’Original article Increased abdominal fat levels measured by bioelectrical impedance are associated with histological lesions of nonalcoholic steatohepatitis Aikaterini Margaritia, Meropi D. Kontogiannic, Nafsika Tilelic, Michael Georgoulisc, Melanie Deutscha, Rodessa Zafeiropouloua, Dina Tiniakosd, Yannis Maniosc, Dimitrios Pectasidesa and George V. Papatheodoridisa,b Background/aim Abdominal fat is considered to play an important role in nonalcoholic fatty liver disease (NAFLD), although it is not adequately studied because abdominal fat levels cannot be estimated easily. In this study, associations between abdominal obesity, as assessed by abdominal bioelectrical impedance analysis (BIA), and the characteristics of patients with NAFLD were explored. Patients and methods Seventy-four consecutive NAFLD patients who underwent measurement of abdominal fat levels by BIA were included. Levels of abdominal fat 12.5 or less and more than 12.5 were considered to be average and increased, respectively. Results The mean ± SD BMI was 30 ± 4 kg/m2 and the mean abdominal fat levels were 16 ± 5, whereas 26% of patients had average abdominal fat levels. Patients with average compared with those with increased abdominal fat levels were more frequently women (50 vs. 12%, P = 0.001), had lower BMI (27 ± 3 vs. 31 ± 4 kg/m2, P < 0.001), lower Homeostasis Model Assessment index (2.6 ± 1.4 vs. 3.9 ± 2.7, P = 0.045), and lower median liver stiffness on transient elastography (5.3 vs. 6.8 kPa, P = 0.025). In patients with available liver biopsy, steatohepatitis was present more frequently in patients with increased compared with average abdominal fat levels (78 vs. 38%, P = 0.030) and in patients with BMI 30 or more compared with less than 30 kg/m2 (87 vs. 48%, P = 0.033), but similar in patients with increased or normal waist circumference (67 vs. 56%, P = 0.693). Conclusion Average levels of abdominal fat, as assessed by abdominal BIA, are mainly present in female patients with NAFLD and are associated with a lower degree of insulin resistance. Increased abdominal fat as assessed by BIA and obesity seem to represent strong risk factors for histological steatohepatitis. Eur J Gastroenterol Hepatol 00:000–000 Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
Introduction
Abdominal fat is one of the key components of insulin resistance [1] and has been shown to be related to the presence of insulin resistance associated with metabolic disorders, including nonalcoholic fatty liver disease (NAFLD) [2–4]. Moreover, visceral fat plays a key role in the pathogenesis of NAFLD [5], whereas increased amounts of visceral fat have been associated with the development of nonalcoholic steatohepatitis (NASH) [6,7]. However, although the amount of visceral fat might be useful in diagnosing patients at an increased risk for European Journal of Gastroenterology & Hepatology 2015, 00:000–000 Keywords: abdominal fat, bioelectrical impedance analysis, nonalcoholic fatty liver disease, nonalcoholic steatohepatitis a
2nd Department of Internal Medicine, Hippokration Hospital of Athens, Academic Department of Gastroenterology, Laiko Hospital of Athens, Athens University Medical School, cDepartment of Nutrition and Dietetics, Harokopio University and dLaboratory of Histology and Embryology, Medical School, National and Kapodistrian University of Athens, Athens, Greece b
Correspondence to George V. Papatheodoridis, MD, Academic Department of Gastreonterology, Laiko General Hospital of Athens, 17 Agiou Thoma Street, 115 27 Athens, Greece Tel: + 30 210 745 6513; fax: + 30 210 746 2601; e-mail: [email protected] Received 8 December 2014 Accepted 1 April 2015
development of NASH, it cannot be estimated easily and accurately. The two most reliable methods, computed tomography and MRI, are expensive and sometimes not widely available in daily clinical practice, whereas computed tomography also involves patient exposure to ionizing radiation [8]. Anthropometric indices such as waist circumference (WC) and waist to hip ratio may be used as surrogate markers of abdominal adiposity, but their accuracy remains questionable [8–10]. Bioelectrical impedance analysis (BIA) is a noninvasive body composition method that has been used extensively in assessing the total body water, the fat-free mass, and the fat mass of various groups of individuals. It is a safe method, rapid, portable, and easy to perform, and requires minimal operator training [11]. Recently, a new technique, combining the use of infrared and abdominal BIA, has been developed to measure WC and to estimate trunk fat percentage and total abdominal fat [12–15]. The aim of this study was to explore, for the first time, associations between abdominal obesity, as assessed by abdominal BIA, and metabolic or histological characteristics of patients with NAFLD and compare them with more classical indices of obesity, namely, increased BMI and increased WC.
0954-691X Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
DOI: 10.1097/MEG.0000000000000381
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Month 2015 • Volume 00 • Number 00
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Patients and methods
Seventy-four patients with NAFLD evaluated between March 2009 and July 2011 were included in this prospective cohort study. NAFLD patients of this study had abnormal alanine aminotransferase and/or γ glutamyl transferase activity, ultrasonographic evidence of hepatic steatosis and/or compatible liver histology, and no other cause of liver injury. More specifically, all patients were negative for hepatitis B surface antigen (HBsAg), antibodies against hepatitis C virus (anti-HCV), and antibodies against HIV. In addition, none of the patients reported alcohol use of more than 210 or 140 g/week for men and women, respectively. The history of alcohol use was provided by the patients and was confirmed by the patients’ relatives or friends. None of the patients reported use of any hepatotoxic drug or agent or had any systemic disease with potential liver involvement. The demographic characteristics and medical history details were recorded for all patients. The history of known arterial hypertension was recorded, whereas arterial blood pressure was also measured during the initial visit with the patient in a relaxed state. The presence of diabetes mellitus was recorded, with diabetes being diagnosed in cases with a known history on antidiabetic treatment and/or fasting glucose more than 126 mg/dl on more than one occasion. The study was approved by the hospital’s ethics committee. Informed consent was obtained from all the study participants. Anthropometric and body composition assessment
The body weight of the participants was measured using a digital scale (Seca Robusta 813; Seca, Hamburg, Germany) to the nearest 100 g and height to the nearest 0.5 cm. BMI was calculated as weight (kg) divided by height squared (m2). WC was tape measured to the nearest 0.1 cm midway between the lowest rib and the superior border of the iliac crest at the end of normal expiration using a nonelastic measuring tape positioned at a level parallel to the floor and with the participant in a standing position. Increased WC was defined as more than 102 cm for men and more than 88 cm for women. Abdominal fat compartments were estimated by the abdominal BIA method using the device ViScan AB-140 (Tanita Corporation, Tokyo, Japan). BIA is a noninvasive, simple, and inexpensive method used to estimate body composition based on a two-compartment model. It measures the impedance or resistance to a small electrical current as it circulates through the body’s water pool. An estimate of total body water is obtained from which total body fat-free mass is calculated on the basis of the assumption that 73% of the body’s fat-free mass is water [16]. Unlike whole-body BIA, the ViScan AB-140 is directly measuring abdominal transimpedance and is therefore considered to better reflect the local conducting tissue compartments, whereas the algorithm used by the device does not rely on factors such as age, weight, or height to estimate body fat. For the conduction of the measurement, the patients lay supine on an examination bed. The device uses a tetrapolar impedance method, involving two pairs of injecting and sensing electrodes. These electrodes are located on a wireless measurement
belt, which was placed directly on wet skin at the umbilicus in the sagittal plane, as described in the device manual. The measurements were performed in the morning, after overnight fasting, and at least 2 h after consumption of water or any other liquid. The patient was in a relaxed state for at least 1 h before the measurement. ViScan abdominal body composition values were derived from extrapolation of impedance measures (at 6.25 and 50 kHz) using in-built software and subdivided into total abdominal adiposity (i.e. intra-abdominal adipose tissue and subcutaneous abdominal adipose tissue) expressed as trunk fat% (range 0–75%) and intra-abdominal adipose tissue (corresponding to visceral fat), expressed as abdominal fat level (range 1–59 AU) [17]. Level 13 has been found to correspond to 130 cm2 of visceral fat, as estimated by computed tomography of the abdomen, but the overall prediction of the visceral fat has been reported to be limited, especially in individuals with abdominal obesity [17]. The device also rates the results of its measurements using arbitrary band ratings and thus levels of abdominal fat are rated as average (≤ 12.5), high (12.6–17.5), and very high (>17.5). Laboratory markers
The laboratory data recorded included complete blood count, prothrombin time, uric acid, urea, creatinine, liver enzymes (alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, γ glutamyl transferase), total protein, albumin, serum copper, ceruloplasmin, iron and ferritin, as well as detection of HBsAg, anti-HBc, antiHBs, anti-HCV, anti-HIV, and liver autoantibodies (antinuclear, antismooth muscles, antimicrosomial, antimitochondrial). Serum fasting glucose, total cholesterol, and high-density lipoprotein-cholesterol were measured using the enzymatic colorimetric method (Analyzer Cobas 8000; Roche Diagnostics International Ltd, Rotkreuz, Switzerland) and low-density lipoprotein-cholesterol was calculated using the Friedewald formula [18]. Serum triglycerides were measured using the chromatometric enzymatic method (Analyzer Cobas 8000; Roche Diagnostics International Ltd), insulin and ferritin with chemiluminescence (Centaur Analyzer; Siemens), and high sensitivity C-reactive protein was measured using a nephelometric assay (BN II Nephelometer; Siemens AG, Erlangen, Germany). Tumor necrosis factor-α (TNF-α), interleukin (IL)-6, IL-8, vascular endothelial growth factor (VEGF), transforming growth factor-β1 (TGF-β1), and adiponectin were measured using a sensitive enzyme-linked immunosorbent assay (ELISA, Quantikine/Immunoassay Kit; R&D Systems, Minneapolis, Minnesota, USA). The intraassay coefficient of variation was less than 7% for TNF-α, IL-8, and VEGF and less than 5% for IL-6, TGF-β1, and adiponectin. The interassay coefficient of variation was less than 8% for TNF-α, IL-6, and adiponectin and less than 10% for IL-8, TGF-β1, and VEGF. Definitions
BMI was calculated as weight (kg) divided by height squared (m2). Patients were considered obese if they had BMI 30 kg/m2 or more. Metabolic syndrome was defined according to the National Cholesterol Education Program: Adult Treatment Panel III criteria [19]. In this study, the
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Abdominal fat and NASH Margariti et al.
