ABSTRACT
Background/Aims
Benefits of the Mediterranean diet (MD) in reducing hepatic steatosis among individuals with metabolic dysfunction–associated steatotic liver disease (MASLD) have been well established. This study aims to evaluate the relationship between MD adherence and liver fibrosis among the MASLD population.
Methods
This cross‐sectional study analyzed data from the National Health and Nutrition Examination Survey 2017 to March 2020. Individuals with MASLD were identified based on the vibration‐controlled transient elastography–defined steatosis. Participants' MD adherence was evaluated using the alternate Mediterranean diet (aMED) score, with higher scores indicating greater adherence. Risk of significant liver fibrosis was compared between low, moderate, and high aMED groups.
Results
Of 2672 MASLD participants, 27.2%, 42.3%, and 30.6% were categorized into low, moderate, and high aMED groups, respectively. After adjusting for the number of cardiometabolic risk factors (CMRFs), physical activity, and other covariates, participants in the high aMED group were associated with a lower risk of significant liver fibrosis compared with those in the low aMED group (aMED 5–9 vs. aMED 0–2: OR = 0.662, 95% confidence interval [CI]: 0.660–0.663; p for trend < 0.0001). In the sensitivity analyses, the protective association of higher MD adherence against the risk of significant liver fibrosis weakened with higher cardiometabolic burden (aMED 5–9: aOR 0.582, 95% CI: 0.580–0.584 [4–5 CMRFs] vs. aOR 0.383, 95% CI: 0.380–0.386 [1 CMRF]).
Conclusions
In MASLD patients, higher MD adherence was associated with lower risk of significant liver fibrosis. Our findings support the recommendation of the MD as a crucial lifestyle intervention to lower the risk of liver fibrosis in this population.
Keywords: liver fibrosis, Mediterranean diet, metabolic dysfunction–associated steatotic liver disease, National Health and Nutrition Examination Survey, vibration‐controlled transient elastography
Abbreviations
- AASLD
American Association for the Study of Liver Diseases
- aMED
alternate Mediterranean diet
- ANOVA
analysis of variance
- AUROC
area under the receiver operating characteristic curve
- BMI
body mass index
- CAP
controlled attenuation parameter
- CI
confidence interval
- CMRF
cardiometabolic risk factor
- EASD
European Association for the Study of Diabetes
- EASL
European Association for the Study of the Liver
- EASO
European Association for the Study of Obesity
- FIB‐4
fibrosis‐4
- HBV
hepatitis B virus
- HCC
hepatocellular carcinoma
- HCV
hepatitis C virus
- LSM
liver stiffness measurement
- MASLD
metabolic dysfunction–associated steatotic liver disease
- MD
Mediterranean diet
- MET
metabolic equivalent
- NHANES
National Health and Nutrition Examination Survey
- OR
odds ratio
- RCT
randomized controlled trial
- SLD
steatotic liver disease
- SMD
standardized mean difference
- TE
transient elastography
- VCTE
vibration‐controlled transient elastography
1. Introduction
Global prevalence of metabolic dysfunction–associated steatotic liver disease (MASLD) has reached over 30% in the past decade [1, 2]. The Global Burden of Disease studies revealed an increasing proportion of MASLD‐related hepatocellular carcinoma (HCC) [3, 4], with this trend being particularly alarming in developed countries [5, 6]. MASLD, the new nomenclature, replaces the stigmatizing term “nonalcoholic fatty liver disease” while highlighting the role of metabolic dysfunction and providing a more accurate representation of the disease's clinical characteristics [7]. Individuals with MASLD are at elevated risk for not only HCC but also significant liver fibrosis, cirrhosis, and liver‐related mortality. Among these, liver fibrosis has been identified as the strongest predictor of both HCC development and liver‐related mortality [8, 9]. Moreover, past evidence suggests that HCC may develop at an earlier stage of fibrosis in MASLD compared with other etiologies of liver diseases [10].
To improve liver injury in MASLD management, the Mediterranean diet (MD) was listed as a key nonpharmacological approach in the recently updated global consensus recommendations [11], European Association for the Study of the Liver–European Association for the Study of Diabetes–European Association for the Study of Obesity (EASL–EASD–EASO) and American Association for the Study of Liver Diseases (AASLD) practice guidelines [12, 13]. The MD is considered a healthy dietary pattern, rich in plant‐based foods like vegetables and legumes, monounsaturated fats, and omega‐3 fatty acids—such as those found in fish—with a relatively low proportion of red and processed meats. This dietary pattern was recommended by the American Heart Association [14] and European Society of Cardiology guidelines for its advantages in reducing cardiovascular‐related and all‐cause mortality [15]. It has also shown benefits in the management of cardiovascular diseases, metabolic syndrome, and type 2 diabetes.
