Prevalence and associated factors of MAFLD in adults with type 2 diabetes

Yifei He; Feng Xiao; Bin Yi; Jin Lu

doi:10.1371/journal.pgph.0003572

. 2024 Dec 30;4(12):e0003572. doi: 10.1371/journal.pgph.0003572

Prevalence and associated factors of MAFLD in adults with type 2 diabetes

Yifei He ^1,^#, Feng Xiao ^2,^#, Bin Yi ^2,^*, Jin Lu ^1,^*

Editor: Collins Otieno Asweto³

PMCID: PMC11684647 PMID: 39775020

Abstract

To estimate the prevalence and associated factors of hepatic steatosis and fibrosis in adults with type 2 diabetes (T2DM) in the United States.Data were retrieved from the 2017‒March 2020 prepandemic cycle of the National Health and Nutritional Examination and Survey (NHANES). The study population included patients with T2DM. The controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) were used to assess hepatic steatosis and fibrosis, respectively. A total of 1,290 T2DM patients were included, 85.2% (1044 patients) of whom presented with hepatic steatosis (CAP>248 dB/m). Among the 1044 T2DM patients with metabolically associated fatty liver disease (MAFLD), 29.5% developed hepatic fibrosis (LSM>8 kPa). Non-Hispanic black individuals (adjusted OR = 0.4008), BMI (adjusted OR = 1.1627), HbA1c (adjusted OR = 1.1450), TG (adjusted OR = 1.2347), HDL (adjusted OR = 0.4981), ALT (adjusted OR = 1.0227), AST (adjusted OR = 0.9396), and albumin (adjusted OR = 1.7030) were independently associated with steatosis. Age (adjusted OR = 1.0300), female sex (adjusted OR = 0.6655), BMI (adjusted OR = 1.1324), AST (adjusted OR = 1.0483), and GGT (adjusted OR = 1.0101) were independently associated with fibrosis. Heart failure was an independent factor associated with advanced fibrosis (adjusted OR = 1.9129) and cirrhosis (adjusted OR = 2.228). In the United States, hepatic steatosis is highly prevalent among T2DM patients, with 29.5% of these patients developing hepatic fibrosis. Some components of metabolic syndrome are related to hepatic steatosis and fibrosis. Moreover, heart failure is an independent factor associated with advanced fibrosis and cirrhosis.

Introduction

With the increasing incidence of obesity and metabolic syndrome worldwide, nonalcoholic fatty liver disease (NAFLD) has become the leading cause of chronic liver disease in developed regions [1]. NAFLD is most closely related to the mortality of chronic liver disease and is even the major indication for liver transplantation [2]. In the past 20 years, numerous studies have clearly shown that NAFLD is a liver manifestation of a systemic metabolic disorder and is, in fact, a metabolic disease [3]. Consequently, the existing name "NAFLD" has been replaced by a new landmark term, "metabolically associated fatty liver disease" (MAFLD) [4, 5]. The significant difference between MAFLD and NAFLD is that the diagnosis of MAFLD does not require the exclusion of alcohol consumption [6]. This implies that individuals with metabolic disorders, regardless of heavy alcohol intake or hepatitis virus infection, are classified under MAFLD. Consequently, the prevalence of MAFLD may be greater than that of NAFLD, warranting recalibration. In accordance with the diagnostic criteria for MAFLD, we conducted an analysis of prevalence statistics and associated factors related to this condition.

To be diagnosed with MAFLD, patients must first meet one or more of the following criteria: obesity or overweight, type 2 diabetes mellitus, and metabolic disorders. These conditions can be identified through blood biochemistry tests, anthropometric measurements, or medical history inquiries. Second, there must be evidence of steatosis or fibrosis in the liver. Liver biopsy is considered the gold standard for diagnosis [7], but it is an invasive operation with obvious complications and shortcomings. As a result, the following non-invasive methods have received considerable attention [8, 9]: (1) hematological tests (serum fibrosis markers, laboratory tests); (2) methods to assess the physical properties of liver tissue (liver stiffness, degree of attenuation, viscosity); and (3) assessment of imaging of the liver and other abdominal organ learning methods.

Transient elastography (TE) is the most widely used noninvasive examination in the United States [10]. It is performed quickly and can be easily repeated. Furthermore, meta-analyses have shown that TE results have significant prognostic value [11], and the FDA has approved it as a test to evaluate liver fibrosis. TE incorporates two physical parameters: the controlled attenuation parameter (CAP) [12] and liver stiffness measurement (LSM) [13]. The CAP is a promising rapid and standardized instantaneous detection index of hepatic steatosis [14]. It ranges from 100–400 dB/m. A large meta-analysis revealed that the three values of 248 dB/m, 268 dB/m and 280 dB/m represent 5–10%, 33%, and 66% steatosis, respectively. The sensitivity and specificity of these values are 69%, 77%, and 88% and 82%, 81%, and 78%, respectively [15]. Therefore, in our study, MAFLD was also defined as a CAP≥248 dB/m, 268 dB/m, and 280 dB/m, which are considered indicative of moderate hepatic steatosis and severe hepatic steatosis. LSM reflects liver hardness. In a systematic evaluation comparing TE and biopsy for the detection of severe liver fibrosis, the overall sensitivity and specificity were 82% and 86%, respectively [16]. LSM is also included in the examination of the NHANES database during the 2017–March 2020 prepandemic cycle, and 14,400 out of 15,660 people underwent this examination. The guidelines [17] recommend the use of an LSM>8 kPa to diagnose liver fibrosis, with 9.6 kPa and 13 kPa as the cutoff values for medium-term and late fibrosis, respectively. Our study also adopted these cutoff values [18].

