Next Article in Journal
Impact of IL-12B Genetic Variants on Antiviral Treatment Response among Hepatitis B Patients in Pakistan
Previous Article in Journal
Perspective on Quantitative Structure–Toxicity Relationship (QSTR) Models to Predict Hepatic Biotransformation of Xenobiotics
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Livers
Volume 3
Issue 3
10.3390/livers3030033
livers-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Relationship between Non-Alcoholic Fatty Liver Disease and Visceral Fat Measured by Imaging-Based Body Composition Analysis: A Systematic Review

by
Ker Ming Seaw
1,
Christiani Jeyakumar Henry
1,2 and
Xinyan Bi
1,*
1
Clinical Nutrition Research Centre (CNRC), Singapore Institute of Food and Biotechnology Innovation (SIFBI), Agency for Science, Technology and Research (A*STAR), Yong Loo Lin School of Medicine, 14 Medical Drive #07-02, MD 6 Building, Singapore 117599, Singapore
2
Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117599, Singapore
*
Author to whom correspondence should be addressed.
Livers 2023, 3(3), 463-493; https://doi.org/10.3390/livers3030033
Submission received: 14 July 2023 / Revised: 1 August 2023 / Accepted: 22 August 2023 / Published: 5 September 2023
Browse Figures
Review Reports Versions Notes

Abstract

:
Imaging-based body composition analysis can quantify visceral fat, which is an important feature of lean non-alcoholic fatty liver disease (NAFLD) patients. This review assesses current evidence of the relationship between NAFLD, particularly hepatic steatosis, and visceral fat that is measured using imaging-based body composition analysis. PubMed Central and ScienceDirect were searched for studies that provided quantification of the relationship between NAFLD, hepatic steatosis and visceral fat. Twenty studies comprising 15,763 subjects were included, consisting of the relationship with NAFLD (n = 15) and the relationship with hepatic steatosis (n = 7). All studies reported a positive relationship between NAFLD and visceral fat. For hepatic steatosis regardless of severity, only one study reported no correlation with visceral fat. Further results showed that visceral fat is more related to NAFLD and hepatic steatosis in females than males. More studies including NAFLD of different stages must be performed in the future to validate the degree of association between visceral fat and NAFLD at all stages as well as this relationship difference between genders.

1. Introduction

Non-alcoholic fatty liver disease (NAFLD) refers to a range of liver diseases that can be confirmed to not be caused by the overconsumption of alcohol [1]. When fat infiltrates the liver and accounts for more than 5% of the liver’s weight, it can be termed a fatty liver, also known as hepatic steatosis [2]. NAFLD is an umbrella term that comprises a few different stages of liver conditions, beginning from hepatic steatosis to more severe or significant steatosis, followed by non-alcoholic steatohepatitis (NASH), then fibrosis and eventually cirrhosis. In hepatic steatosis, the accumulation of fat cells may result in the inflammation of the liver, known as NASH. As it worsens, fibrosis eventually occurs as the inflammation results in the scarring of the liver [3].
There is a changing trend of NAFLD as their prevalence and incidence are increasing over the years especially among different Asian countries, with the highest being reported as 43.3% in Shanghai, China as of 2016 [4]. Despite this, in a global study with data collected from 102 countries, no country has a clear strategy for NAFLD, and only 32 countries have national NAFLD clinical guidelines [5]. This poses a concern as there are different implications resulting from NAFLD. If left untreated, it can eventually lead to cirrhosis, which, although a later stage of NAFLD, can cause a nodular transformation of the liver, and the reversibility of the disease is less likely [3]. It has been shown by many studies that NAFLD is associated with other illnesses including hepatocellular carcinoma, cholangiocarcinoma, gallstone disease, and coronary heart disease. NAFLD has been reported to have a greater risk of both all-cause and cardiovascular-related mortality [6].
NAFLD could be largely due to unhealthy diets such as overeating or overconsumption of fats and sugar, and hence it should be properly managed with the right nutrition therapy [7]. Therefore, it is important to detect NAFLD at the early stage so that appropriate treatments and management, e.g., nutrition therapy, can be delivered to improve patient outcomes [8]. Inevitably, the challenging part is that not all NAFLD patients are overweight or obese as approximately 10–20% of affected NAFLD patients are “lean NAFLD” [9], with some reported “lean NAFLD” comprising 7–20% of NAFLD patients among different studies [4]. This calls for a comprehensive body composition assessment instead of relying on the traditional body weight to correlate with NAFLD in monitoring any anthropometric factors that can affect NAFLD progression.
With numerous factors that can lead to NAFLD, high visceral fat, also known as visceral adipose tissue (VAT), is one of the prominent observations present in a subset of NAFLD patients [10]. It is also well established that beyond a certain threshold, excess VAT may result in a malfunction of adipose tissue and cardiometabolic disturbances [11]. As such, VAT is a measurement of concern that can be studied for its relationship with NAFLD. Several ways can be used to measure VAT such as bioelectrical impedance analysis (BIA) and the various radiological modalities. Although easily accessible, multiple studies have found that BIA was inferior to radiological techniques for measuring VAT in terms of accuracy [12,13,14,15]. Moreover, multidisciplinary collaboration engaging different expertise for healthcare delivery is essential to provide comprehensive care and management to NAFLD patients [16].
Radiological methods can accurately measure VAT regardless of the form of visceral fat area (VFA) or visceral fat thickness (VFT). Furthermore, scanning provides images of the liver for assessment of the severity. Although different imaging modalities present different advantages and disadvantages, ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), and dual-energy x-ray absorptiometry (DEXA) can measure VAT as required [17]. Many studies with a wide range of clinical interests have adopted the use of different imaging-based body composition analysis for VAT measurement, thereby proving its values and usefulness in clinical research [18,19,20,21]. Considering the increasing prevalence of NAFLD, it is desirable to seek alternatives in the field of imaging-based body composition analysis since it can also help in assessing the degree of steatosis [22,23,24].
Despite the radiology technological advancements in assessing steatosis, liver biopsy remains the gold standard for diagnosing NAFLD [3]. Thus, this systematic review aims to assess the existing evidence of the relationship between NAFLD and VAT that is measured by using imaging-based body composition analysis. Moreover, the degree of the association will be evaluated for its difference between genders.

2. Materials and Methods

This review and the study protocol were conducted in adherence to the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) guidelines [25].

2.1. Data Sources

A systematic literature search was conducted to source articles from the databases: PubMed Central and ScienceDirect. Specific keywords included “Non-Alcoholic Fatty Liver Disease”, “NAFLD” or “Fatty Liver” combined with any of the terms: “Visceral Fat”, “Visceral Adipose Tissue”, “Body Composition”, “Computed Tomography”, “CT”, “Magnetic Resonance Imaging”, “MRI”, “Ultrasound”, “Dual-Energy X-Ray Absorptiometry”, “DEXA” or “DXA”. Boolean operators, specifically “AND” and “OR”, were also taken into consideration when searching for articles.

2.2. Study Selection

The inclusion criteria are: (1) The articles are published within 15 years from January 2008 to December 2022. (2) Quantification of the relationship between visceral fat with NAFLD was identified. (3) Visceral fat is measured directly by radiological technique. (4) The condition is not caused by excessive consumption of alcohol if specific liver conditions are reported instead of NAFLD. (5) Provides r, odds ratio (OR), risk, hazards ratio (HR) or coefficients together with 95% confidence interval (CI) for quantification of the relationship.
The exclusion criteria are: (1) Articles were published more than 15 years ago, i.e., before January 2008. (2) No correlation, association nor quantification of association between visceral fat with NAFLD was identified. (3) Visceral fat measured from non-radiological techniques, e.g., BIA. (4) No mention of alcoholism being excluded if specific liver condition is reported instead of NAFLD. (5) Outcomes not appropriate. (6) Conference abstracts or reviews.

2.3. Quality Assessment and Data Extraction

Studies that meet the inclusion criteria were then subjected to quality assessment using the mixed-methods appraisal tool (MMAT) checklist [26]. The MMAT allows for the screening of various study designs including qualitative, quantitative, and mixed-method studies [27]. This comprises 5 different categories of the design study, namely (1) qualitative, (2) non-randomized, (3) randomized controlled trial, (4) quantitative descriptive, and (5) mixed-methods study. Following 2 screening questions, within each category, the quality of the study was based on 5 core criteria, whereby, within each criterion, there are three levels of score, namely “Yes”, “No” and “Can’t tell”. The MMAT score was not used to eliminate studies, but rather to signify the studies’ methodological solidity, with the following approach: 4–5 criteria met = high quality, 2–3 criteria met = moderate quality, and 0–1 criteria met = low quality.
Thereafter, descriptive characteristics of the studies are extracted as follows: first author with the year of publication, journal title, the aim of the study, study design, the MMAT score, population size and their breakdown by gender, age, and location of the study conducted. Details about their radiological procedure were also extracted independently, namely modality used in assessing VAT and liver (if applicable), equipment model and/or brand as well as the landmark used in measuring VAT. Finally, their statistical analysis method, association and correlation results, as well as conclusion were then extracted. Numerous forest plots were plotted for studies with odds ratio (OR) only just for a clearer comparison and visualization of the results. Only 1 study [28] with OR was not included in any of the forest plots due to the different parameter of liver–spleen attenuation index (LAI) being used to diagnose NAFLD.

3. Results

3.1. Search Results

The detailed procedure of article retrieval is depicted as a flow diagram in Figure 1. The search from PubMed Central and ScienceDirect initially yielded 97,511 results altogether. After excluding duplicates and identifying records to be screened, 16,000 journals were screened by their title and abstracts for keywords before 50 full-text articles were assessed for 20 studies [28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47] eventually being accounted in this review.
The descriptive characteristics of the studies together with their MMAT score are shown in Table 1. Out of the 20 studies, only 16 reported their study design. There were reported seven cross-sectional studies, three prospective studies, two retrospective studies, one cohort study, one large cohort longitudinal prospective study, one population-based cohort, retrospective study, and one cross-sectional, retrospective cohort study. Except for two studies which were conducted on participants aged between 12 and 18 [36] and 15 to 19 [33], respectively, the rest of the studies were conducted on adults. Altogether, two studies were conducted in the USA, two studies in Brazil, one in France, three in Japan, three in China, and nine in Republic of Korea.
Studies where the design of the study was not reported were not subjected to MMAT score quality assessment to avoid an inaccurate MMAT score overall. Collectively, these 20 studies included 15,763 subjects comprising 7808 males and 7955 females. One study recruited only males [36] and had the lowest number of participants (n = 57), while the study with the highest number of participants had a total of 3846 [47]. Furthermore, the risk of bias for several components in the study design was assessed individually for all included studies using the Risk of Bias in Non-randomized Studies of Exposure (ROBINS-E) tool (Figure 2) [48].
The imaging modalities and tests used in assessing VAT and liver profile, respectively, are collated in Table 2. CT (n = 13) was the most common method for measuring VAT, followed by ultrasound (n = 4) and MRI (n = 3). In assessing the liver, two studies used ultrasound-guided percutaneous liver biopsy, four studies used MRI of which three performed MRS, one study used NAFLD-LFS score, which was developed from MRS, four studies used CT, and nine studies used ultrasound of which one performed a fibro scan. No study meeting inclusion criteria that assess the relationship between NAFLD and VAT measured by using DEXA was identified.
Main relationship findings for all studies are summarized in Table 3. It should be noted that while some studies related VAT to NAFLD in general, hepatic steatosis, severe or significant steatosis were assessed individually in a few studies as they are part of NAFLD. It should also be noted that in summarizing these findings, association with any later stages of NAFLD including NASH and fibrosis was not reported or determined in all of the studies. Only one study [44] also included for only with fibrosis but the association between visceral fat and fibrosis was also excluded from Table 3 due to the limitation in the number of studies assessing for it. As seen from Table 3, 13 studies assessed the relationship between visceral fat with NAFLD of which 1 study used LAI, which is an indicator of NAFLD, 3 studies between visceral fat with hepatic steatosis, 1 study between visceral fat with significant hepatic steatosis, 1 study between visceral fat with both mild and severe hepatic steatosis separately, 1 study between visceral fat with both NAFLD and hepatic steatosis separately, and 1 study between visceral fat with both NAFLD and severe hepatic steatosis separately.