For liver‐related diseases, a systematic review and meta‐analysis of six randomized controlled trials (RCTs) found that MD improved hepatic steatosis in individuals with MASLD, based on tests like fatty liver index, magnetic resonance imaging, and liver biopsy [16]. Similarly, another RCT demonstrated the positive effect of MD on hepatic steatosis in MASLD patients but found no significant improvement in liver stiffness [17]. A meta‐analysis of 10 RCTs also did not detect a significant influence of MD on improving liver stiffness [18]. Conversely, an earlier systematic review showed a marginal reduction in liver stiffness for patients undergoing MD [19]. The current evidence of MD on liver fibrosis has been inconsistent. Because hepatic steatosis plays a key role in fibrogenesis among the MASLD population, we hypothesized that improving liver steatosis may also be associated with the alleviation of fibrosis [20]. Thus, the aim of this study was to evaluate the link between MD adherence and liver fibrosis in a MASLD population.
2. Materials and Methods
2.1. Data Source and Study Population
For this cross‐sectional analysis, we used the nationally representative National Health and Nutrition Examination Survey (NHANES) data from 2017 to March 2020 to retrospectively identify individuals aged 18 or above who met the diagnostic criteria of MASLD from a total of 15 560 participants [7]. The NHANES is a population‐based survey conducted in the United States that gathers extensive health and nutrition information through health examinations, laboratory tests, and dietary interviews. Data collected during this cycle incorporated vibration‐controlled transient elastography (VCTE) measurement, which is a well‐validated method for detecting both hepatic steatosis and fibrosis; it boasts AUROCs exceeding 0.8 for detecting significant fibrosis and controlled attenuation parameter (CAP) for identifying steatosis [21, 22]. Only participants with complete dietary, alcohol use, and VCTE data (e.g., 10 valid measurements with an IQR/M ratio less than 30%) were included in the study.
A CAP of ≥ 275 dB/m was used to define liver steatosis [23]. Cardiometabolic risk factors (CMRFs) were specified using the following criteria: (1) body mass index (BMI) ≥ 25 kg/m2 (≥ 23 kg/m2 in Asians) or waist circumference ≥ 94 cm in men or ≥ 80 cm in women; (2) fasting serum glucose ≥ 100 mg/dL or hemoglobin A1c level ≥ 5.7% or receiving treatment for type 2 diabetes; (3) blood pressure ≥ 130/85 mmHg or receiving antihypertensive treatment; (4) plasma triglyceride level ≥ 150 mg/dL or receiving lipid‐lowering treatment; (5) plasma high‐density lipoprotein–cholesterol ≤ 40 mg/dL for men and ≤ 50 mg/dL for women or receiving lipid‐lowering treatment [7].
Individuals who met the criteria for MASLD—evidence of liver steatosis, at least one CMRF, and alcohol consumption below 30 g/day for men and 20 g/day for women—comprised our study population (n = 2672). Participants were excluded if they were under 18 years of age, lacked valid CAP measurements, had incomplete nutrient or alcohol consumption data, or did not fulfill the consensus criteria for MASLD. Detailed laboratory protocols and reference ranges for NHANES datasets are publicly available for review [24].
2.2. Mediterranean Diet Evaluation
Adherence to the MD was evaluated using the alternate Mediterranean diet (aMED) score, which ranges from 0 to 9, with 9 representing maximal adherence [25, 26]. The aMED score has been widely utilized in previous NHANES‐based studies to investigate relationships between dietary habit changes and various clinical outcomes, including metabolic disorders, cardiovascular diseases, and cancer risks in the US population [27, 28, 29, 30]. Dietary data were collected by trained interviewers who completed an intensive 1‐week training course and supervised practice interviews prior to working independently. Annual retraining sessions were conducted to maintain protocol standards. Based on these data, two experienced researchers calculated the aMED score using the two 24‐h dietary recall data points and linkage to the United States Department of Agriculture Food Patterns Equivalents Database, focusing on nine specific dietary components.
Participants with higher than median consumption of whole fruits, vegetables, whole grain products, legumes, nuts, and fish, as well as a higher ratio of monounsaturated to saturated fats, received 1 point for each of these components. Conversely, participants whose red and processed meat intake was below the median value also received 1 point.
For alcohol consumption, those with an intake between 5 and 25 g per day for males and 5 and 15 g per day for females were assigned 1 point [27]. The aMED score, calculated as the sum of the points from all nine components, was categorized into three tertiles representing low (scores 0–2), moderate (scores 3–4), and high (scores 5–9) adherence to the MD [31].
2.3. Covariates of Interest
There were other variables considered in the analyses: age at time of screening, sex, laboratory data relevant to liver disease, hepatitis B virus (HBV) exposure, hepatitis C virus (HCV) infection, number of CMRFs, physical activity, current smoking, and alcohol consumption.
Laboratory data relevant to liver disease included aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin, albumin, creatinine, and platelet count. To assess HBV status, we utilized anti‐HBc serostatus as a marker of prior exposure. This approach was chosen over defining chronic infection with HBsAg due to the high proportion of missing HBsAg data in the NHANES 2017–March 2020 dataset. Regarding HCV, active infection was defined as the presence of detectable HCV RNA following a positive anti‐HCV screening result.