The National Health and Nutritional Examination and Survey(NHANES) [19] is a nationally representative public database that collects considerable medical and health information about Americans, including demographic, socioeconomic, dietary and health-related issues. TE is a new project in the NHANES database. At present, no article describes the use of TE to assess the prevalence of MAFLD in patients with T2DM. Our study fills this gap. We also identified independent factors associated with the development of MAFLD in these patients.

Study design and methods

This was a cross-sectional study. Population data were collected from the 2017–March 2020 pre-pandemic cycle of the NHANES; these data are the latest data currently available in the database. The data for the NHANES 2019–2020 cycle were incomplete, as data collection was suspended due to the start of the coronavirus epidemic in 2019; therefore, these data were integrated into the 2017–2018 cycle to form the 2017–March 2020 prepandemic cycle. The Research Ethics Review Board of the Centers for Disease Control and Prevention approved all surveys and medical examinations, and the respondents provided written informed consent.

A total of 15,560 individuals participated in the surveys and medical examinations, and we excluded participants who did not undergo TE (N = 5277) or MEC (N = 1260) assessment, leaving 9,023 people. Among these people, 7733 individuals were excluded because they did not meet the criteria for a diagnosis of T2DM (HbA1c ≤ 6.5%, fasting blood glucose ≤ 7 mmol/l, other types of diabetes, age ≤18Y, and absence of a history of T2DM). In total, 1290 participants with T2DM were included in the study. In addition, we selected 1044 patients with both T2DM and MAFLD to calculate the prevalence of fibrosis in those individuals (Fig 1).

The basic characteristics, complications and habits were collected via questionnaire. The basic characteristics included age, sex, and race. The complications included hypertension, stroke, coronary heart disease, renal insufficiency, heart failure, and diabetic retinopathy. Habits included alcohol consumption.

The laboratory biochemical tests included metabolism-related indicators and liver sclerosis indicators. Glycosylated hemoglobin, (HbA1c), total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), and uric acid (UA) levels were measured and used as metabolism-related indicators. Alanine aminotransferase (ALT), aspartate aminotransferase (AST), glutamyl transpeptidase (GGT), platelet (PLT), and albumin levels were measured and used as liver sclerosis indicators. All biochemical blood tests were performed with patients in a fasted condition.

The anthropometric measurements used in our research included weight and height. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared and then rounded to one decimal place.

Liver ultrasound transient elastography

The NHANES Mobile Examination Centre (MEC) has used the FibroScan 502 V2 Touch model for TE examination since 2017. The machine is equipped with medium (M) or ultralarge (XL) rods (probes). To obtain accurate data, the TE test must meet all of the following criteria: subjects fasted for more than 3 hours, 10 or more complete hardness (E) measurements, and a liver hardness interquartile range (IQRe)/median E < 30%.

Statistical analysis

All the statistical data were obtained with Empowerstats software (www.empowerstats.com; X&Y Solutions, Inc., Boston MA). Due to population bias, prevalence statistics were performed with NHANES MEC weights as suggested by the National Center for Health Statistics and were calculated via the following formula. To describe the basic information of the population, categorical variables are expressed as percentages, and the chi-square test was used to compare the differences between different groups. Continuous variables are expressed as the mean ± standard deviation, and linear regression analysis was used to compare the differences between different groups. After adjusting for confounding factors, logistic regression was used to analyze the effects of different variables on hepatic steatosis and hepatic fibrosis. p <0.05 was considered to indicate a statistically significant difference.

\begin{array}{l} w_{i}, M E C = w_{i} (b a s e, M E C) f_{i} (N R, M E C) f_{i} (T R, M E C) f_{i} (C, M E C) = w_{i} (b a s e, s c r e e n e r) \\ f_{i} (N R, s c r e e n e r) f_{i} (T R, s c r e e n e r) \end{array}

f_{i} (N R, i n t e r v i e w) f_{i} (T R, i n t e r v i e w) f_{i} (C, i n t e r v i e w) f_{i} (N R, M E C) f_{i} (T R, M E C) f_{i} (C, M E C)

Results

Weighted prevalence of hepatic steatosis and fibrosis

In this study, a total of 1290 T2DM patients were screened from 15560 Americans. According to the CAP cut-off in Fig 2A, these patients were divided into four groups: nonadipose tissue (S0, CAP≤248 dB/m), mild steatosis (S1, 248 dB/m<CAP≤268 dB/m), moderate steatosis (S2, 268 dB/m<CAP≤280 dB/m) and severe steatosis (S3, CAP>280 dB/m). A total of 1044 patients had hepatic steatosis (S1–S3), the weighted prevalence rate was 85.2%, and the weighted prevalence rates of S1-, S2- and S3-grade steatosis were 8%, 6.2%, and 70.9%, respectively. As shown in Fig 2B, 1044 T2DM patients with hepatic steatosis (S1–S3) were divided into four groups based on LSM values: mild fibrosis (F0–F1, LSM≤8 kPa), significant fibrosis (F2, 8 kPa<LSM≤9.6 kPa), advanced fibrosis (F3, 9.6 kPa<LSM≤13 kPa) and cirrhosis (F4, LSM>13 kPa). The overall weighted prevalence of fibrosis (F2-F4) was estimated to be 29.5%, and the weighted prevalence rates of grades F2 and F3 fibrosis were 11.4% and 7.7%, respectively. In total, 91 patients developed cirrhosis (F4), with a weighted prevalence rate of 10.4%.

Characteristics of the participants stratified by CAP

All participants (1290 T2DM patients) were divided into four groups based on their CAP values, as shown in Table 1. Age, BMI, HbA1c, TG, HDL, ALT, AST, GGT, albumin, occurrence of CVD, and occurrence of HF were significantly different (all P < 0.05). In addition, the proportion of Mexican Americans and non-Hispanic whites increased with increasing steatosis, whereas the proportion of non-Hispanic blacks was the opposite.

Table 1. Features of the study population according to CAP values.

