title: Assessment of triglyceride and cholesterol in overweight people based on multiple linear regression and artificial intelligence model.
abstract: BACKGROUND
  The prevalence of high hyperlipemia is increasing around the world. Our aims are to analyze the relationship of triglyceride (TG) and cholesterol (TC) with indexes of liver function and kidney function, and to develop a prediction model of TG, TC in overweight people.
  
  
  METHODS
  A total of 302 adult healthy subjects and 273 overweight subjects were enrolled in this study. The levels of fasting indexes of TG (fs-TG), TC (fs-TC), blood glucose, liver function, and kidney function were measured and analyzed by correlation analysis and multiple linear regression (MRL). The back propagation artificial neural network (BP-ANN) was applied to develop prediction models of fs-TG and fs-TC.
  
  
  RESULTS
  The results showed there was significant difference in biochemical indexes between healthy people and overweight people. The correlation analysis showed fs-TG was related to weight, height, blood glucose, and indexes of liver and kidney function; while fs-TC was correlated with age, indexes of liver function (P < 0.01). The MRL analysis indicated regression equations of fs-TG and fs-TC both had statistic significant (P < 0.01) when included independent indexes. The BP-ANN model of fs-TG reached training goal at 59 epoch, while fs-TC model achieved high prediction accuracy after training 1000 epoch.
  
  
  CONCLUSIONS
  In conclusions, there was high relationship of fs-TG and fs-TC with weight, height, age, blood glucose, indexes of liver function and kidney function. Based on related variables, the indexes of fs-TG and fs-TC can be predicted by BP-ANN models in overweight people.
authors.affiliation: Department of Laboratory Medicine, First Affiliated Hospital, College of Medicine, Zhejiang University, Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Ma
authors.affiliation: The State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 79 Qingchun Rd., Hangzhou City, 310003, China.
authors.forename: Jiong
authors.initials: J
authors.lastname: Yu
authors.affiliation: Key Laboratory for Laboratory Medicine of Ministry of Education, Wenzhou Medical University, Wenzhou, Zhejiang, China.
authors.forename: Guangshu
authors.initials: G
authors.lastname: Hao
authors.affiliation: Key Laboratory for Laboratory Medicine of Ministry of Education, Wenzhou Medical University, Wenzhou, Zhejiang, China.
authors.forename: Dan
authors.initials: D
authors.lastname: Wang
authors.affiliation: Key Laboratory for Laboratory Medicine of Ministry of Education, Wenzhou Medical University, Wenzhou, Zhejiang, China.
authors.forename: Yanni
authors.initials: Y
authors.lastname: Sun
authors.affiliation: Key Laboratory for Laboratory Medicine of Ministry of Education, Wenzhou Medical University, Wenzhou, Zhejiang, China.
authors.forename: Jianxin
authors.initials: J
authors.lastname: Lu
authors.affiliation: The State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 79 Qingchun Rd., Hangzhou City, 310003, China. chc2016@sina.com.|Key Laboratory for Laboratory Medicine of Ministry of Education, Wenzhou Medical University, Wenzhou, Zhejiang, China. chc2016@sina.com.
authors.forename: Hongcui
authors.initials: H
authors.lastname: Cao
authors.affiliation: Central laboratory, The First Affiliated Hospital of Wenzhou Medical University, Nanbaixiang street, Ouhai District, Wenzhou, 325000, China. singlelin@yeah.net.
authors.forename: Feiyan
authors.initials: F
authors.lastname: Lin
mesh_terms: D000328:Adult; D016022:Case-Control Studies; D002784:Cholesterol / Q000097:blood*; D005215:Fasting; D006801:Humans; D016014:Linear Models; D008875:Middle Aged; D008954:Models, Biological; D016571:Neural Networks, Computer; D050177:Overweight / Q000097:blood*; D014280:Triglycerides / Q000097:blood*
chemical_list: D014280:Triglycerides; D002784:Cholesterol
keywords: Back propagation artificial neural network; Cholesterol; Overweight; Regression; Triglyceride