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Association between coronary atherosclerosis and visceral adiposity index
Journal Pre-proof Association between coronary atherosclerosis and visceral adiposity index Zsolt Bagyura, MD, PhD, Loretta Kiss, MD, Árpád Lux, MD, PhD, Csaba CsobayNovák, MD, PhD, Ádám L. Jermendy, MD, PhD, Lívia Polgár, MD, Zsolt Szelid, MD, PhD, Pál Soós, MD, PhD, Béla Merkely, MD, PhD PII:
S0939-4753(20)30046-6
DOI:
https://doi.org/10.1016/j.numecd.2020.01.013
Reference:
NUMECD 2218
To appear in:
Nutrition, Metabolism and Cardiovascular Diseases
Received Date: 29 July 2019 Revised Date:
29 December 2019
Accepted Date: 29 January 2020
Please cite this article as: Bagyura Z, Kiss L, Lux Á, Csobay-Novák C, Jermendy ÁL, Polgár L, Szelid Z, Soós P, Merkely B, Association between coronary atherosclerosis and visceral adiposity index, Nutrition, Metabolism and Cardiovascular Diseases, https://doi.org/10.1016/j.numecd.2020.01.013. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier B.V. on behalf of The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University.
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Association between coronary atherosclerosis and visceral adiposity index
3
Authors
4 5
Zsolt Bagyura, MD, PhD1
6
Loretta Kiss, MD1
7
Árpád Lux, MD, PhD 1
8
Csaba Csobay-Novák, MD, PhD1
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Ádám L. Jermendy, MD, PhD 1
10
Lívia Polgár, MD 1
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Zsolt Szelid, MD, PhD 1
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Pál Soós, MD, PhD 1
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Béla Merkely, MD, PhD1
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1
Heart and Vascular Center, Semmelweis University, Városmajor utca 68, Budapest H-1122, Hungary
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Corresponding author Zsolt Bagyura, MD, PhD; Heart and Vascular Center, Semmelweis University, Városmajor utca 68, Budapest H-1122, Hungary, Phone: +3670-436-8341, Email: [email protected]
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Keywords visceral adiposity index, central obesity, coronary calcification, calcium score, cardiovascular risk, cardiology
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Acronyms ACE – angiotensin-converting-enzyme, ACS - acute coronary syndrome; ASA – acetylsalicylic acid, BMI - body mass index; CA - Cochran-Armitage; CACS - Coronary artery calcium score; CI confidence interval; CT - computer tomography; CVD - cardiovascular disease; DBP - diastolic blood pressure; DM - diabetes mellitus; HBa1c - haemoglobin-A1c; HDL-C - high-density lipoprotein cholesterol; HU - Hounsfield unit; IQR - interquartile range; LDL-C - low-density lipoprotein cholesterol; OR - odds ratio; VAI - visceral adiposity index; SBP - systolic blood pressure; SD standard deviation
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Abstract: 235 words, text: 3057 words, number of references: 29, tables: 4, figures: 1. 1
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Abstract
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Background and Aims
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Visceral obesity is a marker of dysfunctional adipose tissue and ectopic fat infiltration. Many studies
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have shown that visceral fat dysfunction has a close relationship with cardiovascular disease. For a
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better identification of visceral adiposity dysfunction, the visceral adiposity index (VAI) is used.
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Coronary artery calcium score (CACS) is known to have a strong correlation with the total plaque
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burden therefore provides information about the severity of the coronary atherosclerosis. CACS is a
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strong predictor of cardiac events and it refines cardiovascular risk assessment beyond conventional
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risk factors. Our aim was to evaluate the association between VAI and CACS in an asymptomatic
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Caucasian population.
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Methods and Results
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screening program. A health questionnaire, physical examination and laboratory tests were also
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performed. Participants with a history of cardiovascular disease were excluded from the analysis.
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Mean VAI was 1.41±0.07 in men and 2.00±0.15 in women. VAI showed a positive correlation with
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total coronary calcium score (r=0.242) in males but not in females. VAI was stratified into tertiles by
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gender. In males, third VAI tertile was independently associated with CACS>100 (OR: 3.21, p=0.02)
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but not with CACS>0 after the effects of conventional risk factors were eliminated.
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Conclusion
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predictor for the presence of CACS>100 in males but not in females.
Computed tomography scans of 460 participants were analyzed in a cross-sectional, voluntary
VAI tertiles were associated with calcium scores and the highest VAI tertile was an independent
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2
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Introduction
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Atherosclerosis is among the leading causes of death in the Western world [1]. Obesity is a well-
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known risk factor of cardiovascular disease (CVD) [2]. However, central or visceral obesity appear to
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be more strongly associated with cardiovascular risk [3]. Many studies have shown proinflammatory
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cytokines, adipocytokines [4] tend to increase and insulin sensitivity decrease in patients with central
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obesity [5]. Estimating the extent of visceral adiposity with waist circumference (WC) measurement
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is widely used CVD risk assessment. However, this method cannot distinguish between subcutaneous
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and visceral fat accumulation. Recently, the visceral adiposity index (VAI) was developed [6] for
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identification of visceral adiposity dysfunction. VAI is a simple, gender specific marker combining
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anthropometric data and lipid profiles and are reliable indicator of visceral at dysfunction. Several
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studies found a strong association of VAI with cardiometabolic risk [7]. Recently, Barazzoni et al.
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found that compared to WC or BMI VAI had the highest 5-year predictive value for metabolic
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syndrome in overweight or obese patients [8]. Several studies showed that VAI is a predictor of
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incident hypertension [9]. Ji et al. reported that VAI has a strong correlation with insulin resistance
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even in a population without central obesity [10].
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Calcification of the coronary plaques shows a strong correlation with the total plaque burden [11].
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Scanning of the heart with low-dose non-contrast computer tomography (CT) provides quantitative
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information of the extent of the coronary calcification. Coronary artery calcium score (CACS) or
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Agatston score is a reliable surrogate marker of atherosclerosis and it is a strong predictor of cardiac
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events [12], therefore could be used for assess the cardiovascular risk beyond conventional risk
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factors [13]. For ruling out obstructive coronary artery disease CAD, the negative predictive value of
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a 0 CACS is almost 100%, therefore it indicates a very low cardiovascular event rate [14] CACS
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above 100 is associated with moderate risk for coronary heart disease [15].
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Only limited number of studies have examined the relationship between VAI and CACS [16].
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Therefore, our aim was to evaluate the association between VAI and CACS in an asymptomatic
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Caucasian population. 3
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Methods
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Budakalász Health Examinaton Survey, a cross-sectional voluntary cardiovascular screening program
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targeting the adult population (>20 years, ~8000 inhabitants) of a Central-Hungarian town
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(Budakalász) was performed in 2011–2013 [17]. Medical history with special attention to
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cardiovascular disease, related signs and symptoms, lifestyle (alcohol consumption, sport activities,
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smoking habits) and family history were recorded by an experienced physician. Anthropometric
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parameters rounded to the nearest 0.1 cm and 0.1 kg were measured in standing position while
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participants were wearing light indoor clothing without shoes.
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All laboratory tests were performed in our institution’s central laboratory with rigorous quality
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control. Concentration of lipid fractions was measured by using a colorimetric assay (Roche
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Diagnostics Ltd, Mannheim, Germany). Hypertension, dyslipidaemia and diabetes mellitus in medical
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history were regarded positive if they have been was formerly diagnosed or the patient had received
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treatment. Body mass index was calculated by using Quetelet’s form. Blood pressure measurement
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was performed on the arms after 20 minutes rest in a flat lying position. Blood pressure above 140
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mmHg systolic and/or 90 mmHg diastolic was defined as pathologically high.
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Prospectively ECG-triggered low dose cardiac CT scans (Brilliance iCT, Philips Healthcare, Best,
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The Netherlands) for calcium scoring were acquired of the heart with a narrow field-of-view.
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Effective radiation dose was 0.5 mSv or less. Axial images were used for the quantitative analysis of
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coronary calcification using a commercially available software application (Calcium scoring,
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Heartbeat-CS, Philips Healthcare). Coronary artery plaques were identified by the software
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automatically, followed by selection of real coronary plaques by an expert observer manually. Based
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on these results the software calculated the CACS, the calcification area and the volume in a semi-
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automatic way.
