Abstract
Compiling evidence supports that selenium plays a vital role in glucose metabolism. Triglyceride-glucose index (TyG) and triglyceride-glucose-body mass index (TyG-BMI) are commonly used in epidemiologic studies to evaluate insulin resistance and cardiovascular disease (CVD) risks. This study is aimed to investigate the association between whole blood selenium concentration and TyG and TyG-BMI. A total of 6290 participants (age ≥ 20 years) from the National Health and Nutrition Examination Survey (NHANES) 2011–2018 were included. Multiple linear regression models were used to examine the association between blood selenium quartiles and TyG and TyG-BMI. Subgroup analysis stratified by diabetes status was also performed. The adjusted model showed a positive association between TyG and blood selenium concentration (β [95%CI] = 0.099 [0.063, 0.134], p < 0.001) and TyG-BMI (β [95%CI] = 3.185 [2.102, 4.268], p < 0.001). The association persisted after stratification by diabetes status (p < 0.001). Participants were stratified into four quartiles based on selenium concentration (Q1: 1.08–2.24 μmol/L, Q2: 2.25–2.42 μmol/L, Q3: 2.43–2.62 µmol/L, Q4: 2.63–8.08). Compared with the Q1 group, TyG in the Q3 and Q4 groups was significantly higher (β = 0.075 [95%CI 0.039 to 0.112] and β = 0.140 [95%CI 0.103 to 0.176], respectively). Additionally, TyG-BMI in the Q2, Q3, and Q4 groups was higher than that in the Q1 group (β = 1.189 [95%CI 0.065 to 2.314], β = 2.325 [95%CI 1.204 to 3.446], and β = 4.322 [95%CI 3.210 to 5.435], respectively). Blood level of selenium was positively associated with TyG and TyG-BMI, indicating that excessive blood selenium may be associated with impaired insulin sensitivity and increased risk of cardiovascular disease.
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Introduction
Selenium is an essential trace element for humans, participating in the formation of various selenoproteins, including glutathione peroxidase (GPx), iodothyronine deiodinase (DIO), selenoprotein P (SELENOP), selenoprotein S (SELENOS), and thioredoxin reductase (Trxr) [1,2,3]. Early studies suggest that selenium plays a role in insulin mimic and anti-diabetes [4, 5]. Studies have shown that serum selenium levels in diabetic populations are lower than in healthy populations [6]. Furthermore, selenium has been suggested to play a protective role against type 2 diabetes (T2DM) [7, 8], and high levels of selenium may reduce the prevalence of diabetes [9]. In addition, selenium has been shown to prevent atherosclerosis by modulating inflammatory processes, inhibiting oxidative stress, and protecting endothelial cells from apoptosis [10, 11]. However, the relationships between selenium and metabolic diseases are complex, and recent studies have revealed that excessive selenium supplementation may have adverse effects on β-cell function and insulin sensitivity [2]. Higher selenium concentration may interfere with insulin signal transduction, leading to the acceleration of impaired glucose metabolism [12]. Selenium in obesity was negatively associated with body mass index (BMI); however, selenium levels were higher in subjects with metabolic syndrome[13]. Furthermore, a longitudinal study found that a high level of selenium is associated with the development of hypertension [14].
Triglyceride-glucose index (TyG) and triglyceride-glucose-body mass index (TyG-BMI), derived from fasting plasma glucose (FPG) and triglyceride (TG), are two indicators for evaluating insulin resistance(IR) in epidemiological studies [15]. IR contributes to developing CVD in individuals with diabetes and non-diabetes. TyG emerged as a new force, which was shown to be superior to homeostasis model assessment-insulin resistance (HOMA-IR) in evaluating IR, especially for diabetes individuals receiving insulin therapy or without functioning beta cells [35, 36]. TyG and TyG-IBM are positively correlated with insulin resistance (HOMR-IR and HbA1c) [37, 38]. TyG may be helpful to predict the occurrence of DM and it is a useful index reflecting glycemic control for T2DM (AUC = 0.806) [35, 39, 40]. Furthermore, TyG has been proved to be an independent predictor for atherosclerotic cardiovascular diseases (ASCVD) by several studies [41,42,43]. Since a 10 years follow-up study promulgate a positive correlation between TyG and CVD events (AUC = 0.708), the investigations detecting their relationships emerge in large numbers [43,44,45]. Elevated TyG is a marker for macro- and microvascular damage [16]. A cross-sectional study from Japan shows a positive correlation between TyG and subclinical atherosclerosis [17].
