Guilaine Boursier1, Ariane Sultan2, Nicolas Molinari3, Laurent Maimoun4, Catherine Boegner2, Marion Picandet2, Nils Kuster1, Anne-Sophie Bargnoux1, Stéphanie Badiou1, Anne-Marie Dupuy1, Jean-Paul Cristol5, Antoine Avignon2. 1. PHYMEDEXP, CNRS, INSERM, Univ Montpellier, Department of Biochemistry and Hormonology, CHU Montpellier, Montpellier, France. 2. PHYMEDEXP, CNRS, INSERM, Univ Montpellier, Department of Nutrition and Diabetes, CHU Montpellier, Montpellier, France. 3. MISTEA, INRA, Univ Montpellier, Department of Statistics, CHU Montpellier, Montpellier, France. 4. Department of Nuclear Medicine, CHU Montpellier, Univ Montpellier, Montpellier, France. 5. PHYMEDEXP, CNRS, INSERM, Univ Montpellier, Department of Biochemistry and Hormonology, CHU Montpellier, Montpellier, France. Electronic address: jp-cristol@chu-montpellier.fr.
Abstract
OBJECTIVE: Assessment of insulin resistance (IR) is essential in non-diabetic patients with obesity. Thus study aims to identify the best determinants of IR and to propose an original approach for routine assessment of IR in obesity. DESIGN AND PATIENTS: All adult with obesity defined by a body mass index ≥30kg/m2, evaluated in the Nutrition Department between January 2010 and January 2015 were included in this cross-sectional study. Patients with diabetes were excluded. IR was diagnosed according to the HOMA-IR. Based on a logistic regression, we determined a composite score of IR. We then tested the variables with a principal component analysis and a hierarchical clustering analysis. RESULTS: A total of 498 patients with obesity were included. IR was associated with grade III obesity (OR=2.6[1.6-4.4], p<0.001), HbA1c≥5.7% (OR=2.6[1.7-4.0], p<0.001), hypertriglyceridemia >1.7mmol/l (OR=3.0[2.0-4.5], p<0.001) and age (OR=0.98[0.96-0.99], p=0.002). Exploratory visual analysis using factor map and clustering analysis revealed that lipid and carbohydrates metabolism abnormalities were correlated with insulin resistance but not with excessive fat accumulation and low-grade inflammation. CONCLUSIONS: Our results highlight the interest of simple blood tests such as HbA1c and triglyceride determination, which associated with BMI, may be widely available tools for screening IR in obese patients.
OBJECTIVE: Assessment of insulin resistance (IR) is essential in non-diabeticpatients with obesity. Thus study aims to identify the best determinants of IR and to propose an original approach for routine assessment of IR in obesity. DESIGN AND PATIENTS: All adult with obesity defined by a body mass index ≥30kg/m2, evaluated in the Nutrition Department between January 2010 and January 2015 were included in this cross-sectional study. Patients with diabetes were excluded. IR was diagnosed according to the HOMA-IR. Based on a logistic regression, we determined a composite score of IR. We then tested the variables with a principal component analysis and a hierarchical clustering analysis. RESULTS: A total of 498 patients with obesity were included. IR was associated with grade III obesity (OR=2.6[1.6-4.4], p<0.001), HbA1c≥5.7% (OR=2.6[1.7-4.0], p<0.001), hypertriglyceridemia >1.7mmol/l (OR=3.0[2.0-4.5], p<0.001) and age (OR=0.98[0.96-0.99], p=0.002). Exploratory visual analysis using factor map and clustering analysis revealed that lipid and carbohydratesmetabolism abnormalities were correlated with insulin resistance but not with excessive fat accumulation and low-grade inflammation. CONCLUSIONS: Our results highlight the interest of simple blood tests such as HbA1c and triglyceride determination, which associated with BMI, may be widely available tools for screening IR in obesepatients.