The number of CMRFs was calculated for each participant based on the total number of conditions they met for each of the 5 CMRFs mentioned previously when identifying our study population.
Total weekly metabolic equivalent (MET) hours were estimated to represent physical activity level. This measure was calculated by multiplying the frequency (days), duration (average time), and intensity (MET score) of activities at different levels and summing the results. Based on the distribution of these MET hours, participants were grouped into tertiles (T): T1 (0–12 MET hours/week), T2 (13–68 MET hours/week), and T3 (> 68 MET hours/week).
Participants were classified as a current smoker if they reported smoking cigarettes every day or some days now and smoked at least 100 cigarettes in their life. A noncurrent smoker was someone who reported they do not smoke at all now. The “never smoked” classification was defined as those who had never smoked a whole cigarette in their entire life, but no participants met this criterion in the study. Individuals who reported “a quit attempt in the past 12 months” were initially identified but were subsequently reclassified as current smokers upon confirming they had resumed smoking. It is important to note that a large portion of the cigarette use data are missing because participants who were subject to a skip pattern were coded as missing in the questionnaire.
Alcohol consumption data, including weekly drinking frequency and the number of drinks per occasion in the 12 months prior to the survey, were extracted from the self‐report questionnaire. To standardize consumption, one drink was defined as 14 g of alcohol (equivalent to 12‐oz beer, 5‐oz wine, or 1.5‐oz liquor). For the analysis, we converted the reported average weekly drinks into daily gram intake of alcohol.
2.4. Study Outcome
The main outcome of the study is the presence of significant liver fibrosis, which was defined as liver stiffness measurement (LSM) of 8 kPa or higher by VCTE.
2.5. Statistical Analyses
Descriptive statistics were evaluated using one‐way ANOVA for continuous variables and the Chi‐square test for categorical variables. The association between MD adherence and significant liver fibrosis was assessed using logistic regression models in both crude and adjusted analyses. Multicollinearity was tested for all the variables before placing them in the multivariate analyses. In the multivariate model, the aMED score, number of CMRFs, physical activity, age, sex, current smoking status, and alcohol intake were adjusted. To test the robustness of our results, sensitivity analysis was performed with varying levels of CMRFs. NHANES sample weights (Mobile Exam Center exam weight, 2‐day dietary recall data weight, and fasting sample weight) were incorporated in all analyses of this study wherever appropriate.
Odds ratios (ORs) and confidence intervals (CIs) were estimated for the risk of outcome using logistic regression models. Two‐sided statistical tests were used with a significance level of 0.05. All statistical analyses were conducted using SAS version 9.4 (SAS Institute, Cary, North Carolina). The NHANES 2017–2020 study protocol was approved by the National Center for Health Statistics (NCHS) Ethics Review Board (Protocol #2018‐01) to ensure protections of all human participants [32].
3. Results
During the study period from 2017 to prepandemic March 2020, the NHANES database included 15 560 interviewed participants. Of these, 9693 were aged 18 years or older, 8317 had CAP measurement data, and 6688 had complete nutrient and alcohol data. These participants were categorized into two groups: steatotic liver disease (SLD) (n = 2888) and non‐SLD (n = 3800). Among those with SLD, 2870 (99.4%) presented with at least one CMRF, and 2672 of these were classified as MASLD individuals by the amount of alcohol consumption, who are the subjects of this study (Figure 1).
FIGURE 1.
Subject selection flowchart. Abbreviations: ALD, alcohol‐related liver disease; CAP, controlled attenuation parameter; CMRF, cardiometabolic risk factor; MASLD, metabolic dysfunction–associated steatotic liver disease; MetALD, MASLD and excessive alcohol intake; NHANES, National Health and Nutrition Examination Survey; SLD, steatotic liver disease. MASLD was defined with a CAP ≧ 275 dB/m and with presence of any CMRFs.
3.1. Distribution of Clinical Parameters According to MD Adherence
Of 2672 participants with MASLD, 27.2% (n = 726), 42.3% (n = 1129), and 30.6% (n = 817) were categorized into the low (aMed: 0–2), moderate (aMed: 3–4), and high (aMED: 5–9) MD adherence groups, respectively. After stratifying MASLD subjects by their aMED score, we observed notable differences in age, BMI, current smoking status, alcohol intake, and HCV status across the three aMED groups (Table 1) (Table S1). Mean age significantly increased with higher levels of MD adherence (p < 0.0001), while BMI and the proportion of current smokers significantly decreased (p < 0.01). Although daily alcohol intake increased with higher diet adherence, the mean intake remained within an acceptable range (5.00 ± 0.44 g/day for the aMED 5–9 group). Furthermore, the lowest CAP measurement was observed in the group with the highest aMED score (320.1 ± 2.06 dB/m for aMED 5–9 vs. 326.6 ± 2.06 dB/m for aMED 3–4 and 324.7 ± 2.52 dB/m for aMED 0–2); however, this difference did not reach statistical significance (p = 0.08). The distribution of other potential risk factors, including physical activity, type 2 diabetes, hypertension, dyslipidemia, number of CMRFs, and HBV, did not differ significantly among the three adherence groups. Although the number of positive cases was very low, the proportion of HCV RNA positivity was higher in the low aMED group (aMED 0–2: n = 7, 1.8%; aMED 3–4: n = 4, 0.2%; and aMED 5–9: n = 2, 0.2%; p = 0.0002) (Table 1).
