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Robust Compositional Analysis of Physical Activity and Sedentary Behaviour Data

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Listed:
  • Nikola Štefelová

    (Faculty of Science, Palacký University Olomouc, 771 11 Olomouc, Czech Republic)

  • Jan Dygrýn

    (Faculty of Physical Culture, Palacký University Olomouc, 771 11 Olomouc, Czech Republic)

  • Karel Hron

    (Faculty of Science, Palacký University Olomouc, 771 11 Olomouc, Czech Republic)

  • Aleš Gába

    (Faculty of Physical Culture, Palacký University Olomouc, 771 11 Olomouc, Czech Republic)

  • Lukáš Rubín

    (Faculty of Physical Culture, Palacký University Olomouc, 771 11 Olomouc, Czech Republic)

  • Javier Palarea-Albaladejo

    (Biomathematics and Statistics Scotland, JCMB, The King’s Buildings, Edinburgh EH9 3FD, UK)

Abstract

Although there is an increasing awareness of the suitability of using compositional data methodology in public health research, classical methods of statistical analysis have been primarily used so far. The present study aims to illustrate the potential of robust statistics to model movement behaviour using Czech adolescent data. We investigated: (1) the inter-relationship between various physical activity (PA) intensities, extended to model relationships by age; and (2) the associations between adolescents’ PA and sedentary behavior (SB) structure and obesity. These research questions were addressed using three different types of compositional regression analysis—compositional covariates, compositional response, and regression between compositional parts. Robust counterparts of classical regression methods were used to lessen the influence of possible outliers. We outlined the differences in both classical and robust methods of compositional data analysis. There was a pattern in Czech adolescents’ movement/non-movement behavior—extensive SB was related to higher amounts of light-intensity PA, and vigorous PA ratios formed the main source of potential aberrant observations; aging is associated with more SB and vigorous PA at the expense of light-intensity PA and moderate-intensity PA. The robust counterparts indicated that they might provide more stable estimates in the presence of outlying observations. The findings suggested that replacing time spent in SB with vigorous PA may be a powerful tool against adolescents’ obesity.

Suggested Citation

  • Nikola Štefelová & Jan Dygrýn & Karel Hron & Aleš Gába & Lukáš Rubín & Javier Palarea-Albaladejo, 2018. "Robust Compositional Analysis of Physical Activity and Sedentary Behaviour Data," IJERPH, MDPI, vol. 15(10), pages 1-18, October.
  • Handle: RePEc:gam:jijerp:v:15:y:2018:i:10:p:2248-:d:175551
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    References listed on IDEAS

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    1. Agerbo, Esben & Sterne, Jonathan A.C. & Gunnell, David J., 2007. "Combining individual and ecological data to determine compositional and contextual socio-economic risk factors for suicide," Social Science & Medicine, Elsevier, vol. 64(2), pages 451-461, January.
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    1. Suzanne Lerato Merkus & Pieter Coenen & Mikael Forsman & Stein Knardahl & Kaj Bo Veiersted & Svend Erik Mathiassen, 2022. "An Exploratory Study on the Physical Activity Health Paradox—Musculoskeletal Pain and Cardiovascular Load during Work and Leisure in Construction and Healthcare Workers," IJERPH, MDPI, vol. 19(5), pages 1-17, February.
    2. Luiz Augusto Brusaca & Dechristian França Barbieri & Svend Erik Mathiassen & Andreas Holtermann & Ana Beatriz Oliveira, 2021. "Physical Behaviours in Brazilian Office Workers Working from Home during the COVID-19 Pandemic, Compared to before the Pandemic: A Compositional Data Analysis," IJERPH, MDPI, vol. 18(12), pages 1-11, June.
    3. David M. Hallman & Svend Erik Mathiassen & Allard J. van der Beek & Jennie A. Jackson & Pieter Coenen, 2019. "Calibration of Self-Reported Time Spent Sitting, Standing and Walking among Office Workers: A Compositional Data Analysis," IJERPH, MDPI, vol. 16(17), pages 1-15, August.
    4. Margo Ketels & Charlotte Lund Rasmussen & Mette Korshøj & Nidhi Gupta & Dirk De Bacquer & Andreas Holtermann & Els Clays, 2020. "The Relation between Domain-Specific Physical Behaviour and Cardiorespiratory Fitness: A Cross-Sectional Compositional Data Analysis on the Physical Activity Health Paradox Using Accelerometer-Assesse," IJERPH, MDPI, vol. 17(21), pages 1-17, October.
    5. Mayara S. Bianchim & Melitta A. McNarry & Anne Holland & Narelle S. Cox & Julianna Dreger & Alan R. Barker & Craig A. Williams & Sarah Denford & Kelly A. Mackintosh, 2022. "A Compositional Analysis of Physical Activity, Sedentary Time, and Sleep and Associated Health Outcomes in Children and Adults with Cystic Fibrosis," IJERPH, MDPI, vol. 19(9), pages 1-15, April.
    6. Ryan Donald Burns & Timothy A. Brusseau & Yang Bai & Wonwoo Byun, 2021. "Segmented School Physical Activity and Weight Status in Children: Application of Compositional Data Analysis," IJERPH, MDPI, vol. 18(6), pages 1-11, March.
    7. Dorothea Dumuid & Željko Pedišić & Javier Palarea-Albaladejo & Josep Antoni Martín-Fernández & Karel Hron & Timothy Olds, 2020. "Compositional Data Analysis in Time-Use Epidemiology: What, Why, How," IJERPH, MDPI, vol. 17(7), pages 1-17, March.
    8. Meiyuan Chen & Terence Chua & Zhi Shen & Lee Yong Tay & Xiaozan Wang & Michael Chia, 2022. "The Associations between 24-Hour Movement Behaviours and Quality of Life in Preschoolers: A Compositional Analysis of Cross-Sectional Data from 2018–2021," IJERPH, MDPI, vol. 19(22), pages 1-19, November.
    9. Stuart J. Fairclough & Liezel Hurter & Dorothea Dumuid & Ales Gába & Alex V. Rowlands & Borja del Pozo Cruz & Ashley Cox & Matteo Crotti & Lawrence Foweather & Lee E. F. Graves & Owen Jones & Deborah , 2022. "The Physical Behaviour Intensity Spectrum and Body Mass Index in School-Aged Youth: A Compositional Analysis of Pooled Individual Participant Data," IJERPH, MDPI, vol. 19(14), pages 1-15, July.
    10. Kar Hau Chong & Anne-Maree Parrish & Dylan P. Cliff & Dorothea Dumuid & Anthony D. Okely, 2021. "Cross-Sectional and Longitudinal Associations between 24-Hour Movement Behaviours, Recreational Screen Use and Psychosocial Health Outcomes in Children: A Compositional Data Analysis Approach," IJERPH, MDPI, vol. 18(11), pages 1-15, June.

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