Relationship between the triglyceride–glucose index, blood uric acid levels, and prevalence of gout in Korean adults: Eighth Korean National Health and Nutrition Examination Survey (2019–2021)

Relationship between the triglyceride–glucose index, blood uric acid levels, and prevalence of gout in Korean adults: Eighth Korean National Health and Nutrition Examination Survey (2019–2021) | 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 Relationship between the triglyceride–glucose index, blood uric acid levels, and prevalence of gout in Korean adults: Eighth Korean National Health and Nutrition Examination Survey (2019–2021) Taejin Ahn, Young-Sang Kim, Yang-Im Hur, Moon Jong Kim, Ji-Hee Haam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4223516/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : The triglyceride and glucose (TyG) index is a useful marker of insulin resistance and metabolic syndrome. Several studies have reported a link between this index and serum uric acid levels. However, few studies have shown a concrete association between the TyG index, uric acid levels, and prevalence of gout. The objective of this study was to investigate the correlation between this index and uric acid levels, as well as their potential associations with the incidence of gout. Methods: Data derived from the Eighth Korea National Health and Nutrition Examination Survey conducted from 2019 to 2021 were used. The study population included adults >19 years of age andconsisted of 16,340 participants who were subjected to blood tests to measure their fasting blood glucose and triglyceride levels. Additionally, the participants responded to a questionnaire regarding the diagnosis of gout, making them eligible for inclusion in the study. The TyG index was categorized into quartiles. Results: Of the 16,340 total subjects, 321(2.1 %) were diagnosed with gout. After an adjustment for age and metabolic parameters, the TyG index was positively related to serum uric acid levels (β = 0.247, p < 0.001). Compared to the risk in the lowest quartile group, as a reference, the adjusted odd ratio, with a 95 % confidence interval, for the incidence of gout was 2.002 (1.157–3.465) in the highest quartile group. Conclusion: An elevated TyG index is associated with increased blood uric acid levels, and the TyG index is also associated with the prevalence of gout. triglyceride and glucose index gout uric acid Figures Figure 1 Figure 2 Figure 3 Introduction Gout is the most common form of inflammatory arthritis, and its global prevalence is increasing [1]. This condition is precipitated by the accumulation of monosodium urate crystals in the joints, and hyperuricemia is a pivotal factor in gout and is considered a cause of monosodium urate crystal formation [2, 3]. Meanwhile, the manifestation of gout does not occur in all patients with hyperuricemia, and its occurrence is influenced by various other contributing factors. Structural damage at topological points, immune responses, connective tissue factors, and genetic variations all contribute to this process [3]. The triglyceride glucose (TyG) index, comprising measurements of serum triglyceride levels and fasting plasma glucose concentrations, is considered a surrogate indicator for evaluating insulin resistance [4, 5]. Furthermore, it is significantly associated with coronary vessel disease, type 2 diabetes mellitus, and several metabolic disturbances. [6-8]. Several studies have reported an association between the TyG index and hyperuricemia [9-11] suggesting that the TyG index may also be related to gout. However, few studies have investigated the association between the TyG index and the prevalence of gout so far. Moreover, previous investigations included a notably limited cohort of participants. Therefore, this study aimed to determine the relationship between the TyG index, uric acid levels, and the incidence of gout in Korean adults using data from the eighth Korean National Health and Nutrition Examination Survey (2019–2021). Methods Study population Raw datasets from the Eighth Korea National Health and Nutrition Examination Survey (KNHANES) by the Korea Centers for Disease Control and Prevention were used. The national survey program assessed the health and nutritional status of Koreans. The raw data from the KNHANES are a composite sample with statistical weights applied, and a complex sample analysis method was used. Complex sample data were analyzed by referring to a primary sampling unit , a secondary sampling unit representing residential types, and survey weight to analyze the complex sample data. The method for KNHANES has been described previously [12]. In total, 22,559 individuals participated in the KNHANES from 2019 to 2021 and the process of selecting study subjects is shown in Fig. 1. We excluded participants younger than 19 years of age (n =3,868), those who fasted for less than 8 h, and those who did not fast (n = 1,246). Of the remaining 17,445 subjects, we further excluded two participants for whom the serum uric acid data were missing (n = 11). Responses to the gout-related questionnaire were also missing for some participants (n = 1.094). Ultimately, 16,340 individuals (7,259 males and 9,081 females) were included. This study was approved by the Institutional Review Board of CHA Bundang Medical Center (approval no. 2023-07-0731). The requirement for written informed consent was waived owing to the retrospective design of the study. Medical history and lifestyle habits The medical history, medications, and lifestyle habits of the participants were recorded. In the health survey, specific disease prevalence, medication use, physical activity, and nutrition-related sections were assessed through face-to-face interviews. Participants were categorized as non-smokers or current smokers based on their smoking habits. Significant alcohol consumption was defined as >1 standard drink/month over 1 year. Significant physical activity was defined as walking or riding a bicycle for more than 10 minutes when moving to another place. Anthropometric measurements Height was measured using a stadiometer SECA 274 (SECA Deutschland, Hamburg, Germany), and weight was measured using a weighing scale GL-6000-20 (G-Tech International, Uijeongbu, Korea). The participants removed their clothing and wore disposable examination gowns. Height and weight were measured in cm and kg, respectively. Body mass index (BMI) was calculated by dividing the weight (kg) by the square of height (m). Blood pressure was measured in a sitting position using a Greenlight 300 Sphygmomanometer (Accoson, Irvine, United Kingdom) with an appropriate cuff size. Blood pressure was calculated as the average of the second and third measurements following a total of three consecutive measurements. Biochemical measurements Blood samples were collected from the antecubital vein after at least 8 hours of fasting. Fasting plasma glucose, HbA1c, insulin, triglyceride, aspartate aminotransferase (AST), alanine transaminase (ALT), and uric acid