Epidemiology of metabolic dysfunction-associated steatotic liver disease/metabolic dysfunction-associated steatohepatitis and associated cardiometabolic factors in adults in China (2013-2023): A systematic review and meta-analysis

Abstract

BACKGROUND

Although epidemiological data on non-alcoholic fatty liver disease in China are available, data on cardiometabolic risk factors have not been addressed under the metabolic dysfunction-associated steatotic liver disease (MASLD) consensus.

AIM

To synthesize the epidemiological characteristics of MASLD/metabolic dysfunction-associated steatohepatitis (MASH), especially their associated cardiometabolic risk factors in China.

METHODS

We searched EMBASE, MEDLINE, Central Cochrane, CNKI, and Wangfan for studies from January 1, 2013 to December 31, 2023. Studies involving individuals with MASLD/MASH in China that reported epidemiological outcomes were included. Meta-analysis was performed to assess the prevalence of MASLD/MASH. Exploratory outcomes included extrahepatic comorbidities and genetic variants related to MASLD.

RESULTS

In total, 561 studies involving 6632718 participants were included in this analysis. The prevalence of MASLD and MASH and the annual incidence of MASLD were 30.4% [95% confidence interval (CI): 29.4-31.3], 6.7% (95%CI: 2.2-13.4), and 37 cases per 1000 person-years (95%CI: 28-47), respectively. In addition, the prevalence rates of MASLD in individuals with dyslipidemia, obesity, and hypertension were 59.9% (95%CI: 52.6-67.0), 53.9% (95%CI: 47.9-59.9), and 44.3% (95%CI: 41.1-47.6), respectively. The prevalence of lean MASLD (body mass index < 24 kg/m²) was 12.0% (95%CI: 10.0-14.0), and 21.7% of the total MASLD population in China had lean MASLD.

CONCLUSION

This study provides a comprehensive overview of the epidemiology and disease burden of MASLD/MASH in China, providing additional evidence for optimizing MASLD/MASH management in China and a reference for the global understanding of MASLD/MASH epidemiology.

Key Words: Metabolic dysfunction-associated steatohepatitis; Metabolic dysfunction-associated steatotic liver disease; Epidemiology; Disease burden; Meta-analysis

Core Tip: According to our analysis, the prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) was 30.4% [95% confidence interval (CI): 29.4-31.3] during the study period in China, and its prevalence is increasing over time. Several prevalent extrahepatic comorbidities of MASLD were identified. Meanwhile, the prevalence rates of MASLD in individuals with dyslipidemia, obesity, and hypertension were 59.9% (95%CI: 52.6-67.0), 53.9% (95%CI: 47.9-59.9), and 44.3% (95%CI: 41.1-47.6), respectively. Furthermore, the prevalence of lean MASLD (body mass index < 24 kg/m²), which is usually ignored in clinical practice, was 12.0% (95%CI: 10.0-14.0), with 21.7% of the total MASLD population in China having lean MASLD. Additionally, several single-nucleotide polymorphisms were linked to the risk of MASLD.

INTRODUCTION

Non-alcoholic fatty liver disease (NAFLD) has been the leading global cause of chronic liver disease worldwide in recent decades[1,2]. NAFLD ranges from simple steatosis to non-alcoholic steatohepatitis (NASH), which tends to progress to liver cirrhosis and hepatocellular carcinoma (HCC)[3]. The estimated annual incidence of HCC globally ranges 0.01%-0.13% and 0.5%-2.6% among individuals with NAFLD and NASH, respectively[4]. In addition, NASH is one of the most common indications for liver transplantation in the United States[5]. Therefore, NAFLD/NASH is a substantial public health challenge globally, associated with significant economic losses, high healthcare costs, and adverse effects on health-related quality of life[6-9]. In 2023, NAFLD and NASH were renamed metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH), respectively, by multinational liver societies. The main reason for updating the names from “non-alcoholic” to “metabolic dysfunction-associated” was the recognition of metabolic dysfunction as the underlying disease pathogenesis[10]. Furthermore, under the new terminology, MASLD includes the presence of at least one of five cardiometabolic risk factors[11]. Therefore, there is a need to understand varying cardiometabolic risk factors in the Chinese MASLD/MASH population.

Many conditions and diseases, such as obesity, type 2 diabetes, hypertension, metabolic syndrome, and dyslipidemia, are associated with MASLD/MASH[12-14]. Because of the increased prevalence of these diseases in China, a substantial proportion of the Chinese population has MASLD or carries a risk of developing MASLD[15,16]. It was predicted that the number of cases of MASLD would reach 314.58 million in China by 2030[17]. On a global level, the median age of individuals with MASLD is lowest in China, indicating the potential long-term outcomes and burden of this disease in later decades[17]. In addition, the occurrence of MASH has increased in China[18]. Regarding to the treatment, the United States Food and Drug Administration approved Madrigal Pharmaceuticals’ Rezdiffra (resmetirom) in 2024 as the first MASH drug[19] based on the results of a phase 3 clinical trial[20]. In addition, semaglutide has displayed potential efficacy against MASLD[21-24], and studies and clinical trials are ongoing and planned in China. Research indicates that semaglutide can reduce liver fat, improve metabolic markers such as blood glucose and lipids, and reduce liver inflammation in NAFLD models[25]. An ongoing Chinese clinical trial is evaluating the combination of semaglutide and empagliflozin for type 2 diabetes mellitus and NAFLD, with efforts ongoing to identify effective treatments for this increasingly prevalent condition in China[26]. In addition, an exploratory study evaluating linafexor (CS-0159) in combination with semaglutide in patients with MASH alongside obesity and type 2 diabetes mellitus is ongoing in China (NCT06492330). However, no drugs have been approved for the treatment of MASH in China. Therefore, the increasing burden of both MASLD and MASH is a significant public health concern in China[16].