fulfillment of the criterion of elevated arterial pressure was based on the patients’ history and repeated measurements and not on the single arterial pressure measurement on the day of evaluation. Patients were considered to have dyslipidemia if they fulfilled at least one of the following criteria: (i) total cholesterol more than 200 mg/dl, (ii) lowdensity lipoprotein-cholesterol more than 120 mg/dl, (iii) triglycerides more than 150 mg/dl at the time of diagnosis or during follow-up, or (iv) were being treated with lipidlowering medication. Transient elastography
Reliable liver stiffness measurements (LSMs) (in kPa) by transient elastography (FibroScan; Echosens, Paris, France) were available in 53 of the 74 patients. The examination was considered to be reliable if 10 successful measurements were obtained, with a success rate more than 60% and a ratio of interquartile range to mean stiffness less than 30%. For patients who underwent both transient elastography and liver biopsy, LSM was performed a few hours before liver biopsy in most or within 4 weeks before or after liver biopsy in some patients. In any case, LSM was performed within the first 4 weeks from the diagnosis of NAFLD. Liver histology
Adequate liver biopsies were available in 36 of the 74 patients. They were evaluated by a single hepatopathologist (D.T.), who was blinded to the clinical data. A liver biopsy was considered to be adequate if at least six portal tracts were identified and the specimen length was 1.5 cm or more. The diagnosis of NASH was made on the basis of the overall pattern of injury and the criteria of Brunt et al. [20] modified by Kleiner et al. [21]. Global grading of necroinflammatory activity and staging of fibrosis were assessed according to Brunt et al. [20]. The severity of steatosis and the NAFLD activity score (NAS) were evaluated according to Kleiner et al. [21]. Statistical analysis
All analyses were carried out using the SPSS statistics (SPSS Inc., an IBM Company, Chicago, Illinois, USA). Quantitative data were expressed as mean ± SD or as median (range) values. The normality of distribution of continuous quantitative variables was tested using the Shapiro–Wilk or the Kolmogorov–Smirnov test, as appropriate. Comparisons between groups of quantitative variables with a normal or a non-normal distribution were performed using the t-test or the Mann–Whitney test, respectively. Comparisons of categorical variables were performed using the corrected χ2 or the Fischer’s exact test, as appropriate. Correlations between quantitative variables were assessed using Pearson’s or Spearman’s correlation coefficients. A two-tailed P value less than 0.05 was considered to be statistically significant. Results
The main demographic, medical history, anthropometric, and laboratory characteristics of the 74 patients according
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to categories of abdominal fat level BMI and WC are presented in Table 1. For the statistical analyses, patients with high and very high levels of abdominal fat were included in the same category of increased abdominal fat. The prevalence of the metabolic syndrome was similar between patients with increased and average levels of abdominal fat, whereas increased WC and obesity were associated with a significantly higher prevalence of metabolic syndrome (nonobese: 29% vs. obese patients: 61%, P = 0.010; patients with normal WC: 13% vs. increased WC: 59%, P < 0.001) (Table 1). WC as a continuous variable correlated positively with systolic blood pressure (r = 0.302, P = 0.019), serum fasting glucose (r = 0.350, P = 0.003), and serum triglycerides (r = 0.272, P = 0.025), as well as with levels of abdominal fat, as estimated by BIA (r = 0.644, P < 0.001) The number of criteria of the metabolic syndrome correlated significantly with the levels of abdominal fat (r = 0.290, P = 0.030). The levels of inflammatory markers and cytokines are shown in Table 2. Insulin levels were higher and insulin resistance was more prominent among patients with increased than patients with average levels of abdominal fat (insulin: P = 0.015; Homeostasis Model Assessment (HOMA): P = 0.045), as well as among obese than nonobese patients (insulin: P = 0.002; HOMA: P = 0.001). Moreover, patients with increased compared with those with normal WC had a higher degree of insulin resistance (HOMA: P = 0.029), but not significantly different insulin levels (P = 0.115). The histological characteristics of this cohort are shown in Table 3. The majority (64%) of patients with available liver biopsy had NASH. The presence of NASH was associated with increased levels of abdominal fat (OR 5.76, 95% CI 1.29–25.64, P = 0.030) and the presence of obesity (OR 7.15, 95% CI 1.28–39.83, P = 0.033), but not with increased WC. There was no association between grade of necroinflammation, stage of fibrosis, or severity of steatosis and levels of abdominal fat as a continuous variable, BMI, or WC. However, when patients were grouped into those with average and those with increased abdominal fat, more than half (54%) of the cases with average levels of abdominal fat had no fibrosis on liver biopsy compared with only 13% of cases with increased abdominal adiposity (P = 0.018). The mean LSMs by transient elastography differed only among patients with average or increased levels of abdominal fat, being lower in the former group (P = 0.025) (Table 3). As obesity can be a strong confounding factor, the associations between patients’ characteristics and abdominal fat level were explored only in the 38 nonobese patients (BMI < 30 kg/m2) as well. In this subgroup, the 23 patients with increased compared with the 15 patients with average abdominal fat level were more frequently men [22/23 (95.7%) vs. 9/15 (60.0%), P < 0.001] and had lower levels of high-density lipoprotein-cholesterol (26.3 ± 9.4 vs. 32.4 ± 11.8 mg/dl, P = 0.002), whereas they did not differ in the frequency of diabetes mellitus [2/23 (8.7%) vs. 0/15 (0%), P = 0.509], arterial hypertension [3/23 (13%) vs. 3/15 (20%), P = 0.663], metabolic syndrome [5/23 (22%) vs. 6/15 (40%), P = 0.285], and NASH [6/10 (60.0%) vs. 4/11 (36.4%), P = 0.395]. Associations between patients’ characteristics and abdominal fat level were then limited only to 23 patients
