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ObjectiveWe aimed to assess the effectiveness of the first 6 months of a 24 month multidisciplinary intervention program including circuit training and a balanced diet in children and adolescents with obesity.MethodsA quasi-experimental intervention trial included 242 participants (age [mean±standard deviation]: 11.3±2.06 years, 97 girls) of at least 85th percentile of age- and sex-specific body mass index (BMI). Participants were grouped into three to receive usual care (usual care group), exercise intervention with circuit training (exercise group), or intensive nutritional and feedback intervention with a balanced diet (nutritional group). Primary outcome was BMI z-score, while secondary outcomes included body composition, cardiometabolic risk markers, nutrition, and physical fitness.ResultsAmong the participants, 80.6% had a BMI ≥ the 97th percentile for age and sex. The BMI z-score of the overall completers decreased by about 0.080 after 6 months of intervention (p < 0.001). After the intervention, both exercise and nutritional groups had significantly lower BMI z-scores than the baseline data by about 0.14 and 0.075, respectively (p < 0.05). Significant group by time interaction effects were observed between exercise versus usual care group in BMI z-score (β, -0.11; 95% confidence interval (CI), -0.20 to -0.023) and adiponectin (β, 1.31; 95% CI, 1.08 to 1.58); and between nutritional versus usual care group in waist circumference (β, -3.47; 95% CI, -6.06 to -0.89). No statistically significant differences were observed in any of the other secondary outcomes assessed.ConclusionMultidisciplinary intervention including circuit training and a balanced diet for children and adolescents with obesity reduced the BMI z-score and improved cardiometabolic risk markers such as adiponectin and waist circumference.

Data on the association between alcohol consumption and the risk of type 2 diabetes mellitus (T2DM) have accumulated, but little has been reported about this association in terms of lean T2DM. The present study analyzed 10-year longitudinal data to investigate the association between alcohol consumption and T2DM risk among lean individuals. This prospective study included 2,366 male and female Koreans aged 40-69 years who were free of DM and had a body mass index (BMI) 60g/day among alcohol drinkers. No protective effect of moderate alcohol consumption

Obesity is an increasing public health concern worldwide. According to the latest Organization for Economic Co-operation and Development (OECD) report (2014), the incidence of child obesity in Korea has exceeded the OECD average. To better understand and control this condition, the present study examined the composition of the gut microbial community in normal and obese adolescents. Fecal samples were collected from 67 obese (body mass index [BMI] ≥ 30 kg/m2, or ≥ 99th BMI percentile) and 67 normal (BMI < 25 kg/m2 or < 85th BMI percentile) Korean adolescents aged 13-16 years and subjected to 16S rRNA gene sequencing. Analysis of bacterial composition according to taxonomic rank (genus, family, and phylum) revealed marked differences in the Bacteroides and Prevotella populations in normal and obese samples (p < 0.005) at the genus and family levels; however, there was no difference in the Firmicutes-to-Bacteroidetes (F/B) ratio between normal and obese adolescents samples at the phylum level (F/B normal = 0.50 ± 0.53; F/B obese = 0.56 ± 0.86; p = 0.384). Statistical analysis revealed a significant association between the compositions of several bacterial taxa and child obesity. Among these, Bacteroides and Prevotella showed the most significant association with BMI (p < 0.0001 and 0.0001, respectively). We also found that the composition of Bacteroides was negatively associated with triglycerides (TG), total cholesterol, and high-sensitive C-reactive protein (hs-crp) (p = 0.0049, 0.0023, and 0.0038, respectively) levels, whereas that of Prevotella was positively associated with TG and hs-crp levels (p = 0.0394 and 0.0150, respectively). We then applied the association rule mining algorithm to generate "rules" to identify the association between the populations of multiple bacterial taxa and obesity; these rules were able to discriminate obese from normal states. Therefore, the present study describes a systemic approach to identify the association between bacterial populations in the gut and childhood obesity.