Approaches to the Prevention and Management of Childhood Obesity: The Role of Social Networks and the Use of Social Media and Related Electronic Technologies
Despite the significant attention and resources committed to the prevention and treatment of childhood obesity, the epidemic shows no sign of abating.1 Although all children are at risk for obesity, there are marked disparities by race/ethnicity, socioeconomic status, neighborhood, and access to health care.2 Any successful approach to addressing the overall burden of obesity must not rely solely on the healthcare system,3 but must include the implementation of policies that take into account the physical and social environment to change the eating and activity behaviors of children and their families. Examples of such policy efforts include the attempts to ban food marketing to children and to increase access to safe and appealing venues for exercise.4,5 Despite these important policy directions, efforts to sustain changes in behavior remain challenging, and the evidence about which interventions are most effective is still incomplete.6
Social networks are groupings of interconnected 2-way relationships. Modern-day social networks typically rely on social media for communication. More specifically, the term social media refers to the use of Web-based and mobile technologies that are commonly used for interaction and communication within networks. Research underscores strong associations between participation in social networks and preventive health behavior.7–11 Recently, it was observed that obesity may spread across social networks, suggesting that these networks could be leveraged for prevention or treatment.12,13 The main purpose of this statement is to evaluate the role of social networks and social media in relation to childhood obesity. We build on a recent statement by the American Heart Association directed at the management of adult weight management strategies in the ambulatory setting that focused on the use of Internet-based and other related technologies.14 In this statement, we provide an overview of social networks and their relationship to health and obesity and describe social network–based interventions. In addition, we review specific intervention strategies for obesity that rely on various forms of social media. Finally, we suggest recommendations for future directions.
Overview of Social Networks
As groupings of interconnected relationships, social networks can be constructed by asking individuals, referred to as “egos,” to nominate contacts, referred to as “alters.” For example, a school-aged child (ie, ego) may be asked to nominate 5 best friends (ie, alters), creating ties between the ego and the alters. Both the directionality (eg, reciprocal versus unidirectional) and the strength of the relationships are important when considering social influence. Both strong and weak ties affect health, and their relative roles and importance in networks are subjects of current research.15 Strong ties (eg, family and friends) are characterized by emotional attachment, reciprocity, and time spent together,16 and often link people with similar characteristics, whereas weak ties (eg, acquaintances) tend to be more formal and organized by social rules and roles.15 Strong ties may be more important in relation to social support, whereas weak ties may serve as information conduits and may link individuals to other contacts and resources.15,16 Both strong and weak ties likely help to establish cultural norms.15,17
People tend to select friends with similar behaviors, interests, and appearances. Researchers must disentangle peer selection based on this similarity, known as homophily, from causal peer influences on an individual’s behaviors, known as induction.12,18 The environmental context is another important factor affecting social networks. Friends may exhibit similar behavior because they are subject to the same environmental constraints or social circumstances, such as neighborhood, school setting, or socioeconomic status.19
Pathways Linking Social Networks to Health
Social networks can influence health through numerous pathways. Alters may provide emotional support, instrumental support (financial or practical), informational support, or appraisal (decision-making) support.20 Social support, whether real or perceived, can buffer stress by enhancing coping skills.17 Although social support may buffer stress, social interactions can also be a source of stress, thereby negatively affecting health.17 Another pathway is social integration, which can increase access to health information and promote self-worth and self-care on the basis of societal norms and expectations.17 However, if cultural norms promote unhealthy behaviors, social integration could negatively affect health. For example, smoking was once a highly accepted and socially valued behavior that was more common in higher socioeconomic groups. Social norms have changed, and smoking is now considered a destructive behavior. Smoking is now more common in lower socioeconomic and disadvantaged populations and is likely implicated in social inequalities in health.21,22
A separate concept that is related to social networks is social capital. Social capital has been defined as the resources obtained by a group or an individual through a network of social relationships, as well as the number and quality of the relationships in the network.23 An alternative definition of social capital focuses on the trust, norms, and networks that social organizations provide that allow the facilitation of coordinated action to advance civil society, democratization, and political development.24 Thus, social networks may enhance health by contributing to social capital, and social capital can be thought of as a capital that resides between individuals, enabling them to access other resources or benefits.
Social Networks and Childhood Obesity
An analysis of the Framingham Heart Study, which included only adults, found that spouses, siblings, and friends were at greater risk for obesity if their alters were obese. Furthermore, the risk of obesity was increased for those contacts up to 3 ties away.12 Among children and adolescents, body mass index (BMI) is associated with school-based friendship clusters; school friends are significantly similar in terms of their BMI, with friends of the highest BMI appearing to be most similar. The frequency of fast food consumption clusters within groups of boys, as do body image concerns, dieting, and eating disorders among girls.19 The same is true for tobacco use in that peer pressure is a potent stimulus for smoking initiation.25 Additional longitudinal research is needed to clarify the degree to which these associations are due to induction, homophily, or environmental factors.19
Overweight youth are more likely to be socially isolated and marginalized.26–28 Social networks can also affect their body image. For example, adolescents are more likely to underestimate their own weight status when surrounded by obese peers.29 Obesity-related health behaviors are also associated with adolescent social networks, including participation in organized sports, fast food consumption, and computer/video game screen time.30 Social networks therefore may be critical in shaping young people’s eating behaviors and body weight and vice versa, and their role suggests the potential of social network–based health promotion interventions.