levels were measured using a chemistry autoanalyzer. The TyG index was calculated using the formula below, as defined in previous studies [13]: TyG index = ln[fasting triglycerides (mg/dL) × fasting glucose (mg/dL) / 2]. Statical analysis SPSS version 25.0 (IBM, Armonk, NY, USA) was used for all the data analyses. All the continuous variables are reported as the means ± standard errors (SEs). Categorical variables are expressed as numbers (percentages). The statistical significance level for all the tests was set at p < 0.05. Associations between the TyG index and serum uric acid levels were tested based on covariate-adjusted multivariable regression with adjustments for the confounding factors. Age and sex were included in Model 1. In addition to those variables included in Model 1, Model 2 adjusted for BMI, smoking and alcohol history, physical activity, and medication history for hypertension, diabetes mellitus, and dyslipidemia. In addition to what was adjusted for in Model 2, Model 3 also adjusted for systolic blood pressure (BP), AST, and ALT. Multivariate logistic regression analysis was performed to evaluate the odds ratios (ORs) with 95 % confidence intervals for gout prevalence according to the TyG index quartiles. The ORs for gout prevalence were estimated based on the aforementioned adjustments (Model 1 and Model 2). Systolic BP, AST, ALT, and serum uric acid levels were additionally adjusted (Model 3). Results General characteristics of the study participants The baseline characteristics of the study participants are presented in Table 1. Of the 16,340 subjects, 321 (2.1 %) were diagnosed with gout. Of the 321 patients with gout, 279 (90.7 %) were men, and their mean age was 53.18 ± 0.813 years. Participants with gout had a higher rate of drinking than those without gout. Moreover, patients with gout had significantly higher fasting glucose, HbA1c, insulin, and triglyceride levels than those without gout. The uric acid levels in the subjects without gout and those with gout were 5.25 ± 0.015 mg/dL and 6.86 ± 0.109 mg/dL, respectively. Further, the TyG index was significantly higher in the subjects with gout than in those without gout (8.5798 ± 0.01 vs. 9.0284 ± 0.05, respectively). Table 1. General characteristics of the study population Total (=16340) Non-Gout (=16019) Gout (=321) p Age 47.62 ± 0.245 47.51 ± 0.247 53.18 ± 0.813 <0.001 Sex (men) 7259 (44.4 %) 6980 (49.0 %) 279 (90.7 %) <0.001 Alcohol 8449 (56 %) 8247 (55.7 %) 202 (67.7 %) <0.001 Smoking 2707 (19.1 %) 2624 (18.9 %) 83 (28.1 %) <0.001 Physical activity 8266 (51.6 %) 8125 (51.8 %) 141 (41.8 %) 0.002 Medication History Hypertension 3859 (18.5 %) 3703 (18.0 %) 156 (42.4 %) 0.669 Diabetes 1653 (8.1 %) 1608 (7.9 %) 45 (13.3 %) 0.449 Dyslipidemia 2725 (13.6 %) 2621 (13.2 %) 104 (29 %) 0.143 Anthropometry and measurements BMI (kg/m2) 24.14±0.041 24.10±0.041 25.90±0.275 <0.001 Systolic BP (mm Hg) 118.22±0.194 75.35±0.125 124.36±0.951 <0.001 Diastolic BP (mm Hg) 75.43±0.124 100.63±0.235 79.51±0.734 <0.001 Laboratory tests Fasting glucose (mg/dl) 100.73±0.235 100.63±0.235 105.66±1.794 <0.001 HbA1c (%) 5.75±0.009 5.75±0.008 5.89±0.066 <0.001 Insulin (IU/mL) 9.43±0.083 9.39±0.084 11.50±0.506 <0.001 Total cholesterol (mg/dL) 192.08±0.390 192.19±0.392 186.81±2.679 <0.001 Triglyceride (mg/dL) 131.79±1.145 130.30±1.132 202.24±12.133 <0.001 HDL cholesterol (mg/dL) 52.29±0.145 52.42±0.146 46.11±0.650 <0.001 LDL cholesterol (mg/dL) 117.18±0.925 117.99±0.937 100.80±4.916 <0.001 AST (U/L) 24.80±0.150 24.67±0.151 30.84±1.393 <0.001 ALT (U/L) 24.47±0.210 24.32±0.213 31.43±1.380 <0.001 Uric acid (mg/dL) 5.28±0.015 5.25±0.015 6.86±0.109 <0.001 TyG index 8.5891±0.00718 8.5798±0.00715 9.0284±0.04773 <0.001 Values are presented as n, mean (SE), or n, percentage (SE), unless otherwise indicated. Abbreviations: BMI, body mass index; BP, blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein; AST, aspartate aminotransferase; ALT, alanine transaminase; TyG, triglyceride and glucose Correlation between the TyG index and serum uric acid concentrations The correlation between the TyG index and serum uric acid concentrations was also evaluated (Table 2).The TyG index was positively associated with the serum uric acid concentrations after adjusting for metabolic parameters. Table 2. Regression coefficients of the metabolic parameters for serum uric acid levels Model 1 * Model 2 ** Model 3 *** β p β p β p TyG index 0.402 <0.001 0.283 <0.001 0.247 <0.001 Age –0.012 <0.001 –0.011 <0.001 –0.012 <0.001 Sex 1.403 <0.001 1.334 <0.001 1.291 <0.001 BMI 0.071 <0.001 0.061 <0.001 smoking –0.053 0.119 –0.053 0.12 alcohol 0.083 <0.001 0.081 <0.001 physical activity 0.019 0.398 0.026 0.241 Hypertension 0.218 <0.001 0.195 <0.001 Diabetes –0.442 <0.001 –0.422 <0.001 dyslipidemia –0.182 <0.001 –0.189 <0.001 systolic BP 0.004 <0.001 AST 0.006 <0.001 ALT 0.002 0.036 * Adjusted for age and sex ** Additional adjustments, including those for BMI, smoking and alcohol history, physical activity, and medication history for hypertension, diabetes mellitus, and dyslipidemia *** Additional adjustments, including those for systolic BP, AST, and ALT Abbreviations: TyG, triglyceride and glucose; BMI, body mass index; BP, blood pressure; AST, aspartate aminotransferase; ALT, alanine transaminase Association between the TyG index quartiles, uric acid levels, and prevalence of gout The participants were divided into four groups according to their TyG index values. Figure 2 shows the serum acid levels and gout prevalence according to the TyG index quartiles, respectively. Figure 3 and Table 3 show the ORs of the high-level TyG index groups based on the prevalence of gout through logistic analysis; the ORs corresponding to gout incidence in the groups were analyzed compared to those in the lowest quartile group. In the unadjusted model, the 2 nd , 3 rd , and 4 th quartile groups had a significantly higher prevalence of gout than the lowest quartile group. After adjusting for all the metabolic parameters, only the highest quartile (4th quartile) group had a significantly higher incidence of gout than the lowest quartile group (Table 3). Table 3. Odds ratios and 95 % confidence intervals for gout incidence based on the TyG index quartiles TyG index quartiles Q1 Q2 Q3 Q4 Unadjusted 1.00 (Reference) 2.020 (1.204–3.388) 3.864 (2.410–6.197) 6.256 (3.962–9.876) Adjusted Model 1 * 1.00 (Reference) 1.424 (0.849–2.388) 2.305 (1.434–3.706) 3.134 (1.962–5.006) Model 2 ** 1.00 (Reference) 1.258 (0.739–2.142) 1.918 (1.161–3.169) 2.521 (1.517–4.191) Model 3 *** 1.00 (Reference) 1.201 (0.691–2.087) 1.703 (0.995–2.913) 2.002 (1.157–3.465) The participants were divided into four groups according to their TyG index values. The group with the lowest values among the four groups was denoted Q1, followed by Q2, Q3, and Q4. * Adjusted for age and sex ** Additional adjustments, including those for BMI, smoking and alcohol history, physical activity, and medication history for hypertension, diabetes mellitus, and dyslipidemia *** Additional adjustments, including