Since TyG and TyG-BMI are reliable and easy to obtain, they may be effective indicators to demonstrate CVD events in the future for diabetes and non-diabetes individuals. To date, the relationship between blood level of selenium and TyG or TyG-BMI has not been investigated. Therefore, our study aims to investigate the relationship of selenium with TyG and TyG-BMI.
Methods
Data Sources
The NHANES (National Health and Nutrition Examination Survey) is a population-based cross-sectional survey designed to collect information on the health and nutrition status of adults and children in the USA. Most of the data in NHANES is freely accessible to researchers worldwide. This investigation pooled data from 2011 to 2018.
Study Population
A total of 39,156 persons were enrolled in NHANES from 2011 to 2018. Participants (n = 16,539) with ages younger than 20 years old were excluded. We excluded 12,685, 2540, and 193 individuals due to the absence of data on FPG, whole blood selenium, and TG, respectively. Individuals without self-report diabetes status (n = 146) or hypertension status (n = 9) were excluded. Besides, 67 persons with diabetes onset age below 30 years were excluded to minimize the confounding factor for type 1 diabetes mellitus. Individuals having no record of education level (n = 4), current alcohol use (n = 617), smoking status (n = 3), and physical activity habits (n = 3) were also excluded. Finally, a total of 6290 participants was included for data analysis (see Fig. 1 for details). The survey protocol was approved by the Institutional Review Board of the Centers for Disease Control and Prevention (CDC). Written consent informs were obtained from all participants.
Study Variables
The exposure variable in this study is whole-blood selenium. Through inductively coupled plasma mass spectrometry (ICP-MS) and dynamic reaction cell technology (ELAN ® DRC II, Perkin Elmer Norwalk) measures blood selenium concentration using a diluted sample preparation step followed by a whole blood sample. The lower limit of detection (LLOD) is 24.48 μg/L. All data are above LLOD. The index for our investigation was TyG and TyG-BMI. TyG was calculated by the formula of Ln[TG (mg/dL) × FPG (mg/dL)/2] [18], and TyG-BMI was calculated by TyG × BMI [19]. Type 2 diabetes was defined by self-report or FPG ≥ 7.0 mmol/L (126 mg/dL) or glycosylated hemoglobin (HbA1c) ≥ 6.5%. Hypertension was defined by self-report, or the measured systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg. Smoker was defined as the consumption of more than 100 cigarettes in the whole life [20]. Current alcohol use was defined as the consumption of more than 12 drinks last year [21]. Active physical activity status was defined as a continuously vigorous and intensive activity for at least 10 min in a typical week. Education level was stratified according to whether he or she had attended high school. Sociodemographic variables such as age, sex, and race were extracted from the file named demographic variables. BMI was extracted from the file named body measures. Serum uric acid (SUA) and creatinine (SCr) were extracted from standard biochemistry profiles. Total cholesterol, triglyceride, FPG, HbA1c, and whole blood selenium were extracted from the laboratory data. The selection of covariates in this study was based on a review of relevant literature, and multiple possible covariates related to selenium levels were selected, including age, race, sex, hypertension, smoking, physical activity, alcohol consumption, cholesterol, and kidney function-related indicators (such as serum uric acid and serum creatinine) [22,23,24,25,26,27].
Statistical Analyses
All analysis was performed by Empower Stats (Version 4.1) and with the built-in R packages. NHANES sample weights were used as recommended by the National Center for Health Statistics (NCHS). Continuous variables were represented as mean ± SD, and the p-value was calculated by weighted linear regression model between T2DM and non-DM groups. Categorical variables were represented as %, and the p-value was calculated by weighted chi-square test between T2DM and non-DM groups. The association between blood level of selenium and TyG or TyG-BMI was evaluated by multiple linear regression analysis models. Participants were stratified to 4 quartiles according to selenium concentration. (Q1:1.08–2.24 μmol/L, Q2: 2.25–2.42 μmol/L, Q3: 2.43–2.62 µmol/L, Q4: 2.63–8.08). Compared with the Q1 quartile group, the association between whole blood selenium and TyG/TyG-BMI in Q2-4 quartile groups by multiple linear regression analysis models. The models were adjusted for age, sex, race, smoker, current alcohol use, education level, physical activity, BMI, HTN, diabetes status, HbA1c, TC, SUA, and Scr. Subgroup analysis, according to diabetic status, was performed. The models for subgroup analysis were not adjusted to diabetes status. Tests for linear trend were performed by entering the median value for each quintile in the models. P value < 0.05 is defined as a significant difference.
