Characteristics of Metabolic Dysfunction-Associated Steatotic Liver Disease and Its Risk for Hepatic Fibrosis in 476,124 Korean Adults: A Cross-Sectional Study
Article information
Abstract
As the new terminology of metabolic dysfunction-associated steatotic liver disease (MASLD) and MASLD with increased alcohol intake (MetALD) has emerged, the clinical significance of MASLD is increasing. This cross-sectional study analyzed 476,124 health checkup participants (2002–2022) to compare hepatic fibrosis risks across MASLD, MetALD, non-alcoholic fatty liver disease (NAFLD), and metabolic dysfunction-associated fatty liver disease (MAFLD). Steatotic liver was identified via ultrasonography, and fibrosis risk was assessed using aspartate aminotransferase to platelet ratio index and NAFLD fibrosis score. The prevalence of NAFLD, MAFLD, MASLD, and MetALD was 30.1%, 32.3%, 29.8%, and 3.0%, respectively, with a 27.9% overlap among three conditions. Participants with steatotic liver were predominantly male, with higher glucose, lipids, liver enzymes, and homeostasis model assessment of insulin resistance levels. Three disease definitions largely overlapped, with MASLD and NAFLD being very similar, while participants with MAFLD and MetALD showed increased fibrosis risk (clinical trial registration number: 2024-11-050).
INTRODUCTION
Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease, contributing to liver-related morbidity and mortality [1,2]. Traditional NAFLD diagnosis is limited by reliance on exclusion criteria and liver biopsy [3]. To address these limitations, metabolic dysfunction-associated fatty liver disease (MAFLD) was proposed in 2020, but challenges remain in accounting for alcohol use and steatohepatitis [4,5].
In 2023, metabolic dysfunction-associated steatotic liver disease (MASLD) was introduced, defining steatotic liver disease (SLD) with at least one out of five specified cardiometabolic risk factors. Additionally, MASLD with increased alcohol intake (MetALD) was introduced to account for alcohol consumption levels [6].
This shift to adopting MASLD criteria has fomented research in this area. Nevertheless, there is a need to better understand the characteristics of both MASLD and MetALD. In addition, concerns have also been raised regarding the direct applicability of existing NAFLD data to the newer MASLD concept [7-10].
This study aimed to evaluate the characteristics of MASLD and MetALD in large scale of Korean adults, analyzing their risk for hepatic fibrosis via an assessment of multiple fibrosis scores. Furthermore, these analyses were compared with those of NAFLD and MAFLD.
METHODS
This cross-sectional study used data from the Kangbuk Samsung Health Study, including 476,124 participants, aged 18 and above, who underwent health checkups with abdominal ultrasonography between 2002 and 2022.
Measurements included height, weight, blood pressure, and blood tests for fasting glucose, serum creatinine, total cholesterol, triglycerides, low density lipoprotein cholesterol, high-density lipoprotein cholesterol, high sensitivity C-reactive protein (hs-CRP), aspartate aminotransferase (AST), alanine aminotransferase, hemoglobin, fasting insulin, and homeostasis model assessment of insulin resistance (HOMA-IR) score.
SLD was defined as moderate to severe hepatic steatosis on ultrasonography [11]. NAFLD was defined as the presence of SLD without excessive alcohol intake (≥20g/day for females and ≥30g/day for males) and/or other hepatic conditions (e.g., viral hepatitis) [12]. MAFLD was defined as SLD with either overweight, diabetes, or two of the seven metabolic components [13]. MASLD was defined as SLD with one of five metabolic components. Liver fibrosis was assessed using two scores: the AST to platelet ratio index (APRI) and the NAFLD fibrosis score (NFS) [14]. Participants were categorized into low-risk (APRI <0.5; NFS <–1.455), intermediate-risk (APRI 0.5 to 1.5; NFS –1.455 to 0.676), and high-risk groups (APRI >1.5; NFS >0.676) based on established cutoff values.
Odds ratios (ORs) for retinal disorders based on the SLD status were estimated using multinomial logistic regression models, adjusting for age, sex, body mass index (BMI), and diabetes status, among other confounders. Statistical analysis was performed using IBM SPSS Statistics for Windows, version 19.0 (IBM Corp., Armonk, NY, USA), with P values <0.05 considered significant.
