v
Search
Advanced Search

Publications > Journals > Journal of Clinical and Translational Hepatology > Article Full Text

  • Original Article
  • OPEN ACCESS

Comparing the Diagnostic Criteria of MAFLD and NAFLD in the Chinese Population: A Population-based Prospective Cohort Study

  • Cheng Yu1,
  • Minzhen Wang1,* ,
  • Shan Zheng1,
  • Miao Xia1,
  • Hongyan Yang1,
  • Desheng Zhang2,
  • Chun Yin2,
  • Ning Cheng3 and
  • Yana Bai1,* 
 Author information  Cite
Journal of Clinical and Translational Hepatology   2022;10(1):6-16

doi: 10.14218/JCTH.2021.00089

Abstract

Background and Aims

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a new concept, proposed in 2020; however, its applicability in Asia populations has yet to be evaluated. Therefore, we aimed to compare the difference in epidemiological and clinical characteristics between MAFLD and non-alcoholic fatty liver disease (NAFLD) among Asian populations.

Methods

Based on the Jinchang cohort, 30,633 participants were collected. The prevalence and incidence of MAFLD and NAFLD were used to analyze the epidemic characteristics and its overlapping effects. In addition, the corresponding clinical characteristics of the two diagnostic criteria populations were compared.

Results

The prevalence rates of MAFLD and NAFLD were 21.03% and 18.83%, respectively. After an average 2.28-year follow-up, the incidence densities of MAFLD and NAFLD were 41.58 per 1,000 person-years and 37.69 per 1,000 person-years, respectively. With the increase of baseline age, body mass index (BMI), and waist circumference (WC) levels, the prevalence and incidence of MAFLD and NAFLD were on the rise (all ptrend<0.05). Among the total patients diagnosed at baseline or follow-up, most patients had both MAFLD and NAFLD, accounting for 78.84% and 82.88%, respectively. Compared with NAFLD, MAFLD patients had greater proportions of males and metabolic diseases (diabetes, dyslipidemia), and had higher BMI, WC, liver enzymes, blood glucose, and lipid levels in the baseline diagnosis patients (p<0.05). Additionally, lean MAFLD patients had higher metabolic disorders than lean NAFLD patients (p<0.05).

Conclusions

Compared with NAFLD, the newly proposed definition of MAFLD is more practical and accurate, and it can help identify more fatty liver patients with high-risk diseases.

Keywords

MAFLD, NAFLD, Diagnostic criteria, Applicability, Prospective cohort study

Introduction

Fatty liver disease (FLD) has become one of the major global public health problems in recent years.1 FLD is currently divided into alcoholic fatty liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD) based on the history of alcohol intake.2 As NAFLD is a common cause of chronic liver disease, it has attracted more and more attention.3 The global prevalence of NAFLD was 25.24%,4 while it was 29.62% in Asia.5 In China, the prevalence of NAFLD was 32.9% in 2018, which had increased by 9.1% compared to the beginning of the 20th century (23.8%).6

The diagnosis of NAFLD adopts exclusion criteria; that is, the secondary causes of liver fat accumulation need to be excluded on the basis of liver steatosis, such as excessive drinking, long-term use of steatogenic medication, chronic viral hepatitis, and so on.7 With the deepening of people’s understanding of the pathogenesis of NAFLD, the current criteria has been challenged. First, due to differences in the basic characteristics, living habits and genetic susceptibility of the population, the clinical manifestations, pathological characteristics and clinical outcomes of NAFLD are obviously heterogeneous.8–11 Therefore, the original diagnostic criteria may affect the clinical prognosis of NAFLD. Second, at present, there is no uniform standard of calculating alcohol intake accurately. Due to information bias, it may not be possible to accurately estimate the actual alcohol intake of the study subjects. Finally, some studies have shown NAFLD can coexist with chronic viral hepatitis, autoimmune liver disease, and ALD, which may contradict the original definition.12,13 For the above reasons, an international expert panel composed of 30 experts from 22 countries proposed a new name for NAFLD, namely metabolic dysfunction-related fatty liver disease (MAFLD).14,15

The diagnosis of MAFLD is based on the evidence of hepatic steatosis and meeting one of the three conditions: overweight/obesity, type 2 diabetes (T2DM), and metabolic dysregulation.15 The new diagnostic criteria are inclusive criteria, which mainly consider the role of metabolic dysfunction in the occurrence of fatty liver, and do not need to exclude excessive drinking and other related factors. Since the MAFLD consensus was proposed in early 2020, it has received a lot of support from experts, liver associations, nurses, and patient advocacy groups.16–19 They all agreed to rename NAFLD to MAFLD. At present, the Association for the Study of the Liver in Latin America, Asia, Middle East, North Africa, and Sub-Saharan Africa have published clinical practice guidelines for MAFLD based on the characteristics of the local population.20–23

Although the MAFLD diagnostic criteria attracted much attention once they were proposed, there are relatively limited studies on the suitability of the criteria in different populations and the connection with NAFLD. Currently, there are only limited reports based on the American population,24–27 but studies in Asian populations have not been reported similarly. Therefore, we aimed to compare the epidemiological and clinical characteristics of MAFLD and NAFLD, and reveal the overlapping effects of patients under the two diagnostic criteria based on a prospective cohort platform in Northwest China.

Methods

Study population

This study was based on the Jinchang cohort,28 which was obtained from Jinchang City, Gansu Province, Northwest China. This represents an ongoing prospective population-based cohort study. The design and methods have been detailed elsewhere.28 In brief, the baseline survey was conducted from June 2011 to December 2013 and the first follow-up was finished in December 2015. There are 33,355 participants who have finished both the baseline and first follow-up surveys. The average follow-up time was 2.28 years. Among these individuals, 2,722 participants were excluded because their B-ultrasound information at baseline and follow-up were missing. As such, 30,633 participants remained as subjects for the prevalence study. Among the 30,633 participants, people who already have fatty liver disease at the time of baseline survey were excluded (n=6,920). The remaining 23,713 participants were the subjects of the incidence study. The cumulative follow-up time was 52,693 person-years. Figure 1 shows the structure of the study participants. The study was approved by the Ethical Committees of School of Public Health, Lanzhou University (Ethical Approval Code: 2017-01), and all participants signed an informed consent form.

