Association Between Peripheral Thyroid Hormone Sensitivity and Hypertriglyceridemia in Euthyroid Population

Association Between Peripheral Thyroid Hormone Sensitivity and Hypertriglyceridemia in Euthyroid Population | 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 Between Peripheral Thyroid Hormone Sensitivity and Hypertriglyceridemia in Euthyroid Population Yu Gong, Qianqian Zhang, Guojuan Wang, Ying Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8867531/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 13 You are reading this latest preprint version Abstract Objective We aimed to investigate the correlation between peripheral thyroid hormone sensitivity and hypertriglyceridemia in euthyroid population. Methods A total of 833 individuals who underwent physical examinations were randomly selected. Biochemical parameters including thyroid hormones, liver and kidney functions, blood glucose, and blood lipids were measured. Peripheral thyroid hormone sensitivity was assessed by the ratio of free triiodothyronine to free thyroxine (FT3/FT4). The data were analyzed for the relationship between peripheral thyroid hormone sensitivity and triglyceride (TG). Results smooth curve fitting and threshold effect analysis showed that FT3/FT4 ratio was a positive correlation with TG before the inflection point at 0.426 (β=1.752, P <0.001). Tests for trend in multiple regression equations showed that with the increase of the quartiles of FT3/FT4 ratio, the gradually increasing trend of TG was statistically significant. For per SD increase in FT3/FT4 ratio, TG increased by 0.0587mmol/L (β=0.0587, P =0.001). Subgroup analysis revealed that in female group (β=1.9040, P <0.001), age <65 years group (before the inflection point 0.4272, β=1.7773, P <0.001), and BMI<28 kg/m 2 group (β=1.4660, P <0.001), the FT3/FT4 ratio was positively correlated with TG. Conclusion Increased peripheral thyroid hormone sensitivity, as reflected by an elevated FT4 to FT3 conversion rate, is associated with increased TG level in euthyroid population. This association is particularly pronounced in females, individuals with aged<65 years, and non-obese (BMI<28 kg/m 2 ) individuals. Thyroid hormone sensitivity Free triiodothyronine to free thyroxine ratio Hypertriglyceridemia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Hyperlipidemia is a chronic disease that seriously endangers human health [1]. Most clinical guidelines for dyslipidemia management focus predominantly on low-density lipoprotein cholesterol[2], while triglyceride (TG) receives comparatively less attention. Hypertriglyceridemia (HTG) often occurs secondary to metabolic disorders such as diabetes, alcohol consumption, and/or overweight, with a prevalence of 10% in the adult population[3]. Epidemiological and genetic studies have confirmed that TG-rich lipoproteins and their remnants are critical risk factors for atherosclerotic cardiovascular disease (ASCVD), and severe HTG also increases the risk of pancreatitis[4]. Despite the well-established clinical hazards of HTG, gaps remain in the identification of its specific risk factors and the formulation of screening strategies for high-risk populations. Additionally, existing risk assessment systems fail to fully incorporate the unique molecular pathophysiological mechanisms underlying HTG. Multiple hormones participate in lipid metabolism within the body, among which thyroid hormone (TH) serves as a critical regulator of lipid homeostasis[5]. TH can achieve systematic regulation of lipid metabolism by regulating the processes of lipid synthesis, mobilization, and degradation, and coordinating the functional interaction between the liver and adipose tissue[6]. Recent studies have shown[7] that even fluctuations in thyroid hormone levels within the reference range can affect the metabolic prognosis of blood lipids in healthy adults. These changes may be related to impaired peripheral deiodination and down - regulation of deiodinase activity[8]. The ratio of free triiodothyronine to free thyroxine (FT3/FT4) is an important indicator reflecting deiodinase activity and the peripheral bioavailability of thyroid hormones[9]. An increasing number of studies have confirmed that an elevated FT3/FT4 ratio in the euthyroid population is associated with obesity, metabolic syndrome, diabetes, and hypertension[10][11][12]-13], and is even closely related to diseases such as heart failure and non - alcoholic fatty liver disease[14],[15]. These findings provide new research directions for in-depth analysis of the relationship between thyroid function and lipid metabolism. Previous studies have preliminarily explored the association between peripheral thyroid hormone sensitivity and TG in patients with coronary heart disease[16], but no relevant studies have been reported for the general population with normal thyroid function. This study aims to investigate the association between the FT3/FT4 ratio and TG levels in euthyroid individuals, potentially offering insights for identifying subgroups at higher risk of HTG. Methods and Materials Study population and design This cross-sectional analysis initially enrolled 1334 adults aged 18 to 90 years who underwent routine health examinations at the Physical Examination Center of the First People's Hospital of Hefei between January 2024 and June 2024. The study protocol was approved by the Research Ethics Committee of the Third Affiliated Hospital of Anhui Medical University (Approval No. 2024-167-01). Participants were excluded based on the following criteria: (1) Individuals with histories of tumors, acute infections, severe liver and kidney dysfunction. (2) Individuals with abnormal thyroid functions, histories of thyroid diseases, including hyperthyroidism, hypothyroidism and hashimoto's thyroiditis. (3) Individuals who have recently used iodine-containing contrast agents, iodine-free salt, thyroid hormones, or anti-thyroid drugs. (4) Individuals who have recently used medications that affect lipid metabolism (such as statins and fibrates). (5) Pregnant or lactating women. (6) Individuals with missing data. After applying these exclusion criteria, a total of 833 euthyroid individuals were included in the final analysis. A detailed flow diagram of participant selection is presented in Fig. 1 . Based on their triglyceride levels, participants were categorized into a hypertriglyceridemia group (TG ³ 2.3 mmol/L, n = 166) and a normal TG group (TG < 2.3 mmol/L, n = 667). The diagnostic criteria and data collection methods followed standardized protocols similar to those described in our previous work [ Frontiers in Endocrinology .2025;16:1616907.DOI: 10.3389/fendo.2025.1616907]. Clinical and laboratory assessments The basic clinical information of all the individuals was collected, including name, gender, age, chronic medical histories including diabetes mellitus (DM), hypertension, hyperlipidemia, medical history and surgical history. Height, weight, systolic blood pressure (SBP), and diastolic blood pressure (DBP) were measured in the state of fasting in the morning. Venous blood samples were drawn from each participant after an overnight fast of at least 8 hours. Biochemical parameters, including fasting blood-glucose (FBG), TG, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), alanine transaminase (ALT), aspartic transaminase (AST), gamma-glutamyl transferase (GGT), total bilirubin (TBIL), direct bilirubin (DBIL), indirect bilirubin (IBIL), albumin (ALB), serum creatinine (SCr), serum uric acid (SUA) were measured by well-trained technicians (Roche automatic biochemical analyzer. Combas 8000). Thyrotropic hormone (TSH), free triiodothyronine (FT3), and free thyroxine (FT4) were determined using a standardized Chemiluminescence method (Abbott 12000SR), and all measurements were performed using the same assays. The reference ranges of thyroid function indicators are as follows: TSH ranges from 0.350 to 4.949 μIU/mL, FT4 ranges from 9.03 to 19.04 pmol/L, and FT3 ranges from 2.43 to 6.01 pmol/L. Standard of diagnosis Hypertension was defined as systolic blood pressure³140 mmHg or diastolic blood pressure ³90 mmHg or self-reported history of hypertension or use of any antihypertensive medication[17]. DM was defined as having a FBG level≥7.0 mmol/L, or a 2-hour postprandial blood glucose level≥11.1 mmol/L, or a HbA1c level≥6.5%, or a documented history of diabetes, or current use of any glucose-lowering medication[18]. HTG was defined as having a TG level of≥2.3 mmol/L without the use of oral lipid-lowering medications[19]. Statistical analysis All statistical analyses were performed using IBM SPSS Statistics Software Version 27, GraphPad Prism 10.0.3, Empower(R) (www.empowerstats.com, X&Y Solutions, Inc.) (Boston, MA), and R (http://www.r-project.org) to complete the statistical analyses. Data normality was assessed using the Shapiro-Wilk test and Q-Q plots. Continuous variables with normal distribution are presented as mean±standard deviation (SD) and were compared between groups using the independent samples t-test. Non-normally distributed variables are expressed as median with interquartile range (IQR) and were compared using the Mann–Whitney U test. Categorical variables are presented as frequencies (percentages) and were compared using the chi-square test. To examine the relationship between the FT3/FT4 ratio and TG levels, we performed multivariate linear regression analyses with progressive adjustment for confounders. Model I was unadjusted; Model II was adjusted for age, sex, BMI, blood pressure (SBP and DBP), FBG, lipid parameters (TC, HDL-C, LDL-C), and liver and kidney function indicators (ALB, ALT, AST, GGT, TBIL, SCr, SUA). Given the potential nonlinear relationship suggested by preliminary analyses, we employed smooth curve fitting (generalized additive models) and conducted a two-piecewise linear regression model to identify threshold effects. The inflection point was determined using a trial-and-error method, and the log-likelihood ratio test was used to compare the one-line linear model with the two-piecewise model. To assess the robustness of the association, we performed trend tests by categorizing the FT3/FT4 ratio into quartiles and treating the quartiles as ordinal variables in regression models. Subgroup analyses were conducted stratified by sex (male vs. female), age (<65 vs. ≥65 years), and BMI (<28 vs. ≥28 kg/m²). All statistical tests were two-sided, and a P -value < 0.05 was considered statistically significant. Results The baseline clinical characteristics of all the individuals in this study The research subjects were divided into two groups based on TG level: TG³2.3 mmol/L group (N=166) and TG<2.3 mmol/L group (N=667). Independent sample T-test