scholarly journals Metabolic Equivalents of Selected Sedentary and Physical Activities in Chinese Youth

2016 ◽  
Vol 13 (s1) ◽  
pp. S48-S52 ◽  
Author(s):  
Yong Gao ◽  
Haichun Sun ◽  
Jie Zhuang ◽  
Jian Zhang ◽  
Lynda Ransdell ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Computer Games ◽  
Resting Metabolic Rate ◽  
Physical Activities ◽  
Daily Activities ◽  
Chinese Youth ◽  
Metabolic Chamber ◽  
Metabolic Equivalents ◽  
Watching Tv ◽  
Jump Rope

Background:This study determined the metabolic equivalents (METs) of several activities typically performed by Chinese youth.Methods:Thirty youth (12 years) performed 7 activities that reflected their daily activities while Energy Expenditure (EE) was measured in a metabolic chamber.Results:METs were calculated as activity EE divided by participant’s measured resting metabolic rate. A MET value ranging from 0.8 to 1.2 was obtained for sleeping, watching TV, playing computer games, reading and doing homework. Performing radio gymnastics had a MET value of 2.9. Jumping rope at low effort required 3.1 METs. Except for watching TV, METs for other activities in this study were lower than Youth Compendium values.Conclusions:The results provide empirical evidence for more accurately assessing EE of activities commonly performed by Chinese youth. This is the first study to determine METs for radio gymnastics and jump rope in Chinese youth.

scholarly journals Energy Expenditure of Daily Living Activities in 3- to 6-Year-Old Children

2016 ◽  
Vol 13 (s1) ◽  
pp. S3-S6 ◽  
Author(s):  
Wonwoo Byun ◽  
Allison Barry ◽  
Jung-Min Lee
Keyword(s):  
Oxygen Consumption ◽  
Energy Expenditure ◽  
Young Children ◽  
Indirect Calorimetry ◽  
Daily Living ◽  
Physical Activities ◽  
Daily Living Activities ◽  
Watching Tv

Background:There has been a call for updating the Youth Compendium of Energy Expenditure (YCEE) by including energy expenditure (EE) data of young children (ie, < 6-year-old children). Therefore, this study examined the activity EE in 3 to 6 year old children using indirect calorimetry.Methods: Using Oxycon Mobile portable indirect calorimetry, both the oxygen consumption (VO2) and the EE of 28 children (Girls: 46%, Age: 4.8 ± 1.0, BMI: 16.4 ± 1.6) were measured while they performed various daily living activities (eg, watching TV, playing with toys, shooting baskets, soccer).Results:Across physical activities, averages of VO2 (ml·kg·min-1), VO2 (L·min-1), and EE ranged from 8.9 ± 1.5 to 33.3 ± 4.8 ml·kg·min-1, from 0.17 ± 0.04 to 0.64 ± 0.16 L·min-1, and from 0.8 ± 0.2 to 3.2 ± 0.7 kcal·min-1, respectively.Conclusions:These findings will contribute to the upcoming YCEE update.

scholarly journals The Energy Expenditure of Free-Living Physical Activities in Primary Schoolchildren

2016 ◽  
Vol 13 (s1) ◽  
pp. S57-S61 ◽  
Author(s):  
Alison L. Innerd ◽  
Liane B. Azevedo
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Resting Metabolic Rate ◽  
Physical Activities ◽  
Free Living ◽  
Metabolic Equivalent ◽  
Primary Schoolchildren ◽  
Vigorous Intensity

Background:The aim of this study is to establish the energy expenditure (EE) of a range of child-relevant activities and to compare different methods of estimating activity MET.Methods:27 children (17 boys) aged 9 to 11 years participated. Participants were randomly assigned to 1 of 2 routines of 6 activities ranging from sedentary to vigorous intensity. Indirect calorimetry was used to estimate resting and physical activity EE. Activity metabolic equivalent (MET) was determined using individual resting metabolic rate (RMR), the Harrell-MET and the Schofield equation.Results:Activity EE ranges from 123.7± 35.7 J/min/Kg (playing cards) to 823.1 ± 177.8 J/min/kg (basketball). Individual RMR, the Harrell-MET and the Schofield equation MET prediction were relatively similar at light and moderate but not at vigorous intensity. Schofield equation provided a better comparison with the Compendium of Energy Expenditure for Youth.Conclusion:This information might be advantageous to support the development of a new Compendium of Energy Expenditure for Youth.

scholarly journals Energy expenditure of type-specific sedentary behaviors estimated using sensewear mini armband

Kinesiology ◽  
2018 ◽  
Vol 50 (1) ◽  
pp. 52-56
Author(s):  
Jing Jin ◽  
Jie Zhuang
Keyword(s):  
Energy Expenditure ◽  
Metabolic Rate ◽  
Children And Adolescents ◽  
Error Rate ◽  
Basal Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Absolute Error ◽  
Sedentary Behaviors ◽  
Metabolic Chamber ◽  
Physiological Sensors