The Role of the Built Environment
The built environment may modify the extent to which social networks affect childhood obesity.31 The built environment encompasses the constructed and open spaces outside the family home, including commercial and noncommercial buildings, public open areas, such as parks playgrounds and green spaces, and road and transportation infrastructure.32 Features of the built environment such as unfavorable community design and poor transportation infrastructure are associated with decreased energy expenditure.33,34
Social capital can also be adversely affected by an environment that limits social connections, such as high-traffic areas and the presence of dense commercial areas.35,36 Combining social network analysis with environmental assessment can identify interventions for childhood obesity treatment or prevention.37 Interventions modifying the built environment may be more likely to be successful if such efforts are designed to enhance social networks. Specific improvements to the built environment could be designed to promote face-to-face contacts and to encourage the formation of social networks.38 Moreover, providing safe and appealing places for peer groups could extend social networks and promote the diffusion of healthy behaviors. For example, improving the condition of school fields, making them available for use outside of school hours, ensuring safe access, and providing supervision support the formation of social networks and involvement in structured physical activity both during and after school.30,39,40 Geocaching, an activity during which individuals or groups search for items described on Web sites using navigational tools, such as GPS tracking devices, also leverages social networks and the built environment to increase physical activity. Thus, participation encourages both social networking and outdoor activity.41 Another example is the Chick Clique program, in which girls wear pedometers to share information on travel distances and destinations to all members within a specific network of friends. The program is based on providing positive role modeling and support and reinforcement from peers.42 These examples can inform innovative strategies that tap into the potential benefits of social networks, the built environment, and technology to reduce the burden of childhood obesity.
Concerns about safety from traffic or crime may be important barriers to outdoor activity.43 Parental perception of the neighborhood safety may be a more salient determinant of childhood obesity compared with more objective indicators of the built environment.44 Thus, using social networks of parents to increase awareness of and response to safety preoccupations (eg, crime, traffic) appears warranted and may help us understand how to combat childhood obesity more effectively. Moreover, targeting disadvantaged areas for improvements in the built environment may ultimately reduce health disparities across social strata and benefit society as a whole.45,46
Interventions Targeting Existing Social Networks
All individuals are members of many diverse social networks. Strategies have been developed to identify opinion leaders within social networks (eg, local celebrities, community observation, interviews).29 It is unclear, however, whether these opinion leaders could be recruited to develop strategies to affect childhood obesity within social networks. However, a cluster-randomized, controlled trial of a peer-led program based on these strategies was effective for tobacco prevention among adolescents.47
The association between social networks and participation in structured physical activity suggests that there is opportunity to develop school-based interventions within physical education classes to target obesity.19 The Chefs Move to Schools initiative within First Lady Michelle Obama’s Let’s Move campaign encourages chefs to partner with schools to support the creation of healthy, affordable meals and to educate children on healthy cooking and eating.48 Because of budget constraints within schools, such interventions will need to be relatively inexpensive and easy to adopt. In addition, churches and other religious settings can serve as important environments for community-based participatory interventions. Such an effort has recently been established to develop a culturally appropriate faith-based obesity intervention examining diet, physical activity, and body image in black children, parents, and church leaders in the Sunday school setting.49 Future work will need to evaluate the effectiveness and sustainability of such interventions.
Many adolescents are part of virtual social networks defined by Internet use. Social network sites like Facebook represent natural points for intervention. Data from these sites have been used to assess the association between social networks and a variety of outcomes,50,51 However, we are unaware of studies that have developed interventions specifically within these social networks. Identifying and measuring outcomes would be difficult. The ethical issues involved in social media interventions are beyond the scope of this statement, and it is the responsibility of each researcher to give this topic careful consideration.
Interventions Based on the Purposeful Development of Social Networks
In addition to targeting existing social networks, future interventions could be based on the development of social networks purposefully developed to address obesity. In fact, this is the basis of the Weight Watchers program.52 Little is known about the effectiveness of these programs in children or adolescents or whether parental involvement has spillover beneficial effects for obesity prevention or treatment in their children. However, these programs are easily accessible and are now available over the Internet. Another example is the Weigh2Rock program (http://www.weigh2rock.com), which offers online health and weight loss education; an online support community of several thousand overweight kids, teens, and parents; and self-managed personal weight loss charts and goal setting, which may be viewed by a child’s healthcare provider.
