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Sagittal abdominal diameter as a marker for epicardial adipose tissue in premenopausal women

Open AccessPublished:April 01, 2013DOI:https://doi.org/10.1016/j.metabol.2013.01.022

      Abstract

      Objective

      Accumulation of epicardial (EAT) adipose tissue is associated with the development of an unfavorable metabolic risk profile. Gold standard methods used to assess this fat depot are not routinely applicable in the clinic. Anthropometric measures, including the sagittal abdominal diameter (SAD), have emerged as surrogate markers of visceral obesity. We determined the relationship between EAT measurement and cardiometabolic risk parameters and the potential use of the SAD, compared with other anthropometric parameters, as a practical estimation of EAT.

      Materials/Methods

      Sixty-seven premenopausal women were evaluated. The anthropometric parameters that were measured included waist circumference, SAD, body mass index and waist-to-hip ratio. EAT was determined by echocardiogram. Visceral adipose tissue (VAT) was determined by abdominal ultrasound. Insulin sensitivity was assessed by the hyperglycemic clamp.

      Results

      The accumulation of EAT was correlated with impaired insulin sensitivity and decreased adiponectin. All of the anthropometric measurements were correlated with EAT. Interestingly, EAT was most significantly correlated with the SAD. From the ROC analysis, we found that the SAD measurements were very accurate, presenting the highest area under the curve for EAT (0.81; p<0.01) when compared with the other measurements. In the multiple linear regression analysis, EAT was moderately predicted by the SAD (R2=0.25; p<0.001).

      Conclusion

      SAD, a simple anthropometric measure, accurately estimated EAT and thus represents a clinically useful non-invasive marker that can identify patients with EAT accumulation.

      Abbreviations:

      ANOVA (analysis of variances), BMI (body mass index), EAT (epicardial adipose tissue), GIR (glucose infusion rate), ISI (insulin sensitivity index), ROC analysis (receiving operating characteristic curve analysis), SAD (sagittal abdominal diameter), VAT (visceral adipose tissue), WC (waist circumference)

