• Journal of Nutrition and Health
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• 제38권10호
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• pp.847-855
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• 2005

This study investigated and compared the daily activities and energy expenditure of normally-weighted and obese elementary school children. The participants were 115 boys and 115 girls (6th grade) at ten elementary schools in Busan. Time spent on each activity was evaluated using the twenty-four hour recall method. 1) The general characteristics of the normally-weighted and obese children did not differ, although the normally-weighted children exercised and used stairs more than the obese children.2) Among their classified activities, the children spent most of their time resting, study, leisure, physiology and hygiene, commuting, and housework in that decreasing order. Normally-weighted children spent less time tying down and in conversation with family and friends than obese ones. 3) The children's average activity factors were 1.47 - 1.50. The normally-weighted children's rest energy expenditure (REE) (1391.4 kcal,1264.7 kcal) was less than that of the obese children (1711.4 kcal. 1461.0 kcal) . The normally-weighted children's daily energy expenditure was less than that of the obese, but energy expenditure per body weight was less in obese children than in the normally-weighted. In conclusion, sedentary activities and energy expenditure per body weight was less in the obese compared to the normally-weighted children. Programs to help children perceive and practice desirable physical activities should be suggested for prevention of obesity in children. (Korean J Nutrition 38(10): 847$\sim$855,2005)

• Journal of Nutrition and Health
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• 제26권4호
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• pp.390-404
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• 1993

The purpose of this paper is to determine the percentage of body fat by measurement of skin-fold thickness of the triceps and the subscapular area to investigate the relationship between the daily energy intake and expenditure among obese women and nonobese women based on the percentage of body fat and age. This survey included 422 females in Cheju. 1) The age distribution of the 422 females surveyed was : 26.8% were in their 20's, 20.6% in their 30's, 21.3% in their 40's, 19.0% in their 50's and 12.3% were above 60 years of age. The 422 females consisted consisted of 78% housewives, 12.8% college student and 9.2% single working women. 2) The average height and weight of the surveyed women were respecitively 159.0$\pm$4.2cm and 56.0$\pm$7.2kg, the percentage of body fat of the surveyed women was 24.8$\pm$9.8%, and the BMI of those surveyed was 22.7$\pm$2.7. If higher than 30% body fat was defined as being obese, 15.6% of the surveyed women were assessed to be obese. 3) Total daily food consumption and energy intake of the group of women aged 60 and older was significantly small. Food consumption and nutrient intake of obese women was greater than that of the nonobese group, but not significant. Carbohydrate intake of the obese group in their 40's was significantly higher than the nonobese group. Total food consumption, energy and carbohydrate intake of the obese group in their 50's was significantly higher than the nonobese group. Vegetable intake of the obese group in their 60's and older was significantly higher than the nonobese group. 4) The total time of physiological activity of women aged 60 and older was significantly higher than for the other age groups and the total work time was significantly lower. The total work time of women in their 20's was not lower than the other groups. Considering the low energy expenditure of physical activity for women in their 20's, they appeared to have light activity. However, there was not a significant difference in the physical activity time among middle aged women groups(from 30 to 50). The entire energy expenditure of the obese group was greater than the nonobese group. However, the energy expenditure per body weight in the obese group was significantly less than that of the nonobese group in terms of the basal metabolic rate in consideration of the fat free mass. 5) There was a positive correlation between the percentage of body fat and the factors of age, sleeping time, total time of physiological activity, housework time, time spent watching TV, energy expenditure, energy intake, carbohydrate and cereal consumption. On the other hand, the percentage of body fat was negatively correlated with energy expenditure per body weight based on the basal metabolic rate in consideration of the free mass.

• 대한영양사협회학술지
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• 제11권2호
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• pp.159-169
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• 2005

The purpose of this study was to assess the energy expenditure and investigate the relationship between related variables in 70 female university students. Resting energy expenditure estimated by Harris-Benedict formula, WHO/NAO/FAO formula and various formulas based on body weight and body surface area were 1366.9$\pm$74.4kcal/day, 1287.8$\pm$106.6kcal/day, 1171.4$\pm$155.8kcal/day and 1342.0$\pm$97.4kcal/day. Measured resting energy expenditure by indirect calorimetry(Model : Metavine and TrueOne2400) were 1582.0$\pm$150.1kcal/day and 1268.2$\pm$152.9kcal/day, respectively. Average step number per day was 11981.2$\pm$3014.4 steps and average step number per hour was 746.1$\pm$198.0 steps/hr. Daily energy expenditure by using Harris-Benedict formula, body weight formula, body surface area formula, WHO/NAO.FAO formula and 15-min check list formula were 2374.7$\pm$249.6kcal, 2033.5$\pm$313.2kcal, 2331.2$\pm$266.0kcal, 2240.8$\pm$185.5kcal and 2195.5$\pm$398.3kcal. Meanwhile energy intake of subjects was 1714.9$\pm$551.2 kcal. Daily energy expenditure has positive correlation(r=0.262) with daily step number. And there was significant positive correlations(r=0.35-0.68) between various daily energy expenditures and muscle mass. These results suggested that increase of daily step number by using pedometer is good method to increase daily energy expenditure. In particular, increase in step number can reinforce the amounts of muscle.

