Background Since the triglyceride glucose (TyG) index can reflect insulin resistance, it has been proven to be an efficient predictor of glycolipid-metabolism-related diseases. Therefore, this study aimed to investigate the predictive value of the TyG index for visceral obesity (VO) and body fat distribution in patients with type 2 diabetes mellitus (T2DM). Methods Abdominal adipose tissue characteristics in patients with T2DM, including visceral adipose area (VAA), subcutaneous adipose area (SAA), VAA-to-SAA ratio (VSR), visceral adipose density (VAD), and subcutaneous adipose density (SAD), were obtained through analyses of computed tomography images at the lumbar 2/3 level. VO was diagnosed according to the VAA (> 142 cm2 for males and > 115 cm2 for females). Logistic regression was performed to identify independent factors of VO, and receiver operating characteristic (ROC) curves were used to compare the diagnostic performance according to the area under the ROC curve (AUC). Results A total of 976 patients were included in this study. VO patients showed significantly higher TyG values than non-VO patients in males (9.74 vs. 8.88) and females (9.59 vs. 9.01). The TyG index showed significant positive correlations with VAA, SAA, and VSR and negative correlations with VAD and SAD. The TyG index was an independent factor for VO in both males (odds ratio [OR] = 2.997) and females (OR = 2.233). The TyG index ranked second to body mass index (BMI) for predicting VO in male (AUC = 0.770) and female patients (AUC = 0.720). Patients with higher BMI and TyG index values showed a significantly higher risk of VO than the other patients. TyG-BMI, the combination index of TyG and BMI, showed significantly higher predictive power than BMI for VO in male patients (AUC = 0.879 and 0.835, respectively) but showed no significance when compared with BMI in female patients (AUC = 0.865 and 0.835, respectively). Conclusions . TyG is a comprehensive indicator of adipose volume, density, and distribution in patients with T2DM and is a valuable predictor for VO in combination with anthropometric indices, such as BMI.
Aims Glucagon‑like peptide 1 receptor agonist (GLP-1RA) treatment can improve adipose distribution. We performed this meta-analysis to investigate whether GLP-1RAs preferentially reduce visceral adipose tissue (VAT) over subcutaneous adipose tissue (SAT) in patients with type 2 diabetes. Materials and methods We searched MEDLINE and the Cochrane Library for randomised controlled trials explicitly reporting changes in VAT and SAT. A random-effects model was performed to estimate the weighted mean difference (MD) for VAT and SAT. Heterogeneity among the studies was assessed using I2 statistics, and publication bias was assessed using Egger’s tests. Meta-regression was performed to identify the correlation between changes in adipose tissues and changes in body weight and glycated haemoglobin level. Results Ten trials with 924 patients were enrolled in the meta-analysis. GLP-1RA treatment led to similar absolute area (cm2) reductions in VAT (MD -21.13 cm2, 95% CI [-29.82, -12.44]) and SAT (MD -22.89 cm2, 95% CI [-29.83, -15.95]). No significant publication bias was detected, and this result was stable in the sensitivity and subgroup analyses. Moreover, GLP-1RA treatment resulted in a greater reduction in VAT and SAT in the subgroup with a greater reduction in body weight. The absolute area reduction in VAT was significantly correlated with the reduction in body weight (r = 6.324, p = 0.035). Conclusions GLP-1RA treatment leads to significant and similar absolute reductions in VAT and SAT, and the reduction in adipose tissues may be correlated with the reduction in body weight.
ObjectiveTo evaluate the association between the growth hormone (GH)/insulin-like growth factor-1 (IGF-1) axis and muscle density in children and adolescents of short stature.MethodsParticipants were children and adolescents of short stature hospitalized in the Affiliated Hospital of Jining Medical University between January 2020 and June 2021. All participants had CT scan images available. We performed an analysis of the images to calculate the muscle density or skeletal muscle attenuation (SMA), skeletal muscle index (SMI), and fat mass index (FMI). Bioelectrical impedance analysis (BIA) was used to ensure that chest CT is a credible way of evaluating body composition.ResultsA total of 297 subjects were included with the mean age of 10.00 ± 3.42 years, mean height standard deviation score (SDS) of -2.51 ± 0.53, and mean IGF-1 SDS of -0.60 ± 1.07. The areas of muscle and fat tissues at the fourth thoracic vertebra level in the CT images showed strong correlation with the total weights of the participants (R2 = 0.884 and 0.897, respectively). The peak of GH was negatively associated with FMI (r = - 0.323, P <.01) and IGF-1 SDS was positively associated with SMI (r = 0.303, P <.01). Both the peak GH and IGF-1 SDS were positively associated with SMA (r = 0.244, P <.01 and r = 0.165, P <.05, respectively). Multiple stepwise linear regression analysis demonstrated that the GH peak was the predictor of FMI (β = - 0.210, P < .01), the IGF-1 SDS was the predictor of SMI (β = 0.224, P < .01), and both the peak GH and IGF-1 SDS were predictors of SMA (β = 0.180, P < .01 and β = 0.222, P < .01).ConclusionsA chest CT scan is a credible method of evaluating body composition in children and adolescents of short stature. In these patients, peak GH and IGF-1 SDS are independent predictors of muscle density and the GF/IGF-1 axis may regulate body composition through complex mechanisms.
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