      Keywords

      1. Introduction

      The accumulation of specific fat depots such as epicardial adipose tissue (EAT) has been associated with poor metabolic outcomes [
      • Chen X.
      • Jiao Z.
      • Wang L.
      • et al.
      Roles of human epicardial adipose tissue in coronary artery atherosclerosis.
      ]. Human EAT is a visceral adipose tissue (VAT), but it is a visceral thoracic fat. In pathological situations, EAT can locally affect the heart and coronary arteries through vasocrine or paracrine secretion of pro-inflammatory cytokines [
      • Iacobellis G.
      • Malavazos A.E.
      • Corsi M.M.
      Epicardial fat: From the biomolecular aspects to the clinical practice.
      ]. EAT has been recognized as a potential cardiac risk marker that contributes to the development of an unfavorable metabolic profile in obesity [
      • Chen X.
      • Jiao Z.
      • Wang L.
      • et al.
      Roles of human epicardial adipose tissue in coronary artery atherosclerosis.
      ,
      • Fain J.N.
      • Sacks H.S.
      • Bahouth S.W.
      • et al.
      Human epicardial adipokine messenger rnas: Comparisons of their expression in substernal, subcutaneous, and omental fat.
      ].
      There is a strong correlation between generalized adiposity and the amount of EAT as well as between EAT and VAT [
      • Silaghi A.C.
      • Poanta L.
      • Valea A.
      • et al.
      Is epicardial adipose tissue, assessed by echocardiography, a reliable method for visceral adipose tissue prediction?.
      ]. The gold standard methods used to assess fat depots are expensive and have limited availability for routine clinical application. Anthropometric measurements are being investigated as indicators of fatty depots in many populations [
      • Pouliot M.C.
      • Despres J.P.
      • Lemieux S.
      • et al.
      Waist circumference and abdominal sagittal diameter: Best simple anthropometric indexes of abdominal visceral adipose tissue accumulation and related cardiovascular risk in men and women.
      ,
      • Riserus U.
      • de Faire U.
      • Berglund L.
      • et al.
      Sagittal abdominal diameter as a screening tool in clinical research: Cutoffs for cardiometabolic risk.
      ,
      • Shen W.
      • Chen J.
      Application of imaging and other noninvasive techniques in determining adipose tissue mass.
      ,
      • Kahn H.S.
      • Simoes E.J.
      • Koponen M.
      • et al.
      The abdominal diameter index and sudden coronary death in men.
      ,
      • Sampaio L.R.
      • Simoes E.J.
      • Assis A.M.
      • et al.
      Validity and reliability of the sagittal abdominal diameter as a predictor of visceral abdominal fat.
      ].
      The classic anthropometric parameters used to assess obesity are body mass index (BMI), waist circumference (WC), and waist-hip ratio [
      • Pouliot M.C.
      • Despres J.P.
      • Lemieux S.
      • et al.
      Waist circumference and abdominal sagittal diameter: Best simple anthropometric indexes of abdominal visceral adipose tissue accumulation and related cardiovascular risk in men and women.
      ]. The sagittal abdominal diameter (SAD) is not widely used to gauge obesity, but an increasing number of studies have demonstrated excellent performance of this novel anthropometric measure in the assessment of VAT, cardiometabolic risk and mortality [
      • Riserus U.
      • de Faire U.
      • Berglund L.
      • et al.
      Sagittal abdominal diameter as a screening tool in clinical research: Cutoffs for cardiometabolic risk.
      ,
      • Kahn H.S.
      • Simoes E.J.
