Clinical usefulness of lipid ratios, visceral adiposity indicators, and the triglycerides and glucose index as risk markers of insulin resistance

et al. 2016

Sci Rep

Most previous studies on metabolic syndrome (MetS) examined urban and high income settings. We thus investigated the prevalence of MetS among a multi-ethnic population living in a low income rural area and explored the use of visceral adiposity and anthropometric indicators to identify men and women with MetS. We recruited 10,029 individuals of nomadic Kazakhs, rural Uyghur and Han residents in Xinjiang, China. MetS was defined by the Joint Interim Statement criteria. The receiver operating characteristic curve (ROC) was used to compare the area under the ROC curve (AUC) of each index. The age-adjusted prevalence of MetS was 21.8%. The visceral adiposity index (VAI), lipid accumulation product (LAP), body adiposity index (BAI) and the waist-to-height ratio (WHtR) were significantly associated with MetS, independent of ethnic, age, and other covariates. The AUC of VAI, LAP and WHtR were all greater than 0.7, and the LAP was the index that most accurately identified MetS status in men (AUC = 0.853) and women (AUC = 0.817), with the optimal cut-offs of 34.7 and 27.3, respectively. In conclusion, the prevalence of MetS in low income rural adults of Xinjiang was high and the LAP was an effective indicator for the screening of MetS.

Section: Discussioncontrasting

confidence: 99%

Visceral Adiposity and Anthropometric Indicators as Screening Tools of Metabolic Syndrome among Low Income Rural Adults in Xinjiang

Guo

et al. 2016

Sci Rep

“…Hypertriglyceridemia is a major metabolic abnormality associated with the presence of NAFLD. [21] Furthermore, we observed in this study that the TyG index, including lipid parameter and proposed as a surrogate marker for insulin resistance, [22,31] was increased in both MetS and NAFLD patients and was associated with a higher risk for the diseases, which indicating the close relationship between lipid metabolism, insulin resistance, and NAFLD. In accordance, the association between TyG and fatty liver has also been demonstrated in previous studies.…”

Section: Discussionmentioning

confidence: 82%

Combined effect of obesity and uric acid on nonalcoholic fatty liver disease and hypertriglyceridemia

et al. 2017

Medicine

Self Cite

Hyperuricemia is associated with metabolic syndrome (MetS), but the association is often confounded by the shared background of obesity. We sought to explore the modifying effects of obesity on the association between uric acid (UA), MetS components, and nonalcoholic fatty liver disease (NAFLD).We conducted a cross-sectional study in a Chinese population of 10,069 participants aged ≥20 years. Multiplicative interaction between obesity (BMI ≥25 kg/m2) and elevated UA was assessed using an interaction term in a logistic regression analysis. The presence of additive interaction was assessed based on the relative excess risk due to the interaction (RERI) and the attributable proportion due to the interaction (AP).There was no evidence of a multiplicative interaction between obesity and elevated UA on MetS components and NAFLD. However, there was a strong additive interaction between obesity and elevated UA with regard to NAFLD (RERI of 6.47 [95% CI 3.42–9.53] for men and 5.87 [1.55–10.19] for women) and hypertriglyceridemia (RERI of 1.38 [0.57–2.20] for men and 1.38 [0.08–2.67] for women). In addition, 42% and 36% of the increased odds of NAFLD for men and women, respectively, can be explained by an interaction between obesity and elevated UA (AP of 0.42 [95% CI (0.30–0.54)] for men and 0.36 [0.17–0.55] for women). Similarly, the interaction accounted for 27% and 26% of the increased risk of hypertriglyceridemia for men and women (AP of 0.27 [0.14–0.41] for men and 0.26 [0.06–0.47] for women).In this population, obesity and elevated UA synergistically interacted to increase the risk of NAFLD and hypertriglyceridemia.

“…[20,31] As it was derived from TG and FPG, these are 2 crucial metabolic variables that are altered in the fatty liver and highly correlated with insulin resistance. [16,17] It is believed that insulin resistance and its related metabolic risk factors still play an important role in the development of NAFLD in nonobese subjects as noted in the development of obese-associated NAFLD. Kwon et al [22] suggested that nonobese NAFLD even had a stronger association with metabolic disorders than obese NAFLD.…”

Section: Discussionmentioning

confidence: 99%

“…[16,17] Previous studies also reported that the TyG index was useful in identifying various metabolic abnormalities associated with insulin resistance, such as type 2 diabetes, [18] the metabolically obese but normal weight phenotype, [19] and NAFLD. [20] In addition, a recent study revealed that TyG combined with body mass index (BMI) was a more efficient marker for insulin resistance than other indicators.…”

Section: Introductionmentioning

confidence: 99%

Triglyceride glucose-body mass index is effective in identifying nonalcoholic fatty liver disease in nonobese subjects

et al. 2017

Medicine

Self Cite

Nonalcoholic fatty liver disease (NAFLD) is an increasingly common condition that is highly correlated with obesity; however, it is not uncommon among nonobese individuals. Triglyceride (TG) and glucose index combined with body mass index (TyG-BMI) has been proposed as a favorable marker of insulin resistance. We sought to investigate the effectiveness of TyG-BMI in identifying NAFLD in nonobese subjects.We conducted a cross-sectional study in a nonobese (BMI <25.0 kg/m2) Chinese population (N = 6809) of adults who underwent health examinations, including abdominal ultrasonography.The prevalence of ultrasonography-detected NAFLD was 23.9% in nonobese subjects. After adjusting for potential confounders, every 1-standard deviation increase in TyG-BMI had an odds ratio (OR) of 3.4 [95% confidence interval (95% CI), 3.0–3.9] for NAFLD. Compared with the lowest quartile of TyG-BMI, multivariable-adjusted ORs were 2.4 (1.6–3.6), 6.4 (4.2–9.7), and 15.3 (9.8–23.9) for those in the second, third, and fourth quartile, respectively. According to the receiver operating characteristic curve analysis, TyG-BMI was effective in diagnosing patients with NAFLD with an area under the curve of 0.835 (95% CI, 0.824–0.845). In comparison, TyG-BMI was superior to its components, including TyG, BMI, TG, and fasting plasma glucose, for identifying nonobese subjects at risk for NAFLD.In this study, the prevalence of NAFLD was over one-fifth in the nonobese population. TyG-BMI was an effective marker to detect NAFLD in nonobese subjects.