IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v11y2021i3p21582440211031606.html
   My bibliography  Save this article

Leveraging Emergent Social Networks to Reduce Sedentary Behavior in Low-Income Parents With Preschool-Aged Children

Author

Listed:
  • Sabina B. Gesell
  • Shari L. Barkin
  • Edward H. Ip
  • Santiago J. Saldana
  • Evan C. Sommer
  • Thomas W. Valente
  • Kayla de la Haye

Abstract

This study tested the hypothesis that parents participating in a pediatric obesity intervention who formed social network ties with a parent in the intervention arm would engage in more daily physical activity and less sedentary behavior (after controlling for participant covariates). Data were collected at baseline, 12 months, and 36 months from 610 low-income parent–child pairs participating in an obesity prevention intervention for 3- to 5-year-old children. A network survey was used to identify social network ties among parents and accelerometers were used to measure parental physical activity and sedentary time. Longitudinal regression analyses tested effects of social network ties on parents’ physical activity and sedentary behavior. Compared with parents without a social network tie, having a tie with an intervention group participant was associated with a clinically meaningful 11.04 min/day decrease in parental sedentary behavior that approached statistical significance (95% confidence interval [CI] = [−22.71, 0.63], p  = .06). Social network ties among parents in a pediatric obesity prevention intervention were not clearly associated with reduced sedentary behavior among those parents at the traditional level of p  = .05. The large effect size (over 77 min per week improvement) suggests there might be potential importance of promoting new social networks in community-based health promotion interventions to elicit and support behavior change, but further examination is needed.

Suggested Citation

  • Sabina B. Gesell & Shari L. Barkin & Edward H. Ip & Santiago J. Saldana & Evan C. Sommer & Thomas W. Valente & Kayla de la Haye, 2021. "Leveraging Emergent Social Networks to Reduce Sedentary Behavior in Low-Income Parents With Preschool-Aged Children," SAGE Open, , vol. 11(3), pages 21582440211, July.
  • Handle: RePEc:sae:sagope:v:11:y:2021:i:3:p:21582440211031606
    DOI: 10.1177/21582440211031606
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440211031606
    Download Restriction: no

    File URL: https://libkey.io/10.1177/21582440211031606?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. Ruth F Hunter & Kayla de la Haye & Jennifer M Murray & Jennifer Badham & Thomas W Valente & Mike Clarke & Frank Kee, 2019. "Social network interventions for health behaviours and outcomes: A systematic review and meta-analysis," PLOS Medicine, Public Library of Science, vol. 16(9), pages 1-25, September.
    2. Hunter, R.F. & McAneney, H. & Davis, M. & Tully, M.A. & Valente, T.W. & Kee, F., 2015. ""hidden" social networks in behavior change interventions," American Journal of Public Health, American Public Health Association, vol. 105(3), pages 513-516.
    3. Zhang, J. & Shoham, D.A. & Tesdahl, E. & Gesell, S.B., 2015. "Network interventions on physical activity in an afterschool program: An agent-based social network study," American Journal of Public Health, American Public Health Association, vol. 105, pages 236-243.
    4. Kelly, J.A. & St. Lawrence, J.S. & Diaz, Y.E. & Stevenson, L.Y. & Hauth, A.C. & Brasfield, T.L. & Kalichman, S.C. & Smith, J.E. & Andrew, M.E., 1991. "HIV risk behavior reduction following intervention with key opinion leaders of population: An experimental analysis," American Journal of Public Health, American Public Health Association, vol. 81(2), pages 168-171.
    5. Wei Pan, 2001. "Akaike's Information Criterion in Generalized Estimating Equations," Biometrics, The International Biometric Society, vol. 57(1), pages 120-125, March.
    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. Paulin Tay Straughan & Chengwei Xu, 2022. "Parents’ Knowledge, Attitudes, and Practices of Childhood Obesity in Singapore," SAGE Open, , vol. 12(4), pages 21582440221, December.

