.6 METs). 13 Although Mackintosh et al 13 included children aged 11.4 (0.3) years, an older population compared with our study population, their results do indicate that the energy cost of fast walking is underestimated in the compendium. This could then be even more pronounced in preschool children, as
Search Results
Energy Cost of Common Physical Activities in Preschoolers
Mirko Brandes, Berit Steenbock, and Norman Wirsik
Reexamining the Energy Cost of Sedentary Behaviors From the 2011 Adult Compendium
Rachel K. Barnett, Cory Greever, Karen Yagi, Brendan Rhoan, and Sarah Kozey Keadle
quantifying sedentary behaviors. 7 , 8 Recently, a consensus definition of sedentary behavior has been proposed that includes both posture (sitting, reclining, or lying) and low energy cost, defined as <1.5 METs. 9 Although the 2011 Adult Compendium was updated to include more “inactivities” or sedentary
Energy Cost of Running in Well-Trained Athletes: Toward Slope-Dependent Factors
Marcel Lemire, Romain Remetter, Thomas J. Hureau, Bernard Geny, Evelyne Lonsdorfer, Fabrice Favret, and Stéphane P. Dufour
factors determine RE, including metabolic, cardiopulmonary, neuromuscular, and biomechanical components, 2 and RE can also be expressed as oxygen cost (amount of oxygen consumed per unit of distance covered) or, preferentially, as energy cost of running (amount of energy used per unit of distance covered
Increasing Shoe Longitudinal Bending Stiffness Is Not Beneficial to Reduce Energy Cost During Graded Running
Titouan P. Perrin, Jeremy Rossi, Hugo A. Kerhervé, and Guillaume Y. Millet
Carbon plates have become one of the main features of high-end running shoes, which act to increase the longitudinal bending stiffness (LBS) of the shoe. Increased LBS has been shown to improve the energy cost of running (Cr) in level running (FLAT), even though Cr changes were found to range ± 3
Video Center Games: Energy Cost and Children’s Behaviors
Kate Ridley and Tim Olds
Time spent playing video games has been linked to increases in childhood obesity and sedentary behavior. However, “new generation” video games require total body movement and greater physical exertion. The aim of this study was to describe children’s behavior and energy expenditure while visiting video game centers. Observations were undertaken on 134 children’s activity patterns while playing at a video game center. The energy cost of 10 children (5 male and 5 female) aged 12.5 ± 0.5 yr, playing 4 popular video games was then measured. Gross energy cost ranged from 7.6 to 26.5 ml · kg−1 · min−1. Based on our observations, we estimate that the gross energy expenditure during a child’s typical session in a video game center will range from 2.3–2.6 METS.
Energy Cost of Activities in Preschool-Aged Children
Maurice R. Puyau, Anne L. Adolph, Yan Liu, Theresa A. Wilson, Issa F. Zakeri, and Nancy F. Butte
Background:
The absolute energy cost of activities in children increases with age due to greater muscle mass and physical capability associated with growth and developmental maturation; however, there is a paucity of data in preschool-aged children. Study aims were 1) to describe absolute and relative energy cost of common activities of preschool-aged children in terms of VO2, energy expenditure (kilocalories per minute) and child-specific metabolic equivalents (METs) measured by room calorimetry for use in the Youth Compendium of Physical Activity, and 2) to predict METs from age, sex and heart rate (HR).
Methods:
Energy expenditure (EE), oxygen consumption (VO2), HR, and child-METs of 13 structured activities were measured by room respiration calorimetry in 119 healthy children, ages 3 to 5 years.
Results:
EE, VO2, HR, and child-METs are presented for 13 structured activities ranging from sleeping, sedentary, low-, moderate- to high-active. A significant curvilinear relationship was observed between child-METs and HR (r 2 = .85; P = .001).
Conclusion:
Age-specific child METs for 13 structured activities in preschool-aged children will be useful to extend the Youth Compendium of Physical Activity for research purposes and practical applications. HR may serve as an objective measure of MET intensity in preschool-aged children.
