IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i5p4531-d1087080.html
   My bibliography  Save this article

The Relationship between Social Support for Physical Activity and Physical Activity across Nine Years in Adults Aged 60–65 Years at Baseline

Author

Listed:
  • Genevieve S. E. Smith

    (School of Applied Psychology, Griffith University, Mt. Gravatt, QLD 4122, Australia
    Menzies Health Institute Queensland, Griffith University, Southport, QLD 4215, Australia
    Centre for Mental Health, Griffith University, Mt. Gravatt, QLD 4122, Australia)

  • Wendy Moyle

    (Menzies Health Institute Queensland, Griffith University, Southport, QLD 4215, Australia
    School of Nursing and Midwifery, Griffith University, Nathan, QLD 4111, Australia)

  • Nicola W. Burton

    (School of Applied Psychology, Griffith University, Mt. Gravatt, QLD 4122, Australia
    Menzies Health Institute Queensland, Griffith University, Southport, QLD 4215, Australia
    Centre for Mental Health, Griffith University, Mt. Gravatt, QLD 4122, Australia)

Abstract

Physical activity is consistently recognized as a key component of healthy aging. The current study aimed to investigate the prospective association between social support specific for physical activity (SSPA) and physical activity across nine years among adults aged 60–65 years at baseline ( n = 1984). An observational longitudinal design was used, with mail surveys administered to a population-based sample across four waves. SSPA was measured using a score ranging from 5–25, and physical activity was assessed as time spent in walking, or engaging in moderate and vigorous activity, during the previous week. Data were analyzed using linear mixed-effects models. The results demonstrated a positive significant relationship between SSPA and physical activity, accounting for sociodemographic and health variables. Each unit of increase in SSPA was associated with 11 extra minutes of physical activity per week ( p < 0.001). There was a significant interaction between SSPA and wave at the final timepoint, such that the relationship was weaker ( p = 0.017). The results highlight the value of even small increases in SSPA. SSPA could be targeted to promote physical activity among older adults, but may be more impactful in young-old adults. More research is needed to understand impactful sources of SSPA, underlying mechanisms between SSPA and physical activity, and potential moderation by age.

