Exploiting social networks to mitigate the obesity epidemic

Empowering Families and Providers With a Lifestyle Medicine Approach to Pediatric Obesity

Pediatric overweight and obesity is a complex chronic medical condition with a multitude of contributing factors. Rates are now nearly double what they were before the COVID-19 pandemic and if the current trajectory holds it is anticipated that by 2050 one in every two US children will experience obesity before the age of thirty-five. Pediatric obesity guidelines emphasize referral to intensive health behavior and lifestyle therapy programs, but these are difficult to access. Front line providers caring for children can use a lifestyle medicine approach within the medical home to make lifestyle changes easier. Lifestyle Medicine can promote a family-oriented, weight-neutral approach by (1) Educating and equipping providers to assess readiness to change and providing high-quality motivational interviewing and lifestyle counseling, (2) Equipping patients and their families with tools involving the six lifestyle interventions to optimize health starting an early age, and (3) Offering a longitudinal uniform office approach to effectively prevent, manage and often reverse obesity and related comorbidities through healthy habit change.

Social Induction via a Social Behavioral Intervention on Changes in Metabolic Risk Factors: A Randomized Controlled Trial in Rural Appalachia, United States

OBJECTIVE

To conduct a randomized controlled trial examining the effects of a social network intervention on health.

PARTICIPANTS AND METHODS

The Microclinic Social Network Program randomized controlled trial (implemented from June 1, 2011, through December 31, 2014) delivered weekly social-health classroom interventions for 9 to 10 months vs standard of care. Longitudinal multilevel analyses examined end-of-trial and 6-month post-intervention outcomes. Social network effects were estimated via a novel social induction ratio.

RESULTS

We randomized 494 participants, comprising 27 classroom clusters from five neighborhood cohorts. Compared with controls, the intervention showed decreased body weight -6.32 pounds (95% CI, -8.65 to -3.98; overall P<.001), waist circumference -1.21 inches (95% CI, -1.84 to -0.58; overall P<.001), hemoglobin A1c % change -1.60 (95% CI, -1.88 to -1.33; overall P<.001), mean arterial blood pressure -1.83 mm Hg (95% CI, -3.79 to 0.32; overall P<.01), borderline-increased high-density lipoprotein cholesterol 1.09 (95% CI, 0.01-2.17; P=.05; overall P=.01). At 6 months post-intervention, net improvements were: weight change 97% sustained (P<.001), waist circumference change 92% sustained (P<.001), hemoglobin A1c change 82.5% sustained (P<.001), high-density lipoprotein change 79% sustained (overall P=.01), and mean arterial blood pressure change greater than 100% sustained improvement of -4.21 mm Hg (P<.001). Mediation analysis found that diet and exercise did not substantially explain improvements. In the intent-to-treat analysis of social causal induction, the weight-change social induction ratio (SIR) was 1.80 for social-network weight change-meaning that social networks explained the greater weight loss in the intervention than controls. Furthermore, we observed an even stronger weight-loss SIR of 2.83 at 6 months post-intervention.

CONCLUSION

Results show intervention effectiveness for improving health in resource-limited communities, with SIR demonstrating that social-network effects helped induce such improvements.

TRIAL REGISTRATION

Clinicaltrials.gov Identifier NCT01651065.

Obesity contagion among classmates: Children's relation with each other regarding weight status, physical activity, and dietary intake

