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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Endocrinol.</journal-id>
<journal-title>Frontiers in Endocrinology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Endocrinol.</abbrev-journal-title>
<issn pub-type="epub">1664-2392</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fendo.2023.1109673</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Endocrinology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Metabolic dysfunction-associated fatty liver disease increased the risk of subclinical carotid atherosclerosis in China</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Lei</surname>
<given-names>Fang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1580757"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Xiao-Ming</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Changquan</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Huang</surname>
<given-names>Xuewei</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1656151"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liu</surname>
<given-names>Ye-Mao</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/287749"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Qin</surname>
<given-names>Juan-Juan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1551852"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Peng</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/306758"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ji</surname>
<given-names>Yan-Xiao</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>She</surname>
<given-names>Zhi-Gang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/426982"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cai</surname>
<given-names>Jingjing</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/873381"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Li</surname>
<given-names>Huo-ping</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Zhang</surname>
<given-names>Xiao-Jing</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1349923/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Li</surname>
<given-names>Hongliang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/382955"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Cardiology, Renmin Hospital, School of Basic Medical Science, Wuhan University</institution>, <addr-line>Wuhan</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Institute of Model Animal, Wuhan University</institution>, <addr-line>Wuhan</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Neurology, Huanggang Central Hospital of Yangtze University</institution>, <addr-line>Huanggang</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Huanggang Institute of Translational Medicine, Huanggang Central Hospital of Yangtze University</institution>, <addr-line>Huanggang</addr-line>, <country>China</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Department of Cardiology, The Third Xiangya Hospital, Central South University</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>Department of Cardiology, Huanggang Central Hospital of Yangtze University</institution>, <addr-line>Huanggang</addr-line>, <country>China</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>Medical Science Research Center, Zhongnan Hospital of Wuhan University</institution>, <addr-line>Wuhan</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Yanan Wang, Xi&#x2019;an Jiaotong University Health Science Center, China</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Yue Wu, The First Affiliated Hospital of Xi&#x2019;an Jiaotong University, China; Ming-Hua Zheng, First Affiliated Hospital of Wenzhou Medical University, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Hongliang Li, <email xlink:href="mailto:lihl@whu.edu.cn">lihl@whu.edu.cn</email>; Xiao-Jing Zhang, <email xlink:href="mailto:zhangxjing@whu.edu.cn">zhangxjing@whu.edu.cn</email>; Huo-ping Li, <email xlink:href="mailto:lihuoping@hgyy.org.cn">lihuoping@hgyy.org.cn</email>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work and share first authorship</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Cardiovascular Endocrinology, a section of the journal Frontiers in Endocrinology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>04</day>
<month>04</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>14</volume>
<elocation-id>1109673</elocation-id>
<history>
<date date-type="received">
<day>28</day>
<month>11</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>21</day>
<month>03</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Lei, Wang, Wang, Huang, Liu, Qin, Zhang, Ji, She, Cai, Li, Zhang and Li</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Lei, Wang, Wang, Huang, Liu, Qin, Zhang, Ji, She, Cai, Li, Zhang and Li</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Background and aims</title>
<p>Metabolic dysfunction-associated fatty liver disease (MAFLD) was proposed to substitute NAFLD in 2020. This new term highlights the systematic metabolic disturbances that accompany fatty liver. We evaluated the correlations between MAFLD and subclinical carotid atherosclerosis (SCA) based on a nationwide health examination population in China.</p>
</sec>
<sec>
<title>Methods</title>
<p>We performed a nationwide cross-sectional population and a Beijing retrospective cohort from 2009 to 2017. SCA was defined as elevated carotid intima-media thickness. The multivariable logistic and Cox models were used to analyze the association between MAFLD and SCA.</p>
</sec>
<sec>
<title>Results</title>
<p>153,482 participants were included in the cross-sectional study. MAFLD was significantly associated with SCA in fully adjusted models, with an odds ratio of 1.66; 95% confidence interval (CI): 1.62-1.70. This association was consistent in the cohort, with a hazard ratio (HR) of 1.31. The association between baseline MAFLD and incident SCA increased with hepatic steatosis severity. Subgroup analysis showed an interaction between age and MAFLD, with a higher risk in younger groups (HR:1.67, 95% CI: 1.17-2.40).</p>
</sec>
<sec>
<title>Conclusion</title>
<p>In this large cross-section and cohort study, MAFLD was significantly associated with the presence and development of SCA. Further, the risk was higher among MAFLD individuals with high hepatic steatosis index and young adults.</p>
</sec>
</abstract>
<kwd-group>
<kwd>MAFLD</kwd>
<kwd>subclinical carotid atherosclerosis</kwd>
<kwd>CIMT</kwd>
<kwd>association</kwd>
<kwd>hepatic steatosis index</kwd>
</kwd-group>
<counts>
<fig-count count="1"/>
<table-count count="5"/>
<equation-count count="0"/>
<ref-count count="63"/>
<page-count count="11"/>
<word-count count="6359"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Non-alcoholic fatty liver disease (NAFLD) is a highly prevalent metabolic disorder that is tightly associated with the overweight and obesity epidemic worldwide, placing a huge burden on families, individuals, and healthcare systems. The serious complications of NAFLD are not limited to advanced cirrhosis and liver cancer but also lead to cardiovascular diseases (<xref ref-type="bibr" rid="B1">1</xref>&#x2013;<xref ref-type="bibr" rid="B4">4</xref>). Several studies, including retrospective and prospective, have shown that the presence and extent of NAFLD are associated with increased prevalence and incidence of cardiovascular disease (CVD). Our previous meta-analysis demonstrated that nearly 55% of NAFLD patients have CVDs in China (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B6">6</xref>).</p>
<p>Metabolic dysfunction-associated fatty liver disease (MAFLD) was proposed to substitute NAFLD in 2020. This new term highlights the systematic metabolic disturbances that accompany fatty liver. Our previous study based on a nationwide health examination population in China showed that the prevalence of MAFLD rose rapidly from 22.8% to 35.6% in 2009-2017 (<xref ref-type="bibr" rid="B7">7</xref>). Subclinical atherosclerosis was considered a precursor to clinical atherosclerosis and is significantly associated with a high risk of CVDs. Carotid intima-media thickness (CIMT) and carotid plaque were imaging indexes of subclinical carotid atherosclerosis (SCA) (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B9">9</xref>). Previous studies demonstrated that NAFLD was strongly correlated with a high risk of subclinical atherosclerosis (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B10">10</xref>). A meta-analysis of more than 20 cross-sectional studies revealed a strong independent association between NAFLD and subclinical atherosclerosis, demonstrated by CIMT, coronary artery calcification, endothelial dysfunction and arterial stiffness (<xref ref-type="bibr" rid="B11">11</xref>). Furthermore, a community-based cohort showed that during 4.3 years, MAFLD was significantly correlated with a high risk of subclinical atherosclerosis, as demonstrated by CIMT, microalbuminuria, and baPWV (<xref ref-type="bibr" rid="B12">12</xref>). However, evidence regarding the hazards of developing subclinical arteriosclerosis as measured by CIMT and carotid plaque with MAFLD based on a large population in China remains to be explored.</p>