3.2. The Relationship between VAT with NAFLD

Altogether, there were 15 studies directly assessing the relationship between visceral fat with NAFLD of which 1 study was assessed with LAI, where an LAI of lower than 0.9 is diagnosed as NAFLD. Of these 15 studies, 1 study has a β-coefficient, 2 studies have HR, 4 studies have both OR and a correlation coefficient, and 8 studies have only OR as their outcome.
One study [33] presented with a β-coefficient = 1.606 (p = 0.014) for developing NAFLD with increased VAT. Studies [34,38] using HR for assessing with NAFLD compared the subjects from the group of highest VAT to the lowest VAT. One study [34] presented with HR 2.23 (95% CI 1.28–3.89, p = 0.002) for developing NAFLD after adjusting for confounding factors while another study [38] established HR 2.45 (95% CI 1.56–3.85, p < 0.001). The study in [38] also reported that the greatest increase in VAT was inversely associated with NAFLD regressing with HR 0.40 (95% CI 0.20–0.80, p = 0.008), indicating that greater VAT hindered the regression of NAFLD. When correlation coefficient was used, except for one study [42] which reported a range of r = 0.154–0.390 (p < 0.05); together with other features, the reported correlation differs between studies from r = 0.537; p = 0.00 [29], r = 0.62; p ≤ 0.05 [36] and r = 0.391; p < 0.001 [43].
For studies using OR, VAT was indicated to be independently associated with NAFLD (Figure 3), presenting statistically significant results after analysis and adjusted for variables. Despite the different study designs and subjects’ profiles, this association was consistently low with four out of five studies having a result of OR < 2.0 while the highest reported result was OR 2.53 (95% 2.04–3.12, p < 0.001). In another study [28] included in this review separately from Figure 3, where it was not included in the forest plot as it uses LAI, it was found that even without obesity but with increased VAT presented with OR 5.88 (95% CI 1.03–33.52, p = 0.046) for developing NAFLD. Surprisingly, patients with high BMI but low VFA did not display a greater risk of lower LAI.
Some studies further broke down the association by genders. As shown in Figure 4, three out of four studies showed higher ORs for females than males, signifying that females with high VAT were at greater risk of developing NAFLD than males.
Two studies [40,47] were included separately in this review as another forest plot (Figure 5) because their OR was derived differently by analyzing between those subjects in the highest VAT category and those subjects in the lowest VAT category, differentiated for between both genders. Results from both studies concurred that females are at greater risk of being affected by NAFLD than males despite having a significantly lower VAT. While Kure et al. (2019) [40] showed OR 21.6 (95% CI 11.3–41.2, p < 0.01) of developing NAFLD for females in comparison to males with OR 8.20 (95% CI 5.38–12.9, p < 0.01), Baek et al. (2020) [47] showed OR 17.84 (95% CI 7.12–44.71, p < 0.001) for females and OR 6.14 (95% 2.96–12.73, p < 0.001) for males of developing NAFLD.

3.3. The Relationship between VAT with Hepatic Steatosis

Conjointly, there were seven studies assessing with hepatic steatosis of all stages. One study assessed the correlation between VAT with both mild and severe hepatic steatosis using HU, whereby the lower the HU value, the denser the visceral fat tissue and the more severe the steatosis is. The reported correlation coefficient was r = −0.481 (p < 0.001) [41], indicating that increasing VAT has a positive correlation with steatosis of increased severity
Three studies [32,37,44] assessed the correlation between VAT and specifically hepatic steatosis with one study [37] differentiated between genders. The overall correlation coefficient reported was r = 0.307 (p = 0.014) [32] and r = 0.569 (p < 0.001) [37]. Only one study established that they are not correlated, presenting a statistically insignificant and lower value result of r = 0.13 (p = 0.090) [44].
When divided by gender, it was found in [37] that the correlation for developing hepatic steatosis from increased VAT was greater in males (r = 0.576, p < 0.001) than females (r = 0.473, p = 0.003). Contrarily, in another study [46] that assessed the correlation of VAT with the degree of hepatic steatosis differentiated between genders on top of NAFLD, it was determined that the correlation between the degree of hepatic steatosis with VAT was greater in females with r = 0.387 (p < 0.001) than males with a correlation of r = 0.307 (p < 0.001).
Two studies assessing the association between VAT with specifically severe or significant hepatic steatosis present with the results of OR 1.010 (95% CI 1.001–1.019, p = 0.028) [35] and OR 5.08 (95% CI 2.00–12.88, p = 0.0006 [39], respectively. When further divided by gender, one study [35] established that in males, VAT was the sole independent risk factor for significant hepatic steatosis with OR 1.008 (95% CI 1.001–1.011, p = 0.045), whereas in females, it was more closely associated and was just one of the independent risk factors with OR 1.029 (95% CI, 1.010–1.048, p = 0.002).

4. Discussion

From the results, it can be ascertained that NAFLD and degree of hepatic steatosis were related to increased visceral adiposity. Besides the study by Kang et al. [44] which showed statistically insignificant correlations for only hepatic steatosis, all other studies demonstrated a statistically significant positive association and correlation between VAT and NAFLD, which can be attributed to a few reasons.
The liver regulates energy by receiving blood from the gut through the portal vein after food intake and will be stored within until being utilized. Visceral fat is metabolically more active as it will produce signals to regulate energy, so it is susceptible to overwork. This will then lead to inadequate blood and subsequent inadequate oxygen supply, which will then cause the fat cells to be swollen, resulting in damaged fat tissues that will then supply harmful substances into the blood to harm the liver [3]. This means that visceral fat can let out free fatty acids (FFA) and triglycerides to circulate, which can cause fatty acids to accumulate straight into the liver through portal circulation [49].
The physiology involves an increase in the inflammation markers and immune cell activity within liver tissue which will then decrease the adiponectin, an insulin sensitivity hormone. Eventually, hepatic insulin clearance will be decreased, increasing hepatic fat deposition. Increased FFAs in the liver will also bring about the production of cytokine, which can contribute to the inflammation pathways associated with NAFLD [49]. This is also as shown in a study performed by Denkmayr et al. (2018) [50] that lean NAFLD patients who were characterized as having higher VAT degrees, also had higher adipokine, which is a cytokine, than lean healthy patients. Moreover, with adiponectin being an adipocyte-derived hormone with properties insulin-sensitizing and anti-inflammation, decreased levels of adiponectin may lower the ability to protect from NAFLD [51]. Besides, in another study [52], it was identified that VFA was dose dependently and independently associated with alanine aminotransferase (ALT), which is an enzyme that can be a liver damage marker.
As liver disease progresses, there would be an accumulation of hepatic fat deposits, which could explain the positive relationship between visceral fat with severe or significant steatosis. As above mentioned, only one study [44] out of all included studies also reported for the presence of fibrosis and no other included studies reported any presence of later stages of NAFLD. As such, the stages of NAFLD the patients included in the studies were unknown. In this study [44], high visceral fat index was found to be one of the independent risk factors for advanced fibrosis. In another instance, also in the abovementioned study by Denkmayr et al. [50], it unexpectedly showed that even lean NAFLD patients with normal BMI but a higher VAT degree, have a higher rate of fibrosis than overweight and obese NAFLD patients. In other separate studies not included in this review, VAT is also found to be positively associated with fibrosis in NAFLD [53,54]. These results could signify presence of an underlying mechanism between visceral fat with the later stages of NAFLD and may not be limited to only fibrosis. As such, this unascertained relationship between visceral fat with later stages of NAFLD could be confounding factors in affecting the association results and ought to be accounted for.
Vitamin D deficiency could be another possible cause for the relationship between VAT and NAFLD [55]. A few studies have shown that there was a positive association between concentrations of vitamin D and adiponectin [56,57]. Not only that, in a 12-month longitudinal follow-up study [57] within these studies, it was displayed that an increased vitamin D level results in a decreased secretion of several inflammatory cytokines. While one study [58] concluded that low vitamin D was closely associated with NAFLD regardless of the visceral obesity status, other studies [59,60] have established that there is a significant relationship between vitamin D status and visceral fat quantity with lower vitamin D status having a higher amount of visceral fat. Separately, Choi et al. [59] have also demonstrated that vitamin D deficiency has a higher NAFLD prevalence. Taken together, these matched findings suggest that low levels of vitamin D can contribute to higher visceral fat and result in NAFLD, considering how a significant reduction in adiponectin and increase in cytokines was positively associated with NAFLD as mentioned [51].
Results divided by gender across all studies were summarized in Table 4. When differentiated by the genders, there were conflicting results. Current evidence suggests that males are more prone to develop higher VAT than females due to their underlying mechanism of higher and larger chylomicrons [61]. Taking this into account, males should have a greater risk of developing NAFLD given their higher visceral fat. Unexpectedly, more results from this review show that without considering other factors, VAT individually as an independent variable is more related to NAFLD for females than males.
As seen in Table 4, five out of six studies indicated females with high VAT have higher ORs in developing NAFLD than males with high VAT. For the relationship with hepatic steatosis, one study deemed the correlation was higher for males while another two studies ascertained it will affect females more. While the reason cannot be validated for the only two studies indicating NAFLD and steatosis are more likely to affect males than females, this illustrated the complex nature of the relationship difference for both genders. Notwithstanding the fact that visceral fat was analyzed independently to give the results in Table 4, a separate meta-analysis [62] performed has determined that while increased serum total testosterone in males decreased the risk of NAFLD, it increases NAFLD risk in females. The difference in the effect of these sex hormones have on the results, thereupon reinforced the difference in the relationship with NAFLD between genders.
Even though visceral fat was analyzed independently to derive results shown in Table 4, it should be known that there is a higher risk of developing NAFLD in postmenopausal women due to their decreased level of estrogen, which affected the visceral distribution and liver lipid metabolism, leading to dyslipidemia milieu [63]. A population-based cross-sectional has demonstrated that NAFLD was more possible to affect women than men, especially in those aged 56–60, i.e., the post-menopausal period [64]. One of the studies included in this review [47] also distinctively showed there were more NAFLD female subjects (n = 326) from age 50 onwards than the younger ones (below age 50, n = 52), as opposed to male subjects where the distribution of NAFLD patients was more evenly distributed across all ages. This indicates that age which impacts the menopausal status, can concurrently affect the NAFLD epidemiology and pathophysiology [65].
It is noteworthy to point out that 5 of the 20 studies also involve the use of visceral-to-subcutaneous ratio (VSR) as a parameter to relate with NAFLD and steatosis. One study [34] presented with a result of HR 1.51, 95% CI 1.03–2.19, p = 0.033 to develop NAFLD. In another study [41], it showed that there was a higher VSR in moderate/severe than mild steatosis but is not statistically significant (p = 0.258). Lean NAFLD has the highest VSR in one study [43] but is also statistically insignificant (p = 0.127). However, in this study, VSR showed a significant association with fatty liver disease (r = 0.342, p < 0.001). There also exist a positive correlation in another study [33] with a result of r = 0.790. When divided by gender, one study [47] showed r = 0.031, p < 0.001 for men; r = 0.162, p < 0.001 for women, as well as OR 1.99 95% CI 1.22–3.26; p = 0.003 for men, OR 6.73 95% 4.10–11.03; p < 0.001 for women. These results are comparable to those from visceral fat and, therefore, suggest that they may not be of less importance than using only visceral fat as a parameter.
To the best of our knowledge, this is the first systematic review assessing the relationship between NAFLD and visceral fat measured using imaging-based body composition analysis. We acknowledge that this review has its own set of challenges and limitations. Meta-analysis was not performed as the included studies and results were too heterogeneous. There are differences in the study design and the included subjects’ profiles differ between all with some of the studies recruiting subjects with existing conditions including diabetes and Crohn’s disease. It should also be noted that the association result shown for the measurement unit of the VAT increase was not constant. While one study showed the result for a per-cm increase in VAT [29], some showed a cm2 increase [40,47], some showed a 1-SD increase in volume (L) [43], and some calculated into and used the VFA index as per 1.0 cm2/m2 increase [45]. However, VAT was analyzed independently of its association with NAFLD in these studies, and the consistency of the results proved the reproducibility of the positive association between VAT and NAFLD regardless of the measurement unit.
Particularly, there was a challenge in sourcing for studies performed in multiple countries from different continents to make this review more generalizable. Of the 20 studies, only 5 studies were from non-Asian populations. This calls for the need to have more studies being performed to account to a wider demographic population. Nevertheless, all the remaining 15 studies were from east Asian countries. Thus, so far as possible, this review provides a comprehensive coverage to be representative of the east Asian population.
In this review, there were different imaging modalities and landmarks used in measuring VAT. Nonetheless, the lack of sufficient studies makes this standardization challenging and the consistent association and correlation results rationalized the importance and validity of the different imaging-based body composition analysis in measuring body fat. This is crucial as there are no single imaging modalities that will fit all patients due to their different risks and subjects’ suitability.