A series of influential articles suggests that obesity may spread between couples, siblings, and close friends via an obesity contagion phenomenon. Classmates, as important structural equivalents in one's social network, may experience obesity contagion. However, this has rarely been examined. Anthropometric measurements, questionnaire surveys, and geographic information were collected from 3670 children from 26 schools in Northeast China. We found that classmates were positively related in terms of body mass index (BMI), body fat, physical activity, and intake of vegetables, fruits, fast food, snacks, and sugar-sweetened beverages. One standard deviation (SD) increase in classmates' mean BMI and percentage body fat was associated with 0.19 SD higher individual BMI (95% confidence interval [CI]: 0.00, 0.39) and 0.31 SD higher percentage body fat (95% CI: 0.13, 0.48). Coefficients ranged from 0.48 to 0.76 in models for physical activity, and the dietary intake of vegetables, fruit, fast food, snacks, and sugar-sweetened beverages. Children's BMI and body fat were more strongly associated with the maximum and minimum body fat levels of their same-sex classmates than with those of their general classmates. Their dietary intake and physical activity were more strongly associated with the mean/median levels of their general classmates than with those of their same-sex classmates. This study suggests that children's BMI, body fat, physical activity, and dietary intake may be related to those of their classmates. Modeling healthy behaviors in the classroom may help children develop habits that support achieving and maintaining a healthy weight. Future interventions should consider the inclusion of classmates as a social network strategy for obesity prevention.

Healthy immigrant community study protocol: A randomized controlled trial of a social network intervention for cardiovascular risk reduction among Hispanic and Somali adults

BACKGROUND

Immigrants to the United States face structural barriers that contribute to rising cardiovascular risk factors and obesity after immigration. This manuscript describes the development of the Healthy Immigrant Community protocol and baseline measures for a stepped wedge cluster randomized trial to test the effectiveness of a social network intervention for cardiovascular risk reduction among two immigrant populations.

METHODS

We developed a social network-informed, community-based, participatory research-derived health promotion intervention with Hispanic and Somali immigrant communities in Minnesota consisting of mentoring, educational and motivational sessions, group activities, and a community toolkit for healthy weight loss delivered by culturally concordant health promoters (HPs) to their social networks. Using a stepped wedge cluster randomized design, social network-based groups were randomly assigned to receive the intervention either immediately or after a delay of one year. Outcomes, measured at baseline, 6 months, 12 months, and 24 months, were derived from the American Heart Association's "Life's Simple 7": BMI and waist circumference, blood pressure, fasting blood glucose, total cholesterol, physical activity level, and dietary quality.

RESULTS

A total of 51 HPs were enrolled and randomized (29 Hispanic; 22 Somali). There were 475 participants enrolled in the study, representing a mean social network group size of 8 (range, 5-12). The mean BMI of the sample (32.2) was in the "obese" range.

CONCLUSION

Processes and products from this Healthy Immigrant Community protocol are relevant to other communities seeking to reduce cardiovascular risk factors and negative health behaviors among immigrant populations by leveraging the influence of their social networks.

Awareness about developmental coordination disorder

The present paper is designed to promote awareness of DCD outside the academic world. With a prevalence of 5-6% it is one of the most common disorders of child development. It is therefore surprising that so little is known about it among professionals in child healthcare and education. Parents have expressed frustration about this lack of awareness, including the general public. The general aim of this paper was to describe those critical aspects of DCD that will promote awareness.

Relationships between personality, emotional well-being, self-efficacy and weight management among adults with type 2 diabetes: Results from a cross-sectional survey

The objective of this study was to examine the associations between personality, general and diabetes-specific well-being and self-efficacy, and weight management indicators, among adults with type 2 diabetes. In addition, to examine whether personality provides incremental explanation of variance in weight management indicators. Australian adults with type 2 diabetes (N = 270; 56% women; age: 61±12 years) were recruited via the national diabetes registry. An online survey included measures of: personality (HEXACO-PI-R), weight management indicators (physical activity, healthy diet, body mass index [BMI]), general well-being (WHO-5), general self-efficacy (GSE), diabetes distress (DDS) and diabetes self-efficacy (DMSES). Analyses included bivariate correlations and linear regression, adjusted for demographic, clinical, and psychological variables. All six personality domains showed significant correlation with at least one weight management indicator: physical activity with extraversion (r = .28), conscientiousness (r = .18) and openness (r = .19); healthy diet with honesty-humility (r = .19), extraversion (r = .24), and agreeableness (r = .14); and BMI with emotionality (r = .20) and extraversion (r = -.20). The strongest associations with general and diabetes-specific well-being and self-efficacy were apparent for extraversion, emotionality and conscientiousness (range: r = -.47-.66). Beyond covariates, personality domains explained additional variance for physical activity (Adjusted R2 = .31, R2 difference = .03, p = .03; openness: β = .16, p = .02, emotionality: β = .15, p = .04) and healthy diet (Adjusted R2 = .19, R2 difference = .03, p = .02; honesty-humility: β = .20, p = .002, extraversion: β = .19, p = .04) but not BMI. This study shows that personality is associated with weight management indicators and psychological factors among adults with type 2 diabetes. Further research is needed, including objective measurement of weight management indictors, to examine how personality influences the experience of type 2 diabetes.

