Association of fatty pancreas and subclinical atherosclerosis: A cross-sectional analysis

Association of fatty pancreas and subclinical atherosclerosis: A cross-sectional analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of fatty pancreas and subclinical atherosclerosis: A cross-sectional analysis Qingxie Liu, Xinyi Liu, Yaodong Wang, Weiwei Luo, Xiaowu Dong, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4258548/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background: To date, no correlation between fatty pancreas and carotid plaque has been reported. Therefore, this study used a large medical examination cohort from Yangzhou to investigate the association between fatty pancreas and subclinical atherosclerosis. Methods: Clinical data were collected between January 2018 and December 2021 from a population undergoing health check-ups at the Health Management Centre of the Affiliated Hospital of Yangzhou University. Carotid vascular ultrasound findings were used to divide the participants into carotid plaque and non-carotid plaque groups on the basis of independent risk factors for carotid plaque. Results: A total of 6976 cases in the carotid plaque group and 17 069 cases in the non-carotid plaque group were included in this study. Logistic regression model analysis of carotid plaque showed that men (odds ratio [OR] = 1.479, P < 0.001), age (OR = 1.110, P < 0.001), body mass index (OR = 1.005, P < 0.001), history of smoking (OR = 1.446, P < 0.001), history of alcohol consumption (OR = 1.160, P < 0.001), hypertension (OR = 3.296, P < 0.001), diabetes mellitus (OR = 4.077, P < 0.001), fatty pancreas (OR = 1.490, P < 0.001), hypercholesterolaemia (OR = 1.175, P < 0.001), and low-density lipoprotein cholesterol atheroma (OR = 1.174, P < 0.001) were independent risk factors for carotid plaque. Subgroup analysis indicated that fatty pancreas was an independent risk factor for carotid plaque in participants without these complications compared with participants with a history of hypertension or diabetes. Conclusion: Fatty pancreas is an independent risk factor for carotid plaque and has a greater impact in individuals without a history of hypertension or diabetes than in those with. Carotid plaque Cervical vascular ultrasound Pancreatology Subclinical atherosclerosis Figures Figure 1 Figure 2 Figure 3 BACKGROUND Cardiovascular disease (CVD) is the leading cause of death worldwide. There were 18.6 million deaths due to cardiovascular diseases worldwide in 2019, which was 6.5 million more than that 30 years ago. In China, deaths due to atherosclerotic cardiovascular disease increased by 1.3 million during the same period 1 . Obesity can lead to ectopic fat deposition in the subcutaneous and visceral tissues, and adipose tissue distribution is closely associated with the risk of cardiovascular diseases. Visceral fat carries a greater risk of cardiovascular disease than subcutaneous fat tissue 2 . Common organs with ectopic fat deposits include the liver, heart, and pancreas 3–4 . Fat deposition occurs earlier in the pancreas than in the liver, and the fatty pancreas (FP) can be used as an initial indicator of fatty ectopic deposition 5 . In recent years, FP, an organ of fatty ectopic deposition, has attracted extensive attention and research. The pancreatic parenchymal and stromal cells of FP undergo pathological and physiological changes of steatosis and triglyceride deposition. This may be due to increased insulin resistance and pathophysiological changes in the production of pro-inflammatory substances in visceral adipose tissue 6 . A 30-year follow-up study of 229 patients after biopsy confirmed non-alcoholic fatty liver disease (NAFLD) found a significantly increased risk of death due to cardiovascular disease (hazard ratio: 1.55, 95% confidence interval: 1.11–2.15, P = 0.01) 7–8 . Kadir et al. 9 reported that NAFLD can be used as an independent risk factor for predicting subclinical atherosclerosis, which is closely related to cardiovascular events, and carotid plaque is a strong predictor of cardiovascular events 10 . Carotid ultrasound follow-up plays an important role in the monitoring and management of adverse cardiovascular events and can be used to noninvasively monitor the presence of subclinical atherosclerosis 11 . Studies have shown that FP is independently correlated with carotid intima-media thickness (CIMT) 12 . To date, no correlation between FP and carotid plaque has been reported. Therefore, this study investigated the correlation between FP and carotid plaque in a large medical examination cohort in Yangzhou. METHODS 2.1 Study design and population The clinical data of patients who underwent a physical examination at the Health Management Centre of the Affiliated Hospital of Yangzhou University from January 2018 to December 2021 were collected to investigate the correlation between FP and carotid plaque. According to the inclusion and exclusion criteria, 24 045 participants were included. A cross-sectional analysis of the clinical data of the enrolled participants was performed. 2.1.1 Inclusion and exclusion criteria All physical examinations that were performed at the Health Management Centre of the Affiliated Hospital of Yangzhou University between January 2018 and December 2021 with complete cervical vascular colour Doppler ultrasonography examinations were included. Patients diagnosed with malignant diseases, such as chronic diseases of the pancreas, liver, kidney, or tumours, who had incomplete clinical and biochemical data were excluded. 2.1.3 Ethics statements This study conformed to the principles of the Declaration of Helsinki and was approved by the Ethics Committee of the Affiliated Hospital of Yangzhou University. 2.2 Research method 2.2.1 Subclinical atherosclerosis CIMT in subclinical atherosclerosis was measured by an experienced radiologist at the Health Management Centre using a B-ultrasound machine with a frequency of 3–5 Hz. Each participant was examined in the supine position with the head rotated to the opposite side. Carotid subclinical atherosclerosis was defined as the presence of carotid plaque, i.e. an abnormal increase in CIMT (> 1.2 mm) 13 . 2.2.2 Data acquisition General information, including sex, age, height, and weight, was recorded. Previous medical history, including smoking and drinking history, hypertension, diabetes, and FP, was collected. Laboratory indicators, including triglycerides (TG), total cholesterol (TC), low high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) levels, were also recorded. The body mass index (BMI) of each participant was calculated according to general data as follows: =weight (kg)/height squared (m 2 ). 2.2.3 Diagnostic criteria Smoking history: smoking at least one cigarette a day, lasting > 6 months or quitting smoking for 6 months. Abnormal lipid metabolism: Hypertriglyceridaemia (HTG) is a metabolic disorder, defined when the serum or plasma triglyceride concentration is > 1.7 mmol/L 14 . Hypercholesterolaemia (HTC) was defined as a serum cholesterol level > 6.2 mmol/L. Mixed hyperlipidaemia refers to hyperlipidaemia in which triglycerides and cholesterol are simultaneously elevated. Mixed hyperlipidaemia is often characterised by elevated cholesterol or elevated TG 15 . 