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Analyzing heterogeneity in the effects of physical activity in children on social network structure and peer selection dynamics

Published online by Cambridge University Press:  12 May 2016

TEAGUE HENRY ,
SABINA B. GESELL  and
EDWARD H. IP
TEAGUE HENRY
Affiliation:
University of North Carolina at Chapel Hill, Chapel Hill, NC, USA (e-mail: [email protected])
SABINA B. GESELL
Affiliation:
Wake Forest School of Medicine, Winston-Salem, NC, USA (e-mails: [email protected]; [email protected])
EDWARD H. IP
Affiliation:
Wake Forest School of Medicine, Winston-Salem, NC, USA (e-mails: [email protected]; [email protected])
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Abstract

Social networks influence children and adolescents' physical activity. The focus of this paper is to examine the differences in the effects of physical activity on friendship selection, with eye to the implications on physical activity interventions for young children. Prior to implementing a network intervention in the field, it is important to understand potential heterogeneities in the effects that activity level have on network structure. In this study, the associations between activity level and cross-sectional network structure, and activity level and change in network structure are assessed. We studied a real-world friendship network among 81 children (average age 7.96 years) who lived in low SES neighborhoods, attended public schools, and attended one of two structured aftercare programs, of which one has existed and the other was new. We modeled network selection effects and cross-sectional properties, while accounting for potential heterogeneities between networks. There was heterogeneity in the effect of physical activity on both cross-sectional network structure and the formation and dissolution processes, both across time and between networks. This suggests that if peer selection processes are changing within a network, a static network intervention strategy for childhood physical activity could become inefficient as the network evolves.

Keywords

ERGMSTERGMnew networkestablished programphysical activityafterschool care programchildhood physical activitysocial supportsocial networkchildren
Type
Research Article
Information
Network Science , Volume 4 , Issue 3 , September 2016 , pp. 336 - 363
Copyright
Copyright © Cambridge University Press 2016 