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The participation rate in the Budakalász Health Examination Survey was around 30% (n=2420) of the
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eligible total population. From this 2420 persons a low dose cardiac CT scan was offered for males
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older than 35 years and in females above 40 years of age (n=2029). Total number of 511 participants
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volunteered for CT scan. This group was not significantly different from those who were offered the
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CT in gender, LDL and triglyceride levels, blood pressure, BMI and VAI but the CT subgroup was
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significantly older (62.12+-10.03 vs. 58.17+-11.91, p<0.001), had slightly higher total cholesterol
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levels (5.57+1.17 vs 5.56+-1.13, p=0.04). Moreover hypertension (27.8% vs. 21.9%, p=0.002),
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dyslipidaemia (30.3% vs. 21.7%, p<0.001) and diabetes mellitus (32.3% vs. 24%, p=0.004) were
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more frequent in this group. Participants with the following cardiovascular history were excluded
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from the further analysis: 24 patients with previous myocardial infarction (4.7%), 20 patients with
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stroke (3.9%), 4 patients with transient ischemic attack (0.8%). Also, 3 persons (0.6%) were excluded
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due to the lack of the laboratory results. As a participant could have more than one exclusion criteria,
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overall four hundred sixty participants were included in the study. The study flowchart is presented in
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Fig. 1. The VAI was calculated using the following sex-specific formula [18]:
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•
Males: VAI = [WC/{39.68 +(1.88*BMI)}]*(TG/1.03)*(1.31/HDL-C)
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•
Females: VAI = [WC/{36.58+(1.89*BMI)}]*(TG/0.81)*(1.52/HDL-C)
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A post hoc power analysis was conducted using online calculator developed by MGH Biostatistics
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Center. The sample size of 460 was used for the statistical power analyses. The significance level
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used for this analysis was p < 0.05. The standard deviation of the dependent variable (CACS) was
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500.6, the standard deviation of the independent variable (VAI) was 0.32, the minimal detectable
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difference entered was 244.8. The post hoc analyses revealed that the probability is 91 percent that the
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study detects a relationship between the independent and the dependent variables.
5
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Statistical methods
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SPSS for Windows, version 18.0 (IBM, Armonk, NY) was used for statistical analysis. All continuous
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variables were expressed as mean with standard deviation (SD) or as medians with interquartile range
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as appropriate depending on the distribution of the values, whereas categorical variables were
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expressed as percentage. Comparisons of means, medians and proportions were performed with
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variance analysis, Kruskal-Wallis test, Jonckheere-Terpstra test, Cochran-Armitage (CA) test and
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Chi-square tests, respectively. Spearman’s correlation was used to test the association between VAI
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and CACS. Multivariate regression analysis was performed adjusted for age, gender and risk factors
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with the 1st VAI tertile as reference category. All analyses were performed two-tailed and p<0.05 was
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considered significant.
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Ethics approval and consent to participate
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The research had ethics approval from the Medical Research Council Scientific and Ethics Committee
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(permission number: 8224-0/2011/EKU (265/PI/11)). All procedures followed were in accordance
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with the ethical standards of the responsible committee on human experimentation (institutional and
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national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Written informed consent
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was obtained from all patients for being included in the study.
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Results
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The basic characteristics of the male and female participants
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The mean age was 61.6 (±10.2) years; 41.1% of the participants were men and all patients belonged to
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the Caucasian race. The mean BMI was 28.6 kg/m2 (±5.1), the mean VAI was 1.76 (± 0.32) and the
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median CACS score was 19.65 (±161.2). Clinical baseline characteristics of the 189 male and 271
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female patients are described in Table 1. Waist circumference, smoking status, mean systolic blood 6
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pressure, HDL-C, total cholesterol and serum creatinine were significantly different between genders.
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Mean VAI was 1.41±0.07 in men and 2.00±0.15 in women (p<0.001), butt BMI was not significantly
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different between the two genders. Drug therapies could have effect on atherosclerotic plaques, but we
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have found no difference in the lipid lowering angiotensin-converting enzyme inhibitor and
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acetylsalicylic acid drug usage between the two genders.
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VAI differs substantially between males and females, therefore VAI was stratified into tertiles by
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gender (Table 2.) for further analysis. Waist circumference was significantly different in the three
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tertile groups in both genders. Age, BMI, low-density lipoprotein (LDL-C), total cholesterol and
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haemoglobin-A1c (HBa1c) levels were significantly different in the three tertile groups in males but
163
not in females. Also, the frequency of hypertension and diabetes increased gradually in males in the
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groups and was highest in the third tertile group. In contrast, there were no significant differences in
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the age, BMI or the other above-mentioned factors’ distribution among the three groups in females.
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Menopause can affect adiposity; therefore, we analysed the menstruation status in females. As there
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was no difference in this parameter across the three tertiles (tertile 1: 64 (71.1%), tertile 2: 63 (69.2%)
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and tertile 3: 63 (70%), p=0.589) the effect of menopause was not further analysed. Clinical
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characteristics in the VAI tertiles by gender are described in Table 3.
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CT scan results
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Median total calcium score was 19.4 (IQR: 161.6) in the study group. VAI only showed a positive
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correlation with total coronary calcium score in males (r=0.242, p<0.001). The Jonckheere-Terpstra
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test for total CACS confirmed a trend across VAI groups in males (J-T statistic: 7419, p<0.001) but
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not in females. Total CACS was 0 in 41 cases in males (21.7%) and in 108 cases (39.9%) in females.
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It was less or equal to 100 in 112 cases (59.3%) in males and 209 cases (77.1%) in females. There was
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no statistically significant difference in the frequency of CACS > 0 in neither gender. Frequency of
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CACS >100 was significantly different in the three VAI groups in males but not in females (Table 3.)
179
and there was a trend across VAI groups (CA statistic: 14.476, p<0.001). The highest tertile group had 7
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significantly higher odds ratio for CACS >100 only in males (OR 5.37, 95% CI: 2.43 – 11.83, p<0.01)
181
compared to the lowest tertile (Table 4).
182
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Multivariate analysis
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We performed multivariate analysis with presence of CACS>100 adjusted for age. In this model the
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highest tertile group had significantly higher odds ratio for CACS >100 in males (Model 1: OR 3.75,
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95% CI:1.55–9.08, p=0.003) compared to the lowest tertile, but not in females (Table 4). Similarly,
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after further adjustments for BMI, hypertension, dyslipidaemia, smoking status, total cholesterol and
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uric acid level, diabetes mellitus and HbA1c levels in model 2 the highest tertile group was
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independently associated with CACS>100 in males (Model 2: OR 3.41, 95% CI: 1.27–9.41, p=0.018)
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compared to the lowest tertile. BMI was not independently associated with CACS>100 in either
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gender.
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Discussion
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In this study we presented an independent association of VAI with coronary calcification in an
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asymptomatic Caucasian population. We found that VAI showed a positive correlation with CACS
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(r=0.242). In logistic regression analyses, compared to the lowest VAI tertile, the highest tertile was
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an independent predictor and showed significantly increased odds for the presence of moderate-risk
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coronary calcification (CACS>100) in males but not in females. The association remained significant
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even after adjusting for confounding variables including BMI. We found no statistically significant
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association of VAI with the presence of any coronary calcification (CACS > 0).
200 201
Visceral obesity is a marker of dysfunctional adipose tissue and a well-known risk factor of CVD [2]
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and the most prevalent manifestation of metabolic syndrome [19], [20], [21], [22]. Waist
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circumference measurement [23] is known to be more informative in connection with visceral 8
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adiposity than BMI, although it cannot distinguish well between subcutaneous fat and visceral
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obesity. To overcome this VAI was developed for more precise assessment of cardiometabolic risk as
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it is based on sex, WC, BMI and lipid parameters [6]. VAI is known to be increased significantly in
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metabolically healthy obese individuals compared to metabolically healthy normal-weight individuals
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and is a novel risk factor of CVD [7].
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There is no ideal cut-off value for VAI that helps to distinguish normal and dysfunctional visceral
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adiposity. Some researchers use tertiles [24], others use quartiles as a cut-off value for the analysis
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[25]. We used tertiles and found that the third tertile of VAI is correlated positively with CACS in
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both regression models.
213
Our results showed that there is an association between VAI and the prevalence of classic markers of
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cardiometabolic risk (BMI, hypertension, as well as diabetes mellitus and HBa1c) in males, but not in
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females. We found no significant differences in the VAI terciles regarding dyslipidaemia, triglyceride
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LDL-C and HDL-C levels. These results are partially in line with the findings of Amaro et al [6] who
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demonstrated that VAI has strong correlation with metabolic markers independently of genders.
