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Relationship between triglyceride-glucose index and endometriosis: a cross-sectional analysis

Abstract

Background

The link between insulin resistance and endometriosis is not well established. The triglyceride-glucose (TyG) index serves as a straightforward and economical indicator of insulin resistance. This study examines the link between the TyG index and the prevalence of endometriosis in a U.S. cohort.

Methods

This cross-sectional study analyzed data from the NHANES conducted between 1999 and 2006. Reproductive health was assessed through questionnaires, and the TyG index was derived from fasting triglyceride and glucose measurements. Weighted logistic regression models were used to analyze the relationship between the TyG index and endometriosis. Restricted cubic spline (RCS) curves explored the linear relationship, while stratified and sensitivity analyses assessed potential interactions and the robustness of the findings.

Results

The study included 2,346 women, with 176 diagnosed with endometriosis and 2,170 without. Women with endometriosis exhibited an elevated TyG index compared to those without the condition. The weighted logistic regression analysis revealed that the TyG index is an independent risk factor for endometriosis (OR = 1.58, 95% CI 1.17–2.14, p = 0.004). RCS analysis indicated a significant positive linear association between the TyG index and endometriosis, with a turning point at 8.51. Subgroup analysis indicated a stronger association in certain populations. The post-propensity score matching analysis confirmed the robustness of these findings.

Conclusion

In the U.S. population, a higher TyG index is positively and linearly associated with endometriosis prevalence. Effective management of blood glucose and lipid levels may reduce the prevalence of endometriosis.

Peer Review reports

Background

Endometriosis is a major challenge among chronic gynecological disorders, impacting 10-15% of women in their reproductive years [1, 2]. It involves endometrial tissue growing outside the uterus, leading to chronic pelvic pain and infertility [3, 4]. Despite extensive research, early diagnosis of endometriosis remains challenging due to its diverse and nonspecific symptoms. While vaginal ultrasound is effective for detecting the disease, it struggles to identify early stages. The gold standard, laparoscopically guided biopsy [5, 6], often results in a delay of 6 to 11 years in diagnosis [7], exacerbating patient suffering and disease progression. Thus, developing novel diagnostic methods and predictive biomarkers to enhance diagnostic accuracy and sensitivity is crucial for improving patients’ quality of life.

Various factors influence women’s fertility, including age, lifestyle, environmental factors, and metabolic disorders like obesity and metabolic syndrome [8,9,10]. Among these, insulin resistance (IR) emerges as a pathophysiological condition that impairs glucose metabolism in tissue cells, potentially leading to metabolic abnormalities such as hyperglycemia, hyperlipidemia, and obesity [11,12,13]. Current research suggests that insulin sensitivity is reduced in endometriosis cells, which is accompanied by an increase in the glycolytic pathway, resulting in elevated lactate levels in follicular fluid. This process induces inflammation, angiogenesis, and cell proliferation [14]. Furthermore, endometriosis has been associated with an increased risk of gestational diabetes [15], highlighting metabolic dysregulation as a significant pathological feature of endometriosis. However, traditional methods for assessing IR, like the hyperinsulinemic-euglycemic clamp (HIEC), suffer from being costly and time-consuming [16]. In recent years, the triglyceride-glucose index (TyG index) has emerged as a novel indicator for IR, demonstrating advantages in evaluating IR [17,18,19,20]. Although the TyG index has been linked to adverse clinical outcomes such as cardiovascular diseases [21,22,23], diabetes [24, 25], atherosclerosis [26, 27], and non-alcoholic fatty liver disease [28, 29], no studies have yet examined the relationship between insulin resistance markers and endometriosis.

This study aims to examine the link between the TyG index and endometriosis in reproductive-aged women, utilizing data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2006. Our objective is to assess the community-level impact of the TyG index on endometriosis risk in this population, providing new insights for clinical practice and deepening our understanding of endometriosis.