Understanding the disease burden of MASLD/MASH in China is vital for effectively allocating healthcare resources and developing national strategies for policy making and new drug development. Unfortunately, owing to their larger disease burden in China, some diseases, such as viral hepatitis, are receiving more attention from healthcare professionals and policymakers than MASLD/MASH[27]. Consequently, nationwide epidemiology studies of MASLD/MASH are rare, and their related intrahepatic and extrahepatic comorbidities have not been well identified. The most recent systematic review on the MASLD burden in China was published in 2019[16], and updates are needed as more important studies have emerged[16]. Although a systematic review on the burden of MASH in China was recently reported[18], there is no integrated review on both MASLD and MASH. In addition, data on cardiometabolic risk factors have not been addressed under the MASLD consensus. Therefore, this meta-analysis presents a comprehensive overview of the epidemiological characteristics and disease burden of MASLD/MASH in China, provides additional evidence for the MASLD/MASH population with varying cardiometabolic risk factors, and updates data to help understand the global MASLD/MASH epidemiology.

MATERIALS AND METHODS

The present study was conducted and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement[28]. The protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO: CRD42024568397).

Eligibility criteria

The inclusion criteria for the studies were as follows: Inclusion of adults (≥ 18 years) with MASLD/MASH in the Chinese Mainland (excluding Hong Kong, Macao, and Taiwan because of their different health care systems); published from 2013 to 2023; available information on various outcomes on MASLD and/or MASH (prevalence; incidence; progression, comorbidities, life impact, resource utility, or clinical characteristics); and study type comprising prospective cohort studies, retrospective cohort studies, or cross-sectional studies. The exclusion criteria were as follows: Case reports, conference abstracts, retracted publications, early-access publications, editorial material, protocols, letters, comments, systematic reviews/meta-analyses, reviews, guidelines, corrections, and notes; languages other than English and Chinese; duplicate studies; and animal studies or cellular experiments.

Literature search

The study covered studies published between January 1, 2013 and December 31, 2023 (search strategies presented in Supplementary material). As the new term MASLD/MASH was not used during this period, they were not used as search keywords. Instead, the search terms included “Non-alcoholic Fatty Liver Disease”, “Chinese or China”, “NAFL* or NASH*”, and “Nonalcoholic Fatty Liver Disease* or Nonalcoholic Fatty-Liver Disease or Non-alcoholic Fatty Liver Disease or Nonalcoholic Steatohepatiti* or Nonalcoholic Fatty Liver or steatohepat* or steatosis or steatoses”, as previously reported[29]. We searched English electronic databases (including MEDLINE, EMBASE, and the Cochrane Library) for China population data. We also searched Chinese electronic databases (including CNKI and Wanfang databases). In addition, we searched for additional references by cross-checking the bibliographies of retrieved studies or relevant reviews.

Study selection

Two reviewers performed the study selection independently. First, after deleting duplicate studies, the titles and abstracts of potentially eligible publications were screened according to the eligibility criteria using EndNote X9. A list of potentially eligible studies was generated after checking the consistency between the two reviews. The full text of the papers or abstracts was downloaded for full-text review and screening using a pretested screening form. The reasons for excluding any study on the list were recorded in detail. Any disagreement between the two reviews was resolved by discussion or referred to a third party.

Data collection

A pretest data collection form was used to extract data from the included studies. Data collection was conducted by two independent reviewers (Chai SY and Zhang RY). Disputes that could be resolved by discussion were resolved by consulting a third party (Wei L). The following data items were collected: Basic characteristics of the included studies, such as the publication year, first author, study location, study period, and demographic information of the target population; data on prevalence, incidence, progression outcomes, characteristics or comorbidities, life impact, and resource use of MASLD/MASH; data related to subgroup analysis according to age, presence of obesity/overweight, and sex; and gene polymorphisms.

Outcomes

The primary outcome was the prevalence of MASLD/MASH in China. The secondary outcomes were as follows: The prevalence of MASLD/MASH stratified by different subgroups according to age category [young (< 45 years), middle-aged (45-65 years), and older (> 65 years)][30-32], study period (before 2010, 2010-2014, 2014-2019, and after 2019), body mass index (BMI), sex, and location; annual incidence of MASLD; and clinical characteristics of MASLD/MASH (e.g., extrahepatic tumor, diabetes, hypertension, cardiac vascular disease, metabolic syndrome).

