METHODS: We used the TyG index as a surrogate measure for insulin resistance. Fasting triglycerides and fasting plasma glucose were measured at the baseline visit in 141 243 individuals aged 35-70 years from 22 countries in the Prospective Urban Rural Epidemiology (PURE) study. The TyG index was calculated as Ln (fasting triglycerides [mg/dL] x fasting plasma glucose [mg/dL]/2). We calculated hazard ratios (HRs) using a multivariable Cox frailty model with random effects to test the associations between the TyG index and risk of cardiovascular diseases and mortality. The primary outcome of this analysis was the composite of mortality or major cardiovascular events (defined as death from cardiovascular causes, and non-fatal myocardial infarction, or stroke). Secondary outcomes were non-cardiovascular mortality, cardiovascular mortality, all myocardial infarctions, stroke, and incident diabetes. We also did subgroup analyses to examine the magnitude of associations between insulin resistance (ie, the TyG index) and outcome events according to the income level of the countries.
FINDINGS: During a median follow-up of 13·2 years (IQR 11·9-14·6), we recorded 6345 composite cardiovascular diseases events, 2030 cardiovascular deaths, 3038 cases of myocardial infarction, 3291 cases of stroke, and 5191 incident cases of type 2 diabetes. After adjusting for all other variables, the risk of developing cardiovascular diseases increased across tertiles of the baseline TyG index. Compared with the lowest tertile of the TyG index, the highest tertile (tertile 3) was associated with a greater incidence of the composite outcome (HR 1·21; 95% CI 1·13-1·30), myocardial infarction (1·24; 1·12-1·38), stroke (1·16; 1·05-1·28), and incident type 2 diabetes (1·99; 1·82-2·16). No significant association of the TyG index was seen with non-cardiovascular mortality. In low-income countries (LICs) and middle-income countries (MICs), the highest tertile of the TyG index was associated with increased hazards for the composite outcome (LICs: HR 1·31; 95% CI 1·12-1·54; MICs: 1·20; 1·11-1·31; pinteraction=0·01), cardiovascular mortality (LICs: 1·44; 1·15-1·80; pinteraction=0·01), myocardial infarction (LICs: 1·29; 1·06-1·56; MICs: 1·26; 1·10-1·45; pinteraction=0·08), stroke (LICs: 1·35; 1·02-1·78; MICs: 1·17; 1·05-1·30; pinteraction=0·19), and incident diabetes (LICs: 1·64; 1·38-1·94; MICs: 2·68; 2·40-2·99; pinteraction <0·0001). In contrast, in high-income countries, higher TyG index tertiles were only associated with an increased hazard of incident diabetes (2·95; 2·25-3·87; pinteraction <0·0001), but not of cardiovascular diseases or mortality.
INTERPRETATION: The TyG index is significantly associated with future cardiovascular mortality, myocardial infarction, stroke, and type 2 diabetes, suggesting that insulin resistance plays a promoting role in the pathogenesis of cardiovascular and metabolic diseases. Potentially, the association between the TyG index and the higher risk of cardiovascular diseases and type 2 diabetes in LICs and MICs might be explained by an increased vulnerability of these populations to the presence of insulin resistance.
FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).
METHODOLOGY: The Cochrane Central Register of Controlled Trials (CENTRAL) and PubMed (1985-January 2022) and trial registries for relevant randomised clinical trials were used. Relevant and published randomised clinical trials were reviewed and evaluated. The primary outcomes were anthropometry measurements, which were weight, waist circumference, body mass index (BMI), and body fat percentages. The secondary outcomes were changes in quality of life, psychological impact, lipid profile measurement, presence of adverse events, and changes in blood pressure and blood glucose. We assessed the data for risk of bias, heterogeneity, sensitivity, reporting bias, and quality of evidence.