2.2.4 FP The diagnosis of fat pancreas was made simultaneously by experienced radiologists at the Health Management Centre using a high-resolution ultrasound system (LOGIQ E9; GE, Boston, MA USA) with a 3.5–5-MHz probe. Ultrasound image characteristics of the FP: As the shape of the pancreas increases, the volume changes, and the outline is clear compared with the echo of neighbouring organs. 2.2.5 Statistical analysis Measurement data are expressed as mean ± standard deviation, and the independent sample t-test was used to compare data between the groups. The statistical data are presented as number (%), and the χ 2 test was used to compare data between the groups. Logistic regression models were used to correct for confounding factors. Independent risk factors of carotid plaque were analysed, and subgroup analysis was performed. Logistic analysis was used to analyse the influence of FP subgroups on the prevalence of carotid plaque. SPSS Statistics (version 25.0; IBM Corp., Armonk, NY, USA) was used to analyse the data. A P-value < 0.05 was considered statistically significant. RESULTS 3.1 Analysis of participants’ general clinical data and laboratory indicators A total of 6976 cases in the carotid plaque group and 17 069 cases in the non-carotid plaque group were included in this study (Fig. 1 ; Table 1 ). Mean ages of the carotid plaque and non-carotid plaque groups were 63 ± 12 and 50 ± 12 years, respectively, and the difference between the groups was statistically significant (P < 0.001). Smoking and drinking histories were significantly higher in the carotid plaque group than in the non-carotid plaque group (P < 0.001). The prevalence of metabolic diseases, such as hypertension, diabetes, FP, and hypercholesterolaemia, was also significantly higher in the carotid plaque group than in the non-carotid plaque group (all, P 0.01). Mean values of LDL-C and ALT were higher in the carotid plaque group than in the non-carotid plaque group (P < 0.001), but there were no statistically significant differences in the blood lipid indices (TG, high-density lipoprotein, and high-density lipoprotein cholesterol [HDL-Ch]) and liver function indices (AST) between the groups (all, P > 0.01). Table 1 General clinical data and laboratory indicators in the carotid plaque and non-carotid plaque groups Variable Carotid plaque (n = 6976) Non-carotid plaque (n = 17 069) P-value Sex < 0.001 Male 5542 (79.4%) 12 344 (72.3%) Female 1434 (20.6%) 4725 (27.7%) Age (ye) 63 ± 12 50 ± 12 < 0.001 BMI (kg/m 2 ) 24.75 ± 1.90 24.61 ± 2.12 < 0.001 Smoking history 2041 (29.3%) 3797 (22.3%) < 0.001 Drinking history 2375 (34.1%) 5257 (30.8%) < 0.001 HBP 2722 (39.0%) 2775 (16.3%) < 0.001 DM 760 (10.9%) 497 (2.9%) < 0.001 LHDL-C level 1253 (17.9%) 2946 (17.3%) 0.193 FP 475 (6.8%) 798 (4.7%) < 0.001 TG level (mmol/L) 1.58 ± 1.53 1.51 ± 1.64 0.032 TC level (mmol/L) 4.93 ± 0.65 4.75 ± 0.55 < 0.001 HDL-Ch level (mmol/L) 1.22 ± 1.80 1.23 ± 1.70 0.002 LDL-C level (mmol/L) 2.77 ± 0.84 2.64 ± 0.75 < 0.001 ALT level (U/L) 20.00 ± 25.21 21.30 ± 24.7 < 0.001 AST level (U/L) 20.50 ± 14.62 19.90 ± 11.38 0.318 BMI, body mass index; HBP, high blood pressure; DM, diabetic mellitus; LHDL-C, low high-density lipoprotein cholesterol; FP, fatty pancreas; TG, total triglyceride; TC, total cholesterol; HDL-Ch, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; ALT, alanine transaminase; AST, aspartate transaminase 3.2 Logistic regression analysis of carotid plaque As shown in Fig. 2 , univariate analysis with logistic regression was conducted to further analyse the independent risk factors for carotid plaque. Male sex (odds ratio [OR] = 1.479, P < 0.001), age (OR = 1.110, P < 0.001), BMI (OR = 1.005, P < 0.001), history of smoking (OR = 1.446, P < 0.001), history of alcohol consumption (OR = 1.160, P < 0.001), hypertension (OR = 3.296, P < 0.001), diabetes mellitus (OR = 4.077, P < 0.001), FP (OR = 1.490, P < 0.001), hypercholesterolaemia (OR = 1.175, P < 0.001), and LDL atheroma (OR = 1.174, P < 0.001) were risk factors for carotid plaque. 3.3 Influence of FP on the prevalence of carotid plaque in multivariate analysis Univariate analysis showed that FP was independently associated with carotid plaque (OR = 1.49, P < 0.001). As shown in Table 2 , after correction for other factors, results of logistic regression analysis showed that regardless of Q1, Q2, or Q3 models, FP was correlated with carotid plaque (P < 0.05). Table 2 The effect of fatty pancreas on carotid plaque Univariate analysis Multivariate analysis Q1 Q2 Q3 OR (95% CI) P OR (95% CI) P-value OR (95% CI) P-value OR (95% CI) P-value Fatty pancreas 1.49 (1.324–1.674) < 0.001 1.207 (1.055–1.38) 0.006 1.183 (1.032–1.354) 0.015 1.146 (1–1.313) 0.049 Notes: Q1: Model 1 adjusted for sex, age, BMI, smoking history, and drinking history. Q2: Model 2 adjusted for variables in Q1 + HBP and DM. Q3: Model 3 adjusted for variables in Q2 + TG, TC, HDL-Ch, LDL-C, ALT, and AST. BMI, body mass index; HBP, high blood pressure; DM, diabetes mellitus; TG, triglycerides; TC, total cholesterol; HDL-Ch, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; ALT, alanine aminotransferase; AST, aspartate aminotransferase 3.4 Subgroup analysis off the association between FP and carotid plaque Subgroup analyses were conducted using model Q3 adjusted for sex, age, BMI, histories of smoking and drinking, HBP, DM, and levels of TG, TC, HDL-Ch, LDL, ALT, and AST. There was a significant interaction between FP and these factors (Fig. 3 ). FP was an independent risk factor for carotid plaque in participants without these complications compared with those with a history of hypertension or diabetes. DISCUSSION The economic and medical burdens of atherosclerotic heart disease are increasing worldwide. Atherosclerosis will further develop into acute myocardial infarction or even sudden cardiac death and other serious adverse consequences 16 . Therefore, the importance of early diagnosis and prevention of subclinical atherosclerosis is self-evident and can reduce the occurrence of adverse cardiovascular events to a certain extent 17 . The relationship between visceral fat deposition and cardiovascular disease has been the focus of clinical research 3 . Physiological and pathological changes in pancreatic fat infiltration have been gradually recognised. The histological feature of FP is an increase in the number of fat cells, and fat accumulation can be observed in the acinar and islet cells. Ectopic adipose tissue itself is a metabolic mediator in vivo, resulting in a significant increase in the release of inflammatory cytokines, e.g. fat tumour necrosis factor and interleukins. At the same time, it leads to the reduction of anti-atherosclerosis factor