• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.277-282
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• 2004

In order to investigate the small female occupant behavior and accompanying injury mechanisms in vehicular trash event, a finite element model of $5^{th}$ percentile female has been developed. The model consists of articulated rigid body, which represents the morphology of small female body, and internal components with anatomical details. Articulated rigid body model serves as a basic platform for joining the detail internal skeletons and organs, while itself can be used for representing the overall kinematics of small female occupant. The modeling details such as anthropometry and finite element structure as well as validation results for the articulated rigid body model are introduced in this paper. The second part of the modeling, i.e. the internal components with anatomical details of small female are presented in subsequent part II of the paper.

• Journal of Nutrition and Health
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• v.30 no.7
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• pp.832-839
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• 1997

The purpose of this study is to survey the prevalence of obesity assessed on the basis of height and weight among students in primary and secondary schools in the metropolitan area of Seoul, Korea during the period of 1979 to 1996. The major findings are as follows ; 1) The fiftieth percentile values of BMI have increased more in mid-ranged age group than upper(16-17 years old) and lower(6-7 years old) ranged age groups. 2) The prevalence of obesity by standard weight of height was higher among male students than female students and students in the primary schools showed higher weight increase than adolescent age(12-17 years old) group. As a whole, the prevalence of obesity over last 18 years has increased 4.6 times in males and 3.2 times in females. 3) Judged on the basis of the BMI 90th, 95th percentile values of 1979 , the prevalence of obesity among male students showed higher increases than among female students. Higher increase was also observed among primary school students than among middle and high school students. Increase of weight was higher for the $\geq$95th percentile group than the 90-95th percentile group. 4) Judged on the basis of the BMI, 90th, 95 th percentile values of NHANES-I, the $\geq$95th percentile group showed higher increase in the prevalence of obesity than the 90-95th percentile group. According to the 1996 data, severe obesity group ($\geq$95th percentile) was about two times of NHANES-I in male primary school students, while the number for female middle and high school students was about 1/5 of NHANES-I.

• Journal of Food Hygiene and Safety
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• v.18 no.3
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• pp.107-112
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• 2003

Probabilistic exposure assessment has been recognized as an important tool in microbial risk assessment, because of obtained the desired results to characterize of variability and uncertainty associated with the microbial hazards. In addition, it will be provided much more actuality information than the point-estimate approaches. In this study, we present methodology using mathematical probability distribution in exposure assessment and estimating of contamination level of Listeria monocytogenes in meat and meat products as a case study. The result of estimation contaminatin level was mean ($50^{th}$ percentile) -4.08 Log CFU/g minimum ($5^{th}$ percentile) -4.88 Log CFU/g, maximum ($95^{th}$ percentile) -3.56 Log CFU/g.

• 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.

• 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.

• Journal of The Korean Association For Science Education
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• v.4 no.1
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• pp.15-25
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• 1984

The purpose of this study is to develop a practical and ideal model of science laboratory enrolled 48-60 students by studying optimal facilities such as laboratory tables and chairs proper to elementary school settings. The science laboratory model was figured out in terms of the following six procedures; (1) Current status as well as problems of science laboratory and its facilities was identified by means of the questionnaires conducted to 201 elementary schools, using stratified cluster sampling tehnique, under the consideration of the school size and the regional characteristics across the country. (2) Collected were the anthropometric data with respect to sitting height, popliteal height, buttock popliteal length, elbow rest height, and back width from the 747 students, 4th-6th grade, in Seoul area. (3) It was measured the work apace necessary for individual student to perform his experiment. (4) Using the data of the process (2), we determined the optimal sizes of laboratory tables and chairs fitted for Korean elementary school students. (5) The optimal area of science laboratory for 48-60 students is determined in terms of the data obtained in (3) for individual work space in addition to the appropriate table size figured out by (4). (6) A practical and ideal model for a science laboratory in elementary school was designed according to the above procedures. For the optimal model of science laboratory, the results of this study can be summarized as follows: The sizes of chair and table are categorized into three groups such as small, medium, and large depending on students' physical outfit. The small size base on the 12.5th percentile point of students' sitting height is used for students of the 0-25th percentile ranks. The medium size base on the 50th percentile point of students' sitting height is used for students of the 26-75th percentile ranks. The large size base on the 87.5th percentile point of students' sitting height is used for students of the 76-100th percentile ranks. (1) Sizes of chairs: The small size is 28cm in width and 33cm in height. The medium size is 31cm in width and 36cm in height. The large size is 35cm in width and 38cm in height. (2) Sizes of laboratory tables: The small size is 120cm in length, 86cm in width, and 60cm in height. The large size is 120cm in length, 86cm in width, and 60cm in height. The large size is 120cm in length, 86cm in width, and 65cm in height. (3) Size of science laboratory: The optimal science laboratory for 48-60 elementary school students, which can install the 12 laboratory tables, is 12m in length and 10m in width.