those for systolic BP, AST, ALT, and uric acid Abbreviations: TyG, triglyceride and glucose; BMI, body mass index; BP, blood pressure; AST, aspartate aminotransferase; ALT, alanine transaminase Discussion In this study, the TyG index was determined to be associated with uric acid levels after adjusting for confounding factors. The incidence of gout was high in the highest quartile group of the TyG index compared to the lowest quartile group. This association was valid even after adjusting for all the metabolic parameters. The TyG index has been identified as an exemplary indicator of insulin resistance in many previous studies [14-17]. Moreover, it has been reported to be associated with cardiovascular disease, diabetes, metabolic syndrome, obesity, and non-alcoholic fatty liver disease [5, 18-20]. However, no previous studies have demonstrated the TyG index as a surrogate factor for gout. Biologically plausible mechanisms support the significant association between the TyG index and gout. As mentioned previously, the TyG index serves as an indicator of insulin resistance, a condition that increases uric acid concentrations by diminishing the renal excretion of uric acid and concurrently promoting elevated triglyceride levels that contribute to the development of gout. In this study, the TyG index showed a positive correlation with serum uric acid levels even after considering other metabolic factors. Previous studies have shown that the TyG index is associated with obesity and that adipose tissue promotes uric acid production, thus causing an increase in serum uric acid levels [21, 22]. In this study, the TyG index also showed a positive correlation with serum uric acid levels even after considering other metabolic factors. Insulin resistance further reflects a state of low-grade inflammation in the body, which could also affect the occurrence of gout [23]. Interestingly, in this study, the TyG index was also associated with gout even after adjusting for all the metabolic parameters including uric acid levels. Our study had several limitations. First, it was cross-sectional; thus, we could not demonstrate a causative relationship between the TyG index and gout. Second, we lacked the dietary history of the participants, a factor that could potentially be linked to the occurrence of gout. Additional long-term studies considering the metabolic status of patients can help to mitigate this limitation. In conclusion, the TyG index, a marker of insulin resistance, is an independent prognostic factor for gout. Specifically, a higher TyG index is associated with a higher serum uric acid level. Moreover, we demonstrated that the TyG index might contribute to the development of gout through alternative mechanisms even after adjusting for serum uric acid levels. Therefore, a longitudinal and comprehensive study investigating the impact of the TyG index on gout development is required. Declarations Conflict of interest No potential conflicts of interest relevant to this article are reported. Ethics approval and consent to participate This study was approved by the Institutional Review Board of CHA Bundang Medical Center (approval no. 2023-07-0731). Informed consent was obtained from all eligible participants. Financial disclosure The authors have no financial disclosures related to this report. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4223516","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":289158309,"identity":"d97f3dfb-5318-4082-8d01-82aa22c9231b","order_by":0,"name":"Taejin Ahn","email":"","orcid":"","institution":"CHA Bundang Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Taejin","middleName":"","lastName":"Ahn","suffix":""},{"id":289158310,"identity":"05f566cb-aeeb-4373-8b05-d8b2e837fdbe","order_by":1,"name":"Young-Sang Kim","email":"","orcid":"","institution":"CHA Bundang Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Young-Sang","middleName":"","lastName":"Kim","suffix":""},{"id":289158311,"identity":"66b1c86e-77da-4120-a46c-3b4fc00c68a9","order_by":2,"name":"Yang-Im Hur","email":"","orcid":"","institution":"CHA Bundang Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Yang-Im","middleName":"","lastName":"Hur","suffix":""},{"id":289158312,"identity":"af4fd277-6a32-43cc-8a78-3d052dba7f10","order_by":3,"name":"Moon Jong Kim","email":"","orcid":"","institution":"CHA Bundang Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Moon","middleName":"Jong","lastName":"Kim","suffix":""},{"id":289158313,"identity":"dc919d15-c40b-46c4-b3db-f74d0894baea","order_by":4,"name":"Ji-Hee Haam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYBACAyA2ZjCwATPAQIJILWkkamFmYDhMghZz9tMJxQUF5+WBjMQPDDU2DJKzD+DXYtmTu8F4hsFtw509uZslGI6lMUjzJRBw2AGgFh6D2wlAxjYGxobDDHI8hPxy/i1Iy7kEIINYLTfAthxIADIgWqQJawHbkmy44cbbzRIJx9J4JHsIOix3mzHPHzt5IGPjhw81NnISZwhoAQI2eJQwJDAwEHIWGDA/IEbVKBgFo2AUjGAAACybPsiS0+lEAAAAAElFTkSuQmCC","orcid":"","institution":"CHA Bundang Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Ji-Hee","middleName":"","lastName":"Haam","suffix":""}],"badges":[],"createdAt":"2024-04-05 14:13:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4223516/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4223516/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54596897,"identity":"23d49394-234d-4299-aa3c-a05023376787","added_by":"auto","created_at":"2024-04-12 19:09:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":118370,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSelection of the study sample from the total number of participants\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4223516/v1/45a8c86a01630c911d9d241d.jpg"},{"id":54597494,"identity":"2f507766-8d83-4bb7-b839-a05b56a896fb","added_by":"auto","created_at":"2024-04-12 19:17:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":279045,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea Serum uric acid levels according to the TyG index quartiles\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb Prevalence of gout according to the TyG index quartiles\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe participants were divided into four groups according to their TyG index values. The group with the lowest values among the four groups was denoted Q1, followed by Q2, Q3, and Q4.\u003c/p\u003e\n\u003cp\u003eError bars show 95 % CI.\u003c/p\u003e\n\u003cp\u003eCI = confidence interval.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4223516/v1/9bbfd66a67402d8efc0e6aad.jpg"},{"id":54596898,"identity":"ef3935f1-113e-42f1-a9e3-70e5a71f4f2f","added_by":"auto","created_at":"2024-04-12 19:09:57","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":177434,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe odds ratios of high-level TyG index for gout prevalence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eError bars show 95 % CI\u003c/p\u003e\n\u003cp\u003eOR = odds ratio, CI = confidence interval.