This study was approved by the Institutional Review Board of Kangbuk Samsung Hospital (IRB: 2024-11-050), with informed consent waived due to anonymized retrospective data use.
RESULTS
Baseline characteristics
A total of 476,124 participants were included in the analysis. The baseline characteristics of the study population are presented in Supplemental Table S1. The number of steatotic livers identified through ultra-sonogram was 164,917 (34.6%).
Characteristics of variables in groups of steatotic liver disease
Participants were categorized into NAFLD, MAFLD, MASLD, and MetALD group, with characteristics presented in Supplemental Table S2. Participants in the MetALD group were predominantly male (91.1%), and showed the highest prevalence of metabolic dysfunction, with fasting glucose levels (106.5±23.5 mg/dL) and triglycerides (192.6±135.0 mg/dL). Among MASLD criteria, overweight (BMI, 26.5±3.3 kg/m2), fasting glucose (102.5±20.8 mg/dL), and triglycerides (160.7±100.5 mg/dL) were most prevalent. NAFLD and MASLD groups demonstrated very similar characteristics.
Prevalence and risk of fibrosis according to steatotic liver disease
The prevalence rates of NAFLD, MAFLD, MASLD, and MetALD were 30.1%, 32.3%, 29.8%, and 3%, respectively (Supplemental Fig. S1). Participants with NAFLD and MAFLD comprised 28.6%, those with NAFLD and MASLD comprised 29.1%, and those with MAFLD and MASLD comprised 28.6%. Those with NAFLD, MAFLD, and MASLD comprised 27.9%, while MASLD alone accounted for 0.08% (Fig. 1).
Number and prevalence of steatotic liver disease summarized through a Venn diagram. NAFLD, non-alcoholic fatty liver disease; MAFLD, metabolic dysfunction-associated fatty liver disease; MASLD, metabolic dysfunction-associated steatotic liver disease.
Assessed by NFS, participants with MetALD showed the highest prevalence of intermediate or high fibrosis risk at 22.2%, followed by those with MAFLD (19.6%) and MASLD (19.1%). The APRI scores revealed a similar trend, with MetALD patients having the highest risk (11.2%), followed by MAFLD (7.1%) and MASLD (6.2%) (Supplemental Fig. S2).
Presence of SLD was associated with an increased OR of being in the intermediate-risk group, particularly using APRI score (Table 1). MAFLD demonstrated the highest crude OR for intermediate fibrosis risk by APRI (3.092; 95% confidence interval [CI], 3.002 to 3.186), which remained significant after adjustment for multiple variables (1.342; 95% CI, 1.290 to 1.396). The NFS-based risk for MAFLD was still significant in the crude analysis (1.410; 95% CI, 1.388 to 1.433) but it was not significant after adjustment (0.676; 95% CI, 0.660 to 0.693). MASLD exhibited a similar trend, with APRI-based risk being higher (crude OR, 2.160; 95% CI, 2.098 to 2.225 and adjusted OR, 1.251; 95% CI, 1.200 to 1.304) compared to NFS-based risk (crude OR, 1.320; 95% CI, 1.299 to 1.342 and adjusted OR, 0.672; 95% CI, 0.656 to 0.689). The APRI-based risk for MetALD was particularly high, even after adjustment (crude OR, 3.257; 95% CI, 3.084 to 3.439 and adjusted OR, 1.420; 95% CI, 1.293 to 1.560). Similarly, the NFS-based risk for MetALD was substantial and remained significant post-adjustment (crude OR, 1.474; 95% CI, 1.425 to 1.545 and adjusted OR, 0.994; 95% CI, 0.929 to 1.063).
Risk of Fibrosis according to Steatotic Liver Disease Classifications
DISCUSSION
This study analyzed the clinical characteristics and risk of fibrosis associated with the different terminologies of SLD, MASLD, NAFLD, MAFLD and MetALD. The MASLD criteria simplify metabolic requirements compared to MAFLD, needing only 1 of 5 factors versus 2 of 7, with lower waist circumference thresholds (MASLD >94/80 cm, MAFLD ≥102/88 cm for men/women) [13].