SenseWear Mini Armband, an accelerometer with multiple physiological sensors, could be a practical means to estimate energy expenditure (EE) of children and adolescents, but its validity reported for these age&nbsp;groups has not been consistent within the literature. EE of twenty-six healthy Chinese 12-year-old adolescents was measured simultaneously using both SenseWear Mini Armband (SWMA) and metabolic chamber (MC) during a 16-hour stay in a MC. SWMA systematically underestimated the adolescents’ EE during sedentary behaviors, resting metabolic rate (RMR), basal metabolic rate (BMR), and total EE, with the absolute error rate ranging from 14.85% to 28.65%. The SWMA significantly underestimated EE compared with MC in Chinese adolescents. However, the amount of error can be reduced by applying correction equation proposed in this study.

scholarly journals Energy cost of selected training and non-training activities of 10-17-year-old Indian athletes: a cross-sectional study

2020 ◽  
Author(s):  
Keren Susan Cherian ◽  
Ashok Sainoji ◽  
Balakrishna Nagalla ◽  
Venkata Ramana Yagnambhatt
Keyword(s):  
Energy Expenditure ◽  
Energy Cost ◽  
Strong Association ◽  
Cross Sectional Study ◽  
Physical Activities ◽  
Sectional Study ◽  
Cross Sectional ◽  
Metabolic Equivalents ◽  
Junior Athletes ◽  
Training Activities

Abstract Background Factorial approach using activity recording and metabolic equivalents (METs) is most often used to compute 24-hr energy expenditure pattern among athletes. However, the existing compendiums for energy cost of physical activities were developed on non-athlete adults or children. Therefore, the present study aimed to determine the energy cost of selected physical activities of junior athletes. Further, the suitability of existing compendiums among Indian junior athletes were assessed.Methods In this cross-sectional study, 91 Indian junior athletes (Boys: 45 and Girls: 46) from athletics, soccer and weightlifting events, were monitored for their activity pattern (Rest, Training and non-training activities) and volume of oxygen consumed (ml/kg/min) using portable metabolic analyser. Sex and/or age-specific differences were determined using ANOVA and measured METs were compared with Compendium of Physical Activity (CPA) and Compendium of Energy Expenditure for Youth (CEEY) using single-sample t-test.Results The energy cost and METs showed sex-specific differences with a strong association between measured Heart rate and METs. The measured METs covered a range of physical activities from 0.7 (Resting Metabolic Rate; RMR) to 10.8 (shuttle run). On comparison with compendium, measured METs for RMR was significantly higher in junior athletes, except in soccer players (junior boys and girls) having lower METs. For majority of the activities, measured METs were comparable with adult compendium (CPA), than children’s (CEEY).Conclusions Thus, the METs determined on Indian junior athletes adds to the existing database and is useful to evaluate energy expenditure. Further, in the absence of athlete-specific compendium, CPA seems prudent for determining energy needs.

scholarly journals No major differences in energy metabolism between matched and unmatched groups of ‘large-eating’ and ‘small-eating’ men

1993 ◽  
Vol 70 (2) ◽  
pp. 393-406 ◽  
Author(s):  
Dallas Clark ◽  
Frank Tomas ◽  
Robert T. Withers ◽  
Sally D. Neville ◽  
Stephen R. Nolan ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Resting Metabolic Rate ◽  
Normal Weight ◽  
Fat Free Mass ◽  
Daily Activities ◽  
Energy Requirements ◽  
Energy Expenditures ◽  
Thermic Effect Of Food ◽  
Effect Of Food ◽  
Thermic Effect

Rates of energy expenditure (J/kg fat-free mass (FFM) per min) in normal weight, ‘small-eating’ men were compared with those obtained for normal weight (n 8) and underweight (n 5) ‘large-eating’ men. For the matched groups of ‘large-’ and ‘small-eaters’ there were no differences in resting metabolic rate (RMR) measurements but during controlled daily activities there was a small but significant increase (P < 0.05) in energy expenditure in the ‘large-eaters’. These results contrast with those obtained for the unmatched groups where energy requirements were about 10 % (P < 0.01) higher in the underweight ‘large-eaters’ at rest but were not different during the more energetic (walking) activities. However, after adjustment for differences in FFM between these two groups, the resting energy expenditures of the ‘large-eaters’ (82·54 (SE 1·51) J/kg FFM per min) were similar to those of the ‘small-eaters’ (81·87 (SE 1·51) J/kg FFM per min). Oral temperatures were significantly higher in the matched (0·35–0·65°) and unmatched (0·7–0·9°) ‘large-eaters’ both at rest and during the different activities, but the thermic effect of food (50 kJ/kg FFM) was one fifth lower (not significant) in both groups of ‘large-eaters’. These results provide little evidence for any major metabolic differences between groups of ‘large-eating’ and ‘small-eating’ men.

scholarly journals Youth Energy Expenditure During Common Free-Living Activities and Treadmill Walking

