Journal of Obesity & Metabolic Syndrome

Search

Article

J Obes Metab Syndr 2024; 33(4): 326-336

Published online December 30, 2024 https://doi.org/10.7570/jomes24005

Copyright © Korean Society for the Study of Obesity.

Association between Body Fat Distribution and Nonalcoholic Fatty Liver Disease/Fibrosis Based on Race/Ethnicity

Donghee Kim1,* , George Cholankeril2, Aijaz Ahmed1

1Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, CA; 2Section of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine, Houston, TX, USA

Correspondence to:
Donghee Kim
https://orcid.org/0000-0003-1919-6800
Division of Gastroenterology and Hepatology, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA 94304, USA
Tel: +1-650-497-9261
Fax: +1-650-498-5692
E-mail: dhkimmd90@gmail.com

Received: February 13, 2024; Reviewed : May 31, 2024; Accepted: June 23, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background: Body fat distribution may impact nonalcoholic fatty liver disease (NAFLD) and significant fibrosis differently according to race/ethnicity. We determined the relationship between body fat distribution and NAFLD/significant fibrosis according to race/ethnicity.
Methods: A cross-sectional study of 2,395 participants used the National Health and Nutrition Examination Survey 2017 to 2018. NAFLD and significant fibrosis (≥F2) were defined by controlled attenuation parameter scores and liver stiffness measurements on transient elastography, respectively. Visceral and subcutaneous fat volumes were defined by dual-energy X-ray absorptiometry.
Results: The odds ratio (OR) for NAFLD per 1-standard deviation in visceral fat volume and subcutaneous fat volume was 2.05 (95% confidence interval [CI], 1.36 to 3.09) and 1.48 (95% CI, 1.04 to 2.09) in total population, respectively. Visceral fat in non-Hispanic Blacks had the highest odds for NAFLD (OR, 2.86; 95% CI, 1.45 to 5.62), and non-Hispanic Whites (OR, 2.29; 95% CI, 1.19 to 4.40) and non-Hispanic Asians (OR, 1.61; 95% CI, 1.13 to 2.29) were in order. Significant associations between subcutaneous fat volume (OR, 2.10; 95% CI, 1.34 to 3.29; P=0.003) or visceral fat volume (OR, 1.35; 95% CI, 1.05 to 1.73; P=0.023) and significant fibrosis were noted among individuals with NAFLD. Hispanics had the highest odds for NAFLD-associated significant fibrosis (OR, 2.74; 95% CI, 1.32 to 5.70 per 1-standard deviation in subcutaneous fat volume), and non-Hispanic Whites (OR, 2.35; 95% CI, 1.11 to 4.98) and non-Hispanic Asians (OR, 2.01; 95% CI, 1.01 to 4.01) were in order.
Conclusion: Visceral adiposity was associated with NAFLD and significant fibrosis despite the association of subcutaneous adiposity in NAFLD and significant fibrosis. Racial/ethnic differences in the association between body fat distribution on NAFLD and significant fibrosis were noted.

Keywords: Intra-abdominal fat, Subcutaneous fat, Obesity, Hepatic steatosis, NHANES, Metabolic dysfunction-associated steatotic liver disease

Globally, nonalcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease, with a prevalence of up to 30%.1 Individuals with NAFLD have experienced higher all-cause mortality than the general population.1 NAFLD-related fibrosis is rising in the United States (US), which could increase all-cause mortality.2 Therefore, identifying individuals at risk of developing NAFLD and NAFLD-related fibrosis is essential for reducing the public health burden. Recommending lifestyle modification and early interventions in these high-risk populations might prevent the development of NAFLD and NAFLD-related fibrosis and reduce the burden of NAFLD-related morbidities and mortalities.

Obesity, a well-known risk factor for NAFLD and NAFLD-related fibrosis, is heterogeneous in the outcome because of the regional body fat distribution. Irrespective of the general obesity assessed by body mass index (BMI), body fat distribution is a significant risk factor for cardiometabolic abnormalities.3 BMI can not reflect the level and distribution of body fat. Regarding NAFLD, the results were inconsistent; some of the studies showed that visceral and subcutaneous fat correlate with NAFLD, whereas other studies showed that only visceral fat is associated with NAFLD.3 NAFLD-related fibrosis had a higher risk for all-cause mortality, and mortality risk increased as the fibrosis stage advanced.4 A study showed the independent association of visceral fat with significant fibrosis in patients with NAFLD.5 Above mentioned studies regarding this topic were limited by small sample sizes, specific race/ethnicity, and highly selected populations, which might account for the discrepant results. Not all individuals with obesity develop NAFLD and fibrosis, indicating that the role of obesity in the pathogenesis of NAFLD is complicated.6 Importantly, it was well-known that there were racial/ethnic differences in body fat distribution.7 For a given BMI, non-Hispanic Blacks have less body fat than non-Hispanic Whites, and non-Hispanic Asians have more body fat than non-Hispanic Whites.8 Therefore, we hypothesize that body fat distribution may impact NAFLD and significant fibrosis differently according to race/ethnicity. Few studies determined the association between body fat distribution and NAFLD and significant fibrosis based on diverse races/ethnicities. We evaluate the relationship between body fat distribution and NAFLD/significant fibrosis according to race/ethnicity in the US general population.

Subjects and study design

We analyzed the recent National Health and Nutrition Examination Survey (NHANES) 2017 to 2018 data, employing a multi-stage, clustered, and stratified probability sampling design to retrieve a nationally representative population of the US non-institutionalized civilians.9 The National Center for Health Statistics’ Institutional Review Board approved the original NHANES survey (Protocol #2011-2017 and #2018-01), and all participants reviewed and signed informed consent. Because the data used in the study was fully de-identified, this analysis was waived by Stanford University’s Institutional Review Board (IRB-57117).