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Table 1. Demographic, clinical, anthropometrical, and laboratory characteristics of the 74 patients with nonalcoholic fatty liver disease at their inclusion in this study BΜΙ (kg/m2)
Abdominal fat level
Waist circumferencea (cm)
Total (N = 74)
≤ 12.5 (n = 19)
> 12.5 (n = 55)
P
< 30 (n = 38)
≥ 30 (n = 36)
P
48 (65) 46 ± 12 30 ± 4 36 (49) 106 ± 12 51 (69)
6 (32) 47 ± 13 27 ± 3 4 (21) 96 ± 6 13 (68)
42 (76) 46 ± 12 31 ± 4 32 (58) 110 ± 11 38 (69)
0.001 0.760 < 0.001 0.007 < 0.001 1.000
28 (74) 42 ± 12 27 ± 2 0 98 ± 6 18 (47)
20 (56) 51 ± 11 34 ± 3 36 (100) 114 ± 11 33 (92)
0.144 0.001 < 0.001 < 0.001 < 0.001 < 0.001
23 (100) 38 ± 11 27 ± 2 3 (13) 97 ± 5 0
25 (49) 50 ± 11 31 ± 4 33 (65) 110 ± 11 51 (100)
16 ± 5 55 (74)
10 ± 2 0
18 ± 4 55 (100)
< 0.001 < 0.001
14 ± 4 23 (61)
19 ± 5 32 (89)
< 0.001 0.007
15 ± 3 13 (68)
17 ± 6 38 (69)
0.076 1.000
40 ± 8 0.97 ± 0.06
38 ± 8 0.9 ± 0.05
41 ± 8 1.0 ± 0.06
0.582 0.004
36 ± 6 0.9 ± 0.06
44 ± 7 1.0 ± 0.06
< 0.001 < 0.001
33 ± 4 0.9 ± 0.04
43 ± 7 1.0 ± 0.06
< 0.001 < 0.001
25 14 16 4 22
0.373
Sex, males (%) Age at diagnosis (years) BMI (kg/m2) BMI ≥ 30 kg/m2 [n (%)] Waist circumference (cm) Waist circumference > 88/102 [n (%)]a Abdominal fat level (0–59) Increased abdominal fat (levels > 12.5) [n (%)] Trunk fat (%) Waist to hip ratio Smoking habits [n (%)] Never smokers Previous smokers Current smokers Diabetes [n (%)] Family history of diabetes [n (%)] Arterial hypertension [n (%)] Coronary artery disease [n (%)] Dyslipidemia [n (%)] ALT (IU/l) (ULN = 40) Normal ALT [n (%)] AST (IU/l) (ULN = 40) GGT (IU/l) (ULN = 50) Total cholesterol (mg/dl) HDL-cholesterol (mg/dl) Low HDL [n (%)]b LDL-cholesterol (mg/dl) Triglycerides (mg/dl) Triglycerides ≥ 150 mg/dl [n (%)] Serum glucose (fasting state) (mg/dl) Serum glucose ≥ 110 mg/dl [n (%)] Uric acid (mg/dl) Metabolic syndrome (≥3 criteria) [n (%)]
37 18 19 4 27
(50) (24) (26) (5) (39)
12 4 3 0 5
(63) (21) (16) (0) (28)
(46) (26) (29) (7) (42)
0.567 0.401
21 8 9 2 11
(55) (21) (24) (5) (31)
16 10 10 2 16
≤ 88/102 (n = 23)
(44) (28) (28) (6) (46)
0.639 > 0.90 0.326 0.036 0.233
14 3 6 1 9/21
(70) (13) (26) (4) (43)
> 88/102 (n = 51)
16 10 10 3 18/49
P < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
(45) (29) (26) (6) (37)
1.000 0.789
3 (13) 0
17 (33) 2 (4)
0.092 1.000 0.490 0.246 0.730 0.425 0.056 0.300 0.256 0.424 0.276 0.116 0.799
20 (27) 2 (3)
6 (32) 0
14 (26) 2 (4)
0.765 1.000
6 (16) 0
14 (39) 2 (6)
64 (87) 75 ± 39 11 (15) 42 ± 20 98 ± 118 210 ± 43 26 ± 10 67 (91) 157 ± 40 134 ± 51 28 (38)
16 (84) 74 ± 44 3 (16) 44 ± 19 140 ± 171 221 ± 46 30 ± 11 17 (90) 166 ± 46 122 ± 52 6 (32)
48 (87) 75 ± 38 8 (15) 42 ± 21 82 ± 90 206 ± 41 25 ± 9 50 (91) 153 ± 39 138 ± 50 22 (40)
0.710 0.697 1.000 0.439 0.156 0.237 0.062 1.000 0.272 0.254 0.591
30 (79) 83 ± 46 4 (11) 47 ± 24 112 ± 139 206 ± 40 29 ± 11 35 (92) 153 ± 38 122 ± 55 14 (37)
34 (94) 66 ± 28 7 (19) 38 ± 16 82 ± 92 213 ± 45 24 ± 8 32 (89) 161 ± 44 146 ± 43 14 (39)
0.087 0.246 0.337 0.152 0.371 0.503 0.031 0.707 0.452 0.019 > 0.900
19 (83) 83 ± 44 4 (17) 47 ± 26 60 ± 48 201 ± 43 28 ± 9 22 (96) 150 ± 38 119 ± 51 8 (35)
45 (88) 71 ± 37 7 (14) 40 ± 18 116 ± 137 213 ± 43 26 ± 10 45 (88) 160 ± 42 140 ± 50 20 (39)
92 ± 12
93 ± 14
91 ± 12
0.713
86 ± 12
97 ± 10
< 0.001
84 ± 13
95 ± 10
8 (11)
2 (11)
6 (11)
1.000
2 (5)
6 (17)
0.147
2 (9)
6.1 ± 1.5 33 (45)
5.4 ± 1.0 9 (47)
6.3 ± 1.6 24 (44)
0.063 0.795
6.1 ± 1.3 11 (29)
6.0 ± 1.6 22 (61)
0.852 0.010
6.3 ± 1.4 3 (13)
0.281
< 0.001
6 (12)
1.000
5.9 ± 1.5 30 (59)
0.206 < 0.001
ALT, alanine aminotransferase; AST, aspartate aminotransferase; GGT, γ glutamyl transferase; HDL-cholesterol, high-density lipoprotein-cholesterol; LDL-cholesterol, low-density lipoprotein-cholesterol; ULN, upper limit of normal. Waist circumference ≤ 88 and > 88 cm for female and ≤ 102 and > 102 cm for male patients. b HDL < 40 mg/dl for men or < 50 mg/dl for women. a
Table 2. Inflammatory markers, cytokines, and insulin resistance in patients with nonalcoholic fatty liver disease BMI (kg/m2)
Abdominal fat
hsCRP (mg/l) Insulin (μIU/ml) HOMA index Ferritin (ng/ml) IL-6 (pg/ml) IL-8 (pg/ml) Adiponectin (μg/ml) TNF-α (pg/ml) TGF-β (µg/ml) VEGF (pg/ml)
Waist circumferencea (cm)
Total (N = 68)
≤ 12.5 (N = 18)
> 12.5 (N = 50)
P
< 30 (N = 36)
≥ 30 (N = 32)
P
≤ 88/102 (N = 21)
> 88/102 (N = 47)
P
2.0 ± 2.0 15.4 ± 9.2 3.6 ± 2.5 190 ± 235 2.0 ± 1.3 34.6 ± 52.5 7.0 ± 4.6
1.6 ± 1.8 11.2 ± 5.2 2.6 ± 1.4 183 ± 243 1.5 ± 0.7 31 ± 64 8.2 ± 6.6
2.1 ± 2.1 16.8 ± 10.0 3.9 ± 2.7 192 ± 235 2.3 ± 1.5 36 ± 47 6.5 ± 3.4
0.081 0.015 0.045 0.254 0.042 0.194 0.817
1.2 ± 1.0 12.5 ± 6.5 2.7 ± 1.7 166 ± 181 1.6 ± 0.7 37 ± 56 6.3 ± 4.8
2.8 ± 2.5 18.5 ± 10.7 4.5 ± 2.9 214 ± 283 2.5 ± 1.8 32 ± 49 7.8 ± 4.3
0.002 0.002 0.001 0.615 0.081 0.441 0.096
1.2 ± 0.7 13.1 ± 7.5 2.8 ± 2.0 178 ± 103 1.6 ± 0.7 52 ± 70 4.6 ± 2.9
2.3 ± 2.3 16.4 ± 10.0 3.9 ± 2.6 195 ± 276 2.2 ± 1.5 27 ± 41 8.0 ± 4.8
0.163 0.115 0.029 0.096 0.323 0.062 0.002
4.3 ± 3.1 40.1 ± 8.3 310 ± 164
3.6 ± 2.90 42.0 ± 9.5 303 ± 109
4.6 ± 3.1 39.4 ± 7.8 312 ± 179
0.178 0.296 0.650
4.2 ± 3.0 42.0 ± 9.0 340 ± 188
4.4 ± 3.2 37.9 ± 6.9 279 ± 130
0.812 0.068 0.224
4.2 ± 2.4 43.4 ± 8.7 341 ± 227
4.4 ± 3.3 38.7 ± 7.9 279 ± 128
0.891 0.062 0.763
HOMA, Homeostasis Model Assessment; hsCRP, high sensitivity C-reactive protein; IL, interleukin; TGF-β, transforming growth factor-β; TNF-α, tumor necrosis factor-α; VEGF, vascular endothelial growth factor. a Waist circumference ≤ 88 and > 88 cm for female and ≤ 102 and > 102 cm for male patients.
