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Prediction of Physical Activity Intensity with Accelerometry in Young Children

Author

Listed:
  • Chiaki Tanaka

    (Division of Integrated Sciences, J. F. Oberlin University, Tokyo 194-0294, Japan)

  • Yuki Hikihara

    (Faculty of Creative Engineering, Chiba Institute of Technology, Chiba 275-0023, Japan)

  • Takafumi Ando

    (Japan Society for the Promotion of Science, Tokyo 102-0083, Japan)

  • Yoshitake Oshima

    (Faculty of Humanities and Social Sciences, University of Marketing and Distribution Sciences, Hyogo 651-2188, Japan)

  • Chiyoko Usui

    (Waseda Institute for Sport Sciences, Waseda University, Saitama 359-1192, Japan)

  • Yuji Ohgi

    (Graduate School of Media and Governance, Keio University, Kanagawa 252-0882, Japan)

  • Koichi Kaneda

    (Faculty of Advanced Engineering, Chiba Institute of Technology, Chiba 275-0023, Japan)

  • Shigeho Tanaka

    (Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo 162-8636, Japan)

Abstract

Background : An algorithm for the classification of ambulatory and non-ambulatory activities using the ratio of unfiltered to filtered synthetic acceleration measured with a triaxial accelerometer and predictive models for physical activity intensity (METs) in adults and in elementary school children has been developed. The purpose of the present study was to derive predictive equations for METs with a similar algorithm in young children. Methods : Thirty-seven healthy Japanese children (four- to six-years old) participated in this study. The five non-ambulatory activities including low-intensity activities, and five ambulatory activities were selected. The raw accelerations using a triaxial accelerometer and energy expenditure by indirect calorimetry using the Douglas bag method during each activity were collected. Results : For non-ambulatory activities, especially light-intensity non-ambulatory activities, linear regression equations with a predetermined intercept (0.9) or quadratic equations were a better fit than the linear regression. The equations were different from those for adults and elementary school children. On the other hand, the ratios of unfiltered to filtered synthetic acceleration in non-ambulatory activities were different from those in ambulatory activities, as in adults and elementary school children. Conclusions : Our calibration model for young children could accurately predict intensity of physical activity including low-intensity non-ambulatory activities.

Suggested Citation

  • Chiaki Tanaka & Yuki Hikihara & Takafumi Ando & Yoshitake Oshima & Chiyoko Usui & Yuji Ohgi & Koichi Kaneda & Shigeho Tanaka, 2019. "Prediction of Physical Activity Intensity with Accelerometry in Young Children," IJERPH, MDPI, vol. 16(6), pages 1-11, March.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:6:p:931-:d:214072
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    References listed on IDEAS

    as
    1. Yuki Hikihara & Chiaki Tanaka & Yoshitake Oshima & Kazunori Ohkawara & Kazuko Ishikawa-Takata & Shigeho Tanaka, 2014. "Prediction Models Discriminating between Nonlocomotive and Locomotive Activities in Children Using a Triaxial Accelerometer with a Gravity-removal Physical Activity Classification Algorithm," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-11, April.
    2. Chiaki Tanaka & Masayuki Okuda & Maki Tanaka & Shigeru Inoue & Shigeho Tanaka, 2018. "Associations of Physical Activity and Sedentary Time in Primary School Children with Their Parental Behaviors and Supports," IJERPH, MDPI, vol. 15(9), pages 1-15, September.
    3. Chiaki Tanaka & John J. Reilly & Maki Tanaka & Shigeho Tanaka, 2018. "Changes in Weight, Sedentary Behaviour and Physical Activity during the School Year and Summer Vacation," IJERPH, MDPI, vol. 15(5), pages 1-19, May.
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    Cited by:

    1. Nao Koizumi & Hitomi Ogata & Yutaro Negishi & Hisashi Nagayama & Miki Kaneko & Ken Kiyono & Naomi Omi, 2023. "Energy Expenditure of Disaster Relief Operations Estimated Using a Tri-Axial Accelerometer and a Wearable Heart Rate Monitor," IJERPH, MDPI, vol. 20(9), pages 1-11, May.
    2. Chiaki Tanaka & Akiko Shikano & Natsuko Imai & Kar Hau Chong & Steven J. Howard & Kosuke Tanabe & Anthony D. Okely & Ellie K. Taylor & Shingo Noi, 2023. "Accelerometer-Measured Physical Activity and Sedentary Time among Children in Japan before and during COVID-19: A Cross-Sectional and Longitudinal Analysis," IJERPH, MDPI, vol. 20(2), pages 1-10, January.

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