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International Journal of Adolescent Medicine and Health

Editor-in-Chief: Merrick, Joav

Editorial Board: Birch, Diana ML / Blum, Robert W. / Greydanus, MD, Dr. HC (Athens), Donald E. / Hardoff, Daniel / Kerr, Mike / Levy, Howard B / Morad, Mohammed / Omar, Hatim A. / de Paul, Joaquin / Rydelius, Per-Anders / Shek, Daniel T.L. / Sher, Leo / Silber, Tomas J. / Towns, Susan / Urkin, Jacob / Verhofstadt-Deneve, Leni / Zeltzer, Lonnie / Tenenbaum, Ariel

CiteScore 2018: 0.79

SCImago Journal Rank (SJR) 2018: 0.350
Source Normalized Impact per Paper (SNIP) 2018: 0.476

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Chronic health conditions and adolescent friendship: perspectives from social network analysis

Emily LongORCID iD: https://orcid.org/0000-0003-1512-4471 / Tyson Barrett / Ginger Lockhart
Published Online: 2019-05-09 | DOI: https://doi.org/10.1515/ijamh-2018-0293



The current study uses methods from social network analysis to examine the relationship between chronic health conditions (CHCs) and adolescent friendships. Particular attention is given to the processes of peer marginalization, peer withdrawal and homophily related to CHCs.


Exponential random graph models were used to investigate the extent to which a CHC is associated with patterns in adolescent friendship connections, while controlling for important social network properties and covariates. The study uses cross-sectional data from six small US high schools (n = 461) within the National Longitudinal Study of Adolescent to Adult Health.


Findings demonstrate no significant differences between adolescents with CHCs and adolescents without CHCs in the number of incoming friendship nominations (peer marginalization) or outgoing friendship nominations (peer withdrawal). In addition, similarity in CHCs (homophily) was not significantly related to friendship between two individuals.


In sum, the presence of an adolescent CHC was not significantly associated with adolescent social network structure, including peer marginalization, peer withdrawal, and homophily related to CHCs, after controlling for alternative social network processes. Although previous literature suggests that adolescents with CHCs experience negative social consequences, the current findings demonstrate that the social network structure of adolescents with CHCs did not differ significantly from that of their peers without CHCs. Thus, findings from the current study suggest that CHCs are not related to objective reductions in social connections.

Keywords: adolescents; chronic health; friendships; social networks


  • [1]

    Prinstein M, Dodge K. Understanding peer influence in children and adolescents. New York, NY: Guilford Press; 2008.Google Scholar

  • [2]

    Rubin K, Bukowski W, Parker J. Peer Interactions, relationships, and groups. In: Damon W, Lerner R (Series editors.), Eisenberg N, (Vol. editor). Handbook of Child Psychology: Vol. 3. Social, Emotional, and Personality Development. 6th Ed. Hoboken, NJ: Wiley; 2006. p. 571–645.Google Scholar

  • [3]

    Crosnoe R, Johnson MK. Research on adolescence in the twenty-first century. Ann Review of Sociology. 2011;37:439–60.CrossrefGoogle Scholar

  • [4]

    Bronfenbrenner U, Morris P. The bioecological model of human development. In: Lerner RM, Damon W, editors. The handbook of child psychology: Vol 1. Theoretical models of human development. 5th ed. New York, NY: Wiley; 2006. p. 793–828.Google Scholar

  • [5]

    Schaefer D, Simpkins S. Using social network analysis to clarify the role of obesity in selection of adolescent friends. Am J Public Health. 2014;104(7):1223–9.Web of SciencePubMedCrossrefGoogle Scholar

  • [6]

    Baggio S, Luisier V, Vladescu C. Relationships between social networks and mental health. Swiss J Psychology. 2017;76(1):5–11.Web of ScienceCrossrefGoogle Scholar

  • [7]

    Wang C, Butts C, Hipp J, Jose R, Lakon C. Multiple imputation for missing edge data: a predictive evaluation method with application to Add Health. Social Networks. 2016;45(1):89–98.CrossrefWeb of ScienceGoogle Scholar

  • [8]

    McPherson M, Smith-Lovin L, Cook J. Birds of a feather: homophily in social networks. Annu Rev Soc. 2001;27(1):415–44.CrossrefGoogle Scholar

  • [9]

    Steglich C, Snijders T, Pearson M. Dynamic networks and behavior: separating selection from influence. Soc Methodol. 2010;40(1):329–93.CrossrefGoogle Scholar

  • [10]

    Ali M, Amialchuk A, Nikaj S. Alcohol consumption and social network ties among adolescents: evidence from Add Health. Addict Behav. 2014;39(5):918–22.Web of SciencePubMedCrossrefGoogle Scholar

  • [11]

    Manning J, Hemingway P, Redsell S. Long-term psychosocial impact reported by childhood critical illness survivors: a systematic review. Nurs Crit Care. 2013;19(3):145–56.Web of SciencePubMedGoogle Scholar