Furthermore, our results demonstrate similar characteristics between the NAFLD and MASLD groups [9,15]. NAFLD classification was consistent with MASLD in approximately 96.7% of cases. This similarity suggests that the previous NAFLD data may continue to be relevant even after the transition to MASLD.
A key revision in the new classification system was the establishment of the MetALD sub-category, in which metabolic- and alcohol-related risk factors coexist [6]. In our study, the MetALD group exhibited the highest prevalence of metabolic dysfunction among all categories; notably, this group was predominantly male compared with the MASLD group. This could reflect a higher degree of alcohol consumption among men compared with women, and underscores the compound effect of metabolic factors and alcohol consumption on liver health leading to disruption of liver metabolic homeostasis [16].
Interestingly, both the MAFLD and MetALD groups showed a higher risk of fibrosis than the MASLD group, highlighting the detrimental effects of alcohol on liver health, even in small quantities [17].
The results also revealed differences between the APRI and NFS scores. The APRI score remained statistically significant even after adjustment, whereas the NFS score did not. This difference may be attributed to the fact that the APRI score incorporates AST and platelet count (PLT) as variables, whereas the NFS score includes age, BMI, and diabetes status within its calculation, effectively applying a form of double adjustment. In the high-risk group, AST and PLT have a greater influence, leading to increased sensitivity of the APRI score. Conversely, in the intermediate-risk group, the NFS score demonstrated relatively higher sensitivity and specificity [18].
This study has several limitations. Due to its cross-sectional design, longitudinal changes in NAFLD, MAFLD, MASLD, and MetALD status over time could not be assessed. The lack of liver biopsies for histological validation limits the ability to definitively confirm the diagnosis and severity of liver disease. Additionally, potential biases in self-reported alcohol consumption may affect the classification of participants. Furthermore, the prevalence of metabolic dysfunction-associated steatohepatitis, which represents a more severe form of the disease, could not be assessed in the present study.
Despite these limitations, the strengths of this study lie in its large sample size (n=476,124), ultrasonography to define hepatic steatosis, and comprehensive analysis of SLD in the Korean population. Furthermore, the data included HOMA-IR and hs-CRP, which are not typically included in national databases. The inclusion of these tests allowed to enhance the accuracy of the diagnostic criteria for MAFLD.
In conclusion, three disease definitions largely overlapped, with MASLD and NAFLD being very similar, while participants with MAFLD and MetALD showed increased fibrosis risk. The higher fibrosis risk in MAFLD and MetALD groups emphasizes the need for targeted interventions and closer monitoring of these subpopulations. Future longitudinal studies are needed to clarify SLD classifications and management.
Supplementary Material
Supplemental Table S1.
General Characteristics of the Participants according to the Presence of Steatotic Liver Disease (n=476,124)
Supplemental Table S2.
Characteristics of Variables in Groups of Steatotic Liver Disease (n=476,124)
Supplemental Fig. S1.
Prevalence of steatotic liver disease according to subtypes. NAFLD, non-alcoholic fatty liver disease; MAFLD, metabolic dysfunction-associated fatty liver disease; MASLD, metabolic dysfunction-associated steatotic liver disease; MetALD, MASLD with increased alcohol intake.
Supplemental Fig. S2.
Prevalence of high- or intermediate-risk of fibrosis according to steatotic liver disease. MAFLD, metabolic dysfunction- associated fatty liver disease; MASLD, metabolic dysfunction-associated steatotic liver disease; MetALD, MASLD with increased alcohol intake; NFS, non-alcoholic fatty liver disease fibrosis score; APRI, aspartate aminotransferase to platelet ratio index.
Notes
CONFLICTS OF INTEREST
Eun-Jung Rhee is a deputy editor of the journal. But she was not involved in the peer reviewer selection, evaluation, or decision process of this article. No other potential conflicts of interest relevant to this article were reported.
AUTHOR CONTRIBUTIONS
Conception or design: D.Y.L., E.J.R. Acquisition, analysis, or interpretation of data: E.J.R. Drafting the work or revising: D.Y.L., J.H.K., H.N.J., S.J.M., H.M.K., S.E.P., C.Y.P., W.Y.L., K.W.O., E.J.R. Final approval of the manuscript: W.Y.L., E.J.R.