analysis was conducted between the two groups. Compared with TG<2.3mmol/L group, TG³2.3mmol/L group showed a higher proportion of women, a lower age, and a significantly higher BMI. Biochemical indicators including FBG, ALB, ALT, AST, GGT, SUA, SCr and TC levels were significantly elevated. In terms of thyroid function, compared with TG0.05) ( Table 1 , Fig. 2 ). Table 1 Baseline characteristics of participants according to TG level Characteristics Total N=833 TG level(mmol/L) P value <2.3 N=667 ≥2.3 N=166 Age (year) 47.40±11.95 47.66±12.29 46.36±10.45 0.165 Male 446（53.5） 331（49.60） 115（69.3） <0.001 Female 387（46.5） 336（50.40） 51（31.7） <0.001 BMI (kg/m 2 ) 24.83±3.27 24.41±3.20 26.55±2.97 <0.001 SBP (mmHg) 122.98±16.65 121.67±16.68 128.22±15.51 <0.001 DBP (mmHg) 75.35±10.92 74.23±10.81 79.86±10.19 <0.001 FBG (mmol/L) 5.17（4.84，5.57） 5.14（4.82，5.50） 5.19（4.94，5.86） 0.004 ALB (g/L) 47.17±2.82 47.06±2.91 47.61±2.38 0.024 ALT (U/L) 19（14，29） 17（13，26） 26（17，40） <0.001 AST (U/L) 22（19，26） 22（19，26） 24（21，31） <0.001 GGT (U/L) 34.94±35.81 29.61±29.96 56.36±47.62 <0.001 TBIL (umol/L) 19.25±7.58 19.63±7.63 17.71±7.21 0.003 IBIL (umol/L) 15.97±6.40 16.21±6.46 15.01±6.11 0.031 DBIL (umol/L) 3（2.30，4.00） 3.1（2.40，4.10） 2.55（1.80，3.20） <0.001 SCr (umol/L) 71.92±16.14 70.87±16.06 76.14±15.81 <0.001 SUA （umol/L） 329.42±92.32 317.36±86.85 377.89±97.87 <0.001 TG （mmol/L） 1.72±1.21 1.27±0.49 3.54±1.49 <0.001 TC (mmol/L) 4.85±0.90 4.78±0.88 5.14±0.92 <0.001 LDL-C (mmol/L) 3.06±0.81 3.07±0.80 3.03±0.84 0.573 HDL (mmol/L) 1.33±0.35 1.40±0.34 1.04±0.19 <0.001 TSH (μIU/mL) 1.84±1.09 1.78±0.88 2.09±1.67 0.022 FT3 (pmol/L) 4.43±0.51 4.40±0.50 4.55±0.51 <0.001 FT4(pmol/L) 13.01±1.45 13.02±1.46 12.98±1.44 0.789 FT3/FT4 0.34±0.04 0.34±0.04 0.35±0.04 0.001 Data are expressed as means ± standard deviations, medians (interquartile ranges), or percentages. Independent samples T-test or Mann-Whitney U-test are used to compare the differences of continuous variables between two groups. BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBG, fasting blood glucose; FBG, fasting blood glucose; ALB, albumin; ALT, alanine transaminase; AST, aspartic transaminase; GGT, γ-glutamyl transferase; TBIL, total bilirubin; IBIL, indirect bilirubin; DBIL, direct bilirubin; TG, triglyceride ; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TSH, Thyrotropic hormone; FT3, free triiodothyronine; FT4, free thyroxine; FT3/FT4, The ratio of free triiodothyronine to free thyroxine. Smooth curve fitting and threshold effect analysis of the relationship between peripheral thyroid hormone sensitivity and TG After adjusting the confounding factors of gender, age, BMI, blood pressure, blood glucose, blood lipids, and liver and kidney function, the FT3/FT4 ratio was curvilinearly correlated with TG. The FT3/FT4 ratio was positively correlated with TG before the inflection point at 0.426, with a corresponding increase of 1.752 in TG for every 1-unit increase in the FT3/FT4 ratio (β=1.752, P <0.001). However, after the inflection point there was no significant difference observed in the correlation between the FT3/FT4 ratio and TG ( P =0.053) ( Table 2 , Fig. 3 ). Table 2 Threshold effect analysis of the relationship between the FT3/FT4 ratio and TG in the overall population Outcome: TG For exposure：FT3/FT4 Model Ⅰ One-line effect 1.305 (0.508, 2.103) 0.001 Model Ⅱ Inflection point (k) 0.426 < K segment effect1 1.752 (0.874, 2.629) K segment effect2 -6.271 (-12.624, 0.082) 0.053 Difference in effect of 2 and 1 -8.023 (-14.698, -1.349) 0.018 Log-likelihood ratio test 0.017 Trend tests of multiple regression equations for the relationship between the FT3/FT4 ratio and TG The smooth curve fitting and threshold effect analysis of the overall data showed the FT3/FT4 ratio was positively correlated with TG before the inflection point. Further trend tests of multiple regression equations were performed to verify whether the correlation trend was statistically significant. P values for trend were calculated with quartiles as continuous variables. The results showed that with the increase of quartiles of the FT3/FT4 ratio, the gradually increasing trend of TG was statistically significant. For each one-grade increase in the FT3/FT4 ratio, the level of TG increased by 0.0624 accordingly (β=0.0624, P <0.001). For each SD increase in the FT3/FT4 ratio, the level of TG increased by 0.0587 mmol/L (β=0.0587, P =0.001) ( Table 3 , Fig. 4 ). Table 3 Logistic regression analysis of the correlation between the FT3/FT4 ratio and TG Outcome Adjust Model I Adjust Model II β (95%CI) P value β (95%CI) P value FT3/FT4 per SD 0.1750 (0.0939, 0.2560) <0.001 0.0587 (0.0229, 0.0946) 0.001 Q1 0 (reference) 0 (reference) Q2 0.3164 (0.0866, 0.5463) 0.007 0.1069 (0.0096, 0.2041) 0.031 Q3 0.2563 (0.0265, 0.4861) 0.029 0.1522 (0.0549, 0.2494) 0.002 Q4 0.4572 (0.2276, 0.6868) <0.001 0.1938 (0.0935, 0.2941) <0.001 FT3/FT4 quartile continuous 0.1311 (0.0585, 0.2038) <0.001 0.0624 (0.0309, 0.0940) <0.001 P for trend <0.001 <0.001 Model 1 did not correct for confounding factors Model 2 Adjusted for gender, age, BMI, blood pressure, blood glucose, blood lipids, and liver and kidney function; β, regression coefficient; CI, confidence interval; P for trend was calculated using the quartiles as continuous variables. Subgroup analysis of the correlation between the FT3/FT4 ratio and TG After adjusting for confounders including age, BMI, SBP, DBP, ALB, ALT, AST, GGT, TBIL, CR, FBG, TC, HDL, and LDL, the FT3/FT4 ratio was positively correlated with TG in female group. For every unit increase in the FT3/FT4 ratio, TG increased by 1.9040 (β=1.9040, P <0.001). In male group, the FT3/FT4 ratio was no significant correlation with TG. After adjusting for confounders including gender, BMI, SBP, DBP, ALB, ALT, AST, GGT, TBIL, CR, FBG, TC, HDL, and LDL, the FT3/FT4 ratio was curvilinearly correlated with TG in age <65 years group. The FT3/FT4 ratio was positively correlated with TG before the inflection point at 0.4272, with a corresponding increase of 1.7773 in TG for every 1-unit increase in the FT3/FT4 ratio (β=1.7773, P <0.001). However, after the inflection point there was no significant difference observed in the correlation between the FT3/FT4 ratio and TG. In age³65 years group, the FT3/FT4 ratio was no significant correlation with TG. After adjusting for confounders including age, gender, SBP, DBP, ALB, ALT, AST, GGT, TBIL, CR, FBG, TC, HDL, and LDL, the FT3/FT4 ratio was positively correlated with TG in BMI<28 kg/m 2 group. For every unit increase in the FT3/FT4 ratio, TG increased by 1.4660 (β=1.4660, P <0.001). In BMI³28 kg/m 2 group, the FT3/FT4 ratio was no significant correlation with TG. We concluded that the FT3/FT4 ratio was positively correlated with TG levels in the female population, in individuals aged <65 years, and in those with BMI <28 kg/m² ( Table 4 , Fig. 5 ). Table 4 Subgroup analysis of the correlation between the FT3/FT4 ratio and TG gender age（year） BMI（kg/m 2 ） female male ³65 <65 ³28 <28 Model Ⅰ One-line effect 1.9040 (0.8208, 2.9872) <0.001 0.7922 (-0.2739, 1.8582) 0.146 1.0829 (-0.7187, 2.8845) 0.244 1.3245 (0.4722, 2.1767) 0.002 0.6371 (-1.7683, 3.0425) 0.604 1.4660 (0.6579, 2.2741) <0.001 Model II Inflection point (k) 0.3680 0.4360 0.2971 0.4272 0.4129 0.3956 < K segment effect1 2.6989 (1.2115, 4.1863) <0.001 1.2753 (0.0798, 2.4708) 0.037 -2.8014 (-8.5552, 2.9523) 0.344 1.7773 (0.8366, 2.7179) <0.001 2.2361 (-0.6550, 5.1271) 0.1321 2.0243 (1.0381, 3.0105) K segment effect2 -0.4695 (-3.7053, 2.7664) 0.776 -8.2217 (-17.5129, 1.0694) 0.083 2.9270 (-0.2241, 6.0782) 0.074 -6.2261 (-12.9966, 0.5445) 0.071 -11.4520 (-24.0818, 1.1779) 0.078 -1.6293 (-4.8774, 1.6189) 0.325 Difference in effect of 2 and 1 -3.1684 (-7.2396, 0.9029) 0.128 5.1749 (-0.9653, 11.3152) 0.099 5.7285 (-2.3382, 13.7952) 0.170 -8.0033 (-15.1231, -0.8835) 0.027 -13.6880 (-27.7321, 0.3560) 0.058 -3.6536 (-7.3675, 0.0604) 0.054 Log-likelihood ratio test 0.119 0.078 0.110 0.026 0.043 0.051 Discussion In this cross-sectional study of euthyroid adults, we observed that individuals with HTG had higher TSH, FT3, and the FT3/FT4 ratio compared to those with normal TG. After comprehensive adjustment for confounders, greater peripheral thyroid hormone sensitivity, which is reflected by a higher FT3/FT4 ratio, was independently associated with elevated TG levels. This association was particularly prominent in females, in individuals aged <65 years, and in those with BMI<28 kg/m². Our findings align partially with those of Gu et al. [7] from the TCLSIH cohort, which also reported that higher FT3 levels within the euthyroid range were linked to an unfavorable lipid profile. Conversely, Gu et al. [16] observed in patients with coronary heart disease that a higher FT3/FT4 ratio was associated with a lower risk of dyslipidemia. This discrepancy might stem from differences in study populations: individuals with coronary heart disease often exhibit atherosclerosis and systemic inflammation, in which peripheral thyroid hormone metabolism could be altered as a compensatory response. In that context, an elevated FT3/FT4 ratio might represent an adaptive mechanism to preserve metabolic homeostasis [20],[21]. By contrast, our study focused on generally healthy adults, which may better capture associations under physiological conditions. The elevation of plasma TG results from both the overproduction and impaired clearance of TG-rich lipoproteins—very-low-density lipoproteins and chylomicrons[22]. Experimental evidence indicates that HTG, accompanied by increased serum fatty acid concentrations, suppresses mitochondrial complex formation in pancreatic acinar cells, induces abnormal elevation of intracellular calcium, promotes cytokine release and tissue injury, and impairs pancreatic ductal function, thereby leading to acute pancreatitis[23]. In the context of HTG, elevated levels of triglyceride-rich lipoproteins and their remnants can penetrate the endothelial barrier and interact with macrophages, promoting foam cell formation and inflammatory responses within the arterial wall. These processes contribute to the development of atherosclerosis and increase the risk of coronary heart disease[24]. In summary, HTG is closely linked to the pathogenesis of multiple diseases, underscoring the importance of its management and control. TH is key regulators of TG metabolism. TH concentrations correlate with hepatic TG content and influence HDL metabolism by enhancing the activity of cholesteryl ester transfer protein, which transfers cholesteryl esters from HDL to very-low-density lipoproteins and TG-rich lipoproteins[25]. T3 stimulates lipoprotein lipase, promoting the catabolism of TG-rich lipoproteins and thereby lowering TG