A total of 2,740 adults (18 to 59 years of age) were examined for laboratory tests and dual-energy X-ray absorptiometry (DXA) at a mobile examination center. Among these, we excluded 494 participants with hepatitis C virus (by hepatitis C antibody), hepatitis B virus (by hepatitis B surface antigen), significant alcohol use (>20 g/day in women and >30 g/day in men), steatogenic medication for more than 6 months (corticosteroid, amiodarone, tamoxifen, valproate, and methotrexate), other races including multiracials, and/or those for whom data on BMI and/or transient elastography were not available. The final cohort consisted of 2,246 participants with complete data.

Clinical and laboratory evaluations

We used a previously described method.10 We defined race/ethnicity as non-Hispanic Whites, non-Hispanic Blacks, Hispanics, or non-Hispanic Asians. We defined marital status as marriage or living with a partner versus others. Educational status was dichotomized as high school graduation versus no high school graduation. We defined current smokers as individuals who reported ongoing current smoking among those who had smoked at least 100 cigarettes in their lifetime. We calculated alcohol consumption based on the amount and frequency of alcohol consumption using a self-reported questionnaire.11 We defined hypertension as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, and/or current treatment with anti-hypertensive medication. We defined diabetes as fasting plasma glucose levels ≥126 mg/dL, glycosylated hemoglobin ≥6.5%, and/or the use of hypoglycemic agents or insulin. We defined leisure-time physical activity according to the ‘2018 Physical Activity Guidelines for Americans’ (adults engaged in ≥150 minutes/week of moderate-intensity physical activity, 75 minutes/week of vigorous-intensity physical activity, or an equivalent combination).12

Definition of NAFLD and significant fibrosis

We used previously described methods for these definitions.13 Individuals were examined for liver stiffness measurement (LSM) and the controlled attenuation parameter (CAP) score by the Fibroscan 502 V2 Touch (Echosens).9 Incompleteness results for transient elastography were reported if they had stiffness interquartile range/median ≥30%, <10 complete LSMs, or fasted <3 hours.9 We defined NAFLD as CAP scores of 263 dB/m or more14 and significant fibrosis as LSM value of 8 kPa or higher15-17 without significant alcohol consumption, other causes of liver disease, and use of steatogenic medication.

Body fat measurements

The NHANES DXA whole-body scans provide nationally representative data on abdominal fat distribution for age, sex, and racial/ethnic groups.18 DXA whole-body scans were eligible for participants aged 8 to 59, excluding pregnancy, self-reported radiographic contrast (barium) use in the past 7 days, and measured weight over 204 kg or height over 1.98 m.18 The whole-body scans were examined using the Hologic Discovery model A densitometers software version APEX 3.2 (Hologic Inc.).18 Visceral and subcutaneous adipose tissue volumes were defined by the Hologic APEX version 4.0 software.18 The visceral fat volume inside the abdominal cavity and subcutaneous fat volume outside the abdominal cavity were measured at the approximate interspace of the L4 and L5 vertebra.18

Statistical analysis

We analyzed the data by applying appropriate sample weights, stratification, and clustering to retrieve representative population-level data for the entire US non-institutionalized civilians because of the complex survey design of the NHANES. The independent relationship between visceral or subcutaneous fat volumes and CAP score or LSM value was determined by multiple regression analysis and the determination of the standardized correlation coefficients. Based on the weighted sample distribution, we calculated the weighted mean and standard deviation (SD) of visceral fat volume and subcutaneous fat volume according to sex and race/ethnicity. The visceral and subcutaneous fat volumes were standardized to a mean of 0 and an SD of 1 based on sex and race/ethnicity. The tests for the odds ratios (OR) and significance of the differences among the visceral and subcutaneous fat volumes were performed to estimate the association between each type of fat and NAFLD/significant fibrosis. The OR per 1-SD was used to show the relative strength of the relationship across race/ethnicity. After adjusting for clinical and metabolic confounders, multivariable logistic regression was performed to investigate the independent association between body fat distribution and NAFLD and significant fibrosis. Using Taylor series linearization, we performed analyses using STATA version 17.0 (Stata Corp.).

Characteristics of the study population

As mentioned in the ‘Methods,’ this study enrolled 2,246 individuals, corresponding to 115.2 million US adults. The weighted prevalence of non-Hispanic Whites, non-Hispanic Blacks, Hispanics, and non-Hispanic Asians was 60.5% (95% confidence interval [CI], 54.5 to 66.2; 69.7 million), 12.6% (95% CI, 8.9 to 17.4; 14.5 million), 19.7% (95% CI, 14.4 to 26.4; 22.7 million), and 7.2% (95% CI, 5.1 to 10.1; 8 million), respectively. Supplementary Table 1 shows the study population’s baseline characteristics. Body fat distribution in men according to race/ethnicity was provided in Fig. 1. In men, visceral and subcutaneous fat volume among non-Hispanic Blacks was lowest compared to other races/ethnicities. Fig. 2 shows body fat distribution in women according to race/ethnicity. Visceral fat volume was lowest in non-Hispanic Asians and non-Hispanic Blacks in order compared with other races/ethnicities. However, subcutaneous fat volume was highest among non-Hispanic Blacks, who had the lowest visceral fat volume out of total fat volume and lowest among non-Hispanic Asians. Visceral fat volume was higher in men than women, while subcutaneous fat volume was higher in women than in men across the race/ethnicity.