adiponectin, anti-inflammatory factors, and other protective substances in the body. These pathological changes may be closely related to atherosclerosis 18 . Numerous studies have shown that hepatic and epicardial lipid deposition is an emerging risk factor for subclinical atherosclerosis 19–20 . Recent studies on the correlation between FP and subclinical atherosclerosis have focused on CIMT. Sinan et al. 12 analysed 183 patients with fatty liver according to whether they had FP, and the results showed that the presence of FP was significantly correlated with CIMT. The same results as reported by Sinan et al. were obtained in a patient with biopsy-confirmed fatty liver disease 21 . CIMT is a valuable tool for detecting clinical atherosclerosis. Carotid plaque is a more potent predictor of cardiovascular disease risk than CIMT 22 . Here, we found that after correcting for known risk factors for subclinical atherosclerosis, such as sex, age, smoking history, drinking history, hypertension, diabetes, and hypercholesterolaemia, FP was still independently associated with carotid plaque. The aforementioned studies prove that FP can be used as a novel predictor of subclinical atherosclerosis in daily clinical practice 23 . LDL-C has the strongest association with carotid plaque among the lipid-related parameters. However, there was no correlation between LDL-C and carotid plaque in this study, which may be related to the small number of samples in our study or the treatment method. Further research on this is needed. Subgroup analyses were performed on the basis of other factors that were independently associated with carotid plaque, including hypertension and diabetes. FP pancreas had different intensity effects on atherosclerosis in different subgroups, including hypertension, diabetes, male sex, smoking history, and alcohol consumption history. This is similar to the results of Kim et al.’s study, which showed that FP was more strongly associated with CIMT in nonobese patients with type 2 diabetes than their counterparts 24 . Carotid plaque formation is caused by atherosclerosis of the neck arteries, which in turn is caused by smoking, hypertension, hyperlipidaemia, diabetes, and obesity. The accumulation of lipids and complex sugars under the intima of the artery, bleeding, and thrombosis occur, followed by fibrous tissue hyperplasia and calcium deposition, resulting in gradual thickening, hardening, and formation of plaque in the artery wall 25 . At present, there are few studies on the correlation between the presence of FP in metabolic diseases and carotid plaque; therefore, more studies are needed to prove these relevant issues. This study had some limitations. This was a cross-sectional study, so future prospective studies should be designed to further reveal the causal relationship between FP and the development of subclinical atherosclerosis. However, our study is the first to explore the association of FP with metabolic diseases and carotid plaque, specifically elevated LDL-C levels, in a large natural population cohort. It also provides clinical data for current clinical research, which has great public health significance and emphasises the importance of monitoring and follow-up for subclinical atherosclerosis in the population with FP. CONCLUSION We found that FP was an independent risk factor for carotid plaque formation, and it had a greater impact in people without a history of hypertension or diabetes than those with. Abbreviations CVD, cardiovascular disease; FP, fatty pancreas; NAFLD, non-alcoholic fatty liver disease; CIMT, carotid intima-media thickness; TG, triglycerides; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; HTG, hypertriglyceridaemia; HTC, hypercholesterolaemia; HDL-C, high-density lipoprotein cholesterol; OR, odds ratio Declarations Ethics approval and consent to participate This study conformed to the principles of the Declaration of Helsinki and was approved by the Ethics Committee of the Affiliated Hospital of Yangzhou University. Consent for publication Not applicable. Availability of data and materials All data generated or analysed during this study are included in this published article. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported by the Yangzhou Key Research and Development Plan (number [no.]: YZ2022080) and National Natural Science Foundation Project (no.: 82370653). Authors’ contributions QL, XL, and YW: study concept and design, data analysis and interpretation, and drafting of the manuscript. WL, XD, QZ, and CY: data acquisition and statistical analysis. GL, WX, and XY: study concept and design, data analysis and interpretation, critical revision of the manuscript for important intellectual content, and study supervision. Acknowledgements References Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al. Global burden of cardiovascular diseases and risk factors, 1990-2019: Update from the GBD 2019 Study. J Am Coll Cardiol. 2020;76:2982-3021. Katsiki N, Athyros VG, Mikhailidis DP. 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Prediction of cardio- and cerebro-vascular events in patients with subclinical carotid atherosclerosis and low HDL-cholesterol. Atherosclerosis. 2008;200:389-95. Kim MK, Chun HJ, Park JH, Yeo DM, Baek KH, Song KH, et al. The association between ectopic fat in the pancreas and subclinical atherosclerosis in type 2 diabetes. Diabetes Res Clin Pract. 2014;106:590-6. Libby P. The changing landscape of atherosclerosis. Nature. 2021;592:524-33. Additional Declarations No competing interests reported. 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University, Yangzhou University","correspondingAuthor":true,"prefix":"","firstName":"Xiaoping","middleName":"","lastName":"Yu","suffix":""}],"badges":[],"createdAt":"2024-04-12 15:05:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4258548/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4258548/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54859308,"identity":"83cac2f4-9df8-405b-aaf3-96644e49c45d","added_by":"auto","created_at":"2024-04-17 19:05:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":50505,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of participant selection\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4258548/v1/d24a7d67e8c88a6f0648b270.png"},{"id":54859309,"identity":"8217d1db-b8c7-4446-8533-93ff91e3e488","added_by":"auto","created_at":"2024-04-17 19:05:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":110999,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of univariate analysis of carotid plaque\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOR, odds ratio; CI, confidence interval; BMI, body mass index; HBP, high blood pressure; DM, diabetic mellitus; LHDL-C, low high-density lipoprotein cholesterol; FP, fatty pancreas; TG, total triglyceride; TC, total cholesterol; HDL-Ch, high-density lipoprotein cholesterol; LDL, low-density lipoprotein; ALT, alanine transaminase; AST, aspartate transaminase; HTG, hypertriglyceridaemia;\u003c/p\u003e\n\u003cp\u003eHTC, hypercholesterolaemia; HLP, hyperlipidaemia.