2016 ◽  
Vol 13 (s1) ◽  
pp. S29-S34 ◽  
Author(s):  
John M. Schuna ◽  
Tiago V. Barreira ◽  
Daniel S. Hsia ◽  
William D. Johnson ◽  
Catrine Tudor-Locke
Keyword(s):  
Energy Expenditure ◽  
Oxygen Uptake ◽  
Physical Activities ◽  
Treadmill Walking ◽  
Stair Climbing ◽  
Free Living ◽  
Metabolic Equivalents ◽  
Age Related ◽  
Age Trends ◽  
Age Range

Background:Energy expenditure (EE) estimates for a broad age range of youth performing a variety of activities are needed.Methods:106 participants (6–18 years) completed 6 free-living activities (seated rest, movie watching, coloring, stair climbing, basketball dribbling, jumping jacks) and up to 9 treadmill walking bouts (13.4 to 120.7 m/min; 13.4 m/min increments). Breath-by-breath oxygen uptake (VO2) was measured using the COSMED K4b2 and EE was quantified as youth metabolic equivalents (METy1:VO2/measured resting VO2, METy2:VO2/estimated resting VO2). Age trends were evaluated with ANOVA.Results:Seated movie watching produced the lowest mean METy1 (6- to 9-year-olds: 0.94 ± 0.13) and METy2 values (13- to 15-year-olds: 1.10 ± 0.19), and jumping jacks produced the highest mean METy1 (13- to 15-year-olds: 6.89 ± 1.47) and METy2 values (16- to 18-year-olds: 8.61 ± 2.03). Significant age-related variability in METy1 and METy2 were noted for 8 and 2 of the 15 evaluated activities, respectively.Conclusions:Descriptive EE data presented herein will augment the Youth Compendium of Physical Activities.

scholarly journals Self -Monitoring system for diabetic individuals based on 3 -axis accelerometer

2017 ◽  
Vol 20 (K3) ◽  
pp. 132-140
Author(s):  
Hanh Ngoc Dang
Keyword(s):  
Diabetes Mellitus ◽  
Energy Expenditure ◽  
Success Rate ◽  
Monitoring System ◽  
Daily Activities ◽  
Monitoring Systems ◽  
Self Monitoring ◽  
Metabolic Equivalents ◽  
Wide Range

In this study, we aim to develop a miniaturized stand-alone system that can detect a wide range of daily activities based on a single integrated consumer 3-axis accelerometer. A novel k-means based classification algorithm was constructed to interpret and translate signals from accelerometer into a recognizable cluster of pre-defined activities. The developed system has given encouraging results with a 100% success rate of classification of the three basic classes of activities based on resting, walking and running, and an 84% success rate for the lower level of different pace of walking and running. The potential extension towards self-monitoring systems for people suffering from diabetes mellitus has been considered by converting the activities into metabolic equivalents that will help predict the associated energy expenditure.

Determination of total energy expenditure, resting metabolic rate and physical activity in lean and overweight people

1997 ◽  
Vol 36 (4) ◽  
pp. 310-312 ◽  
Author(s):  
F. Thielecke ◽  
J. Möseneder ◽  
A. Kroke ◽  
K. Klipstein-Grobusch ◽  
H. Boeing ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Total Energy ◽  
Resting Metabolic Rate ◽  
Total Energy Expenditure ◽  
Overweight People

Metabolic equivalents of physical activities in Indians: a systematic review

Physiotherapy ◽  
2015 ◽  
Vol 101 ◽  
pp. e1584
Author(s):  
S.K. Veluswamy ◽  
S. Samuel ◽  
A. Maiya ◽  
S. Nair
Keyword(s):  
Systematic Review ◽  
Physical Activities ◽  
Metabolic Equivalents

Energy Expenditure of Level Overground Walking in Young Adults: Comparison With Prediction Equations

2021 ◽  
pp. 1-8
Author(s):  
Jingjing Xue ◽  
Shuo Li ◽  
Rou Wen ◽  
Ping Hong
Keyword(s):  
Young Adults ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Energy Cost ◽  
Sports Medicine ◽  
Resting Metabolic Rate ◽  
Prediction Equations ◽  
Overground Walking ◽  
All Speeds ◽  
Walking Energy Cost

Background: The purpose of this study was to investigate the accuracy of the published prediction equations for determining level overground walking energy cost in young adults. Methods: In total, 148 healthy young adults volunteered to participate in this study. Resting metabolic rate and energy expenditure variables at speeds of 4, 5, and 6 km/h were measured by indirect calorimetry, walking energy expenditure was estimated by 3 published equations. Results: The gross and net metabolic rate per mile of level overground walking increased with increased speed (all P < .01). Females were less economical than males. The present findings revealed that the American College of Sports Medicine and Pandolf et al equations significantly underestimated the energy cost of overground walking at all speeds (all P < .01) in young adults. The percentage mean bias for American College of Sports Medicine, Pandolf et al, and Weyand et al was 12.4%, 16.8%, 1.4% (4 km/h); 21.6%, 15.8%, 7.1% (5 km/h); and 27.6%, 12%, 6.6% (6 km/h). Bland–Altman plots and prediction error analysis showed that the Weyand et al was the most accurate in 3 existing equations. Conclusions: The Weyand et al equation appears to be the most suitable for the prediction of overground walking energy expenditure in young adults.

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