METHODS: The systematic review and meta-analysis were performed according to the previously published protocol. The PubMed, Web of Sciences, and Scopus databases were meticulously searched for relevant data, without time or language restriction, up to June 1, 2017. All clinical trials which assessed the effect of Se supplementation on antioxidant markers, including oxidative stress index (OSI), antioxidant potency composite (APC) index, plasma malonaldehyde (MDA), total antioxidant capacity (TAC), antioxidant enzymes (superoxide dismutase (SOD), glutathione peroxidase (GPX), catalase (CAT)), and total antioxidant plasma (TAP), were included. The effect of Se supplementation on antioxidant markers was assessed using standardized mean difference (SMD) and 95% confidence interval (CI). The random-effect meta-analysis method was used to estimate the pooled SMD.
RESULTS: In total, 13 studies which assessed the effect of Se supplementation on antioxidant markers were included. The random-effect meta-analysis method showed that Se supplementation significantly increased GPX (SMD = 0.54; 95% CI = 0.21-0.87) and TAC (SMD = 0.39, 95% CI = 0.13, 0.66) levels and decreased MDA levels (SMD = - 0.54, 95% CI = - 0.78, - 0.30). The effect of Se supplementation on other antioxidant markers was not statistically significant (P > 0.05).
CONCLUSION: The findings showed that Se supplementation might reduce oxidative stress by increasing TAC and GPX levels and decreasing serum MDA, both of which are crucial factors for reduction of oxidative stress.
OBJECTIVE: To develop international WC percentile cutoffs for children and adolescents with normal weight based on data from 8 countries in different global regions and to examine the relation with cardiovascular risk.
DESIGN AND SETTING: We used pooled data on WC in 113,453 children and adolescents (males 50.2%) aged 4 to 20 years from 8 countries in different regions (Bulgaria, China, Iran, Korea, Malaysia, Poland, Seychelles, and Switzerland). We calculated WC percentile cutoffs in samples including or excluding children with obesity, overweight, or underweight. WC percentiles were generated using the general additive model for location, scale, and shape (GAMLSS). We also estimated the predictive power of the WC 90th percentile cutoffs to predict cardiovascular risk using receiver operator characteristics curve analysis based on data from 3 countries that had available data (China, Iran, and Korea). We also examined which WC percentiles linked with WC cutoffs for central obesity in adults (at age of 18 years).
MAIN OUTCOME MEASURE: WC measured based on recommendation by the World Health Organization.
RESULTS: We validated the performance of the age- and sex-specific 90th percentile WC cutoffs calculated in children and adolescents (6-18 years of age) with normal weight (excluding youth with obesity, overweight, or underweight) by linking the percentile with cardiovascular risk (area under the curve [AUC]: 0.69 for boys; 0.63 for girls). In addition, WC percentile among normal weight children linked relatively well with established WC cutoffs for central obesity in adults (eg, AUC in US adolescents: 0.71 for boys; 0.68 for girls).
CONCLUSION: The international WC cutoffs developed in this study could be useful to screen central obesity in children and adolescents aged 6 to 18 years and allow direct comparison of WC distributions between populations and over time.