Energy Cost of Common Activities in Children and Adolescents
Kate Lyden, Sarah Kozey Keadle, John Staudenmayer, Patty Freedson, and Sofiya Alhassan
Background:
The Compendium of Energy Expenditures for Youth assigns MET values to a wide range of activities. However, only 35% of activity MET values were derived from energy cost data measured in youth; the remaining activities were estimated from adult values.
Purpose:
To determine the energy cost of common activities performed by children and adolescents and compare these data to similar activities reported in the compendium.
Methods:
Thirty-two children (8−11 years old) and 28 adolescents (12−16 years) completed 4 locomotion activities on a treadmill (TRD) and 5 age-specific activities of daily living (ADL). Oxygen consumption was measured using a portable metabolic analyzer.
Results:
In children, measured METs were significantly lower than compendium METs for 3 activities [basketball, bike riding, and Wii tennis (1.1−3.5 METs lower)]. In adolescents, measured METs were significantly lower than compendium METs for 4 ADLs [basketball, bike riding, board games, and Wii tennis (0.3−2.5 METs lower)] and 3 TRDs [2.24 m·s-1, 1.56 m·s-1, and 1.34 m·s-1 (0.4−0.8 METs lower)].
Conclusion:
The Compendium of Energy Expenditures for Youth is an invaluable resource to applied researchers. Inclusion of empirically derived data would improve the validity of the Compendium of Energy Expenditures for Youth.
Energy Cost of Children’s Structured and Unstructured Games
Kimberly A. Clevenger, Aubrey J. Aubrey, Rebecca W. Moore, Karissa L. Peyer, Darijan Suton, Stewart G. Trost, and Karin A. Pfeiffer
Background:
Limited data are available on energy cost of common children’s games using measured oxygen consumption.
Methods:
Children (10.6 ± 2.9 years; N = 37; 26 male, 9 female) performed a selection of structured (bowling, juggling, obstacle course, relays, active kickball) and unstructured (basketball, catch, tennis, clothespin tag, soccer) activities for 5 to 30 minutes. Resting metabolic rate (RMR) was calculated using Schofield’s age- and sex-specific equation. Children wore a portable metabolic unit, which measured expired gases to obtain oxygen consumption (VO2), youth METs (relative VO2/child’s calculated RMR), and activity energy expenditure (kcal/kg/min). Descriptive statistics were used to summarize data.
Results:
Relative VO2 ranged from 16.8 ± 4.6 ml/kg/min (bowling) to 32.2 ± 6.8 ml/kg/min (obstacle course). Obstacle course, relays, active kickball, soccer, and clothespin tag elicited vigorous intensity (>6 METs), the remainder elicited moderate intensity (3–6 METs).
Conclusions:
This article contributes energy expenditure data for the update and expansion of the youth compendium.
Developmental Trends in the Energy Cost of Physical Activities Performed by Youth
Stewart G. Trost, Christopher C. Drovandi, and Karin Pfeiffer
Background:
Published energy cost data for children and adolescents are lacking. The purpose of this study was to measure and describe developmental trends in the energy cost of 12 physical activities commonly performed by youth.
Methods:
A mixed age cohort of 209 participants completed 12 standardized activity trials on 4 occasions over a 3-year period (baseline, 12-months, 24-months, and 36-months) while wearing a portable indirect calorimeter. Bayesian hierarchical regression was used to link growth curves from each age cohort into a single curve describing developmental trends in energy cost from age 6 to 18 years.
Results:
For sedentary and light-intensity household chores, YOUTH METs (METy) remained stable or declined with age. In contrast, METy values associated with brisk walking, running, basketball, and dance increased with age.
Conclusions:
The reported energy costs for specific activities will contribute to efforts to update and expand the youth compendium.
Energy Expenditure of Level Overground Walking in Young Adults: Comparison With Prediction Equations
Jingjing Xue, Shuo Li, Rou Wen, and Ping Hong
equations are the 2 most commonly used leading equations, and they were both derived from small sample population. The ACSM walking equations were developed from data on 3 male adults. 9 Pandolf et al 13 established a model from experimental data collected from soldiers to predict the energy cost of
