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

Most subjective and objective methods for measuring physical activity depend to some extent on the use of metabolic equivalent (MET) values. These MET values are used to account for the intensity of different activities when estimating total energy expenditure (EE) during a period, or to classify

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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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Catrine Tudor-Locke, Barbara E. Ainsworth, Tracy L. Washington and Richard Troiano

Background:

The Current Population Survey (CPS) and the American Time Use Survey (ATUS) use the 2002 census occupation system to classify workers into 509 separate occupations arranged into 22 major occupational categories.

Methods:

We describe the methods and rationale for assigning detailed Metabolic Equivalent (MET) estimates to occupations and present population estimates (comparing outputs generated by analysis of previously published summary MET estimates to the detailed MET estimates) of intensities of occupational activity using the 2003 ATUS data comprised of 20,720 respondents, 5323 (2917 males and 2406 females) of whom reported working 6+ hours at their primary occupation on their assigned reporting day.

Results:

Analysis using the summary MET estimates resulted in 4% more workers in sedentary occupations, 6% more in light, 7% less in moderate, and 3% less in vigorous compared with using the detailed MET estimates. The detailed estimates are more sensitive to identifying individuals who do any occupational activity that is moderate or vigorous in intensity resulting in fewer workers in sedentary and light intensity occupations.

Conclusions:

Since CPS/ATUS regularly captures occupation data it will be possible to track prevalence of the different intensity levels of occupations. Updates will be required with inevitable adjustments to future occupational classification systems.

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Mallory S. Kobak, Andrew Lepp, Michael J. Rebold, Hannah Faulkner, Shannon Martin and Jacob E. Barkley

effects of sex ( F  ≤ 1.2, P  ≥ .3), it was removed. Therefore, differences across conditions for accelerometer counts, sedentary minutes, RPE, and liking during each 30-minute session were assessed via 1-way analysis of variances with repeated measures on condition. Metabolic equivalents (METs) were

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Yuki Hikihara, Shigeho Tanaka, Kazunori Ohkawara, Kazuko Ishikawa-Takata and Izumi Tabata

Background:

The current study evaluated the validity of 3 commercially-available accelerometers to assess metabolic equivalent values (METs) during 12 activities.

Methods:

Thirty-three men and thirty-two women were enrolled in this study. The subjects performed 5 nonlocomotive activities and 7 locomotive movements. The Douglas bag method was used to gather expired air. The subjects also wore 3 hip accelerometers, a Lifecorder uniaxial accelerometer (LC), and 2 triaxial accelerometers (ActivTracer, AT; Actimarker, AM).

Results:

For nonlocomotive activities, the LC largely underestimated METs for all activities (20.3%–55.6%) except for desk work. The AT overestimated METs for desk work (11.3%) and hanging clothes (11.7%), but underestimated for vacuuming (2.3%). The AM underestimated METs for all nonlocomotive activities (8.0%–19.4%) except for hanging clothes (overestimated by 16.7%). The AT and AM errors were significant, but much smaller than the LC errors (23.2% for desk work and –22.3 to –55.6% for the other activities). For locomotive movements, the 3 accelerometers significantly underestimated METs for all activities except for climbing down stairs.

Conclusions:

We conclude that there were significant differences for most activities in 3 accelerometers. However, the AT, which uses separate equations for nonlocomotive and locomotive activities, was more accurate for nonlocomotive activities than the LC.

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Jung Eun Lee, David F. Stodden and Zan Gao

Background:

Few studies have examined young children’s leisure- and school-based energy expenditure (EE) and moderateto-vigorous physical activity (MVPA). The purpose of this study was to explore children’s estimated EE rates and time spent in MVPA in 3 time segments: at-school, after-school, and weekends.

Methods:

A total of 187 second and third grade children from 2 elementary schools participated in the study. Accelerometers were used to assess children’s 5-day EE and MVPA. Multiple 2 (Grade) × 2 (Gender) ANOVAs with repeated measures (Time) were conducted to examine the differences in the outcome variables.

Results:

Significant time effects on EE and MVPA were revealed. Children’s EE rate and minutes in MVPA per day were higher during after school and weekends than at school.

Conclusions:

Although children were more active outside of school, their MVPA during weekdays and weekends still fell far short of the recommended level of 60 minutes/day.

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Tamara R. Cohen, Hugues Plourde and Kristine G. Koski

Background:

The Pregnancy Physical Activity Questionnaire (PPAQ) assesses physical activity practices of pregnant women. The purpose of this study was to identify specific pregnancy practices that were associated with a healthy gestational weight gain (GWG).

Methods:

Associations between PPAQ scores, pedometer steps, energy intakes (EI), energy expenditures (EE), and rate of GWG were assessed for 61 pregnant women in their second or third trimester during a home visit. Principle component analyses (PCA) were used to cluster PPAQ questions into Factors associated with either rate or total GWG, physical activity (PA), EE, EI, and parity.

Results:

PCA identified 3 Factors: Factor 1 associated EE with parity and child care; Factor 2 clustered several structured exercise activities; and Factor 3 grouped walking, playing with pets, and shopping with pedometer steps. Only Factor 3 clustered steps with weekly rate of GWG. EI was not associated with PA or GWG.

Conclusions:

PCA analysis identified 15 of 32 PPAQ questions that were related to increased physical activity in pregnant women, but only walking and pedometer steps were associated with GWG. Our analysis supports daily walking as the preferred PA for achieving a healthy rate of GWG.

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Heather Hayes Betz, Jonathan Myers, Alyssa Jaffe, Kimberly Smith and Ronald Dalman

Background:

Quantifying lifetime physical activity using self-reported measures is challenging due to reliance on recall, especially in older populations. The purpose of this study was to determine the 1-year reproducibility of the Veterans Physical Activity Questionnaire (VAPAQ) in a cohort of patients with documented abdominal aortic aneurysm disease (AAA).

Methods:

Subjects included men (n = 52) and women (n = 3) enrolled in AAA STOP, a randomized trial designed to test the ability of supervised exercise training to modify AAA biology and early disease progression.

Results:

The overall correlation coefficient for lifetime recreational energy expenditure between the 2 examinations was 0.93 (P < .001), with an overall difference of 26 kcal/week, a typical error (standard deviation of the differences) of 171 kcals/week, and a coefficient of variation (CV) of 15.5%.

Conclusions:

The VAPAQ is a reproducible tool to quantify lifetime energy expenditure in older adults with documented vascular disease.

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Mirko Brandes, Berit Steenbock and Norman Wirsik

To effectively estimate energy expenditure (EE) of physical activity in children, Ridley et al 1 developed the Compendium of Energy Expenditure for Youth (CEEY). The compendium designates metabolic equivalents (METs) to a broad compilation of everyday activities performed by youth. METs are

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David B. Creel, Leslie M. Schuh, Robert L. Newton Jr, Joseph J. Stote and Brenda M. Cacucci

testing, the investigator controls the workload and can link heart rate (HR) and subjective measures of exertion to speed and grade. Then, the work performed on the treadmill can be compared with previously determined metabolic demands of various activities of daily living. 4 The metabolic equivalents