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Abdominal fat and NASH Margariti et al.
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Table 3. Histological characteristics of 36 patients with nonalcoholic fatty liver disease in relation to visceral fat levels, body mass index, and waist circumference BMI (kg/m2)
Abdominal fat Total (N = 36) Histological diagnosis [n (%)] Fatty liver NASH NAS ≥ 5 [n (%)]a Grade of necroinflammatory activity ≥ 2 [n (%)]b Presence of necroinflammation [n (%)] Fibrosis [n (%)]b Absent or mild (0–1) Moderate/severe (2–4) Steatosis [n (%)]a Mild Moderate Severe Liver stiffness (kPa) (N = 53)
13 23 10 12
(36) (64) (28) (33)
≤ 12.5 (N = 13) 8 5 3 5
(62) (38) (23) (39)
> 12.5 (N = 23) 5 18 7 7
P 0.030
< 30 (N = 21)
≥ 30 (N = 15) 2 13 5 4
(22) (78) (30) (30)
0.716 0.720
11 10 5 8
(52) (48) (24) (38)
Waist circumference P 0.033
≤ 88/102 (N = 9)
(13) (87) (33) (27)
0.709 0.721
4 5 2 4
(44) (56) (22) (44)
> 88/102 (N = 27) 9 18 8 8
P
(33) (67) (30) (30)
0.693 > 0.90 0.443
25 (69)
6 (46)
19 (83)
0.056
12 (57)
13 (87)
0.077
5 (63)
19 (70)
0.685
19 (53) 17 (47)
8 (62) 5 (39)
11 (48) 12 (52)
0.502
13 (62) 8 (38)
6 (40) 9 (60)
0.311
5 (63) 3 (38)
14 (52) 13 (48)
0.700
13 (36) 5 (14) 18 (50) 7.9 ± 6.1
7 (54) 2 (15) 4 (31) 7.1 ± 7.0
6 (26) 3 (13) 14 (71) 8.2 ± 5.6
0.191
9 (43) 4 (19) 8 (38) 8.3 ± 7.6
4 (27) 1 (7) 10 (67) 7.3 ± 3.3
0.220
4 (44) 0 (0) 5 (56) 9.2 ± 8.3
9 (33) 5 (19) 13 (48) 6.7 ± 2.9
0.373
0.025
0.428
0.587
NAS, nonalcoholic fatty liver disease activity score; NASH, nonalcoholic steatohepatitis. NAFLD activity score [21]. According to Brunt et al. [20].
a
b
with normal WC. WC correlated positively and significantly with levels of abdominal fat (r = 0.591, P = 0.03). The frequency of diabetes mellitus, arterial hypertension and metabolic syndrome was similar in patients with average and increased levels of abdominal fat. In contrast, dyslipidemia was a universal finding in the five patients with average levels of abdominal fat (100%), whereas it was observed in 53% of patients with increased levels of abdominal fat (P = 0.056). With respect to histological lesions, NASH was present in 80% of patients with normal WC and increased abdominal fat level, whereas no patient with average levels of abdominal fat had NASH, although this difference did not reach statistical significance (P = 0.143). Discussion
In this study, we evaluated associations between the metabolic and histological characteristics of NAFLD patients and indices of obesity and abdominal adiposity. Although the impact of obesity or increased WC as a marker of central obesity has already been studied in patients with NAFLD, a rather new method – that is, abdominal BIA was applied for the first time. The majority of our NAFLD patients (53%) were not obese according to BMI, whereas approximately one-third of them had normal WC and one-quarter had average levels of ‘visceral’ abdominal fat. Our data suggest that abdominal obesity as assessed by BIA and total body obesity as assessed by BMI, but not central obesity as assessed by WC, are associated with the presence of NASH. In particular, patients with levels of abdominal fat more than 12.5 by BIA or with BMI 30 kg/m2 or more had 5.8-fold and 7.1-fold higher probabilities of having NASH, respectively. These reasonable associations of abdominal and total body obesity with NASH have been reported in previous studies as well [6,7,22]. The absence of an association between increased WC and the presence of NASH has also been reported by others [7,23,24]. LSMs by transient elastography were higher in patients with increased
than average abdominal adiposity. The LSMs obtained by transient elastography have repeatedly been shown to be affected by obesity [25–27] and the presence of the metabolic syndrome [25,26], at least partly because of the presence of subcutaneous fat that interferes with the ultrasound beam. Moreover, the performance of transient elastography in assessing fibrosis among NAFLD patients has yielded conflicting results [28,29]. Patients with increased abdominal adiposity do not necessarily have increased subcutaneous fat, which is more likely among patients with increased WC or BMI, probably allowing for better comparisons between the groups of average and increased abdominal fat, respectively. The absence of an association between total body obesity and the severity of histological lesions has also been reported previously in White patients with NAFLD [30]. Previous studies associating abdominal and more specifically visceral fat levels with liver histology have yielded conflicting results. Eguchi et al. [6] reported a lack of association between visceral fat levels and NAS or the grade of necroinflammation, as evaluated according to Brunt et al. [20], and lack of an independent association of visceral fat levels with advancing fibrosis, despite increased levels of visceral fat among patients with advanced fibrosis. In contrast, van der Poorten et al. [7] have shown that visceral fat levels were associated independently with the grade of necroinflammation and the stage of fibrosis. The prediction of the visceral fat through the ViScan analysis has been found to be limited, especially in abdominally obese individuals, and is therefore not as accurate as MRI [17], which was used in the latter study, in assessing visceral fat levels, thus accounting for the observed differences. Abdominal and more specifically visceral adiposity is considered to be closely related to the metabolic derangements driven by insulin resistance [4,31]. In our cohort, the levels of abdominal fat correlated positively with the number of metabolic syndrome criteria fulfilled by the patients, but the correlation was not strong (r = 0.290).
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Compared with BMI, WC has been shown to correlate better with metabolic disorders stemming from insulin resistance [32–34] and is considered to provide a better estimate of visceral adiposity [35]. In our cohort, however, WC was not associated with the prevalence of any of the other parameters of the metabolic syndrome. A possible explanation for this lack of association, which is in contrast with previous reports [23,30], might be the statistical handling of this parameter. In particular, WC seems to be a better predictor of metabolic abnormalities when used as a continuous [30] or as a trichotomous qualitative variable [23,36,37] instead of a simple dichotomous variable in our analysis. The site of WC could also, at least partly, account for the discrepancies described above, although we attempted to avoid this inconsistency by using a standardized protocol for its measurement [10]. As abdominal obesity as assessed by BIA, central obesity as assessed by WC, and total body obesity do not necessarily coexist, we evaluated the role of increased abdominal obesity, as estimated by BIA, in patients without the other types of obesity. The presence of increased abdominal adiposity seemed to have an effect on the severity of liver histological lesions in overweight patients without central obesity. In particular, the majority (80%) of patients with normal WC and increased abdominal adiposity had NASH on liver biopsy. Thus, abdominal BIA may be useful in identifying patients with a high likelihood of NASH among NAFLD patients with normal WC. Therefore, abdominal BIA seems to be superior compared with WC measurements in the evaluation of NAFLD patients and the diagnosis of existing NASH, offering good prediction even in patients with normal WC. A limitation of this study is its cross-sectional design, which does not enable assessment of causality between increased abdominal fat and the presence of NASH, as well as the relatively small number of patients and particularly the small number of patients with available liver biopsy data. In addition, abdominal BIA is not the optimal method for the assessment of visceral fat and seems to be inferior to MRI in measuring the exact amount of visceral fat [17]. It is, however, much more easy to use than MRI, avoids the discrepancies of WC measurements at different anatomical points [10], and has been shown to have a very good correlation with visceral fat levels, at least in individuals with normal BMI [12,17]. Abdominal BIA does not measure abdominal fat in specific units and has no established cut-off points for ‘normal or average’ levels of abdominal fat as the results vary widely among studies [38–44]. We used the cut-off points provided by the manufacturer, as they are in agreement with visceral fat cut-off points derived from a Turkish population [42], which is likely to be similar to the Greek population. In conclusion, average levels of abdominal fat, as assessed by abdominal BIA, seem to be present in almost one-quarter of patients with NAFLD, most commonly in women, and to be associated with a lower degree of insulin resistance and a lower probability of NASH. Obesity (BMI ≥30 kg/m2) is associated with a worse metabolic profile and the presence of NASH, whereas increased WC does not appear to be associated with the liver histological lesions. These findings should be evaluated further as the confirmation of the associations of the abdominal – and especially visceral – fat levels can have important
implications in the appropriate management of patients with NAFLD.