Association between adipose tissue volume and NAFLD

Table 1 showed correlations adjusted for age and sex and additional variables between body fat distribution and CAP scores or LSM. Visceral and subcutaneous fat volumes were statistically correlated to CAP score in both models. Subcutaneous fat volume was more strongly correlated to CAP score in non-Hispanic Blacks than other races/ethnicities. In contrast, visceral and subcutaneous fat volumes showed weaker correlations to CAP scores in non-Hispanic Asians than in other racial/ethnic groups. As shown in Table 2, in the age and sex-adjusted models, the ORs for NAFLD per 1-SD of visceral fat volume and subcutaneous fat volume were 5.52 (95% CI, 3.69 to 8.26) and 4.05 (95% CI, 3.19 to 5.14), respectively. After further adjusting for education status, marital status, BMI, smoking status, diabetes, hypertension, leisure-time physical activity, total cholesterol, high-density lipoprotein-cholesterol, and total calorie intake, the OR for NAFLD per 1-SD in visceral fat volume and subcutaneous fat volume was 2.31 (95% CI, 1.50 to 3.39) and 1.93 (95% CI, 1.43 to 2.61), respectively. This association persisted after simultaneously adjusting for visceral and subcutaneous fat volume. Both visceral fat volume and subcutaneous fat volume were associated with NAFLD (OR per 1-SD of visceral fat volume, 2.05 [95% CI, 1.36 to 3.09]; and OR per 1-SD of subcutaneous fat volume, 1.48 [95% CI, 1.04 to 2.09]). When we performed similar analyses based on race/ethnicity, there were some differences in the impact of body fat distribution and NAFLD between race/ethnicity. In terms of the impact of visceral fat volume on NAFLD, non-Hispanic Blacks had the highest odds (OR, 2.86; 95% CI, 1.45 to 5.62), and non-Hispanic Whites (OR, 2.29; 95% CI, 1.19 to 4.40) and non-Hispanic Asians (OR, 1.61; 95% CI, 1.13 to 2.29) were in order. Although there was a significant association between subcutaneous fat volume and NAFLD in the total population, this association remained solely significant among non-Hispanic Blacks (OR, 1.55; 95% CI, 1.01 to 2.38).

Association between adipose tissue volume and significant fibrosis

Regarding LSM (Table 1), visceral and subcutaneous fat volumes were statistically correlated to LSM except for non-Hispanic Whites. Visceral fat volume presented the highest correlation coefficients for LSM in non-Hispanic Asians and non-Hispanic Blacks, whereas subcutaneous fat volume showed weaker correlations with LSM in Hispanic and non-Hispanic Asians.

As shown in Table 3, a significant association between visceral fat volume, not subcutaneous fat volume, and significant fibrosis was noted in the total population regardless of NAFLD status (OR per 1-SD of visceral fat volume, 1.37 [95% CI, 1.02 to 1.72; P=0.036]; and OR per 1-SD of subcutaneous fat volume, 1.53 [95% CI, 0.90 to 2.61; P=0.111]). When we performed analyses among individuals with NAFLD, we found significant associations between subcutaneous fat volume (OR, 2.10; 95% CI, 1.34 to 3.29; P=0.003) or visceral fat volume (OR, 1.35; 95% CI, 1.05 to 1.73; P=0.023) and significant fibrosis (Table 4). In terms of the impact of subcutaneous fat volume on significant fibrosis in NAFLD based on race/ethnicity, Hispanics had the highest odds (OR, 2.74; 95% CI, 1.32 to 5.70), and non-Hispanic Whites (OR, 2.35; 95% CI, 1.11 to 4.98) and non-Hispanic Asians (OR, 2.01; 95% CI, 1.01 to 4.01) were in order. Although there was a significant association between visceral fat volume and significant fibrosis in NAFLD, this estimate remained similar (24%–46% for each race/ethnicity vs. 35% for entire NAFLD) but non-significant across the race/ethnicity.

Using nationally representative data on abdominal fat distribution for age, sex, and racial/ethnic groups, we found that visceral adiposity was more strongly associated with NAFLD than subcutaneous adiposity across the various races/ethnicities. Evidence suggests that not all fat contributes to disease risk in NAFLD in the same way. Visceral abdominal fat is more harmful than subcutaneous fat because visceral fat cells release adipokines that contribute to cardiometabolic abnormalities, including NAFLD.19 Several mechanisms explain visceral adiposity’s metabolically adverse effects: (1) a more metabolically active endocrine organ and (2) increased amounts of free fatty acids reach the liver due to the anatomic location allowing direct access to the portal venous system.20