	Total (n = 1290)	CAP (dB/m)
	Total (n = 1290)	≤248 248–268 268–280 >280 (n = 246) (n = 125) (n = 81) (n = 838)				P value
Age(years)	60.6± 12.9	64.2 ± 13.2	61.7 ± 11.5	62.7 ± 13.7	59.5 ± 12.8	<0.0001
Gender(%)						0.0817
Male	54.2	55.7	42.5	51.1	55.4
Female	45.8	44.3	57.5	48.9	44.6
Race(%)						0.0002
Mexican American	9.9	6.1	6.8	10.5	11
Other Hispanic	7.6	7.6	10.3	4.4	7.5
Non-Hipanic White	56.5	49.7	51.2	59.5	58.2
Non-Hipanic Black	13.4	24.3	19.5	14.9	10.2
Other Race	12.7	12.3	12.2	10.6	13
BMI(kg/m2)	33.0±7.1	27.5 ± 5.4	31.1 ± 6.4	30.3 ± 4.9	34.6 ± 7.0	<0.0001
HbA1c(%)	7.3 ± 1.5	6.9 ± 1.3	7.1 ± 1.6	7.0 ± 1.3	7.5 ± 1.6	<0.0001
TC(mmol/l)	4.6 ± 1.2	4.5 ± 1.2	4.4 ± 1.2	4.5 ± 1.0	4.6 ± 1.2	0.2231
TG(mmol/l)	1.7 ± 1.4	1.1 ± 0.5	1.6 ± 1.6	1.5 ± 0.7	1.9 ± 1.5	<0.0001
HDL(mmol/l)	1.2 ± 0.3	1.4 ± 0.4	1.2 ± 0.4	1.2 ± 0.3	1.2 ± 0.3	<0.0001
UA(mmol/l)	333.0 ± 93.6	325.2 ± 100.1	319.9 ± 86.6	332.2 ± 71.7	336.2 ±94.4	0.2315
ALT(U/L)	24.9 ± 17.7	17.9 ± 10.6	19.5 ± 14.3	21.9 ± 15.3	27.3 ± 18.8	<0.0001
AST(U/L)	22.1 ± 13.0	19.2 ± 9.2	20.2 ± 10.6	20.2 ± 8.0	23.1 ± 14.1	0.0004
GGT(U/L)	38.3 ± 45.6	28.7 ± 34.6	34.1 ± 58.7	29.6 ± 17.7	41.6 ± 47.2	0.0008
PLT (10⁹/L)	241.8 ± 68.7	238.42± 66.9	250.3 ± 71.6	231.7± 60.2	242.7 ±69.7	0.2819
Albumin (g/dl)	4.00± 0.34	4.0 ± 0.4	4.0± 0.4	4.13 ± 0.36	3.9 ± 0.33	0.0038
Hypertension(%)	67.9	68.2	63.3	62	68.9	0.7486
CVD(%)	12.2	12.8	3.8	6.8	13.5	0.0017
HF(%)	7.12	3.4	4.9	0.6	8.7	0.0237
Stroke(%)	9.26	10.6	10.5	8.6	8.9	0.5301
CKD(%)	7.4	9.5	7.5	6.0	7.1	0.6060
DR(%)	18.4	23.9	18.7	25.2	16.8	0.0772
Alcohol(%)	90.4	90.7	96.8	90.7	89.5	0.1676

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BMI-body mass index;HbA1c-glycosylated hemoglobin;TC-total cholesterol;TG-triglyceride;HDL-high density lipoprotein;UA-uric acid;ALT-talanine aminotransferase;AST-aspartate aminotransferase; GGT-glutamyltranspeptidase;PLT-platelet;CVD-coronary;HF -heart failure;CKD-renal insufficiency; DR-diabetes retinopathy

Characteristics of the participants stratified by LSM

All 1044 T2DM patients with MAFLD were divided into four groups based on their LSM values, as shown in Table 2. Among the different groups, BMI, HDL, UA, ALT, AST, GGT, PLT, occurrence of stroke, and occurrence of HF were significantly different (all P < 0.05).

Table 2. Features of the study population according to LSM values.

	Total (n = 1044)	LSM (kPa)
	Total (n = 1044)	≤8 8–9.6 9.6–13 >13 (n = 106) (n = 94) (n = 81) (n = 763)				P value
Age(years)	59.8 ± 12.7	60.0 ± 12.8	58.3 ± 11.4	59.6 ± 14.2	60.1 ± 11.5	0.6090
Gender(%)						0.1829
Male	53.93	51.9	61.7	36.7	57
Female	46.07	48.1	38.3	43.3	43
Race(%)						0.5030
Mexican American	10.73	10.6	10.4	12.9	10.3
Other Hispanic	7.66	7.4	6.5	12.2	7.5
Non-Hipanic White	57.18	56.2	61.6	53	62.7
Non-Hipanic Black	11.60	13	9.4	11.6	4.6
Other Race	12.82	12.8	12.6	10.3	15
BMI(kg/m2)	40.0 ± 6.9	32.7 ± 6.3	35.9 ± 6.5	36.8 ± 6.8	39.1 ± 8.8	<0.0001
HbA1c(%)	7.4 ± 1.6	7.4 ± 1.6	7.6 ± 1.6	7.5 ± 1.7	7.3 ± 1.3	0.4010
TC(mmol/l)	4.6 ± 1.2	4.6 ± 1.2	4.6 ± 1.2	4.3 ± 1.1	4.7 ± 1.2	0.1902
TG(mmol/l)	1.8 ± 1.5	1.8 ± 1.3	2.1 ± 2.2	2.0 ± 2.1	1.6 ± 1.0	0.2777
HDL(mmol/l)	1.2 ± 0.3	1.2 ± 0.3	1.1 ± 0.3	1.1 ± 0.3	1.1 ± 0.3	0.0118
UA(mmol/l)	334.3 ± 92.3	327.8 ± 93.7	341.4 ± 79.5	344.9 ±102.5	360.4 ±84.6	0.0031
ALT(U/L)	26.2 ± 18.3	23.9 ± 15.4	31.6 ± 17.7	30.1 ± 18.5	33.2 ± 29.7	<0.0001
AST(U/L)	22.6± 13.5	20.5 ± 8.5	25.8 ± 11.8	25.4 ± 14.4	31.0 ± 28.8	<0.0001
GGT(U/L)	40.0 ± 47.0	33.0 ± 32.5	45.9 ± 47.6	52.7 ± 54.4	71.7 ± 89.1	<0.0001
PLT (10⁹/L)	242.3 ± 69.1	246.0 ± 69.4	236.8 ± 68.9	246.2 ± 64.4	223.3 ± 68.9	0.0101
Albumin (g/dl)	4.0 ± 0.3	4.0 ± 0.3	4.0 ± 0.3	4.0 ± 0.3	4.0 ± 0.4	0.2930
Hypertension(%)	68.1	65.8	72.5	58.1	68.3	0.3794
CVD(%)	12.2	11.6	8.0	20.1	13.4	0.1545
HF(%)	7.9	6.5	5.1	5.6	21.8	<0.0001
Stroke(%)	8.9	9.2	7.2	5.6	11.3	0.004
CKD(%)	7.1	6.70	4.32	13.3	8.04	0.2263
DR(%)	17.3	17.1	11.1	25.7	18.8	0.3618
Alcohol(%)	90.3	90.0	91.5	97.2	85.6	0.0761