Social network-structural position and obesity: Evidence from a national study

This study expands on research on the social-structural bases of obesity by examining the role played by individuals' positions within their egocentric social networks in shaping body mass index. We argue that individuals' tendency to be a bridge between otherwise unconnected people can affect body mass index. Furthermore, health-specific resources flowing through their networks might interact with this network-structural position to shape this association. Using multivariate analyses of recent nationally representative data on older Americans, we find that occupying a bridging position within a network is negatively related to the likelihood of being obese. Moreover, people who have this bridging potential tend to benefit more from health-related knowledge in their networks than those who do not have it. Our findings underscore the importance of considering social network position and the functional specificity of ties in understanding the structural bases of health problems like obesity. We close by discussing implications of these findings for future work on obesity including potential insights into important health disparities.

Modeling obesity in complex food systems: Systematic review

Obesity-related data derived from multiple complex systems spanning media, social, economic, food activity, health records, and infrastructure (sensors, smartphones, etc.) can assist us in understanding the relationship between obesity drivers for more efficient prevention and treatment. Reviewed literature shows a growing adaptation of the machine-learning model in recent years dealing with mechanisms and interventions in social influence, nutritional diet, eating behavior, physical activity, built environment, obesity prevalence prediction, distribution, and healthcare cost-related outcomes of obesity. Most models are designed to reflect through time and space at the individual level in a population, which indicates the need for a macro-level generalized population model. The model should consider all interconnected multi-system drivers to address obesity prevalence and intervention. This paper reviews existing computational models and datasets used to compute obesity outcomes to design a conceptual framework for establishing a macro-level generalized obesity model.

Do outcomes from a behavioral weight loss intervention differ in Alabama versus Colorado?

Background

There are well-established regional differences in obesity prevalence in the United States but relatively little is known about why or whether success in weight loss differs regionally.

Objective

The objective of this study was to determine whether changes in body weight, engagement in physical activity (PA), and psychosocial factors differed in Alabama (AL) versus Colorado (CO) in response to a 16-week behavioral weight loss program.

Design

This is an ancillary study to a weight loss intervention being conducted simultaneously in AL and CO with identical intervention content and delivery in 70 participants (n = 31 AL and n = 39 CO). Body weight, objective (accelerometry) PA, and responses to psychosocial questionnaires (reward-based eating, stress, social support) were collected at baseline and at Week 16.

Results

There were no differences in percent weight loss between states (AL: 10.98%; CO: 11.675%, p = 0.70), and weights at Week 16 were not different for participants in AL and CO (AL: 101.54 ± 4.39 kg, CO: 100.42 ± 3.67 kg, p = 0.84). Accelerometry-derived step count, stepping time, and activity score were all greater at Week 16 for participants in AL compared to participants in CO. Hedonic eating scores were more favorable for participants in AL at baseline (AL: 24.08 ± 2.42; CO: 34.99 ± 2.12, p = 0.0023) and at Week 16 (AL: 18.62 ± 2.70; CO: 29.11 ± 2.19, p = 0.0023). Finally, participants in AL presented more favorable social support scores at Week 16 compared to participants in CO.