Methods

Study population

NHANES is a nationally representative survey of the United States population conducted biennially. Data collection involves structured interviews at participants’ homes and physical examinations with laboratory tests at mobile examination centers. This study is approved by the Ethics Review Committee of the National Center for Health Statistics (NCHS), and all participants provide written informed consent.

This cross-sectional study analyzed data from the NHANES database spanning 1999–2006. Initially, 41,474 participants were considered. Male participants (n = 20,264) were excluded. Additionally, participants with missing endometriosis data (n = 15,653) or those without calculable TyG index (n = 3,049) and fasting weight (n = 162) were excluded. The final analysis included 2,346 participants with complete data (Fig. 1).

Fig. 1
figure 1

Flow chart for the inclusion and exclusion criteria

Diagnosis of endometriosis

Self-reported endometriosis is diagnosed based on the “RHQ360” questionnaire administered in the Mobile Examination Center as part of NHANES. The structured questionnaire includes the following question: “Has a doctor or other health professional ever told you that you have endometriosis?” Individuals who answer “yes” are classified as self-reported endometriosis cases.

Evaluation of TyG index

The TyG index, the study’s exposure variable, was calculated from fasting triglyceride and fasting blood glucose levels using the following formula [30, 31]: TyG index = ln[(Fasting Triglycerides (mg/dL)*Fasting Glucose (mg/dL)/2].

Covariates

The study controlled for multiple factors identified in previous research, including age, race, Body mass index (BMI), poverty-income ratio (PIR), education, smoking, drinking, marital status, menarche, pregnancy, hypertension, and diabetes. The poverty-income ratio (PIR) is calculated based on the U.S. Department of Health and Human Services Family Income Poverty Guidelines [32]. Smokers were defined as individuals who had smoked 100 or more cigarettes, while drinkers were defined as those who had consumed at least 12 drinks. Hypertension and diabetes diagnoses were based on self-report.

Statistical analysis

Data were weighted using fasting weights to provide nationally representative estimates, and multiple imputation was used to estimate missing covariates. Continuous variables were reported as means (standard errors), and categorical variables as percentages (95% confidence intervals). Weighted logistic regression models were used to assess the relationship between the TyG index and endometriosis. Restricted cubic spline (RCS) was used to examine the non-linear relationship. Participants were stratified based on education level, race, alcohol consumption, smoking status, marital status, age at menarche, and pregnancy history. A weighted multivariate logistic regression on the post-propensity score matching (PSM) data assessed whether the TyG index and endometriosis association remained significant. Matching was performed at a 1:2 ratio with a caliper value of 0.02 using the nearest neighbor method. Covariates adjusted for in the PMS included age, race, BMI, PIR, education, smoking, drinking, marital status, menarche, pregnancy, hypertension, and diabetes. Statistical significance was set at P < 0.05. All analyses were conducted using R software.

Results

Characteristics of study participants

Our study included 2,346 participants, of whom 176 were diagnosed with endometriosis. Table 1 presents the descriptive characteristics of the study population by endometriosis status. Compared to participants without endometriosis, those with the condition were generally older, had a higher likelihood of having a high school education, and were more likely to be non-Hispanic white. Additionally, endometriosis patients had higher rates of smoking, alcohol consumption, and marriage. Notably, they also exhibited higher TyG index levels than participants without endometriosis.

Table 1 Weighted baseline characteristics of study participants

Connections between the TyG index and endometriosis

Table 2 shows the results of the weighted logistic regression analysis. The unadjusted model indicates a significant positive association between the TyG index and endometriosis risk (OR = 1.64; 95% CI: 1.27–2.12; P < 0.001). After adjusting for age, race, BMI, PIR, and education in Model 2, the TyG index remained significantly associated with a higher risk of endometriosis (OR = 1.59; 95% CI: 1.17–2.15; P = 0.003). This association persisted in Model 3, which adjusted for all covariates (OR = 1.58; 95% CI: 1.17–2.14; P = 0.004).