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Factors associated with steatosis and fibrosis

As shown in Table 3, we used CAP>248 dB/m as the cutoff point for hepatic steatosis. Logical analysis revealed that BMI (adjusted OR = 1.1627, 95% CI: 1.1245, 1.2023), HbA1c (adjusted OR = 1.1450, 95% CI: 1.0267, 1.2770), TG (adjusted OR = 1.2347, 95% CI: 1.0183, 1.4971), and ALT (adjusted OR = 1.0227 CI: 1.0070, 1.0387) were positively associated with hepatic steatosis, while non-Hispanic black individuals (adjusted OR = 0.4008, 95% CI: 0.2273, 0.7067), HDL (adjusted OR = 0.4981, 95% CI: 0.3024, 0.8206), and AST (adjusted OR = 0.9396, 95% CI: 0.9139, 0.9660) were negatively associated with hepatic steatosis. As shown in Table 4, we used LSM>8 kPa as the cutoff point for hepatic fibrosis; age (adjusted OR = 1.0300, 95% CI: 1.0149, 1.0452), BMI (adjusted OR = 1.1324, 95% CI: 1.1037, 1.1619), AST (adjusted OR = 1.0483, 95% CI: 1.0198, 1.0776), and GGT (adjusted OR = 1.0101, 95% CI: 1.0057, 1.0144) were positively associated with hepatic fibrosis, whereas female sex (adjusted OR = 0.6655, 95% CI: 0.4713, 0.9398) was negatively associated with hepatic fibrosis.

Table 3. Analysis of the different variables involved in the occurrence of hepatic steatosis.

Variables	OR1	Non-adjusted	P value	OR2	Adjusted^*	P value
Age(years)	0.9732	(0.9616, 0.9849)	<0.0001	0.9962	(0.9815, 1.0111)	0.2786
Gender(%)
Male	1			1
Female	1.0716	(0.8107, 1.4164)	0.6271	1.1582	(0.8174, 1.6411)	0.4087
Race
Mexican American	1
Other Hispanic	0.7065	(0.3781,1.3202)	0.2760	0.7919	(0.39431.5904)	0.5119
Non-HipanicWhite	0.8249	(0.4842,1.4054)	0.4788	0.9373	(0.5150,1.7060)	0.8321
Non-Hipanic Black	0.3624	(0.2198,0.5978)	<0.0001	0.4008	(0.2273,0.7067)	0.0015
Other Race	0.6029	(0.3457,1.0513)	0.0744	1.0576	(0.5689,1.9658)	0.8595
BMI(kg/m2)	1.1662	(1.1320, 1.2014)	<0.0001	1.1627	(1.1245, 1.2023)	<0.0001
HbA1c(%)	1.1729	(1.0641, 1.2930)	0.0013	1.1450	(1.0267, 1.2770)	0.0149
TC(mmol/l)	1.1312	(1.5142, 6.9236)	0.0527	1.0087	(0.8547, 1.1904)	0.9187
TG(mmol/l)	1.8299	(1.5006, 2.2314)	<0.0001	1.2347	(1.0183, 1.4971)	0.0320
HDL(mmol/l)	0.2473	(0.1669, 0.3665)	<0.0001	0.4981	(0.3024, 0.8206)	0.0062
UA(mmol/l)	1.0015	(0.0213, 0.0913)	0.0209	0.9983	(0.9980, 1.0017)	0.3009
ALT(U/L)	1.0373	(1.0227, 1.0522)	<0.0001	1.0227	(1.0070, 1.0387)	0.0045
AST(U/L)	1.0101	(0.9967, 1.0237)	0.1399	0.9396	(0.9139, 0.9660)	<0.0001
GGT(U/L)	1.0062	(1.0014, 1.0110)	0.0109	1.0007	(0.9096, 1.0040)	0.9965
PLT(109/L)	1.0025	(1.0004, 1.0046)	0.0209	1.0013	(0.9988, 1.0038)	0.3009
Albumin (g/dl)	1.2142	(0.8054, 1.8305)	0.3541	1.7030	((1.0335, 2.806)	0.0366
Hypertension	0.8755	(0.6476, 1.1837)	0.3875	0.8964	(0.6024, 1.2548)	0.4548
CVD	0.9976	(0.6245, 1.5936)	0.9919	0.8491	(0.4442, 1.6229)	0.6923
HF	1.2220	(0.6899, 2.1643)	0.4918	1.3084	(0.6712, 2.5506)	0.4299
Stroke	0.5867	(0.3804,0.9050)	0.0158	0.7314	(0.4366, 1.2252)	0.2346
CKD	0.6248	(0.4012,0.9731)	0.0374	0.8897	(0.5115, 1.5473)	0.6788
DR	0.6245	(0.4369,0.8928)	0.0098	0.7089	(0.4654,1.0798)	0.1091
Alcohol	1.2499	(0.8051, 1.9404)	0.3203	1.5261	(0.9174, 2.5386)	0.1035