5. Conclusions

Without considering other factors, more results from this review showed that high VAT as an independent factor leads to NAFLD and steatosis affecting females more than males. The large variance, as seen in the data collected in this review, clearly shows the need for more clinical studies to be performed in the future. Nevertheless, a key takeaway from the result is that VAT measured from imaging-based body composition analysis is closely related to NAFLD and hepatic steatosis. This can reinforce the existing evidence that regression or prevention of NAFLD can happen by aiming to reduce the VAT as part of nutrition therapy or management. However, the degree of the association and correlation as well as these results between genders vary between different studies. More studies with both genders, possibly including various age groups and NAFLD stages, still need to be performed to establish the degree of association between visceral fat and all stages of NAFLD and the difference in this association between genders, as well as to further elucidate how this changes with age.

Author Contributions

Conceptualization and writing—original draft preparation, K.M.S.; validation and writing—review and editing, X.B.; supervision, C.J.H. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created in this study.

Acknowledgments

We greatly acknowledge the financial support from Singapore Institute of Food and Biotechnology Innovation, Agency for Science, Technology, and Research (A*Star), Singapore.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Lonardo, A.; Leoni, S.; Alswat, K.A.; Fouad, Y. History of Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2020, 21, 5888. [Google Scholar] [CrossRef] [PubMed]
  2. Juanola, O.; Martínez-López, S.; Francés, R.; Gómez-Hurtado, I. Non-Alcoholic Fatty Liver Disease: Metabolic, Genetic, Epigenetic and Environmental Risk Factors. Int. J. Environ. Res. Public Health 2021, 18, 5227. [Google Scholar] [CrossRef] [PubMed]
  3. Francque, S.M.; Marchesini, G.; Kautz, A.; Walmsley, M.; Dorner, R.; Lazarus, J.V.; Zelber-Sagi, S.; Hallsworth, K.; Busetto, L.; Frühbeck, G.; et al. Non-alcoholic fatty liver disease: A patient guideline. JHEP Rep. Innov. Hepatol. 2021, 3, 100322. [Google Scholar] [CrossRef] [PubMed]
  4. Mitra, S.; De, A.; Chowdhury, A. Epidemiology of non-alcoholic and alcoholic fatty liver diseases. Transl. Gastroenterol. Hepatol. 2020, 5, 16. [Google Scholar] [CrossRef] [PubMed]
  5. Lazarus, J.V.; Mark, H.E.; Villota-Rivas, M.; Palayew, A.; Carrieri, P.; Colombo, M.; Ekstedt, M.; Esmat, G.; George, J.; Marchesini, G.; et al. The Global NAFLD Policy Review and preparedness index: Are countries ready to address this silent public health challenge? J. Hepatol. 2022, 76, 771–780. [Google Scholar] [CrossRef]
  6. Xiao, J.; Ng, C.H.; Chan, K.E.; Fu, C.; Tay, P.; Yong, J.N.; Lim, W.H.; Tan, D.J.; Syn, N.; Wong, Z.Y.; et al. Hepatic, extra-hepatic outcomes and causes of mortality in NAFLD—An umbrella overview of systematic review of meta-analysis. J. Clin. Exp. Hepatol. 2022, 13, 656–665. [Google Scholar] [CrossRef]
  7. Vancells Lujan, P.; Viñas Esmel, E.; Sacanella Meseguer, E. Overview of Non-Alcoholic Fatty Liver Disease (NAFLD) and the Role of Sugary Food Consumption and Other Dietary Components in its Development. Nutrients 2021, 13, 1442. [Google Scholar] [CrossRef]
  8. Rinella, M.E. Nonalcoholic Fatty Liver Disease: A Systematic Review. JAMA 2015, 313, 2263–2273. [Google Scholar] [CrossRef]
  9. Xu, R.; Pan, J.; Zhou, W.; Ji, G.; Dang, Y. Recent advances in lean NAFLD. Biomed. Pharmacother. 2022, 153, 113331. [Google Scholar] [CrossRef]
  10. Albhaisi, S.; Chowdhury, A.; Sanyal, A.J. Non-alcoholic fatty liver disease in lean individuals. JHEP Rep. Innov. Hepatol. 2019, 1, 329–341. [Google Scholar] [CrossRef]
  11. Machado, M.V. Nonalcoholic fatty liver disease in lean subjects: Is it all metabolic-associated fatty liver disease? Hepatoma Res. 2020, 6, 84. [Google Scholar] [CrossRef]
  12. Pietiläinen, K.; Kaye, S.; Karmi, A.; Suojanen, L.; Rissanen, A.; Virtanen, K. Agreement of bioelectrical impedance with dual-energy X-ray absorptiometry and MRI to estimate changes in body fat, skeletal muscle and visceral fat during a 12-month weight loss intervention. Br. J. Nutr. 2013, 109, 1910–1916. [Google Scholar] [CrossRef] [PubMed]
  13. Xu, Z.; Liu, Y.; Yan, C.; Yang, R.; Xu, L.; Guo, Z.; Yu, A.; Cheng, X.; Ma, L.; Hu, C.; et al. Measurement of visceral fat and abdominal obesity by single-frequency bioelectrical impedance and CT: A cross-sectional study. BMJ Open 2021, 11, e048221. [Google Scholar] [CrossRef] [PubMed]
  14. Lu, H.-K.; Chen, Y.-Y.; Yeh, C.; Chuang, C.-L.; Chiang, L.-M.; Lai, C.-L.; Casebolt, K.M.; Huang, A.-C.; Lin, W.-L.; Hsieh, K.-C. Discrepancies between leg-to-leg bioelectrical Impedance analysis and computerized tomography in abdominal visceral fat measurement. Sci. Rep. 2017, 7, 9102. [Google Scholar] [CrossRef]
  15. Chaudry, O.; Grimm, A.; Friedberger, A.; Kemmler, W.; Uder, M.; Jakob, F.; Quick, H.H.; Stengel, S.; Engelke, K. Magnetic Resonance Imaging and Bioelectrical Impedance Analysis to Assess Visceral and Abdominal Adipose Tissue. Obesity 2020, 28, 277–283. [Google Scholar] [CrossRef] [PubMed]
  16. Lazarus, J.V.; Colombo, M.; Cortez-Pinto, H.; Huang, T.T.; Miller, V.; Ninburg, M.; Schattenberg, J.M.; Seim, L.; Wong, V.W.; Zelber-Sagi, S. NAFLD—Sounding the alarm on a silent epidemic. Nat. Rev. Gastroenterol. Hepatol. 2020, 17, 377–379. [Google Scholar] [CrossRef] [PubMed]
  17. Wang, H.; Chen, Y.E.; Eitzman, D.T. Imaging Body Fat: Techniques and Cardiometabolic Implications. Arterioscler. Thromb. Vasc. Biol. 2014, 34, 2217–2223. [Google Scholar] [CrossRef]
  18. Rolfe, E.D.; Sleigh, A.; Finucane, F.M.; Brage, S.; Stolk, R.P.; Cooper, C.; Sharp, S.J.; Wareham, N.J.; Ong, K.K. Ultrasound measurements of visceral and subcutaneous abdominal thickness to predict abdominal adiposity among older men and women. Obesity 2010, 18, 625–631. [Google Scholar] [CrossRef]
  19. Van Dijk, D.P.; Bakens, M.J.; Coolsen, M.M.; Rensen, S.S.; van Dam, R.M.; Bours, M.J.; Weijenberg, M.P.; Dejong, C.H.; Olde Damink, S.W. Low skeletal muscle radiation attenuation and visceral adiposity are associated with overall survival and surgical site infections in patients with pancreatic cancer. J. Cachexia Sarcopenia Muscle 2017, 8, 317–326. [Google Scholar] [CrossRef]
  20. Richards, C.H.; Roxburgh, C.S.; MacMillan, M.T.; Isswiasi, S.; Robertson, E.G.; Guthrie, G.K.; Horgan, P.G.; McMillan, D.C. The Relationships between Body Composition and the Systemic Inflammatory Response in Patients with Primary Operable Colorectal Cancer. PLoS ONE 2012, 7, e41883. [Google Scholar] [CrossRef]
  21. Zhou, Z.; Xiong, Z.; Shen, Y.; Li, Z.; Hu, X.; Hu, D. Magnetic resonance imaging-based body composition is associated with nutritional and inflammatory status: A longitudinal study in patients with Crohn’s disease. Insights Imaging 2021, 12, 178. [Google Scholar] [CrossRef] [PubMed]
  22. Grąt, K.; Grąt, M.; Rowiński, O. Usefulness of Different Imaging Modalities in Evaluation of Patients with Non-Alcoholic Fatty Liver Disease. Biomedicines 2020, 8, 298. [Google Scholar] [CrossRef]
  23. Zhang, Y.N.; Fowler, K.J.; Hamilton, G.; Cui, J.Y.; Sy, E.Z.; Balanay, M.; Hooker, J.C.; Szeverenyi, N.; Sirlin, C.B. Liver fat imaging—A clinical overview of ultrasound, CT, and MR imaging. Br. J. Radiol. 2018, 91, 20170959. [Google Scholar] [CrossRef] [PubMed]
  24. Schwenzer, N.F.; Springer, F.; Schraml, C.; Stefan, N.; Machann, J.; Schick, F. Non-invasive assessment and quantification of liver steatosis by ultrasound, computed tomography and magnetic resonance. J. Hepatol. 2009, 51, 433–445. [Google Scholar] [CrossRef] [PubMed]
  25. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G.; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med. 2009, 6, e1000097. [Google Scholar] [CrossRef]
  26. Hong, Q.N.; Fàbregues, S.; Bartlett, G.; Boardman, F.; Cargo, M.; Dagenais, P.; Gagnon, M.-P.; Griffiths, F.; Nicolau, B.; O’Cathain, A.; et al. The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Educ. Inf. 2018, 34, 285–291. [Google Scholar] [CrossRef]
  27. Hong, Q.N.; Pluye, P.; Fàbregues, S.; Bartlett, G.; Boardman, F.; Cargo, M.; Dagenais, P.; Gagnon, M.-P.; Griffiths, F.; Nicolau, B.; et al. Improving the content validity of the mixed methods appraisal tool: A modified e-Delphi study. J. Clin. Epidemiol. 2019, 111, 49–59.E1. [Google Scholar] [CrossRef]
  28. Bouchi, R.; Takeuchi, T.; Akihisa, M.; Ohara, N.; Nakano, Y.; Nishitani, R.; Murakami, M.; Fukuda, T.; Fujita, M.; Minami, I.; et al. Increased visceral adiposity with normal weight is associated with the prevalence of non-alcoholic fatty liver disease in Japanese patients with type 2 diabetes. J. Diabetes Investig. 2016, 7, 607–614. [Google Scholar] [CrossRef]