Table 2 Correlation of TyG index and endometriosis

Linear association between the TyG index and endometriosis

A restricted cubic spline model was used to evaluate the linear relationship between the TyG index and the risk of endometriosis (Fig. 2). The analysis indicated a significant positive linear association (non-linearity P = 0.24; overall P < 0.001), with a breakpoint identified at 8.51.

Fig. 2
figure 2

The nonlinear relationship between TyG index and Endometriosis. The analysis was adjusted for age, race, BMI, PIR, education, marital status, menarche, pregnancy, smoking, drinking, hypertension, and diabetes

Subgroup analysis

To examine the relationship between endometriosis and the TyG index among different subgroups, we conducted stratified and interaction analyses based on demographic characteristics (Fig. 3). Subgroup analysis revealed a stronger association between the TyG index and endometriosis in specific populations, including non-Hispanic white women, married individuals, smokers, drinkers, and those without a history of pregnancy. However, interaction analysis indicated that the relationship between the TyG index and endometriosis was not significantly modified by race, education, marital status, smoking, drinking, or pregnancy.

Fig. 3
figure 3

Stratified analysis of the relationship between TyG index and endometriosis

Sensitivity analysis

A sensitivity analysis was conducted to examine the association between the TyG index and endometriosis using propensity score matching (PSM). As shown in Table 3, after PSM, covariate differences between the two groups were controlled, and participants with endometriosis still had a significantly higher TyG index than the control group. Additionally, the weighted multivariate regression analysis in Table 4 demonstrated that the results post-PSM were consistent with those before matching, confirming that the TyG index is an independent risk factor for endometriosis.

Table 3 Weighted baseline characteristics of study participants
Table 4 Correlation of TyG index and endometriosis

Discussion

This study analyzed data from the NHANES cycles between 1999 and 2006, evaluating for the first time the relationship between the TyG index and the risk of endometriosis in 2,346 women. The results show a linear positive relationship between endometriosis risk and the TyG index. Subgroup analyses further revealed that this correlation is more pronounced in certain populations. This study underscores the importance of the TyG index in endometriosis development.

Our findings show that patients with endometriosis tend to be older and predominantly non-Hispanic white. Additionally, these patients are more likely to have a history of alcohol consumption and smoking. The delayed diagnosis of endometriosis, often occurring 6 to 11 years after the onset of symptoms [33, 34], likely contributes to the older age observed in these patients. The higher incidence in white individuals may be related to racial susceptibility. Furthermore, we observed increased rates of smoking and alcohol consumption among endometriosis patients, potentially due to the inflammatory responses [35,36,37] triggered by smoking [38, 39] and drinking [40,41,42], which may facilitate the development of endometriosis.

The link between endometriosis and insulin resistance remains unclear. The TyG index is a reliable and effective marker of insulin resistance [43,44,45] and offers significant advantages in terms of cost and convenience compared to traditional markers. Our study is the first to identify a link between the TyG index and endometriosis risk. Multivariable logistic regression analysis showed that an increase in the TyG index is significantly associated with a higher incidence of endometriosis (OR = 1.58, 95% CI 1.17–2.14, p = 0.004). Additionally, RCS curves indicated that the risk of endometriosis increases notably when the TyG index exceeds 8.51. Traditional metabolic markers, such as fasting glucose and triglyceride levels, may not fully capture metabolic health, and individuals with normal ranges may still have early metabolic syndrome symptoms. Therefore, a TyG index over 8.51 suggests potential metabolic abnormalities, warranting proactive management to reduce endometriosis risk.