Results
The characteristics of the participants were shown in Table 1. Compared with the non-diabetes group, the T2DM group had older age, higher BMI, higher level of SUA and SCr, and lower level of TC. At the same time, they had a higher incidence of hypertension, smoking, current alcohol use, and low education level. The blood level of selenium in the T2DM group was 1.2% higher than that in the non-DM group (p = 0.038). TyG and TyG-BMI in the T2DM group were 8.2% and 25.3% higher than those in the non-DM group p < 0.001, respectively). Analysis of simple correlation was conducted to evaluated covariates which affect TyG and TyG-BMI. It was found that sex, race, education, physical activity, BMI, HTN, DM, HbA1c, TC, SUA, SCr, and, selenium were associated with TyG and TyG-BMI (Supplementary Table 1).
Association of Blood Level of Selenium with TyG or with TyG-BMI
There was a positive association of selenium concentration with TyG and TyG-BMI (β = 0.219 and 8.047, 95%CI = 0.174 to 0.265 and 3.350 to 12.744). After fully adjusted, every 1 μmol/L increment in selenium concentration corresponds to 0.099 and 3.185 increase in TyG and TyG-BMI, respectively. In the T2DM group, after being adjusted for multiple covariates, every 1 μmol/L increment in selenium concentration corresponds to 0.137 and 5.332 increases in TyG and TyG-BMI, respectively. In the non-DM group, the corresponding increase in TyG and TyG-BMI was 0.090 and 2.802, respectively. (Details in Table 2).
Association Between TyG, TyG-BMI, and Blood Selenium Concentration Quartiles
Participants were stratified into 4 quartiles according to blood selenium concentration (Q1:1.08–2.24 μmol/L, Q2: 2.25–2.42 μmol/L, Q3: 2.43–2.62 µmol/L, Q4: 2.63–8.08). Compared with the Q1 quartile group, TyG in Q3 and Q4 quartiles was significantly higher with the β’s of 0.075 and 0.140 (both p < 0.001). In the T2DM group, TyG in Q4 was higher than in Q1 with β = 0.187 (p < 0.001). In the non-DM group, TyG in Q3 and Q4 was higher than in Q1 with β = 0.082 and 0.130 (both p < 0.001). The p-trend for 4 quartiles classified by diabetes status was statistically significant (p < 0.001) (details in Table 3 and Fig. 2).
Compared with the Q1 quartile group, TyG-BMI in Q2, Q3, and Q4 were significantly higher with β = 1.189, 2.325, and 4.322 (both p < 0.001), respectively. In the T2DM group, the TyG-BMI in Q2 and Q4 was higher than in Q1 with β = 4.172 and 6.820 (p = 0.014 and p < 0.001). In the non-DM group, TyG-BMI in Q3 and Q4 was higher than in Q1 with β = 2.533 and 3.899 (both p < 0.001). The p-trend for 4 quartiles classified by diabetes status was statistically significant (p < 0.001) (Details in Table 4 and Fig. 3).
Discussion
TyG and TyG-BMI are two novel indicators to evaluate insulin resistance and cardiovascular disease risks in epidemiological studies. Our investigation shows that blood selenium concentration is positively associated with TyG and TyG-BMI. This association still exists despite T2DM or not. This is the first study to reveal a close relationship between selenium concentration and TyG or TyG-BMI, what’s more provides epidemiological evidence that the sensitivity of selenium rich people to insulin may be impaired.
The researchers combined the data from multiple studies to conclude that a blood selenium concentration of 1.0–1.2 μmol/l is sufficient to maximize GPx and SELENOP, as well as possibly other selenoproteins [28]. In our study, the average concentration of selenium in the American population (2.4 μmol/L) is relatively higher than in other countries and regions (0.82–1.41 μmol/L) [29,30,31,32,33,34]. Our investigation demonstrated that excessive blood selenium is associated with more severe insulin resistance indicated by TyG and TyG-BMI. After being adjusted by all compounding factors, the effect of selenium levels on TyG and TyG-BMI was very mild (For every 1 μmol/L increment in selenium concentration, TyG and TyG-BMI would increase by 0.15 SD (0.099/0.671) and 0.05 SD (3.185/68.572), respectively. Our results indicate that supplementation of selenium should not be recommended for people replete with selenium.
