title: Prediction of the presence of insulin resistance using general health checkup data in Japanese employees with metabolic risk factors.
abstract: OBJECTIVE
  The aim of the current study was to develop a predictive model of insulin resistance using general health checkup data in Japanese employees with one or more metabolic risk factors.
  
  
  METHODS
  We used a database of 846 Japanese employees with one or more metabolic risk factors who underwent general health checkup and a 75-g oral glucose tolerance test (OGTT). Logistic regression models were developed to predict existing insulin resistance evaluated using the Matsuda index. The predictive performance of these models was assessed using the C statistic.
  
  
  RESULTS
  The C statistics of body mass index (BMI), waist circumference and their combined use were 0.743, 0.732 and 0.749, with no significant differences. The multivariate backward selection model, in which BMI, the levels of plasma glucose, high-density lipoprotein (HDL) cholesterol, log-transformed triglycerides and log-transformed alanine aminotransferase and hypertension under treatment remained, had a C statistic of 0.816, with a significant difference compared to the combined use of BMI and waist circumference (p＜0.01). The C statistic was not significantly reduced when the levels of log-transformed triglycerides and log-transformed alanine aminotransferase and hypertension under treatment were simultaneously excluded from the multivariate model (p=0.14). On the other hand, further exclusion of any of the remaining three variables significantly reduced the C statistic (all p＜0.01).
  
  
  CONCLUSIONS
  When predicting the presence of insulin resistance using general health checkup data in Japanese employees with metabolic risk factors, it is important to take into consideration the BMI and fasting plasma glucose and HDL cholesterol levels.
authors.affiliation: Department of Metabolic Medicine, Osaka University Graduate School of Medicine.
authors.forename: Mitsuyoshi
authors.initials: M
authors.lastname: Takahara
authors.forename: Naoto
authors.initials: N
authors.lastname: Katakami
authors.forename: Hideaki
authors.initials: H
authors.lastname: Kaneto
authors.forename: Midori
authors.initials: M
authors.lastname: Noguchi
authors.forename: Iichiro
authors.initials: I
authors.lastname: Shimomura
mesh_terms: D044466:Asian People; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000209:etiology; D008076:Cholesterol, HDL / Q000378:metabolism*; D005260:Female; D005951:Glucose Tolerance Test; D006801:Humans; D007333:Insulin Resistance; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010808:Physical Examination / Q000706:statistics & numerical data*; D012372:ROC Curve; D012307:Risk Factors; D014280:Triglycerides / Q000378:metabolism*; D055105:Waist Circumference
chemical_list: D008076:Cholesterol, HDL; D014280:Triglycerides