levels[26]. Furthermore, studies in TSH receptor knockout mouse models demonstrate that TSH dose-dependently suppresses adipose TG lipase expression in mature adipocytes via the cAMP-protein kinase pathway, consequently promoting TG accumulation within fat cells[27]. Substantial evidence confirmed that both elevated and reduced TH levels altered the blood lipid profile. Patients with hypothyroidism exhibit increased levels of TC, LDL-C, and TG, along with decreased HDL-C, with the most pronounced changes observed in TC and LDL-C levels. In contrast, patients with hyperthyroidism showed significantly reduced levels of TC, TG, and LDL-C[28][29]-30]. Even within the normal range, thyroid function correlated with systemic metabolism: when TSH remained within normal limits, a rising TSH level was associated with significant increases in TC, TG, and LDL-C, and a significant decrease in HDL-C[31]. Additionally, elevated FT3 level was frequently observed in euthyroid individuals with obesity and non-alcoholic fatty liver disease[32]. Physiologically, TSH, FT4 and FT3 regulate and influence each other in HPA axis. Compared with a single indicator, the calculation of a composite indicator could systematically reflect the regulation of TH homeostasis. Since FT4 is peripherally converted to FT3 by deiodinases, the FT3/FT4 ratio serves as an indicator of peripheral deiodinase activity[33]. A study by Bilgin and Pirgon suggested that enhanced conversion of FT4 to FT3 via increased deiodinase activity might represent a compensatory mechanism in the context of fat accumulation, aimed at elevating energy expenditure and reflecting heightened TH sensitivity[34]. Our findings demonstrated a positive correlation between the FT3/FT4 ratio and level, suggesting that increased peripheral TH sensitivity was associated with elevated TG. Given the influence of sex hormones[35]and age[36]on thyroid function, we performed subgroup analyses by gender and age. The observed gender-based differences may be attributed to the distinct regulatory effects of sex hormones on thyroid function. For instance, estrogen and androgen exerted differential influences on serum thyroxine-binding globulin concentrations, thereby modulating thyroid activity[37]. The age-related variations in lipid metabolism may be explained by the impact of aging and menopausal hormonal changes. With advancing age, a reduction in thyroid hormone receptor expression occurred, leading to diminished tissue responsiveness to TH[38],[39]. The BMI subgroup differences may involve interactions between TH and leptin. Leptin, an adipokine secreted by adipose tissue, acted directly on the hypothalamic paraventricular nucleus to stimulate transcription of the thyrotropin-releasing hormone (TRH) precursor, thereby promoting TRH secretion[40]. It may also indirectly stimulate TRH secretion in the arcuate nucleus by promoting production of downstream pro-opiomelanocortin derivatives[41]. From a clinical perspective, the FT3/FT4 ratio might serve as a useful adjunctive marker for identifying euthyroid individuals who could be at heightened risk of hypertriglyceridemia. This could be particularly relevant in subgroups such as women, middle-aged adults, and non-obese persons, in whom routine lipid screening might benefit from additional risk stratification. Although further prospective studies are needed to establish causality, incorporating thyroid function parameters into regular health check-ups may help highlight individuals who could benefit from closer metabolic monitoring or early lifestyle counseling. Given the well-documented burden of hypertriglyceridemia in relation to atherosclerotic cardiovascular disease and pancreatitis [42], even modest improvements in risk prediction could have public health implications. The potential utility of such an approach resonates with current recommendations that emphasize targeted screening and primary prevention strategies for high-risk populations [43]. Several limitations of this study should be acknowledged: 1. The cross-sectional design precludes any causal inference regarding the relationship between peripheral thyroid hormone sensitivity and hypertriglyceridemia. Therefore, the observed associations warrant confirmation in prospective cohort studies. 2. As a single-center study with a relatively modest sample size recruited from a specific geographic region, the generalizability of our findings to other populations may be limited and requires validation in larger, multicenter cohorts. 3. Although we adjusted for a wide range of potential confounders—including demographic characteristics, metabolic parameters, and liver and kidney function—the possibility of residual confounding due to unmeasured variables (e.g., insulin resistance, inflammatory markers such as high-sensitivity C-reactive protein, or detailed medication adherence) cannot be entirely excluded. 4. The absence of data on thyroid autoantibodies and urinary iodine levels precluded assessment of potential underlying thyroid autoimmunity or iodine nutritional status, which may influence thyroid hormone metabolism and confound the observed associations. 5. Because the study population consisted of individuals undergoing routine health check-ups, the medication histories relied on self-report and may be subject to recall bias, despite our efforts to exclude those taking lipid-lowering or thyroid-affecting medications. 6. While the FT3/FT4 ratio is a widely used surrogate marker of peripheral deiodinase activity, it remains an indirect measure of thyroid hormone sensitivity; direct assessment of deiodinase enzyme activity or tissue-level thyroid hormone action was not performed and should be addressed in future mechanistic studies. Conclusion In summary, increased peripheral thyroid hormone sensitivity was significantly associated with elevated TG level, with this correlation being more pronounced in female, young and middle-aged adults, and non-obese individuals. These findings highlight the need for longitudinal studies to clarify the directionality and potential mechanisms of this relationship. A better understanding of this association could contribute to more refined risk stratification and ultimately aid in the prevention of HTG and its complications. Declarations Data availability statement All data generated and analysed during our study were included in the supplementary files in the article. Ethics statement This investigation was approved by the Research Ethics Committee of the Third Affiliated Hospital of Anhui Medical University (No.2024-167-01), adhereing to the tenets of the Declaration of Helsinki. Informed consents were obtained from all participants. Author contributions YG: Visualization, Validation, Investigation, Formal analysis, Conceptualization, Writing – original draft, Methodology and Data curation. QQZ: Visualization, Validation, Investigation, Formal analysis, Conceptualization, and Data curation. GJW: Visualization, Validation, Investigation, Formal analysis, Conceptualization, and Data curation. YL: Visualization, Validation, Investigation, Formal analysis, Conceptualization, Writing – review & editing, Methodology and Data curation. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. 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Clinical endocrinology 2013, 79(5): 595-605. https://doi.org/10.1111/cen.12281. Lang X, Li Y, Zhang D, Zhang Y, Wu N, Zhang Y. FT3/FT4 ratio is correlated with all-cause mortality, cardiovascular mortality, and cardiovascular disease risk: NHANES 2007-2012. Frontiers in endocrinology 2022, 13: 964822. https://doi.org/10.3389/fendo.2022.964822. Wang Z, Yu H, Wang K, Han J, Song Y. Association between thyroid hormone resistance and obesity: a cross-sectional study and mouse stimulation test. Obesity (Silver Spring, Md) 2024, 32(8): 1483-93. https://doi.org/10.1002/oby.24084. Lv F, Cai X, Li Y, Zhang X, Zhou X, Han X, et al. Sensitivity to thyroid hormone and risk of components of metabolic syndrome in a Chinese euthyroid population. Journal of diabetes 2023, 15(10): 900-10. https://doi.org/10.1111/1753-0407.13441. Liu B, Wang Z, Fu J, Guan H, Lyu Z, Wang W. Sensitivity to Thyroid Hormones and Risk of Prediabetes: A Cross-Sectional Study. 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Inflammatory Links Between Hypertriglyceridemia and Atherogenesis. Current atherosclerosis reports 2022, 24(5): 297-306. https://doi.org/10.1007/s11883-022-01006-w. Bril F, Kadiyala S, Portillo Sanchez P, Sunny NE, Biernacki D, Maximos M, et al. Plasma thyroid hormone concentration is associated with hepatic triglyceride content in patients with type 2 diabetes. Journal of investigative medicine : the official publication of the American Federation for Clinical Research 2016, 64(1): 63-8. https://doi.org/10.1136/jim-2015-000019. Prieur X, Huby T, Coste H, Schaap FG, Chapman MJ, Rodríguez JC. Thyroid hormone regulates the hypotriglyceridemic gene APOA5. The Journal of biological chemistry 2005, 280(30): 27533-43. https://doi.org/10.1074/jbc.M503139200. Jiang D, Ma S, Jing F, Xu C, Yan F, Wang A, et al. Thyroid-stimulating hormone inhibits adipose triglyceride lipase in 3T3-L1 adipocytes through the PKA pathway. PloS one 2015, 10(1): e0116439. https://doi.org/10.1371/journal.pone.0116439. Peppa M, Betsi G, Dimitriadis G. Lipid abnormalities and cardiometabolic risk in patients with overt and subclinical thyroid disease. Journal of lipids 2011, 2011: 575840. https://doi.org/10.1155/2011/575840. Ahi S, Amouzegar A, Gharibzadeh S, Delshad H, Tohidi M, Azizi F. Trend of lipid and thyroid function tests in adults without overt thyroid diseases: A cohort from Tehran thyroid study. PloS one 2019, 14(5): e0216389. https://doi.org/10.1371/journal.pone.0216389. Jung KY, Ahn HY, Han SK, Park YJ, Cho BY, Moon MK. Association between thyroid function and lipid profiles, apolipoproteins, and high-density lipoprotein function. Journal of clinical lipidology 2017, 11(6): 1347-53. https://doi.org/10.1016/j.jacl.2017.08.015. Kebamo T E, Tantu A, Solomon Y, Walano GA. A comparative study on serum lipid levels in patients with thyroid dysfunction: a single-center experience in Ethiopia. BMC endocrine disorders 2025, 25(1): 47. https://doi.org/10.1186/s12902-025-01851-1. Lai S, Li J, Wang Z, Wang W, Guan H. Sensitivity to Thyroid Hormone Indices Are Closely Associated With NAFLD. Frontiers in endocrinology 2021, 12: 766419. https://doi.org/10.3389/fendo.2021.766419. Zhou Y, He Q, Ai H, Zhao X, Chen X, Li S, et al. The long-term prognostic implications of free triiodothyronine to free thyroxine ratio in patients with obstructive sleep apnea and acute coronary syndrome. Frontiers in endocrinology 2024, 15: 1451645. https://doi.org/10.3389/fendo.2024.1451645. Bilgin