Social Media: Internet-Based Strategies
Recent advances in technology provide new and emerging tools as interactive methods of intervention for the treatment and prevention of obesity. Nearly all (95%) adolescents 12 to 17 years of age have Internet access, and most are active in online social media.53 Internet-based programs and other electronic technologies have been used in both the treatment and prevention of overweight and obesity in youth.54,55 Benefits of the form of these interactive electronic interventions include their widespread availability in the school and home, popularity among youth, ability to engage and immerse participants, and ability to provide immediate tailored feedback. These technologies can also be used to provide specific content addressing healthy lifestyles with regard to diet and exercise. In addition, these technologies hold significant promise for application in the research setting because they are relatively inexpensive to scale up for broad implementation and can facilitate data collection.
Randomized Trials of Internet-Based Obesity Interventions
Several Internet-based randomized trials have been performed in overweight children and adolescents. An et al54 performed a systematic review of studies published in peer-reviewed journals that used randomized, controlled trials via the Internet and reported weight loss, BMI change, physical activity, and dietary intake as outcome variables. Studies were included only if the Internet intervention was directed toward study participants or their families, not solely toward healthcare providers. Eight studies were included. Studies were variable in their use of social media as the main agent of therapy or as an adjunct to other types of therapy, including nutrition and physical activity engagement.
Six of these studies suffered from small sample size (n=35–80),56–60 and 3 studies were from the same cohort of patients.58,59,61 Doyle et al57 and Celio et al56 demonstrated a reduction in BMI z scores in those receiving an interactive Internet-delivered cognitive behavioral program compared with those receiving usual care with basic information provided on nutrition and physical activity. Baranowski et al,60 however, did not show any significant difference in girls randomized to a monthly Internet intervention and those receiving no Internet intervention; however, both groups also attended a special 4-week summer day camp, and there was a significant difference in the baseline mean BMI between the Internet intervention group (21.1±4.4 kg/m2) and the control group (26.3±7.9 kg/m2). White et al61 and Williamson et al58,59 studied the same cohort, demonstrating that active family-based behavioral Internet interventions resulted in more loss of body weight and lower dietary fat intake than passive primary health education. The Internet-based interactive program included e-mail counseling on self-monitoring, problem solving, goal setting, and relapse prevention. Compared with a noninteractive program, greater efficacy was seen in the interactive program.
In 2 larger studies, Marks et al62 studied 359 adolescent girls and did not demonstrate any significant difference between subjects receiving intervention over the Internet and those receiving a print workbook, with both groups improving in the degree of physical activity, self-efficacy, and intentions. Haerens et al63 studied 2991 seventh and eighth graders, randomizing them to receive a computerized, tailored intervention either with or without parental involvement or to a control group with no intervention. In girls, the 1- and 2-year differences in BMI and BMI z score in the intervention with parents group were significant. There was a significant sex interaction with no positive intervention effect seen in boys.
Recently, a school-based, randomized, controlled trial in rural Louisiana was implemented within 14 schools using a student Web site, an Internet counselor Web site, and an Internet counseling process. The Internet intervention contained lessons on health eating and regular physical activity, and students communicated with a counselor through a chat room and e-mail.64 This study was focused on the prevention of weight gain.
In summary, findings from these studies have been mixed, with some finding improvement.56–58,61 Interpreting the effectiveness of these interventions and the role of social networks is challenging because of the small sample sizes, the variations in treatment provided to the intervention and control groups, the outcome measures, and the duration of follow-up. Furthermore, there was variable use of the Internet-based interventions, raising questions about the degree to which the interventions led to meaningful virtual social networks. Two other larger trials had similar limitations and had mixed results.62,63 Although some of these studies focused on the prevention of abnormal weight gain and the treatment of overweight and obesity, studies also need to be performed on the maintenance of appropriate weight once weight loss is achieved.
Of note, attrition rates affect the overall power of the studies. Log-on rates, which are measures of program use, are highly variable. E-mail reminders, financial incentives, and the provision of a Web master to help participants with technical difficulties can have positive effects on the log-on rate.65
Social Media: E-Mail and Texting Interventions
Several studies have demonstrated the benefit of e-mail and texting interventions on weight loss in adolescents. However, these interventions do not necessarily work through social networks, especially if communication is not bidirectional. A school-based intervention incorporating physical activity monitoring with pedometers and e-mail support was successful in promoting physical activity and selected healthy eating behaviors in adolescent boys and girls. Lubans et al66 provided adolescents with an intervention incorporating pedometers and e-mail support on physical activity, sedentary behavior, and healthy eating. Among those in the intervention group, boys increased their step counts by 956±4107 steps per day and girls by 999±1999 steps per day. The intervention significantly decreased the number of energy-dense/low-nutrient snacks consumed by boys (P=0.043) and increased the amount of fruit consumed by girls (P=0.028). The intervention did not have a statistically significant effect on sedentary behavior.
