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Social network concordance in food choice among spouses, friends, and siblings

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  • Pachucki, M.A.
  • Jacques, P.F.
  • Christakis, N.A.

Abstract

Objectives. We investigated whether eating behaviors were concordant among diverse sets of social ties. Methods. We analyzed the socioeconomic and demographic distribution of eating among 3418 members of the Framingham Heart Study observed from 1991 to 2001. We used a data-classification procedure to simplify choices into 7 nonoverlapping patterns that we matched with information on social network ties. We used correlation analysis to examine eating associations among 4 types of peers (spouses, friends, brothers, and sisters). Longitudinal multiple logistic regression was used to evaluate evidence for peer influences on eating. Results. Of all peer types, spouses showed the strongest concordances in eating patterns over time after adjustment for social contextual factors. Across all peers, the eating pattern most likely to be shared by socially connected individuals was "alcohol and snacks." Models estimating one's current eating pattern on the basis of a peer's prior eating provided supportive evidence of a social influence process. Conclusions. Certain eating patterns appeared to be socially transmissible across different kinds of relationships. These findings represent an important step in specifying the relevant social environment in the study of health behaviors to include eating.

Suggested Citation

  • Pachucki, M.A. & Jacques, P.F. & Christakis, N.A., 2011. "Social network concordance in food choice among spouses, friends, and siblings," American Journal of Public Health, American Public Health Association, vol. 101(11), pages 2170-2177.
  • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2011.300282_4
    DOI: 10.2105/AJPH.2011.300282
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    Cited by:

    1. Reczek, Corinne, 2012. "The promotion of unhealthy habits in gay, lesbian, and straight intimate partnerships," Social Science & Medicine, Elsevier, vol. 75(6), pages 1114-1121.
    2. Meena Mahadevan & John Ruzsilla, 2012. "Assessing the Nutritional Health Outcomes of African American Women with HIV and Substance Abuse Disorders Using a Socioecological Approach," SAGE Open, , vol. 2(3), pages 21582440124, September.
    3. Iljana Schubert & Judith I. M. de Groot & Adrian C. Newton, 2021. "Challenging the Status Quo through Social Influence: Changes in Sustainable Consumption through the Influence of Social Networks," Sustainability, MDPI, vol. 13(10), pages 1-17, May.
    4. Els Weinans & George van Voorn & Patrick Steinmann & Elisa Perrone & Ahmadreza Marandi, 2024. "An Exploration of Drivers of Opinion Dynamics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 27(1), pages 1-5.
    5. Shakya, Holly B. & Fleming, Paul & Saggurti, Niranjan & Donta, Balaiah & Silverman, Jay & Raj, Anita, 2017. "Longitudinal associations of intimate partner violence attitudes and perpetration: Dyadic couples data from a randomized controlled trial in rural India," Social Science & Medicine, Elsevier, vol. 179(C), pages 97-105.
    6. Missinne, Sarah & Colman, Elien & Bracke, Piet, 2013. "Spousal influence on mammography screening: A life course perspective," Social Science & Medicine, Elsevier, vol. 98(C), pages 63-70.
    7. Perry, Brea L. & Ciciurkaite, Gabriele, 2019. "Contributions of personality to social influence: Contingent associations between social network body size composition and BMI," Social Science & Medicine, Elsevier, vol. 224(C), pages 1-10.
    8. Conklin, Annalijn I. & Forouhi, Nita G. & Surtees, Paul & Khaw, Kay-Tee & Wareham, Nicholas J. & Monsivais, Pablo, 2014. "Social relationships and healthful dietary behaviour: Evidence from over-50s in the EPIC cohort, UK," Social Science & Medicine, Elsevier, vol. 100(C), pages 167-175.
    9. Matthew Gibson & Raphael Slade & Joana Portugal Pereira & Joeri Rogelj, 2021. "Comparing Mechanisms of Food Choice in an Agent-Based Model of Milk Consumption and Substitution in the UK," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 24(3), pages 1-9.
    10. 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.
    11. Juan Carlos Sánchez Herrera & Carolyn Dimitri, 2019. "The Role of Clustering in the Adoption of Organic Dairy: A Longitudinal Networks Analysis between 2002 and 2015," Sustainability, MDPI, vol. 11(6), pages 1-19, March.
    12. Indrani Saran & Günther Fink & Margaret McConnell, 2018. "How does anonymous online peer communication affect prevention behavior? Evidence from a laboratory experiment," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-16, November.
    13. Shand, Calum & Crozier, Sarah & Vassilev, Ivaylo & Penn-Newman, Daniel & Dhuria, Preeti & Cooper, Cyrus & Rogers, Anne & Baird, Janis & Vogel, Christina, 2021. "Resources in women's social networks for food shopping are more strongly associated with better dietary quality than people: A cross-sectional study," Social Science & Medicine, Elsevier, vol. 284(C).

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