Synthesis methods

The prevalence of MASLD/MASH, its distribution by individuals’ clinical characteristics (e.g., comorbidities), and the incidence of clinical outcomes were presented as percentages. Meta-analysis was performed to assess prevalence, annual incidence, clinical characteristics or comorbidities, and clinical outcomes. Pooled prevalence or event rates were calculated using a double arcsine transformation to stabilize the variances of the original proportion. The results of the pooled proportion were presented as the point estimate with a 95% confidence interval (CI). All analyses were performed using Stata (version 12.0; Stata Corp., College Station, TX, United States).

Statistical analysis

Heterogeneity was estimated using the Q-test and I² test. P < 0.05 (for Q-test) and I² > 50% indicated heterogeneity. As high heterogeneity existed among the included studies, the random-effects model was used for all meta-analyses. Subgroup analysis of the prevalence of MASLD/MASH were conducted according to age, study period, location, BMI categories (18.5 kg/m², 24 kg/m², and 28 kg/m² were set as the cutoffs for normal, overweight, and obese, respectively[33,34]), and gender. The difference in the prevalence of MASLD was assessed by comparing the ranges of the 95%CI. If there was no overlap of the 95%CI, then the difference was considered significant (P < 0.05).

RESULTS

Study selection

In total, 37592 articles were initially retrieved according to the literature search. After removing the duplicates, 34959 studies were subjected to title and abstract screening. Then, 789 potentially eligible articles were selected for further full-text screening. Finally, 561 papers were included in the analysis (Figure 1). The full list of the included citations is presented in the Supplementary material.

Figure 1 PRISMA flow diagram for article selection for the meta-analysis. MASLD: Metabolic dysfunction-associated steatotic liver disease.

The general information of the 561 included papers is presented in Supplementary Table 1. In total, 6632718 participants were included in this study. Concerning study designs, the included studies comprised 174 cross-sectional studies, 67 prospective cohort studies, and 320 retrospective cohort studies. The age of the included individuals ranged from 18.0 years to 95.0 years. Regarding age categories, 41.7% (234/561) of the studies targeted the middle-aged group, 26.2% (147/561) targeted the young group, 9.1% (51/561) targeted the older group, and 21.4% (120/561) targeted other age groups (e.g., all age groups, no specified age, middle-aged and older group, and young and middle-aged group). The mean proportion of men was 55.1% in studies having sex distribution information. The period covered by the studies spanned 1990-2023. Some endpoints listed in our protocol, including patient-reported outcomes, costs, healthcare resource utilization, and liver fibrosis stages, did not have sufficient evidence based on our search strategies.

Prevalence and annual incidence of MASLD/MASH in China

According to our meta-analysis based on 509 datasets from 494 studies, the overall nationwide prevalence of MASLD in China was 30.4% (95%CI: 29.4-31.3). Based on data from seven studies, the pooled prevalence of MASH was estimated to be 6.7% (95%CI: 2.2-13.4; Figure 2A). Meanwhile, based on 75 datasets from 69 studies, the annual incidence of MASLD was 37 cases per 1000 person-years (95%CI: 28-47; Figure 2B).

Figure 2 Forest plot of the prevalence of metabolic dysfunction-associated steatohepatitis and the annual incidence of metabolic dysfunction-associated steatotic liver disease. A: Forest plot of the prevalence of metabolic dysfunction-associated steatohepatitis; B: Forest plot of the annual incidence of metabolic dysfunction-associated steatotic liver disease. CI: Confidence interval.

Subgroup analysis of the MASLD prevalence in China

Meanwhile, 362 studies provided 363 datasets on the prevalence of MASLD in males. The pooled male MASLD prevalence was 35.4% (95%CI: 34.0-36.7), which was slightly higher than that in the overall population. The pooled prevalence of MASLD was 27.2% (95%CI: 25.1-29.3), 33.1% (95%CI: 31.8-34.4), and 32.1% (95%CI: 29.2-35.0), in the young, middle-aged, and older groups, respectively. The MASLD prevalence in the middle-aged and older groups was similar, whereas the prevalence in the young group was significantly lower than those in the other groups (Figure 3).

Figure 3 Subgroup analysis of the prevalence of metabolic dysfunction-associated steatotic liver disease according to age. MASLD: Metabolic dysfunction-associated steatotic liver disease; CI: Confidence interval.

According to our subgroup analysis based on different BMI categories, the prevalence of MASLD increased with increasing BMI. For underweight people, the prevalence of MASLD was only 2.7% (95%CI: 1.3-4.5), whereas it was 12.2% (95%CI: 10.5-14.0) for normal-weight people. Combining these two groups, the lean MASLD prevalence (BMI < 24 kg/m²) was 12.0% (95%CI: 10.0-14.0). Furthermore, approximately 21.7% of the total MASLD population consists of individuals with lean MASLD. For the overweight population, the prevalence of MASLD sharply increased to 42.5% (95%CI: 39.5-45.6), whereas it reached 68.4% for the obese population (95%CI: 62.3-74.1).

The prevalence of MASLD did not significantly differ between North China [30.7% (95%CI: 29.5-40.1)] and South China [30.1% (95%CI: 28.8-31.4)]. However, the lowest prevalence was recorded in Southwestern China [23.9% (95%CI: 20.1-28.1)], and the highest prevalence was recorded in Northeast China [35.2% (95%CI: 31.8-38.7); Figure 4]. Based on the average MASLD prevalence by province, the prevalence was highest in Heilongjiang (40.7%) and lowest in Shaanxi (19.1%; Supplementary Table 2 and Figure 4).