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According to our results the three tertiles in males are more heterogeneous in the frequency of having
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cardiovascular risk factors, and higher tertile means higher frequency of cardiovascular risk factors. In
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contrast there is no significant difference in females among the tertiles. In our study the range of VAI
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differs basically in the two genders. In males in the first tertile group the VAI is between 1.03 and
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1.37, but in females the first tertile is between 1.35 and 1.94, so the average VAI is significantly
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higher even in the first tertile. Moreover, the maximal value in the first tertile of females is higher
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than the overall maximal VAI value in males. Distribution of VAI is different between the two
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genders in our population mainly because females have relatively worse waist circumference. In our
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study group according to our results the metabolically active central obesity affects almost all females
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(high average VAI) in contrast to males were there is a gradual increase from “normal” VAI to the
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worse values.
229 9
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In our study we included males over 35 years and females over 40 years only. If we compare the
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average age in the tertile groups in males age is increasing significantly in contrast to females where
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the first tertiles is almost five years older in average and there is no significant difference among the
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tertile groups. Moreover, the menopause of women could affect the results, but we found no
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difference in this parameter across the three tertiles in females.
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Males with higher CACS had a significantly higher VAI compared to those without CACS in our
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study. The risk of CACS >100 was significantly higher in the upper VAI tertiles compared to the
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lowest tertile (OR 3.41, 95% CI:1.4–8.31, p=0.007), even after adjusting for several factors (OR 3.21,
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95% CI:1.16–8.85, p=0.024). In our study BMI was not independently associated with CACS in
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contrast to VAI. The association between VAI and CACS but not BMI could be explained by the
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metabolically active central fat accumulation, that results in increased circulating free fatty acid
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levels, systemic inflammation, insulin sensitivity and vasculopathy [26] [27].
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In contrast to our results Park et al. [16] have found association between VAI and CACS>100 in both
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genders. Moreover, we did not find association between CACS>0 and VAI, in contrast to Parks’
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group, who found that the risk of CACS >0 was higher in the upper VAI tertiles compared to the
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lowest tertile in both genders. However, there are important differences between our and Park’s study.
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Park et al investigated more than 33,000 patients from the Korean population, 80.2% of total
248
participants were men. This gender imbalance could have affected the results as Park et al, who
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created three tertile groups based only on VAI but not gender. In contrast, in our study 41.1% of the
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participants were men and all participants were from the Caucasian race. It is noteworthy that VAI
251
was modelled on a Caucasian population, and this is an important limitation to consider when it is
252
applied in non-Caucasian populations. According to our results, the distribution of VAI was
253
significantly different between genders, therefore we created gender-based tertiles, and this could
254
explain the difference that we found between males and females. It is probable that the association
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between VAI and CACS is gender-dependent and different in the Central European and Korean 10
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population. Our result are in line with the results of Randrianarisoa et al [28] who found significant
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association between VAI and carotid intima media thickness, a marker of subclinical atherosclerosis,
258
along with age, smoking and male sex and with the results of Kouli et al [29] who found that VAI is
259
independently associated with elevated 10-year CVD risk, particularly in men. Finally, in Park’s
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study, the mean participant age was 41.5 years, and the mean BMI was 24.3 kg/m2. Our study group
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was more than 20 years older and more obese in average. It is possible that these are the main reasons
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behind that the mean CACS was significantly higher (11.2 ± 72.0. vs. 211.8 ±540.1). According to
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their results, they have found 1.8 to 1.2 OR for CACS >100 in the upper VAI tertiles compared to the
264
lowest tertile. In contrast, we have found an approximately two times higher risk, but only in males.
265 266
This study has some limitations. Firstly, as cross-sectional study we cannot imply causality between
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VAI and CACS based on these results. Secondly, we indicated low-dose CT only for men above 35
268
and women above 40, therefore patients with lowest cardiovascular risk were excluded from our
269
study. Third, there is no appropriate VAI cut-off value to estimate cardiovascular risk; we used tertile
270
values and compared to CACS or to the proportion of subjects with CACS>100.
271 272
VAI is a simple, gender specific indicator of visceral fat dysfunction and known to be associated with
273
increased risk of CVD. CACS is a reliable surrogate marker of atherosclerosis, however it is not
274
widely used in primary care settings. In conclusion, in an asymptomatic population VAI tertiles were
275
associated with CACS and the third VAI tertile was an independent predictor for the presence of
276
moderate-risk coronary calcification in males but not in females. Our results suggest that VAI could
277
be a useful clinical marker of cardiometabolic risk and effect of central obesity as a risk factor in more
278
pronounced in males and could have ethnic difference. The association between VAI and CACS may
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have significant implications for identifying patients in risk for atherosclerotic coronary artery disease
280
in primary prevention.
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Acknowledgements
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Competing Interests
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The authors declare that they have no conflict interests.
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Funding
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This work was supported by the National Research, Development and Innovation Office of Hungary
