Energy Cost Expression for a Youth Compendium of Physical Activities: Rationale for Using Age Groups

in Pediatric Exercise Science

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Karin A. PfeifferMichigan State University

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Kathleen B. WatsonCenters for Disease Controland Prevention

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Robert G. McMurrayUniversity of North Carolina, Chapel Hill

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David R. BassettThe University of Tennessee, Knoxville

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Nancy F. ButteBaylor College of Medicine

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Scott E. CrouterThe University of Tennessee, Knoxville

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Stephen D. HerrmannChildren’s Health Research Center, Sanford Research

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Stewart G. TrostQueensland University of Technology

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Barbara E. AinsworthArizona State University

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Janet E. FultonCenters for Disease Control and Prevention

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David BerriganNational Cancer Institute

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For the CDC/NCI/NCCOR Research Group
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Purpose: This study compared the accuracy of physical activity energy expenditure (PAEE) prediction using 2 methods of accounting for age dependency versus 1 standard (single) value across all ages. Methods: PAEE estimates were derived by pooling data from 5 studies. Participants, 6–18 years (n = 929), engaged in 14 activities while in a room calorimeter or wearing a portable metabolic analyzer. Linear regression was used to estimate the measurement error in PAEE (expressed as youth metabolic equivalent) associated with using age groups (6–9, 10–12, 13–15, and 16–18 y) and age-in-years [each year of chronological age (eg, 12 = 12.0–12.99 y)] versus the standard (a single value across all ages). Results: Age groups and age-in-years showed similar error, and both showed less error than the standard method for cycling, skilled, and moderate- to vigorous-intensity activities. For sedentary and light activities, the standard had similar error to the other 2 methods. Mean values for root mean square error ranged from 0.2 to 1.7 youth metabolic equivalent across all activities. Error reduction ranged from −0.2% to 21.7% for age groups and −0.23% to 18.2% for age-in-years compared with the standard. Conclusions: Accounting for age showed lower errors than a standard (single) value; using an age-dependent model in the Youth Compendium is recommended.

Pfeiffer is with the Dept. of Kinesiology, Michigan State University, East Lansing, MI. Watson and Fulton are with the Division of Nutrition, Physical Activity, and Obesity, Centers for Disease Control and Prevention, Atlanta, GA. McMurray is with the Dept. of Exercise and Sport Science and Nutrition, University of North Carolina, Chapel Hill, NC. Bassett and Crouter are with the Dept. of Kinesiology, Recreation and Sport Studies, The University of Tennessee, Knoxville, Knoxville, TN. Butte is with USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, Houston, TX. Herrmann is with Children’s Health Research Center, Sanford Research, Sioux Falls, SD. Trost is with the Institute of Health and Biomedical Innovation at Queensland Centre for Children’s Health Research, Queensland University of Technology, Brisbane, Queensland, Australia. Ainsworth is with the School of Nutrition and Health Promotion, Arizona State University, Phoenix, AZ. Berrigan is with National Cancer Institute, Bethesda, MD.

Address author correspondence to Karin A. Pfeiffer at kap@msu.edu.
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  • 1.

    Ainsworth BE, Haskell WL, Herrmann SD, et al. Compendium of physical activities: a second update of codes and MET values. Med Sci Sports Exerc. 2011;43(8):157581. PubMed doi:10.1249/MSS.0b013e31821ece12

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Ainsworth BE, Haskell WL, Leon AS, et al. Compendium of physical activities: classification of energy costs ofhuman physical activities. Med Sci Sports Exerc. 1993;25(1):7180. PubMed doi:10.1249/00005768-199301000-00011

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Ainsworth BE, Haskell WL, Whitt MC, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32 Suppl 9498504. PubMed

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4.

    Butte NF, Wong WW, Adolph AL, Puyau MR, Vohra FA, Zakeri IF. Validation of cross-sectional time series and multivariate adaptive regression splines models for the prediction of energy expenditure in children and adolescents using doubly labeled water. J Nutr. 2010;140(8):151623. PubMed doi:10.3945/jn.109.120162

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Crouter SE, Horton M, Bassett DR Jr. Use of a two-regression model for estimating energy expenditure in children. Med Sci Sports Exerc. 2012;44(6):117785. PubMed doi:10.1249/MSS.0b013e3182447825

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Crouter SE, Horton M, Bassett DR Jr. Validity of ActiGraph child-specific equations during various physical activities. Med Sci Sports Exerc. 2013;45(7):14039. PubMed doi:10.1249/MSS.0b013e318285f03b

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Harrell JS, McMurray RG, Baggett CD, Pennell ML, Pearce PF, Bangdiwala SI. Energy costs of physical activities in children and adolescents. Med Sci Sports Exerc. 2005;37(2):32936. PubMed doi:10.1249/01.MSS.0000153115.33762.3F

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Kozey S, Lyden K, Staudenmayer J, Freedson P. Errors in MET estimates of physical activities using 3.5 ml·kg−1·min−1 as the baseline oxygen consumption. J Phys Act Health. 2010;7(4):50816. PubMed doi:10.1123/jpah.7.4.508

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9.

    Malina RM, Bouchard C, Bar-Or O. Growth, Maturation and Physical Activity. 2nd ed. Champaign, IL: Human Kinetics; 2004, pp. 30810.

  • 10.

    McMurray RG, Butte NF, Crouter SE, et al. Exploring metrics to express energy expenditure of physical activity in youth. PLoS ONE. 2015;10(6):e0130869. PubMed doi:10.1371/journal.pone.0130869

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Pate RR, Ross R, Dowda M, Trost SG, Sirard JR. Validation of a 3-day physical activity recall instrument in female youth. Pediatr Exerc Sci. 2003;15(3):25765. doi:10.1123/pes.15.3.257

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12.

    Ridley K, Ainsworth BE, Olds TS. Development of a compendium of energy expenditures for youth. Int J Behav Nutr Phys Act. 2008;5:45. PubMed doi:10.1186/1479-5868-5-45

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Ridley K, Olds TS. Assigning energy costs to activities in children: a review and synthesis. Med Sci Sports Exerc. 2008;40(8):143946. PubMed doi:10.1249/MSS.0b013e31817279ef

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Rowland T. Children’s Exercise Physiology. 2nd ed. Champaign, IL: Human Kinetics; 2005, pp. 804.

  • 15.

    Sallis JF, Strikmiller PK, Harsha DW, et al. Validation of interviewer- and self- administered physical activity checklists for fifth grade students. Med Sci Sports Exerc. 1996;28(7):84051. PubMed doi:10.1097/00005768-199607000-00011

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Schofield WN. Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr. 1985;39  Suppl 1 :541. PubMed

  • 17.

    Trost SG, Loprinzi PD, Moore R, Pfeiffer KA. Comparison of accelerometer cut points for predicting activity intensity in youth. Med Sci Sports Exerc2011;43(7):13608. PubMed doi:10.1249/MSS.0b013e318206476e

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
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