TABLE 1.
Demographic and health characteristics of study subjects by aMED score.
| aMED Score | |||||
|---|---|---|---|---|---|
| All (n = 2672) | 0–2 (n = 726) | 3–4 (n = 1129) | 5–9 (n = 817) | p | |
| n (%), mean (SD) | n (%), mean (SD) | n (%), mean (SD) | n (%), mean (SD) | ||
| Age, year | 50.8 (0.44) | 47.7 (1.04) | 51.3 (0.75) | 54.5 (0.92) | < 0.0001 |
| Sex | 0.22 | ||||
| Male | 1492 (56.4) | 414 (55.5) | 638 (59.3) | 440 (53.3) | |
| Female | 1180 (43.6) | 312 (44.5) | 491 (40.7) | 377 (46.7) | |
| BMI (kg/m2) | 34.3 (0.20) | 34.8 (0.47) | 34.3 (0.37) | 33.0 (0.38) | 0.004 |
| Current smoker (past 12 months) | < 0.0001 | ||||
| No | 797 (68.6) | 203 (54.9) | 344 (72.8) | 250 (80.7) | |
| Yes | 409 (31.4) | 171 (45.1) | 159 (27.2) | 79 (19.3) | |
| Missing | 1466 | ||||
| Alcohol (g/day) | 3.59 (0.18) | 3.29 (0.48) | 3.11 (0.28) | 5.00 (0.44) | 0.001 |
| Physical activity | 0.73 | ||||
| T1 | 1158 (41.2) | 317 (40.2) | 473 (41.0) | 368 (42.3) | |
| T2 | 756 (28.5) | 197 (27.9) | 310 (27.7) | 249 (30.3) | |
| T3 | 758 (30.3) | 212 (31.8) | 346 (31.3) | 200 (27.4) | |
| Type 2 diabetes | 0.20 | ||||
| No | 1898 (75.5) | 536 (78.9) | 801 (74.5) | 561 (73.6) | |
| Yes | 774 (24.5) | 190 (21.1) | 328 (25.5) | 256 (26.4) | |
| Hypertension | 0.50 | ||||
| No | 1104 (44.7) | 321 (46.9) | 450 (42.8) | 333 (45.0) | |
| Yes | 1568 (55.3) | 405 (53.1) | 679 (57.2) | 484 (55.0) | |
| Dyslipidemia | 0.25 | ||||
| No | 1741 (67.4) | 488 (69.6) | 748 (68.3) | 505 (64.0) | |
| Yes | 931 (32.6) | 238 (30.4) | 381 (31.7) | 312 (36.0) | |
| Number of CMRFs | 0.55 | ||||
| 1 | 249 (11.0) | 84 (13.4) | 89 (9.6) | 76 (10.6) | |
| 2 | 579 (23.5) | 154 (22.9) | 249 (22.7) | 176 (25.3) | |
| 3 | 696 (26.4) | 189 (27.5) | 309 (27.1) | 198 (24.4) | |
| 4–5 | 1148 (39.0) | 299 (36.2) | 482 (40.6) | 367 (39.8) | |
| Laboratory data | |||||
| ALT (U/L) | 27.1 (0.51) | 26.7 (1.21) | 27.3 (0.85) | 26.6 (0.96) | 0.82 |
| AST (U/L) | 22.6 (0.30) | 22.7 (0.87) | 22.5 (0.44) | 23.1 (0.57) | 0.75 |
| Total bilirubin (mg/dL) | 0.46 (0.01) | 0.46 (0.03) | 0.44 (0.01) | 0.49 (0.02) | 0.09 |
| Albumin (g/dL) | 4.08 (0.01) | 4.06 (0.02) | 4.10 (0.02) | 4.10 (0.02) | 0.25 |
| Creatinine (mg/dL) | 0.89 (0.01) | 0.89 (0.01) | 0.89 (0.01) | 0.92 (0.05) | 0.80 |
| Platelet (1000 cells/μL) | 250.6 (1.91) | 257.0 (5.18) | 250.3 (3.17) | 241.9 (3.78) | 0.05 |
| HBV exposure (HBV anti‐HBc) | 0.43 | ||||
| Negative | 2391 (96.0) | 653 (95.0) | 1022 (96.8) | 716 (95.8) | |
| Positive | 162 (4.0) | 36 (5.0) | 69 (3.2) | 57 (4.2) | |
| HCV (RNA) | 0.0002 | ||||
| Negative | 2520 (99.3) | 675 (98.2) | 1077 (99.8) | 768 (99.8) | |
| Positive | 13 (0.7) | 7 (1.8) | 4 (0.2) | 2 (0.2) | |
| CAP (dB/m) | 324.8 (1.09) | 324.7 (2.52) | 326.6 (2.06) | 320.1 (2.06) | 0.08 |
Abbreviations: ALT, alanine aminotransferase; AST, aspartate aminotransferase; aMED, alternate Mediterranean diet; BMI, body mass index; CAP, controlled attenuation parameter; CMRF, cardiometabolic risk factor; SD, standard deviation.