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(NKFIA; NVKP-16- 1-2016-0017). The research was financed by the Higher Education Institutional
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Excellence Programme of the Ministry of Human Capacities in Hungary, within the framework of the
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Therapeutic Development thematic programme of the Semmelweis University.
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Authors' contributions
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Zsolt Bagyura, Loretta Kiss carried out the statistical analysis and drafted the manuscript. Zsolt
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Bagyura, Loretta Kiss, Pál Soós, Zsolt Szelid participated in the design of the study Zsolt Bagyura,
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Loretta Kiss, Lívia Polgár, Árpád Lux, Pál Soós, Zsolt Szelid performed the data collection from the
297
patients. Csaba Csobay-Novák, Ádám L. Jermendy, Árpád Lux performed the calcium scoring. All
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authors read and approved the final manuscript.
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Tables
400 401
Table 1. Clinical baseline characteristics 16
Males (N=189)
Females (N=271) p
60.55 (11.16)
62.11 (9.41)
0.107
Waist Circumference (cm), mean 103.66 (11.66) (SD)
96.54 (12.81)
<0.001
BMI, mean (SD)
28.61 (4.31)
28.56 (5.53)
0.924
Hypertension, n (%)
153 (81.0%)
221 (81.5%)
0.873
Dyslipidaemia, n (%)
79 (41.8%)
132 (48.7%)
0.143
Statin therapy, n (%)
35 (18.5%)
54 (19.9%)
0.721
Other lipid lowering therapy, n (%)
6 (3.2%)
3 (1.1%)
0.115
ACE inhibitor therapy, n (%)
54 (28.6%)
77 (28.4%)
0.971
ASA therapy, n (%)
27 (14.3%)
31 (11.4%)
0.366
DM, n (%)
30 (15.9%)
33 (12.2%)
0.257
Active smoker, n (%)
24 (12.7%)
28 (10.3%)
0.430
Smoker (current + former), n (%)
92 (48.7%)
91 (33.6%)
0.010
SBP (mmHg), mean (SD)
135.05 (16.16)
138.52 (19.99)
0.040
DBP (mmHg), mean (SD)
80.50 (8.82)
80.26 (9.85)
0.789
LDL-C (mmol/l), mean (SD)
3.45 (0.97)
3.53 (1.05)
0.400
HDL-C (mmol/l), mean (SD)
1.33 (0.26)
1.65 (0.49)
<0.001
Triglyceride (mmol/l), mean (SD)
2.47 (1.50)
2.31 (1.52)
0.265
Total cholesterol (mmol/l), mean 5.54 (1.11) (SD)
5.86 (1.15)
0.003
Serum creatinine (µmol/l), mean 85.77 (15.71)
80.87 (15.11)
0.010
Age, mean (SD)
17
(SD) Serum uric acid (µmol/l), mean (SD)
350.47 (79.11)
299.66 (68.98)
<0.001
HbA1c (%), mean (SD)
5.80 (0.74)
5.91 (0.75)
0.112
VAI, mean (SD)
1.41 (0.07)
2.00 (0.15)
<0.001
LogCACS score, mean (SD)
1.57 (1.13)
1.03 (1.03)
<0.001
CACS, median (IQR)
55.7(349)
6.66 (86.8)
<0.001
CACS >0
148 (78.3%)
163 (60.1%)
<0.001
CACS >100, n (%)
77 (40.7%)
62 (22.9%)
<0.001
Agatston score >400, n (%)
42 (22.2%)
21 (7.7%)
<0.001
402
Means ± SDs (or median±IQR in case of CACS) represented the continuous variables, and proportions the categorical variables. CACS – coronary artery
403
calcium score, DBP - diastolic blood pressure, DM - diabetes mellitus, HDL-C - high-density lipoprotein cholesterol, IQR – interquartile range, LDL-C - low-
404
density lipoprotein cholesterol, SBP - systolic blood pressure, SD – standard deviation
405 406
Table 2 - Tertiles of VAI by gender in the study population
Tertile
Males (min-max, N)
Females (min-max, N)
1
1.03 - 1.37, 62
1.35 - 1.94, 90
2
1.38 - 1.44, 64
1.95 - 2.05, 91
3
1.45 - 1.59, 63
2.06 - 2.36, 90
407 408
Table 3. Clinical baseline characteristics in the VAI tertiles by gender
18
Age, mean (SD)
Males
Females
p VAI VAI VAI tertile 1 tertile 2 tertile 3 (N=62) (N=64) (N=63)
p VAI VAI VAI tertile] 1 tertile 2 tertile 3 (N=90) (N=91) (N=90)
62.4 (10.95)
62.98 (9.98)
<0.001 60.58 (9.54)
61.91 (9.48)
63.84 (9.01)
WC (cm), mean 94.1 (SD) (7.94)
104.2 (7.15)
111.67 (11.69)
<0.001 89.27 (12.55)
98.30 (11.55)
102.05 <0.001 (10.87)
BMI, mean (SD)
28.97 (3.48)
29.84 (5.25)
<0.001 28.73 (6.01)
29.34 (5.68)
27.62 (4.75)
n 41 (66.1%)
53 (82.8%)
58 (92.1%)
0.001
0.497 76 75 70 (84.4%) (82.4%) (77.8%)
Dyslipidaemia, n 21 (%) (33.9%)
30 (46.9%)
27 (42.9%)
0.317
0.571 40 45 48 (44.4%) (49.5%) (52.2%)
DM, n (%)
2 (3.2%)
10 (15.6%)
17 (27.0%)
0.001
0.913 11 12 10 (12.2%) (13.2%) (11.1%)
Active smoker, n 11 (%) (17.7%)
6 (9.4%)
7 (11.1%)
0.332
6 (6.6%) 9 0.220 13 (14.4%) (10.0%)
Smoker (current + 22 former), n (%) (35.5%)
35 (54.7%)
35 (56.6%)
0.04
0.329 28 36 27 (31.1%) (39.6%) (33.6%)
SBP (mmHg), 133.3 mean (SD) (16.42)
135.32 (17.34)
137.8 (14.53)
0.601
139.84 (22.02)
138.15 (19.10)
137.58 0.733 (18.88)
DBP (mmHg), 80.42 mean (SD) (8.71)
80.43 (9.72)
81.87 (8.16)
0.728
81.08 (8.58)
81.01 (11.55)
78.7 (9.03)
0.183
LDL-C (mmol/l), 3.79 mean (SD) (1.11)
3.37 (0.79)
3.25 (0.92)
0.005
3.60 (1.13)
3.49 (1.01)
3.51 (1.02)
0.772
HDL-C (mmol/l), 1.36 mean (SD) (0.31)
1.28 (0.26)
1.37 (0.46)
0.263
1.73 (0.56)
1.60 (0.42)
1.63 (0.49)
0.219
Hypertension, (%)
55.92 (11.55)
26.89 (3.32)
19
0.064
0.104
Triglyceride 2.37 (mmol/l), mean (1.47) (SD)
2.32 (1.36)
2.69 (1.66)
0.311
2.16 (1.23)
2.26 (134)
2.50 (1.91)
0.321
Total cholesterol 5.87 (mmol/l), mean (1.32) (SD)
5.40 (0.9) 5.44 (0.98)
0.019
5.95 (1.19)
5.76 (1.21)
5.86 (1.06)
0.564
Statin therapy, n 5 (8.1) (%)
17 (26.6)
13 (20.6)
0.178
19 (21.1) 20 (22.0) 15 (16.7) 0.672
ACE inhibitor 12 (19.4) therapy, n (%)
22 (34.4)
20 (31)
0.817
30 (33.3) 25 (27.5) 22 (24.4) 0.405
Other lipid 2 (3.2) lowering therapy, n (%)
2 (3.2)
2 (3.2)
0.999
0 (0)
ASA therapy, n 5 (8.1) (%)
10 (14.5)
12 (20.7)
0.142) 9 (10)
11 (12.1) 11 (12.2) 0.871
Serum creatinine 84.53 (µmol/l), mean (15.7) (SD)
87.1 (14.21)
58.2 (15.34)
0.322
69.69 (14.60)
72.69 (15.31)
0.353 70.32 (15.40)
Serum uric acid 344.18 (µmol/l), mean (80.75) (SD)
349.38 (85.83)
357.67 (70.66)
0.634
300.34 (70.49)
297.20 (68.98)
301.48 0.911 (68.17)
HbA1c (%), mean 5.53 (SD) (0.37)
5.81 (0.59)
5.97 (0.72)
<0.001 5.84 (0.74)
5.95 (0.72)
5.96 (0.81)
0.500
VAI, mean (SD)
1.33 (0.05)
1.41 (0.02)
1.48 (0.03)
<0.001 1.84 (0.10)
2.00 (0.32)
2.16 (0.76)
<0.001
LogCACS score, 1.15 mean (SD) (1.05)
1.68 (1.10)
1.85 (1.13)
0.001
1.05 (1.05)
1.02 (0.97)
1.02 (1.01)
0.970
CACS, (IQR)
56.82 (342.1)
147.54 (530.1)
0.001
11.57 (79.9)
6.42 (89.7)
0.963 5.46 (105.5)
52 (81.3%)
52 (82.5%)
0.228
0.534 52 59 52 (57.8%) (64.8%) (57.8%)
CACS >0
median 14.3 (62.4) 44 (71.0%)
20
1 (1.1)
2 (2.2)
0.362
n 13 (21.0%)
26 (40.6%)
37 (58.7%)
<0.001 19 0.753 20 23 (21.1%) (22.0%) (25.6%)
Agatston score 9 >400, n (%) (14.5%)
14 (21.9%)
18 (28.6%)
0.162
CACS (%)
>100,
8 (8.9%) 3 (3.3%) 10 0.128 (11.1%)
409 410
Means ± SDs (or median±IQR in case of CACS) represented the continuous variables, and proportions the categorical variables. Continuous variables were
411
analysed via One-way ANOVA or Kruskal-Wallis test in case of CACS, categorical variables were analysed via the Chi-square test. ACE – angiotensin-
412
converting-enzyme, ASA – acetylsalicylic acid, CACS – coronary artery calcium score, DBP - diastolic blood pressure, DM - diabetes mellitus, HDL-C - high-
413
density lipoprotein cholesterol, IQR – interquartile range LDL-C - low-density lipoprotein cholesterol, SBP - systolic blood pressure, SD - standard deviation
414 415
Table 4. Odds ratios for coronary artery calcification (CACS > 100) by gender according to tertiles of
416
VAI
Unadjusted Female Male Model 1
Female Male
Model 2
Female Male
OR (CI) p OR (CI) p OR (CI) p OR (CI) p OR (CI) p OR (CI) p
VAI tertile 1 1 (reference) 0.754 1 (reference) <0.01 1 (reference) 0.972 1 (reference) 0.09 1 (reference) 0.903 1 (reference) 0.03
VAI tertile 2 1.05 (0.52 – 2.14) 0.887 2.58 (1.17 – 5.68) 0.02 0.915 (0.43 – 1.94) 0.82 1.59 (0.65 – 3.86) 0.308 0.833 (0.37-1.88) 0.66 1.27 (0.47-3.42) 0.642
VAI tertile 3 1.28 (0.64 – 2.57) 0.481 5.37 (2.43 – 11.83) <0.01 0.936 (0.44 – 1.99) 0.86 3.75 (1.55 – 9.08) 0.003 0.95 (0.42-2.12) 0.894 3.41 (1.27-9.41) 0.018
417
Model 1: adjusted for age. Model 2: adjusted for age, hypertension, dyslipidaemia, smoking status, total cholesterol, uric acid, diabetes mellitus and HbA1c.
418
CACS: coronary artery calcium score, OR: odds ratio, CI: 95% confidence interval; VAI: visceral adiposity index
419
420
Figure
421
21
422
Figure 1. Study flowchart
423
22
•
Central obesity is associated with cardiovascular risk
•
Visceral adiposity index is associated with coronary calcification
•
Third VAI tertile is a predictor for moderate coronary calcification in males.