RESULTS: 15 studies are included, involving 1161 participants. The analysis performed is based on three comparisons. For the first comparison between yoga and control, yoga reduces the waist circumference (MD -0.84, 95% CI [-5.12 to 3.44]), while there is no difference in body weight, BMI, or body fat percentages. In the second comparison between yoga and calorie restriction, yoga reduces body weight (MD -3.47, 95% CI [-6.20 to -0.74]), while there is no difference in waist circumference, BMI, or body fat percentage. In the third comparison between yoga and exercise, yoga reduces the body weight (MD -7.58, 95% CI [-11.51 to -3.65]), while there is no difference in waist circumference or BMI. For the secondary outcomes, yoga intervention reduces total cholesterol (MD -17.12, 95% CI [-32.24 to -2.00]) and triglycerides (MD -21.75, 95% CI [-38.77 to -4.73]) compared to the control group, but there is no difference compared to the calorie restriction and exercise group. There is no difference in the rest of the outcomes, which are LDL, HDL, quality of life, psychological impact, adverse events, blood pressure, and blood glucose. However, findings are not robust due to a high risk of bias and low-quality evidence.
CONCLUSION: From our review, there were methodological drawbacks and very low to moderate quality of evidence across all comparisons, and hence, it is inconclusive to say that yoga can significantly improve anthropometric parameters. More well-designed trials are needed to confirm and support the beneficial effects of yoga.
METHODS: The study employed a bidirectional MR analysis with two samples, utilizing a freely accessible genome-wide association study (GWAS). Furthermore, the primary analysis employed the inverse variance weighted (IVW) method. To determine whether the lipid profiles were associated with periodontitis, a variety of sensitivity analyses (including MR-Egger regression, MR-PRESSO, and weighted median), as well as multivariable MR, were employed.
RESULTS: MR analysis performed by IVW did not reveal any relationship between periodontitis and low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides (TG), or total cholesterol (TC). It was also found that LDL, HDL, TG, and TC were not associated to periodontitis. Furthermore, the MR estimations exhibited consistency with other MR sensitivity and multivariate MR (MVMR) analyses. These results show that the correlation between serum lipid levels and periodontitis could not be established.
CONCLUSION: The finding indicates a negligible link between periodontitis and serum lipid levels were identified, despite previous observational studies reporting a link between periodontitis and serum lipid levels.
Methods: This case-control study was carried out on 113 patients with PV and 100 healthy controls. Total cholesterol, high-density lipoprotein (HDL) and triglycerides (TG) levels were measured and low-density lipoprotein (LDL), non-HDL cholesterol (non-HDL-C) and atherogenic index of plasma (AIP) were calculated. Chi-squared test and independent Student t-test (or their alternatives) were used for group comparison.
Results: The mean age and BMI of patients and controls were 47.7 ± 14.5 and 28 ± 6.2 and, 44.5 ± 18.5 and 25.5 ± 5.1, respectively. Total cholesterol, LDL, HDL, non-HDL-C and TG were statistically different between the two groups (P values < 0.001; < 0.001; < 0.001; < 0.001 and 0.021, respectively). However, AIP was not significantly different (P-value = 0.752).
Conclusion: The serum lipid profile was significantly higher in PV patients compared to healthy controls. Therefore, PV patients may be more prone to develop atherosclerosis and this finding can be important in the overall management of these patients.
OBJECTIVE: (i) To examine the triglyceride glucose (TyG) index (Ln[fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]) and its relationship to in vivo insulin sensitivity in obese adolescents (OB) along the spectrum of glucose tolerance and (ii) to compare TyG index with triglyceride/high-density lipoprotein TG/HDL and 1/fasting insulin (1/IF ), other surrogates of insulin sensitivity.
PATIENTS AND DESIGN: Cross-sectional data in 225 OB with normal glucose tolerance (NGT), prediabetes (preDM), and type 2 diabetes (T2DM) who had a 3-h hyperinsulinemic-euglycemic clamp and fasting lipid measurement.
RESULTS: Insulin-stimulated glucose disposal (Rd) declined significantly across the glycemic groups from OB-NGT to OB-preDM to OB-T2DM with a corresponding increase in TyG index (8.3 ± 0.5, 8.6 ± 0.5, 8.9 ± 0.6, p