  • [12]

    Taylor R, Gibson F, Frank L. The experience of living with chronic illness during adolescence: a critical review of the literature. J Clin Nursing. 2008;17(23):3083–91.Web of ScienceCrossrefGoogle Scholar

  • [13]

    Yeo M, Sawyer S. Chronic illness and disability. Br Med J. 2005;330(7493):721–3.CrossrefWeb of ScienceGoogle Scholar

  • [14]

    Barnes A, Eisenberg M, Resnick M. Suicide and self-injury among children and youth with chronic health conditions. Pediatrics. 2010;125(5):889–95.CrossrefWeb of SciencePubMedGoogle Scholar

  • [15]

    Suris J, Michaud P, Akre C, Sawyer S. Health risk behaviors in adolescents with chronic illness. Pediatrics. 2008;122(5):e1113–8.PubMedGoogle Scholar

  • [16]

    Van Cleave J, Gortmaker S, Perrin J. Dynamics of obesity and chronic health conditions among children and youth. J Am Med Assoc. 2010;303(1):623–30.CrossrefWeb of ScienceGoogle Scholar

  • [17]

    van der Lee J, Mokkink L, Grootenhuis M, Heymans HS, Offringa M. Definitions and measurement of chronic health conditions in childhood. J Am Med Assoc. 2007;297(24):2741–51.CrossrefGoogle Scholar

  • [18]

    McCarroll E, Lindsey E, MacKinnon-Lewis C, Chambers JC, Frabutt JM. Health status and peer relationships in early adolescence: the role of peer contact, self-esteem, and social anxiety. J Child and Family Studies. 2009;18(1):473–85.CrossrefWeb of ScienceGoogle Scholar

  • [19]

    Harris K, Halpern C, Whitsel E, Hussey J, Tabor J, Entzel P, et al. The national longitudinal study of adolescent to adult health: research design [WWW document]. Available from: http://www.dpd.unc.edu/projects/addhealth/design. Accessed January 10, 2018.

  • [20]

    An W. Fitting ERGMs on big networks. Soc Sci Res. 2016;59(1):107–19.CrossrefPubMedWeb of ScienceGoogle Scholar

  • [21]

    Snijders T, Baerveldt C. Multilevel network study of the effects of delinquent behavior on friendship evolution. Math Sociology. 2003;27(1):123–51.CrossrefGoogle Scholar

  • [22]

    Jeon K, Goodson P. US adolescents’ friendship networks and health risk behaviors: a systematic review of studies using social network analysis and Add Health data. PeerJ. 2015;3(1):e1052.PubMedWeb of ScienceGoogle Scholar

  • [23]

    Robins G, Pattison P, Kalish Y, Lusher D. An introduction to exponential random graph models. Social Networks. 2007;29(2):173–91.CrossrefGoogle Scholar

  • [24]

    Veenstra R, Steglich C. Actor-based model for network and behavior dynamics. In: Laursen, B, Little T, Card N, editors. Handbook of Developmental Research Methods. New York, NY: Guilford Press, 2012. p. 598–618.Google Scholar

  • [25]

    Koskinen J, Robins G, Pattison P. Analyzing exponential random graph (p-star) models with missing data using Bayesian data augmentation. Stat Methodol. 2010;7(1):366–84.CrossrefGoogle Scholar

  • [26]

    Goodreau S, Kitts J, Morris M. Birds of a feather, or friend of a friend? Using exponential random graph models to investigate adolescent social networks. Demography. 2009;46(1):103–25.PubMedWeb of ScienceCrossrefGoogle Scholar

  • [27]

    Hunter D, Handcock M, Butts C, Goodreau SM, Morris M. Ergm: a package to fit, simulate and diagnose exponential-family models for networks. J Stat Software. 2008;24(3):nihpa54860.Google Scholar

  • [28]

    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available from: https://www.R-project.org/. Accessed January 13, 2018.

  • [29]

    Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Statistical Software. 2010;36(3):1–48.Google Scholar

  • [30]

    Hedges L, Olkin I. Statistical methods for meta-analysis. San Diego, CA: Academic Press; 1985.Google Scholar

  • [31]

    Lubbers M, Snijders T. A comparison of various approaches to the exponential random graph model: a reanalysis of 102 student networks in school classes. Social Networks. 2007;4(1):489–507.Google Scholar

  • [32]

    Snijders T. The statistical evaluation of social network dynamics. Soc Methodol. 2001;31(1):361–95.CrossrefGoogle Scholar

About the article

Received: 2018-12-23

Accepted: 2019-02-12

Published Online: 2019-05-09

Citation Information: International Journal of Adolescent Medicine and Health, 20180293, ISSN (Online) 2191-0278, DOI: https://doi.org/10.1515/ijamh-2018-0293.

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