S0939-4753(20)30046-6
DOI:
https://doi.org/10.1016/j.numecd.2020.01.013
Reference:
NUMECD 2218
To appear in:
Nutrition, Metabolism and Cardiovascular Diseases
Received Date: 29 July 2019 Revised Date:
29 December 2019
Accepted Date: 29 January 2020
Please cite this article as: Bagyura Z, Kiss L, Lux Á, Csobay-Novák C, Jermendy ÁL, Polgár L, Szelid Z, Soós P, Merkely B, Association between coronary atherosclerosis and visceral adiposity index, Nutrition, Metabolism and Cardiovascular Diseases, https://doi.org/10.1016/j.numecd.2020.01.013. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier B.V. on behalf of The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University.
1 2
Association between coronary atherosclerosis and visceral adiposity index
3
Authors
4 5
Zsolt Bagyura, MD, PhD1
6
Loretta Kiss, MD1
7
Árpád Lux, MD, PhD 1
8
Csaba Csobay-Novák, MD, PhD1
9
Ádám L. Jermendy, MD, PhD 1
10
Lívia Polgár, MD 1
11
Zsolt Szelid, MD, PhD 1
12
Pál Soós, MD, PhD 1
13
Béla Merkely, MD, PhD1
14
1
Heart and Vascular Center, Semmelweis University, Városmajor utca 68, Budapest H-1122, Hungary
15 16 17 18
Corresponding author Zsolt Bagyura, MD, PhD; Heart and Vascular Center, Semmelweis University, Városmajor utca 68, Budapest H-1122, Hungary, Phone: +3670-436-8341, Email: [email protected]
19 20 21 22
Keywords visceral adiposity index, central obesity, coronary calcification, calcium score, cardiovascular risk, cardiology
23 24 25 26 27 28 29 30 31
Acronyms ACE – angiotensin-converting-enzyme, ACS - acute coronary syndrome; ASA – acetylsalicylic acid, BMI - body mass index; CA - Cochran-Armitage; CACS - Coronary artery calcium score; CI confidence interval; CT - computer tomography; CVD - cardiovascular disease; DBP - diastolic blood pressure; DM - diabetes mellitus; HBa1c - haemoglobin-A1c; HDL-C - high-density lipoprotein cholesterol; HU - Hounsfield unit; IQR - interquartile range; LDL-C - low-density lipoprotein cholesterol; OR - odds ratio; VAI - visceral adiposity index; SBP - systolic blood pressure; SD standard deviation
32 33
Abstract: 235 words, text: 3057 words, number of references: 29, tables: 4, figures: 1. 1
34
Abstract
35 36
Background and Aims
37
Visceral obesity is a marker of dysfunctional adipose tissue and ectopic fat infiltration. Many studies
38
have shown that visceral fat dysfunction has a close relationship with cardiovascular disease. For a
39
better identification of visceral adiposity dysfunction, the visceral adiposity index (VAI) is used.
40
Coronary artery calcium score (CACS) is known to have a strong correlation with the total plaque
41
burden therefore provides information about the severity of the coronary atherosclerosis. CACS is a
42
strong predictor of cardiac events and it refines cardiovascular risk assessment beyond conventional
43
risk factors. Our aim was to evaluate the association between VAI and CACS in an asymptomatic
44
Caucasian population.
45 46
Methods and Results
47
screening program. A health questionnaire, physical examination and laboratory tests were also
48
performed. Participants with a history of cardiovascular disease were excluded from the analysis.
49
Mean VAI was 1.41±0.07 in men and 2.00±0.15 in women. VAI showed a positive correlation with
50
total coronary calcium score (r=0.242) in males but not in females. VAI was stratified into tertiles by
51
gender. In males, third VAI tertile was independently associated with CACS>100 (OR: 3.21, p=0.02)
52
but not with CACS>0 after the effects of conventional risk factors were eliminated.
53 54
Conclusion
55
predictor for the presence of CACS>100 in males but not in females.
Computed tomography scans of 460 participants were analyzed in a cross-sectional, voluntary
VAI tertiles were associated with calcium scores and the highest VAI tertile was an independent
56
2
57
Introduction
58
Atherosclerosis is among the leading causes of death in the Western world [1]. Obesity is a well-
59
known risk factor of cardiovascular disease (CVD) [2]. However, central or visceral obesity appear to
60
be more strongly associated with cardiovascular risk [3]. Many studies have shown proinflammatory
61
cytokines, adipocytokines [4] tend to increase and insulin sensitivity decrease in patients with central
62
obesity [5]. Estimating the extent of visceral adiposity with waist circumference (WC) measurement
63
is widely used CVD risk assessment. However, this method cannot distinguish between subcutaneous
64
and visceral fat accumulation. Recently, the visceral adiposity index (VAI) was developed [6] for
65
identification of visceral adiposity dysfunction. VAI is a simple, gender specific marker combining
66
anthropometric data and lipid profiles and are reliable indicator of visceral at dysfunction. Several
67
studies found a strong association of VAI with cardiometabolic risk [7]. Recently, Barazzoni et al.
68
found that compared to WC or BMI VAI had the highest 5-year predictive value for metabolic
69
syndrome in overweight or obese patients [8]. Several studies showed that VAI is a predictor of
70
incident hypertension [9]. Ji et al. reported that VAI has a strong correlation with insulin resistance
71
even in a population without central obesity [10].
72
Calcification of the coronary plaques shows a strong correlation with the total plaque burden [11].
73
Scanning of the heart with low-dose non-contrast computer tomography (CT) provides quantitative
74
information of the extent of the coronary calcification. Coronary artery calcium score (CACS) or
75
Agatston score is a reliable surrogate marker of atherosclerosis and it is a strong predictor of cardiac
76
events [12], therefore could be used for assess the cardiovascular risk beyond conventional risk
77
factors [13]. For ruling out obstructive coronary artery disease CAD, the negative predictive value of
78
a 0 CACS is almost 100%, therefore it indicates a very low cardiovascular event rate [14] CACS
79
above 100 is associated with moderate risk for coronary heart disease [15].
80
Only limited number of studies have examined the relationship between VAI and CACS [16].
81
Therefore, our aim was to evaluate the association between VAI and CACS in an asymptomatic
82
Caucasian population. 3
83
84
Methods
85
Budakalász Health Examinaton Survey, a cross-sectional voluntary cardiovascular screening program
86
targeting the adult population (>20 years, ~8000 inhabitants) of a Central-Hungarian town
87
(Budakalász) was performed in 2011–2013 [17]. Medical history with special attention to
88
cardiovascular disease, related signs and symptoms, lifestyle (alcohol consumption, sport activities,
89
smoking habits) and family history were recorded by an experienced physician. Anthropometric
90
parameters rounded to the nearest 0.1 cm and 0.1 kg were measured in standing position while
91
participants were wearing light indoor clothing without shoes.
92
All laboratory tests were performed in our institution’s central laboratory with rigorous quality
93
control. Concentration of lipid fractions was measured by using a colorimetric assay (Roche
94
Diagnostics Ltd, Mannheim, Germany). Hypertension, dyslipidaemia and diabetes mellitus in medical
95
history were regarded positive if they have been was formerly diagnosed or the patient had received
96
treatment. Body mass index was calculated by using Quetelet’s form. Blood pressure measurement
97
was performed on the arms after 20 minutes rest in a flat lying position. Blood pressure above 140
98
mmHg systolic and/or 90 mmHg diastolic was defined as pathologically high.
99
Prospectively ECG-triggered low dose cardiac CT scans (Brilliance iCT, Philips Healthcare, Best,
100
The Netherlands) for calcium scoring were acquired of the heart with a narrow field-of-view.
101
Effective radiation dose was 0.5 mSv or less. Axial images were used for the quantitative analysis of
102
coronary calcification using a commercially available software application (Calcium scoring,
103
Heartbeat-CS, Philips Healthcare). Coronary artery plaques were identified by the software
104
automatically, followed by selection of real coronary plaques by an expert observer manually. Based
105
on these results the software calculated the CACS, the calcification area and the volume in a semi-
106
automatic way.