Figure 4 The metabolic dysfunction-associated steatotic liver disease prevalence map in China. A: Metabolic dysfunction-associated steatotic liver disease prevalence by region; B: Metabolic dysfunction-associated steatotic liver disease prevalence by province. MASLD: Metabolic dysfunction-associated steatotic liver disease; CI: Confidence interval.

The overall MASLD prevalence changed over time. The prevalence was similar for the pre-2010 and 2010-2014 periods [27.6% (95%CI: 25.0-30.2) and 28.6% (95%CI: 26.8-30.4), respectively]. After that, the prevalence has increased significantly. For the 2015-2019 period, the prevalence of MASLD increased to 31.7% (95%CI: 30.0-33.4), and it further increased to 36.5% (95%CI: 33.5-39.6) after 2019 (Figure 5). The MASLD prevalence in different populations is listed in Table 1.

Figure 5 Subgroup analysis of the prevalence of metabolic dysfunction-associated steatotic liver disease by study period. MASLD: Metabolic dysfunction-associated steatotic liver disease; CI: Confidence interval.

Table 1 Prevalence of metabolically dysfunction-associated steatotic liver disease in different populations in China.

Population	MASLD prevalence % (95%CI)
Overall	30.4 (29.4-31.3)
Male	35.4 (34.0-36.7)
Age
< 45 years	27.2 (25.1-29.3)
45-65 years	33.1 (31.8-34.4)
> 65 years	32.1 (29.2-35.0)
Locations
North China	30.7 (29.5-40.1)
South China	30.1 (28.8-31.4)
Regions
Northeast	35.2 (31.8-38.7)
East	30.7 (29.0-32.5)
Southwest	23.9 (20.1-28.1)
North	31.4 (30.0-32.9)
South Central	30.6 (29.1-32.2)
Northwest	28.1 (25.0-31.4)
Study periods
Before 2010	27.6 (25.0-30.2)
2010-2014	28.6 (26.8-30.4)
2015-2019	31.7 (30.0-33.4)
After 2019	36.5 (33.5-39.6)
BMI (kg/m2)
< 18.5	2.7 (1.3-4.5)
18.5-23.9	12.2 (10.5-14.0)
24.0-27.9	42.5 (39.5-45.6)
> 28.0	68.4 (62.3-74.1)

MASLD: Metabolic dysfunction-associated steatotic liver disease; CI: Confidence interval; BMI: Body mass index.

Extrahepatic comorbidities and cardiometabolic factors of MASLD

The most common comorbidity in individuals with MASLD, including associated cardiometabolic factors, was dyslipidemia [59.9% (95%CI: 52.6-67.0) based on data from 42 studies], followed by obesity [53.9% (95%CI: 47.9-59.9) based on data from 70 studies], hypertension [44.3% (95%CI: 41.1-47.6) based on 119 datasets from 118 studies], metabolic syndrome [42.0% (95%CI: 37.7-46.3) based on data from 53 studies], hyperuricemia [29.4% (95%CI: 22.0-37.4) based on data from 30 studies], diabetes [21.0% (95%CI: 18.5-23.6) based on 102 datasets from 101 studies], and cardiovascular disease (CVD) [18.4% (95%CI: 10.7-27.5) based on data from 15 studies; Figure 6].

Figure 6 Prevalence of extrahepatic comorbidities of metabolic dysfunction-associated steatotic liver disease. MASLD: Metabolic dysfunction-associated steatotic liver disease; CI: Confidence interval.

Diagnosis method and genetic variants in individuals with MASLD

Among the studies reporting the MASLD diagnosis method, most of the studies (442/561, 78.8%) used ultrasound alone or together with other techniques (e.g., computed tomography, magnetic resonance imaging) to diagnose MASLD. As an exploratory objective, we harvested 10 studies that provided genetic information related to MASLD in China[35-44] (Table 2 and Supplementary Table 3). The nonsynonymous single-nucleotide polymorphisms (SNPs) identified as risk factors associated with MASLD in the Chinese population included rs10946398 in the cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like 1 gene[35], multiple SNPs (e.g., rs1421085, rs3751812, rs8050136, rs9939609) in the alpha-ketoglutarate dependent dioxygenase (FTO) gene[38], rs2206277 in the transcription factor AP-2 beta gene[38], rs1800591 in the microsomal triglyceride transfer protein gene[39], rs1801133 in the methylenetetrahydrofolate reductase gene[41], and rs738409 in the patatin-like phospholipase domain-containing protein-3 (PNPLA3) gene[42,43]. For rs738409, the two relevant studies reported that both the GG and CG alleles increased the risk of MASLD (CC serotype as reference) according to multivariable logistic regression analysis[42,43]. In addition, three SNPs (rs1260326, rs780093, and rs780096) in the glucokinase regulator (GCKR) gene were related to a lower risk of MASLD in lean people[37]. Zeng et al[40] reported differences in genotype frequency among lean, non-obese, and obese people, in which rs2273773 in the sirtuin 1 gene, rs2070666 in the apolipoprotein C3 gene, and rs5186 in the angiotensin II receptor type I gene were significantly more common in the obese population than in the non-obese population.