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References

Bahr, D. B., Browning, R. C., Wyatt, H. R., & Hill, J. O. (2009). Exploiting social networks to mitigate the obesity epidemic. Obesity (Silver Spring, Md.), 17 (4), 723–728. doi:10.1038/oby.2008.615.CrossRefGoogle ScholarPubMed
Birch, L. L. (1980). Effects of peer models' food choices and eating behaviors on preschoolers' food preferences. Child Development, 51 (2), 489–496. doi:10.2307/1129283.Google Scholar
Christakis, N. a., & Fowler, J. H. (2007). The spread of obesity in a large social network over 32 years. The New England Journal of Medicine, 357 (4), 370–379. doi:10.1056/NEJMsa066082.CrossRefGoogle Scholar
De la Haye, K., Robins, G., Mohr, P., & Wilson, C. (2010). Obesity-related behaviors in adolescent friendship networks. Social Networks, 32 (3), 161–167. doi:10.1016/j.socnet.2009.09.001.CrossRefGoogle Scholar
De la Haye, K., Robins, G., Mohr, P., & Wilson, C. (2011a). Homophily and contagion as explanations for weight similarities among adolescent friends. The Journal of Adolescent Health, 49 (4), 421–427. doi:10.1016/j.jadohealth.2011.02.008.CrossRefGoogle ScholarPubMed
De la Haye, K., Robins, G., Mohr, P., & Wilson, C. (2011b). How physical activity shapes, and is shaped by, adolescent friendships. Social Science & Medicine (1982), 73 (5), 719–728. doi:10.1016/j.socscimed.2011.06.023.CrossRefGoogle ScholarPubMed
Gesell, S. B., Tesdahl, E., & Ruchman, E. (2012). The distribution of physical activity in an after-school friendship network. Pediatrics, 129 (6), 1064–1071. doi:10.1542/peds.2011-2567.CrossRefGoogle Scholar
Glickman, D. (2012). Accelerating progress in obesity prevention solving the weight of the nation. Washington, DC: National Academies Press.Google Scholar
Goodreau, S. M., Handcock, M. S., Hunter, D. R., Butts, C. T., & Morris, M. (2008). A statnet tutorial. Journal of Statistical Software, 24 (9), 1–27. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/18612375.CrossRefGoogle ScholarPubMed
Gortmaker, S., Swinburn, B., & Levy, D. (2011). Changing the future of obesity: Science, policy, and action. The Lancet, 378 (9793), 838–847. doi:10.1016/S0140-6736(11)608155. Changing.CrossRefGoogle ScholarPubMed
Hammond, R. A. (2009). Complex systems modeling for obesity. Preventing Chronic Disease, 6 (3), A97.Google ScholarPubMed
Handcock, M. S. (2003). Statisical models for social networks: Degeneracy and inference. In Breiger, R., Carley, K., & Pattison, P. (Eds.), Dynamic social network modeling and analysis (pp. 229–240). Washington DC: National Academies Press.Google Scholar
Hartl, A. C., Laursen, B., & Cillessen, A. H. N. (2015). A survival analysis of adolescent friendships: The downside of dissimilarity. Psychological Science, 26 (8), 1304–1315. doi:10.1177/0956797615588751.CrossRefGoogle ScholarPubMed
Hunter, D. R., Goodreau, S. M., & Handcock, M. S. (2008). Goodness of fit of social network models. Journal of the American Statistical Association, 103 (481), 248–258.CrossRefGoogle Scholar
Hunter, D. R., & Handcock, M. S. (2006). Inference in curved exponential family models for networks. Journal of Computational and Graphical Statistics, 15 (3), 565–583. doi:10.1198/106186006X133069.CrossRefGoogle Scholar
Jaccard, P. (1901). Étude comparative de la distribution florale dans une portion des Alpes et des Jura. Bulletin de la Société Vaudoise des Sciences Naturelles, 37, 547–579.Google Scholar
Krivitsky, P. N., & Handcock, M. S. (2014). A separable model for dynamic networks. Journal of the Royal Statistical Society. Series B, Statistical Methodology, 76 (1), 29–46. doi:10.1111/rssb.12014.CrossRefGoogle ScholarPubMed
Levy, D. T., Mabry, P. L., Wang, Y. C., Gortmaker, S., Huang, T. T.-K., Marsh, T., . . . Swinburn, B. (2011). wSimulation models of obesity: A review of the literature and implications for research and policy. Obesity Reviews: An Official Journal of the International Association for the Study of Obesity, 12 (5), 378–394. doi:10.1111/j.1467-789X.2010.00804.x.CrossRefGoogle ScholarPubMed
Luke, D. A., & Harris, J. K. (2007). Network analysis in public health: history, methods, and applications. Annual Review of Public Health, 28, 69–93.CrossRefGoogle ScholarPubMed
MacDonald-Wallis, K., Jago, R., Page, A. S., Brockman, R., & Thompson, J. L. (2011). School-based friendship networks and children's physical activity: A spatial analytical approach. Social Science & Medicine, 73 (1), 6–12. doi:10.1016/j.socscimed.2011.04.018.CrossRefGoogle ScholarPubMed