Acknowledgements Conflicts of interest
There are no conflicts of interest.
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Introduction
Abdominal fat is one of the key components of insulin resistance [1] and has been shown to be related to the presence of insulin resistance associated with metabolic disorders, including nonalcoholic fatty liver disease (NAFLD) [2–4]. Moreover, visceral fat plays a key role in the pathogenesis of NAFLD [5], whereas increased amounts of visceral fat have been associated with the development of nonalcoholic steatohepatitis (NASH) [6,7]. However, although the amount of visceral fat might be useful in diagnosing patients at an increased risk for European Journal of Gastroenterology & Hepatology 2015, 00:000–000 Keywords: abdominal fat, bioelectrical impedance analysis, nonalcoholic fatty liver disease, nonalcoholic steatohepatitis a
2nd Department of Internal Medicine, Hippokration Hospital of Athens, Academic Department of Gastroenterology, Laiko Hospital of Athens, Athens University Medical School, cDepartment of Nutrition and Dietetics, Harokopio University and dLaboratory of Histology and Embryology, Medical School, National and Kapodistrian University of Athens, Athens, Greece b
Correspondence to George V. Papatheodoridis, MD, Academic Department of Gastreonterology, Laiko General Hospital of Athens, 17 Agiou Thoma Street, 115 27 Athens, Greece Tel: + 30 210 745 6513; fax: + 30 210 746 2601; e-mail: [email protected] Received 8 December 2014 Accepted 1 April 2015
development of NASH, it cannot be estimated easily and accurately. The two most reliable methods, computed tomography and MRI, are expensive and sometimes not widely available in daily clinical practice, whereas computed tomography also involves patient exposure to ionizing radiation [8]. Anthropometric indices such as waist circumference (WC) and waist to hip ratio may be used as surrogate markers of abdominal adiposity, but their accuracy remains questionable [8–10]. Bioelectrical impedance analysis (BIA) is a noninvasive body composition method that has been used extensively in assessing the total body water, the fat-free mass, and the fat mass of various groups of individuals. It is a safe method, rapid, portable, and easy to perform, and requires minimal operator training [11]. Recently, a new technique, combining the use of infrared and abdominal BIA, has been developed to measure WC and to estimate trunk fat percentage and total abdominal fat [12–15]. The aim of this study was to explore, for the first time, associations between abdominal obesity, as assessed by abdominal BIA, and metabolic or histological characteristics of patients with NAFLD and compare them with more classical indices of obesity, namely, increased BMI and increased WC.
0954-691X Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
DOI: 10.1097/MEG.0000000000000381
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Month 2015 • Volume 00 • Number 00
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Patients and methods
Seventy-four patients with NAFLD evaluated between March 2009 and July 2011 were included in this prospective cohort study. NAFLD patients of this study had abnormal alanine aminotransferase and/or γ glutamyl transferase activity, ultrasonographic evidence of hepatic steatosis and/or compatible liver histology, and no other cause of liver injury. More specifically, all patients were negative for hepatitis B surface antigen (HBsAg), antibodies against hepatitis C virus (anti-HCV), and antibodies against HIV. In addition, none of the patients reported alcohol use of more than 210 or 140 g/week for men and women, respectively. The history of alcohol use was provided by the patients and was confirmed by the patients’ relatives or friends. None of the patients reported use of any hepatotoxic drug or agent or had any systemic disease with potential liver involvement. The demographic characteristics and medical history details were recorded for all patients. The history of known arterial hypertension was recorded, whereas arterial blood pressure was also measured during the initial visit with the patient in a relaxed state. The presence of diabetes mellitus was recorded, with diabetes being diagnosed in cases with a known history on antidiabetic treatment and/or fasting glucose more than 126 mg/dl on more than one occasion. The study was approved by the hospital’s ethics committee. Informed consent was obtained from all the study participants. Anthropometric and body composition assessment
The body weight of the participants was measured using a digital scale (Seca Robusta 813; Seca, Hamburg, Germany) to the nearest 100 g and height to the nearest 0.5 cm. BMI was calculated as weight (kg) divided by height squared (m2). WC was tape measured to the nearest 0.1 cm midway between the lowest rib and the superior border of the iliac crest at the end of normal expiration using a nonelastic measuring tape positioned at a level parallel to the floor and with the participant in a standing position. Increased WC was defined as more than 102 cm for men and more than 88 cm for women. Abdominal fat compartments were estimated by the abdominal BIA method using the device ViScan AB-140 (Tanita Corporation, Tokyo, Japan). BIA is a noninvasive, simple, and inexpensive method used to estimate body composition based on a two-compartment model. It measures the impedance or resistance to a small electrical current as it circulates through the body’s water pool. An estimate of total body water is obtained from which total body fat-free mass is calculated on the basis of the assumption that 73% of the body’s fat-free mass is water [16]. Unlike whole-body BIA, the ViScan AB-140 is directly measuring abdominal transimpedance and is therefore considered to better reflect the local conducting tissue compartments, whereas the algorithm used by the device does not rely on factors such as age, weight, or height to estimate body fat. For the conduction of the measurement, the patients lay supine on an examination bed. The device uses a tetrapolar impedance method, involving two pairs of injecting and sensing electrodes. These electrodes are located on a wireless measurement
belt, which was placed directly on wet skin at the umbilicus in the sagittal plane, as described in the device manual. The measurements were performed in the morning, after overnight fasting, and at least 2 h after consumption of water or any other liquid. The patient was in a relaxed state for at least 1 h before the measurement. ViScan abdominal body composition values were derived from extrapolation of impedance measures (at 6.25 and 50 kHz) using in-built software and subdivided into total abdominal adiposity (i.e. intra-abdominal adipose tissue and subcutaneous abdominal adipose tissue) expressed as trunk fat% (range 0–75%) and intra-abdominal adipose tissue (corresponding to visceral fat), expressed as abdominal fat level (range 1–59 AU) [17]. Level 13 has been found to correspond to 130 cm2 of visceral fat, as estimated by computed tomography of the abdomen, but the overall prediction of the visceral fat has been reported to be limited, especially in individuals with abdominal obesity [17]. The device also rates the results of its measurements using arbitrary band ratings and thus levels of abdominal fat are rated as average (≤ 12.5), high (12.6–17.5), and very high (>17.5). Laboratory markers
The laboratory data recorded included complete blood count, prothrombin time, uric acid, urea, creatinine, liver enzymes (alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, γ glutamyl transferase), total protein, albumin, serum copper, ceruloplasmin, iron and ferritin, as well as detection of HBsAg, anti-HBc, antiHBs, anti-HCV, anti-HIV, and liver autoantibodies (antinuclear, antismooth muscles, antimicrosomial, antimitochondrial). Serum fasting glucose, total cholesterol, and high-density lipoprotein-cholesterol were measured using the enzymatic colorimetric method (Analyzer Cobas 8000; Roche Diagnostics International Ltd, Rotkreuz, Switzerland) and low-density lipoprotein-cholesterol was calculated using the Friedewald formula [18]. Serum triglycerides were measured using the chromatometric enzymatic method (Analyzer Cobas 8000; Roche Diagnostics International Ltd), insulin and ferritin with chemiluminescence (Centaur Analyzer; Siemens), and high sensitivity C-reactive protein was measured using a nephelometric assay (BN II Nephelometer; Siemens AG, Erlangen, Germany). Tumor necrosis factor-α (TNF-α), interleukin (IL)-6, IL-8, vascular endothelial growth factor (VEGF), transforming growth factor-β1 (TGF-β1), and adiponectin were measured using a sensitive enzyme-linked immunosorbent assay (ELISA, Quantikine/Immunoassay Kit; R&D Systems, Minneapolis, Minnesota, USA). The intraassay coefficient of variation was less than 7% for TNF-α, IL-8, and VEGF and less than 5% for IL-6, TGF-β1, and adiponectin. The interassay coefficient of variation was less than 8% for TNF-α, IL-6, and adiponectin and less than 10% for IL-8, TGF-β1, and VEGF. Definitions
BMI was calculated as weight (kg) divided by height squared (m2). Patients were considered obese if they had BMI 30 kg/m2 or more. Metabolic syndrome was defined according to the National Cholesterol Education Program: Adult Treatment Panel III criteria [19]. In this study, the
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Abdominal fat and NASH Margariti et al.