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BMI-body mass index;HbA1c-glycosylated hemoglobin;TC-total cholesterol;TG-triglyceride;HDL-high density lipoprotein; UA-uric acid;ALT-talanine aminotransferase;AST-aspartate aminotransferase; GGT-glutamyltranspeptidase;PLT-platelet;CVD-coronary;HF -heart failure;CKD-renal insufficiency; DR-diabetes retinopathy.

*Models were adjusted for age, sex,race.BMI,HbA1c,TG,HDL,ALT, GGT

Table 4. Analysis of the various variables involved in the occurrence of hepatic fibrosis.

Variables	OR1	Non-adjusted	P value	OR2	Adjusted^*	P value
Age(years)	0.9942	(0.9835, 1.0050)	0.2912	1.0300	(1.0149, 1.0452)	<0.0001
Gender(%)
Male	1			1
Female	0.7499	(0.5688, 0.9886)	0.0412	0.6655	(0.4713, 0.9398)	0.0207
Race
Mexican American	1
Other Hispanic	1.0701	(0.6292, 1.8199)	0.8026	1.0408	(0.5725, 1.8922)	0.8956
Non-HipanicWhite	1.1100	(0.7221, 1.70635)	0.6341	0.9158	(0.5588, 1.5009)	0.7272
Non-Hipanic Black	1.0705	(0.5328, 1.3162)	0.4417	0.6690	(0.3952, 1.1326)	0.1345
Other Race	0.6568	(0.6643, 1.7251)	0.7794	1.5609	(0.9037, 2.6961)	0.1102
BMI(kg/m2)	1.0944	(1.0726, 1.1167)	0.6341	1.1324	(1.1037, 1.1619)	<0.0001
HbA1c(%)	1.0612	(0.9801, 1.1491)	0.4417	1.0537	(0.9537, 1.1642)	0.3040
TC(mmol/l)	0.9126	(0.8096, 1.0288)	0.1346	0.9293	(0.7953, 1.0859)	0.3559
TG(mmol/l)	1.1002	(1.0192, 1.1876)	0.0143	1.0189	(0.9233, 1.1245)	0.7092
HDL(mmol/l)	0.4738	(0.2971, 0.7556)	0.0017	0.6642	(0.3648, 1.2093)	0.1807
UA(mmol/l)	1.0026	(1.0012, 1.0041)	0.0003	1.0007	(0.9989, 1.0024)	0.4571
ALT(U/L)	1.0226	(1.0148, 1.0305)	<0.0001	0.9900	(0.9720, 1.0084)	0.2841
AST(U/L)	1.0463	(1.0323, 1.0605)	<0.0001	1.0483	(1.0198, 1.0776)	0.0008
GGT(U/L)	1.0129	(1.0091, 1.0168)	<0.0001	1.0101	(1.0057, 1.0144)	<0.0001
PLT(109/L)	0.9988	(0.9968, 1.0008)	0.2364	1.0000	(0.9976, 1.0024)	0.9995
Albumin(g/dl)	0.6792	(0.4532, 1.0178)	0.0608	0.9011	(0.5381, 1.5089)	0.6921
Hypertension	1.2604	(0.9359, 1.6976)	0.1275	1.1624	(0.8120, 1.6641)	0.4109
CVD	1.1383	(0.7259, 1.7851)	0.5724	0.9391	(0.5556, 1.5874)	0.8145
HF	1.6187	(0.9955, 2.6319)	0.4109	1.2960	(0.7476, 2.2466)	0.4109
Stroke	1.1824	(0.6895, 1.8437)	0.5383	1.4005	(0.7665, 2.3953)	0.2533
CKD	1.2468	(0.7672, 2.0260)	0.3732	1.2385	(0.7086, 2.1646)	0.4527
DR	0.9003	(0.6024, 1.3455)	0.6083	1.0718	(0.6780, 1.6941)	0.7667
Alcohol	1.1407	(0.7095, 1.8341)	0.5867	0.6951	(0.4000, 1.2081)	0.1972

Open in a new tab

BMI-body mass index;HbA1c-glycosylated hemoglobin;TC-total cholesterol;TG-triglyceride;HDL-high density lipoprotein; UA-uric acid;ALT-talanine aminotransferase;AST-aspartate aminotransferase; GGT-glutamyltranspeptidase;PLT-platelet;CVD-coronary;HF -heart failure;CKD-renal insufficiency; DR-diabetes retinopathy.

*Models were adjusted for age, sex,race.BMI,HbA1c,TG,HDL,ALT, GGT

As shown in Table 5, LSM values of 9.6 kPa and 13 kPa were used as the thresholds for advanced fibrosis (F3) and cirrhosis (F4), respectively. Logistic regression analysis revealed that the occurrence of heart failure in patients with advanced fibrosis (F3) was 1.9129 times greater (adjusted OR = 1.9129, 95% CI: 1.0771, 3.3974) than those without advanced fibrosis. Furthermore, individuals with liver cirrhosis (F4) presented a 2.2289-fold increase in the occurrence of heart failure (adjusted OR = 2.2289, 95% CI: 1.0900, 4.5578). Additionally, other factors, such as BMI, ALT, AST, and GGT, were identified as independent predictors of both advanced fibrosis (F3) and cirrhosis (F4).