<p>Therefore, we aimed to explore the correlations of a new definition MAFLD and SCA based on a cross-sectional study and a retrospective cohort based on nationwide health examination. Further stratification was conducted to analyze the potential effect of age, sex, and degree of hepatic steatosis on these associations.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Materials and methods</title>
<sec id="s2_1">
<title>Study population</title>
<p>This cross-sectional study was conducted in a nationwide health examination population in China. From January 2011 to December 2017, 153,482 participants aged &#x2265; 18 from 13 health management centers were enrolled. We excluded 4,013 individuals without a complete medical record on MAFLD measurements. Finally, 149,469 populations were included in a cross-sectional study to explore the relationship between MAFLD and SCA (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>The Flowchart Showing the Strategy of Participant Enrollment. A schematic overview illustrating participants enrollment and the exclusion and inclusion criteria. <bold>(A)</bold> The flowchart of the cross-sectional study. <bold>(B)</bold> The flowchart of the cohort.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1109673-g001.tif"/>
</fig>
<p>We conducted a retrospective cohort in the population of a Beijing health management center. The individuals had at least two carotid ultrasound examinations over a one-year follow-up between January 1, 2011 to December 31, 2017 (n=2,205). We excluded subjects without complete medical records (n=3) or a history of coronary heart disease, cancer, or stroke at baseline (n=26). The final sample size was 2,179 for analyzing the correlations of baseline MAFLD and incidence of SCA in the cohort (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1B</bold>
</xref>).</p>
<p>The subjects who attended the check-ups were mixed population from nearby urban and rural areas (<xref ref-type="bibr" rid="B13">13</xref>). The population was mainly adults consisted of population with very diverse socioeconomic and occupational backgrounds, including public services employees, doctors, workers, farmers, self-employed persons, and et&#xa0;al. Over 500 million people with diverse socioeconomic backgrounds (public service employees, workers, self-employed persons, farmers, and others) participate in health examinations in China each year (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B15">15</xref>). The statistics showed that approximately 60% of the participants were encouraged by their employers to undergo health examinations, which were offered free of charge (<xref ref-type="bibr" rid="B15">15</xref>). And Participation in the health examinations was voluntary.</p>
<p>The study was approved by the central ethics board of Renmin Hospital of Wuhan University, followed by the acceptance with the ethics center in each collaborating hospital. Individual identification data was removed, and only anonymous information was kept during the study process. The ethics committees from each hospital waived patient informed consent.</p>
</sec>
<sec id="s2_2">
<title>Data collection</title>
<p>All the participants underwent a detailed physical examination and completed a questionnaire that included personal and family history of disease and medication use in the health examination center. Anthropometric measurements, including height, weight, and waist circumference (WC), were performed by physicians according to standard protocols. Blood pressure (BP) was measured after subjects were quietly seated for 10 minutes. After overnight fasting, routine blood tests, biochemical blood tests, and abdominal ultrasounds were measures as part of the health check-up exam.</p>
<p>T2DM was defined according to the Chinese criteria and personal disease history (<xref ref-type="bibr" rid="B16">16</xref>). Hypertension was defined according to the national guidelines in China and personal disease history (<xref ref-type="bibr" rid="B17">17</xref>). Dyslipidemia was diagnosed according to the guidelines for managing dyslipidemia in adults or using the lipid-lowering drug or self-reported history of dyslipidemia (<xref ref-type="bibr" rid="B18">18</xref>). Hyperuricemia was diagnosed as serum uric acid &#x2265; 420 &#x3bc;mol/L in males and &#x2265; 360 &#x3bc;mol/L in females or using acid-reducing drug (<xref ref-type="bibr" rid="B19">19</xref>). Metabolic syndrome (MetS) was diagnosed according to the consensus criteria in 2009 (<xref ref-type="bibr" rid="B20">20</xref>). The hepatic steatosis index (HSI) was calculated according to the existing equation: HSI = BMI (+2, if diabetes mellitus; +2, if female) + (ALT/AST) &#xd7; 8 (<xref ref-type="bibr" rid="B21">21</xref>). The overall HSI was then categorized into low-, middle-, and high-HSI tertiles according to the tri-sectional quantiles range. The Liver fibrosis was calculated by the fibrosis 4 score (FIB-4) (<xref ref-type="bibr" rid="B22">22</xref>). The estimated glomerular filtration rate (eGFR) was measured using the Modification of Diet in Renal Disease (MDRD) formula (<xref ref-type="bibr" rid="B23">23</xref>). Chronic kidney disease (CKD) was diagnosed as the eGFR&#x2009;&lt;&#x2009;60&#x2009;ml/min/1.73&#x2009;m<sup>2</sup> (<xref ref-type="bibr" rid="B24">24</xref>).</p>
</sec>
<sec id="s2_3">
<title>Definitions of MAFLD</title>
<p>MAFLD was defined by ultrasound-detected hepatic steatosis with evidence of metabolic dysregulation, overweight/obesity (BMI &#x2265; 23 kg/m<sup>2</sup>), or the presence of T2MD. Metabolic dysregulation was defined as two or more metabolic risk abnormalities: a) central obesity: WC &#x2265;90/80 cm in males and females; b) hypertension: BP &#x2265;130/85 mmHg or receiving specific drug treatment; c) TG &#x2265;1.70 mmol/L or receiving specific drug treatment; d) HDL-c &#x2265;1.0/1.3 mmol/L in males and females or receiving specific drug treatment; and e) prediabetes: FBG 5.6 to 6.9 mmol/L or 2-hour post-load glucose 7.8 to 11.0 mmol/L or glycated hemoglobin 5.7% to 6.4% (<xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B26">26</xref>). The diagnosis of hepatic steatosis on ultrasound was based on the presence of hepatorenal echo contrast, liver parenchymal brightness, deep attenuation, and vascular blurring (<xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B27">27</xref>).</p>
</sec>
<sec id="s2_4">
<title>Definitions of subclinical carotid atherosclerosis</title>
<p>The examination of the cervical carotid artery was performed by B-mode ultrasonography. The specific examination sites included bilateral scans of the internal carotid arteries, external carotid arteries, common carotid arteries, and bifurcation sites. We defined elevated CIMT as a CIMT value &gt; 1.2 mm. In any carotid segment, focal wall thickening or CIMT &gt; 1.5 mm was identified as carotid plaque. SCA was diagnosed as having carotid plaque or increased CIMT (<xref ref-type="bibr" rid="B28">28</xref>).</p>
</sec>
<sec id="s2_5">
<title>Statistical analysis</title>
<p>All statistical analyses were performed by R-3.6.3 (R Foundation for Statistical Computing, Vienna, Austria). Continuous variables were reported as means &#xb1; standard deviations (sd) or medians and inter-quartile ranges (IQRs). Categorical variables were reported in absolute numbers (percentages). ANOVA was used for comparisons between groups where the variables were normally distributed, the Mann-Whitney U test was used for comparisons when the variables were nonnormal distribution, and Fisher&#x2019;s exact test or Chi-squared test was used for comparisons when the variables were categorical.</p>
<p>The association between MAFLD and subclinical atherosclerosis was examined using multivariable logistic regression models in the cross-sectional study. The mixed-type random forest model was used to impute the missing data with the assessment of internally cross-validated error (<xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>). In model 1, the adjusted variables for comparison between MAFLD and non-MAFLD groups included age and sex. In model 2, we further adjusted leukocyte count, red blood cell count, platelet count, hemoglobin count, self-reported drinking, self-reported smoking, and comorbidities(coronary heart disease, CKD, stroke and cancer).</p>