H, Pirgon Ö. Thyroid function in obese children with non-alcoholic fatty liver disease. Journal of clinical research in pediatric endocrinology 2014, 6(3): 152-7. https://doi.org/10.4274/Jcrpe.1488. Tahboub R, Arafah BM. Sex steroids and the thyroid. Best practice & research Clinical endocrinology & metabolism 2009, 23(6): 769-80. https://doi.org/10.1016/j.beem.2009.06.005. Visser WE, Visser TJ, Peeters RP. Thyroid disorders in older adults. Endocrinology and metabolism clinics of North America 2013, 42(2): 287-303. https://doi.org/10.1016/j.ecl.2013.02.008. Duntas L H, Brenta G. The effect of thyroid disorders on lipid levels and metabolism. The Medical clinics of North America 2012, 96(2): 269-81. https://doi.org/10.1016/j.mcna.2012.01.012. Jasim S, Gharib H. THYROID AND AGING. Endocrine practice: official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists 2018, 24(4): 369-74. https://doi.org/10.4158/ep171796.Ra. Majnarić LT, Bosnić Z, Štefanić M, Wittlinger T. Cross-Talk between the Cytokine IL-37 and Thyroid Hormones in Modulating Chronic Inflammation Associated with Target Organ Damage in Age-Related Metabolic and Vascular Conditions. International journal of molecular sciences 2022, 23(12). https://doi.org/10.3390/ijms23126456. Santini F, Marzullo P, Rotondi M, Ceccarini G, Pagano L, Ippolito S, et al. Mechanisms in endocrinology: the crosstalk between thyroid gland and adipose tissue: signal integration in health and disease. European journal of endocrinology 2014, 171(4): R137-52. https://doi.org/10.1530/eje-14-0067. Mullur R, Liu YY, Brent GA. Thyroid hormone regulation of metabolism. Physiological reviews 2014, 94(2): 355-82. https://doi.org/10.1152/physrev.00030.2013. Ganda OP, Bhatt DL, Mason RP, Miller M, Boden WE. Unmet Need for Adjunctive Dyslipidemia Therapy in Hypertriglyceridemia Management. Journal of the American College of Cardiology 2018, 72(3): 330-43. https://doi.org/10.1016/j.jacc.2018.04.061. Grundy S M, Stone N J, Bailey A L, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation, 2019, 139(25): e1082-e143. https://doi.org/10.1161/cir.0000000000000625. Additional Declarations No competing interests reported. Supplementary Files data.xlsx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 14 May, 2026 Reviews received at journal 04 Apr, 2026 Reviews received at journal 31 Mar, 2026 Reviewers agreed at journal 31 Mar, 2026 Reviews received at journal 28 Mar, 2026 Reviewers agreed at journal 27 Mar, 2026 Reviewers agreed at journal 27 Mar, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviewers invited by journal 17 Mar, 2026 Editor assigned by journal 16 Mar, 2026 Editor invited by journal 25 Feb, 2026 Submission checks completed at journal 24 Feb, 2026 First submitted to journal 24 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-8867531","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":608442450,"identity":"a4a8a1fd-5e25-414e-870c-828b41d93dee","order_by":0,"name":"Yu Gong","email":"","orcid":"","institution":"The First People’s Hospital of Hefei","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Gong","suffix":""},{"id":608442451,"identity":"0d1b0957-80e4-443f-85ad-af8d6ae197ac","order_by":1,"name":"Qianqian Zhang","email":"","orcid":"","institution":"The First People’s Hospital of Hefei","correspondingAuthor":false,"prefix":"","firstName":"Qianqian","middleName":"","lastName":"Zhang","suffix":""},{"id":608442452,"identity":"a37dbecf-ca9d-4894-9b10-f7a76fd9ea27","order_by":2,"name":"Guojuan Wang","email":"","orcid":"","institution":"The First People’s Hospital of Hefei","correspondingAuthor":false,"prefix":"","firstName":"Guojuan","middleName":"","lastName":"Wang","suffix":""},{"id":608442453,"identity":"cab8a4f8-a93e-44f1-8659-00d077d2b502","order_by":3,"name":"Ying Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYBACxvkP0n9+MLCRY2NvIFILc0PCA2mJgjRjfp4DRGphb0h8IMHz4XDizBkJRGrhbTicYCBhkGZscPPxxhsMNTbRBLVINrYlJBQA/WJwO63YguFYWm4DIS2GzTwJB8C23M4xk2BsOExYi/0x/o8NPAaHEzfcPEOkFsYehmQGkJaZM3iI1TKDIY0Z5DB+HqBfEojxC0gL44c/oKg8vPHGhxobwlqQgYFEAinKIVpI1TEKRsEoGAUjAwAAOW1A00y9RkMAAAAASUVORK5CYII=","orcid":"","institution":"The First People’s Hospital of Hefei","correspondingAuthor":true,"prefix":"","firstName":"Ying","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2026-02-13 05:08:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8867531/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8867531/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105563060,"identity":"4c7deac3-2853-403a-b62f-7ec11b138701","added_by":"auto","created_at":"2026-03-27 12:45:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":209992,"visible":true,"origin":"","legend":"\u003cp\u003eThe flow chart of the study population\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8867531/v1/2e99277fccf857b3c48514af.png"},{"id":105076893,"identity":"93d57673-d3fc-4955-b0da-e5b84c6e21f4","added_by":"auto","created_at":"2026-03-20 16:30:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":30028,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical representation of independent samples T-test for comparison between two groups of TG subgroups\u003c/p\u003e\n\u003cp\u003eTG, total cholesterol; FT3/FT4, The ratio of free triiodothyronine to free thyroxine.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8867531/v1/ef33bb0785bdb25b3b2f60aa.png"},{"id":105076895,"identity":"7701b755-6885-46cb-895a-7f629111c950","added_by":"auto","created_at":"2026-03-20 16:30:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":68148,"visible":true,"origin":"","legend":"\u003cp\u003eSmooth curve fitting diagram of the FT3/FT4 ratio and TG\u003c/p\u003e\n\u003cp\u003eTG, total cholesterol; FT3/FT4, The ratio of free triiodothyronine to free thyroxine.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8867531/v1/52b34447685f4c2d2ddc79c4.png"},{"id":105076897,"identity":"0ecd8763-0a59-4ce7-b144-27fbbaa44b27","added_by":"auto","created_at":"2026-03-20 16:30:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":44065,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of correlation between the FT3/FT4 ratio and TG\u003c/p\u003e\n\u003cp\u003eModel 1 did not correct for confounding factors\u003c/p\u003e\n\u003cp\u003eModel 2 Adjusted for gender, age, BMI, blood pressure, blood glucose, blood lipids, and liver and kidney function; β, regression coefficient; CI, confidence interval; \u003cem\u003eP\u003c/em\u003e for trend was calculated using the quartiles as continuous variables.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8867531/v1/1a4700e4816149c51c94d639.png"},{"id":105076896,"identity":"d4c8b56c-2546-4685-8b4a-942f2c5cfb36","added_by":"auto","created_at":"2026-03-20 16:30:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":33513,"visible":true,"origin":"","legend":"\u003cp\u003eSmooth curve fitting of the association between the FT3/FT4 ratio and TG levels in subgroup analysis\u003c/p\u003e\n\u003cp\u003eGender:0, female; 1, male; TG, total cholesterol; FT3/FT4, The ratio of free triiodothyronine to free thyroxine.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8867531/v1/df12cf26264a5bad15ec6025.png"},{"id":105568941,"identity":"aebdc1c0-a958-4e1e-858a-951faf0235c0","added_by":"auto","created_at":"2026-03-27 13:10:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1142202,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8867531/v1/7067ed64-84c7-45e2-82f4-4aeb56e514b6.pdf"},{"id":105562914,"identity":"044f8b01-9b14-4387-bed3-9e7ab31f1092","added_by":"auto","created_at":"2026-03-27 12:45:14","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":227172,"visible":true,"origin":"","legend":"","description":"","filename":"data.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8867531/v1/54280fb5a69ba1d5bdef0864.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Peripheral Thyroid Hormone Sensitivity and Hypertriglyceridemia in Euthyroid Population","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHyperlipidemia is a chronic disease that seriously endangers human health [1]. Most clinical guidelines for dyslipidemia management focus predominantly on low-density lipoprotein cholesterol[2], while triglyceride (TG) receives comparatively less attention. Hypertriglyceridemia (HTG) often occurs secondary to metabolic disorders such as diabetes, alcohol consumption, and/or overweight, with a prevalence of 10% in the adult population[3]. Epidemiological and genetic studies have confirmed that TG-rich lipoproteins and their remnants are critical risk factors for atherosclerotic cardiovascular disease (ASCVD), and severe HTG also increases the risk of pancreatitis[4]. Despite the well-established clinical hazards of HTG, gaps remain in the identification of its specific risk factors and the formulation of screening strategies for high-risk populations. Additionally, existing risk assessment systems fail to fully incorporate the unique molecular pathophysiological mechanisms underlying HTG.\u003c/p\u003e\n\u003cp\u003eMultiple hormones participate in lipid metabolism within the body, among which thyroid hormone (TH) serves as a critical regulator of lipid homeostasis[5]. TH can achieve systematic regulation of lipid metabolism by regulating the processes of lipid synthesis, mobilization, and degradation, and coordinating the functional interaction between the liver and adipose tissue[6].\u003c/p\u003e\n\u003cp\u003eRecent studies have shown[7] that even fluctuations in thyroid hormone levels within the reference range can affect the metabolic prognosis of blood lipids in healthy adults. These changes may be related to impaired peripheral deiodination and down - regulation of deiodinase activity[8]. The ratio of free triiodothyronine to free thyroxine (FT3/FT4) is an important indicator reflecting deiodinase activity and the peripheral bioavailability of thyroid hormones[9]. An increasing number of studies have confirmed that an elevated FT3/FT4 ratio in the euthyroid population is associated with obesity, metabolic syndrome, diabetes, and hypertension[10][11][12]-13], and is even closely related to diseases such as heart failure and non - alcoholic fatty liver disease[14],[15]. These findings provide new research directions for in-depth analysis of the relationship between thyroid function and lipid metabolism.\u003c/p\u003e\n\u003cp\u003ePrevious studies have preliminarily explored the association between peripheral thyroid hormone sensitivity and TG in patients with coronary heart disease[16], but no relevant studies have been reported for the general population with normal thyroid function. \u0026nbsp;This study aims to investigate the association between the FT3/FT4 ratio and TG levels in euthyroid individuals, potentially offering insights for identifying subgroups at higher risk of HTG.