Although visceral adiposity was associated with significant fibrosis in the total population and individuals with NAFLD, we found no significant association between visceral adiposity and significant fibrosis across race and ethnicity. Because we used only one cycle of the NHANES 2017 to 2018 dataset, statistical power due to the small sample across race and ethnicity may diminish. The NHANES 2017 to 2020 dataset had a unique opportunity to determine NAFLD and fibrosis using transient elastography. However, visceral adipose tissue and subcutaneous adipose tissue defined by the DXA scan analysis were included only in the NHANES 2017 to 2018. Therefore, we were unable to combine other cycles to increase the statistical power. In addition, studies have found that the relative distribution of body fat varies across racial and ethnic groups, suggesting that this might explain differences in association with significant fibrosis across racial and ethnic groups. For example, the impact of visceral and subcutaneous adiposity on cardiometabolic health has been investigated, showing racial/ethnic differences in the associations.21-23 Subcutaneous abdominal fat in relation to cardiometabolic risk factors consistently follows similar patterns with visceral abdominal fat among some races/ethnicities, suggesting that subcutaneous abdominal fat is also associated with ethnic-specific cardiometabolic risk factors.23 Interestingly, we found that subcutaneous fat volume was more strongly associated with significant fibrosis than visceral fat volume in some races/ethnicities. Although explaining the mechanistic pathway between subcutaneous fat volume and significant fibrosis is challenging, there may be several explanations. First, a recent in vivo and ex vivo study showed the potential impact of subcutaneous abdominal adipose tissue inflammation and exosomes on the pathogenesis of insulin resistance among individuals with NAFLD.24 A statistically significant difference in subcutaneous abdominal adipose tissue immune cell populations and expression of most proinflammatory cytokines in people with NAFLD than those without NAFLD.24 Second, subcutaneous adipose tissue is divided into two layers: superficial and deep subcutaneous adipose tissue.25,26 Deep subcutaneous adipose tissue displayed an intermediate level of macrophage accumulation between superficial subcutaneous adipose tissue and visceral adipose tissue.25,26 Lipolysis, lipogenesis, and inflammatory protein expression rates are higher in deep subcutaneous adipose tissue than in superficial subcutaneous adipose tissue.26 Also, deep subcutaneous adipose tissue was associated with metabolic syndrome, increased inflammation, and oxidative stress, suggesting that deep subcutaneous adipose tissue may be an essential determinant of nonalcoholic steatohepatitis (NASH) and significant fibrosis. The abundance of macrophages in deep subcutaneous adipose tissue, but not in superficial subcutaneous adipose tissue, significantly increased among individuals with NASH and fibrosis with inflammation.25 In individuals with NASH, longitudinal reductions in deep subcutaneous adipose tissue and potentially visceral adipose tissue volumes related to histologic improvement, independent of reduction in hepatic steatosis.27 However, reduced superficial subcutaneous adipose tissue volume alone was not associated with histologic improvement in NASH.27 These findings suggest that deep subcutaneous adipose tissue might be associated with the exacerbation of NASH, including liver inflammation, hepatocellular ballooning, and fibrosis.27 Other studies have linked increased deep subcutaneous adipose tissue volume to altered insulin resistance,26,28 which accelerates the development of NASH.29 However, we were unable to determine deep or subcutaneous fat in our study, which was the limitation of our study. Third, subcutaneous fat is one of the main secretors of leptin, which was strongly correlated with NASH and significant fibrosis because leptin plays a role in regulating insulin levels.30 Fourth, if the subcutaneous fat stores become saturated and limited storage capacity of subcutaneous fat, ectopic fat accumulation arises in NAFLD.31 We hypothesize that additional ectopic fat accumulation resulted in significant fibrosis in NAFLD, which may already be full of visceral adiposity. An animal study reported that steatosis and diabetes develop secondary to a plateau in adipose expansion, suggesting limited adipose capacity.32 Future studies are needed to determine the mechanistic pathway between subcutaneous fat and significant fibrosis in NAFLD across races/ethnicities.

Emerging evidence suggests racial/ethnic differences in body fat distribution. Although non-Hispanic Blacks had lower total visceral fat compared with non-Hispanic Whites at a similar BMI, non-Hispanic Blacks had paradoxically similar hepatic insulin sensitivity33 and higher low-grade inflammatory markers, such as C-reactive protein and fibrinogen,34,35 which may contribute to the increased impact of visceral fat on NAFLD. Especially, subcutaneous adiposity was more strongly associated with insulin resistance in non-Hispanic Blacks, suggesting that overall body fatness remains important in developing NAFLD in non-Hispanic Blacks.35

In general, Asians have a higher percentage of visceral abdominal fat volume compared to Hispanics and Caucasians of the same age, sex, and BMI.36 In this respect, there appears to be a more significant percentage of individuals with metabolic abnormality but normal weight phenotype among Asians compared with their European counterparts,36 because BMI does not reflect regional body fat distribution. A recent study demonstrated a wide variation in the prevalence of metabolic abnormality but normal weight phenotype between major ethnic groups, with a rate of 21% in non-Hispanic Whites, 31% in non-Hispanic Blacks, 36% in Hispanics, 32% in Chinese Americans, and 44% in South Asians.37 Asians may have the most deleterious body fat distributions of all, with lower subcutaneous fat and higher visceral fat despite lower absolute BMIs.8,38 Impaired expansion of subcutaneous fat volume may predispose individuals to a metabolically unhealthy phenotype among Asians.39 A Korean longitudinal study showed that higher visceral adiposity at baseline was longitudinally associated with a higher incidence of NAFLD.40 Regarding the severity of NAFLD, a Korean study reported that visceral adiposity was independently associated with histology-confirmed NASH and significant fibrosis.5 Therefore, lifestyle modification to decrease visceral adiposity may help prevent the development of NAFLD and slow the progression of NAFLD-related fibrosis, especially in Asians.

Our study has several strengths. First, the NHANES provides nationally representative abdominal fat distribution data for age, sex, and racial/ethnic groups. Second, the NHANES’ clinical data were of high quality, i.e., measurements were taken by trained personnel using a standardized protocol. Third, we defined NAFLD and significant fibrosis by transient elastography, of which sufficient accuracy for detecting steatosis and fibrosis against biopsy has been reported.15 Therefore, our results could apply to clinical situations and be used to develop screening strategies in the US general population.

We acknowledge that this study has limitations. First, this cross-sectional analysis was unable to establish causality between body fat distribution and NAFLD. Second, we were unable to get liver histological samples, which is the gold standard for fibrosis. Third, no universal cut-off guideline for CAP score and LSM exists. However, we used the most validated cut-off point for CAP score and liver stiffness in several studies.15-17

In conclusion, we showed that visceral adiposity was more strongly associated with NAFLD than subcutaneous adiposity; non-Hispanic Blacks had the highest odds, and non-Hispanic Whites and non-Hispanic Asians were in order. There is a stronger significant association between subcutaneous fat and significant fibrosis in individuals with NAFLD than visceral fat. Our study suggests that subcutaneous fat is not protective but a risk factor for significant fibrosis in individuals with NAFLD, especially in Hispanics, non-Hispanic Whites, and non-Hispanic Asians. These data suggest that a certain type of body fat may be a risk factor for NAFLD, whereas other types may be a risk factor for NAFLD-associated significant fibrosis. In addition, there were racial/ethnic differences in the association between body fat distribution on NAFLD and significant fibrosis.