Flow charts for inclusion and exclusion of study participants.
Fig. 1  Flow charts for inclusion and exclusion of study participants.

Data collection

A standardized and structured questionnaire was used to conduct epidemiological investigation by trained investigators. The information included basic demographic characteristics (age, gender, education level, occupation, etc.), lifestyles (smoking, drinking, physical exercise, etc.), history of diseases, family history, and other health-related information.

Physical examinations were performed by clinicians, which included measurements of weight, height, waist circumference (WC), abdominal ultrasound, and so on. Weight and height were measured by automatic recording instruments (SK-X80/TCS-160D-W/H; Sonka, China) in a standing position without shoes, and they were accurate to 0.1 kg with light clothing and 0.1 cm. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. WC was measured with an inelastic tape at the middle of the subject’s ribs and iliac crest, accurate to 0.1 cm. The subjects were put in a supine position and abdominal ultrasound was performed using ultrasound diagnostic apparatus (LOGIQ P5; GE Ultrasound, South Korea) by experienced radiologists who did not know the study aims.

Biochemical examinations were performed using a clinical chemistry automatic analyzer (7600-020; Hitachi, Japan) in the morning after overnight fasting (at least 8 to 10 hours without any food, except water). Indicators included alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), total bilirubin (TBIL), fasting plasma glucose (FPG), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and so on.

Definition of variables

According to the diagnostic criteria for obesity in the Asia-Pacific region recommended by the World Health Organization,29 BMI was divided into normal weight (<23.0 kg/m2), overweight (23.0 kg/m2≤BMI<25.0 kg/m2), and obesity (≥25.0 kg/m2). WC was divided into normal (<90 cm (male)/<80 cm (female)) and central obesity (≥90 cm (male)/≥80 cm (female)).

Outcome ascertainment

MAFLD and nonNAFLD-MAFLD (NNM)

According to the latest consensus proposed by the international expert panel and the diagnostic criteria recommended by the Asian Pacific Association for the Study of the Liver,15,20 MAFLD was diagnosed based on B ultrasound-diagnosed hepatic steatosis, in addition to one of the following three criteria, namely overweight/obesity, presence of T2DM, or evidence of metabolic dysregulation. The metabolic dysregulation was defined as the presence of at least two metabolic risk abnormalities: WC ≥90 cm for men and ≥80 cm for women; blood pressure ≥130/85 mmHg or specific drug treatment; plasma TG ≥1.70 mmol/L or specific drug treatment; plasma HDL-C <1.0 mmol/L for men and <1.3 mmol/L for women or specific drug treatment; prediabetes (FPG levels between 5.6 and 6.9 mmol/L, and self-report has not been clearly diagnosed as diabetes); and plasma high-sensitivity C-reactive protein level >2 mg/L.

The NNM individuals referred to those who meet the definition of MAFLD but did not meet the definition of NAFLD.

NAFLD and nonMAFLD-NAFLD (NMN)

According to the diagnostic criteria recommended by the European Association for the Study of the Liver,30 NAFLD was diagnosed according to the presence of all three conditions as follows, at the same time: B ultrasound showing excessive hepatic fat accumulation and the presence of steatosis in >5% of hepatocytes; no history of drinking or the amount of alcohol being <30 g/d for men and <20 g/d for women; and excluded secondary diseases that may cause liver steatoses, such as viral hepatitis (hepatitis B virus and hepatitis C virus), Wilson’s disease, hemochromatosis, and autoimmune hepatitis.

The NMN were defined as those who meet the diagnostic criteria of NAFLD but did not meet the diagnostic criteria of MAFLD.

MAFLD-NAFLD (MN)

This group included research subjects that met the diagnostic criteria of MAFLD and NAFLD at the same time. That is to say, they had liver steatosis, did not drink or drank less alcohol, and had any one of the following: overweight/obesity, T2DM, or metabolic dysregulation.

Lean NAFLD and lean MAFLD

Lean NAFLD was defined as lean individuals (BMI <23 kg/m2) with the diagnosis of NAFLD. Lean MAFLD was defined as lean individuals (BMI <23 kg/m2) with the diagnosis of MAFLD.

Diabetes

According to the diagnostic criteria recommended by the American Diabetes Association,31 diabetes was defined as FPG ≥7.0 mmol/L or self-report clinical diagnosis of diabetes (subjects must provide the name of diagnosing hospital and time of diagnosis) or self-report used of anti-diabetes drugs.

Dyslipidemia

According to the guidelines for the prevention and treatment of dyslipidemia in Chinese adults (2016 Revised Edition),32 plasma TC ≥6.2 mmol/L, TG ≥2.3 mmol/L, HDL-C <1.0mmol/L and LDL-C ≥4.1mmol/L were defined as TC, TG, HDL-C and LDL-C outside of normal range, respectively. Any of the above can be diagnosed as dyslipidemia.

Statistical analysis

We used frequencies or percentages to describe categorical variables and means±standard deviations to describe continuous variables. Normally distributed variables used the two-sample independent t-test, non-normally distributed variables used the Mann-Whitney U-test, and categorical variables used the Chi-squared test (independent design and paired design) to compare the differences between the groups. The p values for all hypotheses tests were two-sided, and p <0.05 was considered statistically significant. All statistical analyses were performed with SPSS 25.0 and R 3.5.1 statistical software.

Results

General characteristics of the study participants

Table 1 shows the general characteristics of study participants. There were 30,633 participants in the prevalence study, and 23,713 participants in the incidence study. Their average ages were 45.62±12.45 and 45.23±12.47 years-old, respectively. The average BMI and WC were 23.45±3.22 and 22.72±2.90 kg/m2, and 84.07±8.94 and 82.42±8.39 cm, respectively. The proportion of males was 63.50% and 58.44%, respectively.