Similarly, text messaging has also been used as a modality for intervention. Text messaging may be especially useful for self-monitoring because of the potential for providing both support and immediate feedback based on a patient’s specific goals. In a study to evaluate the use of sweetened beverages and amount of screen time and physical activity in adolescents, Shapiro et al67 randomized study participants to text messaging with feedback, paper diaries, or an unmonitored control group. Children randomized to the texting intervention had lower attrition (28%) than both the paper diary (61%) and control (50%) groups and significantly greater adherence to self-monitoring than the paper diary group (43% versus 19%: P<0.02). Seventy-two percent in the texting group completed the study versus 39% and 50% in the paper diary and control groups. From this study, children appear to prefer a technological, tailored, interactive program over a more traditional paper diary program, and when enrolled, those using texting had greater adherence and higher completion rates.
Other Social Media Technologies
Active video games enjoy widespread appeal to youth and have been demonstrated to increase energy expenditure and physical activity compared with sedentary video gaming.68,69 Several of these technologies also offer Internet connectivity, including Nintendo Wii Fit and Microsoft Kinect, and the ability to join an online gaming service that allows one to play games against other members in its online community with the use of an avatar. A recent study of the effects of the exergaming experience70 found that seeing the image of self on screen works positively for individuals with low body image but works negatively for individuals with high body image. The impact of this research may have implications for future studies using active video gaming and the role of social networks.
Risks and Potential Harms of Social Media Use
Because of their limited capacity for self-regulation and susceptibility to peer pressure, adolescents can be at risk as they navigate social media. These risks include being exposed to online expressions of behavior such as bullying, clique formation, and sexual experimentation and have introduced problems such as cyberbullying, privacy issues, and sexting. Other problems that merit awareness include Internet addiction and resultant sleep deprivation.71 Clinicians need to increase their knowledge of digital technology so that they can have a more educated frame of reference for the tools that their patients and families are using, which will aid in providing timely anticipatory media guidance and diagnosing social media–related harms should they arise. In addition, clinicians should counsel parents about the need for awareness about the technology that their children are using.
Role of the Clinician in Using Social Networks to Treat Adolescent Obesity
The American Academy of Pediatrics–endorsed 2007 recommendations from the Expert Committee on the Assessment, Prevention and Treatment of Child and Adolescent Overweight and Obesity make no mention of social networks.72 This is not surprising, given that the evidence gathered to that date was preliminary and that the recommendations focused on what primary care practitioners could do in their offices and clinics. In fact, although adolescents and their families are likely to recognize a problem with overweight, it is the primary care practitioner following the adolescent over time who has the growth data to quantify the magnitude of the problem accurately for the family. That same practitioner, who often is a trusted source of information on health issues, is also in a position to assess and affect the adolescent’s and family’s motivation to change.
It is for this reason that these recommendations cite motivation, particularly motivational interviewing, as part of the clinician’s role.73 A full discussion of motivational interviewing is beyond the scope of this review. Briefly, motivational interviewing takes into account readiness to change, uses neutral questions and reflective listening to explore the beliefs and values, and in so doing elicits motivation.74 As a next step, the clinician is in a position to work with the adolescent to create strategies to address the problem. The clinician could use motivational interviewing to work with the adolescent on diet and physical activity issues on a one-to-one basis.75 Although there is a lack of studies on the use of motivational interviewing with respect to social network or social media use, it would undoubtedly be a more efficient and possibly more effective use of the clinician’s time to direct the adolescent and family to a social networking resource on this topic. The clinician could then continue to serve as a resource to the adolescent and family by providing accurate information, advice, and monitoring of growth but defer the bulk of intervention to the social networking site. In addition, the clinician could reinforce the use of the social networking resource, which can be challenging to sustain over time. Motivational enhancement delivered through social media (typically facilitated online or through electronic communication by a counselor in a nonjudgmental manner) may be helpful in sustaining efforts in weight loss.14,76
Future Directions for Clinicians, Policy Makers, and Researchers
The results of these several studies and ongoing initiatives support the promise and potential of social media and electronic technology as a viable component of weight management programs and underscore the need for additional research to optimize these technologies as effective delivery channels for youth. The Table lists the general steps and describes the key components to guide the development of interventions targeting social networks. In general, more evidence is needed to support specific strategies for incorporating collaborative approaches for weight management. Future work should address whether engagement within a social network either increases the effectiveness of these interventions or promotes greater sustainability. Most treatment is aimed at behavior changes, which include such elements as stimulus control, self-monitoring, goal setting, and rewards. Clinicians, policy makers, and researchers should consider flexible models for behavior change in adolescents that use social networks and social media and determine how the use of social networks and social media applies to each of these elements of behavior change.