While our study has highlighted this correlation, the exact mechanisms linking endometriosis and insulin resistance remain to be fully elucidated. Endometriosis is known to be associated with abnormally high estrogen levels [46,47,48]. Prolonged activation of estrogen receptors by environmental estrogens may lead to excessive insulin release, pancreatic β-cell failure, and peripheral insulin resistance [49, 50], promoting the development of ectopic endometrial tissue. This process is speculated to be closely related to inflammation. Insulin resistance may induce an inflammatory response, creating a vicious cycle that disrupts endometrial tissue function [51, 52], facilitating the attachment and spread of ectopic endometrial tissue [53, 54]. Additionally, inflammation associated with insulin resistance can cause endothelial dysfunction [55], mediating abnormal local angiogenesis and contributing to the formation and growth of ectopic endometrial lesions. Insulin resistance may also affect the balance of cell proliferation and apoptosis [56,57,58], influencing the colonization of ectopic cells. These mechanisms likely interact, collectively driving the onset and progression of endometriosis. Future research is needed to further investigate these potential mechanisms and their interactions to clarify the relationship between insulin resistance and endometriosis.

Subgroup analyses indicated that the association between endometriosis and the TyG index is more pronounced in certain populations, including non-Hispanic white women, married individuals, smokers, drinkers, and those without a history of pregnancy. These groups should particularly monitor their blood glucose and lipid levels, which may help reduce the risk of endometriosis. However, the underlying mechanisms require further clarification. Sensitivity analyses confirmed the robustness of our results.

The strengths of our study include the use of a large, nationally representative NHANES database, enhancing the generalizability of our findings to the U.S. population. Moreover, we were the first to explore the association between the TyG index and the risk of endometriosis. However, our study also has limitations. First, as a cross-sectional study, it cannot establish causality between the TyG index and endometriosis. Second, the diagnosis of endometriosis was based on self-reported data rather than the gold standard, which could introduce both recall bias and report bias, affecting the accuracy of the diagnosis. Despite adjusting for numerous confounding factors, the observed association between the TyG index and endometriosis may still be influenced by other unmeasured confounders. Therefore, more comprehensive prospective cohort studies are needed to verify whether the TyG index can serve as a reliable predictive or diagnostic marker for endometriosis.

Our study highlights the TyG index as a significant predictive marker for endometriosis, demonstrating a clear association between higher TyG index levels and an increased risk of endometriosis. This finding suggests that proactive management of blood glucose and lipid levels could be beneficial for patients at high risk of endometriosis. Regular monitoring of the TyG index in clinical practice may help in the early identification of high-risk women, allowing for timely interventions to reduce the incidence and severity of endometriosis, ultimately improving patient outcomes.

Conclusions

In summary, an elevated TyG index is linked to an increased incidence of endometriosis. Thus, proactive management of blood glucose and lipid levels might help reduce the prevalence of endometriosis. Future research should investigate whether interventions targeting the TyG index can improve clinical outcomes for endometriosis.

Data availability

The data sets produced and/or examined in this study can be found in the NHANES repository at www.cdc.gov/nchs/nhanes.

Abbreviations

TyG:

Triglyceride-Glucose

NHANES:

National Health and Nutrition Examination Survey

IR:

Insulin Resistance

HIEC:

Hyperinsulinemic-Euglycemic Clamp

BMI:

Body Mass Index

RCS:

Restricted Cubic Splines

NCHS:

National Centre for Health Statistics

OR:

Odds Ratio

PIR:

Poverty-Income Ratio

CI:

Confidence Interval

SE:

Standard Error

References

  1. Dull AM, Moga MA, Dimienescu OG, Sechel G, Burtea V, Anastasiu CV. Therapeutic approaches of Resveratrol on endometriosis via anti-inflammatory and anti-angiogenic pathways. Molecules. 2019;24(4):667.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Jiang H, Zhang X, Wu Y, Zhang B, Wei J, Li J, et al. Bioinformatics identification and validation of biomarkers and infiltrating immune cells in endometriosis. Front Immunol. 2022;13:944683.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Choi HJ, Park MJ, Kim BS, Choi HJ, Joo B, Lee KS, et al. Transforming growth factor β1 enhances adhesion of endometrial cells to mesothelium by regulating integrin expression. BMB Rep. 2017;50(8):429–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Vallvé-Juanico J, Barón C, Suárez-Salvador E, Castellví J, Ballesteros A, Gil-Moreno A, et al. Lgr5 does not vary throughout the Menstrual cycle in Endometriotic Human Eutopic Endometrium. Int J Mol Sci. 2018;20(1):22.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Cui X, Zhou S, Lin Y. Long non-coding RNA DHRS4 antisense RNA 1 inhibits ectopic endometrial cell proliferation, migration, and invasion in endometriosis by regulating microRNA-139-5p expression. Bioengineered 13(4):9792–804.