Conclusions

Weight loss did not differ between states, suggesting that factors contributing to higher obesity rates in some regions of the United States may not be barriers to weight loss. Further, participants in AL experienced greater improvements in some factors associated with weight maintenance, indicating the need to study regional differences in weight loss maintenance. National Clinical Trial 03832933.

The influence of social relationships and activities on the health of adults with obesity: A qualitative study

BACKGROUND

Obesity in adults is a leading health challenge that causes millions of deaths worldwide and represents a risk factor for developing long-term conditions. Social relationships are one of the multiple drivers shaping obesity and obesity-related practices. However, there is still little evidence as to the processes by which relationships influence the adoption of positive and negative obesity health-related practices-eating, physical activity and alcohol intake. This study aims first to identify the types of relationships relevant to the adoption of practices in adults with obesity and, second, to explore the type of activities these relationships engage with or promote to produce those practices and their potential health consequences.

METHODS

Nineteen adults who have or had a history of obesity living in the United Kingdom were interviewed between May 2020 and March 2021. Experiences were explored through semi-structured interviews and network mapping via videoconferencing. Data were analysed using a hermeneutic phenomenology informed thematic analysis.

RESULTS

Three main themes were identified: (1) everyday familial routines matter, (2) chasing healthier lifestyles: comparing, modelling and connecting emotionally with friends and (3) healthcare professionals as negative influencers.

DISCUSSION AND CONCLUSIONS

Findings show how different types of relationships might shape the risk of developing and losing weight. They uncover the power of informal networks (family and friends) and highlight the potentially negative impact of formal ones (healthcare professionals). Our exploration could add to arguments about the need for stakeholders confronting obesity to be aware of the relevance of everyday social relationships in health and well-being strategies for tackling the issue, in creating collective and individual person-centred long-term sustainable actions.

PATIENT AND PUBLIC CONTRIBUTION

Feedback on the tone/content of the interview questions was provided by the two first participants. The results were checked and received feedback from one of the interviewees.

A review of mathematical modeling of addiction regarding both (neuro-) psychological processes and the social contagion perspectives

Addiction is a complex biopsychosocial phenomenon, impacted by biological predispositions, psychological processes, and the social environment. Using mathematical and computational models that allow for surrogative reasoning may be a promising avenue for gaining a deeper understanding of this complex behavior. This paper reviews and classifies a selection of formal models of addiction focusing on the intra- and inter-individual dynamics, i.e., (neuro) psychological models and social models. We find that these modeling approaches to addiction are too disjoint and argue that in order to unravel the complexities of biopsychosocial processes of addiction, models should integrate intra- and inter-individual factors.

Pilot Social Network Weight Loss Intervention With Two Immigrant Populations During the COVID-19 Pandemic

Purpose

To examine the feasibility and acceptability of a social network weight loss intervention delivered by lay health promoters (HPs) to immigrant populations.

Design

Single-arm, non-randomized, pilot study of a social network weight loss intervention developed by a community-based participatory research partnership and delivered by HPs.

Setting

Community-based setting in Southeastern Minnesota, United States.

Sample

Somali and Hispanic immigrants to the United States: 4 social networks of adults (2 Hispanic and 2 Somali) with 39 network participants.

Intervention

Twelve-week behavioral weight loss intervention delivered by HPs (4 weeks in-person and then 8 weeks virtual).

Measures

Feasibility was assessed by recruitment and retention rates. Acceptability was assessed by surveys and focus groups with HPs and participants. Behavioral measures included servings of fruits and vegetables, drinking soda, and physical activity. Physiologic measures included weight, blood pressure, glucose, cholesterol, and triglycerides.

Analysis

Paired t-tests of pre- to post-intervention changes at the end of 12 weeks of treatment.