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4223516/v1/33ea0f1c92bd821115008180.jpg"},{"id":58619581,"identity":"e3ef3d97-a898-4f87-920e-6c41c791ca1a","added_by":"auto","created_at":"2024-06-19 02:41:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1895888,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4223516/v1/f00ea41d-cc38-423c-92a5-fbf50c96671b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Relationship between the triglyceride–glucose index, blood uric acid levels, and prevalence of gout in Korean adults: Eighth Korean National Health and Nutrition Examination Survey (2019–2021)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGout is the most common form of inflammatory arthritis, and its global prevalence is increasing [1]. This condition is precipitated by the accumulation of monosodium urate crystals\u0026nbsp;in the joints,\u0026nbsp;and hyperuricemia is a pivotal factor in gout and is considered\u0026nbsp;a cause\u0026nbsp;of monosodium urate crystal formation [2, 3].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eMeanwhile,\u0026nbsp;the manifestation of gout does not occur in all patients with hyperuricemia, and its occurrence is influenced by various other contributing factors.\u0026nbsp;Structural damage at topological points, immune responses, connective tissue factors, and genetic variations all contribute to this process [3].\u003c/p\u003e\n\u003cp\u003eThe triglyceride glucose (TyG) index, comprising measurements of serum triglyceride levels and fasting plasma glucose concentrations, is considered a surrogate indicator for evaluating insulin resistance [4, 5].\u0026nbsp;Furthermore, it is significantly associated with coronary vessel disease, type 2 diabetes mellitus, and several metabolic disturbances. [6-8].\u0026nbsp;Several studies have reported an association between\u0026nbsp;the TyG index and hyperuricemia\u0026nbsp;[9-11]\u0026nbsp;suggesting that the TyG\u0026nbsp;index\u0026nbsp;may also be related to gout.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, few studies have investigated the association between the TyG index and the prevalence of gout so far. Moreover, previous investigations included a notably limited cohort of participants. Therefore, this study aimed to determine the relationship between the TyG index, uric acid levels, and the incidence of gout in Korean adults using data from the eighth Korean National Health and Nutrition Examination Survey (2019\u0026ndash;2021).\u003c/p\u003e"},{"header":"Methods ","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy population\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw datasets from the Eighth Korea National Health and Nutrition Examination Survey (KNHANES) by the Korea Centers for Disease Control and Prevention were used. The national survey program assessed the health and nutritional status of Koreans.\u0026nbsp;The raw data from the KNHANES are a composite sample with statistical weights applied, and a complex sample analysis method was used. Complex sample data were analyzed by referring to a primary sampling unit , a\u0026nbsp;secondary sampling unit representing residential types, and\u0026nbsp;survey weight\u0026nbsp;to analyze the complex sample data.\u0026nbsp;The method for KNHANES has been described previously [12].\u003c/p\u003e\n\u003cp\u003eIn total, 22,559 individuals participated in the KNHANES from 2019 to 2021 and the process of selecting study subjects\u0026nbsp;is shown in Fig. 1.\u0026nbsp;We excluded participants younger than 19 years of age (n =3,868), those who fasted\u0026nbsp;for less than 8 h, and\u0026nbsp;those who did not fast (n = 1,246). Of the remaining 17,445 subjects, we further excluded two participants for whom the serum uric acid data were missing (n = 11). Responses to\u0026nbsp;the gout-related questionnaire were also missing\u0026nbsp;for some participants (n = 1.094). Ultimately, 16,340 individuals (7,259 males and 9,081 females) were included.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of CHA Bundang Medical Center (approval no. 2023-07-0731). The requirement for written informed consent was waived owing to the retrospective design of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMedical history and lifestyle habits\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe medical history, medications, and lifestyle habits of the\u0026nbsp;participants were recorded.\u0026nbsp;In the health\u0026nbsp;survey, specific disease prevalence, medication use, physical activity, and nutrition-related sections were assessed through face-to-face interviews. Participants were categorized as non-smokers or current smokers based on their smoking habits. Significant alcohol consumption was defined as \u0026gt;1 standard drink/month over 1 year. Significant physical activity was defined as walking or riding a bicycle for more than 10 minutes when moving to another place.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAnthropometric measurements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHeight was measured using a stadiometer SECA 274 (SECA Deutschland, Hamburg, Germany), and weight was measured using a weighing scale GL-6000-20 (G-Tech International, Uijeongbu, Korea). The participants removed their clothing and wore disposable examination gowns.\u0026nbsp;Height and weight were measured in cm and kg, respectively. Body mass index (BMI) was calculated by dividing\u0026nbsp;the weight (kg) by the square of height (m).\u003c/p\u003e\n\u003cp\u003eBlood pressure was measured in a sitting position using a Greenlight 300 Sphygmomanometer (Accoson, Irvine, United Kingdom) with an appropriate cuff size. Blood pressure was calculated as the average of the second and third measurements following a total of three consecutive measurements.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBiochemical measurements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlood samples were collected from the antecubital vein after at least 8 hours of fasting. Fasting plasma glucose, HbA1c, insulin, triglyceride, aspartate aminotransferase (AST), alanine transaminase (ALT), and uric acid levels were measured using a chemistry autoanalyzer.\u003c/p\u003e\n\u003cp\u003eThe TyG index was calculated using the formula below, as defined in previous studies [13]:\u003c/p\u003e\n\u003cp\u003eTyG index = ln[fasting triglycerides (mg/dL) × fasting glucose (mg/dL) / 2].\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatical analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSPSS version 25.0 (IBM, Armonk, NY, USA) was used for all the data analyses. All the continuous variables are reported as the means ± standard errors (SEs). Categorical variables are expressed as numbers (percentages).