<p>Cox proportional hazard regression models were used to evaluate the association between the presence of MAFLD and the development of SCA in the cohort. In model 1, the adjusted variables were age and sex. In model 2, we further adjusted leukocyte count, red blood cell count, platelet count, hemoglobin count, self-reported drinking, self-reported smoking, and CKD, <italic>P</italic> values &lt; 0.05 were considered statistically significant.</p>
<p>P values for trend were calculated by treating HSI by tertile as ordinal in multivariable logistic regression models and Cox regression models. P values for the test of interaction for estimates from separate analyses were used to assess interaction by sex and age for each analysis (<xref ref-type="bibr" rid="B31">31</xref>). All reported P values are two sided and P &lt;.05 was considered statistically significant.</p>
</sec>
<sec id="s2_6">
<title>Sensitivity analyses</title>
<p>Three sensitivity analyses were conducted to confirm the reliability of the relation between baseline MAFLD and new-onset subclinical atherosclerosis in a longitudinal cohort. The sensitivity test I estimated the relation between MAFLD and new-onset SCA with follow-up over two years. The sensitivity test II adjusted FIB-4 to determine the relation between MAFLD and new-onset SCA. The sensitivity test III adjusted dyslipidemia to determine the relation between MAFLD and new-onset SCA.</p>
</sec>
</sec>
<sec id="s3" sec-type="result">
<title>Result</title>
<sec id="s3_1">
<title>Baseline characteristics in the cross-sectional study</title>
<p>The baseline clinical and laboratory characteristics of the cross-sectional study are shown in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>. The mean (SD) age of study participants was 50.83 (10.68) in a total of 149,469 participants. Among them, 77,251 (51.68%) were diagnosed as MAFLD according to the definition. Compared with participants in the non-MAFLD group, participants in the MAFLD group were more likely to be males (71.02% vs. 45.58%), self-reported smokers (15.04% vs. 6.06%) and metabolically unhealthy, with higher BMI (26.95 vs. 23.30 kg/cm<sup>2</sup>), waist circumference (93.5 vs. 81.1 cm), FBG (6.04 vs. 5.36 mmol/L), SBP (130 vs. 122 mmHg), DBP (83 vs. 77 mmHg), LDL-c (3.09 vs. 2.89 mmol/L), TG (2.25 vs. 1.34 mmol/L) and lower level of HDL-c (1.16 vs. 1.40 mmol/L) (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Participants in the MAFLD group with higher HSI, were younger and metabolically unhealthy, with higher BMI, waist circumference, FBG, SBP, DBP, TC, TG, LDL-c and lower levels of HDL-c; and had more comorbidities, such as Type 2 diabetes, Hypertension, MetS, Dyslipidemia, Hyperuricaemia, CHD (<xref ref-type="supplementary-material" rid="ST1">
<bold>Table S1</bold>
</xref>).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Baseline characteristics for the cross-sectional population.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left"/>
<th valign="middle" align="center">Total <break/>N=149,469</th>
<th valign="middle" align="center">Non-MAFLD <break/>N=72,218</th>
<th valign="middle" align="center">MAFLD <break/>N=77,251</th>
<th valign="middle" align="center">
<italic>p value</italic>
<xref ref-type="table-fn" rid="fnT1_1">
<sup>a</sup>
</xref>
</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="bottom" align="left">Age (year, mean (SD))</td>
<td valign="middle" align="center">50.83 (10.68)</td>
<td valign="middle" align="center">50.75 (11.77)</td>
<td valign="middle" align="center">50.91 (9.56)</td>
<td valign="bottom" align="center">0.003</td>
</tr>
<tr>
<td valign="bottom" align="left">Gender, Female, n (%)</td>
<td valign="middle" align="center">61691 (41.27)</td>
<td valign="middle" align="center">39300 (54.42)</td>
<td valign="middle" align="center">22391 (28.98)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">BMI (kg/m<sup>2</sup>, mean (SD))</td>
<td valign="middle" align="center">25.19 (3.52)</td>
<td valign="middle" align="center">23.30 (2.87)</td>
<td valign="middle" align="center">26.95 (3.13)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">WC (cm, mean (SD))</td>
<td valign="middle" align="center">88.6 (10.4)</td>
<td valign="middle" align="center">81.1 (8.5)</td>
<td valign="middle" align="center">93.5 (8.4)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">SBP (mmHg, mean (SD))</td>
<td valign="middle" align="center">126 (19)</td>
<td valign="middle" align="center">122 (19)</td>
<td valign="middle" align="center">130 (18)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">DBP (mmHg, mean (SD))</td>
<td valign="middle" align="center">80 (12)</td>
<td valign="middle" align="center">77 (12)</td>
<td valign="middle" align="center">83 (12)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">Self-reported smoking, n (%)</td>
<td valign="middle" align="center">15996 (10.70)</td>
<td valign="middle" align="center">4375 (6.06)</td>
<td valign="middle" align="center">11621 (15.04)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">Self-reported drinking, n (%)</td>
<td valign="middle" align="center">24747 (16.56)</td>
<td valign="middle" align="center">7497 (10.38)</td>
<td valign="middle" align="center">17250 (22.33)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<th valign="bottom" colspan="5" align="left">Laboratory Examination</th>
</tr>
<tr>
<td valign="bottom" align="left">FBG (mmol/L, mean (SD))</td>
<td valign="middle" align="center">5.71 (1.48)</td>
<td valign="middle" align="center">5.36 (1.13)</td>
<td valign="middle" align="center">6.04 (1.68)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">TC (mmol/L, mean (SD))</td>
<td valign="middle" align="center">4.80 (0.95)</td>
<td valign="middle" align="center">4.71 (0.91)</td>
<td valign="middle" align="center">4.88 (0.97)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">TG (mmol/L, mean (SD))</td>
<td valign="middle" align="center">1.81 (1.50)</td>
<td valign="middle" align="center">1.34 (0.94)</td>
<td valign="middle" align="center">2.25 (1.77)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">HDL-c (mmol/L, mean (SD))</td>
<td valign="middle" align="center">1.28 (0.34)</td>
<td valign="middle" align="center">1.40 (0.35)</td>
<td valign="middle" align="center">1.16 (0.28)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">LDL-c (mmol/L, mean (SD))</td>
<td valign="middle" align="center">3.00 (0.83)</td>
<td valign="middle" align="center">2.89 (0.80)</td>
<td valign="middle" align="center">3.09 (0.84)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">ALT (IU/L, mean (SD))</td>
<td valign="middle" align="center">25.04 (21.40)</td>
<td valign="middle" align="center">20.25 (20.88)</td>
<td valign="middle" align="center">29.51 (20.90)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">AST (IU/L, mean (SD))</td>
<td valign="middle" align="center">21.80 (12.30)</td>
<td valign="middle" align="center">20.78 (12.85)</td>
<td valign="middle" align="center">22.76 (11.68)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">BUN (mmol/L, mean (SD))</td>
<td valign="middle" align="center">4.99 (1.34)</td>
<td valign="middle" align="center">4.84 (1.40)</td>
<td valign="middle" align="center">5.12 (1.28)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">Creatinine (&#x3bc;mol/L, mean (SD))</td>
<td valign="middle" align="center">70.06 (19.26)</td>
<td valign="middle" align="center">68.50 (21.91)</td>
<td valign="middle" align="center">71.52 (16.28)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">Uric acid (&#x3bc;mol/L, mean (SD))</td>
<td valign="middle" align="center">338.15 (89.59)</td>
<td valign="middle" align="center">298.99 (78.90)</td>
<td valign="middle" align="center">366.28 (86.19)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">LEU (&#xd7;10<sup>9</sup>/L, mean (SD))</td>
<td valign="middle" align="center">6.17 (1.65)</td>
<td valign="middle" align="center">5.93 (1.62)</td>
<td valign="middle" align="center">6.40 (1.64)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">RBC (&#xd7;10<sup>12</sup>/L, mean (SD))</td>
<td valign="middle" align="center">4.78 (0.47)</td>
<td valign="middle" align="center">4.66 (0.47)</td>
<td valign="middle" align="center">4.90 (0.44)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">HGB (g/L, mean (SD))</td>
<td valign="middle" align="center">146.65 (15.61)</td>
<td valign="middle" align="center">142.16 (16.07)</td>
<td valign="middle" align="center">150.83 (13.93)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">PLT (&#xd7;10<sup>9</sup>/L, mean (SD))</td>
<td valign="middle" align="center">221.58 (54.61)</td>
<td valign="middle" align="center">220.93 (55.67)</td>
<td valign="middle" align="center">222.19 (53.59)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<th valign="bottom" colspan="5" align="left">Comorbidities</th>
</tr>
<tr>
<td valign="bottom" align="left">Type 2 diabetes, n (%)</td>