4
107
The participation rate in the Budakalász Health Examination Survey was around 30% (n=2420) of the
108
eligible total population. From this 2420 persons a low dose cardiac CT scan was offered for males
109
older than 35 years and in females above 40 years of age (n=2029). Total number of 511 participants
110
volunteered for CT scan. This group was not significantly different from those who were offered the
111
CT in gender, LDL and triglyceride levels, blood pressure, BMI and VAI but the CT subgroup was
112
significantly older (62.12+-10.03 vs. 58.17+-11.91, p<0.001), had slightly higher total cholesterol
113
levels (5.57+1.17 vs 5.56+-1.13, p=0.04). Moreover hypertension (27.8% vs. 21.9%, p=0.002),
114
dyslipidaemia (30.3% vs. 21.7%, p<0.001) and diabetes mellitus (32.3% vs. 24%, p=0.004) were
115
more frequent in this group. Participants with the following cardiovascular history were excluded
116
from the further analysis: 24 patients with previous myocardial infarction (4.7%), 20 patients with
117
stroke (3.9%), 4 patients with transient ischemic attack (0.8%). Also, 3 persons (0.6%) were excluded
118
due to the lack of the laboratory results. As a participant could have more than one exclusion criteria,
119
overall four hundred sixty participants were included in the study. The study flowchart is presented in
120
Fig. 1. The VAI was calculated using the following sex-specific formula [18]:
121
•
Males: VAI = [WC/{39.68 +(1.88*BMI)}]*(TG/1.03)*(1.31/HDL-C)
122
•
Females: VAI = [WC/{36.58+(1.89*BMI)}]*(TG/0.81)*(1.52/HDL-C)
123 124
A post hoc power analysis was conducted using online calculator developed by MGH Biostatistics
125
Center. The sample size of 460 was used for the statistical power analyses. The significance level
126
used for this analysis was p < 0.05. The standard deviation of the dependent variable (CACS) was
127
500.6, the standard deviation of the independent variable (VAI) was 0.32, the minimal detectable
128
difference entered was 244.8. The post hoc analyses revealed that the probability is 91 percent that the
129
study detects a relationship between the independent and the dependent variables.
5
130
Statistical methods
131
SPSS for Windows, version 18.0 (IBM, Armonk, NY) was used for statistical analysis. All continuous
132
variables were expressed as mean with standard deviation (SD) or as medians with interquartile range
133
as appropriate depending on the distribution of the values, whereas categorical variables were
134
expressed as percentage. Comparisons of means, medians and proportions were performed with
135
variance analysis, Kruskal-Wallis test, Jonckheere-Terpstra test, Cochran-Armitage (CA) test and
136
Chi-square tests, respectively. Spearman’s correlation was used to test the association between VAI
137
and CACS. Multivariate regression analysis was performed adjusted for age, gender and risk factors
138
with the 1st VAI tertile as reference category. All analyses were performed two-tailed and p<0.05 was
139
considered significant.
140
141
Ethics approval and consent to participate
142
The research had ethics approval from the Medical Research Council Scientific and Ethics Committee
143
(permission number: 8224-0/2011/EKU (265/PI/11)). All procedures followed were in accordance
144
with the ethical standards of the responsible committee on human experimentation (institutional and
145
national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Written informed consent
146
was obtained from all patients for being included in the study.
147
148
Results
149
The basic characteristics of the male and female participants
150
The mean age was 61.6 (±10.2) years; 41.1% of the participants were men and all patients belonged to
151
the Caucasian race. The mean BMI was 28.6 kg/m2 (±5.1), the mean VAI was 1.76 (± 0.32) and the
152
median CACS score was 19.65 (±161.2). Clinical baseline characteristics of the 189 male and 271
153
female patients are described in Table 1. Waist circumference, smoking status, mean systolic blood 6
154
pressure, HDL-C, total cholesterol and serum creatinine were significantly different between genders.
155
Mean VAI was 1.41±0.07 in men and 2.00±0.15 in women (p<0.001), butt BMI was not significantly
156
different between the two genders. Drug therapies could have effect on atherosclerotic plaques, but we
157
have found no difference in the lipid lowering angiotensin-converting enzyme inhibitor and
158
acetylsalicylic acid drug usage between the two genders.
159
VAI differs substantially between males and females, therefore VAI was stratified into tertiles by
160
gender (Table 2.) for further analysis. Waist circumference was significantly different in the three
161
tertile groups in both genders. Age, BMI, low-density lipoprotein (LDL-C), total cholesterol and
162
haemoglobin-A1c (HBa1c) levels were significantly different in the three tertile groups in males but
163
not in females. Also, the frequency of hypertension and diabetes increased gradually in males in the
164
groups and was highest in the third tertile group. In contrast, there were no significant differences in
165
the age, BMI or the other above-mentioned factors’ distribution among the three groups in females.
166
Menopause can affect adiposity; therefore, we analysed the menstruation status in females. As there
167
was no difference in this parameter across the three tertiles (tertile 1: 64 (71.1%), tertile 2: 63 (69.2%)
168
and tertile 3: 63 (70%), p=0.589) the effect of menopause was not further analysed. Clinical
169
characteristics in the VAI tertiles by gender are described in Table 3.
170
171
CT scan results
172
Median total calcium score was 19.4 (IQR: 161.6) in the study group. VAI only showed a positive
173
correlation with total coronary calcium score in males (r=0.242, p<0.001). The Jonckheere-Terpstra
174
test for total CACS confirmed a trend across VAI groups in males (J-T statistic: 7419, p<0.001) but
175
not in females. Total CACS was 0 in 41 cases in males (21.7%) and in 108 cases (39.9%) in females.
176
It was less or equal to 100 in 112 cases (59.3%) in males and 209 cases (77.1%) in females. There was
177
no statistically significant difference in the frequency of CACS > 0 in neither gender. Frequency of
178
CACS >100 was significantly different in the three VAI groups in males but not in females (Table 3.)
179
and there was a trend across VAI groups (CA statistic: 14.476, p<0.001). The highest tertile group had 7
180
significantly higher odds ratio for CACS >100 only in males (OR 5.37, 95% CI: 2.43 – 11.83, p<0.01)
181
compared to the lowest tertile (Table 4).
182
183
Multivariate analysis
184
We performed multivariate analysis with presence of CACS>100 adjusted for age. In this model the
185
highest tertile group had significantly higher odds ratio for CACS >100 in males (Model 1: OR 3.75,
186
95% CI:1.55–9.08, p=0.003) compared to the lowest tertile, but not in females (Table 4). Similarly,
187
after further adjustments for BMI, hypertension, dyslipidaemia, smoking status, total cholesterol and
188
uric acid level, diabetes mellitus and HbA1c levels in model 2 the highest tertile group was
189
independently associated with CACS>100 in males (Model 2: OR 3.41, 95% CI: 1.27–9.41, p=0.018)
190
compared to the lowest tertile. BMI was not independently associated with CACS>100 in either
191
gender.
192
Discussion
193
In this study we presented an independent association of VAI with coronary calcification in an
194
asymptomatic Caucasian population. We found that VAI showed a positive correlation with CACS
195
(r=0.242). In logistic regression analyses, compared to the lowest VAI tertile, the highest tertile was
196
an independent predictor and showed significantly increased odds for the presence of moderate-risk
197
coronary calcification (CACS>100) in males but not in females. The association remained significant
198
even after adjusting for confounding variables including BMI. We found no statistically significant
199
association of VAI with the presence of any coronary calcification (CACS > 0).
200 201
Visceral obesity is a marker of dysfunctional adipose tissue and a well-known risk factor of CVD [2]
202
and the most prevalent manifestation of metabolic syndrome [19], [20], [21], [22]. Waist
203
circumference measurement [23] is known to be more informative in connection with visceral 8
204
adiposity than BMI, although it cannot distinguish well between subcutaneous fat and visceral
205
obesity. To overcome this VAI was developed for more precise assessment of cardiometabolic risk as
206
it is based on sex, WC, BMI and lipid parameters [6]. VAI is known to be increased significantly in
207
metabolically healthy obese individuals compared to metabolically healthy normal-weight individuals
208
and is a novel risk factor of CVD [7].
209
There is no ideal cut-off value for VAI that helps to distinguish normal and dysfunctional visceral
210
adiposity. Some researchers use tertiles [24], others use quartiles as a cut-off value for the analysis
211
[25]. We used tertiles and found that the third tertile of VAI is correlated positively with CACS in
212
both regression models.
213
Our results showed that there is an association between VAI and the prevalence of classic markers of
214
cardiometabolic risk (BMI, hypertension, as well as diabetes mellitus and HBa1c) in males, but not in
215
females. We found no significant differences in the VAI terciles regarding dyslipidaemia, triglyceride
216
LDL-C and HDL-C levels. These results are partially in line with the findings of Amaro et al [6] who
217
demonstrated that VAI has strong correlation with metabolic markers independently of genders.
