Comparing abilities of different lipid measures in diagnosis of insulin resistance: a Survey of Risk Factors of Non-Communicable Diseases (SuRFNCD-2007) study.
BACKGROUND
Dyslipidemia is a distinguishing characteristic of subjects with insulin resistance. Our aim was to determine the predictive abilities and appropriate cutoffs of different lipid variables for insulin resistance.


METHODS
We used the data of the individuals without history of known diabetes mellitus, aged 25-64 years, from the third national Survey of Risk Factors of Non-Communicable Diseases (SuRFNCD-2007). Fasting blood was collected for lipids, glucose and insulin. Receiver operating characteristics (ROC) curves were used to evaluate the predictive abilities of lipid measures for insulin resistance reflected by a homeostasis model assessment value >1.775. The optimal cutoffs of the selected measures were determined using the maximum Youden index and the point closest to (0,1) on the ROC curve, and were compared with metabolic syndrome definitions to diagnose hyperinsulinemia (fasting insulin ≥10 in men and ≥11 U/L in women).


RESULTS
Among lipid measures, low-density lipoprotein cholesterol (LDL-C) was the most tenuously related parameter to insulin resistance. On the contrary, triglycerides and triglycerides to high-density lipoprotein cholesterol ratio (triglycerides/HDL-C) had the highest abilities to determine insulin resistance, regardless of sex and body mass index (BMI). The optimal triglycerides and triglycerides/HDL-C cutoffs were 145 mg/dL and 3.75 for men and 109 mg/dL and 3.00 for women, respectively, which had similar abilities to metabolic syndrome definitions in identifying hyperinsulinemia.


CONCLUSIONS
Among lipid measures, triglycerides and the triglycerides/HDL-C ratio have the highest predictive abilities for insulin resistance, and the diagnostic values of their appropriate cutoffs are similar to those of metabolic syndrome definitions.
Endocrinology and Metabolism Research Center, Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran, Iran. esteghamati@tums.ac.ir
Alireza
A
Esteghamati
Ali
A
Zandieh
Basira
B
Zandieh
Omid
O
Khalilzadeh
Sadaf
S
Esteghamati
Alipasha
A
Meysamie
Manouchehr
M
Nakhjavani
D000328:Adult; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure; D015992:Body Mass Index; D003430:Cross-Sectional Studies; D050171:Dyslipidemias / Q000097:blood / Q000175:diagnosis* / Q000453:epidemiology / Q000503:physiopathology; D005260:Female; D044882:Glucose Metabolism Disorders / Q000097:blood / Q000175:diagnosis* / Q000453:epidemiology / Q000503:physiopathology; D006306:Health Surveys; D006801:Humans; D007328:Insulin / Q000097:blood; D007333:Insulin Resistance; D007492:Iran / Q000453:epidemiology; D016014:Linear Models; D008055:Lipids / Q000097:blood*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors; D055105:Waist Circumference
D015415:Biomarkers; D001786:Blood Glucose; D007328:Insulin; D008055:Lipids