|1. Define the goal of the intervention||As with any intervention, it is important to identify what needs to be improved, expectations for the effectiveness of the intervention, and how to measure change.|
|2. Identify the social network||Based on the goal of the intervention, the social network should be identified and the targeted egos and relevant alters specified. This may involve using an existing social network or developing new social networks.|
|3. Develop and pilot test the intervention||Of prime importance is identifying how the intervention will interact with the social network. Pilot testing should use mixed-methods techniques to evaluate the potential benefits and harms of the intervention.|
|4. Implement the intervention||During implementation, it is critical to assess the impact of the intervention carefully and to revise activities to minimize harm. This evaluation should include both process and outcome measures. Careful attention should be paid to future sustainability.|
|5. Spread the intervention||Many successful projects are not disseminated after completion. However, social network projects are uniquely well suited to the spread of innovation.|
Planning and training should be incorporated into collaborative approaches that involve physicians, nurses, or other providers. Potential collaboration with industry will require transparency to promote healthy behavior over promotional activity for a given product. In addition, electronic technology is constantly evolving and will require continual reevaluation over time. There is clearly a need for larger studies, particularly those that include technologically based interventions that enroll a diverse spectrum of overweight and obese adolescents in terms of sex, race, geographic location, and socioeconomic status. Large sample sizes are required to investigate whether different demographic characteristics modify the impact of social networks and social media on subsets of the population. There is also a need to investigate the specific features of technology-based interventions (eg, content, format, device) that make such interventions appealing to youth and successful in promoting healthy weight. However, it is the mere existence of the technology itself rather than any specific attribute of it that is important to recognize; those who are interested in public health or in providing medical care will likely see social media become a powerful and perhaps dominant communication tool of the 21st century.
Although social networks may be developed to bring about a desired behavior change, it will be important to harness the content of the relationships as they exist within a particular network to inform and direct interventions that are likely to be sustainable. The use of social media with interactive bidirectional interventions, coupled with parental involvement, appears to hold promise. The development of methods to ensure privacy protection and monitoring of outcomes should take priority. Initiating and sustaining behavior change in accordance with the values and goals of the members of that social network needs to be the goal toward empowering members of the community to use the strength of their social ties to choose pathways toward health promotion.
|Writing Group Member||Employment||Research Grant||Other Research Support||Speakers’ Bureau/Honoraria||Expert Witness||Ownership Interest||Consultant/Advisory Board||Other|
|Jennifer S. Li||Duke University||None||None||None||None||None||None||None|
|Tracie A. Barnett||University of Montreal||None||None||None||None||None||None||None|
|Elizabeth Goodman||Massachusetts General Hospital for Children/Harvard Medical School||None||None||None||None||None||None||None|
|Alex R. Kemper||Duke University||None||None||None||None||None||None||None|
|Richard C. Wasserman||University of Vermont||None||None||None||None||None||None||None|
|Reviewer||Employment||Research Grant||Other Research Support||Speakers’ Bureau/Honoraria||Expert Witness||Ownership Interest||Consultant/Advisory Board||Other|
|Stephen R. Daniels||The Children’s Hospital||None||None||None||None||None||None||None|
|Samuel S. Gidding||A.I. duPont Hospital for Children||None||GlaxoSmithKline*||None||None||None||None||None|
|Julie St. Pierre||Chicoutimi Hospital||None||None||None||None||None||None||None|
|Roberta Gay Williams||Children’s Hospital Los Angeles, University of Southern California||None||None||None||None||None||None||None|
Ogden CL, Carroll MD, Curtin LR, Lamb MM, Fegal KM. Prevalence of high body mass index in US children and adolescents, 2007–2008.JAMA. 2010; 303:242–249.CrossrefMedlineGoogle Scholar
Bethell C, Simpson L, Stumbo S, Carle AC, Gobojav N. National, state, and local disparities in childhood obesity.Health Aff (Millwood). 2010; 29:347–356.CrossrefMedlineGoogle Scholar