218
According to our results the three tertiles in males are more heterogeneous in the frequency of having
219
cardiovascular risk factors, and higher tertile means higher frequency of cardiovascular risk factors. In
220
contrast there is no significant difference in females among the tertiles. In our study the range of VAI
221
differs basically in the two genders. In males in the first tertile group the VAI is between 1.03 and
222
1.37, but in females the first tertile is between 1.35 and 1.94, so the average VAI is significantly
223
higher even in the first tertile. Moreover, the maximal value in the first tertile of females is higher
224
than the overall maximal VAI value in males. Distribution of VAI is different between the two
225
genders in our population mainly because females have relatively worse waist circumference. In our
226
study group according to our results the metabolically active central obesity affects almost all females
227
(high average VAI) in contrast to males were there is a gradual increase from “normal” VAI to the
228
worse values.
229 9
230
In our study we included males over 35 years and females over 40 years only. If we compare the
231
average age in the tertile groups in males age is increasing significantly in contrast to females where
232
the first tertiles is almost five years older in average and there is no significant difference among the
233
tertile groups. Moreover, the menopause of women could affect the results, but we found no
234
difference in this parameter across the three tertiles in females.
235
Males with higher CACS had a significantly higher VAI compared to those without CACS in our
236
study. The risk of CACS >100 was significantly higher in the upper VAI tertiles compared to the
237
lowest tertile (OR 3.41, 95% CI:1.4–8.31, p=0.007), even after adjusting for several factors (OR 3.21,
238
95% CI:1.16–8.85, p=0.024). In our study BMI was not independently associated with CACS in
239
contrast to VAI. The association between VAI and CACS but not BMI could be explained by the
240
metabolically active central fat accumulation, that results in increased circulating free fatty acid
241
levels, systemic inflammation, insulin sensitivity and vasculopathy [26] [27].
242 243
In contrast to our results Park et al. [16] have found association between VAI and CACS>100 in both
244
genders. Moreover, we did not find association between CACS>0 and VAI, in contrast to Parks’
245
group, who found that the risk of CACS >0 was higher in the upper VAI tertiles compared to the
246
lowest tertile in both genders. However, there are important differences between our and Park’s study.
247
Park et al investigated more than 33,000 patients from the Korean population, 80.2% of total
248
participants were men. This gender imbalance could have affected the results as Park et al, who
249
created three tertile groups based only on VAI but not gender. In contrast, in our study 41.1% of the
250
participants were men and all participants were from the Caucasian race. It is noteworthy that VAI
251
was modelled on a Caucasian population, and this is an important limitation to consider when it is
252
applied in non-Caucasian populations. According to our results, the distribution of VAI was
253
significantly different between genders, therefore we created gender-based tertiles, and this could
254
explain the difference that we found between males and females. It is probable that the association
255
between VAI and CACS is gender-dependent and different in the Central European and Korean 10
256
population. Our result are in line with the results of Randrianarisoa et al [28] who found significant
257
association between VAI and carotid intima media thickness, a marker of subclinical atherosclerosis,
258
along with age, smoking and male sex and with the results of Kouli et al [29] who found that VAI is
259
independently associated with elevated 10-year CVD risk, particularly in men. Finally, in Park’s
260
study, the mean participant age was 41.5 years, and the mean BMI was 24.3 kg/m2. Our study group
261
was more than 20 years older and more obese in average. It is possible that these are the main reasons
262
behind that the mean CACS was significantly higher (11.2 ± 72.0. vs. 211.8 ±540.1). According to
263
their results, they have found 1.8 to 1.2 OR for CACS >100 in the upper VAI tertiles compared to the
264
lowest tertile. In contrast, we have found an approximately two times higher risk, but only in males.
265 266
This study has some limitations. Firstly, as cross-sectional study we cannot imply causality between
267
VAI and CACS based on these results. Secondly, we indicated low-dose CT only for men above 35
268
and women above 40, therefore patients with lowest cardiovascular risk were excluded from our
269
study. Third, there is no appropriate VAI cut-off value to estimate cardiovascular risk; we used tertile
270
values and compared to CACS or to the proportion of subjects with CACS>100.
271 272
VAI is a simple, gender specific indicator of visceral fat dysfunction and known to be associated with
273
increased risk of CVD. CACS is a reliable surrogate marker of atherosclerosis, however it is not
274
widely used in primary care settings. In conclusion, in an asymptomatic population VAI tertiles were
275
associated with CACS and the third VAI tertile was an independent predictor for the presence of
276
moderate-risk coronary calcification in males but not in females. Our results suggest that VAI could
277
be a useful clinical marker of cardiometabolic risk and effect of central obesity as a risk factor in more
278
pronounced in males and could have ethnic difference. The association between VAI and CACS may
279
have significant implications for identifying patients in risk for atherosclerotic coronary artery disease
280
in primary prevention.
281 11
282
12
283
Acknowledgements
284
285
Competing Interests
286
The authors declare that they have no conflict interests.
287
Funding
288
This work was supported by the National Research, Development and Innovation Office of Hungary
289
(NKFIA; NVKP-16- 1-2016-0017). The research was financed by the Higher Education Institutional
290
Excellence Programme of the Ministry of Human Capacities in Hungary, within the framework of the
291
Therapeutic Development thematic programme of the Semmelweis University.
292
293
Authors' contributions
294
Zsolt Bagyura, Loretta Kiss carried out the statistical analysis and drafted the manuscript. Zsolt
295
Bagyura, Loretta Kiss, Pál Soós, Zsolt Szelid participated in the design of the study Zsolt Bagyura,
296
Loretta Kiss, Lívia Polgár, Árpád Lux, Pál Soós, Zsolt Szelid performed the data collection from the
297
patients. Csaba Csobay-Novák, Ádám L. Jermendy, Árpád Lux performed the calcium scoring. All
298
authors read and approved the final manuscript.
299 300
13
301
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Tables
400 401
Table 1. Clinical baseline characteristics 16
Males (N=189)
Females (N=271) p
60.55 (11.16)