\u003c/p\u003e"},{"header":"Methods and Materials","content":"\u003cp\u003e\u003cstrong\u003eStudy population and design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis cross-sectional analysis initially enrolled 1334 adults aged 18 to 90 years who underwent routine health examinations at the Physical Examination Center of the First People\u0026apos;s Hospital of Hefei between January 2024 and June 2024. The study protocol was approved by the Research Ethics Committee of the Third Affiliated Hospital of Anhui Medical University (Approval No. 2024-167-01).\u003c/p\u003e\n\u003cp\u003eParticipants were excluded based on the following criteria: (1) Individuals with histories of tumors, acute infections, severe liver and kidney dysfunction. (2) Individuals with abnormal thyroid functions, histories of thyroid diseases, including hyperthyroidism, hypothyroidism and hashimoto\u0026apos;s thyroiditis. (3) Individuals who have recently used iodine-containing contrast agents, iodine-free salt, thyroid hormones, or anti-thyroid drugs. (4)\u0026nbsp;Individuals who have recently used medications that affect lipid metabolism\u0026nbsp;(such as statins and fibrates). (5) Pregnant or lactating women. (6) Individuals with missing data.\u003c/p\u003e\n\u003cp\u003eAfter applying these exclusion criteria, a total of 833 euthyroid individuals were included in the final analysis. A detailed flow diagram of participant selection is presented in \u003cstrong\u003eFig. 1\u003c/strong\u003e. Based on their triglyceride levels, participants were categorized into a hypertriglyceridemia group (TG\u0026nbsp;\u0026sup3;\u0026nbsp;2.3 mmol/L, n = 166) and a normal TG group (TG\u0026nbsp;\u0026lt;\u0026nbsp;2.3 mmol/L, n = 667). The diagnostic criteria and data collection methods followed standardized protocols similar to those described in our previous work [\u003cem\u003eFrontiers in Endocrinology\u003c/em\u003e.2025;16:1616907.DOI: 10.3389/fendo.2025.1616907].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical and laboratory assessments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe basic clinical information of all the individuals was collected, including name, gender, age, chronic medical histories including diabetes mellitus (DM), hypertension, hyperlipidemia, medical history and surgical history. Height, weight, systolic blood pressure (SBP), and diastolic blood pressure (DBP) were measured in the state of fasting in the morning.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVenous blood samples were drawn from each participant after an overnight fast of at least 8 hours. Biochemical parameters, including fasting blood-glucose (FBG), TG, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), alanine transaminase (ALT), aspartic transaminase (AST), gamma-glutamyl transferase (GGT), total bilirubin (TBIL), direct bilirubin (DBIL), indirect bilirubin (IBIL), albumin (ALB), serum creatinine (SCr), serum uric acid (SUA) were measured by well-trained technicians (Roche automatic biochemical analyzer. Combas 8000). Thyrotropic hormone (TSH), free triiodothyronine (FT3), and free thyroxine (FT4) were determined using a standardized Chemiluminescence method (Abbott 12000SR), and all measurements were performed using the same assays.\u0026nbsp;The reference ranges of thyroid function indicators are as follows: TSH ranges from 0.350 to 4.949\u0026nbsp;\u0026mu;IU/mL, FT4 ranges from 9.03 to 19.04 pmol/L, and FT3 ranges from 2.43 to 6.01 pmol/L.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStandard of diagnosis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHypertension was defined as systolic blood pressure\u0026sup3;140 mmHg or diastolic blood pressure \u0026nbsp;\u0026sup3;90 mmHg or self-reported history of hypertension or use of any antihypertensive medication[17]. DM was defined as having a FBG level\u0026ge;7.0 mmol/L, or a 2-hour postprandial blood glucose level\u0026ge;11.1 mmol/L, or a HbA1c level\u0026ge;6.5%, or a documented history of diabetes, or current use of any glucose-lowering medication[18]. HTG was defined as having a TG level of\u0026ge;2.3 mmol/L without the use of oral lipid-lowering medications[19].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using IBM SPSS Statistics Software Version 27, GraphPad Prism 10.0.3, Empower(R) (www.empowerstats.com, X\u0026amp;Y Solutions, Inc.) (Boston, MA), and R (http://www.r-project.org) to complete the statistical analyses. Data normality was assessed using the Shapiro-Wilk test and Q-Q plots. Continuous variables with normal distribution are presented as mean\u0026plusmn;standard deviation (SD) and were compared between groups using the independent samples t-test. Non-normally distributed variables are expressed as median with interquartile range (IQR) and were compared using the Mann\u0026ndash;Whitney U test. Categorical variables are presented as frequencies (percentages) and were compared using the chi-square test.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo examine the relationship between the FT3/FT4 ratio and TG levels, we performed multivariate linear regression analyses with progressive adjustment for confounders. Model I was unadjusted; Model II was adjusted for age, sex, BMI, blood pressure (SBP and DBP), FBG, lipid parameters (TC, HDL-C, LDL-C), and liver and kidney function indicators (ALB, ALT, AST, GGT, TBIL, SCr, SUA). Given the potential nonlinear relationship suggested by preliminary analyses, we employed smooth curve fitting (generalized additive models) and conducted a two-piecewise linear regression model to identify threshold effects. The inflection point was determined using a trial-and-error method, and the log-likelihood ratio test was used to compare the one-line linear model with the two-piecewise model.\u003c/p\u003e\n\u003cp\u003eTo assess the robustness of the association, we performed trend tests by categorizing the FT3/FT4 ratio into quartiles and treating the quartiles as ordinal variables in regression models. Subgroup analyses were conducted stratified by sex (male vs. female), age (\u0026lt;65 vs. \u0026ge;65 years), and BMI (\u0026lt;28 vs. \u0026ge;28 kg/m\u0026sup2;). All statistical tests were two-sided, and a \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eThe baseline clinical characteristics of all the individuals in this study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research subjects were divided into two groups based on TG level: TG\u0026sup3;2.3 mmol/L group (N=166) and TG\u0026lt;2.3 mmol/L group (N=667).\u0026nbsp;Independent sample T-test analysis was conducted between the two groups.\u0026nbsp;Compared with TG\u0026lt;2.3mmol/L group, TG\u0026sup3;2.3mmol/L group showed a higher proportion of women, a lower age, and a significantly higher BMI.\u0026nbsp;Biochemical indicators including FBG, ALB, ALT, AST, GGT, SUA, SCr and TC levels were significantly elevated. In terms of thyroid function, compared with TG\u0026lt;2.3mmol/L group, TG\u0026sup3;2.3mmol/L group showed higher levels of TSH, FT3, and the FT3/FT4 ratio, while there was no significant difference in FT4 level between two groups(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.05) (\u003cstrong\u003eTable 1\u003c/strong\u003e,\u003cstrong\u003eFig. 2\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u0026nbsp;\u003c/strong\u003eBaseline characteristics of participants according to TG level\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"488\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 125px;\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 97px;\"\u003e\n \u003cp\u003eTotal\u003cbr\u003e\u0026nbsp;N=833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 202px;\"\u003e\n \u003cp\u003eTG level(mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026lt;2.3\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eN=667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026ge;2.3\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eN=166\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAge (year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e47.40\u0026plusmn;11.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e47.66\u0026plusmn;12.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e46.36\u0026plusmn;10.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e446（53.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e331（49.60）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e115（69.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e387（46.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e336（50.40）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e51（31.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e24.83\u0026plusmn;3.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e24.41\u0026plusmn;3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e26.55\u0026plusmn;2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eSBP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e122.98\u0026plusmn;16.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e121.67\u0026plusmn;16.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e128.22\u0026plusmn;15.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eDBP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e75.35\u0026plusmn;10.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e74.23\u0026plusmn;10.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e79.86\u0026plusmn;10.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFBG (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e5.17（4.84，5.57）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e5.14（4.82，5.50）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e5.19（4.94，5.86）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eALB (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e47.17\u0026plusmn;2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e47.06\u0026plusmn;2.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e47.61\u0026plusmn;2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eALT (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e19（14，29）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e17（13，26）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e26（17，40）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAST (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e22（19，26）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e22（19，26）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e24（21，31）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eGGT (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e34.94\u0026plusmn;35.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e29.61\u0026plusmn;29.