Insulin resistance is associated with central obesity and an increased risk of cardiovascular disease. Our objective is to examine the association between abdominal subcutaneous (SAT) and visceral adipose tissue (VAT) and insulin resistance, to determine which fat depot is a stronger correlate of insulin resistance, and to assess whether there was an interaction between SAT, VAT, and age, sex, or BMI. Participants without diabetes from the Framingham Heart Study (FHS), who underwent multidetector computed tomography to assess SAT and VAT (n = 3,093; 48% women; mean age 50.4 years; mean BMI 27.6 kg/m2), were evaluated. Insulin resistance was measured using the homeostasis model and defined as HOMAIR ≥75th percentile. Logistic regression models, adjusted for age, sex, smoking, alcohol, menopausal status, and hormone replacement therapy use, were used to assess the association between fat measures and insulin resistance. The odds ratio (OR) for insulin resistance per standard deviation increase in SAT was 2.5 (95% confidence interval (CI): 2.2–2.7; P < 0.0001), whereas the OR for insulin resistance per standard deviation increase in VAT was 3.5 (95% CI: 3.1–3.9; P < 0.0001). Overall, VAT was a stronger correlate of insulin resistance than SAT (P < 0.0001 for SAT vs. VAT comparison). After adjustment for BMI, the OR of insulin resistance for VAT was 2.2 (95% CI: 1.9–2.5; P < 0.0001). We observed an interaction between VAT and BMI for insulin (P interaction = 0.0004), proinsulin (P interaction = 0.003), and HOMAIR (P interaction = 0.003), where VAT had a stronger association in obese individuals. In conclusion, SAT and VAT are both correlates of insulin resistance; however, VAT is a stronger correlate of insulin resistance than SAT.
Objective: Volumetric visceral abdominal adipose tissue (VAT) and subcutaneous abdominal adipose tissue (SAT) as measured by computed tomography (CT) are associated with metabolic risk factors. We sought to identify the correlations of VAT and SAT between area-based measures at different anatomic locations with volumetric measurements to identify the optimal anatomic site, and to relate measurements at this site with metabolic risk factors. Methods: We measured SAT and VAT volumes across the total imaging volume, whereas we measured SAT and VAT area at seven predefined anatomic landmarks in 200 participants from the Framingham Heart Study (mean age 54 years, 50% women) who underwent abdominal multi-detector CT. Correlation coefficients were used to assess the association between area measurements and volumes as well as metabolic risk factors stratified by gender. Results: Area-based measurements of SAT and VAT obtained at all anatomic landmarks were strongly associated with SAT and VAT volumes (all r40.93, Po0.0001 and r40.87, Po0.0001, for women and men; respectively). Consistently, area-based measurements of SAT and VAT obtained at L 3/4 were most strongly associated with volumetric measured VAT and SAT independent of age (both r ¼ 0.99 in men, r ¼ 0.96 for SAT and r ¼ 0.99 for VAT in women, all P-value o0.0001) and were similarly correlated with risk factors compared with SAT and VAT volumes (all Po0.05 for fasting plasma glucose, triglycerides, high-density lipoprotein, systolic blood pressure). Conclusion: Among area-based measurements of SAT and VAT, those obtained at the level of L 3/4 were strongly associated with SAT and VAT volumes and cardio-metabolic risk factors in both men and women.
LPA can easily be assessed in LT candidates as part of pretransplant evaluation and was significantly associated with short-term outcome, whereas BMI was not. Assessment of LPA may provide additional information on body composition beyond BMI. However, the clinical utility has to be further evaluated.
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