Results

Recruitment was feasible and post-intervention was 100%. Participants highly rated the intervention on satisfaction, motivation, and confidence to eat a healthy diet, be physically active, and lose weight. Participants were motivated by group social support and cohesion of their social networks. On average, participants lost weight (91.6 ± 15.9 to 89.7 ± 16.6 kg, P < .0001), lowered their systolic blood pressure (133.9±16.9 to 127.2 ± 15.8 mm Hg; P < .001), lowered their diastolic blood pressure (81 ± 9.5 to 75.8 ± 9.6 mm Hg; P < .0001), had more servings of vegetables per day (1.9 ± 1.2 to 2.6 ± 1.4; P < .001), and increased their physical activity (2690 ± 3231 to 6595 ± 7322 MET-minutes per week; P = .02).

Conclusion

This pilot study of 2 immigrant communities who participated in a peer-led weight loss social network intervention delivered during the COVID-19 pandemic demonstrated high feasibility and acceptability. Participants lost weight, improved their health status, and improved their health behaviors.

Estimating the state of epidemics spreading with graph neural networks

When an epidemic spreads into a population, it is often impractical or impossible to continuously monitor all subjects involved. As an alternative, we propose using algorithmic solutions that can infer the state of the whole population from a limited number of measures. We analyze the capability of deep neural networks to solve this challenging task. We base our proposed architecture on Graph Convolutional Neural Networks. As such, it can reason on the effect of the underlying social network structure, which is recognized as the main component in spreading an epidemic. The proposed architecture can reconstruct the entire state with accuracy above 70%, as proven by two scenarios modeled on the CoVid-19 pandemic. The first is a generic homogeneous population, and the second is a toy model of the Boston metropolitan area. Note that no retraining of the architecture is necessary when changing the model.

Personal Social Networks and Adiposity in Adolescents: A Feasibility Study

Background and Objective: Weight-related behaviors are determined by multiple individual and contextual factors, with recent evidence implicating personal social networks (PSNs). Greater understanding of these relationships could help inform healthy weight promoting interventions. We conducted a feasibility study among youth at risk of obesity to document process outcomes, to discern relationships between PSN features and weight-related behaviors, and to generate hypotheses with respect to perceived social support (SS) and sex. Methods: Participants (egos) nominated up to 10 people (alters) with whom they discussed important matters. Egos reported their own and each alter's age, sex, body shape, lifestyle behaviors, relation, frequency of exercising with each alter, and of being encouraged by each alter to exercise. We examined relationships between PSN features and weight-related outcomes and explored the role of SS, using both correlational and linear regression analyses. Results: There were 45 participants (mean age 16.4 years) and body mass index z-score (zBMI) ranged from -1.2 to 3.9. There were few missing responses to PSN items; broad variation across most items, including SS scores, was reported. Correlations pointed to plausible relationships implicating PSN features and lifestyle behaviors. In exploratory analyses, network-based SS was positively associated with adiposity in girls and negatively associated in boys, while lifestyle role modelling was not associated with adiposity. Conclusions: Our findings support the feasibility of measuring the PSN in youth and the potential for using social network analysis to investigate social and behavioral mechanisms associated with obesity.

Social Support Networks and Foreign-Birth Status Associated With Obesity, Hypertension and Diabetes Prevalence Among 21-30 and 50-70 Year Old Adults Living in the San Francisco Bay Area

PURPOSE

To examine whether social network characteristics of US-and foreign-born individuals are related to hypertension, diabetes and obesity prevalence.

DESIGN

Cross-sectional.

SETTING

Six San Francisco Bay Area counties.

PARTICIPANTS

N = 1153 cohorts of young and older adults (21-30 and 50-70 years).

MEASURES

Network structure and support measures were calculated using name elicitation and interpreter questions common in egocentric surveys. Hypertension and diabetes were self-reported, and overweight/obesity was determined using body mass index calculations. Foreign-birth status was based on country of birth.