Table 5. Analysis of the various variables involved in the occurrence of advanced fibrosis (F3) and cirrhosis (F4).

Variables	OR¹	Adjusted^*	P value	OR²	Adjusted*	P value
BMI	1.1205	(1.0911, 1.1508)	<0.0001	1.1218	(1.0849, 1.1600)	<0.0001
HDL	0.5949	(0.2969, 1.1918)	0.1429	0.8077	(0.3070, 2.1254)	0.6653
ALT	1.0244	(1.0150, 1.0339)	<0.0001	1.0238	(1.0133, 1.0343)	<0.0001
UA	0.9999	(0.9979, 1.0019)	0.9154	0.9997	(0.9969, 1.0024)	0.8055
AST	1.0776	(1.0401, 1.1164)	<0.0001	1.0537	(1.0250, 1.0833)	0.0002
GGT	1.0087	(1.0050, 1.0123)	<0.0001	1.0109	(1.0067, 1.0151)	<0.0001
PLT	0.9982	(0.9954, 1.0011)	0.2266	0.9951	(0.9909, 0.9993)	0.0217
HF	1.9129	(1.0771, 3.3974)	0.0268	2.2289	(1.0900, 4.5578)	0.0280
Stroke	1.3019	(0.6790, 2.4961)	0.4269	1.6984	(0.7407, 3.8944)	0.2109

Open in a new tab

BMI-body mass index;HDL-high density lipoprotein;UA-uric acid;ALT-talanine aminotransferase;AST-aspartate aminotransferase; GGT-glutamyltranspeptidase; HF -heart failure;OR1, Logistic regression analysis for binary classification with LSM value of 6.9 kPa; OR2, Logistic regression analysis for binary classification with LSM value of 13kPa.

*Models were adjusted for age, sex,race.BMI,HbA1c,TG,HDL,ALT, GGT

Discussion

In our research, all participants were diagnosed with T2DM, and MAFLD was diagnosed when hepatic steatosis was present. Using CAP>248 dB/m as the criterion for hepatic steatosis and LSM> 8 kPa as the criterion for significant fibrosis, we observed that the weighted prevalence of MAFLD in patients with T2DM was notably high at 85.2%, which is higher than the prevalence of NAFLD reported by Li Cho et al. [20]. They conducted a meta-analysis on different diagnostic tools and different ethnic groups to calculate the prevalence of NAFLD in T2DM patients and reported that the highest prevalence was diagnosed by biopsy, reaching 95%, followed by TE, which is similar to our method used in this study, reaching 75%. When stratified by ethnicity, the prevalence of NAFLD in T2DM patients in the Americas was 70%. They also reported a nonalcoholic steatohepatitis (NASH) prevalence of 31.55%, which is not significantly different from our reported 29%.

In the analysis of factors associated with MAFLD, we demonstrated the association of obesity, high blood glucose, high TG, and low HDL with MAFLD. Among these factors, BMI showed the strongest correlation with hepatic steatosis, and these results were consistent with those of previous studies [21, 22] and even showed a greater correlation in the study by Leite et al. [23] (OR: 7.1, 95% CI: 3.0–17.0). There was a slight difference in the incidence of hypertension. Hypertension is widely recognized as a risk factor for MAFLD in the general population [24]. However, several studies [21, 22] based on the NHANES database and our research did not find a correlation between blood pressure and MAFLD. This may be related to the population selected for the NHANES.

Among the metabolic factors related to liver fibrosis, obesity was the only factor that was significantly and independently correlated with liver fibrosis; this close relationship may be attributed to common pathophysiological insulin resistance mechanisms. Kwok et al. [25] also reported this association. Additionally, the authors suggested that the LSM was related to the duration of diabetes, ALT level, urinary albumin/creatinine ratio, and HDL-C level. However, Joseph [26] reported that advanced fibrosis (F3) and cirrhosis (F4) were not associated with obesity but were associated with diabetes duration and HbA1c. The variation in findings may be attributed to the limited data on liver fibrosis in T2DM patients and the fact that these studies were single-center studies. Additionally, it could also be influenced by differences in ethnicities or different states of diabetes, as observed in Joseph and Raymond’s study involving an Asian population.

We also observed that women were less likely to develop MAFLD, while increasing age promoted the development of liver fibrosis. These results are consistent with the risk factors for NAFLD in the general population [27–29]. In addition, ALT, AST, and GGT are recognized as predictors of steatosis and fibrosis.

Limited research has been conducted on the association between liver fibrosis and heart failure in the diabetic population. The findings of this study confirmed an independent and positive relationship between advanced fibrosis (F3), cirrhosis (F4) and heart failure in this patient cohort, even after controlling for potential confounding factors. A study by Yanjian Wang [30] used the noninvasive biomarker Fibrosis NASH Index (FNI) to assess liver fibrosis and reported a significantly increased risk of HF with pEF (OR 1.59, 95% CI 1.22–2.08) in patients with type 2 diabetes who also had advanced liver fibrosis.

The aforementioned studies on the relationship among liver fibrosis, cirrhosis and heart failure were all cross-sectional studies, which were unable to determine the causal relationship among these conditions. We believe that they share common causative factors and are part of a pathophysiological continuum [31]. The pathogenesis of diabetes, such as the release of inflammatory factors, insulin resistance, and oxidative stress, can affect the development and severity of fatty liver disease and may directly promote the occurrence of heart disease and heart failure. In a hyperglycemic state, the release of inflammatory factors such as IL-6, TNF-α, IL-8, and IL-1β can activate hepatic stellate cells and Kupffer cells, causing liver fibrosis [32], and can also stimulate cardiac fibroblasts, exacerbating myocardial fibrosis [33]. Insulin resistance is the core pathogenesis of MAFLD [34] and simultaneously leads to disorders of glucose and lipid metabolism, promoting atherosclerosis. ROS are the main products of oxidative stress. Excessive ROS production leads to the activation of hepatic stellate cells, causing liver fibrosis [35]. It can also promote the transformation of macrophages into foam cells, which is a key step in the progression of atherosclerotic lesions [36].