Study concept and design: DK and AA; acquisition of data: DK and AA; analysis and interpretation of data: DK, GC, and AA; drafting of the manuscript: DK; critical revision of the manuscript: DK, GC, and AA; statistical analysis: DK; administrative, technical, or material support: DK; and study supervision: DK and AA.

Fig. 1. Body fat distribution in men across the race/ethnicity. (A) Visceral fat volume (VFV) across the race/ethnicity. (B) Subcutaneous fat volume (SFV) across the race/ethnicity. (C) VFV/SFV. (D) VFV/total fat volume (TFV). NHW, non-Hispanic White; NHB, non-Hispanic Black; NHA, non- Hispanic Asian.
Fig. 2. Body fat distribution in women across the race/ethnicity. (A) Visceral fat volume (VFV) across the race/ethnicity. (B) Subcutaneous fat volume (SFV) across the race/ethnicity. (C) VFV/SFV. (D) VFV/total fat volume (TFV). NHW, non-Hispanic White; NHB, non-Hispanic Black; NHA, non- Hispanic Asian.

Age and sex-adjusted and multivariable-adjusted standardized correlation coefficients between body fat distribution and CAP score or LSM

Variable Total population Non-Hispanic White Non-Hispanic Black Hispanic Non-Hispanic Asian
CAP
VFV
Age and sex-adjusted 0.642* 0.660* 0.639* 0.613* 0.579*
Multivariable-adjusted 0.521* 0.541* 0.527* 0.505* 0.351*
SFV
Age and sex-adjusted 0.575* 0.592* 0.640* 0.544* 0.497*
Multivariable-adjusted 0.460* 0.457* 0.570* 0.470* 0.339*
LSM
VFV
Age and sex-adjusted 0.182* 0.169* 0.217* 0.254* 0.339*
Multivariable-adjusted 0.113* 0.075 0.230* 0.187* 0.232*
SFV
Age and sex-adjusted 0.264* 0.297* 0.222* 0.197* 0.239*
Multivariable-adjusted 0.252* 0.287* 0.263* 0.169* 0.173*

The multivariable model was adjusted for age, sex, smoking status, education status, marital status, diabetes, hypertension, leisure-time physical activity, total cholesterol, high-density lipoprotein-cholesterol, and total calorie intake (per day).

*P<0.01.

CAP, controlled attenuation parameter; LSM, liver stiffness measurement; VFV, visceral fat volume; SFV, subcutaneous fat volume.

Age and sex-adjusted and multivariable analyses of the risk for NAFLD

Variable Prevalence of NAFLD (%) Age and sex-adjusted model Multivariable model 1 Multivariable model 2
OR (95% CI) P OR (95% CI) P OR (95% CI) P
Total population (n = 2,246; weighted n= 115,246,070)
VFV (/1-SD) 42.8 (40.2–45.5) 5.52 (3.69–8.26) < 0.001 2.31 (1.50–3.39) < 0.001 2.05 (1.36–3.09) 0.002
SFV (/1-SD) 4.05 (3.19–5.14) < 0.001 1.93 (1.43–2.61) < 0.001 1.48 (1.04–2.09) 0.031
Non-Hispanic White (n = 715; weighted n= 69,721,997)
VFV (/1-SD) 42.2 (37.5–47.0) 5.96 (3.57–9.97) < 0.001 2.43 (1.28–4.61) 0.010 2.29 (1.19–4.40) 0.016
SFV (/1-SD) 4.56 (3.22–6.46) < 0.001 1.69 (0.90–3.16) 0.096 1.21 (0.65–2.25) 0.520
Non-Hispanic Black (n = 525; weighted n= 14,473,305)
VFV (/1-SD) 35.3 (31.3–39.5) 6.77 (4.34–10.57) < 0.001 3.08 (1.53–6.20) 0.004 2.86 (1.45–5.62) 0.005
SFV (/1-SD) 4.22 (3.42–5.20) < 0.001 1.95 (1.20–3.17) 0.011 1.55 (1.01–2.38) 0.045
Hispanic (n = 578; weighted n= 22,743,549)
VFV (/1-SD) 49.5 (45.5–53.4) 5.00 (2.55–9.83) < 0.001 2.46 (0.95–6.40) 0.063 1.78 (0.78–4.04) 0.153
SFV (/1-SD) 3.77 (2.23–6.38) < 0.001 2.82 (1.12–7.08) 0.030 2.23 (0.95–5.23) 0.063
Non-Hispanic Asian (n = 428; weighted n= 8,307,020)
VFV (/1-SD) 43.5 (36.6–50.7) 3.95 (2.91–5.38) < 0.001 1.87 (1.37–2.56) 0.001 1.61 (1.13–2.29) 0.012
SFV (/1-SD) 3.23 (2.52–4.15) < 0.001 1.89 (1.11–3.20) 0.023 1.56 (0.88–2.77) 0.116

The multivariable model 1 was adjusted for age, sex, body mass index, smoking status, education status, marital status, diabetes, hypertension, leisure- time physical activity, total cholesterol, high-density lipoprotein-cholesterol, and total calorie intake (per day). The multivariable model 2 includes visceral adipose tissue volume and subcutaneous adipose tissue volume in addition to the variables addressed in model 1.

NAFLD, nonalcoholic fatty liver disease; OR, odds ratio; CI, confidence interval; VFV, visceral fat volume; SD, standard deviation; SFV, subcutaneous fat volume.