62.11 (9.41)
0.107
Waist Circumference (cm), mean 103.66 (11.66) (SD)
96.54 (12.81)
<0.001
BMI, mean (SD)
28.61 (4.31)
28.56 (5.53)
0.924
Hypertension, n (%)
153 (81.0%)
221 (81.5%)
0.873
Dyslipidaemia, n (%)
79 (41.8%)
132 (48.7%)
0.143
Statin therapy, n (%)
35 (18.5%)
54 (19.9%)
0.721
Other lipid lowering therapy, n (%)
6 (3.2%)
3 (1.1%)
0.115
ACE inhibitor therapy, n (%)
54 (28.6%)
77 (28.4%)
0.971
ASA therapy, n (%)
27 (14.3%)
31 (11.4%)
0.366
DM, n (%)
30 (15.9%)
33 (12.2%)
0.257
Active smoker, n (%)
24 (12.7%)
28 (10.3%)
0.430
Smoker (current + former), n (%)
92 (48.7%)
91 (33.6%)
0.010
SBP (mmHg), mean (SD)
135.05 (16.16)
138.52 (19.99)
0.040
DBP (mmHg), mean (SD)
80.50 (8.82)
80.26 (9.85)
0.789
LDL-C (mmol/l), mean (SD)
3.45 (0.97)
3.53 (1.05)
0.400
HDL-C (mmol/l), mean (SD)
1.33 (0.26)
1.65 (0.49)
<0.001
Triglyceride (mmol/l), mean (SD)
2.47 (1.50)
2.31 (1.52)
0.265
Total cholesterol (mmol/l), mean 5.54 (1.11) (SD)
5.86 (1.15)
0.003
Serum creatinine (µmol/l), mean 85.77 (15.71)
80.87 (15.11)
0.010
Age, mean (SD)
17
(SD) Serum uric acid (µmol/l), mean (SD)
350.47 (79.11)
299.66 (68.98)
<0.001
HbA1c (%), mean (SD)
5.80 (0.74)
5.91 (0.75)
0.112
VAI, mean (SD)
1.41 (0.07)
2.00 (0.15)
<0.001
LogCACS score, mean (SD)
1.57 (1.13)
1.03 (1.03)
<0.001
CACS, median (IQR)
55.7(349)
6.66 (86.8)
<0.001
CACS >0
148 (78.3%)
163 (60.1%)
<0.001
CACS >100, n (%)
77 (40.7%)
62 (22.9%)
<0.001
Agatston score >400, n (%)
42 (22.2%)
21 (7.7%)
<0.001
402
Means ± SDs (or median±IQR in case of CACS) represented the continuous variables, and proportions the categorical variables. CACS – coronary artery
403
calcium score, DBP - diastolic blood pressure, DM - diabetes mellitus, HDL-C - high-density lipoprotein cholesterol, IQR – interquartile range, LDL-C - low-
404
density lipoprotein cholesterol, SBP - systolic blood pressure, SD – standard deviation
405 406
Table 2 - Tertiles of VAI by gender in the study population
Tertile
Males (min-max, N)
Females (min-max, N)
1
1.03 - 1.37, 62
1.35 - 1.94, 90
2
1.38 - 1.44, 64
1.95 - 2.05, 91
3
1.45 - 1.59, 63
2.06 - 2.36, 90
407 408
Table 3. Clinical baseline characteristics in the VAI tertiles by gender
18
Age, mean (SD)
Males
Females
p VAI VAI VAI tertile 1 tertile 2 tertile 3 (N=62) (N=64) (N=63)
p VAI VAI VAI tertile] 1 tertile 2 tertile 3 (N=90) (N=91) (N=90)
62.4 (10.95)
62.98 (9.98)
<0.001 60.58 (9.54)
61.91 (9.48)
63.84 (9.01)
WC (cm), mean 94.1 (SD) (7.94)
104.2 (7.15)
111.67 (11.69)
<0.001 89.27 (12.55)
98.30 (11.55)
102.05 <0.001 (10.87)
BMI, mean (SD)
28.97 (3.48)
29.84 (5.25)
<0.001 28.73 (6.01)
29.34 (5.68)
27.62 (4.75)
n 41 (66.1%)
53 (82.8%)
58 (92.1%)
0.001
0.497 76 75 70 (84.4%) (82.4%) (77.8%)
Dyslipidaemia, n 21 (%) (33.9%)
30 (46.9%)
27 (42.9%)
0.317
0.571 40 45 48 (44.4%) (49.5%) (52.2%)
DM, n (%)
2 (3.2%)
10 (15.6%)
17 (27.0%)
0.001
0.913 11 12 10 (12.2%) (13.2%) (11.1%)
Active smoker, n 11 (%) (17.7%)
6 (9.4%)
7 (11.1%)
0.332
6 (6.6%) 9 0.220 13 (14.4%) (10.0%)
Smoker (current + 22 former), n (%) (35.5%)
35 (54.7%)
35 (56.6%)
0.04
0.329 28 36 27 (31.1%) (39.6%) (33.6%)
SBP (mmHg), 133.3 mean (SD) (16.42)
135.32 (17.34)
137.8 (14.53)
0.601
139.84 (22.02)
138.15 (19.10)
137.58 0.733 (18.88)
DBP (mmHg), 80.42 mean (SD) (8.71)
80.43 (9.72)
81.87 (8.16)
0.728
81.08 (8.58)
81.01 (11.55)
78.7 (9.03)
0.183
LDL-C (mmol/l), 3.79 mean (SD) (1.11)
3.37 (0.79)
3.25 (0.92)
0.005
3.60 (1.13)
3.49 (1.01)
3.51 (1.02)
0.772
HDL-C (mmol/l), 1.36 mean (SD) (0.31)
1.28 (0.26)
1.37 (0.46)
0.263
1.73 (0.56)
1.60 (0.42)
1.63 (0.49)
0.219
Hypertension, (%)
55.92 (11.55)
26.89 (3.32)
19
0.064
0.104
Triglyceride 2.37 (mmol/l), mean (1.47) (SD)
2.32 (1.36)
2.69 (1.66)
0.311
2.16 (1.23)
2.26 (134)
2.50 (1.91)
0.321
Total cholesterol 5.87 (mmol/l), mean (1.32) (SD)
5.40 (0.9) 5.44 (0.98)
0.019
5.95 (1.19)
5.76 (1.21)
5.86 (1.06)
0.564
Statin therapy, n 5 (8.1) (%)
17 (26.6)
13 (20.6)
0.178
19 (21.1) 20 (22.0) 15 (16.7) 0.672
ACE inhibitor 12 (19.4) therapy, n (%)
22 (34.4)
20 (31)
0.817
30 (33.3) 25 (27.5) 22 (24.4) 0.405
Other lipid 2 (3.2) lowering therapy, n (%)
2 (3.2)
2 (3.2)
0.999
0 (0)
ASA therapy, n 5 (8.1) (%)
10 (14.5)
12 (20.7)
0.142) 9 (10)
11 (12.1) 11 (12.2) 0.871
Serum creatinine 84.53 (µmol/l), mean (15.7) (SD)
87.1 (14.21)
58.2 (15.34)
0.322
69.69 (14.60)
72.69 (15.31)
0.353 70.32 (15.40)
Serum uric acid 344.18 (µmol/l), mean (80.75) (SD)
349.38 (85.83)
357.67 (70.66)
0.634
300.34 (70.49)
297.20 (68.98)
301.48 0.911 (68.17)
HbA1c (%), mean 5.53 (SD) (0.37)
5.81 (0.59)
5.97 (0.72)
<0.001 5.84 (0.74)
5.95 (0.72)
5.96 (0.81)
0.500
VAI, mean (SD)
1.33 (0.05)
1.41 (0.02)
1.48 (0.03)
<0.001 1.84 (0.10)
2.00 (0.32)
2.16 (0.76)
<0.001
LogCACS score, 1.15 mean (SD) (1.05)
1.68 (1.10)
1.85 (1.13)
0.001
1.05 (1.05)
1.02 (0.97)
1.02 (1.01)
0.970
CACS, (IQR)
56.82 (342.1)
147.54 (530.1)
0.001
11.57 (79.9)
6.42 (89.7)
0.963 5.46 (105.5)
52 (81.3%)
52 (82.5%)
0.228
0.534 52 59 52 (57.8%) (64.8%) (57.8%)
CACS >0
median 14.3 (62.4) 44 (71.0%)
20
1 (1.1)
2 (2.2)
0.362
n 13 (21.0%)
26 (40.6%)
37 (58.7%)
<0.001 19 0.753 20 23 (21.1%) (22.0%) (25.6%)
Agatston score 9 >400, n (%) (14.5%)
14 (21.9%)
18 (28.6%)
0.162
CACS (%)
>100,
8 (8.9%) 3 (3.3%) 10 0.128 (11.1%)
409 410
Means ± SDs (or median±IQR in case of CACS) represented the continuous variables, and proportions the categorical variables. Continuous variables were
411
analysed via One-way ANOVA or Kruskal-Wallis test in case of CACS, categorical variables were analysed via the Chi-square test. ACE – angiotensin-
412
converting-enzyme, ASA – acetylsalicylic acid, CACS – coronary artery calcium score, DBP - diastolic blood pressure, DM - diabetes mellitus, HDL-C - high-
413
density lipoprotein cholesterol, IQR – interquartile range LDL-C - low-density lipoprotein cholesterol, SBP - systolic blood pressure, SD - standard deviation
414 415
Table 4. Odds ratios for coronary artery calcification (CACS > 100) by gender according to tertiles of
416
VAI
Unadjusted Female Male Model 1
Female Male
Model 2
Female Male
OR (CI) p OR (CI) p OR (CI) p OR (CI) p OR (CI) p OR (CI) p
VAI tertile 1 1 (reference) 0.754 1 (reference) <0.01 1 (reference) 0.972 1 (reference) 0.09 1 (reference) 0.903 1 (reference) 0.03
VAI tertile 2 1.05 (0.52 – 2.14) 0.887 2.58 (1.17 – 5.68) 0.02 0.915 (0.43 – 1.94) 0.82 1.59 (0.65 – 3.86) 0.308 0.833 (0.37-1.88) 0.66 1.27 (0.47-3.42) 0.642
VAI tertile 3 1.28 (0.64 – 2.57) 0.481 5.37 (2.43 – 11.83) <0.01 0.936 (0.44 – 1.99) 0.86 3.75 (1.55 – 9.08) 0.003 0.95 (0.42-2.12) 0.894 3.41 (1.27-9.41) 0.018
417
Model 1: adjusted for age. Model 2: adjusted for age, hypertension, dyslipidaemia, smoking status, total cholesterol, uric acid, diabetes mellitus and HbA1c.
418
CACS: coronary artery calcium score, OR: odds ratio, CI: 95% confidence interval; VAI: visceral adiposity index
419
420
Figure
421
21
422
Figure 1. Study flowchart
423
22
•
Central obesity is associated with cardiovascular risk
•
Visceral adiposity index is associated with coronary calcification
•
Third VAI tertile is a predictor for moderate coronary calcification in males.