<td valign="middle" align="center">21490 (14.38)</td>
<td valign="middle" align="center">5013 (6.94)</td>
<td valign="middle" align="center">16477 (21.33)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">Hypertension, n (%)</td>
<td valign="middle" align="center">52067 (34.83)</td>
<td valign="middle" align="center">18456 (25.56)</td>
<td valign="middle" align="center">33611 (43.51)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">MetS, n (%)</td>
<td valign="middle" align="center">78895 (52.79)</td>
<td valign="middle" align="center">21620 (29.94)</td>
<td valign="middle" align="center">57275 (74.16)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">Dyslipidemia, n (%)</td>
<td valign="middle" align="center">65723 (43.97)</td>
<td valign="middle" align="center">21430 (29.67)</td>
<td valign="middle" align="center">44293 (57.34)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">Hyperuricaemia, n (%)</td>
<td valign="middle" align="center">18311 (12.30)</td>
<td valign="middle" align="center">4149 (5.78)</td>
<td valign="middle" align="center">14162 (18.40)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">CHD, n (%)</td>
<td valign="middle" align="center">3114 (2.08)</td>
<td valign="middle" align="center">1336 (1.85)</td>
<td valign="middle" align="center">1778 (2.30)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">Cancer, n (%)</td>
<td valign="middle" align="center">747 (0.50)</td>
<td valign="middle" align="center">360 (0.50)</td>
<td valign="middle" align="center">387 (0.50)</td>
<td valign="bottom" align="center">0.971</td>
</tr>
<tr>
<td valign="bottom" align="left">Stroke, n (%)</td>
<td valign="middle" align="center">1337 (0.89)</td>
<td valign="middle" align="center">535 (0.74)</td>
<td valign="middle" align="center">802 (1.04)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">CKD, n (%)</td>
<td valign="middle" align="center">1639 (1.11)</td>
<td valign="middle" align="center">938 (1.31)</td>
<td valign="middle" align="center">701 (0.91)</td>
<td valign="bottom" align="center">&lt;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>MAFLD, metabolic dysfunction-associated fatty liver disease; SD, standard deviation; BMI, body mass index; WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBG, fasting blood glucose; TC, total cholesterol; TG, triglycerides; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; ALT, alanine aminotransferase; AST, aspartate transaminase; BUN, blood urea nitrogen; LEU, leukocyte count; RBC, red blood cell; HGB, haemoglobin; PLT, platelet count; MetS, metabolic syndrome; CHD, coronary heart disease; CKD, chronic kidney disease.</p>
</fn>
<fn id="fnT1_1">
<label>a</label>
<p>P values were calculated by student&#x2019;s t-test for normally distributed variables and the Wilcoxon rank-sum test for non-normal distributed variables, as well as the chi-square test or Fisher&#x2019;s exact test for categorical variables.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<title>Association of MAFLD and subclinical carotid atherosclerosis in the cross-sectional population</title>
<p>The proportions of SCA were higher in individuals in the MAFLD group compared to the non-MAFLD group (50.52% vs. 37.24%) (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). The crude OR (95% CI) for SCA comparing by MAFLD was 1.72 (1.69-1.76; p &lt; 0.001). After multivariable adjustment, SCA comparing individuals in the MAFLD group with those in the non-MAFLD group was 1.66 (95% CI 1.62-1.70; p&lt;0.001). Furthermore, participants with higher levels of HSI had a greater risk of SCA after multivariable adjustments (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). In the logistic regression analysis, compared with non-FLD, the ORs was 1.66 (95% CI 1.62-1.71, P &lt; 0.001) for SCA with MAFLD,and 1.12 (95% CI, 1.02-1.24; P &lt; 0.001) for SCA with FLD-nonMAFLD, respectively (<xref ref-type="supplementary-material" rid="ST1">
<bold>Table S2</bold>
</xref>). The participants with MAFLD had a 2.08-fold increased risk of increased CIMT (OR = 2.08; 95% CI = 2.02-2.14; p &lt; 0.001), 1.53-fold increased risk of Carotid plaque (OR = 1.53; 95% CI = 1.49-1.57; p &lt; 0.001) respectively after multivariable adjustments (<xref ref-type="supplementary-material" rid="ST1">
<bold>Table S3</bold>
</xref>).</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Association between MAFLD and subclinical carotid atherosclerosis in the cross-sectional analysis.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="left">Groups</th>
<th valign="middle" rowspan="2" align="center">SCA events,<break/>n/N(%)</th>
<th valign="middle" colspan="9" align="center">Odds ratio (95% confidence interval)</th>
</tr>    <tr>
<th valign="middle" align="center">Crude</th>
<th valign="middle" align="center">
<italic>p value</italic>
<xref ref-type="table-fn" rid="fnT2_3">
<sup>c</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p for trend</italic>
</th>
<th valign="middle" align="center">Model 1<xref ref-type="table-fn" rid="fnT2_1">
<sup>a</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p value</italic>
<xref ref-type="table-fn" rid="fnT2_3">
<sup>c</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p for trend</italic>
</th>
<th valign="middle" align="center">Model 2<xref ref-type="table-fn" rid="fnT2_2">
<sup>b</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p value</italic>
<xref ref-type="table-fn" rid="fnT2_3">
<sup>c</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p for trend</italic>
</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="11" align="left">non-MAFLD Vs MAFLD</th>
</tr>
<tr>
<td valign="middle" align="left">non-MAFLD</td>
<td valign="middle" align="center">26891/72218<break/>(37.24)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="2" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="2" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="2" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">MAFLD</td>
<td valign="middle" align="center">39029/77251<break/>(50.52)</td>
<td valign="middle" align="center">1.72<break/>(1.69,1.76)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.75<break/>(1.70,1.79)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.66<break/>(1.62,1.70)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="11" align="left">non-MAFLD Vs MAFLD subgroups</th>
</tr>
<tr>
<td valign="middle" align="left">non-MAFLD</td>
<td valign="middle" align="center">26891/72218<break/>(37.24)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="4" align="center">&lt;0.001</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="4" align="center">&lt;0.001</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="4" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">MAFLD-lowHSI<break/>(HSI&lt;35.63)</td>
<td valign="middle" align="center">13278/25753<break/>(51.56)</td>
<td valign="middle" align="center">1.79<break/>(1.74,1.85)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.49<break/>(1.44,1.54)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.47<break/>(1.42,1.52)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">MAFLD-middleHSI<break/>(HSI:35.63-39.66)</td>
<td valign="middle" align="center">13217/25749<break/>(51.33)</td>
<td valign="middle" align="center">1.78<break/>(1.73,1.83)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.74<break/>(1.69,1.80)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.66<break/>(1.61,1.72)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">MAFLD-highHSI<break/>(HSI&gt;39.66)</td>
<td valign="middle" align="center">12534/25749<break/>(48.68)</td>
<td valign="middle" align="center">1.60<break/>(1.55,1.65)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">2.06<break/>(2.00,2.13)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.88<break/>(1.82,1.95)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>MAFLD, metabolic dysfunction-associated fatty liver disease; SCA,Subclinical Carotid Atherosclerosis.</p>
</fn>
<fn id="fnT2_1">
<label>a</label>
<p>Model 1 the adjustment factors included age and sex.</p>
</fn>
<fn id="fnT2_2">
<label>b</label>
<p>Model 2 the adjustment factors included age, sex, self-reported smoking, self-reported drinking, red blood cell, leukocyte count, haemoglobin, platelet count, coronary heart disease, cancer, stroke and chronic kidney disease.</p>
</fn>
<fn id="fnT2_3">
<label>c</label>
<p>P values were calculated based on Logistic regression.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_3">
<title>Baseline characteristics of the new-onset subclinical carotid atherosclerosis cohort</title>