\u0026nbsp;The statistical significance level for all the tests was set at p \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003eAssociations between\u0026nbsp;the TyG index\u0026nbsp;and serum uric acid levels were tested based on covariate-adjusted multivariable regression with adjustments for the confounding factors. Age and sex were included in Model 1. In addition to those variables included in Model 1, Model 2 adjusted for BMI, smoking and alcohol history, physical activity, and\u0026nbsp;medication history\u0026nbsp;for hypertension, diabetes mellitus, and dyslipidemia. In addition to what was adjusted for in Model 2, Model 3 also adjusted for systolic blood pressure (BP), AST, and ALT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMultivariate logistic regression analysis was performed to evaluate the odds ratios (ORs) with 95 % confidence intervals for gout prevalence according to the TyG index quartiles. The ORs for gout prevalence were estimated based on the aforementioned adjustments (Model 1 and Model 2). Systolic BP, AST, ALT, and serum uric acid levels were additionally adjusted (Model 3).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGeneral characteristics of the study participants\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe baseline characteristics of the study participants are presented in Table 1. Of the 16,340 subjects, 321 (2.1 %) were diagnosed with gout. Of the 321 patients with gout, 279 (90.7 %) were men, and their mean age was 53.18 \u0026plusmn; 0.813 years. Participants with gout had a higher rate of drinking than those without gout. Moreover, patients with gout had significantly higher fasting glucose, HbA1c, insulin, and triglyceride levels than those without gout. The uric acid levels in the subjects without gout and those with gout were 5.25 \u0026plusmn; 0.015 mg/dL and 6.86 \u0026plusmn; 0.109 mg/dL, respectively. Further, the TyG index was significantly higher in the subjects with gout than in those without gout (8.5798 \u0026plusmn; 0.01 vs. 9.0284 \u0026plusmn; 0.05, respectively).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. General characteristics of the study population\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"682\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.961932650073205%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.183016105417277%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003eTotal (=16340)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.301610541727673%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003eNon-Gout (=16019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.301610541727673%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003eGout (=321)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.102489019033674%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e47.62 \u0026plusmn; 0.245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e47.51 \u0026plusmn; 0.247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e53.18 \u0026plusmn; 0.813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eSex (men)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e7259 (44.4 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e6980 (49.0 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e279 (90.7 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eAlcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e8449 (56 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e8247 (55.7 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e202 (67.7 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e2707 (19.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e2624 (18.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e83 (28.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003ePhysical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e8266 (51.6 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e8125 (51.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e141 (41.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.915080527086385%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedication History\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.2298682284041%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.301610541727673%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.301610541727673%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.102489019033674%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e3859 (18.5 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e3703 (18.0 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e156 (42.4 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e0.669\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eDiabetes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e1653 (8.1 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e1608 (7.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e45 (13.3 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e0.449\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eDyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e2725 (13.6 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e2621 (13.2 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e104 (29 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.14494875549048%\" colspan=\"2\" style=\"width: 47.5806%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnthropometry and measurements\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.301610541727673%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.301610541727673%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.102489019033674%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eBMI (kg/m2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e24.14\u0026plusmn;0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e24.10\u0026plusmn;0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e25.90\u0026plusmn;0.275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eSystolic BP (mm Hg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e118.22\u0026plusmn;0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e75.35\u0026plusmn;0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e124.36\u0026plusmn;0.951\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eDiastolic BP (mm Hg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e75.43\u0026plusmn;0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e100.63\u0026plusmn;0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e79.51\u0026plusmn;0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.14494875549048%\" colspan=\"2\" style=\"width: 47.5806%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory tests\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.301610541727673%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.301610541727673%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.102489019033674%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eFasting glucose (mg/dl)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e100.73\u0026plusmn;0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e100.63\u0026plusmn;0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e105.66\u0026plusmn;1.