  29. Dâmaso, A.R.; do Prado, W.L.; de Piano, A.; Tock, L.; Caranti, D.A.; Lofrano, M.C.; Carnier, J.; Cristofalo, D.J.M.; Lederman, H.; Tufik, S.; et al. Relationship between nonalcoholic fatty liver disease prevalence and visceral fat in obese adolescents. Dig. Liver Dis. 2008, 40, 132–139. [Google Scholar] [CrossRef]
  30. Jeong, S.K.; Kim, Y.K.; Park, J.W.; Shin, Y.J.; Kim, D.S. Impact of Visceral Fat on the Metabolic Syndrome and Nonalcoholic Fatty Liver Disease. J. Korean Med. Sci. 2008, 23, 789–795. [Google Scholar] [CrossRef]
  31. Kim, H.J.; Cho, M.H.; Park, J.S.; Nam, J.S.; Kang, E.S.; Ahn, C.W.; Cha, B.S.; Lee, E.J.; Lim, S.K.; Kim, K.R.; et al. Visceral Fat Thickness Predicts Fatty Liver in Koreans with Type 2 Diabetes Mellitus. J. Korean Med. Sci. 2008, 23, 256–261. [Google Scholar] [CrossRef] [PubMed]
  32. Ducluzeau, P.-H.; Manchec-Poilblanc, P.; Roullier, V.; Cesbron, E.; Lebigot, J.; Bertrais, S.; Aubé, C. Distribution of abdominal adipose tissue as a predictor of hepatic steatosis assessed by MRI. Clin. Radiol. 2010, 65, 695–700. [Google Scholar] [CrossRef]
  33. Grotti Clemente, A.P.; Molin Netto, B.D.; di Ganen, A.; Tock, L.; Arisa Caranti, D.; de Mello, M.T.; Tufik, S.; Dâmaso, A.R. Cut-Off Values of Visceral Adiposity to Predict NAFLD in Brazilian Obese Adolescents. J. Nutr. Metab. 2013, 2013, 724781. [Google Scholar] [CrossRef] [PubMed]
  34. Kim, D.; Chung, G.E.; Kwak, M.-S.; Seo, H.B.; Kang, J.H.; Kim, W.; Kim, Y.J.; Yoon, J.-H.; Lee, H.-s.; Kim, C.Y. Body Fat Distribution and Risk of Incident and Regressed Nonalcoholic Fatty Liver Disease. Clin. Gastroenterol. Hepatol. 2016, 14, 132–138. [Google Scholar] [CrossRef] [PubMed]
  35. Lee, H.W.; Kim, K.J.; Jung, K.S.; Chon, Y.E.; Huh, J.H.; Park, K.H.; Chung, J.B.; Kim, C.O.; Han, K.H.; Park, J.Y. The relationship between visceral obesity and hepatic steatosis measured by controlled attenuation parameter. PLoS ONE 2017, 12, e0187066. [Google Scholar] [CrossRef]
  36. Lee, S.; Kuk, J.L. Visceral fat is associated with the racial differences in liver fat between black and white adolescent boys with obesity. Pediatr. Diabetes 2017, 18, 660–663. [Google Scholar] [CrossRef] [PubMed]
  37. Choi, M.H.; Choi, J.-I.; Park, M.Y.; Rha, S.E.; Oh, S.N.; Jung, S.E.; Byun, J.Y.; Kannengiesser, S.; Son, Y. Validation of intimate correlation between visceral fat and hepatic steatosis: Quantitative measurement techniques using CT for area of fat and MR for hepatic steatosis. Clin. Nutr. 2018, 37, 214–222. [Google Scholar] [CrossRef]
  38. Kim, D.; Chung, G.E.; Kwak, M.-S.; Kim, Y.J.; Yoon, J.-H. Effect of longitudinal changes of body fat on the incidence and regression of nonalcoholic fatty liver disease. Dig. Liver Dis. 2018, 50, 389–395. [Google Scholar] [CrossRef]
  39. Simon, T.G.; Van Der Sloot, K.W.J.; Chin, S.B.; Joshi, A.D.; Lochhead, P.; Ananthakrishnan, A.N.; Xavier, R.; Chung, R.T.; Khalili, H. IRGM Gene Variants Modify the Relationship between Visceral Adipose Tissue and NAFLD in Patients with Crohn’s Disease. Inflamm. Bowel Dis. 2018, 24, 2247–2257. [Google Scholar] [CrossRef]
  40. Kure, T.; Mawatari, S.; Imamura, Y.; Oda, K.; Kumagai, K.; Hiramine, Y.; Miyahara, H.; Kanmura, S.; Moriuchi, A.; Uto, H.; et al. Nonalcoholic fatty liver disease is associated with both subcutaneous and visceral adiposity. Medicine 2019, 98, e17879. [Google Scholar] [CrossRef]
  41. Zhang, W.; Huang, R.; Wang, Y.; Rao, H.; Wei, L.; Su, G.L.; Lok, A.S. Fat Accumulation, Liver Fibrosis, and Metabolic Abnormalities in Chinese Patients with Moderate/Severe Versus Mild Hepatic Steatosis. Hepatol. Commun. 2019, 3, 1585–1597. [Google Scholar] [CrossRef]
  42. Hu, L.; Shao, X.; Qiu, C.; Shao, X.; Wang, X.; Niu, R.; Wang, Y. Hepatic steatosis is associated with abnormal hepatic enzymes, visceral adiposity, altered myocardial glucose uptake measured by 18F-FDG PET/CT. BMC Endocr. Disord. 2020, 20, 75. [Google Scholar] [CrossRef] [PubMed]
  43. Chiyanika, C.; Wong, V.W.; Wong, G.L.; Chan, H.L.; Hui, S.C.N.; Yeung, D.K.W.; Chu, W.C.W. Implications of Abdominal Adipose Tissue Distribution on Nonalcoholic Fatty Liver Disease and Metabolic Syndrome: A Chinese General Population Study. Clin. Transl. Gastroenterol. 2021, 12, e00300. [Google Scholar] [CrossRef] [PubMed]
  44. Kang, M.K.; Baek, J.H.; Kweon, Y.O.; Tak, W.Y.; Jang, S.Y.; Lee, Y.R.; Hur, K.; Kim, G.; Lee, H.W.; Han, M.H.; et al. Association of Skeletal Muscle and Adipose Tissue Distribution with Histologic Severity of Non-Alcoholic Fatty Liver. Diagnostics 2021, 11, 1061. [Google Scholar] [CrossRef]
  45. Igarashi, Y.; Tanaka, M.; Okada, H.; Hashimoto, Y.; Kumagai, M.; Yamaoka, M.; Nishimura, H.; Fukui, M. Visceral adipose tissue quality was associated with nonalcoholic fatty liver disease, independent of its quantity. Nutr. Metab. Cardiovasc. Dis. 2022, 32, 973–980. [Google Scholar] [CrossRef]
  46. Lee, S.; Kim, K.W.; Lee, J.; Park, T.; Koo, K.; Song, G.-W.; Lee, S.-G. Visceral Fat Area Is an Independent Risk Factor for Overweight or Obese Nonalcoholic Fatty Liver Disease in Potential Living Liver Donors. Transplant. Proc. 2022, 54, 702–705. [Google Scholar] [CrossRef] [PubMed]
  47. Baek, J.; Jung, S.J.; Shim, J.S.; Jeon, Y.W.; Seo, E.; Kim, H.C. Comparison of Computed Tomography-Based Abdominal Adiposity Indexes as Predictors of Non-Alcoholic Fatty Liver Disease among Middle-Aged Korean Men and Women. J. Prev. Med. Public Health 2020, 53, 256–265. [Google Scholar] [CrossRef]
  48. ROBINS-E Development Group. Risk of Bias in Non-Randomized Studies—Of Exposure (ROBINS-E). Launch Version, 20 June 2023. Available online: https://www.riskofbias.info/welcome/robins-e-tool (accessed on 31 July 2023).
  49. Hanlon, C.L.; Yuan, L. Nonalcoholic fatty liver disease: The Role of Visceral Adipose Tissue. Clin. Liver Dis. 2022, 19, 106–110. [Google Scholar] [CrossRef]
  50. Denkmayr, L.; Feldman, A.; Stechemesser, L.; Eder, S.K.; Zandanell, S.; Schranz, M.; Strasser, M.; Huber-Schönauer, U.; Buch, S.; Hampe, J.; et al. Lean Patients with Non-Alcoholic Fatty Liver Disease Have a Severe Histological Phenotype Similar to Obese Patients. J. Clin. Med. 2018, 7, 562. [Google Scholar] [CrossRef]
  51. Finelli, C.; Tarantino, G. What is the role of adiponectin in obesity related non-alcoholic fatty liver disease? World J. Gastroenterol. 2013, 19, 802–812. [Google Scholar] [CrossRef]
  52. Chung, G.E.; Kim, D.; Kwark, M.S.; Kim, W.; Yim, J.Y.; Kim, Y.J.; Yoon, J.H. Visceral Adipose Tissue Area as an Independent Risk Factor for Elevated Liver Enzyme in Nonalcoholic Fatty Liver Disease. Medicine 2015, 94, e573. [Google Scholar] [CrossRef]
  53. Hernández-Conde, M.; Llop, E.; Carrillo, C.F.; Tormo, B.; Abad, J.; Rodriguez, L.; Perelló, C.; Gomez, M.L.; Martínez-Porras, J.L.; Puga, N.F.; et al. Estimation of visceral fat is useful for the diagnosis of significant fibrosis in patients with non-alcoholic fatty liver disease. World J. Gastroenterol. 2020, 26, 6658–6668. [Google Scholar] [CrossRef]
  54. Miyake, T.; Miyazaki, M.; Yoshida, O.; Kanzaki, S.; Nakaguchi, H.; Nakamura, Y.; Watanabe, T.; Yamamoto, Y.; Koizumi, Y.; Tokumoto, Y.; et al. Relationship between body composition and the histology of non-alcoholic fatty liver disease: A cross-sectional study. BMC Gastroenterol. 2021, 21, 170. [Google Scholar] [CrossRef] [PubMed]
  55. Cimini, F.A.; Barchetta, I.; Carotti, S.; Bertoccini, L.; Baroni, M.G.; Vespasiani-Gentilucci, U.; Cavallo, M.G.; Morini, S. Relationship between adipose tissue dysfunction, vitamin D deficiency and the pathogenesis of non-alcoholic fatty liver disease. World J. Gastroenterol. 2017, 23, 3407–3417. [Google Scholar] [CrossRef] [PubMed]
  56. Vaidya, A.; Williams, J.S.; Forman, J.P. The Independent Association Between 25-Hydroxyvitamin D and Adiponectin and Its Relation with BMI in Two Large Cohorts: The NHS and the HPFS. Obesity 2012, 20, 186–191. [Google Scholar] [CrossRef] [PubMed]
  57. Roffe-Vazquez, D.N.; Huerta-Delgado, A.S.; Castillo, E.C.; Villarreal-Calderón, J.R.; Gonzalez-Gil, A.M.; Enriquez, C.; Garcia-Rivas, G.; Elizondo-Montemayor, L. Correlation of Vitamin D with Inflammatory Cytokines, Atherosclerotic Parameters, and Lifestyle Factors in the Setting of Heart Failure: A 12-Month Follow-Up Study. Int. J. Mol. Sci. 2019, 20, 5811. [Google Scholar] [CrossRef] [PubMed]
  58. Seo, J.A.; Eun, C.R.; Cho, H.; Lee, S.K.; Yoo, H.J.; Kim, S.G.; Choi, K.M.; Baik, S.H.; Choi, D.S.; Yim, H.J.; et al. Low Vitamin D Status is Associated with Nonalcoholic Fatty Liver Disease Independent of Visceral Obesity in Korean adults. PLoS ONE 2013, 8, e75197. [Google Scholar] [CrossRef]
  59. Choi, D.H.; Jung, C.H.; Mok, J.O.; Kim, C.H.; Kang, S.K.; Kim, B.Y. Nonalcoholic Fatty Liver Disease and Abdominal Fat Accumulation According to Vitamin D Status in Patients with Type 2 Diabetes. J. Obes. Metab. Syndr. 2018, 27, 53–60. [Google Scholar] [CrossRef]
  60. Liu, B.; Fan, D.; Yin, F. The Relationship between Vitamin D Status and Visceral Fat Accumulation in Males with Type 2 Diabetes. J. Nutr. Sci. Vitaminol. 2020, 66, 396–401. [Google Scholar] [CrossRef]