<p>To explore the relationship between baseline MAFLD and new-onset SCA, we built a retrospective cohort that included participants who underwent multiple comprehensive health examinations at least one year apart. These individuals have performed abdominal and carotid ultrasound examinations at a Beijing health management center. The median follow-up period was 2.13 years (IQR: 1.58 - 3.02 years). The mean age was 46.61 years (SD, 7.07), and 32.17% of females at baseline. Compared with participants in the non-MAFLD group, participants in the MAFLD group had higher BMI, WC, BP, SCR, TG, TC, and UA, higher proportions with T2MD, hypertension, MetS, dyslipidemia, and hyperuricemia at baseline (all P &lt; 0.01) (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>). Participants in the MAFLD group with higher HSI, were younger, metabolically unhealthy and more comorbidities (<xref ref-type="supplementary-material" rid="ST1">
<bold>Table S4</bold>
</xref>).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Baseline characteristics for the longitudinal cohort.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left"/>
<th valign="middle" align="center">ALL <break/>N=2,179</th>
<th valign="middle" align="center">Non-MAFLD <break/>N=849</th>
<th valign="middle" align="center">MAFLD <break/>N=1,330</th>
<th valign="middle" align="center">
<italic>p value</italic>
<xref ref-type="table-fn" rid="fnT3_1">
<sup>a</sup>
</xref>
</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">Age (year, mean (SD))</td>
<td valign="middle" align="center">46.61 (7.07)</td>
<td valign="middle" align="center">45.69 (7.66)</td>
<td valign="middle" align="center">47.21 (6.61)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Gender, Female, n (%)</td>
<td valign="middle" align="center">701 (32.17)</td>
<td valign="middle" align="center">475 (55.95)</td>
<td valign="middle" align="center">226 (16.99)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">BMI (kg/m<sup>2</sup>, mean (SD))</td>
<td valign="middle" align="center">25.26 (3.38)</td>
<td valign="middle" align="center">22.67 (2.44)</td>
<td valign="middle" align="center">26.91 (2.82)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">WC (cm, mean (SD))</td>
<td valign="middle" align="center">88.4 (10.6)</td>
<td valign="middle" align="center">80.3 (8.7)</td>
<td valign="middle" align="center">93.5 (8.3)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">SBP (mmHg, mean (SD))</td>
<td valign="middle" align="center">116 (17)</td>
<td valign="middle" align="center">109 (17)</td>
<td valign="middle" align="center">121 (16)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">DBP (mmHg, mean (SD))</td>
<td valign="middle" align="center">77 (11)</td>
<td valign="middle" align="center">72 (10)</td>
<td valign="middle" align="center">79 (11)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Self-reported smoking, n (%)</td>
<td valign="middle" align="center">41 (1.88)</td>
<td valign="middle" align="center">7 (0.82)</td>
<td valign="middle" align="center">34 (2.56)</td>
<td valign="middle" align="center">0.003</td>
</tr>
<tr>
<td valign="middle" align="left">Self-reported drinking, n (%)</td>
<td valign="middle" align="center">89 (4.08)</td>
<td valign="middle" align="center">20 (2.36)</td>
<td valign="middle" align="center">69 (5.19)</td>
<td valign="middle" align="center">0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Laboratory Examination</th>
</tr>
<tr>
<td valign="middle" align="left">FBG (mmol/L, mean (SD))</td>
<td valign="middle" align="center">5.49 (1.17)</td>
<td valign="middle" align="center">5.11 (0.72)</td>
<td valign="middle" align="center">5.73 (1.33)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">TC (mmol/L, mean (SD))</td>
<td valign="middle" align="center">4.72 (0.89)</td>
<td valign="middle" align="center">4.60 (0.84)</td>
<td valign="middle" align="center">4.79 (0.91)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">TG (mmol/L, mean (SD))</td>
<td valign="middle" align="center">1.86 (1.74)</td>
<td valign="middle" align="center">1.24 (0.93)</td>
<td valign="middle" align="center">2.26 (2.01)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">HDL-c (mmol/L, mean (SD))</td>
<td valign="middle" align="center">1.22 (0.34)</td>
<td valign="middle" align="center">1.40 (0.35)</td>
<td valign="middle" align="center">1.11 (0.28)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">LDL-c (mmol/L, mean (SD))</td>
<td valign="middle" align="center">3.03 (0.77)</td>
<td valign="middle" align="center">2.94 (0.75)</td>
<td valign="middle" align="center">3.08 (0.78)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">ALT (IU/L, mean (SD))</td>
<td valign="middle" align="center">25.40 (17.30)</td>
<td valign="middle" align="center">18.10 (11.61)</td>
<td valign="middle" align="center">30.06 (18.67)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">AST (IU/L, mean (SD))</td>
<td valign="middle" align="center">20.59 (8.50)</td>
<td valign="middle" align="center">18.26 (6.34)</td>
<td valign="middle" align="center">22.07 (9.32)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">BUN (mmol/L, mean (SD))</td>
<td valign="middle" align="center">4.95 (1.17)</td>
<td valign="middle" align="center">4.74 (1.17)</td>
<td valign="middle" align="center">5.08 (1.15)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Creatinine (&#x3bc;mol/L, mean (SD))</td>
<td valign="middle" align="center">67.94 (14.11)</td>
<td valign="middle" align="center">64.00 (13.88)</td>
<td valign="middle" align="center">70.46 (13.69)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Uric acid (&#x3bc;mol/L, mean (SD))</td>
<td valign="middle" align="center">346.11 (91.23)</td>
<td valign="middle" align="center">298.25 (80.86)</td>
<td valign="middle" align="center">376.71 (84.05)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">LEU (&#xd7;10<sup>9</sup>/L, mean (SD))</td>
<td valign="middle" align="center">5.84 (1.42)</td>
<td valign="middle" align="center">5.55 (1.41)</td>
<td valign="middle" align="center">6.03 (1.40)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">RBC (&#xd7;10<sup>12</sup>/L, mean (SD))</td>
<td valign="middle" align="center">4.77 (0.48)</td>
<td valign="middle" align="center">4.57 (0.50)</td>
<td valign="middle" align="center">4.89 (0.43)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">HGB (g/L, mean (SD))</td>
<td valign="middle" align="center">145.45 (16.04)</td>
<td valign="middle" align="center">138.21 (17.06)</td>
<td valign="middle" align="center">150.06 (13.46)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">PLT (&#xd7;10<sup>9</sup>/L, mean (SD))</td>
<td valign="middle" align="center">222.33 (53.25)</td>
<td valign="middle" align="center">226.62 (55.60)</td>
<td valign="middle" align="center">219.61 (51.54)</td>
<td valign="middle" align="center">0.003</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Comorbidities</th>
</tr>
<tr>
<td valign="middle" align="left">Type 2 diabetes, n (%)</td>
<td valign="middle" align="center">216 (9.91)</td>
<td valign="middle" align="center">28 (3.30)</td>
<td valign="middle" align="center">188 (14.14)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Hypertension, n (%)</td>
<td valign="middle" align="center">334 (15.33)</td>
<td valign="middle" align="center">55 (6.48)</td>
<td valign="middle" align="center">279 (20.98)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">MetS, n (%)</td>
<td valign="middle" align="center">983 (45.15)</td>
<td valign="middle" align="center">142 (16.75)</td>
<td valign="middle" align="center">841 (63.28)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Dyslipidemia, n (%)</td>
<td valign="middle" align="center">931 (42.73)</td>
<td valign="middle" align="center">186 (21.91)</td>
<td valign="middle" align="center">745 (56.02)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Hyperuricaemia, n (%)</td>
<td valign="middle" align="center">320 (14.70)</td>
<td valign="middle" align="center">43 (5.06)</td>
<td valign="middle" align="center">277 (20.86)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">CHD, n (%)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">Cancer, n (%)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">Stroke, n (%)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">CKD, n (%)</td>
<td valign="middle" align="center">4 (0.18)</td>
<td valign="middle" align="center">1 (0.12)</td>
<td valign="middle" align="center">3 (0.23)</td>
<td valign="middle" align="center">0.999</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>MAFLD, metabolic dysfunction-associated fatty liver disease; SD, standard deviation; BMI, body mass index; WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBG, fasting blood glucose; TC, total cholesterol; TG, triglycerides; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; ALT, alanine aminotransferase; AST, aspartate transaminase; BUN, blood urea nitrogen; LEU, leukocyte count; RBC, red blood cell; HGB, haemoglobin; PLT, platelet count; MetS, metabolic syndrome; CHD, coronary heart disease; CKD, chronic kidney disease.</p>
</fn>