ANALYSIS

Adjusted and unadjusted logistic regression models were used to examine associations between network characteristics and hypertension, diabetes and overweight/obesity. These relationships were tested for moderation by foreign-birth status, age and gender.

RESULTS

Higher percentages of family members (AOR = 4.16, CI: 1.61-10.76) and same-sex individuals (AOR = 3.41, CI: 1.25-9.35) in the composition of respondents' networks were associated with overweight/obesity. Higher composition of family members (AOR = 3.54, CI: 1.09-11.48) was associated with hypertension. Respondents whose networks composed of higher numbers of advice individuals (AOR = 0.88, CI: 0.77-0.99), female respondents (AOR = 0.52, CI: 0.35-0.77) and foreign-born respondents (AOR = 0.54, CI: 0.32-0.92) were less likely to report overweight/obesity. Diabetes was associated with higher composition of individuals living within 5-minutes to respondents (AOR = 5.13, CI: 1.04-25.21).

CONCLUSION

Family and network support members such as advice individuals could be potential targets for chronic disease prevention, particularly among older adults and immigrants.

[Entorno social y obesidad infantil: implicaciones para la investigación y la práctica en Estados Unidos y en los países latinoamericanos]

The environments of children influence their risk for childhood obesity through, among other factors, a child's weight-related behaviors (i.e., diet and physical activity). In this article, we present evidence on social environmental factors associated with a child's diet and physical activity, and more generally, the prevention and control of childhood obesity among Hispanic/Latinx children in the United States and children from countries in Latin America. Using a socio-ecologic lens, we present evidence from cross-sectional and longitudinal studies conducted in the United States involving Hispanic/Latinx children, and evidence from studies involving children in Latin America. Studies examining parenting factors in the home environment (e.g., parenting strategies) are especially emphasized, with more limited evidence on social environmental factors in other lived contexts (e.g., school). The influence of acculturation on social relationships cuts across levels of the socio-ecological framework. Intervention research identified strategies and research gaps for intervening on social factors to promote healthy behaviors and reduce risk for childhood obesity. Community health workers and others forms of peer support were identified as relevant approaches at multiple levels of the socio-ecological framework. This article concludes with directions for future research to further understand the environment using newer information and communication technologies.

Consider the context: An analysis of personal social networks of caregivers of children participating in a paediatric weight management program

Social networks influence the health and well-being of children and families. This study aimed to identify and understand the social networks of caregivers of children participating in the KidFit Health and Wellness Clinic, a paediatric weight management program. An egocentric social network analysis was used. Caregivers with children enrolled in KidFit participated in semi-structured interviews by completing a personal network map and discussing the individuals in their social networks and their influence on them and their family. Twenty-two caregivers (90.9% mothers) completed the interview. Four structural patterns were identified within the networks: existence of a core, star-shaped network, well-connected network and existence of multiple clusters. Healthcare providers and family had the most influence within the caregivers' networks. With the exception of healthcare providers, individuals who communicated less frequently with caregivers tended to have less influence on caregivers. Internet resources, activity-related resources and social media were the top three services, resources or supports that caregivers reported accessing. It is important that practitioners working with children and families within paediatric settings recognize the unique sociocultural context of each family. Reconceptualising a care model that includes community and incorporates services, supports and resources beyond the clinic could enhance treatment.

Health policy and public health implications of obesity in China

China has experienced many drastic social and economic changes and shifts in people's lifestyles since the 1990s, in parallel with the fast rising prevalence of obesity. About half of adults and a fifth of children have overweight or obesity according to the Chinese criteria, making China the country with the highest number of people with overweight or obesity in the world. Assuming that observed time trends would continue in the future, we projected the prevalence of and the number of people affected by overweight and obesity by 2030, and the associated medical costs. The rising incidence of obesity and number of people affected, as well as the related health and economic consequences, place a huge burden on China's health-care system. China has made many efforts to tackle obesity, including the implementation of relevant national policies and programmes. However, these measures are inadequate for controlling the obesity epidemic. In the past decade, China has attached great importance to public health, and the Healthy China 2030 national strategy initiated in 2016 provides a historical opportunity to establish comprehensive national strategies for tackling obesity. China is well positioned to explore an effective model to overcome the obesity epidemic; however, strong commitment and leadership from central and local governments are needed, as well as active participation of all related society sectors and individual citizens. TRANSLATION: For the Chinese translation of the paper see Supplementary Materials section.