  61. Nauli, A.M.; Matin, S. Why Do Men Accumulate Abdominal Visceral Fat? Front. Physiol. 2019, 10, 1486. [Google Scholar] [CrossRef]
  62. Jaruvongvanich, V.; Sanguankeo, A.; Riangwiwat, T.; Upala, S. Testosterone, Sex Hormone-Binding Globulin and Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis. Ann. Hepatol. 2017, 16, 382–394. [Google Scholar] [CrossRef] [PubMed]
  63. Palmisano, B.T.; Zhu, L.; Stafford, J.M. Role of Estrogens in the Regulation of Liver Lipid Metabolism. Adv. Exp. Med. Biol. 2017, 1043, 227–256. [Google Scholar] [CrossRef] [PubMed]
  64. Summart, U.; Thinkhamrop, B.; Chamadol, N.; Khuntikeo, N.; Songthamwat, M.; Kim, C.S. Gender differences in the prevalence of nonalcoholic fatty liver disease in the Northeast of Thailand: A population-based cross-sectional study. F1000Research 2017, 6, 1630. [Google Scholar] [CrossRef]
  65. Ballestri, S.; Nascimbeni, F.; Baldelli, E.; Marrazzo, A.; Romagnoli, D.; Lonardo, A. NAFLD as a Sexual Dimorphic Disease: Role of Gender and Reproductive Status in the Development and Progression of Nonalcoholic Fatty Liver Disease and Inherent Cardiovascular Risk. Adv. Ther. 2017, 34, 1291–1326. [Google Scholar] [CrossRef] [PubMed]
Livers 03 00033 g001
Figure 1. Flow diagram of studies retrieval.
Figure 1. Flow diagram of studies retrieval.
Livers 03 00033 g001
Livers 03 00033 g002
Figure 2. Risk of bias assessed for all studies using ROBINS-E [28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47].
Figure 2. Risk of bias assessed for all studies using ROBINS-E [28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47].
Livers 03 00033 g002
Livers 03 00033 g003
Figure 3. Association (OR) between visceral fat and NAFLD in included studies without gender breakdown [30,36,39,42,43].
Figure 3. Association (OR) between visceral fat and NAFLD in included studies without gender breakdown [30,36,39,42,43].
Livers 03 00033 g003
Livers 03 00033 g004
Figure 4. Association (OR) between visceral fat and NAFLD in included studies with gender breakdown [29,31,45,46].
Figure 4. Association (OR) between visceral fat and NAFLD in included studies with gender breakdown [29,31,45,46].
Livers 03 00033 g004
Livers 03 00033 g005
Figure 5. Included studies with OR for developing NAFLD between subjects of largest VFA and subjects of lowest VFA for both genders [40,47].
Figure 5. Included studies with OR for developing NAFLD between subjects of largest VFA and subjects of lowest VFA for both genders [40,47].
Livers 03 00033 g005
Table 1. Descriptive Characteristics of Included Studies.
Table 1. Descriptive Characteristics of Included Studies.
Authors (Year)Journal TitleAimStudy DesignMMAT Scoren (Males:
Females)		Median or Mean Age (Range)Location
Damaso et al.
(2008) [29]		Relationship between non-alcoholic fatty liver disease prevalence and visceral fat in obese adolescentsDetermine the prevalence of NAFLD in obese adolescents according to visceral adipose tissue quartiles obtained by using an ultrasonography measurement protocol.N.R.N.A.181 (68:113)16.69 ± 1.58
(15–19)		Sao Paulo, Brazil
Jeong et al. (2008) [30]Impact of visceral fat on the metabolic syndrome and non-alcoholic fatty liver disease
-
Determine the prevalence of NAFLD and the metabolic syndrome (MetS), and to evaluate the distribution of NAFLD and its grades of hepatic steatosis according to the addition of the components of the MetS in relatively healthy hospital workers.
-
Investigate how visceral fat content and physical activity were associated with both NAFLD and MetS in men and women.
Cross-sectional3224 (78:146)43.8 ± 7.2 (30–59)Jeonbuk, Republic of Korea
Kim et al. (2008) [31]Visceral fat thickness predicts fatty liver in Koreans with type 2 diabetes mellitusEvaluate whether visceral adiposity is a predictor of diabetic fatty liver in Koreans with type 2 diabetes.N.R.N.A.1898 (944:954)53.7 ± 10.6 to 58.3 ± 9.3 among different subgroupsSeoul, Republic of Korea
Ducluzeau et al.
(2010) [32]		Distribution of abdominal adipose tissue as a predictor of hepatic steatosis assessed by MRIEvaluate the relationship between the distribution of VAT and subcutaneous adipose tissue (SAT) and hepatic steatosis using MRI.N.R.N.A.65 (46:19)57 ± 9.5 (N.R.)Angers,
France
Grotti Clemente
et al. (2013) [33]		Cut-off values of visceral adiposity to predict NAFLD in Brazilian obese adolescentsDetermine cut-off points of visceral fat to predict NAFLD and analyze metabolic disorders of obese adolescents in both genders.Cross-sectional4165 (49:116)N.R. (15–19)Sao Paulo, Brazil
Kim et al. (2016) [34]Body fat distribution and risk of incident and regressed non-alcoholic fatty liver diseaseEvaluate the relationship between body fat distribution and the incidence and regression of NAFLD, adjusting for risk factors for NAFLD in a large population-based cohort.Large cohort longitudinal prospective42017
(1206:811)		51.0 ± 8.2 to 53.8 ± 10.0 among different subgroupsSeoul, Republic of Korea
Bouchi et al. (2016) [28]Increased visceral adiposity with normal weight is associated with the prevalence of non-alcoholic fatty liver disease in Japanese patients with type 2 diabetesInvestigate the impact of increased visceral adiposity with normal weight (OB[−]VA[+]) on the prevalence of NAFLD in type 2 diabetic patients.Cross-sectional5140
(78:62)		65 ± 11 (N.R.)Tokyo, Japan
Lee et al. (2017) [35]The relationship between visceral obesity and hepatic steatosis measured by controlled attenuation parameterEvaluate the relationship between controlled attenuation parameters (CAP) and VFA (quantitative indicators of hepatic steatosis and central obesity, respectively), together with other clinical factors.Prospective5304 (165:139)56.5 ± 10.7 (N.R.)Seoul,
Republic of Korea
Lee and Kuk (2017) [36]Visceral fat is associated with the racial differences in liver fat between black and white adolescent boys with obesityExamine whether racial differences in liver fat in obese black versus white adolescents are attributed to differences in total and regional body fat distribution, including visceral fat, or cardiorespiratory fitness (CRF).N.R.N.A.57 (57:0)N.R. (12–18)Pittsburgh, PA, USA
Choi et al. (2018) [37]Validation of intimate correlation between visceral fat and hepatic steatosis: Quantitative measurement techniques using CT for area of fat and MR for hepatic steatosisInvestigate the relationship between degree of fatty infiltration of the liver measured by magnetic resonance spectroscopy (MRS) and body composition measured from CT images.Retrospective395 (58:37)35.9 ± 12.9 (17–69)Seoul,
Republic of Korea
Kim et al. (2018) [38]Effect of longitudinal changes in body fat on the incidence and regression of non-alcoholic fatty liver diseaseEvaluate the effects of VAT and SAT on the incidence or regression of NAFLD by adjusting for traditional metabolic risk factors and to investigate the interaction of gender and changes in VAT and SAT on incident NAFLD.Cohort study4956
(606:350)		51.3 ± 8.2 to 54.4 ± 10.0 among different subgroupsSeoul,
Republic of Korea
Simon et al. (2018) [39]IRGM gene variants modify the relationship between visceral adipose tissue and NAFLD in patients with Crohn’s diseaseExplore the relationship between VAT volume, previously characterized genetic variants that govern the autophagy pathway, and NAFLD risk in patients with Crohn’s disease.Cross-sectional4462 (216:246)40 ± 15 (≥18)Boston, MA, USA
Kure et al. (2019) [40]Non-alcoholic fatty liver disease is associated with both subcutaneous and visceral adiposityClarify the association between the subcutaneous fat area (SFA) as determined by CT and fatty liver as determined by ultrasonography in the Japanese population.Cross-sectional53197 (1723:1474)Men: 55.2 ± 11.2 (22–74)
Women: 58.6 ± 9.4 (28–74)		Kagoshima, Japan
Zhang et al. (2019) [41]Fat accumulation, liver fibrosis, and metabolic abnormalities in Chinese patients with moderate/severe versus mild hepatic steatosis
-
Measure the subcutaneous, visceral fat, and muscle compartments in Chinese patients with NAFLD and correlate fat in these compartments with the degree of hepatic steatosis.
-
Compare liver damage and the prevalence of metabolic abnormalities between Chinese patients with NAFLD and moderate to severe hepatic steatosis versus those with mild steatosis.
Prospective3160
(73:87)		46.5
(IQR 35.3–58.0)		Beijing, China
Hu et al. (2020) [42]Hepatic steatosis is associated with abnormal hepatic enzymes, visceral adiposity, altered myocardial glucose uptake measured by 18F-FDG PET/CTInvestigate the association between hepatic steatosis and glucose metabolic abnormality in a variety of organs/tissues assessed by using 18F-FDG PET/CT in a population-based cohort.Population-based cohort, retrospective4191 (129:62)48.8 ± 9.0 (N.R.)Jiangsu, China
