• Korean Journal of Community Nutrition
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• v.13 no.3
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• pp.323-333
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• 2008

The aim of this study was to measure and compare nutrient intake, anthropometric measurements and serum indices by percent body fat as one of the index of obesity degree in female college students. Additionally we attempted to investigate percentile distribution of fat free mass index (FFMI) and fat mass index (FMI) for developing reference values for these two parameters. The subjects were 91 female college students who were classified to 4 groups according to the percentile of percent body fat (Group1: 25 th < percentile of percent body fat, Group 2 : 25 th ${\le}$ percentile of percent body fat < 50 th, Group 3 : 50 th ${\le}$ percentile of percent body fat < 75 th, Group 4 : percentile of percent body fat ${\ge}$ 75 th). The mean percent body fat and body mass index were 28.2%, $20.5 kg/m^2$ respectively. The mean energy intake was 1707 kcal(81% of KDRIs) and vitamin C, folate, Ca and Zn intake were 73.9%, 54.7%, 79.6%, 97.5% of KDRIs respectively. Most nutrient intake (energy, carbohydrate, cholesterol, fatty acid, Ca, Fe) of G4 was lower than that of G1, G2 and G3. Serum HDL-cholesterol concentration was significantly lower in G4 than G1, G2, G3 and it tended to increase as percent body fat decreased. LDL/HDL, A1 of G4 were significantly the highest among the 4 groups and increased as percent body fat increased. The mean fat free mass index and fat mass index were $14.5 kg/m^2$, $6.0 kg/m^2$ respectively. The criteria of sarcopenic obesity which has been defined as under 25 th percentile of FFMI and below 75 th percentile of FMI were shown $12.8 kg/m^2$, $8.2 kg/m^2$ respectively in this study. In conclusion, we should continue to more systematically research on the studies of new obesity measurement which includes FFMI and FMI as one of the variables. And the public education for weight control that emphasizes both the understanding of body composition and the importance of nutrition balance is also required.

• Investigative Magnetic Resonance Imaging
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• v.26 no.2
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• pp.104-116
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• 2022

The purpose of this study is to systematically determine an optimal percentile cut-off in histogram analysis for calculating the mean parameters obtained from a non-Gaussian continuous-time random-walk (CTRW) diffusion model for differentiating individual glioma grades. This retrospective study included 90 patients with histopathologically proven gliomas (42 grade II, 19 grade III, and 29 grade IV). We performed diffusion-weighted imaging using 17 b-values (0-4000 s/mm²) at 3T, and analyzed the images with the CTRW model to produce an anomalous diffusion coefficient (D_m) along with temporal (𝛼) and spatial (𝛽) diffusion heterogeneity parameters. Given the tumor ROIs, we created a histogram of each parameter; computed the P-values (using a Student's t-test) for the statistical differences in the mean D_m, 𝛼, or 𝛽 for differentiating grade II vs. grade III gliomas and grade III vs. grade IV gliomas at different percentiles (1% to 100%); and selected the highest percentile with P < 0.05 as the optimal percentile. We used the mean parameter values calculated from the optimal percentile cut-offs to do a receiver operating characteristic (ROC) analysis based on individual parameters or their combinations. We compared the results with those obtained by averaging data over the entire region of interest (i.e., 100th percentile). We found the optimal percentiles for D_m, 𝛼, and 𝛽 to be 68%, 75%, and 100% for differentiating grade II vs. III and 58%, 19%, and 100% for differentiating grade III vs. IV gliomas, respectively. The optimal percentile cut-offs outperformed the entire-ROI-based analysis in sensitivity (0.761 vs. 0.690), specificity (0.578 vs. 0.526), accuracy (0.704 vs. 0.639), and AUC (0.671 vs. 0.599) for grade II vs. III differentiations and in sensitivity (0.789 vs. 0.578) and AUC (0.637 vs. 0.620) for grade III vs. IV differentiations, respectively. Percentile-based histogram analysis, coupled with the multi-parametric approach enabled by the CTRW diffusion model using high b-values, can improve glioma grading.

• Journal of Nutrition and Health
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• v.46 no.1
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• pp.50-60
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• 2013