Table 2 Genetic information related to metabolic dysfunction-associated steatotic liver disease in China.

Ref.	Gene	Genotype	Relationship with MASLD
Zhao et al[39], 2023	rs1800591 in the MTTP gene	GG, GT, and TT	Genotype frequency compared with χ2 tests (P < 0.001); multivariable logistic regression analysis: MTTP rs1800591 GT + TT serotype (GG serotype as reference) increased the risk of MASLD (OR = 1.643, 95%CI: 1.226-2.203, P = 0.001). Frequencies of allele G and allele T compared with χ2 tests (P < 0.001)
Zhu et al[35], 2023	rs10946398 in the CDK5 regulatory CDKAL1 gene	AA, AC, and CC	The CC genotype of rs10946398 (refer to the AA serotype) are more likely to suffer from MASLD (adjusted OR = 1.509, 95%CI: 1.046-2.178, P = 0.022)
Xu et al[36], 2023	rs641738 in MBOAT7 gene	CC, CT, and TT	There was no association between MBOAT7 rs641738 and MASLD, and an increase in the minor T allele did not increase the risk of developing MASLD. T allele carriage (CT + TT) in MASLD patients was independently associated with advanced fibrosis (OR = 3.024, 95%CI: 1.165-7.848, P = 0.023)
Wu et al[37], 2023	rs1260326 in GCKR gene	CC, CT, and TT	The genotypic frequency of these three SNPs on the GCKR gene significantly differed between lean MASLD and lean non-MASLD individuals (P < 0.05). The frequency of the C allele of rs1260326 in GCKR gene was significantly lower in lean MASLD compared with lean non-MASLD individuals (OR = 0.700, 95%CI: 0.499-0.981, P = 0.038. The frequency of the C allele of rs780093 in GCKR gene was significantly lower in lean MASLD compared with lean non-MASLD individuals (OR = 0.685, 95%CI: 0.488-0.962, P = 0.028). The frequency of the C allele of rs780096 in GCKR gene was significantly lower in lean MASLD compared with lean non-MASLD individuals (OR = 0.698, 95%CI: 0.497-0.980, P = 0.037)
	rs780093 in GCKR gene
	rs780096 in GCKR gene
Li et al[38], 2023	rs1421085 in the FTO gene	CC, CT, and TT	Genotype frequency compared with χ2 tests (P = 0.032); MASLD compared to non-MASLD for the frequency of allele C: OR = 1.407 with 95%CI: 1.083-1.828
	rs3751812 in the FTO gene	GG, GT, and TT	Genotype frequency compared with χ2 tests (P = 0.015); MASLD compared to non-MASLD for the frequency of allele G: OR = 1.443 with 95%CI: 1.114-1.869
	rs8050136 in the FTO gene	CC, CA, and AA	Genotype frequency compared with χ2 tests (P = 0.024); MASLD compared to non-MASLD for the frequency of allele C: OR = 1.430 with 95%CI: 1.099-1.861
	rs9939609 in the FTO gene	TT, AA, and AT	Genotype frequency compared with χ2 tests (P = 0.019); MASLD compared to non-MASLD for the frequency of allele T: OR = 1.429 with 95%CI: 1.105-1.849
	rs2206277 in the TFAP2B gene	CC, CT, and TT	Genotype frequency compared with χ2 tests (P = 0.012); MASLD compared to non-MASLD for the frequency of allele C: OR = 1.305 with 95%CI: 1.074-1.586
	rs2279027 in the TBC1D1 gene	CC, CT, and TT	Genotype frequency compared with χ2 tests (P = 0.232); MASLD compared to non-MASLD for the frequency of allele C: OR = 1.093 with 95%CI: 0.921-1.297
	rs2279026 in the TBC1D1 gene	CC, CT, and TT	Genotype frequency compared with χ2 tests (P = 0.232); MASLD compared to non-MASLD for the frequency of allele C: OR = 0.879 with 95%CI: 0.741-1.044
	rs2279028 in the TBC1D1 gene	GA, AA, and GG	Genotype frequency compared with χ2 tests (P = 0.256); MASLD compared to non-MASLD for the frequency of allele G: OR = 0.880 with 95%CI: 0.742-1.045
	rs780093 in the GCKR gene	CC, CT, and TT	Genotype frequency compared with χ2 tests (P = 0.1); MASLD compared to non-MASLD for the frequency of allele C: OR = 1.147 with 95%CI: 0.972-1.353
	rs780094 in the GCKR gene	CC, CT, and TT	Genotype frequency compared with χ2 tests (P = 0.085); MASLD compared to non-MASLD for the frequency of allele C: OR = 0.873 with 95%CI: 0.74-1.03
	rs1260326 in the GCKR gene	CC, CT, and TT	Genotype frequency compared with χ2 tests (P = 0.0.023); MASLD compared to non-MASLD for the frequency of allele C: OR = 0.883 with 95%CI: 0.749-1.041
	rs5215 in the potassium in KCNJ11 gene	CC, CT, and TT	Genotype frequency compared with χ2 tests (P = 0.726); MASLD compared to non-MASLD for the frequency of allele C: OR = 1.070 with 95%CI: 0.904-1.265
Zeng et al[40], 2020	rs2273773 in SIRT1 gene	TT, TC, and CC	Genotype frequency compared with χ2 tests for lean people (P = 0.233), non-obese people (P = 0.363), and obese people (P = 0.022)
	rs2070666 in APOC3 gene	TT, TA, and AA	Genotype frequency compared with χ2 tests for lean people (P = 1.000), non-obese people (P = 0.030), and obese people (P = 0.022)
	rs738409 in PNPLA3 gene	CC, CG, and GG	Genotype frequency compared with χ2 tests for lean people (P = 0.370), non-obese people (P = 0.014), and obese people (P = 0.237)
	rs738408 in PNPLA3 gene	CC, CT, and TT	Genotype frequency compared with χ2 tests for lean people (P = 0.370), non-obese people (P = 0.014), and obese people (P = 0.237)
	rs4823173 in PNPLA3 gene	GG, GA, and AA	Genotype frequency compared with χ2 tests for lean people (P = 0.277), non-obese people (P = 0.010), and obese people (P = 0.237)
	rs2072906 in PNPLA3 gene	AA, AG, and GG	Genotype frequency compared with χ2 tests for lean people (P = 0.332), non-obese people (P = 0.014), and obese people (P = 0.202)
	rs5186 in the AGTR1 gene	AA, AC, and CC	Genotype frequency compared with χ2 tests for lean people (P = 0.900), non-obese people (P = 0.801), and obese people (P = 0.024)
	rs440881 in the AGTR1 gene	CC, CA, and AA	Genotype frequency compared with χ2 tests for lean people (P = 0.639), non-obese people (P = 0.319), and obese people (P = 0.054)
Adila et al[41], 2017	rs1801131 in the MTHFR gene	TT, GG, and GT	Genotype frequency compared with χ2 tests (P = 0.440); multivariable logistic regression analysis: GT + GG serotype (TT serotype as reference) increased the risk of MASLD (OR = 1.159, 95%CI: 0.792-1.696, P = 0.447); GT + TT serotype (GG serotype as reference), decrease the risk of MASLD (OR = 0.648, 95%CI: 0.304-1.383, P = 0.262). Frequencies of allele G and allele T compared with χ2 tests (P = 0.785)
	rs1801133 in MTHFR gene	GG, AA, and GA	Genotype frequency compared with χ2 tests (P = 0.261); multivariable logistic regression analysis: GA + AA serotype (GG serotype as reference) increased the risk of MASLD (OR = 1.061 95%CI: 0.723-1.556, P = 0.763); GT + TT serotype (GG serotype as reference), increased the risk of MASLD (OR = 2.023, 95%CI: 1.057-3.872, P = 0.033). Frequencies of allele G and allele A compared with χ2 tests (P = 0.410)
Liang et al[43], 2016	rs738409 in PNPLA3 gene	CC, CG, and GG	Frequency of GG serotype: MASLD vs non-MASLD = 21.5% vs 12.3%, P = 0.003). Multivariable logistic regression analysis: GG serotype (CC serotype as reference) increased the risk of MASLD (adjusted OR = 2.21, 95%CI: 1.32-3.71); CG serotype (CC serotype as reference) increased the risk of MASLD (adjusted OR = 1.35, 95%CI: 0.92-2.00)
Xia et al[42], 2016	rs738409 in PNPLA3 gene	CC, CG, and GG	Multivariable logistic regression analysis: GC + GG serotype (CC serotype as reference) increased the risk of MASLD (adjusted OR=1.356, 95%CI: 1.189 to 1.546)
Ye et al[44], 2014	rs11377 in adiponectin gene	CC, CG, and GG	Genotype frequency compared with χ2 tests (P = 0.649). Frequencies of allele G and allele C compared with χ2 tests (P = 0.595)