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e56.36\u0026plusmn;47.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eTBIL (umol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e19.25\u0026plusmn;7.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e19.63\u0026plusmn;7.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e17.71\u0026plusmn;7.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eIBIL (umol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e15.97\u0026plusmn;6.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e16.21\u0026plusmn;6.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e15.01\u0026plusmn;6.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eDBIL (umol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e3（2.30，4.00）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e3.1（2.40，4.10）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e2.55（1.80，3.20）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eSCr (umol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e71.92\u0026plusmn;16.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e70.87\u0026plusmn;16.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e76.14\u0026plusmn;15.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eSUA\u0026nbsp;（umol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e329.42\u0026plusmn;92.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e317.36\u0026plusmn;86.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e377.89\u0026plusmn;97.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eTG\u0026nbsp;（mmol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e1.72\u0026plusmn;1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e1.27\u0026plusmn;0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e3.54\u0026plusmn;1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eTC (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e4.85\u0026plusmn;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e4.78\u0026plusmn;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e5.14\u0026plusmn;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eLDL-C (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e3.06\u0026plusmn;0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e3.07\u0026plusmn;0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e3.03\u0026plusmn;0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.573\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eHDL (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e1.33\u0026plusmn;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e1.40\u0026plusmn;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e1.04\u0026plusmn;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eTSH (\u0026mu;IU/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e1.84\u0026plusmn;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e1.78\u0026plusmn;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e2.09\u0026plusmn;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFT3 (pmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e4.43\u0026plusmn;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e4.40\u0026plusmn;0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e4.55\u0026plusmn;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFT4(pmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e13.01\u0026plusmn;1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e13.02\u0026plusmn;1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e12.98\u0026plusmn;1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.789\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFT3/FT4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.34\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 105px;\"\u003e\n \u003cp\u003e0.34\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.35\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eData are expressed as means \u0026plusmn; standard deviations, medians (interquartile ranges), or percentages. Independent samples T-test or Mann-Whitney U-test are used to compare the differences of continuous variables between two groups. BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBG, fasting blood glucose; FBG, fasting blood glucose; ALB, albumin; ALT, alanine transaminase; AST, aspartic transaminase; GGT, \u0026gamma;-glutamyl transferase; TBIL, total bilirubin; IBIL, indirect bilirubin; DBIL, direct bilirubin; TG, triglyceride ; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TSH, Thyrotropic hormone; FT3, free triiodothyronine; FT4, free thyroxine; FT3/FT4, The ratio of free triiodothyronine to free thyroxine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSmooth curve fitting and threshold effect analysis of the relationship between peripheral thyroid hormone sensitivity and TG\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter adjusting the confounding factors of gender, age, BMI, blood pressure, blood glucose, blood lipids, and liver and kidney function, the FT3/FT4 ratio was curvilinearly correlated with TG. The FT3/FT4 ratio was positively correlated with TG before the inflection point at 0.426, with a corresponding increase of 1.752 in TG for every 1-unit increase in the FT3/FT4 ratio (\u0026beta;=1.752, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). However, after the inflection point there was no significant difference observed in the correlation between the FT3/FT4 ratio and TG (\u003cem\u003eP\u003c/em\u003e=0.053)\u0026nbsp;(\u003cstrong\u003eTable 2\u003c/strong\u003e,\u003cstrong\u003eFig. 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThreshold effect analysis of the relationship between the FT3/FT4 ratio\u0026nbsp;and TG in the overall population\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"350\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 142px;\"\u003e\n \u003cp\u003eOutcome: TG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFor exposure：FT3/FT4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 142px;\"\u003e\n \u003cp\u003eModel Ⅰ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 142px;\"\u003e\n \u003cp\u003eOne-line effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 208px;\"\u003e\n \u003cp\u003e1.305 (0.508, 2.103) 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 142px;\"\u003e\n \u003cp\u003eModel Ⅱ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 142px;\"\u003e\n \u003cp\u003eInflection point (k)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.426\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt; K segment effect1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 208px;\"\u003e\n \u003cp\u003e1.752 (0.874, 2.629) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026gt; K segment effect2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 208px;\"\u003e\n \u003cp\u003e-6.271 (-12.624, 0.082) 0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 142px;\"\u003e\n \u003cp\u003eDifference in effect of 2 and 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 208px;\"\u003e\n \u003cp\u003e-8.023 (-14.698, -1.349) 0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 142px;\"\u003e\n \u003cp\u003eLog-likelihood ratio test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTrend tests of multiple regression equations for the relationship between the FT3/FT4 ratio and TG\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe smooth curve fitting and threshold effect analysis of the overall data showed the FT3/FT4 ratio was positively correlated with TG before the inflection point.\u0026nbsp;Further trend tests of multiple regression equations were performed to verify whether the correlation trend was statistically significant. P values for trend were calculated with quartiles as continuous variables.\u003c/p\u003e\n\u003cp\u003eThe results showed that with the increase of quartiles of the FT3/FT4 ratio, the gradually increasing trend of TG was statistically significant. For each one-grade increase in the FT3/FT4 ratio, the level of TG increased by 0.0624 accordingly (\u0026beta;=0.0624, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). For each SD increase in the FT3/FT4 ratio, the level of TG increased by 0.0587 mmol/L (\u0026beta;=0.0587, \u003cem\u003eP\u003c/em\u003e=0.001) (\u003cstrong\u003eTable 3\u003c/strong\u003e,\u003cstrong\u003eFig. 4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eLogistic regression analysis of the correlation between the FT3/FT4 ratio and TG\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"553\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 108px;\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 218px;\"\u003e\n \u003cp\u003eAdjust Model I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"4\" style=\"width: 223px;\"\u003e\n \u003cp\u003eAdjust Model II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026beta; (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 155px;\"\u003e\n \u003cp\u003e\u0026beta; (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003eFT3/FT4\u0026nbsp;per SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 156px;\"\u003e\n \u003cp\u003e0.1750 (0.0939, 0.2560)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 155px;\"\u003e\n \u003cp\u003e0.0587 (0.0229, 0.0946)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 156px;\"\u003e\n \u003cp\u003e0 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 162px;\"\u003e\n \u003cp\u003e0 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 156px;\"\u003e\n \u003cp\u003e0.3164 (0.0866, 0.5463)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 162px;\"\u003e\n \u003cp\u003e0.1069 (0.0096, 0.2041)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 156px;\"\u003e\n \u003cp\u003e0.2563 (0.0265, 0.4861)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 162px;\"\u003e\n \u003cp\u003e0.1522 (0.0549, 0.2494)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 156px;\"\u003e\n \u003cp\u003e0.4572 (0.2276, 0.6868)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 162px;\"\u003e\n \u003cp\u003e0.1938 (0.0935, 0.2941)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003eFT3/FT4 quartile continuous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 156px;\"\u003e\n \u003cp\u003e0.1311 (0.0585, 0.2038)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 162px;\"\u003e\n \u003cp\u003e0.0624 (0.0309, 0.0940)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eP for trend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 62px;\"\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\u003c/div\u003e\n\u003cp\u003eModel 1 did not correct for confounding factors\u003c/p\u003e\n\u003cp\u003eModel 2 Adjusted for gender, age, BMI, blood pressure, blood glucose, blood lipids, and liver and kidney function; \u0026beta;, regression coefficient; CI, confidence interval; \u003cem\u003eP\u003c/em\u003e for trend was calculated using the quartiles as continuous variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSubgroup analysis of the correlation between the FT3/FT4 ratio and TG\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter adjusting for confounders including age, BMI, SBP, DBP, ALB, ALT, AST, GGT, TBIL, CR, FBG, TC, HDL, and LDL, the FT3/FT4 ratio was positively correlated with TG in female group. For every unit increase in the FT3/FT4 ratio, TG increased by 1.9040 (\u0026beta;=1.9040, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). In male group, the FT3/FT4 ratio was no significant correlation with TG.