Wake M. Issues in obesity monitoring, screening and subsequent treatment.Curr Opin Pediatr. 2009; 21:811–816.CrossrefMedlineGoogle Scholar
Nestle M. Food marketing and childhood obesity: a matter of policy.N Engl J Med. 2006; 354:2527–2529.CrossrefMedlineGoogle Scholar
Boehmer TK, Luke DA, Haire-Joshu DL, Bates HS, Brownson RC. Preventing childhood obesity through state policy: predictors of bill enactment.Am J Prev Med. 2008; 34:333–340.CrossrefMedlineGoogle Scholar
Frieden TR, Dietz W, Collins J. Reducing childhood obesity through policy change: acting now to prevent obesity.Health Aff (Millwood). 2010; 29:357–363.CrossrefMedlineGoogle Scholar
Berkman LF, Syme SL. Social networks, host resistance, and mortality: a nine-year follow-up study of Alameda County residents.Am J Epidemiol. 1979; 109:186–204.CrossrefMedlineGoogle Scholar
Cassel J. The contribution of the social environment to host resistance: Fourth Wade Hampton Frost Lecture.Am J Epidemiol. 1976; 104:107–123.CrossrefMedlineGoogle Scholar
Cobb S. Presidential Address-1976: social support as a moderator of life stress.Psychosom Med. 1976; 38:300–314.CrossrefMedlineGoogle Scholar
Smith KP, Christakis NA. Social networks and health.Annu Rev Sociol. 2008; 34:405–429.CrossrefGoogle Scholar
Langlie JK. Social networks, health beliefs, and preventive health behavior.J Health Soc Behav. 1977; 18:244–260.CrossrefMedlineGoogle Scholar
Christakis NA, Fowler JH. The spread of obesity in a large social network over 32 years.N Engl J Med. 2007; 357:370–379.CrossrefMedlineGoogle Scholar
Bahr DB, Browning RC, Wyatt HR, Hill JO. Exploiting social networks to mitigate the obesity epidemic.Obesity. 2009; 17:723–728.CrossrefMedlineGoogle Scholar
Rao G, Burke LE, Spring B, Ewing LJ, Turk M, Lichtenstein AH, Cornier MA, Spence JD, Coons M; on behalf of the American Heart Association Obesity Committee of the Council on Nutrition, Physical Activity and Metabolism; Council on Clinical Cardiology; Council on Cardiovascular Nursing; Council on the Kidney in Cardiovascular Disease; Stroke Council. New and emerging weight management strategies for busy ambulatory settings: a scientific statement from the American Heart Association.Circulation. 2011; 124:1182–1203.LinkGoogle Scholar
Thoits PA. Mechanisms linking social ties and support to physical and mental health.J Health Soc Behav. 2011; 52:145–161.CrossrefMedlineGoogle Scholar
Granovetter MS. The strength of weak ties.Am J Sociol. 1973; 78:1360–1380.CrossrefGoogle Scholar
Cohen S. Social relationships and health.Am Psychol. 2004; 59:676–684.CrossrefMedlineGoogle Scholar
McPherson M, Smith-Lovin L, Cook JM. Birds of a feather: homophily in social networks.Annu Rev Sociol. 2001; 27:415–444.CrossrefGoogle Scholar
Fletcher A, Bonnell C, Sorhaindo A. You are what your friends eat: systematic review of social network analyses of young people’s eating behaviours and bodyweight.J Epidemiol Community Health. 2011; 65:548–555.CrossrefMedlineGoogle Scholar
Berkman LF, Glass T, Brissette I, Seeman TE. From social integration to health: Durkheim in the new millennium.Soc Sci Med. 2000; 51:843–857.CrossrefMedlineGoogle Scholar
Poland B, Frohlich K, Haines RJ, Mykhalovskiy E, Rock M, Sparks R. The social context of smoking: the next frontier in tobacco control?Tob Control. 2006; 15:59–63.CrossrefMedlineGoogle Scholar
Fagan P, King G, Lawrence D, Petrucci SA, Robinson RG, Banks D, Marable S, Grana R. Eliminating tobacco-related health disparities: directions for future research.Am J Public Health. 2004; 94:211–217.CrossrefMedlineGoogle Scholar
Bourdieu P. Social space and the genesis of groups.Theory Soc. 1985; 14:723–744.CrossrefGoogle Scholar
Putnam RD. Bowling Alone: The Collapse and Revival of American Community.New York, NY: Simon and Schuster; 1995.Google Scholar
Scherrer JF, Xian H, Pan H, Pergadia ML, Madden PA, Grant JD, Sartor CE, Haber JR, Jacob T, Bucholz KK. Parent, sibling and peer influences on smoking initiation, regular smoking and nicotine dependence: results from a genetically informative design.Addict Behav. 2012; 37:240–247.CrossrefMedlineGoogle Scholar
Strauss RS, Pollack HA. Social marginalization of overweight children.Arch Pediatr Adolesc Med. 2003; 157:746–752.CrossrefMedlineGoogle Scholar
Trogdon JG, Nonnemaker J, Pais J. Peer effects in adolescent overweight.J Health Econ. 2008; 27:1388–1399.CrossrefMedlineGoogle Scholar
Valente TW, Fujimoto K, Chou CP, Spruijt-Metz D. Adolescent affiliations and adiposity: a social network analysis of friendships and obesity.J Adolesc Health. 2009; 45:202–204.CrossrefMedlineGoogle Scholar
Ali MM, Amialchuk A, Renna F. Social network and weight misperception among adolescents.South Econ J. 2011; 77:827–842.CrossrefGoogle Scholar
de la Haye K, Robins G, Mohr P, Wilson C. Obesity-related behaviors in adolescent friendship networks.Social Networks. 2010; 32:161–167.CrossrefGoogle Scholar