Age and sex-adjusted and multivariable analyses of the risk for significant fibrosis in the total population

Variable Prevalence of significant fibrosis (%) Age and sex-adjusted model Multivariable model 1 Multivariable model 2
OR (95% CI) P OR (95% CI) P OR (95% CI) P
Total population (n = 2,246; weighted n= 115,246,070)
VFV (/1-SD) 5.5 (4.2–7.2) 2.03 (1.56–2.64) < 0.001 1.42 (1.07–2.87) 0.017 1.37 (1.02–1.72) 0.036
SFV (/1-SD) 1.98 (1.35–2.89) 0.002 1.59 (0.98–2.56) 0.059 1.53 (0.90–2.61) 0.111
Non-Hispanic White (n = 715; weighted n= 69,721,997)
VFV (/1-SD) 5.6 (4.0–7.8) 1.88 (1.25–2.83) 0.005 1.44 (0.77–2.69) 0.231 1.44 (0.79–2.62) 0.214
SFV (/1-SD) 1.69 (0.92–3.11) 0.086 1.29 (0.57–2.93) 0.517 1.29 (0.52–3.25) 0.560
Non-Hispanic Black (n = 525; weighted n= 14,473,305)
VFV (/1-SD) 4.7 (2.6–8.3) 1.90 (1.37–2.65) 0.001 1.14 (0.71–1.84) 0.561 1.11 (0.63–1.84) 0.697
SFV (/1-SD) 2.74 (1.69–4.46) 0.001 3.00 (1.17–7.70) 0.026 3.00 (1.13–7.82) 0.030
Hispanic (n = 578; weighted n= 22,743,549)
VFV (/1-SD) 6.4 (4.1–9.9) 2.57 (1.68–3.91) < 0.001 1.43 (0.82–2.50) 0.193 1.17 (0.71–1.82) 0.503
SFV (/1-SD) 2.80 (2.15–3.65) < 0.001 2.55 (1.31–4.93) 0.009 2.41 (1.35–4.33) 0.006
Non-Hispanic Asian (n = 428; weighted n= 8,307,020)
VFV (/1-SD) 4.1 (2.8–5.9) 1.98 (1.19–3.31) 0.013 1.56 (0.58–4.21) 0.342 1.30 (0.54–3.12) 0.530
SFV (/1-SD) 1.53 (1.00–2.35) 0.052 1.83 (0.73–4.63) 0.178 1.71 (0.72–4.03) 0.198

The multivariable model 1 was adjusted for age, sex, body mass index, smoking status, education status, marital status, diabetes, hypertension, leisure- time physical activity, total cholesterol, high-density lipoprotein-cholesterol, and total calorie intake (per day). The multivariable model 2 includes visceral adipose tissue volume and subcutaneous adipose tissue volume in addition to the variables addressed in model 1.

OR, odds ratio; CI, confidence interval; VFV, visceral fat volume; SD, standard deviation; SFV, subcutaneous fat volume.

Age and sex-adjusted and multivariable analyses of the risk for significant fibrosis among individuals with NAFLD

Variable Prevalence of significant fibrosis (%) Age and sex-adjusted model Multivariable model 1 Multivariable model 2
OR (95% CI) P OR (95% CI) P OR (95% CI) P
Total population (n = 987; weighted n= 49,354,065)
VFV (/1-SD) 9.1 (6.8–12.2) 2.13 (1.68–2.71) < 0.001 1.36 (1.05–1.76) 0.023 1.35 (1.05–1.73) 0.023
SFV (/1-SD) 2.63 (1.79–3.86) < 0.001 2.10 (1.36–3.25) 0.002 2.10 (1.34–3.29) 0.003
Non-Hispanic White (n = 313; weighted n= 29,396,675)
VFV (/1-SD) 8.7 (6.0–12.5) 2.11 (1.48–3.01) < 0.001 1.33 (0.77–2.30) 0.279 1.46 (0.93–2.29) 0.091
SFV (/1-SD) 2.87 (1.60–5.14) 0.002 2.20 (1.02–4.73) 0.045 2.35 (1.11–4.98) 0.028
Non-Hispanic Black (n = 195; weighted n= 5,093,467)
VFV (/1-SD) 7.9 (4.0–14.9) 2.29 (1.58–3.30) < 0.001 1.38 (0.80–2.36) 0.222 1.39 (0.77–2.52) 0.249
SFV (/1-SD) 5.31 (1.82–15.49) 0.006 1.73 (0.42–7.04) 0.409 1.82 (0.35–9.58) 0.442
Hispanic (n = 293; weighted n= 11,251,161)
VFV (/1-SD) 11.4 (6.6–19.0) 2.48 (1.27–4.83) 0.011 1.46 (0.82–2.62) 0.180 1.24 (0.81–1.89) 0.281
SFV (/1-SD) 2.54 (1.71–3.77) < 0.001 2.86 (1.33–6.15) 0.011 2.74 (1.32–5.70) 0.011
Non-Hispanic Asian (n = 186; weighted n= 3,612,762)
VFV (/1-SD) 7.8 (5.7–10.5) 1.71 (1.02–2.87) 0.043 1.62 (0.75–3.51) 0.190 1.29 (0.60–2.76) 0.467
SFV (/1-SD) 1.28 (0.78–2.09) 0.282 2.15 (1.07–4.29) 0.034 2.01 (1.01–4.01) 0.049

The multivariable model 1 was adjusted for age, sex, body mass index, smoking status, education status, marital status, diabetes, hypertension, leisure- time physical activity, total cholesterol, high-density lipoprotein-cholesterol, and total calorie intake (per day). The multivariable model 2 includes visceral adipose tissue volume and subcutaneous adipose tissue volume in addition to the variables addressed in model 1.

NAFLD, nonalcoholic fatty liver disease; OR, odds ratio; CI, confidence interval; VFV, visceral fat volume; SD, standard deviation; SFV, subcutaneous fat volume.