      • Koponen M.
      • et al.
      The abdominal diameter index and sudden coronary death in men.
      ,
      • Yim J.Y.
      • Kim D.
      • Lim S.H.
      • et al.
      Sagittal abdominal diameter is a strong anthropometric measure of visceral adipose tissue in the asian general population.
      ]. However, there are no reports evaluating the relationship between the SAD measured anthropometrically and EAT.
      Considering the difficulty of evaluating EAT in clinical practice, and the promising findings related to the SAD, we investigated the potential use of the SAD for the practical estimation of EAT. Additionally, we assessed the relationship between EAT measurement and cardiometabolic risk parameters.

      2. Methods

      A cross-sectional study was conducted with 67 women with different glucose tolerance levels (n=29 with type 2 diabetes). The inclusion criteria were to be over 20 years old, premenopausal, and have a BMI between 18.5 and 45.0 kg/m2. None were on insulin, glitazone and corticosteroids therapy. Patients with a positive history of liver and renal disease or recent neoplasia were not included. Subjects were recruited from the outpatient clinics of the Hospital School of Medicine at the State University of Campinas.
      This study was approved by the Ethics Committee, State University of Campinas, Brazil, in accordance with the Declaration of Helsinki. All participants provided written informed consent before participation.

      2.1 Anthropometric and adiposity measures

      All of the subjects underwent a detailed anthropometric examination wearing light clothes and no shoes. The SAD was measured while the subjects were in a supine position with their knees slightly bent. The measurement was taken at the umbilicus level using the Holtain–Kahn Abdominal Caliper™. Waist and hip circumferences were measured at standing position by a measuring tape. WC was measured at the umbilicus level without clothing present in the measurement area. Hip circumference was measured at the most protuberant point between the waist and the thigh [
      • Sampaio L.R.
      • Simoes E.J.
      • Assis A.M.
      • et al.
      Validity and reliability of the sagittal abdominal diameter as a predictor of visceral abdominal fat.
      ]. All measurements were taken in duplicate and averaged. Waist-to-hip ratio and BMI were also determined. Body fat and free fat mass were determined using a bioimpedance analyzer (model BIA 310).
      Each subject underwent a transthoracic two-dimensional guided M-mode echocardiogram. Echocardiograms were performed using standard techniques on a GE instrument with the subjects in the left lateral decubitus position. EAT thickness was measured on the free wall of the right ventricle from both the parasternal long- and short-axis views. EAT appears as an echo-free space [
      • Iacobellis G.
      • Assael F.
      • Ribaudo M.C.
      • et al.
      Epicardial fat from echocardiography: A new method for visceral adipose tissue prediction.
      ]. All of the measurements were taken in triplicate and averaged. The intraclass coefficients of correlation were 0.95 (95% CI 0.92–0.97) for EAT (p<0.001).
      VAT thickness was determined in supine position 1 cm from the umbilicus by ultrasonographic procedures using a 3.5 MHz probe. VAT was the distance between the internal face of the rectus abdominis muscle and the posterior wall of the aorta [
      • Radominski R.B.
      • Vezozzo D.P.
      • Cerri G.G.
      • et al.
      The use of sonography in the assesment of absominal fat distribution.
      ].