    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. Sabina B. Gesell & Kayla de la Haye & Evan C. Sommer & Santiago J. Saldana & Shari L. Barkin & Edward H. Ip, 2020. "Identifying Social Network Conditions that Facilitate Sedentary Behavior Change: The Benefit of Being a “Bridge” in a Group-based Intervention," IJERPH, MDPI, vol. 17(12), pages 1-13, June.
    2. Gayen, Kaberi & Raeside, Robert, 2007. "Social networks, normative influence and health delivery in rural Bangladesh," Social Science & Medicine, Elsevier, vol. 65(5), pages 900-914, September.
    3. Wei Pan, 2001. "Model Selection in Estimating Equations," Biometrics, The International Biometric Society, vol. 57(2), pages 529-534, June.
    4. Michael S. Rendall & Bonnie Ghosh-Dastidar & Margaret M. Weden & Zafar Nazarov, 2011. "Multiple Imputation for Combined-Survey Estimation With Incomplete Regressors In One But Not Both Surveys," Working Papers WR-887-1, RAND Corporation.
    5. Dimitris Tsintsaris & Milan Tsompanoglou & Evangelos Ioannidis, 2024. "Dynamics of Social Influence and Knowledge in Networks: Sociophysics Models and Applications in Social Trading, Behavioral Finance and Business," Mathematics, MDPI, vol. 12(8), pages 1-27, April.
    6. Katrina N. Burns & Kan Sun & Julius N. Fobil & Richard L. Neitzel, 2016. "Heart Rate, Stress, and Occupational Noise Exposure among Electronic Waste Recycling Workers," IJERPH, MDPI, vol. 13(1), pages 1-16, January.
    7. Song Guo & Feng Ling & Juan Hou & Jinna Wang & Guiming Fu & Zhenyu Gong, 2014. "Mosquito Surveillance Revealed Lagged Effects of Mosquito Abundance on Mosquito-Borne Disease Transmission: A Retrospective Study in Zhejiang, China," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-8, November.
    8. Diana Tsoy & Danijela Godinic & Qingyan Tong & Bojan Obrenovic & Akmal Khudaykulov & Konstantin Kurpayanidi, 2022. "Impact of Social Media, Extended Parallel Process Model (EPPM) on the Intention to Stay at Home during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(12), pages 1-32, June.
    9. Laura Neumeyer & Anna Gründler & Anna-Luisa Stöber, 2023. "Don’t Worry, Be Happy—Does the CEO’s Personality Mitigate the Negative Effect of Financial Constraints on Employee Satisfaction?," Schmalenbach Journal of Business Research, Springer, vol. 75(1), pages 71-98, March.
    10. Li, Gaorong & Lian, Heng & Feng, Sanying & Zhu, Lixing, 2013. "Automatic variable selection for longitudinal generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 174-186.
    11. Mark Rooij, 2018. "Transitional modeling of experimental longitudinal data with missing values," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(1), pages 107-130, March.
    12. Aristides dos Santos, Anderson Moreira & Perelman, Julian & Jacinto, Paulo de Andrade & Tejada, Cesar Augusto Oviedo & Barros, Aluísio J.D. & Bertoldi, Andréa D. & Matijasevich, Alicia & Santos, Iná S, 2019. "Income-related inequality and inequity in children’s health care: A longitudinal analysis using data from Brazil," Social Science & Medicine, Elsevier, vol. 224(C), pages 127-137.
    13. Yuvraj Sunecher & Naushad Mamode Khan & Miroslav M. Ristić & Vandna Jowaheer, 2019. "BINAR(1) negative binomial model for bivariate non-stationary time series with different over-dispersion indices," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 625-653, December.
    14. McMillan, Cassie & Schaefer, David R., 2021. "Comparing targeting strategies for network-based adolescent drinking interventions: A simulation approach," Social Science & Medicine, Elsevier, vol. 282(C).
    15. Linna Luo & Bowen Pang & Jian Chen & Yan Li & Xiaolei Xie, 2019. "Assessing the Impact of Lifestyle Interventions on Diabetes Prevention in China: A Modeling Approach," IJERPH, MDPI, vol. 16(10), pages 1-12, May.
    16. Merlo, Luca & Petrella, Lea & Salvati, Nicola & Tzavidis, Nikos, 2022. "Marginal M-quantile regression for multivariate dependent data," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    17. Bastian Rake, 2017. "Determinants of pharmaceutical innovation: the role of technological opportunities revisited," Journal of Evolutionary Economics, Springer, vol. 27(4), pages 691-727, September.
    18. Zijing Yang & Chengfeng Zhang & Yawen Hou & Zheng Chen, 2023. "Analysis of dynamic restricted mean survival time based on pseudo‐observations," Biometrics, The International Biometric Society, vol. 79(4), pages 3690-3700, December.
    19. Selles Jules & Bonhommeau Sylvain & Guillotreau Patrice & Vallée Thomas, 2020. "Can the Threat of Economic Sanctions Ensure the Sustainability of International Fisheries? An Experiment of a Dynamic Non-cooperative CPR Game with Uncertain Tipping Point," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(1), pages 153-176, May.
    20. Sean Duffy & J. J. Naddeo & David Owens & John Smith, 2024. "Cognitive Load and Mixed Strategies: On Brains and Minimax," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 26(03), pages 1-34, September.

    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:sae:sagope:v:11:y:2021:i:3:p:21582440211031606. 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: SAGE Publications (email available below). General contact details of provider: .

    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.