; Middle Aged; Population Surveillance; Program Development; Renal Insufficiency; Taiwanjournal article10.1007/s10916-011-9664-7