      2.2 Cardiometabolic measurements

      Blood pressure values were assessed with the auscultatory method.
      Hyperglycemic clamp was applied to assess the insulin sensitivity [
      • Mitrakou A.
      • Vuorinen-Markkola H.
      • Raptis G.
      • et al.
      Simultaneous assessment of insulin secretion and insulin sensitivity using a hyperglycemia clamp.
      ]. The insulin sensitivity index (ISI) was calculated by dividing the average glucose infusion rate adjusted for free fat mass (GIR) during the last hour by the average concentration of insulin during the same period.
      Blood samples were collected after a 12-h fast. Glucose (glucose oxidase method), glycated hemoglobin (HPLC method), lipid profile, uric acid (enzymatic colorimetric method), ultra-sensitive C-reactive protein (ELISA, intra and inter-assays variations<10%), serum adiponectin (ELISA, inter-assay: 1.0%–7.4%; intra-assay: 1.0%–7.4%, sensitivity: 1.5 ng/mL) and plasma insulin (ELISA, inter-assay: 9.1%–11.4%; intra-assay: 4.6%–7.0%) were measured.

      2.3 Statistical analysis

      Pearson linear correlation, one-way ANOVA and Tukey's post-hoc test were applied for parametric variables. The Kruskal–Wallis test and Bonferroni's post-hoc test were used for non-parametric variables. ROC analyses were performed for each anthropometric parameter as a predictor of EAT. Stepwise multiple regression was applied with the four anthropometric measurements and age as independent variables and EAT as dependent variable.

      3. Results

      Mean EAT thickness was 8.5±3.0 mm. Generalized obesity, VAT thickness, systolic blood pressure, HDL-cholesterol, triglycerides, fasting blood glucose, glycated hemoglobin, insulin sensitivity, adiponectin, uric acid and C-reactive protein levels worsen with the accumulation of EAT (Table 1).
      Table 1Clinical and metabolic parameters divided into tertiles of epicardial adipose tissue.
      Epicardial adipose tissue
      Tertile 1Tertile 2Tertile 3p
      Weight (kg)72.1±21.9 a84.1±12.5 a, b91.9±12.9 b0.001
      Height (m)1.62±0.06 a1.59±0.07 a1.59±0.06 a0.083
      Body mass index (kg/m2)29.9±7.6 a33.7±4.6 b36.6±3.7 b0.001
      Visceral adipose tissue (mm)54.1±25.3 a67.3±20.8 a,b84.3±20.3 b0.006
      Systolic BP (mmHg)114±16 a116±17 a126±16 b0.049
      Diastolic BP (mmHg)77±1280±1183±100.245
      Total cholesterol (mg/dl)176.5±31.2185.6±40.9190.8±41.40.462
      HDL cholesterol (mg/dl)53.0±10.9 a51.2±13.1a37.9±6.3 b0.001
      LDL cholesterol (mg/dl)104.5±28.4112.5±32.0118.2±35.50.383
      Triglycerides (mg/dl)94.8±52.1 a137.9±78.2 a,b161.7±94.0 b0.007
      Uric acid (mg/dl)3.9±0.9 a4.4±1.0 a5.6±1.3 b0.001
      Fasting glucose (mg/dl)92.4±15.6 a119.9±51.5 a,b133.3±43.9 b0.001
      Glycated hemoglobin (%)4.7±1.0 a6.3±2.0 b6.8±1.5 b0.001
      ISI (mg.kgffm−1.min−1.μU/l)0.70±0.76 a0.24±0.19 b0.22±0.31 b0.001
      Adiponectin (ng/ml)3.9±1.8 a2.6±1.6 b1.6±0.7 b0.001
      C-reactive protein (mg/dl)0.33±0.53 a0.38±0.39 a0.73±0.61 b0.010
      Data are presented as the mean±standard deviation. Abbreviations: BP (blood pressure), GIR (glucose infusion rate), ISI (insulin sensitivity index). The Kruskal–Wallis test followed by Bonferroni's post-hoc test was used for systolic and diastolic BP, triglycerides, fasting glucose and ISI. One-way ANOVA followed by Tukey's post-hoc test was utilized for the other variables.
      VAT and all of the anthropometric parameters were correlated with EAT (p<0.05). The SAD, followed by BMI, was most strongly correlated with EAT. The waist-to-hip ratio was more weakly correlated with EAT than were the other measures (Fig. 1A ).
      Figure thumbnail gr1
      Fig. 1(A) Correlations between anthropometric parameters and adipose tissue depots. (B) ROC curve analyses for the anthropometric parameters that identify the magnitude of epicardial adipose tissue.
      According to the ROC analyses, all of the parameters were effective predictors of EAT depot, but the SAD was the best predictor. The area under the curve for EAT (0.81) indicates that the SAD measurement was very accurate (Fig. 1B).
      In the multiple stepwise linear regression, EAT was best predicted by the SAD (R2=0.25; p<0.001). The rest of anthropometric variables did not contribute significantly to the regression model.