fulfillment of the criterion of elevated arterial pressure was based on the patients’ history and repeated measurements and not on the single arterial pressure measurement on the day of evaluation. Patients were considered to have dyslipidemia if they fulfilled at least one of the following criteria: (i) total cholesterol more than 200 mg/dl, (ii) lowdensity lipoprotein-cholesterol more than 120 mg/dl, (iii) triglycerides more than 150 mg/dl at the time of diagnosis or during follow-up, or (iv) were being treated with lipidlowering medication. Transient elastography
Reliable liver stiffness measurements (LSMs) (in kPa) by transient elastography (FibroScan; Echosens, Paris, France) were available in 53 of the 74 patients. The examination was considered to be reliable if 10 successful measurements were obtained, with a success rate more than 60% and a ratio of interquartile range to mean stiffness less than 30%. For patients who underwent both transient elastography and liver biopsy, LSM was performed a few hours before liver biopsy in most or within 4 weeks before or after liver biopsy in some patients. In any case, LSM was performed within the first 4 weeks from the diagnosis of NAFLD. Liver histology
Adequate liver biopsies were available in 36 of the 74 patients. They were evaluated by a single hepatopathologist (D.T.), who was blinded to the clinical data. A liver biopsy was considered to be adequate if at least six portal tracts were identified and the specimen length was 1.5 cm or more. The diagnosis of NASH was made on the basis of the overall pattern of injury and the criteria of Brunt et al. [20] modified by Kleiner et al. [21]. Global grading of necroinflammatory activity and staging of fibrosis were assessed according to Brunt et al. [20]. The severity of steatosis and the NAFLD activity score (NAS) were evaluated according to Kleiner et al. [21]. Statistical analysis
All analyses were carried out using the SPSS statistics (SPSS Inc., an IBM Company, Chicago, Illinois, USA). Quantitative data were expressed as mean ± SD or as median (range) values. The normality of distribution of continuous quantitative variables was tested using the Shapiro–Wilk or the Kolmogorov–Smirnov test, as appropriate. Comparisons between groups of quantitative variables with a normal or a non-normal distribution were performed using the t-test or the Mann–Whitney test, respectively. Comparisons of categorical variables were performed using the corrected χ2 or the Fischer’s exact test, as appropriate. Correlations between quantitative variables were assessed using Pearson’s or Spearman’s correlation coefficients. A two-tailed P value less than 0.05 was considered to be statistically significant. Results
The main demographic, medical history, anthropometric, and laboratory characteristics of the 74 patients according
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to categories of abdominal fat level BMI and WC are presented in Table 1. For the statistical analyses, patients with high and very high levels of abdominal fat were included in the same category of increased abdominal fat. The prevalence of the metabolic syndrome was similar between patients with increased and average levels of abdominal fat, whereas increased WC and obesity were associated with a significantly higher prevalence of metabolic syndrome (nonobese: 29% vs. obese patients: 61%, P = 0.010; patients with normal WC: 13% vs. increased WC: 59%, P < 0.001) (Table 1). WC as a continuous variable correlated positively with systolic blood pressure (r = 0.302, P = 0.019), serum fasting glucose (r = 0.350, P = 0.003), and serum triglycerides (r = 0.272, P = 0.025), as well as with levels of abdominal fat, as estimated by BIA (r = 0.644, P < 0.001) The number of criteria of the metabolic syndrome correlated significantly with the levels of abdominal fat (r = 0.290, P = 0.030). The levels of inflammatory markers and cytokines are shown in Table 2. Insulin levels were higher and insulin resistance was more prominent among patients with increased than patients with average levels of abdominal fat (insulin: P = 0.015; Homeostasis Model Assessment (HOMA): P = 0.045), as well as among obese than nonobese patients (insulin: P = 0.002; HOMA: P = 0.001). Moreover, patients with increased compared with those with normal WC had a higher degree of insulin resistance (HOMA: P = 0.029), but not significantly different insulin levels (P = 0.115). The histological characteristics of this cohort are shown in Table 3. The majority (64%) of patients with available liver biopsy had NASH. The presence of NASH was associated with increased levels of abdominal fat (OR 5.76, 95% CI 1.29–25.64, P = 0.030) and the presence of obesity (OR 7.15, 95% CI 1.28–39.83, P = 0.033), but not with increased WC. There was no association between grade of necroinflammation, stage of fibrosis, or severity of steatosis and levels of abdominal fat as a continuous variable, BMI, or WC. However, when patients were grouped into those with average and those with increased abdominal fat, more than half (54%) of the cases with average levels of abdominal fat had no fibrosis on liver biopsy compared with only 13% of cases with increased abdominal adiposity (P = 0.018). The mean LSMs by transient elastography differed only among patients with average or increased levels of abdominal fat, being lower in the former group (P = 0.025) (Table 3). As obesity can be a strong confounding factor, the associations between patients’ characteristics and abdominal fat level were explored only in the 38 nonobese patients (BMI < 30 kg/m2) as well. In this subgroup, the 23 patients with increased compared with the 15 patients with average abdominal fat level were more frequently men [22/23 (95.7%) vs. 9/15 (60.0%), P < 0.001] and had lower levels of high-density lipoprotein-cholesterol (26.3 ± 9.4 vs. 32.4 ± 11.8 mg/dl, P = 0.002), whereas they did not differ in the frequency of diabetes mellitus [2/23 (8.7%) vs. 0/15 (0%), P = 0.509], arterial hypertension [3/23 (13%) vs. 3/15 (20%), P = 0.663], metabolic syndrome [5/23 (22%) vs. 6/15 (40%), P = 0.285], and NASH [6/10 (60.0%) vs. 4/11 (36.4%), P = 0.395]. Associations between patients’ characteristics and abdominal fat level were then limited only to 23 patients
