The purpose of the study was to determine relationship of abdominal fat, adipocytokine, bone mineral density, and bone turnover markers in obese male adolescents. Twenty four male adolescents (obese: 12, normal: 12) volunteered to participate in the study. Anthropometry and skeletal maturity were measured. Body composition and bone mineral density were estimated by DXA (Hologic, QDR-4500, USA). Abdominal fat with total adipose tissue (TAT), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and visceral adipose tissue to subcutaneous adipose tissue ratio (VSR) were estimated by computed tomography (ECLOS, HITACH, Japan). Blood samples were obtained for and analysis of adipocytokines including leptin and adiponectin. Bone turnover markers, osteocalcin (OC), bone-specific alkaline phosphatase (BALP) for bone formation markers and N-terminal telopeptide (NTx), C-terminal telopeptide (CTx) for bone resorption markers were analysed. All data were analyzed utilizing SAS 9.3 (SAS Institute, NC, USA). Independent t-test was used to evaluate the differences between obese adolescents and normal adolescents. Pearson correlation analysis was applied to figure out the relationship between abdominal fat, adipocytokines, bone mineral density, and bone turnover markers. Multiple regression analysis was used to find out the factors of abdominal fat which influence on bone mineral density. A level of significance was set at p<.05. The results of the study indicated that fat tissue (p<.001), percent body fat (p<0.001), TAT (p<.001), VAT (p<.001), and SAT (p<0.001) were significantly higher in obese adolescents than normal adolescents. However bone mineral contents were significantly higher in normal adolescents. Normal adolescents have significantly higher whole body BMD and lumber BMD than obese adolescents. Abdominal fat including VAT and SAT related negatively with whole body BMD and lumbar BMD. Leptin related negatively with BMD whereas adiponectin related positively with BMD. NTx for bone resorption marker related positively with abdominal fat. Visceral adipose tissue was a predictor for whole body BMD and lumbar BMD in explaining 46% and 32% in adolescents. In conclusion, obese male adolescents have lower whole body BMD and lumbar BMD than normal adolescents. Abdominal fat including VAT and SAT related negatively with whole body BMD and Lumbar BMD. And leptin and adiponectin were closely related with BMD. Finally, visceral adipose tissue was a predictor for whole body and lumbar BMD in adolescents.
The purpose of this study was to examine the relationship of obesity index, fitness and cardiovascular risk index in middle and high school students. Obesity index, fitness score and cardiovascular risk index were measured from 1,044 middle and high school students. The results of relation between obesity index and fitness showed that the higher obesity index had significantly lower fitness score for both boys and girls (boys: p<0.001, girl: p<0.05) The results of relation between obesity index and cardiovascular risk index indicated that the higher obesity index had significantly higher cardiovascular risk index for both boys and girls (boys: p<0.001, girl: p<0.001). Moreover, The lower fitness index showed significantly higher cardiovascular risk index regardless of gender in middle school students (boys: p<0.001, girl: p<0.01). Therefore, the results of this study indicated that obese adolescents had the lower fitness level and high possibility of cardiovascular risk.
The present study has been carried out with a purpose of a long term estimation for the body size and BMI (Body Mass Index) of Korean children and youth using ARIMA, a time series model. In order to select an estimation model for the optimum time series, among the time series analysis method of SPSS22.0 statistic programs, a multivariate ARIMA (p,d,q) model has been selected that has an input series (physical education facility, time spent for physical education, animal source foods, GDP deflator, animal source food intake ratio), using annual average data of height, weight, and BMI data from 1965 to 2015. Among the several optimal measurements in ARIMA model with estimation variables, an optimal RMSE-based model (RMSE: Root Mean Square Error) has been selected. Using this model, the estimation model and estimated values of children’s height, weight, and BMI have been suggested for each age group. The results are as the following. The trend estimation of height follows a logistic curve, with both male and female groups showing increasing trends. The weight has a trend of increasing ratio higher than height. BMI also shows a trend curve similar to weight. The estimation model has been mostly ARIMA(0,1,0). In particular, the average BMI has been estimated as 22-23 for male students in 6th, 8th, 9th, 11th and 12th grade in 2030. This indicates the recent increasing obesity as children and youth occupy most of daily time for play culture that is far from physical activities, such as computer games, smartphone games, and video games at home.
