title: [Identification of individuals with insulin resistance by means of clinical measurements and routine biochemical markers. Construction of an individual risk index].
abstract: BACKGROUND
  This study aimed to know the markers and routine biochemical measures that are associated to the insulin resistance (IR) and to develop an index of individual IR risk from them.
  
  
  METHODS
  Cross-sectional study made in Primary Health Care population of both genders between 40 and 74 years (n = 2,143). A representative sample was obtained by simple random sampling of 305 patients after excluding the diabetic subjects. Sociodemographic variables, background, examinations, routine analyses as well as fasting insulin levels were obtained. IR was considered if HOMA was higher than 2.9. A step by step logistic regression was done to obtain the best variables to predict IR. A logistic equation, categorical scale and simple additive scale from the beta coefficients was then constructed and was compared with other instruments designed to predict IR.
  
  
  RESULTS
  IR prevalence was 25.2%. There were no differences between genders or by age. The four variables that entered the model were fasting plasma glucose, BMI, HDL cholesterol and diastolic blood pressure. The logistic model had good adjustment. The logistic equation was: IR = 1/ 1 + exp (-[-21.011) - [0.119 * fasting plasma glucose] - [0.231 * BMI] - [-0.046 * HDL cholesterol] - [0.048 * diastolic blood pressure]). The scale constructed assesses each subject between -1 and 7 points; cutoff to predict IR was established at 3.5 points, obtaining a sensitivity and specificity similar to the McAuley index and better than the triglycerides/HDL cholesterol ratio, the first model of Stern and the diagnosis of metabolic syndrome according to ATP-III.
  
  
  CONCLUSIONS
  A very easy-to-use instrument has been obtained to predict IR by means of exploratory measures and routine biochemical measures, which makes it possible to select the patients at the greatest risk in order to intensify preventive actions in them.
authors.affiliation: Centro de Salud Ventanielles-Colloto, Oviedo, Asturias, España. ldiaz@papps.org
authors.forename: L
authors.initials: L
authors.lastname: Díaz González
authors.forename: S
authors.initials: S
authors.lastname: Suárez García
authors.forename: V
authors.initials: V
authors.lastname: López Fernández
authors.forename: A
authors.initials: A
authors.lastname: Alvarez Cosmea
authors.forename: M T
authors.initials: MT
authors.lastname: Arias García
authors.forename: F
authors.initials: F
authors.lastname: Alvarez Menéndez
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism; D001794:Blood Pressure; D015992:Body Mass Index; D008076:Cholesterol, HDL / Q000097:blood; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007333:Insulin Resistance; D008297:Male; D024821:Metabolic Syndrome / Q000175:diagnosis*; D008875:Middle Aged; D018570:Risk Assessment
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D008076:Cholesterol, HDL