Note: All individuals with MASLD were categorized into tertiles representing low (scores 0–2), intermediate (scores 3–4), and high (scores 5–9) adherence to the Mediterranean diet.
Reference range for laboratory data: ALT: 0–31 U/L (female), 0–40 U/L (male); AST 0–31 U/L (female), 0–37 U/L (male); total bilirubin: ≦ 1.0 mg/dL; albumin: 3.5–5.0 g/dL; creatinine: 0.51–0.95 mg/dL (female), 0.67–1.17 mg/dL (male); platelet 168–441 1000 cells/μL (female); 152–386 1000 cells/μL (male).
Continuous variables were expressed as mean (standard deviation), and categorical variables as count (percentage). Descriptive statistics were evaluated using one‐way ANOVA for continuous variables and the chi‐square test for categorical variables across the three adherence groups.
Examining the fibrosis profile of the study participants revealed that the degree of liver stiffness declined with higher aMED scores as shown in Figure 2. This trend persisted in mean LSMs after stratifying aMED into three groups (aMED 0–2: 7.51 ± 0.31 kPa; aMED 3–4: 7.47 ± 0.35 kPa; aMED 5–9: 6.50 ± 0.29 kPa, p = 0.03). Furthermore, the proportion of significant fibrosis was inversely associated with aMED scores, with a significantly lower proportion observed in the higher aMED score groups across both stiffness thresholds defined (≧ 8 kPa, p < 0.001; ≧ 12 kPa, p = 0.04) (Table 2).
FIGURE 2.
Liver stiffness measurement by aMED score. Abbreviation: LSM, liver stiffness measurement. A boxplot showing the relationship between the distribution of liver stiffness measurement with increasing level of Mediterranean diet adherence.
TABLE 2.
Participants' liver stiffness measurement by aMED score.
| aMED Score | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| All (n = 2672) | 0–2 (n = 726) | 3–4 (n = 1129) | 5–9 (n = 817) | p | |||||
| n (mean) | % (SD) | n (mean) | % (SD) | n (mean) | % (SD) | n (mean) | % (SD) | ||
| TE‐LSM (kPa) | |||||||||
| Mean ± SD | 7.19 | 0.19 | 7.51 | 0.31 | 7.47 | 0.35 | 6.50 | 0.29 | 0.03 |
| ≧ 8 | 532 | 19.4 | 164 | 26.0 | 218 | 17.4 | 150 | 15.5 | < 0.001 |
| ≧ 12 | 216 | 7.90 | 72 | 9.15 | 96 | 9.07 | 48 | 5.05 | 0.04 |
Abbreviations: aMED, alternate Mediterranean diet; SD, standard deviation; TE‐LSM, transient elastography‐liver stiffness measurement.
Note: Continuous variables were expressed as mean ± SD, and categorical variables as count with %. To achieve higher sensitivity, cutoffs of ≥ 8 kPa for TE‐LSM were used in evaluating liver fibrosis; for improved specificity, higher cutoffs of ≥ 12 kPa were applied. Descriptive statistics were evaluated using one‐way ANOVA for continuous variables and the chi‐square test for categorical variables across the different adherence groups.
3.2. MD Adherence and Associated Factors for Significant Liver Fibrosis
Crude logistic regression models revealed that the highest aMED group exhibited a significantly reduced risk of significant liver fibrosis compared with the lowest aMED group (odds ratio [OR] = 0.522, 95% confidence interval [CI]: 0.521–0.523, p < 0.0001). Similarly, both the T2 (moderate) and T3 (high) physical activity groups showed significantly lower risks of significant liver fibrosis compared with the T1 (low) group (T2: OR = 0.622, 95% CI: 0.621–0.623, p < 0.0001; T3: OR = 0.722, 95% CI: 0.721–0.723, p < 0.0001). Conversely, individuals with MASLD and a decreasing number of CMRFs generally had a significantly reduced risk of significant liver fibrosis (2 CMRFs vs. 4–5 CMRFs: OR = 0.518, 95% CI: 0.517–0.518; 1 CMRF vs. 4–5 CMRFs: OR = 0.255, 95% CI: 0.255–0.256) (Table 3).
TABLE 3.