The aims of this study were to estimate daily intake of macrominerals from beverages, liquid teas, and liquid coffees and to evaluate their potential health risks for Korean children and adolescents (1-to 19 years old). Assessment of dietary intake was conducted using the actual level of sodium, calcium, phosphorus, potassium, and magnesium in non-alcoholic beverages and (207 beverages, 19 liquid teas, and 24 liquid coffees) the food consumption amount drawn from "The Fourth Korea National Health and Nutrition Examination Survey (2007-2009)". To estimate the dietary intake of non-alcoholic beverages, 6,082 children and adolescents (Scenario I) were compared with 1,704 non-alcoholic beverage consumption subjects among them (Scenario II). Calculation of the estimated daily intake of macrominerals was based on point estimates and probabilistic estimates. The values of probabilistic macromineral intake, which is a Monte-Carlo approach considering probabilistic density functions of variables, were presented using the probabilistic model. The level of safety for macrominerals was evaluated by comparison with population nutrient intake goal (Goal, 2.0 g/day) for sodium, tolerable upper intake level (UL) for calcium (2,500 mg/day) and phosphorus (3,000-3,500 mg/day) set by the Korean Nutrition Society (Dietary Reference Intakes for Koreans, KDRI). For total children and adolescents (Scenario I), mean daily intake of sodium, calcium, phosphorus, potassium, and magnesium estimated by probabilistic estimates using Monte Carlo simulation was, respectively, 7.93, 10.92, 6.73, 23.41, and 1.11, and 95th percentile daily intake of those was, respectively, 28.02, 44.86, 27.43, 98.14, and 3.87 mg/day. For consumers-only (Scenario II), mean daily intake of sodium, calcium, phosphorus, potassium, and magnesium estimated by probabilistic estimates using Monte Carlo simulation was, respectively, 19.10, 25.77, 15.83, 56.56, and 2.86 mg/day, and 95th percentile daily intake of those was, respectively, 62.67, 101.95, 62.09, 227.92, and 8.67 mg/day. For Scenarios I II, sodium, calcium, and phosphorus did not have a mean an 95th percentile intake that met or exceeded the 5% of Goal and UL.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.113-117
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• 2016

Quantile regression is an efficient method for predicting and estimating the relationship between explanatory variables and percentile points of the response distribution, particularly for extreme percentiles of the distribution. To study the relationship between urbanization and cancer morbidity, we here applied quantile regression. This cross-sectional study was conducted for 9 cancers in 345 cities in 2007 in Iran. Data were obtained from the Ministry of Health and Medical Education and the relationship between urbanization and cancer morbidity was investigated using quantile regression and least square regression. Fitting models were compared using AIC criteria. R (3.0.1) software and the Quantreg package were used for statistical analysis. With the quantile regression model all percentiles for breast, colorectal, prostate, lung and pancreas cancers demonstrated increasing incidence rate with urbanization. The maximum increase for breast cancer was in the 90th percentile (${\beta}$=0.13, p-value<0.001), for colorectal cancer was in the 75th percentile (${\beta}$=0.048, p-value<0.001), for prostate cancer the 95th percentile (${\beta}$=0.55, p-value<0.001), for lung cancer was in 95th percentile (${\beta}$=0.52, p-value=0.006), for pancreas cancer was in 10th percentile (${\beta}$=0.011, p-value<0.001). For gastric, esophageal and skin cancers, with increasing urbanization, the incidence rate was decreased. The maximum decrease for gastric cancer was in the 90th percentile(${\beta}$=0.003, p-value<0.001), for esophageal cancer the 95th (${\beta}$=0.04, p-value=0.4) and for skin cancer also the 95th (${\beta}$=0.145, p-value=0.071). The AIC showed that for upper percentiles, the fitting of quantile regression was better than least square regression. According to the results of this study, the significant impact of urbanization on cancer morbidity requirs more effort and planning by policymakers and administrators in order to reduce risk factors such as pollution in urban areas and ensure proper nutrition recommendations are made.

• Journal of Bio-Environment Control
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• v.27 no.3
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• pp.269-275
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• 2018

In order to establish the criterion for analyzing outdoor weather conditions in the greenhouse heating and cooling system design, we analyzed heating and cooling design outdoor temperatures by the annual percentile method and compared with design outdoor temperatures by the existing seasonal percentile method. In the annual percentile method, 0.4%, 1% and 2% of the total 8,760 hours per year are presented as cooling design outdoor temperatures and 99.6% and 99% as heating design outdoor temperatures. When the annual percentile method was adopted, heating design outdoor temperatures increased by 6.7 to 9.6% compared with the seasonal percentile method, and cooling design outdoor temperatures decreased by 0.6 to 1.1%. The maximum heating load in the same greenhouse condition decreased by 3.0 to 3.6% when the annual percentile method was adopted, but the effect on the maximum cooling load was insignificant. Therefore, it is necessary to consider the change of heating design outdoor temperatures to the annual percentile method, but it is not necessary to change the cooling design outdoor temperatures since there is little difference between the two methods.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.2
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• pp.43-51
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• 2011

Probabilistic seismic hazard analysis (PSHA), which can effectively apply inevitable uncertainties in seismic data, considers a number of seismotectonic models and attenuation equations. The calculated hazard by PSHA is generally a value dependent on peak ground acceleration (PGA) and expresses the value as an annual exceedance probability. To represent the uncertainty range of a hazard which has occurred using various seismic data, a hazard curve figure shows both a mean curve and percentile curves (15, 50, and 85). The percentile performs an important role in that it indicates the uncertainty range of the calculated hazard, could be calculated using various methods by the relation of the weight and hazard. This study using the weight accumulation method, the weighted hazard method, the maximum likelihood method, and the moment method, has calculated the percentile of the computed hazard by PSHA on the Shinuljin 1, 2 site. The calculated percentile using the weight accumulation method, the weighted hazard method, and the maximum likelihood method, have similar trends and represent the range of all computed hazards by PSHA. The calculated percentile using the moment method effectively showed the range of hazards at the source which includes a site. This study suggests the moment method as effective percentile calculation method considering the almost same mean hazard for the seismotectonic model and a source which includes a site.