In addition to the common factors mentioned above, these two diseases can also mutually promote each other [37]. The mechanism by which heart failure leads to liver fibrosis is related to liver congestion and hypoxia-reperfusion injury. During heart failure, the pressure in the superior and inferior vena cava increases, resulting in the obstruction of hepatic vein outflow and causing congestive liver disease [38]. This leads to an increase in hepatic sinus pressure, hepatocyte necrosis, and central lobular fibrosis, ultimately leading to cirrhosis. Another possible situation is that hypoxia causes continuous low perfusion, resulting in ischemic necrosis of hepatocytes [39]. The increased risk of heart failure due to liver fibrosis is associated with the exacerbation of insulin resistance in diabetic patients with NAFLD and the increase in pro-inflammatory factors, pro-fibrotic and vasoactive mediators; these factors can promote the development of cardiac and arrhythmic complications [40]. Additionally, liver fibrosis is related to cardiac diastolic dysfunction [41], and the mechanism may be related to the increase in epicardial fat thickness [42].

Although these are the latest data extracted from the NHANES and MAFLD has been redefined according to the latest diagnostic criteria, there are still some limitations in our research. First, the cutoff points of CAP and LSM in elastography have not yet been unified [43], leading to variations in morbidity calculations. In addition, only five subjects were infected with hepatitis B or C, so we did not analyze them. In addition, we found no correlation between alcohol consumption and MAFLD when the quantity of alcohol consumed was used as a continuous variable. Finally, prospective studies are needed to clarify the causal relationships, such as those between BMI and heart failure in relation to liver fibrosis.

In conclusion, the data from the NHANES database represent the characteristics of the American population and show that patients with T2DM have a greater prevalence of MAFLD than NAFLD. In these populations, poor blood sugar control, high TG, low HDL, and overweight or obesity are associated factors for MAFLD. Furthermore, our study revealed that only obesity is an independent factor associated with liver fibrosis. Additionally, we observed a significant association between heart failure and advanced fibrosis (F3) and liver cirrhosis (F4). These findings serve as reminders that clinical physicians should pay timely attention to the impact of heart failure on liver fibrosis in MAFLD patients.

Data Availability

All relevant data for this study are publicly available from the Dryad repository (https://doi.org/10.5061/dryad.dz08kps5g). This study is based on the data set can openly share, because they are derived from nhanes database (https://www.cdc.gov/nchs/nhanes/index.htm), it's free public database.

Funding Statement

This work was funded by a grant from Changhai Hospital (234 Discipline Climbing Plan) Grant ID: 2019YXK021 to JL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0003572.r001

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Prevalence and Factors Associated with MAFLD in Adults with Type 2 Diabetes (T2DM)

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PLOS Global Public Health does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: No

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: General comments:

• This cross-sectional study has very interesting findings for clinical practice and future studies. I congratulate the authors for their work on the predictors of steatosis and fibrosis amongst adult T2DM patients with MAFLD. The statistical analysis was great, the findings and discussions were well presented.

• There are grammatical errors that need correction to ensure readability and clarity. The entire manuscript requires serious proofreading.

o Page 5: under introduction, rephrase reference [1] by removing the ‘’.’’ Between syndrome and NAFLD and replace with a comma ‘’,’’. Also write NAFLD in full (Non-Alcoholic Fatty Liver Disease).

o Page 6: reference 6 should be rephrase e.g: To diagnose MAFLD, patients must first meet one or more of the following conditions: obesity or overweight, diabetes mellitus, metabolic disorders, which can be determined through blood biochemistry tests, anthropometric measurements, or medical history inquiries. Secondly, there must be evidence of steatosis or fibrosis in the liver. Liver biopsy remains the gold standard for diagnosis…….

o Page 7: include ‘’respectively’’ after 78% in reference 14 in relation to sensitivity and specificity.

o Check: Alcoal(%)

o Page 19, line 3: correct ‘’stuties’’ to ‘’studies’’ in relation to references 23 and 24 and also correct repetition after reference 27-29.

o Page 20, line 13 needs correction of the typo

o There is no need to have ‘’ Funding None. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.’’ After the conclusion since it is to be reflected in the matrix on page 1.

• The lingering issue is the relationship between advanced fibrosis/cirrhosis and heart failure (causality or a consequence) and the pathogenesis/pathophysiology involved.

Reviewer #2: The manuscript is technically deficient as the authors do not know what they are doing based on what is written in the abstract (logistic regression) and statistical analysis (linear regression). The weighted analysis is not described well. It also has many grammatical errors that could have been checked before submitting.

Reviewer #3: The study to look in to: Prevalence and factors associated with MAFLD in adults with T2DM- the flow and presentation including justification, what is known and what the authors found is not clear. As it is a cross-sectional study, it is difficult to validate the findings presented as association between MAFLD and other factors. The association presented with increased prevalence of HF and Liver Fibrosis in adults with T2DM is not presented clearly to justify and validate the results.

It was not easy to read as the grammar and language including spellings need revision.

