Literature DB >> 35108122

Adolescent Body Mass Index and Exposure to Peers with Overweight and Obesity: A Structural Equation Model Approach to Longitudinal Network Data.

Sarah E Piombo1, Jimi Huh1, Thomas W Valente1.   

Abstract

Purpose: Considerable evidence has shown that social networks influence a wide variety of health behaviors. This study investigates whether having friends with overweight/obesity in one's social network (network exposure) can predict changes in body mass index (BMI) throughout high school in a diverse urban population of students.
Methods: Racially and ethnically diverse students from five high schools in Los Angeles County were surveyed at four time points throughout high school from 2010 to 2013 (N = 2091). Surveys included questions on students' social networks, demographics, and health-related information. BMI and weight categories were calculated for all students who provided height and weight information (∼50%). A latent growth curve model was used to assess the growth trajectory of BMI and the time-varying effect of network exposure to friends with overweight/obesity while controlling for demographic covariates.
Results: Hispanic students had a significantly higher initial BMI compared with non-Hispanic students (p < 0.01). There was a significant positive slope for time on BMI growth (p < 0.01). Greater personal network exposure to friends with overweight/obesity was associated with a significant 0.65-point average increase in BMI (p < 0.05) at the first follow-up time point (T2) and a significant 0.62-point average increase in BMI (p < 0.01) at the last follow-up (T4) while controlling for covariates. Conclusions: Using structural equation modeling to understand the relationship between BMI and social networks, we found that increased network exposure to peers with overweight/obesity is associated with higher individual BMI, demonstrating that friendships may influence adolescents' weight status over time.

Entities:  

Keywords:  adolescents; body mass index; high school; latent growth curve; obesity; overweight; social networks

Mesh:

Year:  2022        PMID: 35108122      PMCID: PMC9529305          DOI: 10.1089/chi.2021.0270

Source DB:  PubMed          Journal:  Child Obes        ISSN: 2153-2168            Impact factor:   2.867


  41 in total

1.  Homophily and contagion as explanations for weight similarities among adolescent friends.

Authors:  Kayla de la Haye; Garry Robins; Philip Mohr; Carlene Wilson
Journal:  J Adolesc Health       Date:  2011-06-22       Impact factor: 5.012

Review 2.  Network interventions.

Authors:  Thomas W Valente
Journal:  Science       Date:  2012-07-06       Impact factor: 47.728

3.  Comparison of methods to evaluate changes in relative body mass index in pediatric weight control.

Authors:  Rocco A Paluch; Leonard H Epstein; James N Roemmich
Journal:  Am J Hum Biol       Date:  2007 Jul-Aug       Impact factor: 1.937

4.  Characterizing extreme values of body mass index-for-age by using the 2000 Centers for Disease Control and Prevention growth charts.

Authors:  Katherine M Flegal; Rong Wei; Cynthia L Ogden; David S Freedman; Clifford L Johnson; Lester R Curtin
Journal:  Am J Clin Nutr       Date:  2009-09-23       Impact factor: 7.045

5.  A comparison of peer influence measures as predictors of smoking among predominately hispanic/latino high school adolescents.

Authors:  Thomas W Valente; Kayo Fujimoto; Daniel Soto; Anamara Ritt-Olson; Jennifer B Unger
Journal:  J Adolesc Health       Date:  2012-09-05       Impact factor: 5.012

6.  How physical activity shapes, and is shaped by, adolescent friendships.

Authors:  Kayla de la Haye; Garry Robins; Philip Mohr; Carlene Wilson
Journal:  Soc Sci Med       Date:  2011-07-12       Impact factor: 4.634

7.  Friends Like Me: Associations in Overweight/Obese Status among Adolescent Friends by Race/Ethnicity, Sex, and Friendship Type.

Authors:  Meg Bruening; Richard MacLehose; Marla E Eisenberg; Sunkyung Kim; Mary Story; Dianne Neumark-Sztainer
Journal:  Child Obes       Date:  2015-12       Impact factor: 2.992

8.  Identifying the best body mass index metric to assess adiposity change in children.

Authors:  Lisa Kakinami; Mélanie Henderson; Arnaud Chiolero; Tim J Cole; Gilles Paradis
Journal:  Arch Dis Child       Date:  2014-05-19       Impact factor: 3.791

9.  Growth Trajectories of Health Behaviors from Adolescence through Young Adulthood.

Authors:  Nora Wiium; Kyrre Breivik; Bente Wold
Journal:  Int J Environ Res Public Health       Date:  2015-10-28       Impact factor: 3.390

10.  What is the best measure of adiposity change in growing children: BMI, BMI %, BMI z-score or BMI centile?

Authors:  T J Cole; M S Faith; A Pietrobelli; M Heo
Journal:  Eur J Clin Nutr       Date:  2005-03       Impact factor: 4.016

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