Relationship of triglyceride-glucose index and its derivatives with blood pressure abnormalities in adolescents: an analysis based on a restricted cubic spline model
TIAN Mei, MA Xiao-Yan, TONG Ling-Ling, JIA Lei-Na, DING Wen-Qing
School of Public Health, Ningxia Medical University/Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan 750004, China (Ding W-Q, Email: dwqdz@163.com)
Abstract Objective To explore the relationship of triglyceride-glucose index (TyG), triglyceride-glucose-body mass index (TyG-BMI), and triglyceride-glucose-waist circumference index (TyG-WC) with blood pressure abnormalities in adolescents, providing theoretical basis for the prevention and control of hypertension in adolescents. Methods A stratified cluster sampling method was used to select 1 572 adolescents aged 12 to 18 years in Yinchuan City for questionnaire surveys, physical measurements, and laboratory tests. Logistic regression analysis and restricted cubic spline analysis were employed to examine the relationship of TyG, TyG-BMI, and TyG-WC with blood pressure abnormalities in adolescents. Results Multivariable logistic regression analysis revealed that after adjusting for confounding factors, the groups with the highest quartile of TyG, TyG-BMI, and TyG-WC had 1.48 times (95%CI: 1.07-2.04), 3.71 times (95%CI: 2.67-5.15), and 4.07 times (95%CI: 2.89-5.73) higher risks of blood pressure abnormalities compared to the groups with the lowest quartile, respectively. Moreover, as the levels of TyG, TyG-BMI, and TyG-WC increased, the risk of blood pressure abnormalities gradually increased (P<0.05). A non-linear dose-response relationship was observed between TyG-BMI and the risk of blood pressure abnormalities (Poverall trend<0.001, Pnon-linearity=0.002). Linear dose-response relationships were found between TyG and the risk of blood pressure abnormalities (Poverall trend<0.001, Pnon-linearit =0.232), and between TyG-WC and the risk of blood pressure abnormalities (Poverall trend<0.001, Pnon-linearity=0.224). Conclusions Higher levels of TyG and its derivatives are associated with an increased risk of blood pressure abnormalities in adolescents, with linear or non-linear dose-response relationships.
TIAN Mei,MA Xiao-Yan,TONG Ling-Ling et al. Relationship of triglyceride-glucose index and its derivatives with blood pressure abnormalities in adolescents: an analysis based on a restricted cubic spline model[J]. CJCP, 2024, 26(1): 54-61.
TIAN Mei,MA Xiao-Yan,TONG Ling-Ling et al. Relationship of triglyceride-glucose index and its derivatives with blood pressure abnormalities in adolescents: an analysis based on a restricted cubic spline model[J]. CJCP, 2024, 26(1): 54-61.
Wang L, Song L, Liu B, et al. Trends and status of the prevalence of elevated blood pressure in children and adolescents in China: a systematic review and meta-analysis[J]. Curr Hypertens Rep, 2019, 21(11): 88. PMID: 31599364. DOI: 10.1007/s11906-019-0992-1.
Yang L, Magnussen CG, Yang L, et al. Elevated blood pressure in childhood or adolescence and cardiovascular outcomes in adulthood: a systematic review[J]. Hypertension, 2020, 75(4): 948-955. PMID: 32114851. DOI: 10.1161/HYPERTENSIONAHA.119.14168.
Bala C, Gheorghe-Fronea O, Pop D, et al. The association between six surrogate insulin resistance indexes and hypertension: a population-based study[J]. Metab Syndr Relat Disord, 2019, 17(6): 328-333. PMID: 31034338. DOI: 10.1089/met.2018.0122.
Zeng ZY, Liu SX, Xu H, et al. Association of triglyceride glucose index and its combination of obesity indices with prehypertension in lean individuals: a cross-sectional study of Chinese adults[J]. J Clin Hypertens (Greenwich), 2020, 22(6): 1025-1032. PMID: 32442359. PMCID: PMC8029919. DOI: 10.1111/jch.13878.
Falkner B, Daniels SR. Summary of the fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents[J]. Hypertension, 2004, 44(4): 387-388. PMID: 15353515. DOI: 10.1161/01.HYP.0000143545.54637.af.
Simental-Mendía LE, Rodríguez-Morán M, Guerrero-Romero F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects[J]. Metab Syndr Relat Disord, 2008, 6(4): 299-304. PMID: 19067533. DOI: 10.1089/met.2008.0034.