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4258548/v1/dd9f72463e00f44cb6460fa7.png"},{"id":54859310,"identity":"ee841354-ccd2-4ceb-b6eb-df279967a8d1","added_by":"auto","created_at":"2024-04-17 19:05:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":267648,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of subgroup analysis of the association between fatty pancreas and carotid plaque\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOR, odds ratio; CI, confidence interval; HBP, high blood pressure; DM, diabetes mellitus\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4258548/v1/b1e99e084ab0e9d8f698951e.png"},{"id":54859559,"identity":"9d5fa210-3b0c-4ba2-97a4-9618f0624a82","added_by":"auto","created_at":"2024-04-17 19:13:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":815101,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4258548/v1/ffd0b7a9-de7b-4feb-bd45-734a294448da.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of fatty pancreas and subclinical atherosclerosis: A cross-sectional analysis","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eCardiovascular disease (CVD) is the leading cause of death worldwide. There were 18.6\u0026nbsp;million deaths due to cardiovascular diseases worldwide in 2019, which was 6.5\u0026nbsp;million more than that 30 years ago. In China, deaths due to atherosclerotic cardiovascular disease increased by 1.3\u0026nbsp;million during the same period \u003csup\u003e1\u003c/sup\u003e. Obesity can lead to ectopic fat deposition in the subcutaneous and visceral tissues, and adipose tissue distribution is closely associated with the risk of cardiovascular diseases. Visceral fat carries a greater risk of cardiovascular disease than subcutaneous fat tissue \u003csup\u003e2\u003c/sup\u003e. Common organs with ectopic fat deposits include the liver, heart, and pancreas \u003csup\u003e3\u0026ndash;4\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFat deposition occurs earlier in the pancreas than in the liver, and the fatty pancreas (FP) can be used as an initial indicator of fatty ectopic deposition \u003csup\u003e5\u003c/sup\u003e. In recent years, FP, an organ of fatty ectopic deposition, has attracted extensive attention and research. The pancreatic parenchymal and stromal cells of FP undergo pathological and physiological changes of steatosis and triglyceride deposition. This may be due to increased insulin resistance and pathophysiological changes in the production of pro-inflammatory substances in visceral adipose tissue \u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA 30-year follow-up study of 229 patients after biopsy confirmed non-alcoholic fatty liver disease (NAFLD) found a significantly increased risk of death due to cardiovascular disease (hazard ratio: 1.55, 95% confidence interval: 1.11\u0026ndash;2.15, P\u0026thinsp;=\u0026thinsp;0.01) \u003csup\u003e7\u0026ndash;8\u003c/sup\u003e. Kadir et al. \u003csup\u003e9\u003c/sup\u003e reported that NAFLD can be used as an independent risk factor for predicting subclinical atherosclerosis, which is closely related to cardiovascular events, and carotid plaque is a strong predictor of cardiovascular events \u003csup\u003e10\u003c/sup\u003e. Carotid ultrasound follow-up plays an important role in the monitoring and management of adverse cardiovascular events and can be used to noninvasively monitor the presence of subclinical atherosclerosis \u003csup\u003e11\u003c/sup\u003e. Studies have shown that FP is independently correlated with carotid intima-media thickness (CIMT) \u003csup\u003e12\u003c/sup\u003e. To date, no correlation between FP and carotid plaque has been reported. Therefore, this study investigated the correlation between FP and carotid plaque in a large medical examination cohort in Yangzhou.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design and population\u003c/h2\u003e \u003cp\u003eThe clinical data of patients who underwent a physical examination at the Health Management Centre of the Affiliated Hospital of Yangzhou University from January 2018 to December 2021 were collected to investigate the correlation between FP and carotid plaque. According to the inclusion and exclusion criteria, 24 045 participants were included. A cross-sectional analysis of the clinical data of the enrolled participants was performed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.1.1 Inclusion and exclusion criteria\u003c/h2\u003e \u003cp\u003eAll physical examinations that were performed at the Health Management Centre of the Affiliated Hospital of Yangzhou University between January 2018 and December 2021 with complete cervical vascular colour Doppler ultrasonography examinations were included. Patients diagnosed with malignant diseases, such as chronic diseases of the pancreas, liver, kidney, or tumours, who had incomplete clinical and biochemical data were excluded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.1.3 Ethics statements\u003c/h2\u003e \u003cp\u003e This study conformed to the principles of the Declaration of Helsinki and was approved by the Ethics Committee of the Affiliated Hospital of Yangzhou University.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Research method\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Subclinical atherosclerosis\u003c/h2\u003e \u003cp\u003eCIMT in subclinical atherosclerosis was measured by an experienced radiologist at the Health Management Centre using a B-ultrasound machine with a frequency of 3\u0026ndash;5 Hz. Each participant was examined in the supine position with the head rotated to the opposite side. Carotid subclinical atherosclerosis was defined as the presence of carotid plaque, i.e. an abnormal increase in CIMT (\u0026gt;\u0026thinsp;1.2 mm) \u003csup\u003e13\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.2.2 Data acquisition\u003c/h2\u003e \u003cp\u003eGeneral information, including sex, age, height, and weight, was recorded. Previous medical history, including smoking and drinking history, hypertension, diabetes, and FP, was collected. Laboratory indicators, including triglycerides (TG), total cholesterol (TC), low high-density lipoprotein cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) levels, were also recorded. The body mass index (BMI) of each participant was calculated according to general data as follows: =weight (kg)/height squared (m\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.2.3 Diagnostic criteria\u003c/h2\u003e \u003cp\u003eSmoking history: smoking at least one cigarette a day, lasting\u0026thinsp;\u0026gt;\u0026thinsp;6 months or quitting smoking for \u0026lt;\u0026thinsp;15 years.\u003c/p\u003e \u003cp\u003eDrinking history: daily ethanol intake\u0026thinsp;\u0026ge;\u0026thinsp;20 g for men and \u0026ge;\u0026thinsp;10 g for women, and continuous or cumulative drinking for \u0026gt;\u0026thinsp;6 months.