  6. Méar L, Com E, Fathallah K, Guillot L, Lavigne R, Guével B, et al. The Eutopic Endometrium Proteome in Endometriosis reveals candidate markers and molecular mechanisms of Physiopathology. Diagnostics (Basel). 2022;12(2):419.

    Article  PubMed  Google Scholar 

  7. Chapron C, Lafay-Pillet MC, Santulli P, Bourdon M, Maignien C, Gaudet-Chardonnet A, et al. A new validated screening method for endometriosis diagnosis based on patient questionnaires. EClinicalMedicine. 2022;44:101263.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Luongo FP, Passaponti S, Haxhiu A, Raeispour M, Belmonte G, Governini L, et al. Bitter Taste Receptors and endocrine disruptors: Cellular and Molecular insights from an in vitro model of human granulosa cells. Int J Mol Sci. 2022;23(24):15540.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Russo LM, Whitcomb BW, Mumford SL, Hawkins M, Radin RG, Schliep KC, et al. A prospective study of physical activity and fecundability in women with a history of pregnancy loss. Hum Reprod. 2018;33(7):1291–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Garcia-Garcia RM. Integrative Control of Energy Balance and Reproduction in females. ISRN Vet Sci. 2012;2012:121389.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Park S, Kim C, Wu X. Development and validation of an insulin Resistance Predicting Model using a machine-learning Approach in a Population-based cohort in Korea. Diagnostics (Basel). 2022;12(1):212.

    Article  CAS  PubMed  Google Scholar 

  12. Ueda-Wakagi M, Nagayasu H, Yamashita Y, Ashida AH. Green Tea ameliorates hyperglycemia by promoting the translocation of glucose transporter 4 in the skeletal muscle of Diabetic rodents. Int J Mol Sci. 2019;20(10):2436.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Khoshandam A, Razavi BM, Hosseinzadeh H. Interaction of saffron and its constituents with Nrf2 signaling pathway: a review. Iran J Basic Med Sci. 2022;25(7):789–98.

