IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0096460.html
   My bibliography  Save this article

Increasing Specificity of Correlate Research: Exploring Correlates of Children’s Lunchtime and After-School Physical Activity

Author

Listed:
  • Rebecca M Stanley
  • Kate Ridley
  • Timothy S Olds
  • James Dollman

Abstract

Background: The lunchtime and after-school contexts are critical windows in a school day for children to be physically active. While numerous studies have investigated correlates of children’s habitual physical activity, few have explored correlates of physical activity occurring at lunchtime and after-school from a social-ecological perspective. Exploring correlates that influence physical activity occurring in specific contexts can potentially improve the prediction and understanding of physical activity. Using a context-specific approach, this study investigated correlates of children’s lunchtime and after-school physical activity. Methods: Cross-sectional data were collected from 423 South Australian children aged 10.0–13.9 years (200 boys; 223 girls) attending 10 different schools. Lunchtime and after-school physical activity was assessed using accelerometers. Correlates were assessed using purposely developed context-specific questionnaires. Correlated Component Regression analysis was conducted to derive correlates of context-specific physical activity and determine the variance explained by prediction equations. Results: The model of boys’ lunchtime physical activity contained 6 correlates and explained 25% of the variance. For girls, the model explained 17% variance from 9 correlates. Enjoyment of walking during lunchtime was the strongest correlate for both boys and girls. Boys’ and girls’ after-school physical activity models explained 20% variance from 14 correlates and 7% variance from the single item correlate, “I do an organised sport or activity after-school because it gets you fit”, respectively. Conclusions: Increasing specificity of correlate research has enabled the identification of unique features of, and a more in-depth interpretation of, lunchtime and after-school physical activity behaviour and is a potential strategy for advancing the physical activity correlate research field. The findings of this study could be used to inform and tailor gender-specific public health messages and interventions for promoting lunchtime and after-school physical activity in children.

Suggested Citation

  • Rebecca M Stanley & Kate Ridley & Timothy S Olds & James Dollman, 2014. "Increasing Specificity of Correlate Research: Exploring Correlates of Children’s Lunchtime and After-School Physical Activity," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-9, May.
  • Handle: RePEc:plo:pone00:0096460
    DOI: 10.1371/journal.pone.0096460
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0096460
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0096460&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0096460?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sallis, J.F. & Conway, T.L. & Prochaska, J.J. & McKenzie, T.L. & Marshall, S.J. & Brown, M., 2001. "The association of school environments with youth physical activity," American Journal of Public Health, American Public Health Association, vol. 91(4), pages 618-620.
    2. repec:mpr:mprres:3903 is not listed on IDEAS
    3. Rebecca R. Andridge & Roderick J. A. Little, 2010. "A Review of Hot Deck Imputation for Survey Non‐response," International Statistical Review, International Statistical Institute, vol. 78(1), pages 40-64, April.
    Full references (including those not matched with items on IDEAS)

    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. Raymundo M. Campos-Vázquez, 2013. "Efectos de los ingresos no reportados en el nivel y tendencia de la pobreza laboral en México," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 23-54, November.
    2. Paul T. von Hippel, 2013. "Should a Normal Imputation Model be Modified to Impute Skewed Variables?," Sociological Methods & Research, , vol. 42(1), pages 105-138, February.
    3. Jaroslava Kopcakova & Zuzana Dankulincova Veselska & Andrea Madarasova Geckova & Daniel Klein & Jitse P. Dijk & Sijmen A. Reijneveld, 2018. "Are school factors and urbanization supportive for being physically active and engaging in less screen-based activities?," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 63(3), pages 359-366, April.
    4. Laura C. Leviton, 2008. "Children's Healthy Weight and the School Environment," The ANNALS of the American Academy of Political and Social Science, , vol. 615(1), pages 38-55, January.
    5. Siedschlag Iulia & Kaitila Ville & McQuinn John & Zhang Xiaoheng, 2014. "International Investment and Firm Performance: Empirical Evidence from Small Open Economies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(6), pages 662-687, December.
    6. Miller, Elizabeth A. & Paschall, Katherine W. & Azar, Sandra T., 2017. "Latent classes of older foster youth: Prospective associations with outcomes and exits from the foster care system during the transition to adulthood," Children and Youth Services Review, Elsevier, vol. 79(C), pages 495-505.
    7. Meyer, Bruce D. & Mittag, Nikolas, 2019. "Combining Administrative and Survey Data to Improve Income Measurement," IZA Discussion Papers 12266, Institute of Labor Economics (IZA).
    8. Nancy, Jane Y. & Khanna, Nehemiah H. & Arputharaj, Kannan, 2017. "Imputing missing values in unevenly spaced clinical time series data to build an effective temporal classification framework," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 63-79.
    9. Thomas Masterson & Kijong Kim & Fernando Rios-Avila, 2016. "Simulations of Employment for Individuals in LIMTCP Consumption-poor Households in Tanzania and Ghana, 2012," Economics Working Paper Archive wp_871, Levy Economics Institute.
    10. McDonough, Ian K. & Millimet, Daniel L., 2017. "Missing data, imputation, and endogeneity," Journal of Econometrics, Elsevier, vol. 199(2), pages 141-155.
    11. Black, Nicole & Johnston, David W. & Propper, Carol & Shields, Michael A., 2019. "The effect of school sports facilities on physical activity, health and socioeconomic status in adulthood," Social Science & Medicine, Elsevier, vol. 220(C), pages 120-128.
    12. Hamrick, Karen S., 2012. "Nonresponse Bias Analysis of Body Mass Index in the Eating and Health Module," Technical Bulletins 184303, United States Department of Agriculture, Economic Research Service.
    13. Lingyun Lyu & Yu Cheng & Abdus S. Wahed, 2023. "Imputation‐based Q‐learning for optimizing dynamic treatment regimes with right‐censored survival outcome," Biometrics, The International Biometric Society, vol. 79(4), pages 3676-3689, December.
    14. Yijie Xue & Nicole Lazar, 2012. "Empirical likelihood-based hot deck imputation methods," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 629-646.
    15. Marcello D’Orazio, 2015. "Integration and imputation of survey data in R: the StatMatch package," Romanian Statistical Review, Romanian Statistical Review, vol. 63(2), pages 57-68, June.
    16. Zhong, Hua & Hu, Wuyang, 2015. "Farmers’ Willingness to Engage in Best Management Practices: an Application of Multiple Imputation," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196962, Southern Agricultural Economics Association.
    17. Thomas Masterson, 2014. "Quality of Statistical Match and Employment Simulations Used in the Estimation of the Levy Institute Measure of Time and Income Poverty (LIMTIP) for South Korea, 2009," Economics Working Paper Archive wp_793, Levy Economics Institute.
    18. Yanqing Sun & Li Qi & Fei Heng & Peter B. Gilbert, 2020. "A hybrid approach for the stratified mark‐specific proportional hazards model with missing covariates and missing marks, with application to vaccine efficacy trials," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 791-814, August.
    19. Młodak Andrzej, 2021. "An application of a complex measure to model–based imputation in business statistics," Statistics in Transition New Series, Statistics Poland, vol. 22(1), pages 1-28, March.
    20. Thomas Masterson, 2012. "Simulations of Full-Time Employment and Household Work in the Levy Institute Measure of Time and Income Poverty (LIMTIP) for Argentina, Chile, and Mexico," Economics Working Paper Archive wp_727, Levy Economics Institute.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0096460. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.