title: Relationships among insulin resistance, obesity, diagnosis of the metabolic syndrome and cardio-metabolic risk.
abstract: The aim of this study is to test the hypotheses that: 1) diagnosing the metabolic syndrome does not effectively identify insulin-resistant (IR) individuals; and 2) waist circumference (WC) is no better than body mass index (BMI) in predicting insulin resistance or the components of the metabolic syndrome (MetS). Measurements of BMI, WC, blood pressure, and fasting plasma glucose, insulin (FPI), triglycerides (TG), and HDL-cholesterol (HDL-C) concentrations were made in 1,300 adults, without known cardiovascular disease (CVD) or drug treatment of hypertension or diabetes. Receiver operating characteristic curves were used to determine the ability of the MetS, and its components, to identify IR individuals. In addition, comparisons were made of CVD risk factors following division of the population into quartiles of FPI concentrations, and univariate and multiple regression analysis used to compare the ability of WC, BMI, and FPI as predictors of MetS components. The MetS was no more effective in identifying IR individuals than several individual components (sensitivity~40%), and IR individuals not identified were at significantly increased CVD risk. FPI concentration was the best predictor of an abnormal glucose, TG, and HDL-C, whereas the adiposity indices were better predictors of abnormal blood pressure. The relationship between BMI and WC with the MetS and its components seemed comparable.
authors.affiliation: Hospital Interzonal San Martín, La Plata, Buenos Aires, Argentina. salazarlandea@gmail.com
authors.forename: Martin R
authors.initials: MR
authors.lastname: Salazar
authors.forename: Horacio A
authors.initials: HA
authors.lastname: Carbajal
authors.forename: Walter G
authors.initials: WG
authors.lastname: Espeche
authors.forename: Carlos A
authors.initials: CA
authors.lastname: Dulbecco
authors.forename: Marcelo
authors.initials: M
authors.lastname: Aizpurúa
authors.forename: Alberto G
authors.initials: AG
authors.lastname: Marillet
authors.forename: Raúl F
authors.initials: RF
authors.lastname: Echeverría
authors.forename: Gerald M
authors.initials: GM
authors.lastname: Reaven
mesh_terms: D050154:Adiposity; D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001118:Argentina; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000097:blood / Q000453:epidemiology* / Q000503:physiopathology; D016009:Chi-Square Distribution; D008076:Cholesterol, HDL / Q000097:blood; D005260:Female; D006801:Humans; D007328:Insulin / Q000097:blood; D007333:Insulin Resistance; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D008875:Middle Aged; D009765:Obesity / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D011237:Predictive Value of Tests; D015995:Prevalence; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D014280:Triglycerides / Q000097:blood; D055105:Waist Circumference; D055815:Young Adult
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D008076:Cholesterol, HDL; D007328:Insulin; D014280:Triglycerides