Chiyanika et al. (2021) [43]Implications of abdominal adipose tissue distribution on non-alcoholic fatty liver disease and metabolic syndrome: A Chinese general population studyEvaluate the association of abdominal adipose distribution with fatty liver infiltration and MetS development in the lean, overweight, and obese adult populations using a chemical shift-encoded MRI method.Secondary analysis of a prospective trial4625 (238:387)48 ± 10 (19–70)Hong Kong, China
Kang et al. (2021) [44]Association of skeletal muscle and adipose tissue distribution with histologic severity of non-alcoholic fatty liverInvestigate the association between the histologic features, skeletal muscle mass, and adipose tissue distribution using CT scans in patients with NAFLD.Cross-sectional4178 (86:92)53.5 (38–64)Daegu, Republic of Korea
Igarashi et al. (2022) [45]Visceral adipose tissue quality was associated with non-alcoholic fatty liver disease, independent of its quantityInvestigate the association between VAT quantity and quality and the prevalence or incidence of NAFLD in middle-aged Japanese subjects.Cross-sectional, retrospective cohort3627 (349:278)45.2 ± 9.4 to 56.3 ± 10.7 (N.R.)Kyoto, Japan
Lee et al. (2022) [46]Visceral fat area is an independent risk factor for overweight or obese non-alcoholic fatty liver disease in potential living liver donorsEvaluate the correlation between hepatic steatosis, determined by biopsy, and visceral adiposity, measured by CT, in overweight or obese potential living liver donors, and to investigate the risk factors for overweight or obese NAFLD.Retrospective4375 (273:102)30.4 ± 9.5Seoul, Republic of Korea
Baek et al. (2020) [47]Comparison of computed tomography-based abdominal adiposity indexes as predictors of non-alcoholic fatty liver disease among middle-aged Korean men and womenThe associations of three CT-based abdominal NAFLD among middle-aged Korean men and women.Cross-sectional53846 (1366:2480)N.R. (30–64)Seoul, Republic of Korea
N.R. indicates not reported, N.A. indicates not applicable.
Table 2. Radiological modality details of the included studies.
Table 2. Radiological modality details of the included studies.
Authors (Year)Visceral Fat
Measurement
Modality		Machine Model and/or BrandLandmark for
Visceral
Measurement		Liver Feature
Assessment Method		Machine
Model and/or Brand
Damaso et al.
(2008) [29]		Ultrasound3.5 MHz multifrequency transducer (broad band)Distance between the internal face of the same muscle and the anterior wall of the aorta.Ultrasound3.5 MHz multifrequency transducer (broad band)
Jeong et al. (2008) [30]Ultrasound3.5 MHz convex probe (Sequoia, Siemens Medical Solutions, Mountain View, CA, USA)Between the posterior aspect of the anterior abdominal wall and the anterior line of the abdominal aorta, at the mid-point between the transverse portion of the duodenum and the iliac bifurcation of the aorta.Ultrasound3.5 MHz convex probe (Sequoia, Siemens Medical Solutions, Mountain View, CA, USA)
Kim et al. (2008) [31]UltrasoundSA 9900, Medison, Seoul, Republic of Korea1 cm above the umbilicus.UltrasoundSA 9900, Medison, Seoul, Republic of Korea
Ducluzeau et al.
(2010) [32]		MRI1.5 T clinical MRI system (Excite, GE Healthcare, Milwaukee, WI, USA)At the level of the 3rd and 4th lumbar vertebra.MRI1.5 T clinical MRI system (Excite, GE Healthcare, Milwaukee, WI, USA)
Grotti Clemente
et al. (2013) [33]		Ultrasound3.5 MHz multifrequency transducer (broad band)The distance between the internal face of the same muscle and the anterior wall of the aorta.Ultrasound3.5 MHz multifrequency transducer (broad band)
Kim et al. (2016) [34]CT16-detector row CT scanner (Somatom Sensation 16, Siemens Medical Solutions, Forchheim, Germany)N.R.UltrasoundAcuson, Sequoia 512, Siemens, Mountain View, CA
Bouchi et al. (2016) [28]CTAquilion PRIME, Toshiba Medical Systems, Tochigi, JapanN.R.CTAquilion PRIME, Toshiba Medical Systems, Tochigi, Japan
Lee et al. (2017) [35]CTSomatom
Plus, Siemens, Germany		At the level of the 2nd and 3rd lumbar vertebra.Ultrasound, with CAP being assessed with Transient Elastography (TE)Liver FibroScan® (Echosens, Paris, France) M probe
Lee and Kuk (2017) [36]MRI3T MR system (Siemens, Tim Trio, Erlangen, Germany)At the level of 4th/5th lumbar vertebrae.MRS3T MR system (Siemens, Tim Trio, Erlangen, Germany)
Choi et al. (2018) [37]CT64-detector
CT (Somatom Sensation 64/Definition AS+, Siemens Healthcare, Erlangen, Germany, or Discovery CT750HD, GE Healthcare, Milwaukee, WI, USA)		At the level of the 3rd lumbar vertebral body transverse processes.MRS3-T system
(MAGNETOM Verio, Siemens Healthcare, Erlangen, Germany)
Kim et al. (2018) [38]CT16-detector row CT scanner (Somatom Sensation 16, Siemens Medical Solutions, Forchheim, Germany)The area at the umbilicus level.UltrasoundAcuson, Sequoia 512, Siemens, Mountain View, CA, USA
Simon et al. (2018) [39]CT64-slice CT scanner (Siemens Medical Solutions, Andover, MA, USA)From the 11th thoracic vertebra to the 5th sacral vertebra.CT64-slice CT scanner (Siemens Medical Solutions, Andover, MA, USA)
Kure et al. (2019) [40]CTN.R.At an umbilical slice.UltrasoundN.R.
Zhang et al. (2019) [41]CTN.R.At the level of
2nd lumbar vertebrae.		CTN.R.
Hu et al. (2020) [42]CTGerman Siemens Biograph mCT (64) PET/CT instrumentThe anterior vertebral body was delineated from the first sacrum up to the abdominal wall muscles and the VAT volumes were divided into 25 consecutive layers with a total length of 125 mm.CTGerman Siemens Biograph mCT (64) PET/CT instrument
Chiyanika et al. (2021) [43]MRI3.0 T scanner (Achieva, Philips Medical Systems, Best, the Netherlands)N.R.Proton MRS3.0 T scanner (Achieva, Philips Medical Systems, Best, the Netherlands)
Kang et al. (2021) [44]CTN.R.At the level of 3rd lumbar vertebrae.Ultrasound-guided percutaneous liver biopsyN.R.
Igarashi et al. (2022) [45]CTActivation 16 CT Scanner (Toshiba Medical Systems, Japan)At the level of 3rd lumbar vertebrae.UltrasoundN.R.
Lee et al. (2022) [46]CT128-slice
multidetector-row CT scanner (Definition AS+ or Edge, Siemens, Erlangen, Germany).		At the level of 3rd lumbar vertebrae.Ultrasound-guided percutaneous liver biopsyN.R.
Baek et al. (2020) [47]CTAquarius iNtuition Viewer (version 4.4.12; TeraRecon, Foster City, CA, USA)At the level of the 4th and 5th lumbar vertebrae.NAFLD liver fat score (NAFLD-LFS) which was developed from MRSN.R.
Table 3. Findings from the included studies.
Table 3. Findings from the included studies.
Authors (Year)Output Variable (Liver Indicator) of InterestStatistical Analysis MethodVisceral
Quantification		CorrelationConclusions
Damaso et al. (2008) [29]NAFLD
-
Pearson’s correlation: for the association between the variables.
-
Multivariate logistic regression analysis: to investigate the independent predictors for NAFLD development.
Visceral Fat in cmOnly visceral fat remained statistically significant. Every 1 cm increase in visceral fat was associated with an increased risk of 1.97 (95% CI 1.06–3.66, p = 0.03)-fold and 2.08 (95% CI 1.38–3.13, p = 0.0003)-fold in boys and girls, respectively, to develop NAFLD. Positive correlation between visceral fat and steatosis degree was found (r = 0.537).Visceral fat was a determining factor to increase NAFLD prevalence and steatosis degree.
Jeong et al. (2008) [30]NAFLDMultivariate logistic regression: to determine the independent association with NAFLD for those independent variables that showed differences of more than borderline significance (p < 0.1).Visceral fat thickness (VFT) in cmVFT increased significantly according to the severity of NAFLD in both genders (p < 0.001).
After adjustment for all potential confounders, NAFLD was independently and positively associated with VFT (OR 1.10, 95% CI 1.01–1.19, p = 0.015).
VFT was independently associated with NAFLD (OR 1.10, 95% CI 1.02–1.19) in subjects with more than two components of the MetS.		VFT was significantly associated with both the severity of hepatic steatosis in NAFLD and the addition of components of the MetS. An increased visceral fat content could be not only biological markers but also therapeutic targets in the treatment of NAFLD and MetS.
Kim et al. (2008) [31]NAFLDMultiple logistic regression: to evaluate risk factors of fatty liver in male and female type 2 diabetic patients.Visceral fat thickness (VFT) in mmHigh VFT was independently associated with fatty liver in both male and female type 2 diabetic patients. The OR of high VFT for fatty liver showed the highest values (OR 3.14, 95% CI: 2.24–4.39, p = 0.00) and (OR 2.84, 95% CI: 2.04–3.93, p = 0.00) in males and females, respectively.VFT of all metabolic indices showed the strongest predictive value for fatty liver and that even in centrally non-obese male subjects with a waist circumference < 90 cm but with high visceral fat accumulation, fatty liver is implicated.
Ducluzeau et al. (2010) [32]Hepatic steatosisSpearman rank correlation: to assess the univariate relationships with steatosis as some variables were not normally distributed.Visceral adipose tissue (VAT) in cm2There was a significant correlation between the percentage of liver steatosis and the abdominal distribution of adipose tissue when calculated with VAT surface (r = 0.307, p = 0.014).The distribution of adipose tissue is more relevant than total fat mass when assessing the possibility of liver steatosis in overweight subjects.