Cohen-Cole E, Fletcher JM. Is obesity contagious? Social networks vs. environmental factors in the obesity epidemic.J Health Econ. 2008; 27:1382–1387.CrossrefMedlineGoogle Scholar
Frank LD, Engelke PO, Schmid TL. Health and Community Design: The Impact of the Built Environment on Physical Activity.Washington, DC: Island Press; 2003.Google Scholar
Frank LD, Andresen MA, Schmid TL. Obesity relationships with community design, physical activity, and time spent in cars.Am J Prev Med. 2004; 27:87–96.CrossrefMedlineGoogle Scholar
Lopez R. Urban sprawl and risk for being overweight or obese.Am J Public Health. 2004; 94:1574–1579.CrossrefMedlineGoogle Scholar
Mullan E. Do you think that your local area is a good place for young people to group up? The effects of traffic and car parking on young people’s views.Health Place. 2003; 9:351–360.CrossrefMedlineGoogle Scholar
Wood L, Frank LD, Giles-Corti B. Sense of community and its relationship with walking and neighborhood design.Soc Sci Med. 2010; 70:1381–1390.CrossrefMedlineGoogle Scholar
Davison KK, Birch LL. Childhood overweight: a contextual model and recommendations for future research.Obes Rev. 2001; 2:159–171.CrossrefMedlineGoogle Scholar
Cocciolo A, Mineo C, Meier E. Using online social networks to build healthy communities: a design-based research investigation. Paper presented at: World Conference on Educational Multimedia; June 28-July 2, 2010; Toronto, ON, Canada.Google Scholar
Voorhees CC, Murray D, Welk G, Birnbaum A, Ribisl KM, Johnson CC, Pfeiffer KA, Saksvig B, Jobe JB. The role of peer social network factors and physical activity in adolescent girls.Am J Health Behav. 2005; 29:183–190.CrossrefMedlineGoogle Scholar
Wallis-MacDonald K, Jago R, Page AS, Brockman R, Thompson JL. School-based friendship networks and children’s physical activity: a spatial analytical approach.Soc Sci Med. 2011; 73:6–12.CrossrefMedlineGoogle Scholar
Flett MR, Moore RW, Pfeiffer KA, Belonga J, Navarre J. Connecting children and family with nature-based physical activity.Am J Health Educ. 2010; 41:292–300.CrossrefGoogle Scholar
Toscos T, Farber A, An S, Gandhi MP. Chick clique: persuasive technology to motivate teenage girls to exercise. Paper presented at: ACM CHI 2006 Conference; April 22–27, 2006; Montreal, QC, Canada.Google Scholar
- 43. Committee on Environmental Health; Tester M. The built environment: designing communities to promote activity in children.Pediatrics. 2009; 123:1591–1598.CrossrefMedlineGoogle Scholar
Timperio A, Salmon J, Telford A, Crawford D. Perceptions of local neighbourhood environments and their relationship to childhood overweight and obesity.Int J Obes (Lond). 2005; 29:170–175.CrossrefMedlineGoogle Scholar
Cutts BB, Darby KJ, Boone CG, Brewis A. City structure, obesity, and environmental justice: an integrated analysis of physical and social barriers to walkable streets and park access.Soc Sci Med. 2009; 69:1314–1322.CrossrefMedlineGoogle Scholar
Wood L, Shannon T, Bulsara M, Pikora T, McCormack G, Giles-Corti B. The anatomy of the safe and social suburb: an exploratory study of the built environment, social capital and residents’ perceptions of safety.Health Place. 2008; 14:15–31.CrossrefMedlineGoogle Scholar
Starkey F, Audrey S, Holliday J, Moore L, Campbell R. Identifying influential young people to undertake effective peer-led health promotion: the example of A Stop Smoking in Schools Trial (ASSIST).Health Educ Res. 2009; 24:977–988.CrossrefMedlineGoogle Scholar
Tanne JH. Michelle Obama launches programme to combat US childhood obesity.BMJ. 2010; 340:c948.CrossrefMedlineGoogle Scholar
Davis DS, Goldmon MV, Coker-Appiah DS. Using a community-based participatory research approach to develop a faith-based obesity intervention for African American children.Health Promot Pract. 2011; 12:811–822.CrossrefMedlineGoogle Scholar
Lewis K, Kaufman J, Gonzalez M, Wimmer A, Christakis N. Tastes, ties, and time: a new social network dataset using Facebook.com.Social Networks. 2008; 30:330–342.CrossrefGoogle Scholar
Moreno MA, Briner LR, Williams A, Brockman L, Walker L, Christakis DA. A content analysis of displayed alcohol references on a social networking web site.J Adolesc Health. 2010; 47:168–175.CrossrefMedlineGoogle Scholar
Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish, Weight Watchers, and Zone diets for weight loss and heart disease risk reduction: a randomized trial.JAMA. 2005; 293:43–53.CrossrefMedlineGoogle Scholar
Lenhart A, Madden M, Smith A, Purcell K, Zickuhr K, Rainie L. Teens, Kindness and Cruelty on Social Networking Sites.Washington, DC: Pew Research Center; 2011.Google Scholar
An JY, Hayman LL, Park YS, Dusaj TK, Ayres CG. Web-based weight management programs for children and adolescents: a systematic review of randomized controlled trial studies.ANS Adv Nurs Sci. 2009; 32:222–240.CrossrefMedlineGoogle Scholar