\u003c/p\u003e \u003cp\u003eAbnormal lipid metabolism: Hypertriglyceridaemia (HTG) is a metabolic disorder, defined when the serum or plasma triglyceride concentration is \u0026gt;\u0026thinsp;1.7 mmol/L \u003csup\u003e14\u003c/sup\u003e. Hypercholesterolaemia (HTC) was defined as a serum cholesterol level\u0026thinsp;\u0026gt;\u0026thinsp;6.2 mmol/L.\u003c/p\u003e \u003cp\u003eMixed hyperlipidaemia refers to hyperlipidaemia in which triglycerides and cholesterol are simultaneously elevated. Mixed hyperlipidaemia is often characterised by elevated cholesterol or elevated TG \u003csup\u003e15\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.2.4 FP\u003c/h2\u003e \u003cp\u003eThe diagnosis of fat pancreas was made simultaneously by experienced radiologists at the Health Management Centre using a high-resolution ultrasound system (LOGIQ E9; GE, Boston, MA USA) with a 3.5\u0026ndash;5-MHz probe. Ultrasound image characteristics of the FP: As the shape of the pancreas increases, the volume changes, and the outline is clear compared with the echo of neighbouring organs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eMeasurement data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, and the independent sample t-test was used to compare data between the groups. The statistical data are presented as number (%), and the χ\u003csup\u003e2\u003c/sup\u003e test was used to compare data between the groups. Logistic regression models were used to correct for confounding factors. Independent risk factors of carotid plaque were analysed, and subgroup analysis was performed. Logistic analysis was used to analyse the influence of FP subgroups on the prevalence of carotid plaque. SPSS Statistics (version 25.0; IBM Corp., Armonk, NY, USA) was used to analyse the data. A P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Analysis of participants\u0026rsquo; general clinical data and laboratory indicators\u003c/h2\u003e \u003cp\u003eA total of 6976 cases in the carotid plaque group and 17 069 cases in the non-carotid plaque group were included in this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Mean ages of the carotid plaque and non-carotid plaque groups were 63\u0026thinsp;\u0026plusmn;\u0026thinsp;12 and 50\u0026thinsp;\u0026plusmn;\u0026thinsp;12 years, respectively, and the difference between the groups was statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Smoking and drinking histories were significantly higher in the carotid plaque group than in the non-carotid plaque group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The prevalence of metabolic diseases, such as hypertension, diabetes, FP, and hypercholesterolaemia, was also significantly higher in the carotid plaque group than in the non-carotid plaque group (all, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). There was no significant difference in HTG levels between the groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.01). Mean values of LDL-C and ALT were higher in the carotid plaque group than in the non-carotid plaque group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but there were no statistically significant differences in the blood lipid indices (TG, high-density lipoprotein, and high-density lipoprotein cholesterol [HDL-Ch]) and liver function indices (AST) between the groups (all, P\u0026thinsp;\u0026gt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral clinical data and laboratory indicators in the carotid plaque and non-carotid plaque groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarotid plaque (n\u0026thinsp;=\u0026thinsp;6976)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-carotid plaque (n\u0026thinsp;=\u0026thinsp;17 069)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5542 (79.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 344 (72.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1434 (20.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4725 (27.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (ye)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2041 (29.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3797 (22.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2375 (34.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5257 (30.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2722 (39.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2775 (16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e760 (10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e497 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLHDL-C level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1253 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2946 (17.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e475 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e798 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG level (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC level (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-Ch level (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C level (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT level (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.00\u0026thinsp;\u0026plusmn;\u0026thinsp;25.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.30\u0026thinsp;\u0026plusmn;\u0026thinsp;24.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST level (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.50\u0026thinsp;\u0026plusmn;\u0026thinsp;14.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.90\u0026thinsp;\u0026plusmn;\u0026thinsp;11.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eBMI, body mass index; HBP, high blood pressure; DM, diabetic mellitus; LHDL-C, low high-density lipoprotein cholesterol; FP, fatty pancreas; TG, total triglyceride; TC, total cholesterol; HDL-Ch, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; ALT, alanine transaminase; AST, aspartate transaminase\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Logistic regression analysis of carotid plaque\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, univariate analysis with logistic regression was conducted to further analyse the independent risk factors for carotid plaque. Male sex (odds ratio [OR]\u0026thinsp;=\u0026thinsp;1.479, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), age (OR\u0026thinsp;=\u0026thinsp;1.110, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), BMI (OR\u0026thinsp;=\u0026thinsp;1.005, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), history of smoking (OR\u0026thinsp;=\u0026thinsp;1.446, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), history of alcohol consumption (OR\u0026thinsp;=\u0026thinsp;1.160, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hypertension (OR\u0026thinsp;=\u0026thinsp;3.296, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), diabetes mellitus (OR\u0026thinsp;=\u0026thinsp;4.077, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), FP (OR\u0026thinsp;=\u0026thinsp;1.490, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hypercholesterolaemia (OR\u0026thinsp;=\u0026thinsp;1.175, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and LDL atheroma (OR\u0026thinsp;=\u0026thinsp;1.174, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were risk factors for carotid plaque.