• Journal of Korean Medicine for Obesity Research
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• v.10 no.1
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• pp.17-28
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• 2010

Objectives It is significant to determine the validation of a self-administered somatotype drawing for the simple assessment of childhood obesity in elementary school and clinical practice. Methods The subjects were 202 children(112 boys and 90 girls) who answered a questionnaire for somatotype drawing and weremeasured for body components with bioelectrical impedance. The somatotype drawing of children was analysed according to the three criteria of childhood obesity - BMI percentile, obesity index and percent body fat, respectively. Results BMI, waist-hip ratio, skeletal musclemass and proteinmass had significant differences(p<.05) between boys and girls. Somatotype drawing had the highest correlation with BMI in both boys and girls, and also showed a high correlation with BMI percentile, obesity index and percent body fat.According to these criteria of childhood obesity, the somatotype drawing was the best consistent with the obesity index, next turn was the percent body fat and then the BMI percentile. Conclusions The validation of somatotype drawing for the assessment of childhood obesity was analysed according to BMI percentile, obesity index and percent body fat, and the somatotype drawing was the best consistent with obesity index in both boys and girls.

• Clinical and Experimental Pediatrics
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• v.57 no.1
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• pp.35-40
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• 2014

Purpose: Height-specific blood pressure (BP) is the standard parameter used to diagnose childhood hypertension. However, there has been some argument that weight may be a better variable than height in the reference BP standards. Therefore, before assessing the BP status using the reference BP standards, a basic understanding of the fundamental association of weight and height with BP is required. Methods: In the present study, we analyzed the correlation of BP with height and weight in Korean adolescents (age, 10-19 years), using data from the Korean National Health and Nutrition Examination Surveys (2009-2011). Results: Systolic BP (SBP) was more closely correlated with weight than with height in the normal weight (body mass index [BMI], ${\leq}85th$ percentile) and overweight (BMI, >85th percentile) groups and in the normal waist circumference (WC, ${\leq}90th$ percentile) and high WC (>90th percentile) groups in both sexes. Diastolic BP (DBP) had a higher correlation with height than with weight in the normal weight and normal WC groups, whereas weight was more closely associated with DBP than height in the overweight and high WC groups in both boys and girls. Conclusion: In Korean adolescents, weight had a greater effect on SBP than height in both the normal weight and overweight groups. DBP was mainly affected by height in the normal weight group, whereas weight was the major determinant of DBP in the overweight group. Therefore, it may be necessary to consider weight in the establishment of reference BP standards.

• The Journal of Pediatrics of Korean Medicine
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• v.23 no.2
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• pp.145-157
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• 2009

Objectives : The purpose of this study was to examine relationships between bone age and body composition to make efficient clinical reviews on children's growth. Methods : 157 of children in age of 3 years to 16 years old were participated in this study(88 of boys and 69 of girls). They visited the department of pediatrics, OO university oriental hospital and were measured their body composition and bone age. Results : 1. An age and bone age, height, weight, and body mass index were positively correlated, and also a bone age and height, weight, and body mass index were positively correlated. 2. The level of soft lean mass, body fat mass, and MPH were increased in boys in higher height percentile. Children's predicted adult height was higher in children in higher height percentile. 3. The level of body fat mass was increased as weight percentile increased. Bone age, MPH was increased as weight percentile increased, especially in case of boys. In girl's case, the level of soft lean mass, their predicted adult height, the difference between children's bone age and their actual age was increased as weight percentile increased. Conclusions : Measuring bone age and body composition is the effective way to estimate children's growth and development in future.

• The Journal of Pediatrics of Korean Medicine
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• v.23 no.2
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• pp.131-144
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• 2009

Objectives : The purpose of this study is to have better data and to make efficient clinical reviews on pre-school children's growth based on two measurements; Body composition for measuring body volume and bone age for potential growth. Methods : The study was conducted with 221 children(118 of boys and 103 of girls) from three kindergartens. Body compositions(soft lean mass, body fat mass, percent body fat) were measured by bioelectrical impedance analysis, bone age was measured by bone density through ultrasonic image of calcaneus. Results and Conclusions : 1. The higher level on weight or BMI, the more averages of soft lean mass, body fat mass, percent body fat. 2. The average bone ages and bone age-chronological age were lower in under 50 percentile's group, but it was higher in upper 50 percentile's group. Also, children with high BMI had older in bone ages and bone age-chronological age. 3. The higher in height percentile based on the bone age; there were more soft lean mass. 4. The averages of bone age and bone age-chronological age were significantly decreased, the more percentiles of height according to bone age were big, they were higher than total average in under 50 percentile's group of height, lower than total average in over 50 percentile's group of height in both boys and girls. 5. The average of MPH were significantly decreased in top percentiles of children's height distribution. Also, in the upper percentiles of height distribution based on bone age were big in only boys. 6. The body compositions(soft lean mass, body fat mass, percent body fat) were related to body volume growth, which can he measured by weight or BMI. The bone age, bone age-chronological age, and MPH were related in terms of hight. The body volume growth was a little hit related with potential growth.