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  • 标题:Analytical hierarchy process model for severity of risk factors associated with type 2 diabetes
  • 本地全文:下载
  • 作者:B. Y. Baha ; G. M. Wajiga ; N. V. Blamah
  • 期刊名称:Scientific Research and Essays
  • 印刷版ISSN:1992-2248
  • 出版年度:2013
  • 卷号:8
  • 期号:39
  • 页码:1906-1910
  • DOI:10.5897/SRE12.665
  • 语种:English
  • 出版社:Academic Journals
  • 摘要:Type 2 diabetes has been an increasing public health problem with an estimated forecast of 300 million around the world by the year 2025. It places a serious constraint on individual’s activities caused by hyperglycemia resulting from defects in insulin secretion, insulin action or both. Although extensive epidemiological researches have shown an association between various risk factors and the development of type 2 diabetes, there has been no research on the measurement or determination of the relative severity of these risk factors regarding their contributions to the incidence and prevalence of type 2 diabetes. In this research, 13 risk factors associated with type 2 diabetes were identified from epidemiological studies. The degree of severity of these risk factors was ascertained by professionals using structured Liket format with 6 choices. The data obtained were used in ranking the risk factors, which assisted in selecting the most contributing risk factors to the development of type 2 diabetes. The result revealed that heredity contributes as high as 0.5388; obesity contributes 0.1038; physical inactivity contributes 0.0230; dietary contributes 0.0230; age contributes 0.1038; IGT contributes 0.1038; and gestational diabetes is 0.1038. This result could serve as input to neural network model.
  • 关键词:Type 2 diabetes; severity; risk factors; analytical hierarchy process; artificial neural network
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