In this study, TyG and TyG-BMI were used as surrogates to explore the relationship between insulin sensitivity and blood level of selenium. Previous studies showed a beneficial effect of selenium supplementation on glucose metabolism in populations with low selenium [5, 35]. Both animal and epidemiologic investigations have found that selenium deficiency is associated with decreased insulin sensitivity, which could be improved by appropriate supplementation [36,37,38,39,40]. However, recent emerging evidence showed that excessive selenium may have a detrimental effect on insulin sensitivity. Cardoso et al. (2021) found that the serum concentration of selenium in the selenium-replete population in the United States was positively correlated with fast insulin level and insulin resistance (HOMA-IR) [41]. A meta-analysis, collecting data from five experimental studies, found that selenium supplementation (200 μg/day) increased the risk of diabetes by 11% (RR 1.11, 95% CI 1.01–1.22) [42]. Although the comprehensive influences of selenium on glucose metabolism and insulin sensitivity are not conclusive, our investigation, by using indexes of TyG and TyG-BMI, indicated a detrimental effect on glucose metabolism by a higher level of selenium. We noticed that in the T2DM population, higher selenium concentration is associated with poorer glycemic control (high TyG and TyG-BMI). In a word, all these data revealed that deficient or excessive selenium would bring adverse effects on glycemic metabolism.
Considering the relationship between TyG and TyG-BMI and CVD, we speculate that selenium may be related to CVD, although we did not use CVD as the outcome of our research. The relationship and underlying mechanism between selenium concentration and CVD risk had not been fully investigated. Selenium supplementation showed some anti-atherosclerosis effects in cell lines and animal models researches [10]. It is estimated that increasing selenium concentration is associated with reducing CVD risks when the selenium concentration was 0.70–1.84 μmol/L [43,44,45]. Above this range, the anti-atherosclerosis effect of selenium could not be observed [46]. Consistent with the above evidence, our study revealed an association between higher blood selenium concentration and TyG and TyG-BMI in the population with excessive blood selenium. It is conjectured a U-shaped curve relationship between selenium concentration and CVD risks.
The biological form of selenium consists essentially of the amino acid selenocysteine which is incorporated into selenoproteins, such as SELENOP, GPx, and Trxr.. These molecules exert pivotal anti-oxidation effects. These selenoproteins are linked to the insulin signaling pathway and insulin secretion pathway as an antioxidant [47]. The activity of some key enzymes in insulin signaling was inhibited by SELENOP, leading to reduced insulin sensitivity [48]. Overexpression of GPx1 would impair the insulin signaling pathway by inhibiting ROS or hydrogen peroxide (H2O2) production, weakening the activation of protein tyrosine phosphatase 1B, and inhibiting the phosphorylation of insulin receptor and protein kinase B [49, 50]. Abnormal GPx3 expression may lead to the accumulation of local reactive oxygen species in adipose tissue and increase the risk of diabetes [51].
This study has some limitations. First, due to limited data from the US population, we could not figure out the whole picture reflecting the association between selenium concentration and insulin sensitivity since the population with selenium deficiency was not included. Second, a cross-sectional designed study could not conclude a causal relationship between selenium concentration and TyG and TyG-BMI. Thirdly, the study is in the lack of data on selenium intake in the population under investigation. High-quality, interventional and prospective studies are required to clarify the effects of selenium on diabetes development.
In conclusion, selenium concentration is positively correlated with TyG and TyG-BMI in the population with replete selenium, indicating detrimental effects of excessive selenium intake on glucose metabolism and CVD risks. The underlying mechanism needs to be further investigated.
Data Availability
The original contributions presented in the study are included in the article material, further inquiries can be directed to the corresponding authors.