Table 1

General characteristics of the study participants, n (%) / x ± s)

VariablesPrevalence studyIncidence study
Total, n30,633 (100)23,713 (100)
Age in years45.62±12.4545.23±12.47
  <409,088 (29.67)7,338 (30.95)
  40–4912,678 (41.38)9,924 (41.85)
  50–594,007 (13.08)2,831 (11.93)
  ≥604,860 (15.87)3,620 (15.27)
Gender
  Male19,451 (63.50)13,859 (58.44)
  Female11,182 (36.50)9,854 (41.56)
BMI in kg/m223.45±3.2222.72±2.90
  <23.014,184 (46.30)13,175 (55.56)
  23.0–24.97,114 (23.23)5,508 (23.23)
  ≥25.09,335 (30.47)5,030 (21.21)
WC in cm84.07±8.9482.42±8.39
  Normal19,351 (63.17)16,799 (70.84)
  Central obesity11,282 (36.83)6,914 (29.16)
T2DM
  No28,529 (93.13)22,577 (95.21)
  Yes2,104 (6.87)1,136 (4.79)
Dyslipidemia
  No19,403 (63.34)16,647 (70.20)
  Yes11,230 (36.66)7,066 (29.80)
ALT in U/L34.87±29.3130.83±25.62
AST in U/L34.53±19.5032.80±17.49
GGT in U/L37.20±47.2930.25±40.27
TBIL in µmol/L16.54±6.6716.48±6.63
DBIL in µmol/L4.28±2.634.24±2.67
IBIL in µmol/L12.25±4.7712.24±4.70
TP in g/L76.18±4.4675.98±4.45
ALB in g/L48.13±2.8047.99±2.80
GLO in g/L28.12±3.7828.07±3.77
ALP in U/L67.96±20.6566.73±20.76
LDH in U/L190.46±36.64189.03±36.16
FPG in mmol/L5.32±1.385.18±1.15
TC in mmol/L4.68±0.894.62±0.86
TG in mmol/L1.96±1.561.74±1.33
HDL-C in mmol/L1.36±0.351.41±0.35
LDL-C in mmol/L3.05±0.743.03±0.71
Scr in µmol/L70.24±15.1369.44±15.52
UA in µmol/L328.56±78.94316.45±75.02
BUN in mmol/L5.39±1.425.36±1.44

ALB, albumin; ALP, alkaline phosphatase; ALT, alanine transaminase; AST, aspartate aminotransferase; BMI, body mass index; BUN, blood urea nitrogen; DBIL, direct bilirubin; FPG, fasting plasma glucose; GGT, γ-glutamyl transferase; GLO, globulin; HDL-C, high-density lipoprotein cholesterol; IBIL, indirect bilirubin; LDH, lactate dehydrogenase; LDL-C, low-density lipoprotein cholesterol; Scr, serum creatinine; T2DM, type 2 diabetes; TBIL, total bilirubin; TC, total cholesterol; TG, triglyceride; TP, total protein; UA, uric acid; WC, waist circumference.

Prevalence and incidence of MAFLD and NAFLD

The prevalence rates of MAFLD and NAFLD in the baseline population were 21.03% and 18.83%, respectively. After an average follow-up of 2.28 years, the incidence densities of MAFLD and NAFLD were 41.58 per 1,000 person-years and 37.69 per 1,000 person-years, respectively. As the population’s age, BMI, and WC levels increase during the baseline survey, the prevalence and incidence of MAFLD and NAFLD were both on the rise (ptrend<0.05). Compared with females, non-diabetics, and non-dyslipidemia patients, the prevalence and incidence of MAFLD and NAFLD were higher than that among males, diabetics, and dyslipidemia patients (p<0.05) (Table 2).

Table 2

Prevalence and incidence density of MAFLD and NAFLD at different levels of high-risk factors, %/per 1,000 person-years

VariablesTotalMAFLD
NAFLD
Person-yearsMAFLD
NAFLD
nPre, %nPre, %CasesIDCasesID
Age in years
  <409,0881,55717.131,48716.3615,05450533.5546831.09
  40–4912,6782,55620.162,29918.1321,34287841.1481438.14
  50–594,0071,11927.9398224.516,65537656.5033350.04
  ≥604,8601,21024.901,00120.609,64243244.8037138.48
Total30,6336,44221.03*5,76918.8352,6932,19141.58#1,98637.69
  χ2191.59979.853114.07176.558
  ptrend<0.001<0.001<0.001<0.001
Gender
  Male19,4515,20926.784,49423.1030,8601,51349.031,28341.57
  Female11,1821,23311.031,27511.4021,83367831.0570332.20
Total30,6336,44221.035,76918.8352,6932,19141.581,98637.69
  χ21,061.032636.058111.09433.838
  p<0.001<0.001<0.001<0.001
BMI in kg/m2
  <23.014,1845313.748165.7529,20252217.8853918.46
  23.0–24.97,1141,60622.581,36219.1512,27166253.9558247.43
  ≥25.09,3354,30546.123,59138.4711,2201,00789.7586577.09
Total30,6336,44221.035,76918.8352,6932,19141.581,98637.69
  χ26,081.7413,911.2191,185.337859.615
  ptrend<0.001<0.001<0.001<0.001
WC in cm
  Normal19,3512,10610.882,14911.1137,3761,01927.2697726.14
  Central obesity11,2824,33638.433,62032.0915,3171,17276.521,00965.87
Total30,6336,44221.035,76918.8352,6932,19141.581,98637.69
  χ23,257.1642,052.417692.075491.799
  p<0.001<0.001<0.001<0.001
T2DM
  No28,5295,47419.195,00117.5349,9361,96039.251,79435.93
  Yes2,10496846.0176836.502,75723183.7919269.64
Total30,6336,44221.035,76918.8352,6932,19141.581,98637.69
  χ2848.728461.417175.142113.034
  p<0.001<0.001<0.001<0.001
Dyslipidemia
  No19,4032,37512.242,31011.9136,8381,06828.9998826.82
  Yes11,2304,06736.223,45930.8015,8551,12370.8399862.95
Total30,6336,44221.035,76918.8352,6932,19141.581,98637.69
  χ22,461.9841,661.532531.316433.487
  p<0.001<0.001<0.001<0.001

* and # indicate that there was a difference in the prevalence and incidence of MAFLD and NAFLD (p<0.05). BMI, body mass index; ID, incidence density; MAFLD, metabolic dysfunction-associated fatty liver disease; NAFLD, non-alcoholic fatty liver disease; Pre, prevalence; T2DM, type 2 diabetes; WC, waist circumference.

Overlapping effects between the prevalence and incidence of MAFLD and NAFLD

Figure 2 shows that a total of 6,828 people in the baseline population suffered from MAFLD and (or) NAFLD, of which 5,383 patients had both MAFLD and NAFLD, accounting for 78.84% (Fig. 2A). In addition, there were 1,893 patients that had both MAFLD and NAFLD among the 2,284 newly diagnosed patients, which accounted for 82.88% (Fig. 2B).