Khamseh ME, Malek M, Abbasi R, et al. Triglyceride glucose index and related parameters (triglyceride glucose-body mass index and triglyceride glucose-waist circumference) identify nonalcoholic fatty liver and liver fibrosis in individuals with overweight/obesity[J]. Metab Syndr Relat Disord, 2021, 19(3): 167-173. PMID: 33259744. DOI: 10.1089/met.2020.0109.
Li X, Sun M, Yang Y, et al. Predictive effect of triglyceride glucose-related parameters, obesity indices, and lipid ratios for diabetes in a Chinese population: a prospective cohort study[J]. Front Endocrinol (Lausanne), 2022, 13: 862919. PMID: 35432185. PMCID: PMC9007200. DOI: 10.3389/fendo.2022.862919.
Rattanatham R, Tangpong J, Chatatikun M, et al. Assessment of eight insulin resistance surrogate indexes for predicting metabolic syndrome and hypertension in Thai law enforcement officers[J]. PeerJ, 2023, 11: e15463. PMID: 37273533. PMCID: PMC10234272. DOI: 10.7717/peerj.15463.
Yuan Y, Sun W, Kong X. Comparison between distinct insulin resistance indices in measuring the development of hypertension: the China health and nutrition survey[J]. Front Cardiovasc Med, 2022, 9: 912197. PMID: 36277749. PMCID: PMC9582523. DOI: 10.3389/fcvm.2022.912197.
Wang A, Tian X, Zuo Y, et al. Change in triglyceride-glucose index predicts the risk of cardiovascular disease in the general population: a prospective cohort study[J]. Cardiovasc Diabetol, 2021, 20(1): 113. PMID: 34039351. PMCID: PMC8157734. DOI: 10.1186/s12933-021-01305-7.
Chen L, He L, Zheng W, et al. High triglyceride glucose-body mass index correlates with prehypertension and hypertension in east Asian populations: a population-based retrospective study[J]. Front Cardiovasc Med, 2023, 10: 1139842. PMID: 37180805. PMCID: PMC10166815. DOI: 10.3389/fcvm.2023.1139842.
Koay YC, Coster ACF, Chen DL, et al. Metabolomics and lipidomics signatures of insulin resistance and abdominal fat depots in people living with obesity[J]. Metabolites, 2022, 12(12): 1272. PMID: 36557310. PMCID: PMC9781703. DOI: 10.3390/metabo12121272.
Trouwborst I, Bowser SM, Goossens GH, et al. Ectopic fat accumulation in distinct insulin resistant phenotypes; targets for personalized nutritional interventions[J]. Front Nutr, 2018, 5: 77. PMID: 30234122. PMCID: PMC6131567. DOI: 10.3389/fnut.2018.00077.
Esser N, Legrand-Poels S, Piette J, et al. Inflammation as a link between obesity, metabolic syndrome and type 2 diabetes[J]. Diabetes Res Clin Pract, 2014, 105(2): 141-150. PMID: 24798950. DOI: 10.1016/j.diabres.2014.04.006.
Le Brocq M, Leslie SJ, Milliken P, et al. Endothelial dysfunction: from molecular mechanisms to measurement, clinical implications, and therapeutic opportunities[J]. Antioxid Redox Signal, 2008, 10(9): 1631-1674. PMID: 18598143. DOI: 10.1089/ars.2007.2013.
Gu Q, Hu X, Meng J, et al. Associations of triglyceride-glucose index and its derivatives with hyperuricemia risk: a cohort study in Chinese general population[J]. Int J Endocrinol, 2020, 2020: 3214716. PMID: 33014043. PMCID: PMC7519459. DOI: 10.1155/2020/3214716.
Cheng Y, Fang Z, Zhang X, et al. Association between triglyceride glucose-body mass index and cardiovascular outcomes in patients undergoing percutaneous coronary intervention: a retrospective study[J]. Cardiovasc Diabetol, 2023, 22(1): 75. PMID: 36997935. PMCID: PMC10064664. DOI: 10.1186/s12933-023-01794-8.
Rosano GM, Aversa A, Vitale C, et al. Chronic treatment with tadalafil improves endothelial function in men with increased cardiovascular risk[J]. Eur Urol, 2005, 47(2): 214-220; discussion 220-222. PMID: 15661417. DOI: 10.1016/j.eururo.2004.10.002.