Multivariate logistic regression analysis of factors associated with significant liver fibrosis.
| Crude | Adjusted | |||||||
|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | p | OR | 95% CI | p | p for trend | ||
| aMED score | < 0.0001 | |||||||
| 0–2 (ref) | — | — | — | — | — | — | ||
| 3–4 | 0.602 | 0.601–0.603 | < 0.0001 | 0.632 | 0.630–0.633 | < 0.0001 | ||
| 5–9 | 0.522 | 0.521–0.523 | < 0.0001 | 0.662 | 0.660–0.663 | < 0.0001 | ||
| No. of cardiometabolic risk factors | < 0.0001 | |||||||
| 4–5 (ref) | — | — | — | — | — | |||
| 3 | 1.101 | 1.100–1.103 | < 0.0001 | 0.931 | 0.930–0.933 | < 0.0001 | ||
| 2 | 0.518 | 0.517–0.518 | < 0.0001 | 0.429 | 0.428–0.430 | < 0.0001 | ||
| 1 | 0.255 | 0.255–0.256 | < 0.0001 | 0.202 | 0.201–0.203 | < 0.0001 | ||
| Physical activity | < 0.0001 | |||||||
| T1 (ref) | — | — | — | — | — | |||
| T2 | 0.622 | 0.621–0.623 | < 0.0001 | 0.529 | 0.528–0.530 | < 0.0001 | ||
| T3 | 0.722 | 0.721–0.723 | < 0.0001 | 1.024 | 1.022–1.026 | < 0.0001 | ||
| Age (year) | 1.002 | 1.002–1.002 | < 0.0001 | 0.989 | 0.989–0.989 | < 0.0001 | — | |
| Sex | Female vs. male | 0.758 | 0.758–0.759 | < 0.0001 | 0.556 | 0.555–0.557 | < 0.0001 | — |
| Current smoker | Yes vs. no | 0.934 | 0.932–0.936 | < 0.0001 | 0.819 | 0.818–0.821 | < 0.0001 | — |
| Alcohol (g/day) | 0.965 | 0.965–0.965 | < 0.0001 | 0.966 | 0.966–0.966 | < 0.0001 | — | |
Abbreviations: aMED, alternate Mediterranean diet; BMI, body mass index; CI, confidence interval; OR, odds ratio.
Note: Significant liver fibrosis was defined by liver stiffness measurement ≧ 8 kPa. The number of cardiometabolic risk factors, physical activity, age, sex, smoking status, and daily alcohol intake were further adjusted. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for the risk of significant liver fibrosis using multivariate logistic regression Bold values were used to highlight odds ratios (ORs) in the table.
After adjusting for the number of CMRFs, level of physical activity, age, sex, current smoking, and daily alcohol intake, higher aMED score groups remained associated with lower risk of significant liver fibrosis (aMED 3–4 vs. aMED 0–2: OR = 0.632, 95% CI: 0.630–0.633, p < 0.0001; aMED 5–9 vs. aMED 0–2: OR = 0.662, 95% CI: 0.660–0.663, p < 0.0001; p for trend < 0.0001). It is interesting to note that the impact of a decreasing number of CMRFs on the risk of significant liver fibrosis was observed in a dose‐dependent fashion in the adjusted model. Individuals with a single CMRF had the lowest risk (OR = 0.202, 95% CI: 0.201–0.203), followed by those with 2 CMRFs (OR = 0.429, 95% CI: 0.428–0.430) and then those with 3 CMRFs (OR = 0.931, 95% CI: 0.930–0.933), when compared with those with 4–5 CMRFs (p for trend < 0.0001).
3.3. Sensitivity Analyses by Different CMRF Burdens
Given the opposing effects of aMED score and CMRFs on significant liver fibrosis seen in the multivariate regression model, we investigated further into the joint influence of the MD adherence and CMRF burden on liver fibrosis. As illustrated in previous studies, higher adherence to the MD has been linked to improvements in various CMRF components, including obesity, glycemic control, hypertension, and lipid metabolism (LDL cholesterol and triglycerides) [33]. To further explore the complex interplay between these factors, we performed sensitivity analyses combining aMED score categories with different CMRF levels.
Figure 3 shows that the proportions of significant liver fibrosis varied across different diet adherence and CMRF groups. Although the difference in fibrosis proportion across aMED groups for any given number of CMRFs was not statistically significant, a trend toward lower fibrosis proportions with higher aMED scores was generally observed (e.g., 29.1%, 22.2%, and 18.2% of significant liver fibrosis for MASLD individuals with 4–5 CMRFs across aMED 0–2, 3–4, and 5–9 groups, p = 0.16).
FIGURE 3.
Proportion of significant liver fibrosis by aMED score and the number of cardiometabolic risk factors. Abbreviation: aMED, alternate Mediterranean diet. Comparing the proportions of significant liver fibrosis across Mediterranean diet adherence and cardiometabolic risk factor groups using the chi‐square test.
Among MASLD individuals with a high aMED score (5–9) and single CMRF, only 7.1% was observed with significant liver fibrosis. Conversely, this proportion increased substantially to 29.1% in MASLD individuals with a low aMED score (0–2) and 4–5 CMRFs (Figure 3).