  1. Chan WK, Chuah KH, Rajaram RB, Lim LL, Ratnasingam J, Vethakkan SR. Metabolic dysfunction-associated steatotic liver disease (MASLD): a state-of-the-art review. J Obes Metab Syndr 2023;32:197-213.
    Pubmed KoreaMed CrossRef
  2. Konyn P, Ahmed A, Kim D. Causes and risk profiles of mortality among individuals with nonalcoholic fatty liver disease. Clin Mol Hepatol 2023;29(Suppl):S43-57.
    Pubmed KoreaMed CrossRef
  3. Wijarnpreecha K, Ahmed A, Kim D. Body fat distribution: a crucial target for intervention in nonalcoholic fatty liver disease and fibrosis. Hepatobiliary Surg Nutr 2022;11:738-42.
    Pubmed KoreaMed CrossRef
  4. Kim D, Kim WR, Kim HJ, Therneau TM. Association between noninvasive fibrosis markers and mortality among adults with nonalcoholic fatty liver disease in the United States. Hepatology 2013;57:1357-65.
    Pubmed KoreaMed CrossRef
  5. Yu SJ, Kim W, Kim D, Yoon JH, Lee K, Kim JH, et al. Visceral obesity predicts significant fibrosis in patients with nonalcoholic fatty liver disease. Medicine (Baltimore) 2015;94:e2159.
    Pubmed KoreaMed CrossRef
  6. Thörne A, Löfgren P, Hoffstedt J. Increased visceral adipocyte lipolysis: a pathogenic role in nonalcoholic fatty liver disease? J Clin Endocrinol Metab 2010;95:E209-13.
    Pubmed CrossRef
  7. Carroll JF, Chiapa AL, Rodriquez M, Phelps DR, Cardarelli KM, Vishwanatha JK, et al. Visceral fat, waist circumference, and BMI: impact of race/ethnicity. Obesity (Silver Spring) 2008;16:600-7.
    Pubmed CrossRef
  8. Nazare JA, Smith JD, Borel AL, Haffner SM, Balkau B, Ross R, et al. Ethnic influences on the relations between abdominal subcutaneous and visceral adiposity, liver fat, and cardiometabolic risk profile: the international study of prediction of intra-abdominal adiposity and its relationship with cardiometabolic risk/intra-abdominal adiposity. Am J Clin Nutr 2012;96:714-26.
    Pubmed CrossRef
  9. National Health and Nutrition Examination Survey: liver ultrasound transient elastography procedures manual [Internet]. Centers for Disease Control and Prevention; 2018 [cited 2024 Oct 21]. Available from: https://wwwn.cdc.gov/nchs/data/nhanes/2017-2018/manuals/2018_Liver_Ultrasound_Elastography_Procedures_Manual.pdf.
  10. Kim D, Vazquez-Montesino LM, Li AA, Cholankeril G, Ahmed A. Inadequate physical activity and sedentary behavior are independent predictors of nonalcoholic fatty liver disease. Hepatology 2020;72:1556-68.
    Pubmed CrossRef
  11. Ruhl CE, Everhart JE. Joint effects of body weight and alcohol on elevated serum alanine aminotransferase in the United States population. Clin Gastroenterol Hepatol 2005;3:1260-8.
    Pubmed CrossRef
  12. Piercy KL, Troiano RP, Ballard RM, Carlson SA, Fulton JE, Galuska DA, et al. The physical activity guidelines for Americans. JAMA 2018;320:2020-8.
    Pubmed KoreaMed CrossRef
  13. Kim D, Cholankeril G, Loomba R, Ahmed A. Prevalence of fatty liver disease and fibrosis detected by transient elastography in adults in the United States, 2017-2018. Clin Gastroenterol Hepatol 2021;19:1499-501.e2.
    Pubmed CrossRef
  14. Siddiqui MS, Vuppalanchi R, Van Natta ML, Hallinan E, Kowdley KV, Abdelmalek M, et al. Vibration-controlled transient elastography to assess fibrosis and steatosis in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol 2019;17:156-63.e2.
    Pubmed KoreaMed CrossRef
  15. Castera L, Friedrich-Rust M, Loomba R. Noninvasive assessment of liver disease in patients with nonalcoholic fatty liver disease. Gastroenterology 2019;156:1264-81.e4.
    Pubmed KoreaMed CrossRef
  16. Abeysekera KW, Fernandes GS, Hammerton G, Portal AJ, Gordon FH, Heron J, et al. Prevalence of steatosis and fibrosis in young adults in the UK: a population-based study. Lancet Gastroenterol Hepatol 2020;5:295-305.
    Pubmed CrossRef
  17. Eddowes PJ, Sasso M, Allison M, Tsochatzis E, Anstee QM, Sheridan D, et al. Accuracy of fibroscan controlled attenuation parameter and liver stiffness measurement in assessing steatosis and fibrosis in patients with nonalcoholic fatty liver disease. Gastroenterology 2019;156:1717-30.
    Pubmed CrossRef
  18. National Health and Nutrition Examination Survey: 2017-2018 data documentation, codebook, and frequencies. Dual-energy X-ray absorptiometry: whole body [Internet]. Centers for Disease Control and Prevention; 2021 [cited 2024 Oct 21]. Available from: https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/DXXAG_J.htm.
  19. Vilalta A, Gutiérrez JA, Chaves S, Hernández M, Urbina S, Hompesch M. Adipose tissue measurement in clinical research for obesity, type 2 diabetes and NAFLD/NASH. Endocrinol Diabetes Metab 2022;5:e00335.
    Pubmed KoreaMed CrossRef
  20. Meng K, Lee CH, Saremi F. Metabolic syndrome and ectopic fat deposition: what can CT and MR provide?. Acad Radiol 2010;17:1302-12.
    Pubmed CrossRef