<fn id="fnT3_1">
<label>a</label>
<p>P values were calculated by student&#x2019;s t-test for normally distributed variables and the Wilcoxon rank-sum test for non-normal distributed variables, as well as the chi-square test or Fisher&#x2019;s exact test for categorical variables.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_4">
<title>Association of the baseline MAFLD and the incidence subclinical carotid atherosclerosis in the longitudinal cohort</title>
<p>During the follow-up period, 849 participants developed SCA in 2,179 participants in the longitudinal cohort. In the multivariable-adjusted model, participants with baseline MAFLD had a higher risk of new-onset SCA, HR: 1.31 (95% CI 1.12-1.54, p=0.001). MAFLD groups had a greater risk of SCA after multivariable adjustments in the longitudinal cohort, HR 1.33 (95% CI 1.13,1.57). However, compared with non-FLD, FLD-nonMAFLD group is not associated with a high risk of SCA occurring, HR 1.35 (95% CI 0.75-2.42; p = 0.312) (<xref ref-type="supplementary-material" rid="ST1">
<bold>Table S5</bold>
</xref>). After multivariable-adjusted, increased CIMT, Carotid plaque comparing individuals in the MAFLD group with those in the non-MAFLD group were 1.38 (95% CI 1.15-1.66; p&lt;0.001) and 1.31 (95% CI 1.04-1.65; p=0.024) (<xref ref-type="supplementary-material" rid="ST1">
<bold>Table S6</bold>
</xref>). Consistent with cross-sectional studies, the correlations between baseline MAFLD hepatic steatosis level and the progression of SCA were described in <xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>. Compared with the Non-MAFLD group, participants in the MAFLD group with higher hepatic steatosis levels at baseline had a higher risk of developing SCA after adjustment for confounders (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>).</p>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Association between baseline MAFLD and the incidence of subclinical carotid atherosclerosis in the longitudinal cohort.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="left">Groups</th>
<th valign="middle" rowspan="2" align="center">SCA events,<break/>n/N(%)</th>
<th valign="middle" colspan="9" align="center">Hazards ratio (95% confidence interval)</th>
</tr>    <tr>
<th valign="middle" align="center">Crude</th>
<th valign="middle" align="center">
<italic>p value</italic>
<xref ref-type="table-fn" rid="fnT4_3">
<sup>c</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p for trend</italic>
</th>
<th valign="middle" align="center">Model 1<xref ref-type="table-fn" rid="fnT4_1">
<sup>a</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p value</italic>
<xref ref-type="table-fn" rid="fnT4_3">
<sup>c</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p for trend</italic>
</th>
<th valign="middle" align="center">Model 2<xref ref-type="table-fn" rid="fnT4_2">
<sup>b</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p value</italic>
<xref ref-type="table-fn" rid="fnT4_3">
<sup>c</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p for trend</italic>
</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="11" align="left">non-MAFLD Vs MAFLD</th>
</tr>
<tr>
<td valign="middle" align="left">non-MAFLD</td>
<td valign="middle" align="center">243/849<break/>(28.62)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="2" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="2" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="2" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">MAFLD</td>
<td valign="middle" align="center">642/1330<break/>(48.27)</td>
<td valign="middle" align="center">1.51<break/>(1.30,1.75)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.30<break/>(1.11,1.53)</td>
<td valign="middle" align="center">0.001</td>
<td valign="middle" align="center">1.31<break/>(1.12,1.54)</td>
<td valign="middle" align="center">0.001</td>
</tr>
<tr>
<td valign="middle" colspan="11" align="left">
<bold>non-MAFLD Vs</bold> MAFLD <bold>subgroups</bold>
</td>
</tr>
<tr>
<td valign="middle" align="left">non-MAFLD</td>
<td valign="middle" align="center">243/849<break/>(28.62)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="4" align="center">&lt;0.001</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="4" align="center">0.001</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="4" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">MAFLD-lowHSI<break/>(HSI&lt;35.63)</td>
<td valign="middle" align="center">208/464<break/>(44.83)</td>
<td valign="middle" align="center">1.49<break/>(1.24,1.80)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.22<break/>(1.00,1.48)</td>
<td valign="middle" align="center">0.044</td>
<td valign="middle" align="center">1.23<break/>(1.02,1.50)</td>
<td valign="middle" align="center">0.035</td>
</tr>
<tr>
<td valign="middle" align="left">MAFLD-middleHSI<break/>(HSI:35.63-39.66)</td>
<td valign="middle" align="center">211/438<break/>(48.17)</td>
<td valign="middle" align="center">1.56<break/>(1.30,1.88)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.33<break/>(1.10,1.62)</td>
<td valign="middle" align="center">0.004</td>
<td valign="middle" align="center">1.34<break/>(1.10,1.63)</td>
<td valign="middle" align="center">0.003</td>
</tr>
<tr>
<td valign="middle" align="left">MAFLD-highHSI<break/>(HSI&gt;39.66)</td>
<td valign="middle" align="center">223/428<break/>(52.10)</td>
<td valign="middle" align="center">1.48<break/>(1.23,1.77)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.36<break/>(1.12,1.65)</td>
<td valign="middle" align="center">0.002</td>
<td valign="middle" align="center">1.38<break/>(1.14,1.68)</td>
<td valign="middle" align="center">0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>MAFLD, metabolic dysfunction-associated fatty liver disease; SCA,Subclinical Carotid Atherosclerosis.</p>
</fn>
<fn id="fnT4_1">
<label>a</label>
<p>Model 1 the adjustment factors included age and sex.</p>
</fn>
<fn id="fnT4_2">
<label>b</label>
<p>Model 2 the adjustment factors included age, sex, self-reported smoking, self-reported drinking, red blood cell, leukocyte count, haemoglobin, platelet count and chronic kidney disease.</p>
</fn>
<fn id="fnT4_3">
<label>c</label>
<p>P values were calculated based on Cox regression.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Subgroup analysis according to sex and age for baseline MAFLD and new-onset SCA were shown in <xref ref-type="table" rid="T5">
<bold>Table&#xa0;5</bold>
</xref>. After multivariable-adjusted, the HR (95% CI) of new-onset SCA comparing non-MAFLD group to MAFLD group for female and male was 1.46 (1.09-1.95; p = 0.011) and 1.24 (1.02-1.50; p = 0.029) respectively. At follow-up visit, participants with MAFLD younger than 45 years old had a 1.67-fold increased risk of new-onset SCA (HR = 1.67; 95% CI = 1.17-2.40; p = 0.005), which were higher than a 1.21-fold risk of incident SCA in MAFLD individuals over 45 years of age (HR = 1.21; 95% CI = 1.01&#x2013;1.45; p = 0.041). Interestingly, we found a significant interaction between MAFLD and age (p for interaction = 0.034).</p>
<table-wrap id="T5" position="float">
<label>Table&#xa0;5</label>
<caption>
<p>Association between baseline MAFLD and the subclinical carotid atherosclerosis in the cohort subgroups.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="left">Subgroups</th>
<th valign="middle" rowspan="2" align="center">Groups</th>
<th valign="middle" rowspan="2" align="center">SCA events,<break/>n/N (%)</th>
<th valign="middle" colspan="7" align="center">Hazards ratio (95% confidence interval)</th>
</tr>    <tr>
<th valign="middle" align="center">Crude</th>
<th valign="middle" align="center">
<italic>p value<xref ref-type="table-fn" rid="fnT5_3">
<sup>c</sup>
</xref>
</italic>
</th>
<th valign="middle" align="center">Model 1<xref ref-type="table-fn" rid="fnT5_1">
<sup>a</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p value<xref ref-type="table-fn" rid="fnT5_3">
<sup>c</sup>
</xref>
</italic>
</th>
<th valign="middle" align="center">Model 2<xref ref-type="table-fn" rid="fnT5_2">
<sup>b</sup>
</xref>
</th>
<th valign="middle" align="center">
<italic>p value<xref ref-type="table-fn" rid="fnT5_3">
<sup>c</sup>
</xref>
</italic>
</th>
<th valign="middle" align="center">
<italic>p for interaction<xref ref-type="table-fn" rid="fnT5_4">
<sup>d</sup>
</xref>
</italic>
</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="10" align="left">Sex subgroups</th>
</tr>
<tr>
<td valign="middle" rowspan="2" align="left">
<bold>Female</bold>
</td>
<td valign="middle" align="center">non-MAFLD</td>
<td valign="middle" align="center">112/475 (23.58)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="4" align="center">0.304</td>
</tr>
<tr>
<td valign="middle" align="center">MAFLD</td>
<td valign="middle" align="center">92/226 (40.71)</td>