• The Journal of Pediatrics of Korean Medicine
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• v.25 no.1
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• pp.82-89
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• 2011

Objectives: This study was designed to regulate the percentile of body fat percentage by Bioelectrical Impedence Analysis (BIA) in order to detect overweight and obesity in preschool children. Methods 1301 three to six year old children's height, weight, and body fat percentage using BIA was measured. Results: The percent of the boys with 85th percentiles of the body fat percentage were 22.3%(3years), 23.4%(3.5years), 23.9%(4years), 24.8%(4.5years), 22.8%(5years), 24.6%(5.5years) and 23.8%(6years). The percent of the girls with 95th percentiles of the body fat percentage were 24.9%(3years), 27.5%(3.5years), 27.3%(4years), 28.6%(4.5years), 28.1%(5years), 33.3%(5.5years) and 32.7%(6years). For the girls, the percent of girls with 85th percentiles of body fat percentage were 23.3%(3years), 24.4%(3.5years), 23.6%(4years), 23.7%(4.5years), 24.7%(5years), 26.0%(5.5years) and 28.1%(6years). And the 95th percentiles of the body fat percentage were 28.6%(3years), 27.3%(3.5years), 25.4%(4years), 28.0%(4.5years), 31.7%(5years), 33.5%(5.5years) and 36.4%(6years). Conclusions: The 85th percentiles of body fat percentage to classify as overweight and the 95th percentiles of body fat percentage to classify as obesity were accord with the Body Mass Index (BMI) criteria by the Korean pediatrics society in 2007.

• Journal of Community Nutrition
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• v.1 no.2
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• pp.81-87
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• 1999

Body mass index(BMI) is recognized as one of the most useful indexes for adiposity in children and adults. This study was conducted to provide information on BMI distribution by age and sex in Korean children, and to identify sociodemographic factors that affected BMI among children. The study was conducted on 2376 children(boys 1184, girls 1192) living in a middle-size city in Korea. Subjects were selected from the primary schoolchildren in grades 1-6 using the two-stage sampling method. Their mean age was 9.4 years. The percentile of BMI tended to increase as age increased in both sexes. The 85th percentile for boys, aged 6-12 years, was 19.8kg/㎡, and the 95th percentile was 22.5kg/㎡. The 85th percentile for girls, aged 6-12 years, was 18.9kg/㎡, and the 95th percentile was 21.5kg/㎡. Multiple regression analysis was carried out to predict BMI from percent ideal body weight (PIBW), age and sex. After adjusting PIBW and age, BMI for boys was 0.062kg/㎡ lower than that for girls. One year of age increased BIM by 0.55kg/㎡. The prevalence rate of overweight and obesity based on PIBW was 15.8% and 15.0% for boys, and 14.0% and 11.0% for girls, respectively. Demographic factors such as sex, age, and parents' obesity influenced children's BMI. After adjusting for sex, age and parents' BMI, the presence of another children in family, and mother's employment status showed a strong effect on children's BMI. The results suggest an age-sex specific BMI distribution of Korean children. The present study also provides direct evidence of a correlation between early life environmental factors, such as presence of siblings or mother's employment, and BMI level in Korean children.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.443-450
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• 1997

본 연구에서는 safework 소프트웨어를 이용하여 쾌적한 운전좌석에 대한 3차원 모델링을 하였다. 자동차 시트와 운전대의 조절 범위 및 레이아웃(layout), 그리고 운전자의 눈의 위치 등을 결정하기 위하여, 한국인과 미국인 체형의 95th percentile의 성인 남자와 5th percentile의 성인 여자, 그리고 50th percentile의 성인 남자에 대한 최적 운전상태에서의 엉덩이 점(hip point), 운전대 중심(steering wheel center), 눈의 위치(eye point) 등의 3차원상의 위치를 측정하였다. 인간의 모든 치수와 형태학적 윤곽 뿐만 아니라. 신체의 유동성, 기능적 제한 등이 충실히 반영된 safework 마네킹(mannequin)을 이용하 였으며, 여러 신체 부위의 복합적 움직임을 결정하는 역기구학(inverse kinematics)에 근거하여운전좌석을 모델링 하였다. Safework을 이용함으로써 기존의 마네킹이나 실물모형(mockup)의 제작에필요한 시간과 비용을 절약할 수 있을 뿐만 아니라, 인간의 신체 특성과 유사한 마네킹을 이용하여 인간과 환경사이의 인터페이스를 보다 효율적으로 모델링 할 수 있을 것이다.

• Clinical and Experimental Pediatrics
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• v.61 no.3
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• pp.71-77
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• 2018

Purpose: Small for gestational age (SGA) is confusingly defined as birth weight (BW) either below 3rd percentile or 10th percentile for infants. This study aimed to compare postnatal catch-up growth between SGA groups according to different definitions. Methods: Data of 129 infants born with BW below the 10th percentile and admitted to Korea University Anam Hospital and Ansan Hospital were retrospectively reviewed. Height and weight were measured at 6, 12, and 24 months. Results were compared between group A (BW: <3rd percentile) and group B (BW: 3rd-10th percentile). Results: Group A included 66 infants and group B included 63. At age 6 months (n=122), 62.9% of group A and 71.7% (P=0.303) of group B showed catch-up growth in weight. At 6 months (n=69), 55.9% of group A and 80.0% of group B (P<0.05) showed catch-up growth in height. At 12 months (n=106), 58.5% of group A, and 75.5% (P=0.062) of group B showed catch-up growth in weight. At 12 months (n=75), 52.8% of group A and 64.1% of group B (P=0.320) showed catch-up growth in height. Up to age 24 months, 66.7%/80.0% in group A and 63.6%/80.0% in group B showed catch-up growth in weight/height. Conclusion: Despite different definitions, there were no significant differences between the two SGA groups in postnatal catch-up growth up to age 24 months, except for height at 6 months. Compared to infants with appropriate catch-up growth, low gestational age and BW were risk factors for failed catch-up growth at 6 months.