MASLD: Metabolic dysfunction-associated steatotic liver disease; MTTP: Microsomal triglyceride transfer protein; OR: Odds ratio; CI: Confidence interval; CDK5: Cyclin-dependent kinase 5; CDKAL1: Cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like 1; MBOAT7: Membrane bound O-acyltransferase domain containing 7; GCKR: Glucokinase regulator; SNPs: Single-nucleotide polymorphisms; TFAP2B: Transcription factor AP-2 beta; TBC1D1: TBC1 domain family member 1; KCNJ11: Wardly rectifying channel subfamily J member 11; SIRT1: Sirtuin 1; APOC3: Apolipoprotein C3; PNPLA3: Patatin-like phospholipase domain-containing protein-3; AGTR1: Angiotensin II receptor type I; MTHFR: Methylenetetrahydrofolate reductase.

DISCUSSION

This systematic review and meta-analysis included 561 studies involving 6632718 participants and provided a comprehensive overview of the epidemiology and disease burden of MASLD/MASH in China. The prevalence of MASLD/MASH and the annual incidence of MASLD were pooled by meta-analysis. According to our subgroup analysis, the prevalence of MASLD differed by sex, location, BMI, and study period. We also found several highly prevalent extrahepatic comorbidities of MASLD, such as dyslipidemia, hyperuricemia, diabetes, and hypertension. In China, ultrasound was a prominent diagnostic method, and several SNPs were linked to the risk of MASLD.

