Evaluation of the predictive value of different dietary antioxidant capacity assessment methods on healthy and unhealthy phenotype in overweight and obese women.

Purpose: Predictive value of different dietary antioxidant capacity assessment methods on healthy and unhealthy phenotypes in overweight and obese women is still unclear. This study aimed to evaluate the predictive value of different dietary antioxidant capacity assessment methods on healthy and unhealthy phenotypes in overweight and obese women. Methods: A total of 290 overweight and obese women were included in this cross-sectional study. Food intake was assessed using a semi-quantitative food frequency questionnaire (FFQ). Dietary antioxidant capacity was calculated using valid databases of antioxidant value. The receiver operating characteristic (ROC) curve method was used to evaluate the predictive value of antioxidant capacity indices, including dietary antioxidant quality score (DAQS), ferric reducing ability of plasma (FRAP), total reactive antioxidant potential (TRAP), and trolox equivalent antioxidant capacity (TEAC). Results: The results showed that the highest area under the ROC curve for predicting metabolically healthy obesity (MHO) belongs to the TRAP method (area under the curve (AUC) = 0.53). In addition, this method had the highest AUC for predicting inflammatory marker of C-reactive protein (hs-CRP) (AUC = 0.54) and the index of the homeostatic model assessment for insulin resistance (HOMA-IR) (AUC = 0.59). The highest AUC for triglyceride prediction was related to the DAQS method (AUC = 0.56). Moreover, a significant correlation of FRAP (r = -0.15, P = 0.02), TRAP (r = -0.19, P < 0.001), TEAC (r = -0.18, P< 0.001) with HOMA-IR was reached. Conclusion: The findings of this study show that the best way to predict the status of MHO is TRAP method. This method is also the best predictor of hs-CRP and HOMA-IR. DAQS method is the best predictor for TG.

Effect of orlistat on serum uric acid level in adults: A systematic review and meta-analysis of randomised controlled trials.

OBJECTIVE: Hyperuricemia increases the risk of gout and cardiovascular diseases. Obesity increases the risk of hyperuricemia while weight loss (>5 kg) has been reported to decrease urate. The effects of orlistat on serum uric acid (SUA) are still controversial. The aim of this meta-analysis was to evaluate the influence of orlistat on SUA levels in adults. METHODS: Relevant studies, published up to May 2020, were searched systematically through PubMed/Medline, Scopus and Google Scholar. All relevant randomised controlled clinical trials were included. Meta-analysis was performed using random-effect model. Subgroup analysis, sensitivity analysis and meta-regression were also carried out. RESULTS: Overall 7 trials (9 datasets) that enrolled 1786 subjects were included. Orlistat showed in a significant change in SUA level (Difference in means: -17.661 µmol, 95% CI: -31.615 to -3.707, P = .01). A low heterogeneity observed across the studies (I2 = 25.119%). After categorising studies on the basis of duration and sample size, the effect of orlistat on SUA was significant. The results of meta-regression were showed that significant relationships were not found between orlistat and SUA in the duration of intervention. CONCLUSION: We found a significant reduction in SUA following orlistat therapy in adults.