    PubMed  PubMed Central  Google Scholar 

  14. Akbaba E, Sezgin B, Edgünlü T. The role of adropin, salusin-α, netrin-1, and nesfatin-1 in endometriosis and their association with insulin resistance. Turk J Obstet Gynecol. 2021;18(3):175–80.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Salmeri N, Li Piani L, Cavoretto PI, Somigliana E, Viganò P, Candiani M. Endometriosis increases the risk of gestational diabetes: a meta-analysis stratified by mode of conception, disease localization and severity. Sci Rep. 2023;13:8099.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Yang Y, Huang X, Wang Y, Leng L, Xu J, Feng L, et al. The impact of triglyceride-glucose index on ischemic stroke: a systematic review and meta-analysis. Cardiovasc Diabetol. 2023;22:2.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Wang S, Shi J, Peng Y, Fang Q, Mu Q, Gu W, et al. Stronger association of triglyceride glucose index than the HOMA-IR with arterial stiffness in patients with type 2 diabetes: a real-world single-centre study. Cardiovasc Diabetol. 2021;20:82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Zhao X, Wang Y, Chen R, Li J, Zhou J, Liu C, et al. Triglyceride glucose index combined with plaque characteristics as a novel biomarker for cardiovascular outcomes after percutaneous coronary intervention in ST-elevated myocardial infarction patients: an intravascular optical coherence tomography study. Cardiovasc Diabetol. 2021;20:131.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Luo E, Wang D, Yan G, Qiao Y, Liu B, Hou J, et al. High triglyceride–glucose index is associated with poor prognosis in patients with acute ST-elevation myocardial infarction after percutaneous coronary intervention. Cardiovasc Diabetol. 2019;18:150.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Miao M, Zhou G, Bao A, Sun Y, Du H, Song L, et al. Triglyceride-glucose index and common carotid artery intima-media thickness in patients with ischemic stroke. Cardiovasc Diabetol. 2022;21:43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Huang R, Wang Z, Chen J, Bao X, Xu N, Guo S, et al. Prognostic value of triglyceride glucose (TyG) index in patients with acute decompensated heart failure. Cardiovasc Diabetol. 2022;21:88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Zhang W, Liu L, Chen H, Li S, Wan M, Mohammed AQ, et al. Association between the triglyceride-glucose index and the presence and prognosis of coronary microvascular dysfunction in patients with chronic coronary syndrome. Cardiovasc Diabetol. 2023;22:113.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Guo Q, Feng X, Zhang B, Zhai G, Yang J, Liu Y, et al. Influence of the triglyceride-glucose index on adverse Cardiovascular and cerebrovascular events in prediabetic patients with Acute Coronary Syndrome. Front Endocrinol (Lausanne). 2022;13:843072.

    Article  PubMed  Google Scholar 

  24. Li X, Sun M, Yang Y, Yao N, Yan S, Wang L, et al. Predictive effect of triglyceride glucose – related parameters, obesity indices, and lipid ratios for diabetes in a Chinese Population: a prospective cohort study. Front Endocrinol (Lausanne). 2022;13:862919.

    Article  PubMed  Google Scholar 

  25. Kuang M, Yang R, Huang X, Wang C, Sheng G, Xie G, et al. Assessing temporal differences in the predictive power of baseline TyG-related parameters for future diabetes: an analysis using time-dependent receiver operating characteristics. J Transl Med. 2023;21:299.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Irace C, Carallo C, Scavelli FB, De Franceschi MS, Esposito T, Tripolino C, et al. Markers of insulin resistance and carotid atherosclerosis. A comparison of the homeostasis model assessment and triglyceride glucose index. Int J Clin Pract. 2013;67(7):665–72.

    Article  CAS  PubMed  Google Scholar 

  27. Jia X, Zhu Y, Qi Y, Zheng R, Lin L, Hu C, et al. Association between triglyceride glucose index and carotid intima-media thickness in obese and nonobese adults. J Diabetes. 2022;14(9):596–605.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Beran A, Ayesh H, Mhanna M, Wahood W, Ghazaleh S, Abuhelwa Z, et al. Triglyceride-glucose index for early prediction of nonalcoholic fatty liver disease: a Meta-analysis of 121,975 individuals. J Clin Med. 2022;11(9):2666.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Lee SB, Kim MK, Kang S, Park K, Kim JH, Baik SJ, et al. Triglyceride glucose index is Superior to the Homeostasis Model Assessment of Insulin Resistance for Predicting nonalcoholic fatty liver disease in Korean adults. Endocrinol Metab (Seoul). 2019;34(2):179–86.

    Article  PubMed  Google Scholar 

  30. Yan Y, Zhou L, La R, Jiang M, Jiang D, Huang L, et al. The association between triglyceride glucose index and arthritis: a population-based study. Lipids Health Dis. 2023;22:132.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Wu S, Wu Y, Fang L, Zhao J, Cai Y, Xia W. A negative association between triglyceride glucose-body mass index and testosterone in adult males: a cross-sectional study. Front Endocrinol (Lausanne). 2023;14:1187212.

    Article  PubMed  Google Scholar 

  32. Abdalla SM, Yu S, Galea S. Trends in Cardiovascular Disease Prevalence by Income Level in the United States. JAMA Netw Open. 2020;3(9):e2018150.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Hirsch M, Davis CJ. Preoperative assessment and diagnosis of endometriosis: are we any closer? Curr Opin Obstet Gynecol. 2015;27(4):284–90.