Grotti Clemente et al. (2013) [33]NAFLDLogistic regression analysis: to compare individuals with NAFLD as well as individuals with NAFLD and non-NAFLD to determine the predictor variables in the final model.Visceral Fat in cm. NAFLD patients had significantly higher values for visceral fat when compared with non-NAFLD obese patients in both genders.
In the logistic regression analysis, visceral fat was found to be one of the independent predictors of NAFLD (β-coefficient: 1.606, p = 0.014).
In the correlation, visceral-to-subcutaneous ratio has r = 0.771 with non-NAFLD but presented with higher r = 0.790 with NAFLD patients.		Visceral fat cut-off point for the prediction of NAFLD adolescents in both genders was reported. However, the cut-off point cannot be generalized to other populations.
Kim et al. (2016) [34]NAFLDCox proportional hazard models: to analyze the HRs and 95% CI for the incident and regressed NADLF per 1-SD increase in VAT and SAT area for each quintile or quartile of VAT and SAT area, while controlling for potential confounders.Visceral adipose tissue (VAT) in cm2In the age-, sex-, and BMI-adjusted models, when the subjects in quintile 5 were compared with those in quintile 1 of the VAT area there was (HR 2.94, 95% CI 1.78–4.86, p < 0.001) for incident NAFLD. After further adjusting for all possible confounding factors including smoking status, diabetes, hypertension, soft drink consumption, physical activity, SAT area, cholesterol, TG, and serum HDL cholesterol levels, the association between the highest and lowest quintile for developing NAFLD was (HR 2.23, 95% CI 1.28–3.89, p = 0.005; HR 1.36, 95% CI 1.16–1.59, per 1-SD, p < 0.001).
In the age-, sex-, and BMI-adjusted models, VAT to subcutaneous fat (SAT) ratio has (HR 1.80, 95% CI 1.27–2.57, p = 0.001) for incident NAFLD. After further adjusting for all possible confounding factors including smoking status, diabetes, hypertension, soft drink consumption, physical activity, SAT area, cholesterol, TG, and serum HDL cholesterol levels, the association for VAT/SAT ratio to develop NAFLD was (HR 1.51, 95% CI 1.03–2.19, p = 0.033).		An increased VAT area at baseline independently predicted incident NAFLD in a healthy general population. Visceral obesity was the most important target for future interventions in the treatment of NAFLD.
Bouchi et al. (2016) [28]NAFLDLinear and logistic regression: to assess the cross-sectional association of each manifestation of VFA and the entire body weight with LAI.Visceral fat area (VFA) in cm2, where >100 cm2 would means increased visceral adiposity.NAFLD in this study is defined by liver-spleen attenuation index (LAI) < 0.9.
LAI was calculated as follows: the mean attenuation value of eight different sites in the liver (two ROIs each in Couinaud hepatic segments, V, VI, VII and VIII) divided by that of three different sites in the spleen (the upper, middle and lower third of the spleen). The lower the LAI, the greater the lipid accumulation
Patients with or without obesity but with high visceral fat remained significant as a risk factor for LAI < 0.9. The OR was found to be 6.79 (95% CI 1.24–36.88, p = 0.027) and 5.88 (95% CI 1.03–33.52, p = 0.046) for patients with and without obesity, respectively.
Compared with those with BMI < 23.0 kg/m2 and VFA < 100 cm2, patients with BMI < 23.0 kg/m2 and VFA ≥ 100 cm2 had a significantly increased risk for lower LAI; whereas patients with BMI ≥ 23.0 kg/m2 and VFA < 100 cm2 did not show increased risk for lower LAI.		Increased visceral adiposity with normal weight is a strong predictor for the prevalence of NAFLD in Japanese patients with type 2 diabetes. Moreover, normal BMI patients with high visceral fat present with almost similar risks to those with high BMI patients.
Lee et al. (2017) [35]Significant hepatic steatosisUnivariate and subsequent multivariate binary logistic regression analyses: to identify independent factors related to significant hepatic steatosis.Visceral fat area (VFA) in cm2. VFA was identified as an independent risk factor for significant hepatic steatosis (OR 1.010, 95% CI 1.001–1.019, p = 0.028). VFA was the only independent risk factor for significant hepatic steatosis in males (OR 1.008, 95% CI 1.001–1.011, p = 0.045), whereas VFA was one of the independent risk factors for females (OR 1.029, 95% CI 1.010–1.048, p = 0.002).VFA was significantly correlated with hepatic steatosis measured by CAP and therefore, patients with NAFLD should rely on parameters indicative of central obesity, and not only BMI.
Lee and Kuk (2017) [36]NAFLDLogistic regression: to assess the simple and independent associations between fatty liver and the body composition factors and CRF adjusting for age and race.Visceral fat in cm2Liver fat was associated with visceral fat r = 0.62, p ≤ 0.05) after adjusting for age and race. Only waist circumference and visceral fat were associated with higher odds of fatty liver (p < 0.05). In a model with age, ethnicity, total body fat, total FFM, visceral fat, ASAT, and CRF, only visceral fat was independently associated with increased odds of having fatty liver (OR 1.12, 95% CI 1.04–1.21, p = 0.003).Visceral fat was associated with an increased propensity to NAFLD independent of race. It also explained that the racial disparities in liver fat between obese black versus white are in part due to the differences in visceral fat.
Choi et al. (2018) [37]Hepatic steatosisPearson’s correlation: to investigate the relationship between hepatic fat amount measured by MRS and various factors associated with body composition.Visceral fat area (VFA) in cm2. The highest Pearson correlation coefficient was found between hepatic steatosis and the area of visceral fat for the significant correlation.
Overall: r = 0.569, p < 0.001
Male: r = 0.576, p < 0.001
Female: r = 0.473, p = 0.003.		Visceral fat area correlated most highly to hepatic steatosis in males and had the most intimate correlation to hepatic steatosis among all significantly correlated parameters associated with body habitus.
Kim et al. (2018) [38]NAFLDCox proportional hazards models: to analyze the adjusted HR and 95% CI for the incident and regressed NAFLD for each tertile of difference in the VAT and SAT area after controlling for potential confounders.Visceral adipose tissue (VAT) area in cm2.An increased VAT area was associated with a higher incidence of NAFLD (HR 2.45, 95% CI 1.56–3.85, p < 0.001) after adjusting for VAT and SAT area at baseline. Subjects with a 10% increase in VAT during follow-up had a 15% greater hazard of incident NAFLD (95% CI 1.09–1.22). The addition of longitudinal change in liver enzymes, total cholesterol, TG, and fasting glucose levels to the final model did not significantly reduce the HRs for change in VAT area on incident NAFLD.
An increasing change in VAT area was inversely associated with the regression of NAFLD (HR 0.40, 95% CI 0.20–0.80, p = 0.008).		An increase in VAT area over time independently predicted the incident NAFLD. Additionally, temporal decrease in VAT area in patients with NAFLD had a protective effect and led to a regression of NAFLD.
Simon et al. (2018) [39]NAFLDLogistic regression: to evaluate the relationship between VAT volume and risk of NAFLD.Visceral adipose tissue (VAT) Volume in cm3After adjusting for known NAFLD risk factors and variables associated with inflammatory bowel disease (IBD) severity, VAT quartile (OR 1.37, 95% CI 1.03–1.81, p = 0.012) is one of the factors that remained significantly associated with NAFLD. Increased VAT quartile was associated with a significantly increased risk of radiographic NAFLD (p = 0.032).Increasing VAT volume was associated with a significantly increased risk of NAFLD and with markers of NAFLD severity in the cohort of Crohn’s disease patients.
Severe SteatosisAlthough the number of patients was small (n = 13), there was a consistent relationship between increasing VAT quartile and risk of severe steatosis in age- and sex-adjusted analyses (OR 5.08, 95% CI 2.00–12.88, p = 0.0006).
Kure et al. (2019) [40]NAFLDLogistic regression: to calculate the maximum likelihood of ORs for the risk of fatty liver and 95% CI.Visceral fat area (VFA) in cm2. The OR for the association between VFA and NFALD increased across from V-Q1 to V-Q4 for both men and women, even after adjusting for the age, SFA, presence of hypertension, dyslipidemia, and impaired glucose metabolism, and smoking status. OR of NAFLD for different VFA with p-value < 0.001:
For men:
V-Q1 (10.0–73.8 cm2): OR 1 (reference)
V-Q2 (73.8–103.2 cm2): OR 3.51, 95% CI 2.40–5.12
V-Q3 (103.2–139.6 cm2): OR 5.61, 95% CI 3.81–8.27
V-Q4 (139.7–447.8 cm2): OR 8.20, 95% CI 5.38–12.5
For women:
V-Q1 (2.7–44.1 cm2): OR 1 (reference)
