IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i3p415-d202377.html
   My bibliography  Save this article

Exploratory Determined Correlates of Physical Activity in Children and Adolescents: The MoMo Study

Author

Listed:
  • Steffen CE Schmidt

    (Institute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany)

  • Jennifer Schneider

    (Institute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany)

  • Anne Kerstin Reimers

    (Institute of Human Movement Science and Health, Faculty of Behavioral and Social Sciences, Technical University of Chemnitz, 09111 Chemnitz, Germany)

  • Claudia Niessner

    (Institute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany)

  • Alexander Woll

    (Institute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany)

Abstract

Background : Physical activity is an important contributor to reducing the risk for a variety of diseases. Understanding why people are physically active contributes to evidence-based planning of public health interventions because successful actions will target factors known to be related to physical activity (PA). Therefore the aim of this study is to identify the most meaningful correlates of PA in children and adolescents using a large, representative data set. Methods : Among n = 3539 (1801 boys) 6 to 17-year-old participants of the German representative Motorik-Modul baseline study (2003–2006) a total of 1154 different demographic, psychological, behavioral, biological, social and environmental factors were ranked according to their power of predicting PA using least absolute shrinkage and selection operator (LASSO) regressions. Results : A total of 18 (in girls) and 19 (in boys) important PA predictors from different, personal, social and environmental factors have been identified and ranked by LASSO. Peer modeling and physical self-concept were identified as the strongest correlates of PA in both boys and girls. Conclusions : The results confirm that PA interventions must target changes in different categories of PA correlates, but we suggest to focus particularly on the social environment and physical self-concept for interventions targeting children and adolescents in Germany nowadays. We also strongly recommend to repeatedly track correlates of PA, at least every 10 years, from representative samples in order to tailor contemporary PA interventions.

Suggested Citation

  • Steffen CE Schmidt & Jennifer Schneider & Anne Kerstin Reimers & Claudia Niessner & Alexander Woll, 2019. "Exploratory Determined Correlates of Physical Activity in Children and Adolescents: The MoMo Study," IJERPH, MDPI, vol. 16(3), pages 1-16, January.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:3:p:415-:d:202377
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/3/415/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/16/3/415/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sara Pereira & Thayse Natacha Gomes & Alessandra Borges & Daniel Santos & Michele Souza & Fernanda K. Dos Santos & Raquel N. Chaves & Peter T. Katzmarzyk & José A. R. Maia, 2015. "Variability and Stability in Daily Moderate-to-Vigorous Physical Activity among 10 Year Old Children," IJERPH, MDPI, vol. 12(8), pages 1-16, August.
    2. E. W. Steyerberg & M. J. C. Eijkemans & J. D. F. Habbema, 2001. "Application of Shrinkage Techniques in Logistic Regression Analysis: A Case Study," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 55(1), pages 76-88, March.
    3. Tsair-Fwu Lee & Pei-Ju Chao & Hui-Min Ting & Liyun Chang & Yu-Jie Huang & Jia-Ming Wu & Hung-Yu Wang & Mong-Fong Horng & Chun-Ming Chang & Jen-Hong Lan & Ya-Yu Huang & Fu-Min Fang & Stephen Wan Leung, 2014. "Using Multivariate Regression Model with Least Absolute Shrinkage and Selection Operator (LASSO) to Predict the Incidence of Xerostomia after Intensity-Modulated Radiotherapy for Head and Neck Cancer," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-11, February.
    4. Steffen C. E. Schmidt & Annette Henn & Claudia Albrecht & Alexander Woll, 2017. "Physical Activity of German Children and Adolescents 2003–2012: The MoMo-Study," IJERPH, MDPI, vol. 14(11), pages 1-10, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Louisa R. Peralta & Renata L. Cinelli & Wayne Cotton & Sarah Morris & Olivier Galy & Corinne Caillaud, 2022. "The Barriers to and Facilitators of Physical Activity and Sport for Oceania with Non-European, Non-Asian (ONENA) Ancestry Children and Adolescents: A Mixed Studies Systematic Review," IJERPH, MDPI, vol. 19(18), pages 1-26, September.
    2. Amanda N. Spitzer & Katrina Oselinsky & Rachel G. Lucas-Thompson & Dan J. Graham, 2022. "Environmental Physical Activity Cues and Children’s Active vs. Sedentary Recreation," IJERPH, MDPI, vol. 19(3), pages 1-12, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Isabel Marzi & Anne Kerstin Reimers, 2018. "Children’s Independent Mobility: Current Knowledge, Future Directions, and Public Health Implications," IJERPH, MDPI, vol. 15(11), pages 1-15, November.
    2. Rotaris, Lucia & Del Missier, Fabio & Scorrano, Mariangela, 2023. "Comparing children and parental preferences for active commuting to school. A focus on Italian middle-school students," Research in Transportation Economics, Elsevier, vol. 97(C).
    3. Tarun Mehra & Christian Thomas Benedikt Müller & Jörk Volbracht & Burkhardt Seifert & Rudolf Moos, 2015. "Predictors of High Profit and High Deficit Outliers under SwissDRG of a Tertiary Care Center," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-18, October.
    4. Longxi Li & Michelle E. Moosbrugger, 2021. "Correlations between Physical Activity Participation and the Environment in Children and Adolescents: A Systematic Review and Meta-Analysis Using Ecological Frameworks," IJERPH, MDPI, vol. 18(17), pages 1-21, August.
    5. Laura Cella & Giuseppe Palma & Joseph O Deasy & Jung Hun Oh & Raffaele Liuzzi & Vittoria D’Avino & Manuel Conson & Novella Pugliese & Marco Picardi & Marco Salvatore & Roberto Pacelli, 2014. "Complication Probability Models for Radiation-Induced Heart Valvular Dysfunction: Do Heart-Lung Interactions Play a Role?," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-11, October.
    6. Muhammad Amin & Lixin Song & Milton Abdul Thorlie & Xiaoguang Wang, 2015. "SCAD-penalized quantile regression for high-dimensional data analysis and variable selection," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 212-235, August.
    7. Dunkler, Daniela & Sauerbrei, Willi & Heinze, Georg, 2016. "Global, Parameterwise and Joint Shrinkage Factor Estimation," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 69(i08).
    8. Campbell Foubister & Esther M F van Sluijs & Anna Vignoles & Paul Wilkinson & Edward C F Wilson & Caroline H D Croxson & Helen Elizabeth Brown & Kirsten Corder, 2021. "The school policy, social, and physical environment and change in adolescent physical activity: An exploratory analysis using the LASSO," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-14, April.
    9. Akram Farhadi & Joshua J. Chern & Daniel Hirsh & Tod Davis & Mingyoung Jo & Frederick Maier & Khaled Rasheed, 2018. "Intracranial Pressure Forecasting in Children Using Dynamic Averaging of Time Series Data," Forecasting, MDPI, vol. 1(1), pages 1-12, August.
    10. Ekele Alih & Hong Choon Ong, 2015. "Cluster-based multivariate outlier identification and re-weighted regression in linear models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(5), pages 938-955, May.
    11. Ming-jian Nie & Chao-qun Fan & Rui-zhe Sun & Jing-jing Wang & Qiang Feng & Yan-feng Zhang & Zhi Yao & Mei Wang, 2019. "Accelerometer-Measured Physical Activity in Children and Adolescents at Altitudes over 3500 Meters: A Cross-Sectional Study in Tibet," IJERPH, MDPI, vol. 16(5), pages 1-16, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:16:y:2019:i:3:p:415-:d:202377. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.