Following adjustment for covariates in the sensitivity analyses with multivariate logistic regression, the risks of significant liver fibrosis across different aMED and CMRF categories were compared using the highest CMRF and lowest aMED group as a reference. Among individuals with 4–5 CMRFs, the risk of significant fibrosis decreased with the increment of aMED scores (aMED 3–4: aOR 0.780, 95% CI: 0.778–0.782; aMED 5–9: aOR 0.582, 95% CI: 0.580–0.584) (Table 4). However, this progressive benefit of the MD was not observed among patients with only a single CMRF (aMED 0–2: aOR 0.080, 95% CI: 0.079–0.081; aMED 3–4: aOR 0.150, 95% CI: 0.149–0.151; aMED 5–9: aOR 0.383, 95% CI: 0.380–0.386). Overall, fibrosis risk rose with increasing CMRFs, and the negative dose–response relationship between aMED score and fibrosis risk varied depending on the number of concurrent CMRFs.
TABLE 4.
Sensitivity analysis of significant liver fibrosis risk using multivariate logistic regression.
| aMED | |||
|---|---|---|---|
| Cardiometabolic risk factors | 0–2 | 3–4 | 5–9 |
| aOR (95% CI) | aOR (95% CI) | aOR (95% CI) | |
| 4–5 | Reference | 0.780 (0.778–0.782) * | 0.582 (0.580–0.584) * |
| 3 | 0.908 (0.905–0.911) * | 0.545 (0.544–0.547) * | 0.873 (0.870–0.876) * |
| 2 | 0.714 (0.711–0.716) * | 0.192 (0.191–0.193) * | 0.168 (0.167–0.169) * |
| 1 | 0.080 (0.079–0.081) * | 0.150 (0.149–0.151) * | 0.383 (0.380–0.386) * |
Abbreviations: aMED, alternate Mediterranean diet; aOR, adjusted odds ratio; CI, confidence interval.
Note: The risk of significant liver fibrosis across Mediterranean diet adherence and cardiometabolic risk factor groups using multivariate logistic regression. All models adjusted for physical activity, age, sex, current smoking status, and daily alcohol intake. Odds ratios are color‐shaded according to their magnitude, with darker shades representing higher values and lighter shades representing lower ones.
p < 0.001.
4. Discussion
This population‐based cross‐sectional study demonstrated higher adherence to MD was significantly associated with lower risk of significant liver fibrosis in individuals with MASLD. A higher number of CMRFs correlated with increased risk of significant liver fibrosis in a dose‐dependent manner. After controlling for covariates, MASLD patients with multiple (4, 5) CMRFs who demonstrated high MD adherence had a 42% reduced risk of significant liver fibrosis compared with those with low MD adherence.
MD has been well documented for its positive effect on reducing hepatic steatosis in MASLD patients [16, 17]. Its benefit on liver fibrosis in patients with MASLD, however, remains unclear. A meta‐analysis of 271 participants across five studies revealed a marginal improvement in liver stiffness after MD intervention in MASLD patients (standardized mean difference (SMD) = −0.75, 95% CI: −1.51 to 0.00, p = 0.05) [19]. Among the five included studies, the one with the most significant dietary effect comprised a small sample size of 20 intervention and 10 control participants recruited in an outpatient clinic setting [34]. Another RCT demonstrated a significant improvement in liver stiffness following intervention with the MD diet (adjusted mean liver stiffness difference: −0.83 kPa; 95% CI: −0.70, −0.98, p < 0.05). However, this study also involved a small sample recruited from an outpatient clinic setting (n = 21 intervention; n = 11 control) [35]. Their findings have yet to be confirmed in a community‐based setting with a larger population.
A potential explanation for the MD's role in reducing MASLD fibrosis risk is the high antioxidant content of its foods, which may inhibit hepatic inflammation and consequently prevent fibrogenesis. By promoting the consumption of vegetables, fruits, whole grains, beans, and legumes and limiting processed foods and saturated fats, the MD already contributes to overall health [36, 37]. This benefit stems from the MD components such as monounsaturated fatty acids, polyphenols, and antioxidants found in olive oil, nuts, and produce. These components can suppress reactive oxygen species and inhibit pro‐inflammatory signaling by significantly reducing circulating inflammatory markers such as interleukin‐6, which is highly relevant to fibrosis development [38]. In contrast, saturated fatty acid intake is associated with the activation of inflammatory pathways, notably Toll‐like receptor 4 signaling. The restricted intake of saturated fatty acids seen in the MD is likely to suppress this pathway [39]. This reduced inflammatory potential may be beneficial for maintaining hepatic homeostasis, as its disruption is linked to the activation of hepatic stellate cells, which are essential for fibrogenesis [40].
Our study findings also demonstrated that the risk of significant fibrosis escalated in a dose‐dependent manner with the increasing number of CMRFs. At the same time, higher MD adherence appeared to offset the risk of fibrosis, especially in individuals with a high cardiometabolic burden. This observation is consistent with the evidence from a population‐based multi‐cohort study using United Kingdom, United States, and Korea databases, which indicated that both the number and the type of CMRFs were strongly linked to liver fibrosis [41]. Recent MASLD studies also suggest that an increased number of CMRFs is associated with major adverse cardiovascular events, as well as liver‐related and all‐cause mortality [42, 43]. The absence of a clear dose‐dependent protective association in individuals with a single CMRF suggests that the MD's anti‐inflammatory and metabolic benefits may be overshadowed by the relatively low underlying risk, becoming clinically significant only in the context of a substantial cardiometabolic burden.