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Influence of FP on the prevalence of carotid plaque in multivariate analysis\u003c/h2\u003e \u003cp\u003eUnivariate analysis showed that FP was independently associated with carotid plaque (OR\u0026thinsp;=\u0026thinsp;1.49, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, after correction for other factors, results of logistic regression analysis showed that regardless of Q1, Q2, or Q3 models, FP was correlated with carotid plaque (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effect of fatty pancreas on carotid plaque\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"19\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"15\" nameend=\"c18\" namest=\"c4\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c19\" namest=\"c19\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c12\" namest=\"c9\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c16\" namest=\"c13\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c19\" namest=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c19\" namest=\"c16\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatty pancreas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.49 (1.324\u0026ndash;1.674)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.207 (1.055\u0026ndash;1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e1.183 (1.032\u0026ndash;1.354)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e1.146 (1\u0026ndash;1.313)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"19\"\u003eNotes: Q1: Model 1 adjusted for sex, age, BMI, smoking history, and drinking history.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"19\"\u003eQ2: Model 2 adjusted for variables in Q1\u0026thinsp;+\u0026thinsp;HBP and DM.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"19\"\u003eQ3: Model 3 adjusted for variables in Q2\u0026thinsp;+\u0026thinsp;TG, TC, HDL-Ch, LDL-C, ALT, and AST.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"19\"\u003eBMI, body mass index; HBP, high blood pressure; DM, diabetes mellitus; TG, triglycerides; TC, total cholesterol; HDL-Ch, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; ALT, alanine aminotransferase; AST, aspartate aminotransferase\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Subgroup analysis off the association between FP and carotid plaque\u003c/h2\u003e \u003cp\u003eSubgroup analyses were conducted using model Q3 adjusted for sex, age, BMI, histories of smoking and drinking, HBP, DM, and levels of TG, TC, HDL-Ch, LDL, ALT, and AST. There was a significant interaction between FP and these factors (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). FP was an independent risk factor for carotid plaque in participants without these complications compared with those with a history of hypertension or diabetes.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe economic and medical burdens of atherosclerotic heart disease are increasing worldwide. Atherosclerosis will further develop into acute myocardial infarction or even sudden cardiac death and other serious adverse consequences \u003csup\u003e16\u003c/sup\u003e. Therefore, the importance of early diagnosis and prevention of subclinical atherosclerosis is self-evident and can reduce the occurrence of adverse cardiovascular events to a certain extent \u003csup\u003e17\u003c/sup\u003e. The relationship between visceral fat deposition and cardiovascular disease has been the focus of clinical research \u003csup\u003e3\u003c/sup\u003e. Physiological and pathological changes in pancreatic fat infiltration have been gradually recognised. The histological feature of FP is an increase in the number of fat cells, and fat accumulation can be observed in the acinar and islet cells. Ectopic adipose tissue itself is a metabolic mediator in vivo, resulting in a significant increase in the release of inflammatory cytokines, e.g. fat tumour necrosis factor and interleukins. At the same time, it leads to the reduction of anti-atherosclerosis factor adiponectin, anti-inflammatory factors, and other protective substances in the body. These pathological changes may be closely related to atherosclerosis \u003csup\u003e18\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNumerous studies have shown that hepatic and epicardial lipid deposition is an emerging risk factor for subclinical atherosclerosis \u003csup\u003e19\u0026ndash;20\u003c/sup\u003e. Recent studies on the correlation between FP and subclinical atherosclerosis have focused on CIMT. Sinan et al. \u003csup\u003e12\u003c/sup\u003e analysed 183 patients with fatty liver according to whether they had FP, and the results showed that the presence of FP was significantly correlated with CIMT. The same results as reported by Sinan et al. were obtained in a patient with biopsy-confirmed fatty liver disease \u003csup\u003e21\u003c/sup\u003e. CIMT is a valuable tool for detecting clinical atherosclerosis. Carotid plaque is a more potent predictor of cardiovascular disease risk than CIMT \u003csup\u003e22\u003c/sup\u003e. Here, we found that after correcting for known risk factors for subclinical atherosclerosis, such as sex, age, smoking history, drinking history, hypertension, diabetes, and hypercholesterolaemia, FP was still independently associated with carotid plaque. The aforementioned studies prove that FP can be used as a novel predictor of subclinical atherosclerosis in daily clinical practice \u003csup\u003e23\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eLDL-C has the strongest association with carotid plaque among the lipid-related parameters. However, there was no correlation between LDL-C and carotid plaque in this study, which may be related to the small number of samples in our study or the treatment method. Further research on this is needed. Subgroup analyses were performed on the basis of other factors that were independently associated with carotid plaque, including hypertension and diabetes. FP pancreas had different intensity effects on atherosclerosis in different subgroups, including hypertension, diabetes, male sex, smoking history, and alcohol consumption history. This is similar to the results of Kim et al.\u0026rsquo;s study, which showed that FP was more strongly associated with CIMT in nonobese patients with type 2 diabetes than their counterparts \u003csup\u003e24\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCarotid plaque formation is caused by atherosclerosis of the neck arteries, which in turn is caused by smoking, hypertension, hyperlipidaemia, diabetes, and obesity. The accumulation of lipids and complex sugars under the intima of the artery, bleeding, and thrombosis occur, followed by fibrous tissue hyperplasia and calcium deposition, resulting in gradual thickening, hardening, and formation of plaque in the artery wall \u003csup\u003e25\u003c/sup\u003e. At present, there are few studies on the correlation between the presence of FP in metabolic diseases and carotid plaque; therefore, more studies are needed to prove these relevant issues.