    Article  PubMed  Google Scholar 

  34. Yang Y, Li J, Chen H, Feng W. Assessment of Risk factors Associated with severe endometriosis and establishment of Preoperative Prediction Model. Diagnostics (Basel). 2022;12(10):2348.

    Article  PubMed  Google Scholar 

  35. Liu E, Nisenblat V, Farquhar C, Fraser I, Bossuyt PM, Johnson N, et al. Urinary biomarkers for the non-invasive diagnosis of endometriosis. Cochrane Database Syst Rev. 2015;2015(12):CD012019.

    PubMed  PubMed Central  Google Scholar 

  36. Bruner-Tran KL, Yeaman GR, Crispens MA, Igarashi TM, Osteen KG. Dioxin May promote inflammation-related development of endometriosis. Fertil Steril. 2008;89(5 Suppl):1287–98.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Chadchan SB, Cheng M, Parnell LA, Yin Y, Schriefer A, Mysorekar IU, et al. Antibiotic therapy with metronidazole reduces endometriosis disease progression in mice: a potential role for gut microbiota. Hum Reprod. 2019;34(6):1106–16.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Brody JS, Steiling K. Interaction of cigarette exposure and airway epithelial cell gene expression. Annu Rev Physiol. 2011;73:437–56.

    Article  CAS  PubMed  Google Scholar 

  39. Choi WJ, Lee JW, Cho AR, Lee YJ. Dose-dependent toxic effect of cotinine-verified Tobacco Smoking on systemic inflammation in apparently healthy men and women: a Nationwide Population-based study. Int J Environ Res Public Health. 2019;16(3):503.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Andersen V, Agerstjerne L, Jensen D, Østergaard M, Saebø M, Hamfjord J, et al. The multidrug resistance 1 (MDR1) gene polymorphism G-rs3789243-A is not associated with disease susceptibility in Norwegian patients with colorectal adenoma and colorectal cancer; a case control study. BMC Med Genet. 2009;10:18.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Wang P, Guo P, Wang Y, Teng X, Zhang H, Sun L, et al. Propolis ameliorates Alcohol-Induced depressive symptoms in C57BL/6J mice by regulating intestinal mucosal barrier function and inflammatory reaction. Nutrients. 2022;14(6):1213.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Ambade A, Satishchandran A, Szabo G. Alcoholic hepatitis accelerates early hepatobiliary cancer by increasing stemness and miR-122-mediated HIF-1α activation. Sci Rep. 2016;6:21340.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Teng Z, Feng J, Dong Y, Xu J, Jiang X, Chen H, et al. Triglyceride glucose index is associated with cerebral small vessel disease burden and cognitive impairment in elderly patients with type 2 diabetes mellitus. Front Endocrinol (Lausanne). 2022;13:970122.

    Article  PubMed  Google Scholar 

  44. Hong S, Han K, Park CY. The triglyceride glucose index is a simple and low-cost marker associated with atherosclerotic cardiovascular disease: a population-based study. BMC Med. 2020;18:361.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Kim B, Kim G, Lee Y, Taniguchi K, Isobe T, Oh S. Triglyceride–glucose index as a potential Indicator of Sarcopenic obesity in older people. Nutrients. 2023;15(3):555.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Sapkota Y, Steinthorsdottir V, Morris AP, Fassbender A, Rahmioglu N, De Vivo I, et al. Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism. Nat Commun. 2017;8:15539.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Bulun SE, Monsavais D, Pavone ME, Dyson M, Xue Q, Attar E, et al. Role of Estrogen Receptor-β in endometriosis. Semin Reprod Med. 2012;30(1):39–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Hu JX, Helleberg M, Jensen AB, Brunak S, Lundgren J. A Large-Cohort, Longitudinal Study determines Precancer Disease routes across different Cancer types. Cancer Res. 2019;79(4):864–72.