Schematic diagram of overlap effects between the prevalence and incidence of MAFLD and NAFLD.
Fig. 2  Schematic diagram of overlap effects between the prevalence and incidence of MAFLD and NAFLD.

(A) Overlapping effect of MAFLD and NAFLD patients in the baseline survey. (B) Overlapping effect of new cases of MAFLD and NAFLD in the follow-up population. Red represents the MAFLD patients, and grey-green represents the NAFLD patients. MAFLD, metabolic dysfunction-associated fatty liver disease; NAFLD, non-alcoholic fatty liver disease.

Comparison of MAFLD and NAFLD groups at related high-risk factors

Compared with NAFLD, the MAFLD group had higher BMI and WC levels (χ2=108.160, p<0.001; χ2=27.864, p<0.001), were more likely to be male (χ2=16.348, p<0.001), and had higher prevalence of T2DM and dyslipidemia (χ2=12.968, p<0.001; χ2=7.330, p<=.007) at baseline (Fig. 3A).

Comparison of related high-risk factors in different groups of patients.
Fig. 3  Comparison of related high-risk factors in different groups of patients.

(A) Comparison of MAFLD and NAFLD with different high-risk factors in the baseline diagnosed patients. (B) Comparison of MAFLD and NAFLD with different high-risk factors in the follow-up newly diagnosed cases. (C) Comparison of MN, NNM and NMN with different high-risk factors in the baseline diagnosed patients. (D) Comparison of MN, NNM and NMN with different high-risk factors in the follow-up newly diagnosed cases. *p<0.05 for MAFLD vs. NAFLD; $p<0.05 for MN vs. NMN; #p<0.05 for MN vs. NNM; &p<0.05 for NMN vs. NNM. BMI, body mass index; MAFLD, metabolic dysfunction-associated fatty liver disease; MN, those who meet both the definitions of MAFLD and NAFLD; NAFLD, non-alcoholic fatty liver disease; NMN, those who meet the definition of NAFLD but do not meet the definition of MAFLD; NNM, those who meet the definition of MAFLD but do not meet the definition of NAFLD; T2DM, type 2 diabetes; WC, waist circumference.

For newly diagnosed MAFLD and NAFLD, patients with MAFLD had higher BMI level (χ2=6.142, p=0.046) and were more likely to be male (χ2=9.332, p=0.002) than the NAFLD patients. There were no statistical difference in the distribution of baseline age, WC, and dyslipidemia between the two groups (p>0.05) (Fig. 3B).

The comparison of high-risk factors among the three internal groups of patients is shown in Figure 3C–D. The NMN group had the least proportion of males, with normal BMI and WC, and the lowest proportion of T2DM and dyslipidemia in both the baseline patients and the follow-up new cases (all p<0.05). However, the levels of the above factors in the NNM group seemed to be the highest.

Clinical parameters in different groups of patients

Table 3 shows the difference of clinical parameters between different groups of patients. The MAFLD group had higher ALT, AST, GGT, LDH, FPG, TG, serum creatinine (Scr) and uric acid (UA) levels than those in NAFLD group, but a lower level of HDL-C (p<0.05). Additionally, by comparing the MN and NMN and NNM groups, we found that NMN group had lower levels of liver enzymes, blood glucose, TC/TG/LDL-C, Scr/UA/blood urea nitrogen (BUN), and higher HDL-C levels than the other groups (p<0.05).

Table 3

Comparison of clinical parameters in different groups of patients, x ± s

VariablesMAFLDNAFLDP1MNNMNNNMP2P3P4
Total, n6,4425,769–5,3833861,059–––
Liver function metabolic
  ALT in U/L49.34±33.4448.05±32.030.03149.05±35.1736.23±28.1451.50±39.42<0.0010.061<0.001
  AST in U/L40.64±23.9039.54±22.100.00839.80±21.8835.67±24.7144.82±31.96<0.001<0.001<0.001
  GGT in U/L55.28±63.8050.00±48.59<0.00151.00±48.7036.14±44.9277.05±110.225<0.001<0.001<0.001
  TBIL in µmol/L16.77±6.7716.65±6.720.31916.71±6.7215.80±6.6117.08±7.030.0110.1030.001
  DBIL in µmol/L4.41±2.484.37±2.470.3824.36±2.474.47±2.474.65±2.560.4030.0010.250
  IBIL in µmol/L12.36±4.9712.28±4.940.35712.35±4.9411.33±4.7312.43±5.13<0.0010.595<0.001
  TP in g/L76.91±4.4576.87±4.440.59876.91±4.4475.85±4.3776.73±4.47<0.0010.2230.001
  ALB in g/L48.63±2.7448.64±2.740.80148.64±2.7448.61±2.6948.55±2.750.8380.3410.720
  GLO in g/L28.34±3.7928.29±3.750.47028.35±3.7627.29±3.4828.21±3.91<0.0010.263<0.001
  ALP in U/L72.19±19.6471.88±19.410.38271.88±19.3869.42±20.0172.70±21.040.0160.2170.008
  LDH in U/L196.43±37.95194.99±38.020.036195.97±38.08178.50±33.24197.28±37.40<0.0010.305<0.001
Glucose metabolism
  FPG in mmol/L5.88±1.935.78±1.840.0025.84±1.894.85±0.446.07±2.15<0.0010.001<0.001
Lipid metabolism
  TC in mmol/L4.93±0.954.90±0.940.0684.92±0.944.56±0.864.96±0.99<0.0010.178<0.001
  TG in mmol/L2.81±2.012.69±1.910.0012.77±1.941.51±0.923.00±2.35<0.0010.003<0.001
  HDL-C in mmol/L1.20±0.291.21±0.290.0411.19±0.281.43±0.341.22±0.32<0.0010.002<0.001
  LDL-C in mmol/L3.18±0.803.15±0.800.1103.18±0.792.76±0.803.15±0.82<0.0010.270<0.001
Renal function metabolic
  Scr in µmol/L73.18±13.5272.65±13.470.02972.85±13.6069.70±11.0374.81±13.01<0.001<0.001<0.001
  UA in µmol/L372.07±78.65366.20±79.07<0.001367.84±78.87319.56±73.38382.56±79.35<0.001<0.001<0.001
  BUN in mmol/L5.51±1.375.49±1.350.5935.51±1.365.26±1.235.49±1.43<0.0010.6220.003