Findings from this meta-analysis indicated that the annual incidence of MASLD (37.0 cases per 1000 person-years) was relatively lower than the global average (48.9 per 1000 person-years)[45], Asian average (50.9 cases per 1000 person-years)[46], and the previously reported Chinese average (50.0 cases per 1000 person-years)[16]. This inconsistency might be related to the diversity concerning study participants, study periods, and study settings. However, the overall prevalence of MASLD in China was 30.4% (95%CI: 29.4-31.3), consistent with the most recent systematic reviews reporting the global prevalence [30.1% (95%CI: 27.9-32.3)][45] and Chinese prevalence [29.2% (95%CI: 27.7-30.7)][16]. According to the subgroup analysis, the overall prevalence reached 36.5% (95%CI: 33.5-39.6) after 2019, which was significantly higher than that recorded in studies covering earlier periods. Compared with the reported prevalence (29.2%) from 2008 to 2018 by Zhou et al[16], the prevalence of MASLD is increasing. In addition, we found a pooled MASH prevalence of 6.7% (95%CI: 2.2-13.4), which exceeded the reported global prevalence (3.0%-5.0%)[47] and the Chinese prevalence (2.4%-6.1%)[18]. As discussed by Lekakis and Papatheodoridis[48], the increased prevalence of MASLD/MASH might be related to increasing overnutrition attributable to economic growth.

Based on our analysis, most individuals with MASLD were diagnosed with ultrasound. More accurate diagnostic methods (e.g., computed tomography, magnetic resonance imaging, biopsy) were seldom used. The possible reasons might include accessibility, cost-effectiveness, cultural acceptance, and guidance on medical resources for ultrasound examination to diagnose MASLD/MASH[49]. With the advancement of technology, other methods could be gradually integrated to improve the diagnosis and treatment of MASLD/MASH in the future. However, ultrasound will remain the cornerstone of screening and diagnostic methods in China. In other words, the observed reported prevalence might be lower than the true population prevalence. As MASLD and MASH might be increasing in prevalence, policymakers and healthcare providers should pay more attention to optimizing the prevention and management of these conditions and their associated comorbidities.

Older age, male sex, and overweight have emerged as independent risk factors for MASLD and MASH[16,18]. Similarly, findings from our review indicated that the prevalence of MASLD in the middle-aged (33.1%) and older groups (32.1%) was significantly higher than that in the young group (27.1%), the prevalence in men (35.4%) was significantly higher than that in the entire population (30.4%), and the prevalence in the obese population was approximately 5.7-fold higher than that in the lean population. Therefore, individuals with higher BMI, particularly in the obese range, carry a substantially increased risk of developing MASLD than those with lower BMI[50]. Our findings concerning the prevalence of lean MASLD (12%) were consistent with the existing evidence (lean MASLD prevalence: 3.8%-34.1%)[51,52]. However, the proportion of lean people with MASLD was relatively high (21.7%), as previous studies found that normal-weight individuals comprised approximately 10%-20% of the total MASLD population[51,53]. One possible reason for this difference might be the definition of MASLD. Under new nomenclature, patients with lean NAFLD can be further divided into lean MASLD (presence of ≥ 1 cardiometabolic risk factor) and cryptogenic steatotic liver disease (absence of cardiometabolic risk factors)[54]. Thus, patients with lean NAFLD from the studies included in the review should not necessarily be reclassified as having MASLD. Lean MASLD is more often encountered in Asian populations even though the BMI cutoffs have been adjusted to lower thresholds (i.e., BMI of 24 kg/m²)[55]. As the development of MASLD in lean individuals involves a wide variety of underlying factors (i.e., genetic causes), lean MASLD should receive more attention in the Chinese population. In addition, lean individuals with MASLD had similar cancer- and cardiovascular-related mortality as obese individuals with MASLD but an increased risk of all-cause mortality[52]. Therefore, in practice, the management of MASLD in lean people should not be ignored.

The geographic location might be another important factor associated with an increased risk of MASLD, and this risk might be attributable to diverse food cultures, ethnic groups, and economic development[16,56,57]. In this study, the prevalence of MASLD did not significantly differ between North and South China. However, the difference in the prevalence of MASLD between Southwestern and Northeast China was statistically significant (P < 0.05).

Individuals with MASLD have an increased risk of extrahepatic comorbidities, several of which were associated with cardiometabolic factors[58]. Consistent with prior studies[15], we identified seven comorbidities, namely dyslipidemia, hyperuricemia, diabetes, hypertension, metabolic syndrome, obesity, and CVD, with a prevalence exceeding 15% among individuals with MASLD (Figure 6). For those top comorbidities, dyslipidemia, hyperuricemia, diabetes, hypertension, metabolic syndrome, and obesity are all strongly associated with various cardiometabolic risk factors and diseases[59-63]. Early identification and intervention for cardiometabolic risk factors in patients with MASLD, including lifestyle modifications and medication, are crucial for preventing or delaying the onset of serious health problems. Conversely, we did not find the prevalence of CVD outcomes, chronic kidney disease, liver cancers, or extrahepatic malignancies, contradicting a few studies in other countries[64-66].