The social environment and childhood obesity: Implications for research and practice in the United States and countries in Latin America

The environments of children influence their risk for childhood obesity through, among other factors, a child's weight-related behaviors (i.e., diet and physical activity). In this article, we present evidence on social environmental factors associated with a child's diet and physical activity, and more generally, the prevention and control of childhood obesity among Hispanic/Latinx children in the United States and children from countries in Latin America. Using a socio-ecologic lens, we present evidence from cross-sectional and longitudinal studies conducted in the United States involving Hispanic/Latinx children, and evidence from studies involving children in Latin America. Studies examining parenting factors in the home environment (e.g., parenting strategies) are especially emphasized, with more limited evidence on social environmental factors in other lived contexts (e.g., school). The influence of acculturation on social relationships cuts across levels of the socio-ecological framework. Intervention research identified strategies and research gaps for intervening on social factors to promote healthy behaviors and reduce risk for childhood obesity. Community health workers and others forms of peer support were identified as relevant approaches at multiple levels of the socio-ecological framework. This article concludes with directions for future research to further understand the environment using newer information and communication technologies.

A User-Centered Chatbot (Wakamola) to Collect Linked Data in Population Networks to Support Studies of Overweight and Obesity Causes: Design and Pilot Study

BACKGROUND

Obesity and overweight are a serious health problem worldwide with multiple and connected causes. Simultaneously, chatbots are becoming increasingly popular as a way to interact with users in mobile health apps.

OBJECTIVE

This study reports the user-centered design and feasibility study of a chatbot to collect linked data to support the study of individual and social overweight and obesity causes in populations.

METHODS

We first studied the users' needs and gathered users' graphical preferences through an open survey on 52 wireframes designed by 150 design students; it also included questions about sociodemographics, diet and activity habits, the need for overweight and obesity apps, and desired functionality. We also interviewed an expert panel. We then designed and developed a chatbot. Finally, we conducted a pilot study to test feasibility.

RESULTS

We collected 452 answers to the survey and interviewed 4 specialists. Based on this research, we developed a Telegram chatbot named Wakamola structured in six sections: personal, diet, physical activity, social network, user's status score, and project information. We defined a user's status score as a normalized sum (0-100) of scores about diet (frequency of eating 50 foods), physical activity, BMI, and social network. We performed a pilot to evaluate the chatbot implementation among 85 healthy volunteers. Of 74 participants who completed all sections, we found 8 underweight people (11%), 5 overweight people (7%), and no obesity cases. The mean BMI was 21.4 kg/m2 (normal weight). The most consumed foods were olive oil, milk and derivatives, cereals, vegetables, and fruits. People walked 10 minutes on 5.8 days per week, slept 7.02 hours per day, and were sitting 30.57 hours per week. Moreover, we were able to create a social network with 74 users, 178 relations, and 12 communities.

CONCLUSIONS

The Telegram chatbot Wakamola is a feasible tool to collect data from a population about sociodemographics, diet patterns, physical activity, BMI, and specific diseases. Besides, the chatbot allows the connection of users in a social network to study overweight and obesity causes from both individual and social perspectives.

Health professionals' perceptions of weight loss programmes and recommendations for future implementation: a qualitative study

OBJECTIVE

Obesity is an increasing public health challenge and most weight loss programmes are still inadequate to support sustainable weight loss. One reason for the continued lack of success might be the dominant biomedical, individualised approach to weight loss. Holistic approaches that focus on overall health and well-being in addition to weight loss are increasingly recommended. In Denmark, health professionals in the municipalities are responsible for developing and conducting weight loss programmes. The objective of this study was to explore what health professional's perceived as an ideal, holistic weight loss programme that could be feasibly implemented in the municipalities.