P1: MAFLD vs. NAFLD; P2: MN vs. NMN; P3: MN vs. NNM; P4: NMN vs. NNM. ALB, albumin; ALP, alkaline phosphatase; ALT, alanine transaminase; AST, aspartate aminotransferase; BUN, blood urea nitrogen; DBIL, direct bilirubin; FPG, fasting plasma glucose; GGT, γ-glutamyl transferase; GLO, globulin; HDL-C, high-density lipoprotein cholesterol; IBIL, indirect bilirubin; LDH, lactate dehydrogenase; LDL-C, low-density lipoprotein cholesterol; MAFLD, metabolic dysfunction-associated fatty liver disease; MN, those who meet both the definitions of MAFLD and NAFLD; NAFLD, non-alcoholic fatty liver disease; NMN, those who meet the definition of NAFLD but do not meet the definition of MAFLD; NNM, those who meet the definition of MAFLD but do not meet the definition of NAFLD; Scr, serum creatinine; TBIL, total bilirubin; TC, total cholesterol; TG, triglyceride; TP, total protein; UA, uric acid.

Table 4 shows a comparison of the differences in baseline clinical parameters between different groups of new patients. Compared with the NAFLD group, the MAFLD group had higher AST and GGT levels (p<0.05), and there was no statistical difference in the distribution of other parameters (p>0.05). After comparing the three groups of MN and NMN and NNM, we found that NMN group had lower ALT, GGT, DBIL, LDH, FPG, Scr and UA levels, but a higher level of HDL-C than the other groups (p<0.05).

Table 4

Comparison of baseline clinical parameters in different groups of new cases, x ± s

VariablesMAFLDNAFLDP1MNNMNNNMP2P3P4
Total, n2,1911,986–1,89393298–––
Liver function metabolic
  ALT in U/L36.73±23.3335.73±22.150.15336.31±23.9427.79±16.0741.55±32.27<0.0010.008<0.001
  AST in U/L34.24±14.6133.37±12.490.04033.47±12.5531.35±11.2039.13±23.300.111<0.001<0.001
  GGT in U/L43.28±51.8039.64±45.870.01640.19±46.7328.40±18.8462.93±73.64<0.001<0.001<0.001
  TBIL in µmol/L16.38±6.5216.13±6.350.21016.17±6.4215.32±4.6717.71±7.010.095<0.001<0.001
  DBIL in µmol/L4.16±2.364.03±2.250.0634.05±2.273.53±1.624.85±2.760.003<0.001<0.001
  IBIL in µmol/L12.22±4.7612.10±4.690.42512.12±4.7311.79±3.6512.87±4.900.5140.0120.024
  TP in g/L76.40±4.3176.38±4.250.90676.39±4.2876.09±3.6576.40±4.530.4950.9740.493
  ALB in g/L48.22±2.8248.22±2.790.96948.23±2.8048.12±2.6448.22±2.940.7330.9550.789
  GLO in g/L28.31±3.6728.30±3.600.91828.30±3.6128.12±3.3528.33±4.070.6230.9330.619
  ALP in U/L70.68±19.8370.25±19.480.48370.41±19.4367.08±20.3472.41±22.140.1080.1060.040
  LDH in U/L193.49±35.91192.24±35.250.260192.71±35.26182.82±33.84198.44±39.520.0080.0100.001
Glucose metabolism
  FPG in mmol/L5.50±1.455.45±1.370.2145.47±1.395.01±0.515.71±1.79<0.0010.026<0.001
Lipid metabolism
  TC in mmol/L4.83±0.914.83±0.910.9964.83±0.914.88±0.834.84±0.900.6110.7790.753
  TG in mmol/L2.35±1.622.33±1.630.6532.34±1.622.07±1.762.42±1.580.1200.4650.077
  HDL-C in mmol/L1.26±0.301.27±0.300.6501.26±0.301.47±0.371.30±0.33<0.0010.024<0.001
  LDL-C in mmol/L3.14±0.723.15±0.710.8043.15±0.713.22±0.723.13±0.750.3150.7500.305
Renal function metabolic
  Scr in µmol/L71.25±15.2270.68±15.670.23670.85±15.6667.11±15.5773.73±11.780.025<0.001<0.001
  UA in µmol/L346.18±78.40342.58±78.500.139343.98±78.41314.25±75.26360.17±76.97<0.0010.001<0.001
  BUN in mmol/L5.52±1.445.53±1.460.9475.54±1.465.34±1.405.45±1.350.2050.3200.513

P1: MAFLD vs. NAFLD; P2: MN vs. NMN; P3: MN vs. NNM; P4: NMN vs. NNM. ALB, albumin; ALP, alkaline phosphatase; ALT, alanine transaminase; AST, aspartate aminotransferase; BUN, blood urea nitrogen; DBIL, direct bilirubin; FPG, fasting plasma glucose; GGT, γ-glutamyl transferase; GLO, globulin; HDL-C, high-density lipoprotein cholesterol; IBIL, indirect bilirubin; LDH, lactate dehydrogenase; LDL-C, low-density lipoprotein cholesterol; MAFLD, metabolic dysfunction-associated fatty liver disease; MN, those who meet both the definitions of MAFLD and NAFLD; NAFLD, non-alcoholic fatty liver disease; NMN, those who meet the definition of NAFLD but do not meet the definition of MAFLD; NNM, those who meet the definition of MAFLD but do not meet the definition of NAFLD; Scr, serum creatinine; TBIL, total bilirubin; TC, total cholesterol; TG, triglyceride; TP, total protein; UA, uric acid.

Comparison of lean MAFLD and lean NAFLD at baseline and follow-up

There were 531 lean MAFLD patients and 816 lean NAFLD patients in the baseline population, and the prevalence rates were 1.73% and 2.66%, respectively. After an average follow-up of 2.28 years, the new cases of lean MAFLD and lean NAFLD were 204 and 259, and the incidence densities were 3.87 per 1,000 person-years and 4.92 per 1,000 person-years, respectively.