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eHbA1c (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e5.75\u0026plusmn;0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e5.75\u0026plusmn;0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e5.89\u0026plusmn;0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eInsulin (IU/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e9.43\u0026plusmn;0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e9.39\u0026plusmn;0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e11.50\u0026plusmn;0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.976608187134502%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eTotal cholesterol (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e192.08\u0026plusmn;0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e192.19\u0026plusmn;0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e186.81\u0026plusmn;2.679\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eTriglyceride (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e131.79\u0026plusmn;1.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e130.30\u0026plusmn;1.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e202.24\u0026plusmn;12.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.976608187134502%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eHDL cholesterol (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e52.29\u0026plusmn;0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e52.42\u0026plusmn;0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e46.11\u0026plusmn;0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.976608187134502%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eLDL cholesterol (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e117.18\u0026plusmn;0.925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e117.99\u0026plusmn;0.937\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e100.80\u0026plusmn;4.916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eAST (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e24.80\u0026plusmn;0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e24.67\u0026plusmn;0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e30.84\u0026plusmn;1.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eALT (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e24.47\u0026plusmn;0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e24.32\u0026plusmn;0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e31.43\u0026plusmn;1.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eUric acid (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e5.28\u0026plusmn;0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e5.25\u0026plusmn;0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e6.86\u0026plusmn;0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.92982456140351%\" style=\"width: 25.3958%;\"\u003e\n \u003cp\u003eTyG index\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.198830409356724%\" style=\"width: 22.0388%;\"\u003e\n \u003cp\u003e8.5891\u0026plusmn;0.00718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e8.5798\u0026plusmn;0.00715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.27485380116959%\" style=\"width: 19.2657%;\"\u003e\n \u003cp\u003e9.0284\u0026plusmn;0.04773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.087719298245615%\" style=\"width: 10.3626%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are\u0026nbsp;presented as n, mean (SE), or n, percentage (SE), unless otherwise indicated.\u003c/p\u003e\n\u003cp\u003eAbbreviations: BMI, body mass index; BP, blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein; AST, aspartate aminotransferase; ALT, alanine transaminase; TyG, triglyceride and glucose\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCorrelation\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003ebetween the TyG index and serum uric acid concentrations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe correlation between the TyG index and serum uric acid concentrations was also evaluated (Table 2).The TyG index was positively associated with the serum uric acid concentrations after adjusting for metabolic parameters.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Regression coefficients of the metabolic parameters for serum uric acid levels\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"608\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28735632183908%\" colspan=\"2\" style=\"width: 20.4464%;\"\u003e\n \u003cp\u003eModel 1\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28735632183908%\" colspan=\"3\" style=\"width: 24.6477%;\"\u003e\n \u003cp\u003eModel 2\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28735632183908%\" colspan=\"2\" style=\"width: 4.0837%;\"\u003e\n \u003cp\u003eModel 3\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003eTyG index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026ndash;0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026ndash;0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026ndash;0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e1.403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e1.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e1.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003esmoking\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026ndash;0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026ndash;0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003ealcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003ephysical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026ndash;0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026ndash;0.422\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003edyslipidemia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026ndash;0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4630541871921183%\" style=\"width: 4.2013%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.822660098522167%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e\u0026ndash;0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003esystolic BP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003eAST\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.24137931034483%\" style=\"width: 16.2451%;\"\u003e\n \u003cp\u003eALT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" colspan=\"2\" style=\"width: 14.9847%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.001642036124794%\" style=\"width: 9.663%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.986863711001641%\" style=\"width: 10.7834%;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* Adjusted for age and sex \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e** Additional adjustments, including those for BMI, smoking and alcohol history, physical activity, and medication history for hypertension, diabetes mellitus, and dyslipidemia\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e*** Additional adjustments, including those for systolic BP, AST, and ALT\u003c/p\u003e\n\u003cp\u003eAbbreviations: TyG, triglyceride and glucose; BMI, body mass index; BP, blood pressure; AST, aspartate aminotransferase; ALT, alanine transaminase\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAssociation between the TyG index quartiles, uric acid levels, and prevalence of gout\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe participants were divided into four groups\u0026nbsp;according to their TyG index values. Figure 2 shows the serum acid levels and gout prevalence according to the TyG index quartiles, respectively. Figure 3 and Table 3 show the\u0026nbsp;ORs of the high-level TyG index groups based on the prevalence of gout\u0026nbsp;through logistic analysis;\u0026nbsp;the ORs corresponding to gout incidence in the groups were analyzed compared to those in the lowest quartile group.