V-Q2 (44.1–67.3 cm2): OR 3.12, 95% CI 1.63–5.97
V-Q3 (67.3–94.2 cm2): OR 10.5, 95% CI 5.58–19.8
V-Q4 (94.2–346.0 cm2): OR 21.6, 95% CI 11.3–41.2.		NAFLD had an independent association with subcutaneous adiposity ab initio, which highlights a possible role of NAFLD in the development of obesity.
Zhang et al. (2019) [41]Mild hepatic steatosis (liver Hounsfield unit (HOUNSFIELD UNIT) > 40)
Severe hepatic steatosis (liver HOUNSFIELD UNIT < 40)
-
Pearson’s correlation: to assess bivariate associations between variables of interest.
-
Spearman’s correlation: to assess associations when variables were not normally distributed.
Visceral fat area (VFA) in cm2. Hepatic steatosis measured by the liver HOUNSFIELD UNIT showed a moderate correlation with fat in the visceral compartment (r = −0.481, p < 0.001)
Compared to patients with mild hepatic steatosis, those with moderate/severe hepatic steatosis had larger VFA and SFA, but after adjustment for BMI, only the ratio of VFA to BMI, but not SFA to BMI, was significantly higher (p = 0.001).
Patients with moderate/severe hepatic steatosis also had a higher ratio of VFA to SFA (1.2) than those with mild steatosis (1.0), but this difference was not significant (p = 0.258).		NAFLD patients with moderate/severe steatosis had more visceral and subcutaneous fat as well as more fat infiltration in muscle. They also had more liver damage and a higher prevalence of MetS, which was not limited to patients with abnormal BMI but also those with normal BMI.
Hu et al. (2020) [42]NAFLD
-
Pearson’s correlation: to analyze the correlation between continuous variables in univariate analysis
-
Logistic multivariate regression: to analyze the independent correlation factors for NAFLD of two categorical variables.
Visceral adipose tissue (VAT) volume in mm. Compared with the non-NAFLD patients, patients with NAFLD had significantly increased abdominal fat, including VAT and SAT, volumes (p < 0.05). Univariate analysis showed that NAFLD had significant positive correlations with BMI, diabetes, insulin resistance, VAT, and SAT volumes, with the correlation coefficient r = 0.154–0.390 (p < 0.05). Logistic regression analyses of these factors showed that increased VAT volume was an independent risk factor for NAFLD (OR 1.002, 95% CI 1.001–1.003, p < 0.05).Although BMI, abdominal fat volume, and SAT volume were significantly higher in NAFLD patients than in non-NAFLD subjects (p < 0.05), they were not independent correlation factors for NAFLD, suggesting that increased VAT volume was more clinically significant. VAT volume was an independent correlation factor for NAFLD.
Chiyanika et al. (2021) [43]NAFLD
-
Pearson’s correlation: test for association.
-
Multiple linear and binary logistic regression analyses with correction for multiple comparisons: to evaluate the causation relationship.
Visceral adipose tissue (VAT) in volume (L). The incidence of fatty liver disease showed an increasing linear trend with an increase in VAT volume (p < 0.001). Fatty liver was increased by 2.53 (95% CI 2.04–3.12)-fold for a 1-SD increase in VAT volume. VAT also showed a significant association with fatty liver disease (r = 0.391, p < 0.001).
VAT/SAT ratio also showed a significant association with fatty liver disease (r = 0.342, p < 0.001). Among all the subgroups, lean with fatty liver showed the highest VAT/SAT ratio (0.54) without a significant difference between the lean and obese with NAFLD (p = 0.127).		Regardless of the BMI, increased VAT volume and disproportional distribution of VAT/SAT may be vital drivers to the development of the MetS and NAFLD.
Kang et al. (2021) [44]Hepatic steatosis
-
Spearman’s correlation: to analyze the association between the histologic findings and body composition indices.
Visceral adipose tissue (VAT) index, which were defined as the body composition area (cm2) by height squared (m2).The VAT index was not correlated with hepatic steatosis (rs = 0.13, p = 0.090).The histologic severity of NAFLD was correlated with visceral adiposity, which was independently associated with advanced fibrosis in patients with NAFLD.
Igarashi et al. (2022) [45]NAFLD
-
Logistic regression: to assess the association of abdominal adipose tissue area parameters with the prevalence of NAFLD.
Visceral fat area (VFA) index, normalized in height squared (cm2/m2).The VFA index was independently associated with the prevalence of NAFLD in males (OR 1.04, 95% CI 1.01–1.06, p = 0.0078, per 1.0 cm2/m2) and females (OR 1.11, 95% CI 1.05–1.18, p = 0.0003, per 1.0 cm2/m2), respectively.VFA index and VFD had an interaction effect on the NAFLD prevalence. High VAT quantity or low VAT quality was independently associated with the prevalence of NAFLD. VAT quality might be more related to the incidence of NAFLD than VAT quantity.
Lee et al. (2022) [46]NAFLD
-
Pearson’s correlation: evaluate correlations between the degree of hepatic steatosis and other variables.
-
Multivariable logistic
-
regression: to investigate the factors associated with overweight or obese NAFLD.
Visceral fat area (VFA) in cm2VFA was an independent risk factor for overweight or obese NAFLD in men (OR 1.015, 95% CI 1.008–1.022, p < 0.001) and women (OR 1.029, 95% CI 1.011–1.047, p = 0.002), respectively.Visceral adiposity was positively correlated with the degree of hepatic steatosis in overweight or obese potential living liver donors. Additionally, visceral adiposity may be an independent risk factor for overweight or obese NAFLD.
Hepatic steatosisIn men, the degree of hepatic steatosis was positively correlated with VFA (r = 0.307; p < 0.001). In women, the degree of hepatic steatosis was positively correlated with only VFA (r = 0.387; p < 0.001).
Baek et al. (2020) [47]NAFLDLogistic regression: to evaluate the associations between the abdominal adiposity indexes and NAFLD.Visceral fat area (VFA) in cm2.Pearson’s correlation for VFA/SFA ratio with NAFLD for men and women is r = 0.031 (p < 0.001) and r = 0.162 (p < 0.001), respectively.Measuring the amount of visceral fat from the abdomen can help in identifying probable NAFLD, with the best predictive indicators in men is VFA while in women is the visceral-to-subcutaneous ratio.
OR for each quintile increase in VFA with p < 0.001:
For men:
VFA Q1: 1.00 (reference)
VFA Q2: 2.59 (95% 1.36–4.95)
VFA Q3: 4.73 (95% 2.45–9.16)
VFA Q4: 6.14 (95% 2.96–12.73).
For women:
VFA Q1: 1.00 (reference)
VFA Q2: 2.99 (95% 1.19–7.51)
VFA Q3: 6.65 (95% 2.72–16.23)
VFA Q4: 17.84 (95% 7.12–44.71)
OR for each quintile increase in VFA/SFA ratio:
For men: (p = 0.003)
VFA/SFA Q1: 1.00 (reference)
VFA/SFA Q2: 1.39 (95% 0.88–2.20)
VFA/SFA Q3: 1.91 (95% 1.20–3.03)
VFA/SFA Q4: 1.99 (95% 1.22–3.26)
For women: (p < 0.001)
VFA/SFA Q1: 1.00 (reference)
VFA/SFA Q2: 1.39 (95% 0.81–2.38)
VFA/SFA Q3: 3.06 (95% 1.83–5.12)
VFA/SFA Q4: 6.73 (95% 4.10–11.03)
Table 4. Summary of association and correlation results differentiated by genders.
Table 4. Summary of association and correlation results differentiated by genders.
StudyUnit of MeasurementMaleFemaleGender with Higher Association or Correlation
NAFLD
Damaso et al. (2008) [30]OR1.97 (95% CI 1.06–3.66, p = 0.03)2.08 (95% CI 1.38–3.13, p = 0.0003)Female
Kim et al. (2008) [31]3.14, (95% CI: 2.24–4.39, p = 0.00)2.84 (95% CI: 2.04–3.93, p = 0.00)Male
Igarashi et al. (2022) [45]1.04 (95% CI 1.01–1.06, p = 0.0078)1.11 (95% CI 1.05–1.18, p = 0.0003)Female
Lee at al. (2022) [46]1.015 (95% CI 1.008–1.022, p < 0.001)1.029 (95%CI 1.011–1.047, p = 0.002)Female
Risk of NAFLD measured between largest visceral fat area group and reference group
Kure et al. (2019) [40]OR8.20 (95% CI 5.38–12.5, p < 0.001)21.6 (95% CI 11.3–41.2, p < 0.001)Female
Baek et al. (2020) [47]6.14 (95% CI 2.96–12.73, p < 0.001)17.84 (95% CI 7.12–44.71, p < 0.001)Female
Hepatic Steatosis (Mild and Severe/Significant)
Lee et al. (2017) [35]OR1.008 (95% CI 1.001–1.011, p = 0.045)1.029 (95% CI, 1.010–1.048, p = 0.002)Female
Choi et al. (2018) [37]Correlationr = 0.576, p < 0.001r = 0.473, p = 0.003Male
Lee et al. (2022) [46]r = 0.307; p < 0.001r = 0.387; p < 0.001Female
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Seaw, K.M.; Henry, C.J.; Bi, X. Relationship between Non-Alcoholic Fatty Liver Disease and Visceral Fat Measured by Imaging-Based Body Composition Analysis: A Systematic Review. Livers 2023, 3, 463-493. https://doi.org/10.3390/livers3030033

AMA Style

Seaw KM, Henry CJ, Bi X. Relationship between Non-Alcoholic Fatty Liver Disease and Visceral Fat Measured by Imaging-Based Body Composition Analysis: A Systematic Review. Livers. 2023; 3(3):463-493. https://doi.org/10.3390/livers3030033

Chicago/Turabian Style

Seaw, Ker Ming, Christiani Jeyakumar Henry, and Xinyan Bi. 2023. "Relationship between Non-Alcoholic Fatty Liver Disease and Visceral Fat Measured by Imaging-Based Body Composition Analysis: A Systematic Review" Livers 3, no. 3: 463-493. https://doi.org/10.3390/livers3030033

Article Metrics

Back to TopTop