Among the patients diagnosed at baseline, compared with the lean NAFLD, the lean MAFLD group was significantly older (χ2=21.315, p<0001), had higher WC level (χ2=20.827, p<0001), and had higher prevalence of T2DM and dyslipidemia (χ2=26.872, p<0.001; χ2=68.862, p<0.001) (Fig. 4). Meanwhile, it also showed higher levels of liver enzymes, FPG, blood lipids, and UA than the lean group of NAFLD patients (p<0.05) (Table 5). Among newly diagnosed cases, the lean MAFLD patients had higher levels of AST (35.39±18.97 vs. 32.19±11.41, p=0.034) and FPG (5.84±1.77 vs. 5.50±1.48, p=0.030) than the lean NAFLD patients (p<0.05) (Table 5).

Comparison of lean MAFLD and lean NAFLD at different high-risk factors.
Fig. 4  Comparison of lean MAFLD and lean NAFLD at different high-risk factors.

(A) Comparison of lean MAFLD and lean NAFLD with different high-risk factors in the baseline diagnosed patients. (B) Comparison of lean MAFLD and lean NAFLD with different high-risk factors in the follow-up newly diagnosed cases. *p<0.05 for lean MAFLD vs. lean NAFLD. T2DM, type 2 diabetes; WC, waist circumference.

Table 5

Comparison of clinical parameters according to the presence of lean MAFLD and lean NAFLD

VariablesBaseline
Follow-up
Lean MAFLDLean NAFLDP1Lean MAFLDLean NAFLDP2
Total, n531816204259
Liver function metabolic
  ALT in U/L42.70±31.2038.91±28.220.02130.72±22.6428.11±15.030.138
  AST in U/L41.60±35.2037.27±25.790.01535.39±18.9732.19±11.410.034
  GGT in U/L66.94±137.6244.78±69.370.00142.27±83.2533.29±68.560.204
  TBIL in µmol/L17.12±6.8716.34±6.570.03716.14±6.3215.82±5.930.568
  DBIL in µmol/L4.25±2.614.26±2.470.9383.88±2.313.61±2.020.184
  IBIL in µmol/L12.87±4.9512.08±4.790.00312.27±4.6712.21±4.480.892
  TP in g/L77.53±4.4876.83±4.510.00576.82±4.1076.48±3.910.363
  ALB in g/L48.88±2.7248.81±2.690.61747.92±2.5348.04±2.580.606
  GLO in g/L28.74±3.6728.11±3.580.00228.94±3.7228.52±3.440.208
  ALP in U/L74.24±22.4671.50±21.030.02369.41±20.2968.30±20.220.557
  LDH in U/L191.47±39.20185.06±36.910.002189.28±31.58187.58±32.550.573
Glucose metabolism
  FPG in mmol/L6.16±2.325.52±1.81<0.0015.84±1.775.50±1.480.030
  Lipid metabolism
  TC in mmol/L5.06±1.014.82±0.93<0.0015.02±1.044.98±1.000.683
  TG in mmol/L2.86±1.762.20±1.51<0.0012.26±1.372.20±1.530.635
  HDL-C in mmol/L1.27±0.381.34±0.36<0.0011.37±0.331.40±0.350.464
  LDL-C in mmol/L3.21±0.833.00±0.82<0.0013.28±0.713.27±0.720.920
Renal function metabolic
  Scr in µmol/L69.06±13.2869.02±12.450.96065.81±13.7565.55±14.490.849
  UA in µmol/L352.96±84.39334.02±78.98<0.001316.66±76.60309.81±75.070.334
  BUN in mmol/L5.28±1.355.30±1.270.8685.21±1.415.27±1.440.671

ALB, albumin; ALP, alkaline phosphatase; ALT, alanine transaminase; AST, aspartate aminotransferase; BUN, blood urea nitrogen; DBIL, direct bilirubin; FPG, fasting plasma glucose; GGT, γ-glutamyl transferase; GLO, globulin; HDL-C, high-density lipoprotein cholesterol; IBIL, indirect bilirubin; LDH, lactate dehydrogenase; LDL-C, low-density lipoprotein cholesterol; Scr, serum creatinine; TBIL, total bilirubin; TC, total cholesterol; TG, triglyceride; TP, total protein; UA, uric acid.

Discussion

Based on the Jinchang cohort platform, this study explored the difference between the two diagnostic criteria of MAFLD and NAFLD. The prevalence and incidence density of MAFLD were 21.03% and 41.58/1,000 person-years, which were higher than that of NAFLD (18.83%, 37.69/1,000 person-years). Epidemiological studies based on MAFLD diagnostic criteria are relatively limited. A study from the US NHANES-III (1988–1994) database showed that the prevalence of MAFLD was lower than that of NAFLD (31.24% vs. 33.23%, p<0.05).24 An analysis based on a random sample of 1,016 cases in Hong Kong showed that there were no significant differences in the prevalence of MAFLD and NAFLD (25.9% vs. 25.7%, p>0.05), and that the incidence of MAFLD was lower than that of NAFLD (2.8/100 person-years vs. 3.7/100 person-years, p<0.05).26 In our cohort population, the prevalence of metabolic syndrome was highest,33 which may cause the prevalence and incidence of MAFLD to be higher than those of NAFLD.

For existing and new cases, most patients met both diagnostic criteria, accounting for 78.84% and 82.88%, respectively. This phenomenon indicates that NAFLD is actually a metabolic disease.34 In addition, the criteria of MAFLD could detect more fatty liver patients (13–15%) than the criteria of NAFLD and excluded some non-metabolic fatty liver patients. As an inclusive diagnostic criterion, MAFLD will more effectively contribute to managing this type of patient in terms of prevention, treatment, and disease prognosis.

The 2017 US Liver Disease Prevention and Control Guidelines suggested that obesity, T2DM, dyslipidemia, age, gender, and race were high-risk factors for fatty liver.35 Based on this guideline, this study found that elderly, male, obese, and prevalence of T2DM and dyslipidemia were factors indicating a greater likelihood to develop MAFLD and NAFLD, which was consistent with the results conducted by Sulin et al.24 In addition, the proportions of related indicators of abnormal metabolism (such as overweight/obesity, dyslipidemia, central obesity, etc.) in MAFLD patients were higher than those in the NAFLD group. This result indicated that the diagnostic criteria of MAFLD can fully reflect the current status of metabolic dysfunction.

