title: Predictors of insulin resistance in the obese with metabolic syndrome.
abstract: BACKGROUND
  In the obese, the metabolic syndrome (MetS) is assumed to reflect insulin resistance.
  
  
  OBJECTIVE
  To determine the predictors of insulin resistance in obese subjects with MetS.
  
  
  METHODS
  We used the 90th percentile of the homeostasis model assessment (HOMA) to define insulin resistance in 4958 nondiabetic adults evaluated in the National Health and Nutrition Examination Surveys, 1999-2004, and compared the 373 obese subjects who were insulin-resistant (HOMA 9.52+/-5.73) to a control group of 373 obese who had the highest sensitivity to insulin (HOMA 1.79+/-0.44).
  
  
  METHODS
  MetS was present in 312 (83.6%) obese with insulin resistance and in 156 (41.8%) obese from the insulin-sensitive control group. Demographic, metabolic, and lifestyle variables were analyzed with logistic regression.
  
  
  RESULTS
  In a logistic model of insulin resistance given the presence of MetS, the significant predictors were triglycerides (P=0.0021), body mass index (P=0.0096), HDL-cholesterol (P=0.0098), age (P=0.0242) and smoking (P=0.0366).
  
  
  CONCLUSIONS
  Cross-sectional design prevents elucidation of causality for the association between insulin resistance and MetS.
  
  
  CONCLUSIONS
  Insulin resistance is not an obligatory correlate of MetS in the obese. Its likelihood can be predicted by cigarette smoking and by the severity of obesity and dyslipidemia.
authors.affiliation: The Zucker Hillside Hospital, 59-75 263rd Street, Glen Oaks, NY 11004, USA. pmanu@lij.edu
authors.forename: Peter
authors.initials: P
authors.lastname: Manu
authors.forename: James
authors.initials: J
authors.lastname: Tsang
authors.forename: Barbara A
authors.initials: BA
authors.lastname: Napolitano
authors.forename: Martin L
authors.initials: ML
authors.lastname: Lesser
authors.forename: Christoph U
authors.initials: CU
authors.lastname: Correll
mesh_terms: D000328:Adult; D015992:Body Mass Index; D008076:Cholesterol, HDL / Q000097:blood; D003430:Cross-Sectional Studies; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology / Q000378:metabolism; D050171:Dyslipidemias / Q000453:epidemiology / Q000378:metabolism; D005260:Female; D006706:Homeostasis / Q000502:physiology; D006801:Humans; D007249:Inflammation / Q000453:epidemiology / Q000378:metabolism; D007333:Insulin Resistance / Q000502:physiology*; D016015:Logistic Models; D008297:Male; D024821:Metabolic Syndrome / Q000453:epidemiology* / Q000378:metabolism*; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology* / Q000378:metabolism*; D011237:Predictive Value of Tests; D012307:Risk Factors; D012907:Smoking / Q000453:epidemiology / Q000378:metabolism; D014280:Triglycerides / Q000097:blood
chemical_list: D008076:Cholesterol, HDL; D014280:Triglycerides