• 한방비만학회지
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• 제3권1호
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• pp.17-24
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• 2003

Obesity increases the risk of knee and to a lesser extent hip OA, which combined affect a large percentage of middle-aged and elderly adults and which are major source of disability, and factor of drop a lowering in the physical exercise ability. Energy expenditure from physical activity accounts for up to 30% of total energy expenditure, it can have a significant impact on energy balance. We studied a exercise therapy that improved long-term weight management and produced additional benefits - loss of joint pain, improved joint mobility, and this exercise program will enhance the weight loss and health benefits from physical activity in the treatment of obese patients with osteoarthritis.

• The Korean Journal of Physiology
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• 제4권2호
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• pp.69-81
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• 1970

These studies were carried out on 176 persons ranging in age from 20 to 50 years to determine the basal metabolic rates, energy expenditure of various activities, and daily energy expenditure of service personnel in Korea. The measurements of basal metabolic rates were made on 42 subjects by indirect calorimetry using a Douglas' bag and Scholander's gas analyzer. The energy expenditures of various activities of daily life were also measured. The greatest increase in ratio of energy expenditure in the basis of resting metabolism was 277.3% in floor sopping and the least was 40.9% during hair cutting by beauticians. The assessment of the dailly energy expenditure for each subject was made by the factorial method, using a record of their activities throughout each of 24 hours of every survey day. Certain activities were recorded in minute units. The total daily energy expenditure is the sum of all energy expenditure. This was calculated by multiplying the caloric value of the metabolic rate by the time spent on each activity. The result of the total daily energy expenditure records for 17 occupations are summarized. In respect to the daily energy expenditure, most of the occupations are moderate or light work. But the janiter (F), laundress, cook (F), room maid and nurse's aid do heavy work.

• The Korean Journal of Physiology
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• 제6권1호
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• pp.39-42
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• 1972

This study was carried out on the energy expenditure and physical capacity of 504 persons from 17 occupations. The energy expenditure was measured by indirect calorimetry using a Douglas' bag and Scholander's gas analyser. The physical capacity was determined by the Harvard's step test and the maximum oxygen consumption using a treadmill. The assessment of the daily energy expenditure for each subject was made by the factorial method using a record of the activies throughout 24 hours of every survey day. The total daily energy expenditure is the sum of all energy expenditure. This was calculated by multiplying the caloric value of the metabolic rate by the time spent on each activity. Most of the occupations involved moderate or heavy work.

• 한국콘텐츠학회논문지
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• 제8권8호
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• pp.253-260
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• 2008

최근 핸드폰, PDA 등에서 가속도센서를 이용한 연구가 많이 증가하고 있다. 본 논문에서는 3축 가속도센서를 이용해 사람이 보행 시 발생하는 데이터를 취득하여 사람의 걸음 수를 계산해 내는 알고리즘과 활동량을 실시간으로 모니터링 할 수 있는 UI 시스템을 개발하였다. 걷기, 제자리 걷기, 뛰기, 천천히 걷기 등의 각 상황별 걸음 수를 정밀하게 측정하기 위해 적응적인 임계값을 사용하는 보행 횟수 검출 알고리즘을 제안하였다. 또 이러한 알고리즘에 의해 얻은 보행 횟수를 이용해서 활동량으로 환산하고 UI화면에 실시간으로 보임으로써 정량화된 활동량으로 실시간 모니터링이 가능하도록 하였다. 실험결과 제안한 보행 횟수 검출 알고리즘이 에너지 기반의 기존의 고정 임계값을 이용하는 알고리즘 보다 $5{\sim}10%$ 정확도가 높은 결과 값을 얻을 수 있었으며 특히, 천천히 걷기에서 정확도가 높아진 것을 확인하였다.