Compared with NAFLD patients, MAFLD patients had higher levels of liver enzymes, blood lipids, and blood glucose. Sakura et al.36 reported that MAFLD was more associated with patients with significant hepatic fibrosis than NAFLD. In addition, we also compared the relevant clinical indicators of each component of the two diagnostic criteria. The results showed that as long as the component contained MAFLD, the clinically relevant metabolic indicators were higher than those without the component. Therefore, this high-risk group should be given more attention.

Considering that obesity is one of the important factors leading to metabolic abnormalities, this study excluded the obese population and analyzed the applicability of the MAFLD diagnostic criteria in the normal-weight population. Lean MAFLD patients still showed higher levels of liver enzymes, FPG, and blood lipids than the lean NAFLD patients. Previous research studies have shown lean NAFLD and obese NAFLD had similar metabolic characteristics, such as insulin resistance and dyslipidemia.37 It can be seen that the MAFLD diagnostic criteria proposed from the perspective of metabolic abnormalities had good applicability for the early detection of fatty liver.

Although this study found some significant results, there are still some limitations. First, due to the lack of relevant data on fasting insulin and the diagnosis of diabetes being solely based on FPG or patient’s self-report, the prevalence and incidence of MAFLD may be underestimated. Nevertheless, patients who self-reported diabetes were required to provide the name of the diagnosing hospital and the diagnosis time in order to ensure their accuracy. Second, hepatic steatosis was diagnosed by ultrasound in this study, which has limited sensitivity and does not reach 100% accuracy. When the subject’s BMI was >40 kg/m2, the detection result is not ideal. Although liver biopsy is the gold standard for diagnosing liver steatosis, it is not suitable for large-scale epidemiological investigations because of its invasive operation and safety issues.

In summary, the new definition of MAFLD is more suitable for describing liver diseases related to metabolic dysfunction, and compared to NAFLD, it can better identify fatty liver patients with high-risk diseases.

Abbreviations

ALB: 

albumin

ALD: 

alcoholic fatty liver disease

ALP: 

alkaline phosphatase

ALT: 

alanine transaminase

AST: 

aspartate aminotransferase

BMI: 

body mass index

BUN: 

blood urea nitrogen

DBIL: 

direct bilirubin

FLD: 

fatty liver disease

FPG: 

fasting plasma glucose

GGT: 

γ-glutamyl transferase

GLO: 

globulin

IBIL: 

indirect bilirubin

HDL-C: 

high-density lipoprotein cholesterol

LDH: 

lactate dehydrogenase

LDL-C: 

low-density lipoprotein cholesterol

MAFLD: 

metabolic dysfunction-associated fatty liver disease

MN: 

those who meet both the definitions of MAFLD and NAFLD

NAFLD: 

non-alcoholic fatty liver disease

NMN: 

those who meet the definition of NAFLD but do not meet the definition of MAFLD

NNM: 

those who meet the definition of MAFLD but do not meet the definition of NAFLD

Scr: 

serum creatinine

T2DM: 

type 2 diabetes

TBIL: 

total bilirubin

TC: 

total cholesterol

TG: 

triglyceride

TP: 

total protein

UA: 

uric acid

WC: 

waist circumference

Declarations

Acknowledgement

We thank all study participants and staff of the Worker’s Hospital of the Jinchuan Nonferrous Metals Corporation (JNMC) for their generous work, and the interviewers from the Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University. We also thank Professor Xiaolong Qi from the First Hospital of Lanzhou University for his interpretation of the MAFLD diagnostic criteria.

Data sharing statement

The datasets used during the current study are available from the corresponding author on reasonable request.

Funding

This study was supported by the National Natural Science Foundation of China (Grant Number: 41705122).

Conflict of interest

The authors have no conflict of interests related to this publication.

Authors’ contributions

Software, formal analysis, investigation, and writing of the original draft (CY), conceptualization, methodology, writing-reviewing and editing, and study supervision (MW), conceptualization, methodology, investigation, and data curation (SZ), formal analysis and investigation (MX, HY), resources (DZ, CY, NC), and project administration and supervision (YB).