Suggested Citation

  • Genevieve S. E. Smith & Wendy Moyle & Nicola W. Burton, 2023. "The Relationship between Social Support for Physical Activity and Physical Activity across Nine Years in Adults Aged 60–65 Years at Baseline," IJERPH, MDPI, vol. 20(5), pages 1-13, March.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:4531-:d:1087080
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/5/4531/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/20/5/4531/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Conor Cunningham & Roger O’Sullivan, 2021. "Healthcare Professionals Promotion of Physical Activity with Older Adults: A Survey of Knowledge and Routine Practice," IJERPH, MDPI, vol. 18(11), pages 1-13, June.
    2. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    3. Po-Wen Ku & Kenneth R. Fox & Li-Jung Chen, 2016. "Leisure-Time Physical Activity, Sedentary Behaviors and Subjective Well-Being in Older Adults: An Eight-Year Longitudinal Research," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 127(3), pages 1349-1361, July.
    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. Ioana Gutu & Daniela Tatiana Agheorghiesei & Alexandru Tugui, 2023. "Assessment of a Workforce Sustainability Tool through Leadership and Digitalization," IJERPH, MDPI, vol. 20(2), pages 1-30, January.
    2. Daniela Andreini & Diego Rinallo & Giuseppe Pedeliento & Mara Bergamaschi, 2017. "Brands and Religion in the Secularized Marketplace and Workplace: Insights from the Case of an Italian Hospital Renamed After a Roman Catholic Pope," Journal of Business Ethics, Springer, vol. 141(3), pages 529-550, March.
    3. S. A. Abu Bakar & Saralees Nadarajah & Z. A. Absl Kamarul Adzhar, 2018. "Loss modeling using Burr mixtures," Empirical Economics, Springer, vol. 54(4), pages 1503-1516, June.
    4. Byrd, T. A. & Marshall, T. E., 1997. "Relating information technology investment to organizational performance: a causal model analysis," Omega, Elsevier, vol. 25(1), pages 43-56, February.
    5. Herbert Hoijtink & Meinte Vollema, 2003. "Contemporary Extensions of the Rasch Model," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(3), pages 263-276, August.
    6. Jaewoong Yun, 2023. "Strategies for Improving the Sustainability of Fare-Free Policy for the Elderly through Preferences by Travel Modes," Sustainability, MDPI, vol. 15(20), pages 1-14, October.
    7. Malerba, Martino E. & Connolly, Sean R. & Heimann, Kirsten, 2015. "An experimentally validated nitrate–ammonium–phytoplankton model including effects of starvation length and ammonium inhibition on nitrate uptake," Ecological Modelling, Elsevier, vol. 317(C), pages 30-40.
    8. Aline Riboli Marasca & Maurício Scopel Hoffmann & Anelise Reis Gaya & Denise Ruschel Bandeira, 2021. "Subjective Well-Being and Psychopathology Symptoms: Mental Health Profiles and their Relations with Academic Achievement in Brazilian Children," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 14(3), pages 1121-1137, June.
    9. Friederike Paetz, 2016. "Persönlichkeitsmerkmale als Segmentierungsvariablen: Eine empirische Studie [Personality traits for market segmentation: An empirical study]," Schmalenbach Journal of Business Research, Springer, vol. 68(3), pages 279-306, August.
    10. Emre Demirkaya & Yang Feng & Pallavi Basu & Jinchi Lv, 2022. "Large-scale model selection in misspecified generalized linear models [Information theory and an extension of the maximum likelihood principle]," Biometrika, Biometrika Trust, vol. 109(1), pages 123-136.
    11. Rosbergen, Edward & Wedel, Michel & Pieters, Rik, 1997. "Analyzing visual attention tot repeated print advertising using scanpath theory," Research Report 97B32, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    12. Eduardo Correia & Rodrigo Calili & José Francisco Pessanha & Maria Fatima Almeida, 2023. "Definition of Regulatory Targets for Electricity Non-Technical Losses: Proposition of an Automatic Model-Selection Technique for Panel Data Regressions," Energies, MDPI, vol. 16(6), pages 1-22, March.
    13. Nalan Basturk & Richard Paap & Dick van Dijk, 2008. "Structural Differences in Economic Growth," Tinbergen Institute Discussion Papers 08-085/4, Tinbergen Institute.
    14. Golob, Thomas F. & Regan, A C, 2002. "Trucking Industry Preferences for Driver Traveler Information Using Wireless Internet-enabled Devices," University of California Transportation Center, Working Papers qt40q8h6sf, University of California Transportation Center.
    15. Golob, Thomas F. & Regan, A C, 2003. "Traffic Congestion and Trucking Managers' Use of Automated Routing and Scheduling," University of California Transportation Center, Working Papers qt74z234n4, University of California Transportation Center.
    16. Francesco BARTOLUCCI & Silvia BACCI & Claudia PIGINI, 2015. "A Misspecification Test for Finite-Mixture Logistic Models for Clustered Binary and Ordered Responses," Working Papers 410, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    17. Bijmolt, T.H.A. & Wedel, M., 1996. "A Monte Carlo Evaluation of Maximum Likelihood Multidimensional Scaling Methods," Other publications TiSEM f72cc9d8-f370-43aa-a224-4, Tilburg University, School of Economics and Management.
    18. Omar N. Solinger & Woody van Olffen & Robert A. Roe & Joeri Hofmans, 2013. "On Becoming (Un)Committed: A Taxonomy and Test of Newcomer Onboarding Scenarios," Organization Science, INFORMS, vol. 24(6), pages 1640-1661, December.
    19. Naiara Escalante Mateos & Eider Goñi Palacios & Arantza Fernández-Zabala & Iratxe Antonio-Agirre, 2020. "Internal Structure, Reliability and Invariance across Gender Using the Multidimensional School Climate Scale PACE-33," IJERPH, MDPI, vol. 17(13), pages 1-24, July.
    20. Sarah Brown & William Greene & Mark N. Harris, 2014. "A New Formulation for Latent Class Models," Working Papers 2014006, The University of Sheffield, Department of Economics.

    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:20:y:2023:i:5:p:4531-:d:1087080. 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.