\u003c/p\u003e\n\u003cp\u003eAfter adjusting for confounders including gender, BMI, SBP, DBP, ALB, ALT, AST, GGT, TBIL, CR, FBG, TC, HDL, and LDL, the FT3/FT4 ratio was curvilinearly correlated with TG in age \u0026lt;65 years group. The FT3/FT4 ratio was positively correlated with TG before the inflection point at 0.4272, with a corresponding increase of 1.7773 in TG for every 1-unit increase in the FT3/FT4 ratio (\u0026beta;=1.7773, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). However, after the inflection point there was no significant difference observed in the correlation between the FT3/FT4\u0026nbsp;ratio and TG. In age\u0026sup3;65 years group, the FT3/FT4 ratio was no significant correlation with TG.\u003c/p\u003e\n\u003cp\u003eAfter adjusting for confounders including age, gender, SBP, DBP, ALB, ALT, AST, GGT, TBIL, CR, FBG, TC, HDL, and LDL,\u0026nbsp;the FT3/FT4 ratio\u0026nbsp;was\u0026nbsp;positively\u0026nbsp;correlated with TG\u0026nbsp;in\u0026nbsp;BMI\u0026lt;28 kg/m\u003csup\u003e2\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003egroup. For every unit increase in the FT3/FT4 ratio, TG increased by 1.4660 (\u0026beta;=1.4660, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). In BMI\u0026sup3;28 kg/m\u003csup\u003e2\u003c/sup\u003e group, the FT3/FT4 ratio was no significant correlation with TG.\u003c/p\u003e\n\u003cp\u003eWe concluded that the FT3/FT4 ratio was positively correlated with TG levels in the female population, in individuals aged \u0026lt;65 years, and in those with BMI \u0026lt;28 kg/m\u0026sup2; (\u003cstrong\u003eTable 4\u003c/strong\u003e,\u003cstrong\u003eFig. 5\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eSubgroup analysis of the correlation between the FT3/FT4 ratio and TG\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"609\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 53px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 174px;\"\u003e\n \u003cp\u003egender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 174px;\"\u003e\n \u003cp\u003eage（year）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 174px;\"\u003e\n \u003cp\u003eBMI（kg/m\u003csup\u003e2\u003c/sup\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026sup3;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026sup3;28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 87px;\"\u003e\n \u003cp\u003eModel Ⅰ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 87px;\"\u003e\n \u003cp\u003eOne-line effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.9040 (0.8208, 2.9872) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.7922 (-0.2739, 1.8582) 0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.0829 (-0.7187, 2.8845) 0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.3245 (0.4722, 2.1767) 0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.6371 (-1.7683, 3.0425) 0.604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.4660 (0.6579, 2.2741) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 87px;\"\u003e\n \u003cp\u003eModel II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 87px;\"\u003e\n \u003cp\u003eInflection point (k)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.3680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.4360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.2971\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.4272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.4129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.3956\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt; K segment effect1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e2.6989 (1.2115, 4.1863) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.2753 (0.0798, 2.4708) 0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-2.8014 (-8.5552, 2.9523) 0.344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.7773 (0.8366, 2.7179) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;2.2361 (-0.6550, 5.1271) 0.1321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e2.0243 (1.0381, 3.0105) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026gt; K segment effect2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.4695 (-3.7053, 2.7664) 0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-8.2217 (-17.5129, 1.0694) 0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e2.9270 (-0.2241, 6.0782) 0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-6.2261 (-12.9966, 0.5445) 0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-11.4520 (-24.0818, 1.1779) 0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-1.6293 (-4.8774, 1.6189) 0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 87px;\"\u003e\n \u003cp\u003eDifference in effect of 2 and 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-3.1684 (-7.2396, 0.9029) 0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e5.1749 (-0.9653, 11.3152) 0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e5.7285 (-2.3382, 13.7952) 0.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-8.0033 (-15.1231, -0.8835) 0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-13.6880 (-27.7321, 0.3560) 0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-3.6536 (-7.3675, 0.0604) 0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 87px;\"\u003e\n \u003cp\u003eLog-likelihood ratio test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this cross-sectional study of euthyroid adults, we observed that individuals with HTG had higher TSH, FT3, and the FT3/FT4 ratio compared to those with normal TG. After comprehensive adjustment for confounders, greater peripheral thyroid hormone sensitivity, which is reflected by a higher FT3/FT4 ratio, was independently associated with elevated TG levels. This association was particularly prominent in females, in individuals aged \u0026lt;65 years, and in those with BMI\u0026lt;28 kg/m\u0026sup2;.\u003c/p\u003e\n\u003cp\u003eOur findings align partially with those of Gu et al. [7] from the TCLSIH cohort, which also reported that higher FT3 levels within the euthyroid range were linked to an unfavorable lipid profile. Conversely, Gu et al. [16] observed in patients with coronary heart disease that a higher FT3/FT4 ratio was associated with a lower risk of dyslipidemia. This discrepancy might stem from differences in study populations: individuals with coronary heart disease often exhibit atherosclerosis and systemic inflammation, in which peripheral thyroid hormone metabolism could be altered as a compensatory response. In that context, an elevated FT3/FT4 ratio might represent an adaptive mechanism to preserve metabolic homeostasis [20],[21]. By contrast, our study focused on generally healthy adults, which may better capture associations under physiological conditions.\u003c/p\u003e\n\u003cp\u003eThe elevation of plasma TG results from both the overproduction and impaired clearance of TG-rich lipoproteins\u0026mdash;very-low-density lipoproteins and chylomicrons[22]. Experimental evidence indicates that HTG, accompanied by increased serum fatty acid concentrations, suppresses mitochondrial complex formation in pancreatic acinar cells, induces abnormal elevation of intracellular calcium, promotes cytokine release and tissue injury, and impairs pancreatic ductal function, thereby leading to acute pancreatitis[23]. In the context of HTG, elevated levels of triglyceride-rich lipoproteins and their remnants can penetrate the endothelial barrier and interact with macrophages, promoting foam cell formation and inflammatory responses within the arterial wall. These processes contribute to the development of atherosclerosis and increase the risk of coronary heart disease[24]. In summary, HTG is closely linked to the pathogenesis of multiple diseases, underscoring the importance of its management and control.\u003c/p\u003e\n\u003cp\u003eTH is key regulators of TG metabolism. TH concentrations correlate with hepatic TG content and influence HDL metabolism by enhancing the activity of cholesteryl ester transfer protein, which transfers cholesteryl esters from HDL to very-low-density lipoproteins and TG-rich lipoproteins[25]. T3 stimulates lipoprotein lipase, promoting the catabolism of TG-rich lipoproteins and thereby lowering TG levels[26]. Furthermore, studies in TSH receptor knockout mouse models demonstrate that TSH dose-dependently suppresses adipose TG lipase expression in mature adipocytes via the cAMP-protein kinase pathway, consequently promoting TG accumulation within fat cells[27].\u0026nbsp;Substantial evidence confirmed that both elevated and reduced TH levels altered the blood lipid profile. Patients with hypothyroidism exhibit increased levels of TC, LDL-C, and TG, along with decreased HDL-C, with the most pronounced changes observed in TC and LDL-C levels. In contrast, patients with hyperthyroidism showed significantly reduced levels of TC, TG, and LDL-C[28][29]-30]. Even within the normal range, thyroid function correlated with systemic metabolism: when TSH remained within normal limits, a rising TSH level was associated with significant increases in TC, TG, and LDL-C, and a significant decrease in HDL-C[31]. Additionally, elevated FT3 level was frequently observed in euthyroid individuals with obesity and non-alcoholic fatty liver disease[32].\u003c/p\u003e\n\u003cp\u003ePhysiologically, TSH, FT4 and FT3 regulate and influence each other in HPA axis. Compared with a single indicator, the calculation of a composite indicator could systematically reflect the regulation of TH homeostasis. Since FT4 is peripherally converted to FT3 by deiodinases, the FT3/FT4 ratio serves as an indicator of peripheral deiodinase activity[33]. A study by Bilgin and Pirgon suggested that enhanced conversion of FT4 to FT3 via increased deiodinase activity might represent a compensatory mechanism in the context of fat accumulation, aimed at elevating energy expenditure and reflecting heightened TH sensitivity[34].