References
Tsutsumi R, Saito Y (2020) Selenoprotein P; P for plasma, prognosis, prophylaxis, and more. Biol Pharm Bull 43(3):366–374
Steinbrenner H, Duntas LH, Rayman MP (2022) The role of selenium in type-2 diabetes mellitus and its metabolic comorbidities. Redox Biol 50:102236
Akahoshi N et al (2019) Dietary selenium deficiency or selenomethionine excess drastically alters organ selenium contents without altering the expression of most selenoproteins in mice. J Nutr Biochem 69:120–129
Stapleton SR (2000) Selenium: an insulin-mimetic. Cell Mol Life Sci 57(13–14):1874–1879
Erbayraktar Z et al (2007) Effects of selenium supplementation on antioxidant defense and glucose homeostasis in experimental diabetes mellitus. Biol Trace Elem Res 118(3):217–226
Navarro-Alarcon M et al (1999) Serum and urine selenium concentrations as indicators of body status in patients with diabetes mellitus. Sci Total Environ 228(1):79–85
Wei J et al (2015) The association between dietary selenium intake and diabetes: a cross-sectional study among middle-aged and older adults. Nutr J 14(1):1–6
Rajpathak S et al (2005) Toenail selenium and cardiovascular disease in men with diabetes. J Am Coll Nutr 24(4):250–256
Kljai K, Runje R (2001) Selenium and glycogen levels in diabetic patients. Biol Trace Elem Res 83(3):223–229
Liu H, Xu H, Huang K (2017) Selenium in the prevention of atherosclerosis and its underlying mechanisms. Metallomics 9(1):21–37
Krohn RM et al (2016) High-selenium lentil diet protects against arsenic-induced atherosclerosis in a mouse model. J Nutr Biochem 27:9–15
Stahel P et al (2017) Supranutritional selenium intake from enriched milk casein impairs hepatic insulin sensitivity via attenuated IRS/PI3K/AKT signaling and decreased PGC-1α expression in male Sprague-Dawley rats. J Nutr Biochem 41:142–150
Tinkov AA et al (2020) Selenium and selenoproteins in adipose tissue physiology and obesity. Biomolecules 10(4):1–31
Su L et al (2016) Longitudinal association between selenium levels and hypertension in a rural elderly Chinese cohort. J Nutr Health Aging 20(10):983–988
Sánchez-García A et al (2020) Diagnostic Accuracy of the Triglyceride and Glucose Index for Insulin Resistance: A Systematic Review. Int J Endocrinol 2020:1–7
Zhao S et al (2019) Association between macro- and microvascular damage and the triglyceride glucose index in community-dwelling elderly individuals: the Northern Shanghai Study. Cardiovasc Diabetol 18(1):1–8
Yang X et al (2022) The correlation of atherosclerosis and triglyceride glucose index: a secondary analysis of a national cross-sectional study of Japanese. BMC Cardiovasc Disord 22(1):1–12
Zhao J et al (2022) TyG index is positively associated with risk of CHD and coronary atherosclerosis severity among NAFLD patients. Cardiovasc Diabetol 21(1):123
Jiang C et al (2021) Triglyceride glucose-body mass index in identifying high-risk groups of pre-diabetes. Lipids Health Dis 20(1):161
Wang Y et al (2022) Association between electronic cigarettes use and whole blood cell among adults in the USA—a cross-sectional study of National Health and Nutrition Examination Survey analysis. Environ Sci Pollut Res 29(59):88531–88539
Midanik LT et al (1996) Risk functions for alcohol-related problems in a 1988 US national sample. Addiction 91(10):1427–37; discussion 1439–56
Ju W et al (2018) Relationship between higher serum selenium level and adverse blood lipid profile. Clin Nutr 37(5):1512–1517
Li A et al (2022) Novel Strategies for assessing associations between selenium biomarkers and cardiometabolic risk factors: concentration, visit-to-visit variability, or individual mean? Evidence From a repeated-measures study of older adults with high selenium. Front Nutr 9:1–20
Bastola MM et al (2020) Selenium, copper, zinc and hypertension: an analysis of the National Health and Nutrition Examination Survey (2011–2016). BMC Cardiovasc Disord 20(1):1–8
Lai H et al (2021) Selenium Deficiency-induced damage and altered expression of mitochondrial biogenesis markers in the kidneys of mice. Biol Trace Elem Res 199(1):185–196
Sebastiani G et al (2018) The Effects of alcohol and drugs of abuse on maternal nutritional profile during pregnancy. Nutrients 10(8):1008
Li J et al (2009) Effect of Dietary Selenium and Cigarette Smoke on Pulmonary Cell Proliferation in Mice. Toxicol Sci 111(2):247–253
Thomson CD (2004) Assessment of requirements for selenium and adequacy of selenium status: a review. Eur J Clin Nutr 58(3):391–402
Burk RF (2002) Selenium, an antioxidant nutrient. Nutr Clin Care 5(2):75–79