\u003c/p\u003e \u003cp\u003eThis study had some limitations. This was a cross-sectional study, so future prospective studies should be designed to further reveal the causal relationship between FP and the development of subclinical atherosclerosis. However, our study is the first to explore the association of FP with metabolic diseases and carotid plaque, specifically elevated LDL-C levels, in a large natural population cohort. It also provides clinical data for current clinical research, which has great public health significance and emphasises the importance of monitoring and follow-up for subclinical atherosclerosis in the population with FP.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eWe found that FP was an independent risk factor for carotid plaque formation, and it had a greater impact in people without a history of hypertension or diabetes than those with.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCVD, cardiovascular disease; FP, fatty pancreas; NAFLD, non-alcoholic fatty liver disease; CIMT, carotid intima-media thickness; TG, triglycerides; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; HTG, hypertriglyceridaemia; HTC, hypercholesterolaemia; HDL-C, high-density lipoprotein cholesterol; OR, odds ratio\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study conformed to the principles of the Declaration of Helsinki and was approved by the Ethics Committee of the Affiliated Hospital of Yangzhou University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Yangzhou Key Research and Development Plan (number [no.]: YZ2022080) and\u0026nbsp;National Natural Science Foundation Project (no.: 82370653).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQL, XL, and YW: study concept and design,\u0026nbsp;data analysis and interpretation, and drafting of the manuscript. WL, XD, QZ, and CY:\u0026nbsp;data acquisition\u0026nbsp;and statistical analysis. GL, WX,\u0026nbsp;and XY: study concept and design, data analysis and interpretation, critical revision of the manuscript for important intellectual content, and study supervision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eRoth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al.\u0026nbsp;Global burden of cardiovascular diseases and risk factors, 1990-2019: Update from the GBD 2019 Study.\u0026nbsp;J Am Coll Cardiol. 2020;76:2982-3021.\u003c/li\u003e\n \u003cli\u003eKatsiki N, Athyros VG, Mikhailidis DP.\u0026nbsp;Abnormal peri-organ or intra-organ fat (APIFat) deposition: An underestimated predictor of vascular risk.\u0026nbsp;Curr Vasc Pharmacol. 2016;14:432-41.\u003c/li\u003e\n \u003cli\u003eDietrich\u0026nbsp;P,\u0026nbsp;Hellerbrand\u0026nbsp;C. Non-alcoholic fatty liver disease, obesity and the metabolic syndrome.\u0026nbsp;Best Pract Res Clin Gastroenterol. 2014;28:637-53.\u003c/li\u003e\n \u003cli\u003eSilva LLSE, Fernandes MSS, Lima EA, Stefano JT, Oliveira CP, Jukemura J.\u0026nbsp;Fatty Pancreas: Disease or finding.\u0026nbsp;Clinics (Sao Paulo).\u0026nbsp;2021;76:e2439.\u003c/li\u003e\n \u003cli\u003ePinnick KE, Collins SC, Londos\u0026nbsp;C,\u0026nbsp;Gauguier D, Clark A, Fielding BA.\u0026nbsp;Pancreatic ectopic fat is characterized by adipocyte infiltration and altered lipid composition.\u0026nbsp;Obesity (Silver Spring).\u0026nbsp;2008;16:522-30.\u003c/li\u003e\n \u003cli\u003eNeeland IJ, Ross\u0026nbsp;R,\u0026nbsp;Despr\u0026eacute;s JP, Matsuzawa Y, Yamashita S, Shai I,\u0026nbsp;et al. Visceral and ectopic fat, atherosclerosis, and cardiometabolic disease: a position statement.\u0026nbsp;Lancet Diabetes Endocrinol. 2019;7:715-25.\u003c/li\u003e\n \u003cli\u003eEslam\u0026nbsp;M,\u0026nbsp;Newsome PN, Sarin SK, Anstee QM, Targher G, Romero-Gomez M,\u0026nbsp;et al. A new definition for metabolic dysfunction-associated fatty liver disease: An international expert consensus statement.\u0026nbsp;J Hepatol. 2020;73:202-9.\u003c/li\u003e\n \u003cli\u003eEkstedt\u0026nbsp;M,\u0026nbsp;Hagstr\u0026ouml;m\u0026nbsp;H,\u0026nbsp;Nasr\u0026nbsp;P,\u0026nbsp;Fredrikson M, St\u0026aring;l P, Kechagias S,\u0026nbsp;et al. Fibrosis stage is the strongest predictor for disease-specific mortality in NAFLD after up to 33 years of follow-up.\u0026nbsp;Hepatology. 2015;61:1547-54.\u003c/li\u003e\n \u003cli\u003eZheng\u0026nbsp;J,\u0026nbsp;Zhou\u0026nbsp;Y,\u0026nbsp;Zhang\u0026nbsp;K,\u0026nbsp;Qi Y, An S, Wang S,\u0026nbsp;et al. Association between nonalcoholic fatty liver disease and subclinical atherosclerosis: A cross-sectional study on population over 40\u0026nbsp;years old.\u0026nbsp;BMC Cardiovasc Disord. 2018;18:147.\u003c/li\u003e\n \u003cli\u003eAhmadi\u0026nbsp;A,\u0026nbsp;Argulian\u0026nbsp;E,\u0026nbsp;Leipsic\u0026nbsp;J,\u0026nbsp;Newby DE, Narula J. From subclinical atherosclerosis to plaque progression and acute coronary\u0026nbsp;events: JACC state-of-the-art review.\u0026nbsp;J Am Coll Cardiol. 2019;74:1608-17.\u003c/li\u003e\n \u003cli\u003eCaproni\u0026nbsp;S,\u0026nbsp;Riva\u0026nbsp;A,\u0026nbsp;Barresi\u0026nbsp;G,\u0026nbsp;Costanti D, Costantini F, Galletti F,\u0026nbsp;et al. Predictors of carotid atherosclerosis progression: Evidence from an ultrasonography laboratory.\u0026nbsp;Brain Sci. 2022;12:1600.\u003c/li\u003e\n \u003cli\u003eSahin\u0026nbsp;S,\u0026nbsp;Karadeniz\u0026nbsp;A. Pancretic fat accumulation is associated with subclinical atherosclerosis.\u0026nbsp;Angiology. 2022;73:508-13.\u003c/li\u003e\n \u003cli\u003eWang\u0026nbsp;J,\u0026nbsp;Sun\u0026nbsp;H,\u0026nbsp;Wang\u0026nbsp;Y,\u0026nbsp;An Y, Liu J, Wang G. Glucose metabolism status modifies the relationship between lipoprotein(a) and carotid plaques in individuals with fatty liver disease. Front Endocrinol (Lausanne).\u0026nbsp;2022;13:947914.\u003c/li\u003e\n \u003cli\u003eKiss L, Fűr G, Pisipati S, Rajalingamgari P, Ewald N, Singh V, et al. Mechanisms linking hypertriglyceridemia to acute pancreatitis. Acta Physiol (Oxf). 2023;237:e13916.\u003c/li\u003e\n \u003cli\u003eBrahm AJ, Hegele RA.\u0026nbsp;Combined hyperlipidemia: familial but not (usually) monogenic. Curr Opin Lipidol.\u0026nbsp;2016;27:131-40.\u003c/li\u003e\n \u003cli\u003eOlvera Lopez\u0026nbsp;E,\u0026nbsp;Ballard BD, Jan\u0026nbsp;A. Cardiovascular disease.\u0026nbsp;Florida: Treasure Island StatPearls Publishing; 2022.\u003c/li\u003e\n \u003cli\u003eSigamani\u0026nbsp;A,\u0026nbsp;Gupta\u0026nbsp;R. Revisiting secondary prevention in coronary heart disease.\u0026nbsp;Indian Heart J. 2022;74:431-40.\u003c/li\u003e\n \u003cli\u003eOmran\u0026nbsp;F,\u0026nbsp;Christian\u0026nbsp;M. Inflammatory signaling and brown fat activity.\u0026nbsp;Front Endocrinol (Lausanne).\u0026nbsp;2020;11:156.