      4. Discussion

      The present study reinforces that the magnitude of EAT depot is related to cardiometabolic risk factors in a sample of women with a wide range of adiposity and glucose tolerance levels. Our data show that the SAD best correlated with EAT; this particular anthropometric parameter performed best in the ROC analysis in evaluating EAT depots and was an independent predictor of EAT.
      The SAD has been reported as an excellent marker of VAT in many ethnic groups [
      • Pouliot M.C.
      • Despres J.P.
      • Lemieux S.
      • et al.
      Waist circumference and abdominal sagittal diameter: Best simple anthropometric indexes of abdominal visceral adipose tissue accumulation and related cardiovascular risk in men and women.
      ,
      • Yim J.Y.
      • Kim D.
      • Lim S.H.
      • et al.
      Sagittal abdominal diameter is a strong anthropometric measure of visceral adipose tissue in the asian general population.
      ], including the Brazilian population [
      • Sampaio L.R.
      • Simoes E.J.
      • Assis A.M.
      • et al.
      Validity and reliability of the sagittal abdominal diameter as a predictor of visceral abdominal fat.
      ]. A study from Korea established that SAD was more strongly associated with VAT than WC and BMI irrespective of age, sex, and degree of obesity [
      • Yim J.Y.
      • Kim D.
      • Lim S.H.
      • et al.
      Sagittal abdominal diameter is a strong anthropometric measure of visceral adipose tissue in the asian general population.
      ]. Increased VAT tends to elevate the abdominal wall in the sagittal direction when subjects are in the supine position. Subcutaneous fat compresses the abdomen or tends to flow out at the flanks. Variance in the supine SAD might reflect variance in the VAT volume [
      • Sjostrom L.
      A computer-tomography based multicompartment body composition technique and anthropometric predictions of lean body mass, total and subcutaneous adipose tissue.
      ].
      Although WC measured in the standing position is widely accepted as a marker of a dysmetabolic state and increased cardiovascular risk, it can be confounded by subcutaneous fat. This likely accounts for the finding that WC was not a better measure of the dysmetabolic state or cardiovascular risk than the SAD in the present study. Iacobellis et al. [
      • Iacobellis G.
      • Ribaudo M.C.
      • Assael F.
      • et al.
      Echocardiographic epicardial adipose tissue is related to anthropometric and clinical parameters of metabolic syndrome: A new indicator of cardiovascular risk.
      ] reported a moderate correlation between EAT and SAD not measured anthropometrically. Other studies have shown similar correlations to those in the present study between EAT and BMI, WC and waist-to-hip ratio [
      • Iacobellis G.
      • Ribaudo M.C.
      • Assael F.
      • et al.
      Echocardiographic epicardial adipose tissue is related to anthropometric and clinical parameters of metabolic syndrome: A new indicator of cardiovascular risk.
      ,
      • Karadag B.
      • Ozulu B.
      • Ozturk F.Y.
      • et al.
      Comparison of epicardial adipose tissue (eat) thickness and anthropometric measurements in metabolic syndrome (ms) cases above and under the age of 65.
      ].
      Furthermore, the SAD has been strongly associated with insulin resistance [
      • Nakata K.
      • Choo J.
      • Hopson M.J.S.
      • et al.
      Stronger associations of sagittal abdominal diameter with atherogenic lipoprotein subfractions than waist circumference in middle-aged us white and japanese men.
      ], with atherogenic lipoprotein subfractions [
      • Nakata K.
      • Choo J.
      • Hopson M.J.S.
      • et al.
      Stronger associations of sagittal abdominal diameter with atherogenic lipoprotein subfractions than waist circumference in middle-aged us white and japanese men.
      ] and with cardiovascular risk [
      • Kahn H.S.
      • Simoes E.J.
      • Koponen M.
      • et al.
      The abdominal diameter index and sudden coronary death in men.
      ]. A recent follow up pointed out that the combination of SAD and BMI measurements yields a new predictor of diabetes [
      • Pajunen P.
      • Rissanen H.
      • Laaksonen M.A.
      • et al.
      Sagittal abdominal diameter as a new predictor for incident diabetes.
      ]. In the CODAM study, SAD and WC were significantly associated with serum complement factor 3 levels [
      • Wlazlo N.
      • van Greevenbroek M.M.
      • Ferreira I.
      • et al.
      Low-grade inflammation and insulin resistance independently explain substantial parts of the association between body fat and serum c3: The codam study.
      ].
      The metabolic characteristics of EAT may clarify the association of EAT with cardiometabolic risk parameters. Adiponectin expression is significantly lower in epicardial than in subcutaneous fat, which may explain why poor insulin sensitivity is related to EAT accumulation [
      • Bambace C.
      • Telesca M.
      • Zoico E.
      • et al.
      Adiponectin gene expression and adipocyte diameter: A comparison between epicardial and subcutaneous adipose tissue in men.
      ]. In the present study, ISIffm index was also associated with the magnitude of EAT depot.
      The limitations of the present study are the relative small sample size and the absence of the magnetic resonance imaging. The strength of the present study was to provide a clamp-derived insulin sensitivity measurement.
      Our findings are of potential interest for obesity researchers and clinicians. The SAD is a non-invasive marker that can be used to identify pre-menopausal female patients with EAT accumulation. Further studies are required to validate its utility in men and postmenopausal women [
      • Bambace C.
      • Telesca M.
      • Zoico E.
      • et al.
      Adiponectin gene expression and adipocyte diameter: A comparison between epicardial and subcutaneous adipose tissue in men.
      ].

      Conflict of interest

      There are none potential conflicts of interest or financial disclosure for all the authors involved.

      Author contributions

      • Ana Carolina Junqueira Vasques: design/conduct of the study, data collection, statistical analysis/interpretation, manuscript writing.
      • José Roberto Matos Souza: echocardiography data collection.
      • Ademar Yamanaka: abdominal ultrasound data collection.
      • Maria da Saúde de Oliveira: conduct of the study.
      • Fernanda Satake Novaes: conduct of the study.
      • José Carlos Pareja: data interpretation, manuscript writing.
      • Bruno Geloneze: study design, data interpretation, manuscript writing.

      Funding

      Study supported by São Paulo Research Foundation (FAPESP) , grants n.2008/09451-7 and n.2008/07312-0 .

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