<td valign="middle" align="center">1.72 (1.31,2.27)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.41 (1.06,1.88)</td>
<td valign="middle" align="center">0.018</td>
<td valign="middle" align="center">1.46 (1.09,1.95)</td>
<td valign="middle" align="center">0.011</td>
</tr>
<tr>
<td valign="middle" rowspan="2" align="left">
<bold>Male</bold>
</td>
<td valign="middle" align="center">non-MAFLD</td>
<td valign="middle" align="center">131/374 (35.03)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="center">MAFLD</td>
<td valign="middle" align="center">550/1104 (49.82)</td>
<td valign="middle" align="center">1.24 (1.02,1.50)</td>
<td valign="middle" align="center">0.029</td>
<td valign="middle" align="center">1.24 (1.03,1.50)</td>
<td valign="middle" align="center">0.026</td>
<td valign="middle" align="center">1.24 (1.02,1.50)</td>
<td valign="middle" align="center">0.029</td>
</tr>
<tr>
<th valign="middle" colspan="10" align="left">Age subgroups</th>
</tr>
<tr>
<td valign="middle" rowspan="2" align="left">
<bold>Age&lt;45</bold>
</td>
<td valign="middle" align="center">non-MAFLD</td>
<td valign="middle" align="center">48/351 (13.68)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" rowspan="4" align="center">0.034</td>
</tr>
<tr>
<td valign="middle" align="center">MAFLD</td>
<td valign="middle" align="center">170/427 (39.81)</td>
<td valign="middle" align="center">2.20 (1.59,3.04)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.72 (1.20,2.46)</td>
<td valign="middle" align="center">0.003</td>
<td valign="middle" align="center">1.67 (1.17,2.40)</td>
<td valign="middle" align="center">0.005</td>
</tr>
<tr>
<td valign="middle" rowspan="2" align="left">
<bold>Age&#x2265;45</bold>
</td>
<td valign="middle" align="center">non-MAFLD</td>
<td valign="middle" align="center">195/498 (39.16)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="center">MAFLD</td>
<td valign="middle" align="center">472/903 (52.27)</td>
<td valign="middle" align="center">1.31 (1.11,1.55)</td>
<td valign="middle" align="center">0.001</td>
<td valign="middle" align="center">1.18 (0.99,1.41)</td>
<td valign="middle" align="center">0.072</td>
<td valign="middle" align="center">1.21 (1.01,1.45)</td>
<td valign="middle" align="center">0.041</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>MAFLD, metabolic dysfunction-associated fatty liver disease.</p>
</fn>
<fn id="fnT5_1">
<label>a</label>
<p>Model 1 the adjustment factors included age and sex.</p>
</fn>
<fn id="fnT5_2">
<label>b</label>
<p>Model 2 the adjustment factors included age, sex, self-reported smoking, self-reported drinking, red blood cell, leukocyte count, haemoglobin, platelet count and chronic kidney disease.</p>
</fn>
<fn id="fnT5_3">
<label>c</label>
<p>P values were calculated based on Cox regression.</p>
</fn>
<fn id="fnT5_4">
<label>d</label>
<p>P for interaction were calculated based on Cox regression and the adjustment factors included age, sex, self-reported smoking, self-reported drinking, red blood cell, leukocyte count, haemoglobin, platelet count and chronic kidney disease.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_5">
<title>Sensitivity analysis</title>
<p>Our findings in longitudinal studies were robust to the following sensitivity analyses. First, MAFLD was associated with the development of SCA in the cohort with a follow-up time of &gt; 2 years (<xref ref-type="supplementary-material" rid="ST1">
<bold>Table S7</bold>
</xref>). Second, the association between baseline MAFLD and new-onset SCA persisted after further adjusted FIB-4 in Cox proportional hazard regression model (<xref ref-type="supplementary-material" rid="ST1">
<bold>Table S8</bold>
</xref>). Last, considering the influence of lipid abnormalities on SCA, we further adjusted dyslipidemia in the Cox proportional hazard regression model (<xref ref-type="supplementary-material" rid="ST1">
<bold>Table S9</bold>
</xref>).</p>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>In this study of 153,482 participants from health examination centers, we found that MAFLD was significantly associated with SCA after adjusting for potential confounders. And the association was progressive increased with the categories of hepatic steatosis index. In a Beijing longitudinal population, we found that participants with MAFLD had a high risk of SCA developing compared to those without MAFLD. The risk of developing SCA was also higher in participants with severe hepatic steatosis in the longitudinal study. Interaction with age should be mentioned. Furthermore, this association was present across genders and ages and was more pronounced in males and young adults (aged &lt; 45 years old). Thus, Our findings suggested that MAFLD may be a risk factor for carotid atherosclerosis development and the impacts from MAFLD are more pronounced in younger populations or those with severe hepatic steatosis.</p>
<p>NAFLD is considered a demonstration of multisystem metabolic dysfunction, with insulin resistance as a common pathophysiological mechanism (<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B33">33</xref>). NAFLD has been underestimated as an independent risk factor for ASCVD after adjustment for conventional ASCVD risk factors in a large number of studies (<xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B35">35</xref>). The correlation between NAFLD and the presence and occurrence of SCA has been established by several previous studies and meta-analyses (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B36">36</xref>&#x2013;<xref ref-type="bibr" rid="B38">38</xref>). As a new definition proposed by an international panel of experts, MAFLD has been demonstrated to have superior utility in clinical practice by multiple studies from the United States and Japan, to identify high-risk groups for early intervention for diseases such as fibrosis and metabolic disorders and chronic kidney disease (<xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B40">40</xref>). Results from a community-based cohort study from Sri Lanka showed that subjects excluded by the NAFLD definition but captured by the MAFLD definition were significantly more likely to be excluded by MAFLD definition but captured by the NAFLD definition than subjects excluded by MAFLD definition but captured by the NAFLD definition, new-onset metabolic characteristics and cardiovascular events were higher (<xref ref-type="bibr" rid="B41">41</xref>). Two cohort studies from the UK and Korea confirmed that this MAFLD was independently associated with an increased risk of intrahepatic and extrahepatic events. In the non-Chinese population, participants with MAFLD were reported to be at higher risk of CVD than participants with NAFLD (<xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B43">43</xref>). A cross-sectional study based on participants enrolled in East China demonstrated that individuals with MAFLD have a similar or higher risk of future CVD than those with NAFLD (<xref ref-type="bibr" rid="B44">44</xref>). A recent cross-sectional study and a community-based cohort study also reported positive correlations between MAFLD and subclinical atherosclerosis measured by CIMT, brachial-ankle pulse wave velocity, microalbuminuria and coronary artery calcification score (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B45">45</xref>). A matched case-control study that included 3306 patients from China showed that MAFLD was significantly associated with the risk of MACEs in patients with chronic coronary syndrome (<xref ref-type="bibr" rid="B46">46</xref>). However, NAFLD/MAFLD still haven&#x2019;t received sufficient attention from the Cardiology community (<xref ref-type="bibr" rid="B47">47</xref>). The association between MAFLD and CVD/SCA is mainly attributed to their common risk factors, such as obesity and lipid abnormalities (<xref ref-type="bibr" rid="B48">48</xref>). MAFLD highlights the systemic metabolic disorders that accompany fatty liver disease. Therefore, it is necessary to further explore the relationship between MAFLD and SCA development in a large Chinese population. In this study, the correlation between MAFLD and SCA detected using ultrasound was observed in a nationwide health examination population in China. Furthermore, among a retrospective cohort population who underwent at least two comprehensive health check-up examinations in Beijing, the risk of the development of carotid atherosclerosis in participants with MAFLD was significantly higher than in participants without MAFLD.</p>