Nguyen B, Kornman KP, Baur LA. A review of electronic interventions for prevention and treatment of overweight and obesity in young people.Obes Rev. 2011; 12:e298–e314.CrossrefMedlineGoogle Scholar
Celio A. Early Intervention of Eating- and Weight-Related Problems via the Internet in Overweight Adolescents: A Randomized Controlled Trial [dissertation].San Diego: Joint Doctoral Program in Clinical Psychology, University of California/San Diego State University; 2005.Google Scholar
Doyle AC, Goldschmidt A, Huang C, Winzelberg AJ, Taylor CB, Wilfley DE. Reduction of overweight and eating disorder symptoms via the Internet in adolescents: a randomized controlled trial.J Adolesc Health. 2008; 43:172–179.CrossrefMedlineGoogle Scholar
Williamson DA, Martin PD, White MA, Newton R, Walden H, York-Crowe E, Alfonso A, Gordon S, Ryan D. Efficacy of an Internet-based behavioral weight loss program for overweight adolescent African-American girls.Eat Weight Disord. 2005; 10:193–203.CrossrefMedlineGoogle Scholar
Williamson DA, Walden HM, White MA, York-Crowe E, Newton RL, Alfonso A, Gordon S, Ryan D. Two-year Internet-based randomized controlled trial for weight loss in African-American girls.Obesity (Silver Spring). 2006; 14:1231–1243.CrossrefMedlineGoogle Scholar
Baranowski T, Baranowski JC, Cullen KW, Thompson DI, Nicklas T, Zakeri IE, Rochon J. The Fun, Food, and Fitness Project (FFFP): the Baylor GEMS pilot study.Ethn Dis. 2003; 13:S30–S39.MedlineGoogle Scholar
White MA, Martin PD, Newton RL, Walden HM, York-Crowe EE, Gordon ST, Ryan DH, Williamson DA. Mediators of weight loss in a family-based intervention presented over the Internet.Obes Res. 2004; 12:1050–1059.CrossrefMedlineGoogle Scholar
Marks JT, Campbell MK, Ward DS, Ribisl KM, Wildemuth BM, Symons MJ. A comparison of Web and print media for physical activity promotion among adolescent girls.J Adolesc Health. 2006; 39:96–104.CrossrefMedlineGoogle Scholar
Haerens L, Deforche B, Maes L, Stevens V, Cardon G, De Bourdeaudhuij I. Body mass effects of a physical activity and healthy food intervention in middle schools.Obesity (Silver Spring). 2006; 14:847–853.CrossrefMedlineGoogle Scholar
Gabriele JM, Stewart TM, Sample A, Davis AB, Allen R, Martin CK, Newton RL, Williamson DA. Development of an Internet-based obesity prevention program for children.J Diabetes Sci Technol. 2010; 4:723–732.CrossrefMedlineGoogle Scholar
Thompson D, Baranowski T, Cullen K, Watson K, Canada A, Bhatt R, Liu Y, Zakeri I. Food, Fun and Fitness Internet program for girls: influencing log-on rate.Health Educ Res. 2007; 23:228–237.CrossrefMedlineGoogle Scholar
Lubans DR, Morgan PJ, Callister R, Collins CE. Effects of integrating pedometers, parental materials, and e-mail support within an extracurricular school sport intervention.J Adolesc Health. 2009; 44:176–183.CrossrefMedlineGoogle Scholar
Shapiro JR, Bauer S, Hamer RM, Kordy H, Ward D, Bulik CM. Use of text messaging for monitoring sugar-sweetened beverages, physical activity, and screen time in children: a pilot study.J Nutr Educ Behav. 2008; 40:385–391.CrossrefMedlineGoogle Scholar
Biddiss E, Irwin J. Active video games to promote physical activity in children and youth: a systematic review.Arch Pediatr Adolesc Med. 2010; 164:664–672.CrossrefMedlineGoogle Scholar
Graves LE, Ridgers ND, Williams K, Stratton G, Atkinson G, Cable NT. The physiological cost and enjoyment of Wii Fit in adolescents, young adults, and older adults.J Phys Act Health. 2010; 7:393–401.CrossrefMedlineGoogle Scholar
Song H, Peng W, Lee KM. Promoting exercise self-efficacy with an exergame.J Health Commun. 2011; 16:148–162.CrossrefMedlineGoogle Scholar
O’Keeffe GS, Clarke-Pearson K; Council on Communications and Media. Clinical report: the impact of social media on children, adolescents, and families.Pediatrics. 2011; 127:800–804.CrossrefMedlineGoogle Scholar
Barlow SE; Expert Committee. Expert Committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report.Pediatrics. 2007; 120(suppl 4):S164–S192.CrossrefMedlineGoogle Scholar
Rollnick S, Miller WR, Butler CC. Motivational Interviewing in Health Care: Helping Patients Change Behavior.New York, NY: Guilford Press; 2008.Google Scholar
Naar-King S. Motivational interviewing in adolescent treatment.Can J Psychiatry. 2011; 56:651–657.CrossrefMedlineGoogle Scholar
Resnicow K, Davis R, Rollnick S. Motivational interviewing for pediatric obesity: conceptual issues and evidence review.J Am Diet Assoc. 2006; 106:2024–2033.CrossrefMedlineGoogle Scholar
Woolford SJ, Clark SJ, Strecher VJ, Resnicow K. Tailored mobile phone text messages as an adjunct to obesity treatment for adolescents.J Telemed Telecare. 2010; 16:458–461.CrossrefMedlineGoogle Scholar