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Table 1. Demographic, clinical, anthropometrical, and laboratory characteristics of the 74 patients with nonalcoholic fatty liver disease at their inclusion in this study BΜΙ (kg/m2)
Abdominal fat level
Waist circumferencea (cm)
Total (N = 74)
≤ 12.5 (n = 19)
> 12.5 (n = 55)
P
< 30 (n = 38)
≥ 30 (n = 36)
P
48 (65) 46 ± 12 30 ± 4 36 (49) 106 ± 12 51 (69)
6 (32) 47 ± 13 27 ± 3 4 (21) 96 ± 6 13 (68)
42 (76) 46 ± 12 31 ± 4 32 (58) 110 ± 11 38 (69)
0.001 0.760 < 0.001 0.007 < 0.001 1.000
28 (74) 42 ± 12 27 ± 2 0 98 ± 6 18 (47)
20 (56) 51 ± 11 34 ± 3 36 (100) 114 ± 11 33 (92)
0.144 0.001 < 0.001 < 0.001 < 0.001 < 0.001
23 (100) 38 ± 11 27 ± 2 3 (13) 97 ± 5 0
25 (49) 50 ± 11 31 ± 4 33 (65) 110 ± 11 51 (100)
16 ± 5 55 (74)
10 ± 2 0
18 ± 4 55 (100)
< 0.001 < 0.001
14 ± 4 23 (61)
19 ± 5 32 (89)
< 0.001 0.007
15 ± 3 13 (68)
17 ± 6 38 (69)
0.076 1.000
40 ± 8 0.97 ± 0.06
38 ± 8 0.9 ± 0.05
41 ± 8 1.0 ± 0.06
0.582 0.004
36 ± 6 0.9 ± 0.06
44 ± 7 1.0 ± 0.06
< 0.001 < 0.001
33 ± 4 0.9 ± 0.04
43 ± 7 1.0 ± 0.06
< 0.001 < 0.001
25 14 16 4 22
0.373
Sex, males (%) Age at diagnosis (years) BMI (kg/m2) BMI ≥ 30 kg/m2 [n (%)] Waist circumference (cm) Waist circumference > 88/102 [n (%)]a Abdominal fat level (0–59) Increased abdominal fat (levels > 12.5) [n (%)] Trunk fat (%) Waist to hip ratio Smoking habits [n (%)] Never smokers Previous smokers Current smokers Diabetes [n (%)] Family history of diabetes [n (%)] Arterial hypertension [n (%)] Coronary artery disease [n (%)] Dyslipidemia [n (%)] ALT (IU/l) (ULN = 40) Normal ALT [n (%)] AST (IU/l) (ULN = 40) GGT (IU/l) (ULN = 50) Total cholesterol (mg/dl) HDL-cholesterol (mg/dl) Low HDL [n (%)]b LDL-cholesterol (mg/dl) Triglycerides (mg/dl) Triglycerides ≥ 150 mg/dl [n (%)] Serum glucose (fasting state) (mg/dl) Serum glucose ≥ 110 mg/dl [n (%)] Uric acid (mg/dl) Metabolic syndrome (≥3 criteria) [n (%)]
37 18 19 4 27
(50) (24) (26) (5) (39)
12 4 3 0 5
(63) (21) (16) (0) (28)
(46) (26) (29) (7) (42)
0.567 0.401
21 8 9 2 11
(55) (21) (24) (5) (31)
16 10 10 2 16
≤ 88/102 (n = 23)
(44) (28) (28) (6) (46)
0.639 > 0.90 0.326 0.036 0.233
14 3 6 1 9/21
(70) (13) (26) (4) (43)
> 88/102 (n = 51)
16 10 10 3 18/49
P < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
(45) (29) (26) (6) (37)
1.000 0.789
3 (13) 0
17 (33) 2 (4)
0.092 1.000 0.490 0.246 0.730 0.425 0.056 0.300 0.256 0.424 0.276 0.116 0.799
20 (27) 2 (3)
6 (32) 0
14 (26) 2 (4)
0.765 1.000
6 (16) 0
14 (39) 2 (6)
64 (87) 75 ± 39 11 (15) 42 ± 20 98 ± 118 210 ± 43 26 ± 10 67 (91) 157 ± 40 134 ± 51 28 (38)
16 (84) 74 ± 44 3 (16) 44 ± 19 140 ± 171 221 ± 46 30 ± 11 17 (90) 166 ± 46 122 ± 52 6 (32)
48 (87) 75 ± 38 8 (15) 42 ± 21 82 ± 90 206 ± 41 25 ± 9 50 (91) 153 ± 39 138 ± 50 22 (40)
0.710 0.697 1.000 0.439 0.156 0.237 0.062 1.000 0.272 0.254 0.591
30 (79) 83 ± 46 4 (11) 47 ± 24 112 ± 139 206 ± 40 29 ± 11 35 (92) 153 ± 38 122 ± 55 14 (37)
34 (94) 66 ± 28 7 (19) 38 ± 16 82 ± 92 213 ± 45 24 ± 8 32 (89) 161 ± 44 146 ± 43 14 (39)
0.087 0.246 0.337 0.152 0.371 0.503 0.031 0.707 0.452 0.019 > 0.900
19 (83) 83 ± 44 4 (17) 47 ± 26 60 ± 48 201 ± 43 28 ± 9 22 (96) 150 ± 38 119 ± 51 8 (35)
45 (88) 71 ± 37 7 (14) 40 ± 18 116 ± 137 213 ± 43 26 ± 10 45 (88) 160 ± 42 140 ± 50 20 (39)
92 ± 12
93 ± 14
91 ± 12
0.713
86 ± 12
97 ± 10
< 0.001
84 ± 13
95 ± 10
8 (11)
2 (11)
6 (11)
1.000
2 (5)
6 (17)
0.147
2 (9)
6.1 ± 1.5 33 (45)
5.4 ± 1.0 9 (47)
6.3 ± 1.6 24 (44)
0.063 0.795
6.1 ± 1.3 11 (29)
6.0 ± 1.6 22 (61)
0.852 0.010
6.3 ± 1.4 3 (13)
0.281
< 0.001
6 (12)
1.000
5.9 ± 1.5 30 (59)
0.206 < 0.001
ALT, alanine aminotransferase; AST, aspartate aminotransferase; GGT, γ glutamyl transferase; HDL-cholesterol, high-density lipoprotein-cholesterol; LDL-cholesterol, low-density lipoprotein-cholesterol; ULN, upper limit of normal. Waist circumference ≤ 88 and > 88 cm for female and ≤ 102 and > 102 cm for male patients. b HDL < 40 mg/dl for men or < 50 mg/dl for women. a
Table 2. Inflammatory markers, cytokines, and insulin resistance in patients with nonalcoholic fatty liver disease BMI (kg/m2)
Abdominal fat
hsCRP (mg/l) Insulin (μIU/ml) HOMA index Ferritin (ng/ml) IL-6 (pg/ml) IL-8 (pg/ml) Adiponectin (μg/ml) TNF-α (pg/ml) TGF-β (µg/ml) VEGF (pg/ml)
Waist circumferencea (cm)
Total (N = 68)
≤ 12.5 (N = 18)
> 12.5 (N = 50)
P
< 30 (N = 36)
≥ 30 (N = 32)
P
≤ 88/102 (N = 21)
> 88/102 (N = 47)
P
2.0 ± 2.0 15.4 ± 9.2 3.6 ± 2.5 190 ± 235 2.0 ± 1.3 34.6 ± 52.5 7.0 ± 4.6
1.6 ± 1.8 11.2 ± 5.2 2.6 ± 1.4 183 ± 243 1.5 ± 0.7 31 ± 64 8.2 ± 6.6
2.1 ± 2.1 16.8 ± 10.0 3.9 ± 2.7 192 ± 235 2.3 ± 1.5 36 ± 47 6.5 ± 3.4
0.081 0.015 0.045 0.254 0.042 0.194 0.817
1.2 ± 1.0 12.5 ± 6.5 2.7 ± 1.7 166 ± 181 1.6 ± 0.7 37 ± 56 6.3 ± 4.8
2.8 ± 2.5 18.5 ± 10.7 4.5 ± 2.9 214 ± 283 2.5 ± 1.8 32 ± 49 7.8 ± 4.3
0.002 0.002 0.001 0.615 0.081 0.441 0.096
1.2 ± 0.7 13.1 ± 7.5 2.8 ± 2.0 178 ± 103 1.6 ± 0.7 52 ± 70 4.6 ± 2.9
2.3 ± 2.3 16.4 ± 10.0 3.9 ± 2.6 195 ± 276 2.2 ± 1.5 27 ± 41 8.0 ± 4.8
0.163 0.115 0.029 0.096 0.323 0.062 0.002
4.3 ± 3.1 40.1 ± 8.3 310 ± 164
3.6 ± 2.90 42.0 ± 9.5 303 ± 109
4.6 ± 3.1 39.4 ± 7.8 312 ± 179
0.178 0.296 0.650
4.2 ± 3.0 42.0 ± 9.0 340 ± 188
4.4 ± 3.2 37.9 ± 6.9 279 ± 130
0.812 0.068 0.224
4.2 ± 2.4 43.4 ± 8.7 341 ± 227
4.4 ± 3.3 38.7 ± 7.9 279 ± 128
0.891 0.062 0.763
HOMA, Homeostasis Model Assessment; hsCRP, high sensitivity C-reactive protein; IL, interleukin; TGF-β, transforming growth factor-β; TNF-α, tumor necrosis factor-α; VEGF, vascular endothelial growth factor. a Waist circumference ≤ 88 and > 88 cm for female and ≤ 102 and > 102 cm for male patients.
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Abdominal fat and NASH Margariti et al.