\u003c/li\u003e\n \u003cli\u003eKoulaouzidis\u0026nbsp;G,\u0026nbsp;Charisopoulou\u0026nbsp;D,\u0026nbsp;Kukla\u0026nbsp;M,\u0026nbsp;Marlicz W, Rydzewska G, Koulaouzidis A,\u0026nbsp;et al. Association of non-alcoholic fatty liver disease with coronary artery calcification progression: a systematic review and meta-analysis.\u0026nbsp;Prz Gastroenterol. 2021;16:196-206.\u003c/li\u003e\n \u003cli\u003eKul\u0026nbsp;S,\u0026nbsp;Karadeniz\u0026nbsp;A,\u0026nbsp;Dursun\u0026nbsp;İ,\u0026nbsp;Şahin S, Faruk \u0026Ccedil;ırakoğlu \u0026Ouml;, Raşit Sayın M,\u0026nbsp;et al. Non-alcoholic fatty pancreas disease is associated with increased epicardial adipose tissue and aortic intima-media thickness.\u0026nbsp;Acta Cardiol Sin. 2019;35:118-25.\u003c/li\u003e\n \u003cli\u003eOzturk\u0026nbsp;K,\u0026nbsp;Dogan\u0026nbsp;T,\u0026nbsp;Celikkanat\u0026nbsp;S,\u0026nbsp;Ozen A, Demirci H, Kurt O,\u0026nbsp;et al. The association of fatty pancreas with subclinical atherosclerosis in nonalcoholic fatty liver disease.\u0026nbsp;Eur J Gastroenterol Hepatol. 2018;30:411-7.\u003c/li\u003e\n \u003cli\u003eNaqvi TZ, Lee MS.\u0026nbsp;Carotid intima-media thickness and plaque in cardiovascular risk assessment.\u0026nbsp;JACC Cardiovasc Imaging. 2014;7:1025-38.\u003c/li\u003e\n \u003cli\u003eRizzo\u0026nbsp;M,\u0026nbsp;Corrado\u0026nbsp;E,\u0026nbsp;Coppola\u0026nbsp;G,\u0026nbsp;Muratori I, Novo G, Novo S.\u0026nbsp;Prediction of cardio- and cerebro-vascular events in patients with subclinical carotid atherosclerosis and low HDL-cholesterol.\u0026nbsp;Atherosclerosis. 2008;200:389-95.\u003c/li\u003e\n \u003cli\u003eKim MK, Chun HJ, Park JH, Yeo DM, Baek KH, Song KH, et al.\u0026nbsp;The association between ectopic fat in the pancreas and subclinical atherosclerosis in type 2 diabetes.\u0026nbsp;Diabetes Res Clin Pract. 2014;106:590-6.\u003c/li\u003e\n \u003cli\u003eLibby P. The changing landscape of atherosclerosis. Nature. 2021;592:524-33.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"lipids-in-health-and-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"lhad","sideBox":"Learn more about [Lipids in Health and Disease](http://lipidworld.biomedcentral.com/)","snPcode":"12944","submissionUrl":"https://submission.nature.com/new-submission/12944/3","title":"Lipids in Health and Disease","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Carotid plaque, Cervical vascular ultrasound, Pancreatology, Subclinical atherosclerosis","lastPublishedDoi":"10.21203/rs.3.rs-4258548/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4258548/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eTo date, no correlation between fatty pancreas and carotid plaque has been reported. Therefore, this study used a large medical examination cohort from Yangzhou to investigate the association between fatty pancreas and subclinical atherosclerosis.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eClinical data were collected between January 2018 and December 2021 from a population undergoing health check-ups at the Health Management Centre of the Affiliated Hospital of Yangzhou University. Carotid vascular ultrasound findings were used to divide the participants into carotid plaque and non-carotid plaque groups on the basis of independent risk factors for carotid plaque.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eA total of 6976 cases in the carotid plaque group and 17 069 cases in the non-carotid plaque group were included in this study. Logistic regression model analysis of carotid plaque showed that men (odds ratio [OR]\u0026thinsp;=\u0026thinsp;1.479, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), age (OR\u0026thinsp;=\u0026thinsp;1.110, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), body mass index (OR\u0026thinsp;=\u0026thinsp;1.005, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), history of smoking (OR\u0026thinsp;=\u0026thinsp;1.446, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), history of alcohol consumption (OR\u0026thinsp;=\u0026thinsp;1.160, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hypertension (OR\u0026thinsp;=\u0026thinsp;3.296, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), diabetes mellitus (OR\u0026thinsp;=\u0026thinsp;4.077, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), fatty pancreas (OR\u0026thinsp;=\u0026thinsp;1.490, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hypercholesterolaemia (OR\u0026thinsp;=\u0026thinsp;1.175, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and low-density lipoprotein cholesterol atheroma (OR\u0026thinsp;=\u0026thinsp;1.174, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were independent risk factors for carotid plaque. Subgroup analysis indicated that fatty pancreas was an independent risk factor for carotid plaque in participants without these complications compared with participants with a history of hypertension or diabetes.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eFatty pancreas is an independent risk factor for carotid plaque and has a greater impact in individuals without a history of hypertension or diabetes than in those with.\u003c/p\u003e","manuscriptTitle":"Association of fatty pancreas and subclinical atherosclerosis: A cross-sectional analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-17 19:05:23","doi":"10.21203/rs.3.rs-4258548/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2024-06-06T06:23:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33092139642881218127727145851204389392","date":"2024-06-06T05:54:07+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-09T02:22:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"270891646089209140959890433091225575246","date":"2024-05-06T16:52:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"0ac7ef2d-1674-49e1-9d8a-21ae213e4206","date":"2024-05-01T19:44:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308330893600618283980488792720018910766","date":"2024-04-30T00:26:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-15T08:52:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-15T04:00:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-15T01:28:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Lipids in Health and Disease","date":"2024-04-12T15:04:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"lipids-in-health-and-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"lhad","sideBox":"Learn more about [Lipids in Health and Disease](http://lipidworld.biomedcentral.com/)","snPcode":"12944","submissionUrl":"https://submission.nature.com/new-submission/12944/3","title":"Lipids in Health and Disease","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"17ad2bc7-9ed1-4514-b7bf-72c971bb420c","owner":[],"postedDate":"April 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-04-17T19:05:23+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-17 19:05:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4258548","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4258548","identity":"rs-4258548","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}