• 대한지역사회영양학회지
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• 제18권1호
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• pp.45-54
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• 2013

This study was conducted to investigate the physical activity pattern, activity coefficient, basal metabolic rate and energy expenditure of female university students. One-day activity diaries were collected from 95 female university students in Seoul. Body composition was measured by Inbody 720. Subjects spent 7 hr 8min on sleeping, 6 hr 31min on studying, 2 hr 50min on physiological activity, 2 hr 3min on leisure, 2 hr 2min on walking and jogging, 1 hr 58 min on commuting and 22min on house chores. The activity coefficient of these subjects was 1.58. The comparison of body composition of subjects according to PAL showed that body weight, body fat mass, arm circumference and arm muscle circumference of physically active group were significantly higher than those of the sedentary group. BMR calculated by Harris-Benedict (H-B) formula and DRI formula and BMR measured by Inbody 720 was 1375 kcal, 1306 kcal and 1209 kcal, respectively. Total energy expenditure (TEE) examined by one-day activity diaries and calculated by H-B formula and estimated energy requirement (EER) formula in DRI was 2102.1 kcal, 2184.4 kcal, and 2164.5 kcal, respectively. The Pearson correlation coefficient between TEE examined by one-day activity diaries and H-B TEE was 0.795 (p < 0.001) while that between TEE examined and DRI EER was 0.604 (p < 0.001). Overall data indicated that female university students seemed to be less active. Therefore it is recommended that universities develop good exercise programs for their students. Further studies are needed to generate more meaningful results with a larger sample size and using machine attached to the body, which are able to detect physical activity more accurately.

• Journal of Nutrition and Health
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• 제54권2호
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• pp.129-138
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• 2021

To set the estimated energy requirement (EER) in Dietary Reference Intakes for Koreans (KDRI), we need the coefficient by physical activity stage, as determined by the physical activity level(PAL). Thus, there has been demand for a tool to calculate PAL based on the physical activity diary. This study was undertaken to develop a physical activity (PA) classification table for Koreans, using the 2011 Compendium of physical activities in the United States. The PA classification table for Koreans contains 262 codes, and values of the metabolic equivalent of task (MET) for specific activities. Of these, 243 PAs which do not have Korean specific data or information, were selected from the 2011 Compendium of PAs that originated in the United States; another 19 PAs were selected from the previous research data of Koreans. The PA classification table is codified to facilitate the selection of energy values corresponding to each PA. The code for each PA consists of a single letter alphabet (activity category) and four numeric codes that display the activity type (2 digit number), activity intensity (1 digit number), and specific activities (1 digit number). In addition, the intensity (sedentary behavior, low, middle and high) of specific PA and its rate of energy expenditure in MET are presented together. The activity categories are divided into 4 areas: Daily Activity (A), Movement (B), Occupation (C), and Exercise and Sports (D). The developed PA classification table can be applied to quantify the energy cost of PA for adults in research or practice, and to assess energy expenditure and physical activity levels based on self-reported PA.

• 대한지역사회영양학회지
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• 제22권5호
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• pp.413-425
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• 2017

Objectives: Accurate assessment of energy expenditure is important for estimation of energy requirements in athletic children. The objective of this study was to evaluate the accuracy of accelerometer for prediction of selected activities' energy expenditure and intensity in athletic elementary school children. Methods: The present study involved 31 soccer players (16 males and 15 females) from an elementary school (9-12 years). During the measurements, children performed eight selected activities while simultaneously wearing the accelerometer and carrying the portable indirect calorimeter. Five equations (Freedson/Trost, Treuth, Pate, Puyau, Mattocks) were assessed for the prediction of energy expenditure from accelerometer counts, while Evenson equation was added for prediction of activity intensity, making six equations in total. The accuracy of accelerometer for energy prediction was assessed by comparing measured and predicted values, using the paired t-test. The intensity classification accuracy was evaluated with kappa statistics and ROC-Curve. Results: For activities of lying down, television viewing and reading, Freedson/Trost, Treuth were accurate in predicting energy expenditure. Regarding Pate, it was accurate for vacuuming and slow treadmill walking energy prediction. Mattocks was accurate in treadmill running activities. Concerning activity intensity classification accuracy, Pate (kappa=0.72) had the best performance across the four intensities (sedentary, light, moderate, vigorous). In case of the sedentary activities, all equations had a good prediction accuracy, while with light activities and Vigorous activities, Pate had an excellent accuracy (ROC-AUC=0.91, 0.94). For Moderate activities, all equations showed a poor performance. Conclusions: In conclusion, none of the assessed equations was accurate in predicting energy expenditure across all assessed activities in athletic children. For activity intensity classification, Pate had the best prediction accuracy.