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5
Table 3. Histological characteristics of 36 patients with nonalcoholic fatty liver disease in relation to visceral fat levels, body mass index, and waist circumference BMI (kg/m2)
Abdominal fat Total (N = 36) Histological diagnosis [n (%)] Fatty liver NASH NAS ≥ 5 [n (%)]a Grade of necroinflammatory activity ≥ 2 [n (%)]b Presence of necroinflammation [n (%)] Fibrosis [n (%)]b Absent or mild (0–1) Moderate/severe (2–4) Steatosis [n (%)]a Mild Moderate Severe Liver stiffness (kPa) (N = 53)
13 23 10 12
(36) (64) (28) (33)
≤ 12.5 (N = 13) 8 5 3 5
(62) (38) (23) (39)
> 12.5 (N = 23) 5 18 7 7
P 0.030
< 30 (N = 21)
≥ 30 (N = 15) 2 13 5 4
(22) (78) (30) (30)
0.716 0.720
11 10 5 8
(52) (48) (24) (38)
Waist circumference P 0.033
≤ 88/102 (N = 9)
(13) (87) (33) (27)
0.709 0.721
4 5 2 4
(44) (56) (22) (44)
> 88/102 (N = 27) 9 18 8 8
P
(33) (67) (30) (30)
0.693 > 0.90 0.443
25 (69)
6 (46)
19 (83)
0.056
12 (57)
13 (87)
0.077
5 (63)
19 (70)
0.685
19 (53) 17 (47)
8 (62) 5 (39)
11 (48) 12 (52)
0.502
13 (62) 8 (38)
6 (40) 9 (60)
0.311
5 (63) 3 (38)
14 (52) 13 (48)
0.700
13 (36) 5 (14) 18 (50) 7.9 ± 6.1
7 (54) 2 (15) 4 (31) 7.1 ± 7.0
6 (26) 3 (13) 14 (71) 8.2 ± 5.6
0.191
9 (43) 4 (19) 8 (38) 8.3 ± 7.6
4 (27) 1 (7) 10 (67) 7.3 ± 3.3
0.220
4 (44) 0 (0) 5 (56) 9.2 ± 8.3
9 (33) 5 (19) 13 (48) 6.7 ± 2.9
0.373
0.025
0.428
0.587
NAS, nonalcoholic fatty liver disease activity score; NASH, nonalcoholic steatohepatitis. NAFLD activity score [21]. According to Brunt et al. [20].
a
b
with normal WC. WC correlated positively and significantly with levels of abdominal fat (r = 0.591, P = 0.03). The frequency of diabetes mellitus, arterial hypertension and metabolic syndrome was similar in patients with average and increased levels of abdominal fat. In contrast, dyslipidemia was a universal finding in the five patients with average levels of abdominal fat (100%), whereas it was observed in 53% of patients with increased levels of abdominal fat (P = 0.056). With respect to histological lesions, NASH was present in 80% of patients with normal WC and increased abdominal fat level, whereas no patient with average levels of abdominal fat had NASH, although this difference did not reach statistical significance (P = 0.143). Discussion
In this study, we evaluated associations between the metabolic and histological characteristics of NAFLD patients and indices of obesity and abdominal adiposity. Although the impact of obesity or increased WC as a marker of central obesity has already been studied in patients with NAFLD, a rather new method – that is, abdominal BIA was applied for the first time. The majority of our NAFLD patients (53%) were not obese according to BMI, whereas approximately one-third of them had normal WC and one-quarter had average levels of ‘visceral’ abdominal fat. Our data suggest that abdominal obesity as assessed by BIA and total body obesity as assessed by BMI, but not central obesity as assessed by WC, are associated with the presence of NASH. In particular, patients with levels of abdominal fat more than 12.5 by BIA or with BMI 30 kg/m2 or more had 5.8-fold and 7.1-fold higher probabilities of having NASH, respectively. These reasonable associations of abdominal and total body obesity with NASH have been reported in previous studies as well [6,7,22]. The absence of an association between increased WC and the presence of NASH has also been reported by others [7,23,24]. LSMs by transient elastography were higher in patients with increased
than average abdominal adiposity. The LSMs obtained by transient elastography have repeatedly been shown to be affected by obesity [25–27] and the presence of the metabolic syndrome [25,26], at least partly because of the presence of subcutaneous fat that interferes with the ultrasound beam. Moreover, the performance of transient elastography in assessing fibrosis among NAFLD patients has yielded conflicting results [28,29]. Patients with increased abdominal adiposity do not necessarily have increased subcutaneous fat, which is more likely among patients with increased WC or BMI, probably allowing for better comparisons between the groups of average and increased abdominal fat, respectively. The absence of an association between total body obesity and the severity of histological lesions has also been reported previously in White patients with NAFLD [30]. Previous studies associating abdominal and more specifically visceral fat levels with liver histology have yielded conflicting results. Eguchi et al. [6] reported a lack of association between visceral fat levels and NAS or the grade of necroinflammation, as evaluated according to Brunt et al. [20], and lack of an independent association of visceral fat levels with advancing fibrosis, despite increased levels of visceral fat among patients with advanced fibrosis. In contrast, van der Poorten et al. [7] have shown that visceral fat levels were associated independently with the grade of necroinflammation and the stage of fibrosis. The prediction of the visceral fat through the ViScan analysis has been found to be limited, especially in abdominally obese individuals, and is therefore not as accurate as MRI [17], which was used in the latter study, in assessing visceral fat levels, thus accounting for the observed differences. Abdominal and more specifically visceral adiposity is considered to be closely related to the metabolic derangements driven by insulin resistance [4,31]. In our cohort, the levels of abdominal fat correlated positively with the number of metabolic syndrome criteria fulfilled by the patients, but the correlation was not strong (r = 0.290).
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6
Month 2015 • Volume 00 • Number 00
European Journal of Gastroenterology & Hepatology
Compared with BMI, WC has been shown to correlate better with metabolic disorders stemming from insulin resistance [32–34] and is considered to provide a better estimate of visceral adiposity [35]. In our cohort, however, WC was not associated with the prevalence of any of the other parameters of the metabolic syndrome. A possible explanation for this lack of association, which is in contrast with previous reports [23,30], might be the statistical handling of this parameter. In particular, WC seems to be a better predictor of metabolic abnormalities when used as a continuous [30] or as a trichotomous qualitative variable [23,36,37] instead of a simple dichotomous variable in our analysis. The site of WC could also, at least partly, account for the discrepancies described above, although we attempted to avoid this inconsistency by using a standardized protocol for its measurement [10]. As abdominal obesity as assessed by BIA, central obesity as assessed by WC, and total body obesity do not necessarily coexist, we evaluated the role of increased abdominal obesity, as estimated by BIA, in patients without the other types of obesity. The presence of increased abdominal adiposity seemed to have an effect on the severity of liver histological lesions in overweight patients without central obesity. In particular, the majority (80%) of patients with normal WC and increased abdominal adiposity had NASH on liver biopsy. Thus, abdominal BIA may be useful in identifying patients with a high likelihood of NASH among NAFLD patients with normal WC. Therefore, abdominal BIA seems to be superior compared with WC measurements in the evaluation of NAFLD patients and the diagnosis of existing NASH, offering good prediction even in patients with normal WC. A limitation of this study is its cross-sectional design, which does not enable assessment of causality between increased abdominal fat and the presence of NASH, as well as the relatively small number of patients and particularly the small number of patients with available liver biopsy data. In addition, abdominal BIA is not the optimal method for the assessment of visceral fat and seems to be inferior to MRI in measuring the exact amount of visceral fat [17]. It is, however, much more easy to use than MRI, avoids the discrepancies of WC measurements at different anatomical points [10], and has been shown to have a very good correlation with visceral fat levels, at least in individuals with normal BMI [12,17]. Abdominal BIA does not measure abdominal fat in specific units and has no established cut-off points for ‘normal or average’ levels of abdominal fat as the results vary widely among studies [38–44]. We used the cut-off points provided by the manufacturer, as they are in agreement with visceral fat cut-off points derived from a Turkish population [42], which is likely to be similar to the Greek population. In conclusion, average levels of abdominal fat, as assessed by abdominal BIA, seem to be present in almost one-quarter of patients with NAFLD, most commonly in women, and to be associated with a lower degree of insulin resistance and a lower probability of NASH. Obesity (BMI ≥30 kg/m2) is associated with a worse metabolic profile and the presence of NASH, whereas increased WC does not appear to be associated with the liver histological lesions. These findings should be evaluated further as the confirmation of the associations of the abdominal – and especially visceral – fat levels can have important
implications in the appropriate management of patients with NAFLD.
Acknowledgements Conflicts of interest
There are no conflicts of interest.
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