\u0026nbsp;In the unadjusted model, the 2\u003csup\u003end\u003c/sup\u003e, 3\u003csup\u003erd\u003c/sup\u003e, and 4\u003csup\u003eth\u003c/sup\u003e quartile groups had a significantly higher prevalence of gout than the lowest quartile group. After adjusting for all the metabolic parameters, only the highest quartile (4th quartile) group had a significantly higher incidence of gout than the lowest quartile group (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Odds ratios and 95 % confidence intervals for gout incidence based on the TyG index quartiles\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"702\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.517780938833571%\" style=\"width: 13.7595%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.49928876244665%\" colspan=\"4\" style=\"width: 40.8927%;\"\u003e\n \u003cp\u003eTyG index quartiles\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.4822695035461%\" style=\"width: 13.7595%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.163120567375888%\" style=\"width: 14.3012%;\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.418439716312058%\" style=\"width: 15.9263%;\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.141843971631207%\" style=\"width: 15.0596%;\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.865248226950353%\" style=\"width: 13.8678%;\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.346590909090908%\" style=\"width: 13.7595%;\"\u003e\n \u003cp\u003eUnadjusted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.1875%\" style=\"width: 14.3012%;\"\u003e\n \u003cp\u003e1.00 (Reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.448863636363637%\" style=\"width: 15.9263%;\"\u003e\n \u003cp\u003e2.020 (1.204\u0026ndash;3.388)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.170454545454547%\" style=\"width: 15.0596%;\"\u003e\n \u003cp\u003e3.864 (2.410\u0026ndash;6.197)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.892045454545453%\" style=\"width: 13.8678%;\"\u003e\n \u003cp\u003e6.256 (3.962\u0026ndash;9.876)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.346590909090908%\" style=\"width: 13.7595%;\"\u003e\n \u003cp\u003eAdjusted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.1875%\" style=\"width: 14.3012%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.448863636363637%\" style=\"width: 15.9263%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.170454545454547%\" style=\"width: 15.0596%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.892045454545453%\" style=\"width: 13.8678%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.4822695035461%\" style=\"width: 13.7595%;\"\u003e\n \u003cp\u003eModel 1\u003csup\u003e*\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.163120567375888%\" style=\"width: 14.3012%;\"\u003e\n \u003cp\u003e1.00 (Reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.418439716312058%\" style=\"width: 15.9263%;\"\u003e\n \u003cp\u003e1.424 (0.849\u0026ndash;2.388)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.141843971631207%\" style=\"width: 15.0596%;\"\u003e\n \u003cp\u003e2.305 (1.434\u0026ndash;3.706)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.865248226950353%\" style=\"width: 13.8678%;\"\u003e\n \u003cp\u003e3.134 (1.962\u0026ndash;5.006)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.4822695035461%\" style=\"width: 13.7595%;\"\u003e\n \u003cp\u003eModel 2\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.163120567375888%\" style=\"width: 14.3012%;\"\u003e\n \u003cp\u003e1.00 (Reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.418439716312058%\" style=\"width: 15.9263%;\"\u003e\n \u003cp\u003e1.258 (0.739\u0026ndash;2.142)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.141843971631207%\" style=\"width: 15.0596%;\"\u003e\n \u003cp\u003e1.918 (1.161\u0026ndash;3.169)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.865248226950353%\" style=\"width: 13.8678%;\"\u003e\n \u003cp\u003e2.521 (1.517\u0026ndash;4.191)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.4822695035461%\" style=\"width: 13.7595%;\"\u003e\n \u003cp\u003eModel 3\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.163120567375888%\" style=\"width: 14.3012%;\"\u003e\n \u003cp\u003e1.00 (Reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.418439716312058%\" style=\"width: 15.9263%;\"\u003e\n \u003cp\u003e1.201 (0.691\u0026ndash;2.087)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.141843971631207%\" style=\"width: 15.0596%;\"\u003e\n \u003cp\u003e1.703 (0.995\u0026ndash;2.913)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.865248226950353%\" style=\"width: 13.8678%;\"\u003e\n \u003cp\u003e2.002 (1.157\u0026ndash;3.465)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe participants were divided into four groups according to their TyG index values. The group with the lowest values among the four groups was denoted Q1, followed by Q2, Q3, and Q4.\u003c/p\u003e\n\u003cp\u003e* Adjusted for age and sex\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e** Additional adjustments, including those for BMI, smoking and alcohol history, physical activity, and medication history for hypertension, diabetes mellitus, and dyslipidemia\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e*** Additional adjustments, including those for systolic BP, AST, ALT, and uric acid\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAbbreviations: TyG, triglyceride and glucose; BMI, body mass index; BP, blood pressure; AST, aspartate aminotransferase; ALT, alanine transaminase\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study,\u0026nbsp;the TyG\u0026nbsp;index was determined to be associated with uric acid levels after adjusting for confounding factors. The incidence of gout was high in the highest quartile group of the TyG index compared to the lowest quartile group. This association was valid even after adjusting for all the metabolic parameters.\u003c/p\u003e\n\u003cp\u003eThe TyG index has been identified as an exemplary indicator of insulin resistance in many previous studies [14-17].\u0026nbsp;Moreover, it has been reported to be associated with cardiovascular disease, diabetes, metabolic syndrome, obesity, and non-alcoholic fatty liver\u0026nbsp;disease [5, 18-20].\u0026nbsp;However, no previous studies have demonstrated\u0026nbsp;the TyG index\u0026nbsp;as a surrogate factor for gout.