This study possesses several notable strengths. First, the utilization of well‐validated VCTE for liver stiffness assessment provides a robust and noninvasive measure of fibrosis. Second, its population‐based design, coupled with a nationally representative sample, increases the generalizability of the results to the broader MASLD population, mitigating potential biases associated with selection. Third, this is the first study to jointly examine the MD and CMRFs in relation to liver fibrosis. Finally, the adoption of the latest MASLD consensus nomenclature ensures that the study findings are aligned with current clinical understanding.
Overall, our findings first supported that the increased adherence to MD (by a greater aMED score) was associated with less liver fibrosis risk. We included a high number of patients from the community setting, using a well‐established evaluation for MD adherence and thus provide an important reference for further large‐scale prospective study design and clinical implications.
The interpretation of these findings should account for several limitations. First, causality between MD adherence and liver fibrosis cannot be established due to the cross‐sectional design of this study. Second, we used a lower LSM cutoff for significant fibrosis to maximize the number of individuals at risk. Third, alcohol consumption data from NHANES was collected using standardized questions to quantify the consumption amount during the past 12 months prior to the interview. Self‐reported alcohol consumption may be underestimated, consistent with previous research on this limitation [44, 45]. There is growing evidence supporting the use of objective blood‐based biomarkers for alcohol consumption. Among these, phosphatidylethanol is the most well‐recognized biomarker, and it may help address the limitations of self‐reported data. However, it only reflects the recent 4 weeks intake and does not provide information on long‐term drinking behavior [46]. In contrast, the questionnaire data used in our study assessed alcohol consumption over the past year. Unfortunately, the phosphatidylethanol data are not available in the NHANES database. Fourth, dietary data collection relied on two 24‐h dietary recall interviews. The interviews were conducted by well‐trained personnel adhering to standardized protocols to minimize data collection bias. While acknowledging that two 24‐h recalls may not fully capture long‐term habitual dietary patterns, we averaged the nutrient data obtained from both interviews to mitigate measurement error and intraindividual variability inherent in a single assessment. The primary advantage of this standardized 24‐h recall format is its proven feasibility in large‐scale, population‐based surveys. Furthermore, the use of NHANES 24‐h recall data to investigate long‐term dietary trends among the US population has been previously validated in the literature [30].
In conclusion, our study supported the significant impact of CMRFs on liver fibrosis, and confirmed the notion of MD as a lifestyle modification for MASLD patients in preventing their risk of significant liver fibrosis, in line with AASLD and EASL–EASD–EASO's recommendation. Furthermore, encouraging adherence to the MD in MASLD patients, in conjunction with the reduction of CMRFs, may be an effective strategy to prevent significant liver fibrosis.
Funding
This study is supported in part by the National Science and Technology Council, Taiwan (Grant Number: NSTC 113‐2410‐H‐039‐004) and China Medical University (CMU113‐MF‐114).
Ethics Statement
All data underlying this study are publicly available on the National Health and Nutrition Examination Survey website, maintained by the National Center for Health Statistics. The NHANES 2017–2020 study protocol was approved by the National Center for Health Statistics Ethics Review Board (Protocol #2018–01) to ensure protections of all human participants.
Conflicts of Interest
T‐H. Su received a research grant from Gilead Sciences, served as a consultant for Gilead Sciences, and was on speaker's bureaus for Abbott, Abbvie, Bristol‐Myers Squibb, Eisai, Gilead Sciences, Merck Sharp and Dohme, Roche, and Sysmex. The other authors declare no conflict of interest.
Supporting information
Table S1: Proportion of study subjects aged over 65 years old.
Figure S1: Distribution of significant fibrosis by aMED score group.
Acknowledgments
We gratefully acknowledge the NHANES participants and the National Center for Health Statistics for providing public access to the database. Generative AI ChatGPT‐4o (accessed in April 2025, OpenAI, San Francisco, CA, USA) and Gemini 3 pro (accessed in December 2025, Google, Mountain View, CA, USA) were used in the preparation of this manuscript for grammar correction. The authors take full responsibility for the accuracy and integrity of its contents.
Contributor Information
Yen‐Chun Peng, Email: pychun@vghtc.gov.tw.
Vivian Chia‐Rong Hsieh, Email: hsiehchiarong@gmail.com.
Data Availability Statement
The data that support the findings of this study are available in NHANES 2017–March 2020 Pre‐pandemic at https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=20.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1: Proportion of study subjects aged over 65 years old.
Figure S1: Distribution of significant fibrosis by aMED score group.
Data Availability Statement
The data that support the findings of this study are available in NHANES 2017–March 2020 Pre‐pandemic at https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=20.