MacDonald-Wallis, K., Jago, R., & Sterne, J. a. C. (2012). Social network analysis of childhood and youth physical activity: A systematic review. American Journal of Preventive Medicine, 43 (6), 636–642. doi:10.1016/j.amepre.2012.08.021.CrossRefGoogle ScholarPubMed
McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27 (1), 415–444. doi:10.1146/annurev.soc.27.1.415.CrossRefGoogle Scholar
Nader, P. R., Huang, T. T.-K., Gahagan, S., Kumanyika, S., Hammond, R. a., & Christoffel, K. K. (2012). Next steps in obesity prevention: Altering early life systems to support healthy parents, infants, and toddlers. Childhood Obesity (Print), 8 (3), 195–204. doi:10.1089/chi.2012.0004.CrossRefGoogle ScholarPubMed
Pate, R. R., Almeida, M. J., McIver, K. L., Pfeiffer, K. a., & Dowda, M. (2006). Validation and calibration of an accelerometer in preschool children. Obesity (Silver Spring, Md.), 14 (11), 2000–2006. doi:10.1038/oby.2006.234.CrossRefGoogle ScholarPubMed
Pearce, M. J., Boergers, J., & Prinstein, M. J. (2002). Adolescent obesity, overt and relational peer victimization, and romantic relationships. Obesity Research, 10 (5), 386–393. doi:10.1038/oby.2002.53.CrossRefGoogle ScholarPubMed
Puyau, M. R., Adolph, A. L., Vohra, F. a., & Butte, N. F. (2002). Validation and calibration of physical activity monitors in children. Obesity Research, 10 (3), 150–157. doi:10.1038/oby.2002.24.CrossRefGoogle ScholarPubMed
Robins, G., Pattison, P., Kalish, Y., & Lusher, D. (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks, 29 (2), 173–191. doi:10.1016/j.socnet.2006.08.002.CrossRefGoogle Scholar
Sallis, J. F., Prochaska, J. J., & Taylor, W. C. (2000). A review of correlates of physical activity of children and adolescents. Medicine and Science in Sports and Exercise, 32 (5), 963–975.CrossRefGoogle ScholarPubMed
Salvy, S. J., de la Haye, K., Bowker, J. C., & Hermans, R. C. J. (2012). Influence of peers and friends on children's and adolescents' eating and activity behaviors. Physiology and Behavior, 106 (3), 369–378. doi:10.1016/j.physbeh.2012.03.022.CrossRefGoogle ScholarPubMed
Sawka, K. J., McCormack, G. R., Nettel-Aguirre, A., Hawe, P., & Doyle-Baker, P. K. (2013). Friendship networks and physical activity and sedentary behavior among youth: A systematized review. The International Journal of Behavioral Nutrition and Physical Activity, 10, 130. doi:10.1186/1479-5868-10-130.CrossRefGoogle ScholarPubMed
Shoham, D. a., Tong, L., Lamberson, P. J., Auchincloss, A. H., Zhang, J., Dugas, L., & Luke, A. (2012). An actor-based model of social network influence on adolescent body size, screen time, and playing sports. PloS One, 7 (6), e39795. doi:10.1371/journal.pone.0039795.CrossRefGoogle ScholarPubMed
Simpson, S., Hayasaka, S., & Laurienti, P. (2011). Exponential random graph modeling for complex brain networks. PloS One, 6 (5), e20039. doi:10.1371/journal.pone.0020039.CrossRefGoogle ScholarPubMed
Snijders, T. a. B., van de Bunt, G. G., & Steglich, C. E. G. (2010). Introduction to stochastic actor-based models for network dynamics. Social Networks, 32 (1), 44–60.CrossRefGoogle Scholar
Tudor-Locke, C., Johnson, W., & Katzmarzyk, P. (2009). Accelerometer-determined steps per day in US adults. Medicine & Science in Sports & Exercise, 41 (7), 1384–1391.CrossRefGoogle Scholar
Valente, T. W., Ritt-Olson, A., Stacy, A., Unger, J. B., Okamoto, J., & Sussman, S. (2007). Peer acceleration: Effects of a social network tailored substance abuse prevention program among high-risk adolescents. Addiction, 102 (11), 1804–1815.CrossRefGoogle ScholarPubMed
Valente, T. W. (2010). Social networks and health: models, methods, and applications. Oxford: Oxford University Press.CrossRefGoogle Scholar
Valente, T. W. (2012). Network interventions. Science, 337 (6090), 49–53. doi:10.1126/science.1217330.CrossRefGoogle ScholarPubMed
Valente, T. W., Fujimoto, K., Chou, C.-P. & Spruijt-Metz, D (2009). Adolescent affiliations and adiposity: A social network analysis of friendships and obesity. Journal of Adolescent Health, 45 (2), 202–204. doi:10.1016/j.jadohealth.2009.01.007.CrossRefGoogle ScholarPubMed
Wasserman, S., & Pattison, P. (1996). Logit models and logistic regressions for social networks: I. An introduction to Markov graphs and p*. Psychometrika, 61 (3), 401–425.CrossRefGoogle Scholar
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, 105 (S2), S236–S243.CrossRefGoogle Scholar