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Jordan Andre Martenstyn, Lauren Powell, Natasha Nassar, Mark Hamer and Emmanuel Stamatakis

.2.241 2305711 21. Lee SH , Kim EK . Accuracy of predictive equations for resting metabolic rates and daily energy expenditures of police officials doing shift work by type of work . Clin Nutr Res . 2012 ; 1 ( 1 ): 66 – 77 . PubMed ID: 23429979 doi: 10.7762/cnr.2012.1.1.66 23429979 22. Stamatakis E

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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

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.

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Lisa H. Colbert, Charles E. Matthews, Dale A. Schoeller, Thomas C. Havighurst and KyungMann Kim

This study examined the intensity of activity contributing to physical activity energy expenditure in older adults. In 57 men and women aged ≥ 65, total energy expenditure (TEE) was measured using doubly labeled water and resting metabolic rate was measured using indirect calorimetry to calculate a physical activity index (PAI). Sedentary time and physical activity of light and moderate to vigorous (mod/vig) intensity was measured using an accelerometer. The subjects were 75 ± 7 yrs (mean ± SD) of age and 79% female. Subjects spent 66 ± 8, 25 ± 5, and 9 ± 4% of monitor wear time in sedentary, light, and mod/vig activity per day, respectively. In a mixture regression model, both light (β = 29.6 [15.6–43.6, 95% CI]), p < .001) and mod/vig intensity activity (β = 28.7 [7.4−50.0, 95% CI]), p = .01) were strongly associated with PAI, suggesting that both light and mod/vig intensity activities are major determinants of their physical activity energy expenditure.

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Miguel Camões, Andreia Oliveira and Carla Lopes

Objective:

Evaluate the role of different types of physical activity (PA) and diet on overall and central obesity incidence.

Methods:

A cohort study with 1621 adults was conducted in an urban Portuguese population. Anthropometrics were objectively obtained during 1999−2003 and 2005−2008. Overall, obesity was defined by a body mass index (BMI) ≥ 30.0 kg/m2 and central obesity by a waist circumference (WC) > 88.0 cm in women and >102.0 cm in men. Usual PA and dietary intake were assessed using validated questionnaires. Analyses of obesity incidence were conducted through different types of PA and a “healthy” dietary score.

Results:

Significant inverse associations were found between leisure-time PA and obesity incidence, namely among subjects classified into the last tertile of energy expenditure, who had approximately a 40% lower risk of developing the disease. Despite higher energy intakes, individuals with a high Physical Activity Level (PAL > 1.60) were significantly protected against obesity incidence, relative risks (RR) = 0.25 (0.09−0.72) and RR = 0.47(0.27−0.94), for overall and central obesity, respectively. No significant associations were found between dietary score and obesity incidence rates.

Conclusions:

In our population, leisure-time PA played a significant role in preventing obesity. In both overall and central obesity, PAL above 60% of the resting metabolic rate and moderate energy intake seem to strike the right balance to prevent obesity.

Open access

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.

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.

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Nicolas Aguilar-Farias, Wendy J. Brown, Tina L. Skinner and G.M.E.E. (Geeske) Peeters

each activity for at least 5 minutes and remain silent during the recording period. EE was used as a proxy for resting metabolic rate (RMR) while lying down and remaining silent in a quiet environment without disturbance. During the walking activity, participants were asked to walk at their usual

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Mirko Brandes, Berit Steenbock and Norman Wirsik

calculated as the metabolic rate observed for a specific activity divided by the resting metabolic rate. However, only 35% of the METs included in the CEEY are based on measured data in youth. Instead, the majority of MET values were adopted from the adults’ compendium and expert opinions. 2 , 3 In addition

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Mindy Patterson, Wanyi Wang and Alexis Ortiz

body mass is one of the factors related to lower resting metabolic rate in older adults during both arousal and sleeping hours ( Manini, 2010 ; Manini et al., 2006 ; St-Onge & Gallagher, 2010 ). Males have higher lean body mass than females, thus have a higher EE at rest. However, previous studies