<p>In recent years, numerous population-based studies have also shown that the severity of liver fibrosis in NAFLD patients is closely associated with increased CIMT (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B49">49</xref>, <xref ref-type="bibr" rid="B50">50</xref>). However, the impact of steatosis is less clear and controversial. Liver fibrosis is the manifestation of advanced NAFLD after a long-term metabolic disorder. It might not be conducive to the early intervention of the disease that correlates with subclinical atherosclerosis and liver fibrosis. If the correlation between early lipogenesis and atherosclerosis is established, early intervention of lipogenesis may be beneficial for early intervention of the disease. Therefore, fibrosis is considered the most important factor for identifying risk stratification in NAFLD (<xref ref-type="bibr" rid="B51">51</xref>). However, this may mask the risk of quality of life and early subclinical outcomes in patients with steatosis. In this study, we observed the association of MAFLD and the presence and occurrence of SCA were progressive across categories of hepatic steatosis index, which showed a significant correlation with fatty liver grade (<xref ref-type="bibr" rid="B21">21</xref>).</p>
<p>Furthermore, in the sensitivity analysis of this study, we further adjusted FIB-4 and found that the relationship between MAFLD and SCA still existed. Interestingly, we first observed a higher risk of developing SCA in the younger MAFLD population. However, well-designed prospective studies are warranted to elucidate this relationship between carotid atherosclerosis and MAFLD in this patient subgroup.</p>
<p>There are pathological mechanisms linking MAFLD and atherosclerosis. Insulin resistance and systematical inflammation were considered key mediators in this association (<xref ref-type="bibr" rid="B52">52</xref>&#x2013;<xref ref-type="bibr" rid="B54">54</xref>). In the patient with insulin resistance, the activity of various lipases is disturbed, leading to an excessive influx of free fatty acids and the intestinal production of chylomicrons (CMs) and VLDL to the liver. Hyperinsulinemia also leads to increased esterification of fatty acids rather than &#x3b2;-oxidation, resulting in the formation of TGs in hepatocytes. Patients with metabolic disorders have increased systematic oxidative stress and glucose levels, and excessive circulating LDL levels can be further modified to generate large amounts of ox-LDL and glycated-LDL, which lead to foam cell formation and atherosclerotic disease (<xref ref-type="bibr" rid="B4">4</xref>). Recently, a study revealed that nicotine accumulates in the gut during smoking and promotes NASH progression through the gut-liver dialogue (<xref ref-type="bibr" rid="B55">55</xref>). In fact, as the most common unhealthy behaviours among humans, Smoking may be a risk factor shared by CVD and MAFLD, dur to studies have shown that smokers have a higher risk of insulin resistance and hyperinsulinemia compared with non-smokers. And smoking could altered lipid metabolism by increasing lipolysis, insulin resistance, and tissue lipotoxicity (<xref ref-type="bibr" rid="B56">56</xref>). The fatty hepatocyte in NAFLD is inevitably accompanied by mitochondrial dysfunction and the occurrence of hepatocyte degeneration and necrosis, inducing the production of inflammatory chemicals such as c-reactive protein, tumor necrosis factors &#x3b1;, interleukin-6, interleukin-12 and monocyte chemoattractant protein-1 in hepatocytes, leading to an inflammatory response in the liver, and systemic low-grade inflammatory response. These inflammatory mediators play synergistic and antagonistic roles in the initiation and progression of arteriosclerosis diseases (<xref ref-type="bibr" rid="B57">57</xref>, <xref ref-type="bibr" rid="B58">58</xref>). In addition, adiponectin concentration, oxidative stress, and endothelial dysfunction in NAFLD patients also contribute to the development of atherosclerosis (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B59">59</xref>&#x2013;<xref ref-type="bibr" rid="B61">61</xref>). Currently, there is no consensus on how NAFLD steatosis degree affects atherosclerosis. The more severe lipotoxicity, inflammation, and marked hepatic insulin resistance in the progression of hepatic steatosis may partially explain the relationship between the severity of hepatic steatosis and atherosclerosis (<xref ref-type="bibr" rid="B62">62</xref>). A population study which provided ideas for early warning of SCA risk in MAFLD patients found that cystine, sphingomyelin (16:1/18:1), <italic>de novo</italic> lipogenesis (16:0/18:2n-6) were significant associated with SCA in obese MAFLD patients and phosphatidylethanolamine (PE 20:2/16:0), phosphatidylglycerol (PG 18:0/20:4), <italic>de novo</italic> lipogenesis (16:0/18:2n-6) were significant associated with SCA were significant associated with SCA in nonobese MAFLD patients (<xref ref-type="bibr" rid="B63">63</xref>).</p>
<p>There are several limitations to consider when interpreting our findings. First, our study is based on the national health screening population, which is not a random sample and may not represent the Chinese rural population. Second, retrospective study designs can lead to unavoidable biases, including selection or misclassification bias. Third, due to the long duration of the study, different ultrasound scanners and radiological technologists were involved in FLD measurements over time. However, the researchers who collected the data did not know the purpose of the study, and equipment changes were not related to participant characteristics. Finally, our study was conducted in a population with regular health checks, and these findings may not generalize to other populations, especially different age or racial/ethnic groups.</p>
</sec>
<sec id="s5" sec-type="conclusion">
<title>Conclusion</title>
<p>In conclusion, our study showed that MAFLD had an increased risk of the presence and development of SCA in cross-sectional and longitudinal populations. The risk of SCA was higher among individuals with more advanced MAFLD steatosis and the younger population. This study provides critical evidence for the risks of existing and emerging SCA in MAFLD. It highlights the importance of early interventions in MAFLD in young adults and patients with severe steatosis to prevent clinical atherosclerosis. Prospective studies and clinical trials focusing on whether the management of MAFLD can result in a reduced risk of cardiovascular disease are warranted.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="s12"><bold>Supplementary Material</bold></xref>. Further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s7" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>The study was in accordance with the principles of the Declaration of Helsinki and was approved by the central ethics board of Renmin Hospital of Wuhan University, followed by the acceptance with the ethics center in each collaborating hospital. Individual identification data was removed, and only anonymous information was kept during the study process. The ethics committees from each hospital waived patient informed consent.</p>
</sec>
<sec id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>FL, X-MW and CW designed the study, collected and analyzed data and drafted the manuscript. XH, Y-ML and J-JQ collected and interpreted data and contributed to data analysis. PZ, Y-XJ, Z-GS and JC performed critical revision of the manuscript for important intellectual content. H-PL, X-JZ and HL conceived and supervised the study, critical revision of the manuscript for important intellectual content, and supervised the study. All authors approved the paper for submission.</p>
</sec>
</body>
<back>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>This work was supported by the National Science Foundation of China [82170595, 81970364, 81770053, 82170436, 82000299], and the Medical Science Advancement Program of Wuhan University [TFJH2018006].</p>
</sec>
<sec id="s10" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s12" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fendo.2023.1109673/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fendo.2023.1109673/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table_1.docx" id="ST1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
</sec>
<fn-group>
<title>Abbreviations</title>
<fn fn-type="abbr">
<p>MAFLD, metabolic (dysfunction)-associated fatty liver disease; NAFLD, Nonalcoholic fatty liver disease; CIMT, Carotid intima-media thickness; SCA, Subclinical carotid atherosclerosis; MetS, Metabolism syndrome; T2DM, Type 2 diabetes; BMI, Body mass index; FBG, Fasting blood glucose; SBP, Systolic blood pressure; DBP, Diastolic blood pressure; BP, Blood pressure; TG, Triglycerides; TC, Total cholesterol; LDL-c, Low-density lipoprotein cholesterol; HDL-c, High-density lipoprotein cholesterol; HSI, hepatic steatosis index; FIB-4, Fibrosis 4 Score; CKD, chronic kidney disease; SD, Standard deviation; ORs, Odd ratios; HR, hazard ratios.</p>
</fn>
</fn-group>
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