  21. Després JP, Couillard C, Gagnon J, Bergeron J, Leon AS, Rao DC, et al. Race, visceral adipose tissue, plasma lipids, and lipoprotein lipase activity in men and women: the health, risk factors, exercise training, and genetics (HERITAGE) family study. Arterioscler Thromb Vasc Biol 2000;20:1932-8.
    Pubmed CrossRef
  22. Lesser IA, Gasevic D, Lear SA. The effect of body fat distribution on ethnic differences in cardiometabolic risk factors of Chinese and Europeans. Appl Physiol Nutr Metab 2013;38:701-6.
    Pubmed CrossRef
  23. Liu J, Coady S, Carr JJ, Hoffmann U, Taylor HA, Fox CS. Differential associations of abdominal visceral, subcutaneous adipose tissue with cardiometabolic risk factors between African and European Americans. Obesity (Silver Spring) 2014;22:811-8.
    Pubmed KoreaMed CrossRef
  24. Fuchs A, Samovski D, Smith GI, Cifarelli V, Farabi SS, Yoshino J, et al. Associations among adipose tissue immunology, inflammation, exosomes and insulin sensitivity in people with obesity and nonalcoholic fatty liver disease. Gastroenterology 2021;161:968-81.e12.
    Pubmed KoreaMed CrossRef
  25. Tordjman J, Divoux A, Prifti E, Poitou C, Pelloux V, Hugol D, et al. Structural and inflammatory heterogeneity in subcutaneous adipose tissue: relation with liver histopathology in morbid obesity. J Hepatol 2012;56:1152-8.
    Pubmed CrossRef
  26. Kim SH, Chung JH, Song SW, Jung WS, Lee YA, Kim HN. Relationship between deep subcutaneous abdominal adipose tissue and metabolic syndrome: a case control study. Diabetol Metab Syndr 2016;8:10.
    Pubmed KoreaMed CrossRef
  27. Shen W, Middleton MS, Cunha GM, Delgado TI, Wolfson T, Gamst A, et al. Changes in abdominal adipose tissue depots assessed by MRI correlate with hepatic histologic improvement in non-alcoholic steatohepatitis. J Hepatol 2023;78:238-46.
    Pubmed KoreaMed CrossRef
  28. Bódis K, Jelenik T, Lundbom J, Markgraf DF, Strom A, Zaharia OP, et al. Expansion and impaired mitochondrial efficiency of deep subcutaneous adipose tissue in recent-onset type 2 diabetes. J Clin Endocrinol Metab 2020;105:e1331-43.
    Pubmed KoreaMed CrossRef
  29. Ota T, Takamura T, Kurita S, Matsuzawa N, Kita Y, Uno M, et al. Insulin resistance accelerates a dietary rat model of nonalcoholic steatohepatitis. Gastroenterology 2007;132:282-93.
    Pubmed CrossRef
  30. Uygun A, Kadayifci A, Yesilova Z, Erdil A, Yaman H, Saka M, et al. Serum leptin levels in patients with nonalcoholic steatohepatitis. Am J Gastroenterol 2000;95:3584-9.
    Pubmed CrossRef
  31. Larter CZ, Chitturi S, Heydet D, Farrell GC. A fresh look at NASH pathogenesis. Part 1: the metabolic movers. J Gastroenterol Hepatol 2010;25:672-90.
    Pubmed CrossRef
  32. Larter CZ, Yeh MM, Van Rooyen DM, Teoh NC, Brooling J, Hou JY, et al. Roles of adipose restriction and metabolic factors in progression of steatosis to steatohepatitis in obese, diabetic mice. J Gastroenterol Hepatol 2009;24:1658-68.
    Pubmed CrossRef
  33. Reed RM, Nevitt SJ, Kemp GJ, Cuthbertson DJ, Whyte MB, Goff LM. Ectopic fat deposition in populations of Black African ancestry: a systematic review and meta-analysis. Acta Diabetol 2022;59:171-87.
    Pubmed KoreaMed CrossRef
  34. Wee CC, Mukamal KJ, Huang A, Davis RB, McCarthy EP, Mittleman MA. Obesity and C-reactive protein levels among White, Black, and Hispanic US adults. Obesity (Silver Spring) 2008;16:875-80.
    Pubmed KoreaMed CrossRef
  35. Carroll JF, Fulda KG, Chiapa AL, Rodriquez M, Phelps DR, Cardarelli KM, et al. Impact of race/ethnicity on the relationship between visceral fat and inflammatory biomarkers. Obesity (Silver Spring) 2009;17:1420-7.
    Pubmed CrossRef
  36. Farrell GC, Chitturi S, Lau GK, Sollano JD; Asia-Pacific Working Party on NAFLD. Guidelines for the assessment and management of non-alcoholic fatty liver disease in the Asia-Pacific region: executive summary. J Gastroenterol Hepatol 2007;22:775-7.
    Pubmed CrossRef
  37. Gujral UP, Vittinghoff E, Mongraw-Chaffin M, Vaidya D, Kandula NR, Allison M, et al. Cardiometabolic abnormalities among normal-weight persons from five racial/ethnic groups in the United States: a cross-sectional analysis of two cohort studies. Ann Intern Med 2017;166:628-36.
    Pubmed KoreaMed CrossRef
  38. Jeong SM, Jung JH, Yang YS, Kim W, Cho IY, Lee YB, et al. 2023 Obesity fact sheet: prevalence of obesity and abdominal obesity in adults, adolescents, and children in Korea from 2012 to 2021. J Obes Metab Syndr 2024;33:27-35.
    Pubmed KoreaMed CrossRef
  39. Stefan N, Häring HU, Schulze MB. Metabolically healthy obesity: the low-hanging fruit in obesity treatment?. Lancet Diabetes Endocrinol 2018;6:249-58.
    Pubmed CrossRef
  40. Kim D, Chung GE, Kwak MS, Seo HB, Kang JH, Kim W, et al. Body fat distribution and risk of incident and regressed nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol 2016;14:132-8.e4.
    Pubmed CrossRef