    Article  CAS  PubMed  Google Scholar 

  49. Wang Z, Mínguez-Alarcón L, Williams PL, Bellavia A, Ford JB, Keller M, et al. Perinatal urinary benzophenone-3 concentrations and glucose levels among women from a fertility clinic. Environ Health. 2020;19:45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Yan D, Jiao Y, Yan H, Liu T, Yan H, Yuan J. Endocrine-disrupting chemicals and the risk of gestational diabetes mellitus: a systematic review and meta-analysis. Environ Health. 2022;21:53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Alemi H, Khaloo P, Rabizadeh S, Mansournia MA, Mirmiranpour H, Salehi SS, et al. Association of extracellular heat shock protein 70 and insulin resistance in type 2 diabetes; independent of obesity and C-reactive protein. Cell Stress Chaperones. 2019;24(1):69–75.

    Article  CAS  PubMed  Google Scholar 

  52. Ross AB, Shertukde SP, Livingston Staffier K, Chung M, Jacques PF, McKeown NM. The relationship between whole-grain intake and measures of Cognitive decline, Mood, and Anxiety—A systematic review. Adv Nutr. 2023;14(4):652–70.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Riley CF, Moen MH, Videm V. Inflammatory markers in endometriosis: reduced peritoneal neutrophil response in minimal endometriosis. Acta Obstet Gynecol Scand. 2007;86(7):877–81.

    Article  PubMed  Google Scholar 

  54. Jafari R, Taghavi SA, Amirchaghmaghi E, Yazdi RS, Karimian L, Ashrafi M, et al. Detailed investigation of downstream TLR Signaling in the follicular cells of women with endometriosis. J Reprod Infertil. 2020;21(4):231–9.

    PubMed  PubMed Central  Google Scholar 

  55. Kamalesh M. Heart failure in diabetes and related conditions. J Card Fail. 2007;13(10):861–73.

    Article  PubMed  Google Scholar 

  56. Medarova Z, Bonner-Weir S, Lipes M, Moore A. Imaging beta-cell death with a near-infrared probe. Diabetes. 2005;54(6):1780–8.

    Article  CAS  PubMed  Google Scholar 

  57. Nam SY. Obesity-related Digestive diseases and their pathophysiology. Gut Liver. 2017;11(3):323–34.

    Article  CAS  PubMed  Google Scholar 

  58. Valadez-Bustos N, Escamilla-Silva EM, García-Vázquez FJ, Gallegos-Corona MA, Amaya-Llano SL, Ramos-Gómez M. Oral administration of Microencapsulated B. Longum BAA-999 and Lycopene modulates IGF-1/IGF-1R/IGFBP3 protein expressions in a colorectal murine model. Int J Mol Sci. 2019;20(17):4275.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We sincerely thank all the participants and staff involved in the NHANES, as well as the NCHS, for their valuable contributions. Special appreciation also goes to Zhang Jing for his work on the nhanesR package.

Funding

This study was funded by Shunde Hospital, Southern Medical University (grant numbers SRSP2023021 and SRSP2023001).

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Contributions

Y Cao & Q Yang: Draft writing, project conception and design, data acquisition, analysis, and interpretation.QQ Mai & JX Wuliu: Data acquisition and analysis.KX Deng: Manuscript review-editing and supervision.All authors have reviewed and approved the final manuscript and consent to the author order.

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Correspondence to Kaixian Deng.

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Ethics approval and consent to participate

This study followed the principles set forth in the Declaration of Helsinki and was approved by the Ethics Review Board of the National Center for Health Statistics (NCHS). Informed written consent was obtained from all participants.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Cao, Y., Yang, Q., Mai, Q. et al. Relationship between triglyceride-glucose index and endometriosis: a cross-sectional analysis. BMC Women's Health 24, 447 (2024). https://doi.org/10.1186/s12905-024-03287-6

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