Browse

You are looking at 161 - 170 of 285 items for :

  • Psychology and Behavior in Sport/Exercise x
  • Sport and Exercise Science/Kinesiology x
  • User-accessible content x
Clear All
Open access

Jeffery J. Honas, Erik A. Willis, Stephen D. Herrmann, Jerry L. Greene, Richard A. Washburn and Joseph E. Donnelly

Background:

There is limited data regarding objectively measured energy cost and intensity of classroom instruction. Therefore, the purpose of current study was to objectively measure energy cost and subsequently calculate MET values using a portable indirect calorimeter (IC) for both normal classroom instruction (NCI) and active classroom instruction (ACI).

Methods:

We assessed energy expenditure (EE) and intensity levels (METs) in elementary school children (17 boys and 15 girls) using an IC (COSMED K4b2). Independent t-tests were used to evaluate potential sex and grade level differences for age, BMI, VO2, EE, and METs.

Results:

The average EE for NCI and ACI were 1.8 ± 0.4 and 3.9 ± 1.0, respectively. The average intensity level for NCI and ACI were 1.9 ± 0.4 and 4.2 ± 0.9 METs, respectively.

Conclusions:

PA delivered through ACI can elicit EE at a moderate intensity level. These results provide evidence for ACI as a convenient/feasible avenue for increasing PA in youth without decreasing instruction time.

Open access

Jeffer Eidi Sasaki, Cheryl A. Howe, Dinesh John, Amanda Hickey, Jeremy Steeves, Scott Conger, Kate Lyden, Sarah Kozey-Keadle, Sarah Burkart, Sofiya Alhassan, David Bassett Jr and Patty S. Freedson

Background:

Thirty-five percent of the activities assigned MET values in the Compendium of Energy Expenditures for Youth were obtained from direct measurement of energy expenditure (EE). The aim of this study was to provide directly measured EE for several different activities in youth.

Methods:

Resting metabolic rate (RMR) of 178 youths (80 females, 98 males) was first measured. Participants then performed structured activity bouts while wearing a portable metabolic system to directly measure EE. Steady-state oxygen consumption data were used to compute activity METstandard (activity VO2/3.5) and METmeasured (activity VO2/measured RMR) for the different activities.

Results:

Rates of EE were measured for 70 different activities and ranged from 1.9 to 12.0 METstandard and 1.5 to 10.0 METmeasured.

Conclusion:

This study provides directly measured energy cost values for 70 activities in children and adolescents. It contributes empirical data to support the expansion of the Compendium of Energy Expenditures for Youth.

Open access

Melissa Lau, Li Wang, Sari Acra and Maciej S. Buchowski

Background:

Standardized measures of energy expenditure (EE) for sedentary activities in youth are needed. The goal was to determine EE of common contemporary and computer-related sedentary activities in youth.

Methods:

We measured EE for sedentary tasks in 10- to 17-year-old youths (n = 24) during ~24 hours in a whole-room indirect calorimeter. Directly monitored tasks were performed for ~10-min. EE was calculated from oxygen consumed and carbon dioxide produced, converted to metabolic equivalents (MET) by normalization to an individual’s measured resting EE, and compared with the Compendium of Energy Expenditures for Youth.

Results:

Compared with the youth compendium, measured METs were lower for internet surfing (1.3), computer keyboard typing (1.3), and sorting beads/crafts (1.5) (all P < .002), and similar for handwriting (1.4), playing cards (1.6), video-gaming (1.6), and telephoning (1.5).

Conclusions:

Current youth compendium MET estimates should be used with caution when predicting EE of common contemporary and computer-related sedentary activities in youth.

Open access

Wonwoo Byun, Allison Barry and Jung-Min Lee

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.

Open access

Alison L. Innerd and Liane B. Azevedo

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.

Open access

Jourdin Barkman, Karin Pfeiffer, Allie Diltz and Wei Peng

Background:

Replacing sedentary time with physical activity through new generation exergames (eg, XBOX Kinect) is a potential intervention strategy. The study’s purpose was to compare youth energy expenditure while playing different exergames in single- vs. multiplayer mode.

Methods:

Participants (26 male, 14 female) were 10 to 13 years old. They wore a portable metabolic analyzer while playing 4 XBOX Kinect games for 15 minutes each (2 single-, 2 multiplayer). Repeated-measures ANOVA (with Bonferroni correction) was used to examine player mode differences, controlling for age group, sex, weight status, and game.

Results:

There was a significant difference in energy expenditure between single player (mean = 15.4 ml/kg/min, SD = 4.5) and multiplayer mode (mean = 16.8 ml/kg/min, SD = 4.7). Overweight and obese participants (mean = 13.7 ml/kg/min, SD = 4.2) expended less energy than normal weight (mean = 17.8 ml/kg/min, SD = 4.5) during multiplayer mode (d = 0.93).

Conclusion:

Player mode, along with personal factors such as weight status, may be important to consider in energy expenditure during exergames.

Open access

Yong Gao, Haichun Sun, Jie Zhuang, Jian Zhang, Lynda Ransdell, Zheng Zhu and Siya Wang

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.

Open access

Stephen D. Herrmann and Karin A. Pfeiffer

Open access

Christiana M.T. van Loo, Anthony D. Okely, Marijka Batterham, Tina Hinkley, Ulf Ekelund, Soren Brage, John J. Reilly, Gregory E. Peoples, Rachel Jones, Xanne Janssen and Dylan P. Cliff

Background:

To validate the activPAL3 algorithm for predicting metabolic equivalents (TAMETs) and classifying MVPA in 5- to 12-year-old children.

Methods:

Fifty-seven children (9.2 ± 2.3y, 49.1% boys) completed 14 activities including sedentary behaviors (SB), light (LPA) and moderate-to-vigorous physical activities (MVPA). Indirect calorimetry (IC) was used as the criterion measure. Analyses included equivalence testing, Bland-Altman procedures and area under the receiver operating curve (ROC-AUC).

Results:

At the group level, TAMETs were significantly equivalent to IC for handheld e-game, writing/coloring, and standing class activity (P < .05). Overall, TAMETs were overestimated for SB (7.9 ± 6.7%) and LPA (1.9 ± 20.2%) and underestimated for MVPA (27.7 ± 26.6%); however, classification accuracy of MVPA was good (ROC-AUC = 0.86). Limits of agreement were wide for all activities, indicating large individual error (SB: −27.6% to 44.7%; LPA: −47.1% to 51.0%; MVPA: −88.8% to 33.9%).

Conclusions:

TAMETs were accurate for some SB and standing, but were overestimated for overall SB and LPA, and underestimated for MVPA. Accuracy for classifying MVPA was, however, acceptable.

Open access

John M. Schuna Jr., Tiago V. Barreira, Daniel S. Hsia, William D. Johnson and Catrine Tudor-Locke

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.