Van Cauwenbergh R et al (2004) Comparison of the serum selenium content of healthy adults living in the Antwerp region (Belgium) with recent literature data. J Trace Elem Med Biol 18(1):99–112
Van Cauwenbergh R et al (1994) Selenium concentration in serum of healthy Greek adults. J Trace Elem Electrolytes Health Dis 8(2):99–109
Safaralizadeh R et al (2005) Serum concentration of selenium in healthy individuals living in Tehran. Nutr J 4(1):32–32
Chen CJ et al (2006) Serum selenium in adult Taiwanese. Sci Total Environ 367(1):448–450
Laustsen BH et al (2021) Serum selenium levels and asthma among seafood processing workers in Greenland. Int J Circumpolar Health 80(1):1–9
Kilinc M et al (2008) Evaluation of serum selenium levels in Turkish women with gestational diabetes mellitus, glucose intolerants, and normal controls. Biol Trace Elem Res 123(1–3):35–40
Yao X et al (2021) Zinc, selenium and chromium co-supplementation improves insulin resistance by preventing hepatic endoplasmic reticulum stress in diet-induced gestational diabetes rats. J Nutr Biochem 96:108810
Becker DJ et al (1996) Oral selenate improves glucose homeostasis and partly reverses abnormal expression of liver glycolytic and gluconeogenic enzymes in diabetic rats. Diabetologia 39(1):3–11
Mueller AS, Pallauf J, Rafael J (2003) The chemical form of selenium affects insulinomimetic properties of the trace element: investigations in type II diabetic dbdb mice. J Nutr Biochem 14(11):637–647
Mueller AS, Pallauf J (2006) Compendium of the antidiabetic effects of supranutritional selenate doses. In vivo and in vitro investigations with type II diabetic db/db mice. J Nutr Biochem 17(8):548–60
Reddi AS, Bollineni JS (2001) Selenium-deficient diet induces renal oxidative stress and injury via TGF-beta1 in normal and diabetic rats. Kidney Int 59(4):1342–1353
Cardoso BR, Braat S, Graham RM (2021) Selenium Status Is Associated With Insulin Resistance Markers in Adults: Findings From the 2013 to 2018 National Health and Nutrition Examination Survey (NHANES). Front Nutr 8:1–7
Vinceti M, Filippini T, Rothman KJ (2018) Selenium exposure and the risk of type 2 diabetes: a systematic review and meta-analysis. Eur J Epidemiol 33(9):789–810
Rayman MP (2012) Selenium and human health. Lancet 379(9822):1256–1268
Fairweather-Tait SJ et al (2011) Selenium in human health and disease. Antioxid Redox Signal 14(7):1337–1383
Benstoem C et al (2015) Selenium and its supplementation in cardiovascular disease—what do we know? Nutrients 7(5):3094–3118
Alehagen U, Alexander J, Aaseth J (2016) Supplementation with selenium and coenzyme Q10 Reduces cardiovascular mortality in elderly with low selenium status. a secondary analysis of a randomised clinical trial. PLoS One 11(7):e0157541
Czech MP, Lawrence JJ, Lynn WS (1974) Evidence for the involvement of sulfhydryl oxidation in the regulation of fat cell hexose transport by insulin. Proc Natl Acad Sci U S A 71(10):4173–4177
Mita Y et al (2017) Selenoprotein P-neutralizing antibodies improve insulin secretion and glucose sensitivity in type 2 diabetes mouse models. Nat Commun 8(1):1658
Mueller AS et al (2009) Regulation of the insulin antagonistic protein tyrosine phosphatase 1B by dietary Se studied in growing rats. J Nutr Biochem 20(4):235–247
Petersen MC, Shulman GI (2018) Mechanisms of Insulin Action and Insulin Resistance. Physiol Rev 98(4):2133–2223
Lee YS et al (2008) Dysregulation of adipose glutathione peroxidase 3 in obesity contributes to local and systemic oxidative stress. Mol Endocrinol 22(9):2176–2189
Acknowledgements
The authors thank the staff and the participants of the NHANES study for their valuable contributions.
Funding
This work was supported by the Beijing Municipal Natural Science Foundation (No. 7212080) and the Health Science and Technology Development Major Project of Nanjing (No. ZDX21001).
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Shuying Li and Jie Ding as the co-first authors contributed equally to data collection, statistical analysis, and writing of the manuscript. Li Feng and Xiaoxiao Sun contributed to statistical analysis. Jiengfeng Mao, Zhen Gui, and Weihong Zhou supervised the study and contributed to polishing and reviewing of the manuscript. All authors read and approved the manuscript.
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Li, S., Ding, J., Sun, X. et al. Selenium Concentration Is Positively Associated with Triglyceride-Glucose Index and Triglyceride Glucose-Body Mass Index in Adults: Data from NHANES 2011–2018. Biol Trace Elem Res 202, 401–409 (2024). https://doi.org/10.1007/s12011-023-03684-2
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DOI: https://doi.org/10.1007/s12011-023-03684-2