Although robust data from Western cohorts have established MASLD/MASH as a multisystem disorder with increased risks of CVD mortality, cirrhosis, and extrahepatic cancers, evidence from Chinese populations remains strikingly limited. No large-scale longitudinal studies have specifically addressed the hard endpoints in China’s unique metabolic ethnic context, as their follow-up durations (< 5 years) might have been insufficient to capture HCC or CVD events. In addition, Chinese MASLD epidemiology studies often rely on transient elastography or ultrasonography, with limited histologic confirmation, especially in MASH, which precludes accurate stratification for fibrosis stages linked to liver outcomes. In addition, because hepatitis B virus remains China’s leading HCC etiology, national cancer registries rarely capture MASLD comorbidity, obscuring its true attributable risk. The gap critically hinders risk stratification in Chinese patients. For instance, the lack of CVD outcome data can delay timely cardioprotective interventions. Notably, Chinese individuals exhibit lower BMI thresholds for metabolic dysfunction than Caucasians. Lean MASLD might have distinct CVD/oncogenic trajectories requiring urgent characterization. Our findings provide important evidence for the practical management of individuals with MASLD and clues for further exploration of the associated cardiometabolic factors. However, further research is needed to comprehensively assess extrahepatic comorbidities associated with MASLD and MASH.

Another exploratory objective of the present study was to assess potential gene variants in MASLD in China. In addition to rs738409 in the PNPLA3 gene, which was reported in the systematic review by Zhou et al[16], we found several other SNPs associated with the risk of MASLD reported in the literature (Table 1). For instance, the frequency of the C allele of SNPs in the GCKR gene was related to a lower risk of MASLD in lean people[27], consistent with a recent meta-analysis[67]. This could have implications for predicting the MASLD risk among lean individuals. In the future, genetic testing might become more relevant in identifying and managing individuals at higher risk for MASLD.

Understanding gene polymorphisms is becoming increasingly important for personalized medicine and drug development, as these variations can significantly affect drug efficacy and safety, particularly in diverse ethnic populations, such as the Chinese population[68]. Some of the nonsynonymous SNPs reported as risk factors for MASLD in the Chinese population include rs10946398 in the cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like 1 gene[35]; rs1421085, rs3751812, rs8050136, and rs9939609 in the FTO gene[38]; rs2206277 in the transcription factor AP-2 beta gene[38]; rs1800591 in the microsomal triglyceride transfer protein gene[39]; rs1801133 in the methylenetetrahydrofolate reductase gene[41]; and rs738409 in the PNPLA3 gene[42,43]. In addition, three SNPs (rs1260326, rs780093, and rs780096) in the GCKR gene were related to a lower risk of MASLD in lean people[37]. Zeng et al[40] reported differences in genotype frequency among lean, non-obese, and obese people. Specifically, rs2273773 in the sirtuin 1 gene, rs2070666 in the apolipoprotein C3 gene, and rs5186 in the angiotensin II receptor type I gene were significantly more common in obese individuals with MASLD than in non-obese individuals with MASLD.

To the best of our knowledge, the present study is among the largest systematic reviews (561 studies of 6632718 participants) of the epidemiology of MASLD/MASH in China. One of the limitations of this review was the high heterogeneity of the included studies. Because of the large sample size of the included studies, we reported a fairly narrow 95%CI for the prevalence of MASLD. In addition, subgroup analysis was performed to decrease the heterogeneity. Because of the large number of included studies, it was infeasible to perform a quality assessment in this review. Next, we collected the diagnostic method but not the details of the diagnostic criteria of MASLD/MASH in this project, which might affect the comparability and credibility of the results. Finally, some vital related information, such as that on fibrosis, cirrhosis, and HCC, was not sufficiently reported in the included papers, potentially affecting the comprehensive assessment of disease burden in this project. However, future research targeting this area should be conducted. Despite these limitations, this systematic review and meta-analysis provides insights into the prevalence of MASLD and MASH in China and risk factors for their prevalence.

Future research on MASLD in China should focus on developing more accurate and individualized diagnosis and treatment plans, incorporating multidisciplinary collaborations, and conducting long-term studies to validate treatment efficacy. Specific research directions include assessing the prevalence of MASH and fibrosis in Chinese individuals with varying metabolic factors, identifying the metabolic factors that increase the risk of severe long-term outcomes in individuals with MASLD/MASH, and determining the specific SNPs associated with severe long-term consequences for these conditions.

CONCLUSION

In conclusion, this large-scale systematic review and meta-analysis provided a comprehensive overview of the epidemiology of MASLD/MASH in China. According to our analysis, the prevalence of MASLD and MASH might be increasing in China, and the prevalence of MASLD differed by sex, geographic location, BMI, and study period. Individuals with MASLD have an increased risk of extrahepatic comorbidities, several of which are associated with cardiometabolic factors. Despite the limitations inherent to many systematic reviews, the evidence in this systematic review provides insights into the growing prevalence of MASLD in China and the populations most at risk. Future reviews should focus on MASLD- and MASH-related outcomes such as cirrhosis, HCC, liver transplantation, and liver-related mortality, with an emphasis on the clinical and economic burden of MASLD/MASH in China.

ACKNOWLEDGEMENTS

Zhi-Yuan Ning of MSD China, assisted literature research of the manuscript. Administrative assistance was provided by Li Qi of MSD China. This assistance was funded by MSD China.