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6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Shital Bhandary

Reviewer #3: Yes: Somasundari Gopalakrishnan

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLOS Glob Public Health. 2024 Dec 30;4(12):e0003572. doi: 10.1371/journal.pgph.0003572.r002

Author response to Decision Letter 0

27 Jul 2024

Attachment

Submitted filename: renamed_e7c21.docx

pgph.0003572.s001.docx^{(27.9KB, docx)}

PLOS Glob Public Health. doi: 10.1371/journal.pgph.0003572.r003

Decision Letter 1

Collins Otieno Asweto

16 Sep 2024

PGPH-D-24-00927R1

Prevalence and Factors Associated with MAFLD in Adults with Type 2 Diabetes (T2DM)

PLOS Global Public Health

Dear Bin

Please submit your revised manuscript by 16th October 2024. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at globalpubhealth@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pgph/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Collins Otieno Asweto, PhD

Academic Editor

PLOS Global Public Health

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #4: All comments have been addressed

Reviewer #5: All comments have been addressed

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2. Does this manuscript meet PLOS Global Public Health’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #4: Yes

Reviewer #5: No

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #4: Yes

Reviewer #5: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

Reviewer #4: Yes

Reviewer #5: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #4: Yes

Reviewer #5: No

**********

6. Review Comments to the Author

Reviewer #4: The findings for the study are well represented and all issues raised by previous reviewers have been adequately addressed. However, the paper has some typos and minimal texts errors that need to be reviewed for clarity a simple proof reading should be able to resolve the issues. I have no further issues with the study.

Reviewer #5: This is an interesting study and the authors are well appreciated for the idea and the statistical analysis. However, the manuscript still needs thorough revision.

1. The introduction section lacks clear idea of what the research problem and gap are .

2. The objective of the study as mentioned, is not limited to Type 2 diabetes thus, the objective should include the association of MAFLD with variables other than Type 2 DM as observed in the statistical analysis and discussion section (eg. Hypertention, cardiac failure etc.)

3. The authors should clearly mention the nature of NHANES survey (cross-sectional or cohort) in the methodology section, as the authors try to establish a causal relationship of MAFLD with diabetes and other factors. If the survey was cross-sectional avoid making causal inferences. Also, justify including Liver function test parameters like ALT and AST as test variables. Raised ALT and AST are not the cause of MAFLD but an indicator of liver disease. There are several other variables whose inclusion into the study as a cause of MAFLD are not justified in the manuscript eg. GGT, Platelets count, HF, stroke etc.

4. The authors should justify that patients who were not classified as having Type 2 diabetes based on their HbA1c and fasting blood glucose levels were not actually cases of controlled diabetes.

5. Please justify why individuals with type 1 DM were excluded from the study.

6. The discussion needs to be re-written to be in line with the objective of the study.

7. Please avoid using the terms prevalence, or incidence in the results and discussion. The authors can rather recommend a randomized trial for causal inference based on the findings of the study.

7. There are numerous errors related grammatical and sentence structure. The whole manuscript needs english language expert editing.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #4: No

Reviewer #5: No

**********

PLOS Glob Public Health. 2024 Dec 30;4(12):e0003572. doi: 10.1371/journal.pgph.0003572.r004

Author response to Decision Letter 1

10 Oct 2024

Attachment

Submitted filename: renamed_fe228.docx

pgph.0003572.s002.docx^{(27.7KB, docx)}

PLOS Glob Public Health. doi: 10.1371/journal.pgph.0003572.r005

Decision Letter 2

Collins Otieno Asweto

5 Nov 2024

Prevalence and Factors Associated with MAFLD in Adults with Type 2 Diabetes (T2DM)

PGPH-D-24-00927R2

Dear Bin yi,

We are pleased to inform you that your manuscript 'Prevalence and Factors Associated with MAFLD in Adults with Type 2 Diabetes (T2DM)' has been provisionally accepted for publication in PLOS Global Public Health.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they'll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact globalpubhealth@plos.org.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Global Public Health.

Best regards,

Collins Otieno Asweto, PhD

Academic Editor

PLOS Global Public Health

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #5: All comments have been addressed

**********

Reviewer #1: Yes

Reviewer #5: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #5: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

Reviewer #1: Yes

Reviewer #5: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #5: Yes

**********

6. Review Comments to the Author

Reviewer #1: Congratulations to the team for responding to all the reviewers' comments and improving the write up for focus and clarity.

Reviewer #5: All comments by the reviewer have been addressed. Considerable improvement in the language has been observed however, there are still some typological and grammatical errors throughout the manuscript.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #5: No

**********

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Attachment

Submitted filename: renamed_e7c21.docx

pgph.0003572.s001.docx^{(27.9KB, docx)}

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Submitted filename: renamed_fe228.docx

pgph.0003572.s002.docx^{(27.7KB, docx)}

Data Availability Statement

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Prevalence and associated factors of MAFLD in adults with type 2 diabetes

Yifei He

Feng Xiao

Bin Yi

Jin Lu

Roles

Abstract

Introduction

Study design and methods

Fig 1. Flow chart of the study.

Liver ultrasound transient elastography

Statistical analysis

Results

Weighted prevalence of hepatic steatosis and fibrosis

Fig 2. Prevalence of hepatic steatosis and fibrosis.

Characteristics of the participants stratified by CAP

Table 1. Features of the study population according to CAP values.

Characteristics of the participants stratified by LSM

Table 2. Features of the study population according to LSM values.

Factors associated with steatosis and fibrosis

Table 3. Analysis of the different variables involved in the occurrence of hepatic steatosis.

Table 4. Analysis of the various variables involved in the occurrence of hepatic fibrosis.

Table 5. Analysis of the various variables involved in the occurrence of advanced fibrosis (F3) and cirrhosis (F4).

Discussion

Data Availability

Funding Statement

References

Decision Letter 0

Collins Otieno Asweto

Roles

Author response to Decision Letter 0

Decision Letter 1

Collins Otieno Asweto

Roles

Author response to Decision Letter 1

Decision Letter 2

Collins Otieno Asweto

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

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RESOURCES

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