\u003c/p\u003e\n\u003cp\u003eBiologically plausible mechanisms support the significant association between the TyG\u0026nbsp;index and gout. As\u0026nbsp;mentioned previously,\u0026nbsp;the TyG index serves as an indicator of insulin resistance, a condition that increases uric acid concentrations by diminishing the renal excretion of uric acid\u0026nbsp;and concurrently promoting elevated triglyceride levels that contribute to the development of gout. In this study,\u0026nbsp;the TyG\u0026nbsp;index showed a positive correlation with serum uric acid levels\u0026nbsp;even after considering other metabolic factors. Previous studies have shown that\u0026nbsp;the TyG index is associated with obesity and that adipose tissue\u0026nbsp;promotes uric acid production, thus causing an increase in serum uric acid levels [21, 22].\u0026nbsp;In this study,\u0026nbsp;the TyG index also showed a positive correlation with serum uric acid levels\u0026nbsp;even after considering other metabolic factors. Insulin resistance further reflects a state of low-grade inflammation in the body, which could also affect the occurrence of gout [23]. Interestingly, in this study,\u0026nbsp;the TyG index was also associated with gout even\u0026nbsp;after adjusting for all the metabolic parameters including uric acid levels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study had several limitations. First, it was cross-sectional; thus, we could not demonstrate a causative relationship between the TyG index and gout. Second, we\u0026nbsp;lacked the dietary history of the participants, a factor that could potentially be linked to the occurrence of gout. Additional long-term studies considering the metabolic status of patients can help to mitigate this limitation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn conclusion, the TyG index, a marker of insulin resistance, is an independent prognostic factor for gout. Specifically, a higher TyG index is associated with a higher serum uric acid level. Moreover, we demonstrated that the TyG index might contribute to the development of gout through alternative mechanisms even after adjusting for serum uric acid levels. Therefore, a longitudinal and comprehensive study investigating the impact of the TyG index on gout development is required.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential conflicts of interest relevant to this article are reported.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of CHA Bundang Medical Center (approval no. 2023-07-0731). Informed consent was obtained from all eligible participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial disclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no financial disclosures related to this report.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw datasets from the Eighth Korea National Health and Nutrition Examination Survey (KNHANES) can be obtained from the Korea Centers for Disease Control and Prevention after submission of an appropriate research proposal. (http://www.cdc.go.kr/CDC/eng/main.jsp)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKuo CF, Grainge MJ, Zhang W, Doherty M: \u003cstrong\u003eGlobal epidemiology of gout: prevalence, incidence and risk factors.\u003c/strong\u003e \u003cem\u003eNat Rev Rheumatol \u003c/em\u003e2015, \u003cstrong\u003e11:\u003c/strong\u003e649-662.\u003c/li\u003e\n\u003cli\u003eJin JL, Cao YX, Wu LG, You XD, Guo YL, Wu NQ, Zhu CG, Gao Y, Dong QT, Zhang HW, et al: \u003cstrong\u003eTriglyceride glucose index for predicting cardiovascular outcomes in patients with coronary artery disease.\u003c/strong\u003e \u003cem\u003eJ Thorac Dis \u003c/em\u003e2018, \u003cstrong\u003e10:\u003c/strong\u003e6137-6146.\u003c/li\u003e\n\u003cli\u003eNarang RK, Dalbeth N: \u003cstrong\u003ePathophysiology of Gout.\u003c/strong\u003e \u003cem\u003eSemin Nephrol \u003c/em\u003e2020, \u003cstrong\u003e40:\u003c/strong\u003e550-563.\u003c/li\u003e\n\u003cli\u003eLee YC, Lee JW, Kwon YJ: 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increase in obesity.\u003c/strong\u003e \u003cem\u003eJ Biol Chem \u003c/em\u003e2013, \u003cstrong\u003e288:\u003c/strong\u003e27138-27149.\u003c/li\u003e\n\u003cli\u003eRehman K, Akash MS: \u003cstrong\u003eMechanisms of inflammatory responses and development of insulin resistance: how are they interlinked?\u003c/strong\u003e \u003cem\u003eJ Biomed Sci \u003c/em\u003e2016, \u003cstrong\u003e23:\u003c/strong\u003e87.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"triglyceride and glucose index, gout, uric acid ","lastPublishedDoi":"10.21203/rs.3.rs-4223516/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4223516/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: The triglyceride and glucose (TyG) index is a useful marker of insulin resistance and metabolic syndrome. Several studies have reported a link between this index and serum uric acid levels. However, few studies have shown a concrete association between the TyG index, uric acid levels, and prevalence of gout. The objective of this study was to investigate the correlation between this index and uric acid levels, as well as their potential associations with the incidence of gout.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Data derived from the Eighth Korea National Health and Nutrition Examination Survey conducted from 2019 to 2021 were used. The study population included adults \u0026gt;19 years of age andconsisted of 16,340 participants who were subjected to blood tests to measure their fasting blood glucose and triglyceride levels. Additionally, the participants responded to a questionnaire regarding the diagnosis of gout, making them eligible for inclusion in the study. The TyG index was categorized into quartiles.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Of the 16,340 total subjects, 321(2.1 %) were diagnosed with gout. After an adjustment for age and metabolic parameters, the TyG index was positively related to serum uric acid levels (β = 0.247, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Compared to the risk in the lowest quartile group, as a reference, the adjusted odd ratio, with a 95 % confidence interval, for the incidence of gout was 2.002 (1.157–3.465) in the highest quartile group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e An elevated TyG index is associated with increased blood uric acid levels, and the TyG index is also associated with the prevalence of gout.\u003c/p\u003e","manuscriptTitle":"Relationship between the triglyceride–glucose index, blood uric acid levels, and prevalence of gout in Korean adults: Eighth Korean National Health and Nutrition Examination Survey (2019–2021)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-12 19:09:52","doi":"10.21203/rs.3.rs-4223516/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6beab26d-0498-4da3-b558-a6cbe2f9d03e","owner":[],"postedDate":"April 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-19T02:33:51+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-12 19:09:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4223516","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4223516","identity":"rs-4223516","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}