\u0026nbsp;Our findings demonstrated a positive correlation between the FT3/FT4 ratio and level, suggesting that increased peripheral TH sensitivity was associated with elevated TG. Given the influence of sex hormones[35]and age[36]on thyroid function, we performed subgroup analyses by gender and age. The observed gender-based differences may be attributed to the distinct regulatory effects of sex hormones on thyroid function. For instance, estrogen and androgen exerted differential influences on serum thyroxine-binding globulin concentrations, thereby modulating thyroid activity[37].\u0026nbsp;The age-related variations in lipid metabolism may be explained by the impact of aging and menopausal hormonal changes. With advancing age, a reduction in thyroid hormone receptor expression occurred, leading to diminished tissue responsiveness to TH[38],[39]. The BMI subgroup differences may involve interactions between TH and leptin. Leptin, an adipokine secreted by adipose tissue, acted directly on the hypothalamic paraventricular nucleus to stimulate transcription of the thyrotropin-releasing hormone (TRH) precursor, thereby promoting TRH secretion[40]. It may also indirectly stimulate TRH secretion in the arcuate nucleus by promoting production of downstream pro-opiomelanocortin derivatives[41].\u003c/p\u003e\n\u003cp\u003eFrom a clinical perspective, the FT3/FT4 ratio might serve as a useful adjunctive marker for identifying euthyroid individuals who could be at heightened risk of hypertriglyceridemia. This could be particularly relevant in subgroups such as women, middle-aged adults, and non-obese persons, in whom routine lipid screening might benefit from additional risk stratification. Although further prospective studies are needed to establish causality, incorporating thyroid function parameters into regular health check-ups may help highlight individuals who could benefit from closer metabolic monitoring or early lifestyle counseling. Given the well-documented burden of hypertriglyceridemia in relation to atherosclerotic cardiovascular disease and pancreatitis [42], even modest improvements in risk prediction could have public health implications. The potential utility of such an approach resonates with current recommendations that emphasize targeted screening and primary prevention strategies for high-risk populations [43].\u003c/p\u003e\n\u003cp\u003eSeveral limitations of this study should be acknowledged: 1. The cross-sectional design precludes any causal inference regarding the relationship between peripheral thyroid hormone sensitivity and hypertriglyceridemia. Therefore, the observed associations warrant confirmation in prospective cohort studies. 2. As a single-center study with a relatively modest sample size recruited from a specific geographic region, the generalizability of our findings to other populations may be limited and requires validation in larger, multicenter cohorts. 3. Although we adjusted for a wide range of potential confounders\u0026mdash;including demographic characteristics, metabolic parameters, and liver and kidney function\u0026mdash;the possibility of residual confounding due to unmeasured variables (e.g., insulin resistance, inflammatory markers such as high-sensitivity C-reactive protein, or detailed medication adherence) cannot be entirely excluded. 4. The absence of data on thyroid autoantibodies and urinary iodine levels precluded assessment of potential underlying thyroid autoimmunity or iodine nutritional status, which may influence thyroid hormone metabolism and confound the observed associations. 5. Because the study population consisted of individuals undergoing routine health check-ups, the medication histories relied on self-report and may be subject to recall bias, despite our efforts to exclude those taking lipid-lowering or thyroid-affecting medications. 6. While the FT3/FT4 ratio is a widely used surrogate marker of peripheral deiodinase activity, it remains an indirect measure of thyroid hormone sensitivity; direct assessment of deiodinase enzyme activity or tissue-level thyroid hormone action was not performed and should be addressed in future mechanistic studies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, increased peripheral thyroid hormone sensitivity was significantly associated with elevated TG level, with this correlation being more pronounced in female, young and middle-aged adults, and non-obese individuals. These findings highlight the need for longitudinal studies to clarify the directionality and potential mechanisms of this relationship. A better understanding of this association could contribute to more refined risk stratification and ultimately aid in the prevention of HTG and its complications.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated and analysed during our study were included in the supplementary files in the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis investigation was approved by the Research Ethics Committee of the Third Affiliated Hospital of Anhui Medical University (No.2024-167-01), adhereing to the tenets of the Declaration of Helsinki. Informed consents were obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYG: Visualization, Validation, Investigation, Formal analysis, Conceptualization, Writing \u0026ndash; original draft, Methodology and Data curation. QQZ: Visualization, Validation, Investigation, Formal analysis, Conceptualization, and Data curation. GJW: Visualization, Validation, Investigation, Formal analysis, Conceptualization, and Data curation. YL: Visualization, Validation, Investigation, Formal analysis, Conceptualization, Writing \u0026ndash; review \u0026amp; editing, Methodology and Data curation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col class=\"decimal_type\"\u003e\n \u003cli\u003eNewman CB, Blaha MJ, Boord JB, Cariou B, Chait A, Fein HG, et al. Lipid Management in Patients with Endocrine Disorders: An Endocrine Society Clinical Practice Guideline. 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Circulation, 2019, 139(25): e1082-e143. https://doi.org/10.1161/cir.0000000000000625.\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":"bmc-endocrine-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bend","sideBox":"Learn more about [BMC Endocrine Disorders](http://bmcendocrdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bend/default.aspx","title":"BMC Endocrine Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Thyroid hormone sensitivity, Free triiodothyronine to free thyroxine ratio, Hypertriglyceridemia","lastPublishedDoi":"10.21203/rs.3.rs-8867531/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8867531/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e We aimed to investigate the correlation between peripheral thyroid hormone sensitivity and hypertriglyceridemia in euthyroid population.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e A total of 833 individuals who underwent physical examinations were randomly selected. Biochemical parameters including thyroid hormones, liver and kidney functions, blood glucose, and blood lipids were measured.\u003cstrong\u003e \u003c/strong\u003ePeripheral thyroid hormone sensitivity was assessed by the ratio of free triiodothyronine to free thyroxine (FT3/FT4). The data were analyzed for the relationship between peripheral thyroid hormone sensitivity and triglyceride (TG).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003esmooth curve fitting and threshold effect analysis showed that FT3/FT4 ratio was a positive correlation with TG before the inflection point at 0.426 (β=1.752,\u003cem\u003e P\u003c/em\u003e\u0026lt;0.001). Tests for trend in multiple regression equations showed that with the increase of the quartiles of FT3/FT4 ratio, the gradually increasing trend of TG was statistically significant. For per SD increase in FT3/FT4 ratio, TG increased by 0.0587mmol/L (β=0.0587, \u003cem\u003eP\u003c/em\u003e=0.001). Subgroup analysis revealed that\u003c/p\u003e\n\u003cp\u003ein female group (β=1.9040, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), age \u0026lt;65 years group (before the inflection point 0.4272, β=1.7773, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), and BMI\u0026lt;28 kg/m\u003csup\u003e2\u003c/sup\u003e group (β=1.4660, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), the FT3/FT4 ratio was positively correlated with TG.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e Increased peripheral thyroid hormone sensitivity, as reflected by an elevated FT4 to FT3 conversion rate, is associated with increased TG level in euthyroid population. This association is particularly pronounced in females, individuals with aged\u0026lt;65 years, and non-obese (BMI\u0026lt;28 kg/m\u003csup\u003e2\u003c/sup\u003e) individuals.\u003c/p\u003e","manuscriptTitle":"Association Between Peripheral Thyroid Hormone Sensitivity and Hypertriglyceridemia in Euthyroid Population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-20 16:30:54","doi":"10.21203/rs.3.rs-8867531/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-14T15:49:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-04T17:35:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-31T21:21:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"141558511338427285597587634463313115250","date":"2026-03-31T20:11:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-28T17:44:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214120545457895025134808967611366830947","date":"2026-03-27T12:12:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"124938007179445461774620412797517835024","date":"2026-03-27T08:43:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"284980829903950135541942145415387609134","date":"2026-03-20T12:45:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-17T18:19:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-16T08:04:13+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-25T06:02:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-24T14:40:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Endocrine Disorders","date":"2026-02-24T14:34:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-endocrine-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bend","sideBox":"Learn more about [BMC Endocrine Disorders](http://bmcendocrdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bend/default.aspx","title":"BMC Endocrine Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f40828d2-7019-41fd-81f2-0bb53b85c9bf","owner":[],"postedDate":"March 20th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-14T15:49:39+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T16:00:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-20 16:30:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8867531","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8867531","identity":"rs-8867531","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}