References

  1. Yeh M, Brunt E. Pathological features of fatty liver disease. Gastroenterology 2014;147(4):754-764 View Article
  2. Diehl AM, Day C. Cause, pathogenesis, and treatment of nonalcoholic steatohepatitis. N Engl J Med 2017;377(21):2063-2072 View Article
  3. Rinella ME. Nonalcoholic fatty liver disease: a systematic review. Jama 2015;313(22):2263-2273 View Article
  4. Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M. Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology 2016;64(1):73-84 View Article
  5. Li J, Zou B, Yeo YH, Feng Y, Xie X, Lee DH, et al. Prevalence, incidence, and outcome of non-alcoholic fatty liver disease in Asia, 1999-2019: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol 2019;4(5):389-398 View Article
  6. Zhou J, Zhou F, Wang W, Zhang XJ, Ji YX, Zhang P, et al. Epidemiological features of NAFLD from 1999 to 2018 in China. Hepatology 2020;71(5):1851-1864 View Article
  7. Bellentani S. The epidemiology of non-alcoholic fatty liver disease. Liver Int 2017;37(Suppl 1):81-84 View Article
  8. Friedman SL, Neuschwander-Tetri BA, Rinella M, Sanyal AJ. Mechanisms of NAFLD development and therapeutic strategies. Nat Med 2018;24(7):908-922 View Article
  9. Stefan N, Häring HU, Cusi K. Non-alcoholic fatty liver disease: causes, diagnosis, cardiometabolic consequences, and treatment strategies. Lancet Diabetes Endocrinol 2019;7(4):313-324 View Article
  10. Eslam M, George J. Genetic contributions to NAFLD: leveraging shared genetics to uncover systems biology. Nat Rev Gastroenterol Hepatol 2020;17(1):40-52 View Article
  11. Eslam M, Valenti L, Romeo S. Genetics and epigenetics of NAFLD and NASH: Clinical impact. J Hepatol 2018;68(2):268-279 View Article
  12. Blonsky JJ, Harrison SA. nonalcoholic fatty liver disease and hepatitis C virus-partners in crime. Aliment Pharmacol Ther 2008;27(10):855-865 View Article
  13. Mehta M, Satsangi S, Duseja A, Taneja S, Dhiman RK, Chawla Y. Can alcoholic liver disease and nonalcoholic fatty liver disease co-exist?. J Clin Exp Hepatol 2017;7(2):121-126 View Article
  14. Eslam M, Sanyal AJ, George J. MAFLD: a consensus-driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology 2020;158(7):1999-2014.e1991 View Article
  15. Eslam M, Newsome PN, Sarin SK, Anstee QM, Targher G, Romero-Gomez M, et al. A new definition for metabolic dysfunction-associated fatty liver disease: an international expert consensus statement. J Hepatol 2020;73(1):202-209 View Article
  16. Sierra F, Cárdenas A. Re: Fouad Y, et al. The NAFLD-MAFLD debate: eminence versus evidence. Liver Int 2021;41(5):1162-1163 View Article
  17. Fouad Y, Waked I, Bollipo S, Gomaa A, Ajlouni Y, Attia D. What’s in a name? renaming ‘NAFLD’ to ‘MAFLD’. Liver Int 2020;40(6):1254-1261 View Article
  18. Clayton M, Fabrellas N, Luo J, Alghamdi MG, Hafez A, Qadiri TA, et al. From NAFLD to MAFLD: nurse and allied health perspective. Liver Int 2021;41(4):683-691 View Article
  19. Shiha G, Korenjak M, Eskridge W, Casanovas T, Velez-Moller P, Högström S, et al. Redefining fatty liver disease: an international patient perspective. Lancet Gastroenterol Hepatol 2021;6(1):73-79 View Article
  20. Eslam M, Sarin SK, Wong VW, Fan JG, Kawaguchi T, Ahn SH, et al. The Asian Pacific Association for the Study of the Liver clinical practice guidelines for the diagnosis and management of metabolic associated fatty liver disease. Hepatol Int 2020;14(6):889-919 View Article
  21. Mendez-Sanchez N, Arrese M, Gadano A, Oliveira CP, Fassio E, Arab JP, et al. The Latin American Association for the Study of the Liver (ALEH) position statement on the redefinition of fatty liver disease. Lancet Gastroenterol Hepatol 2021;6(1):65-72 View Article
  22. Spearman CW, Desalegn H, Ocama P, Awuku YA, Ojo O, Elsahhar M, et al. The sub-Saharan Africa position statement on the redefinition of fatty liver disease: from NAFLD to MAFLD. J Hepatol 2021;74(5):1256-1258 View Article
  23. Shiha G, Alswat K, Al Khatry M, Sharara AI, Örmeci N, Waked I, et al. Nomenclature and definition of metabolic-associated fatty liver disease: a consensus from the Middle East and north Africa. Lancet Gastroenterol Hepatol 2021;6(1):57-64 View Article
  24. Lin S, Huang J, Wang M, Kumar R, Liu Y, Liu S, et al. Comparison of MAFLD and NAFLD diagnostic criteria in real world. Liver Int 2020;40(9):2082-2089 View Article
  25. Sun DQ, Jin Y, Wang TY, Zheng KI, Rios RS, Zhang HY, et al. MAFLD and risk of CKD. Metabolism 2021;115:154433 View Article
  26. Wai-Sun Wong V, Lai-Hung Wong G, Woo J, Abrigo JM, Ka-Man Chan C, She-Ting Shu S, et al. Impact of the new definition of metabolic associated fatty liver disease on the epidemiology of the disease. Clin Gastroenterol Hepatol 2020 View Article
  27. Li H, Guo M, An Z, Meng J, Jiang J, Song J, et al. Prevalence and risk factors of metabolic associated fatty liver disease in Xinxiang, China. Int J Environ Res Public Health 2020;17(6):1818 View Article
  28. Bai Y, Yang A, Pu H, Dai M, Cheng N, Ding J, et al. Cohort Profile: The China Metal-Exposed Workers Cohort Study (Jinchang Cohort). Int J Epidemiol 2017;46(4):1095-1096e View Article
  29. World Health Organization. The Asia Pacific Perspectives: redefining obesity and its treatment. World Health Organization 2000. Available from: https://www.worldobesity.org/asiapacific
  30. European Association for the Study of the Liver (EASL), European Association for the Study of Diabetes (EASD), European Association for the Study of Obesity (EASO). EASL-EASD-EASO Clinical Practice Guidelines for the management of non-alcoholic fatty liver disease. Diabetologia 2016;59(6):1121-1140 View Article
  31. American Diabetes Association. Classification and diagnosis of diabetes: standards of medical care in diabetes-2018. Diabetes care 2018;41(Suppl 1):S13-S27 View Article
  32. Chinese Joint Committee. Chinese guidelines for prevention and treatment of dyslipidemia in adults (2016 Revision). Chinese Journal of Cardiology 2016;31:937-952
  33. Peng Z, Bai YN, Wang FJ, Li JS, Li HY, Liu YQ, et al. Prevalence and component analysis of metabolic syndrome in Jinchang cohort. Journal of Lanzhou University (Medical Sciences) 2015;41:54-58
  34. Samuel VT, Shulman GI. Nonalcoholic fatty liver disease as a nexus of metabolic and hepatic diseases. Cell Metab 2018;27(1):22-41 View Article
  35. Chalasani N, Younossi Z, Lavine JE, Charlton M, Cusi K, Rinella M, et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases. Hepatology 2018;67(1):328-357 View Article
  36. Yamamura S, Eslam M, Kawaguchi T, Tsutsumi T, Nakano D, Yoshinaga S, et al. MAFLD identifies patients with significant hepatic fibrosis better than NAFLD. Liver Int 2020;40(12):3018-3030 View Article
  37. Wang AY, Dhaliwal J, Mouzaki M. Lean non-alcoholic fatty liver disease. Clin Nutr 2019;38(3):975-981 View Article
Copyright © 2022 Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 4.0 License (CC BY-NC 4.0), permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • Journal of Clinical and Translational Hepatology
  • pISSN 2225-0719
  • eISSN 2310-8819

Article Options

Metrics

Cite this Article

  • © 2024 Xia & He Publishing Inc.
  • Total visits : 2636322
  • Visits today : 2315
Back to Top

Comparing the Diagnostic Criteria of MAFLD and NAFLD in the Chinese Population: A Population-based Prospective Cohort Study

Cheng Yu, Minzhen Wang, Shan Zheng, Miao Xia, Hongyan Yang, Desheng Zhang, Chun Yin, Ning Cheng, Yana Bai
  • Reset Zoom
  • Download TIFF