DESIGN

A phenomenological-hermeneutical qualitative study was performed using semistructured interviews.

SETTING

Thirty-two Danish municipalities were weight loss programmes are developed and conducted.

PARTICIPANTS

Thirty-five health professionals with experience conducting weight loss programmes.

RESULTS

Three themes emerged from the analysis: Support from the social network are important both during and after a weight loss, Changing the self-belief by positive discussions and doing activities, Maintaining changes through daily life.

CONCLUSION

Future municipal weight loss programmes should emphasise overall health and well-being instead of weight loss and adopt a holistic approach including a focus on social relationships, meaningful activities and successes as part of a balanced daily life.

Social network characteristics are correlated with dietary patterns among middle aged and older South Asians living in the United States (U.S.)

Background

Social and cultural norms, operating through social networks, may influence an individual’s dietary choices. We examined correlations between social network characteristics and dietary patterns among South Asians in the United States (U.S.)

Methods

Data from the Mediators of Atherosclerosis in South Asians Living in America (MASALA) Social Network study were analyzed among 756 participants (mean age = 59 y standard deviation [SD] = 9 y; 44% women). A culturally adapted, validated food frequency questionnaire was used for dietary assessment. A posteriori dietary patterns using principal component analysis were named 1) animal protein, 2) fried snacks, sweets and high-fat dairy, and 3) fruits, vegetables, nuts and legumes. Social network characteristics were assessed using a standard egocentric approach, where participants (egos) self-reported data on perceived dietary habits of their network members. Partial correlations between social network characteristics and egos’ dietary patterns were examined.

Results

The mean social network size of egos was 4.2 (SD = 1.1), with high proportion of network members being family (72%), South Asian ethnicity (89%), and half having daily contact. Animal protein pattern scores were negatively correlated with fruits and cooked vegetables consumption of network. Fried snacks, sweets and high-fat dairy pattern scores were positively correlated with sugar-sweetened beverages, South Asian sweets, fried/fast foods and ghee (clarified butter) consumption of network. Fruits, vegetables, nuts and legumes pattern scores were positively correlated with vegetables, fruits, and brown rice/quinoa consumption of network.

Conclusions

Network member characteristics and their perceived dietary behaviors were correlated with dietary patterns of egos. Dietary intervention studies among South Asians should consider social network characteristics as candidate components for dietary intervention.

Social norms and obesity prevalence: From cohort to system dynamics models

Group-level obesity can be seen as an emergent property of a complex system, consisting of feedback loops between individual body weight perception, individual weight-related behaviour and group-level social norms (a product of group-level 'normal' body mass index (BMI) and sociocultural 'ideal' BMI). As overweight becomes normal, the norm might be counteracting health awareness in shaping individual weight-related behaviour. System dynamics modelling facilitates understanding and simulating this system's emergent behaviour. We constructed six system dynamics models (SDMs) based on an expert-informed causal loop diagram and data from six sociocultural groups (Dutch, Moroccan and South-Asian Surinamese men and women). The SDMs served to explore the effect of three scenarios on group-level BMI: 'what if' weight-related behaviour were driven by (1) health awareness, (2) norms or (3) a combination of the two. Median BMI decreased approximately 50% and 30% less in scenarios 2 and 3, respectively, than in 1. In men, the drop in BMI was approximately two times larger in scenario 1 versus 3, whereas in women, the drop was approximately equal in these scenarios. This study indicates that the overweight norm in men holds group-level BMI close to overweight despite health awareness. Since norms are counteracting health awareness less strongly in women, other drivers of obesity must be more relevant.

Evaluating social network-based weight loss interventions in Chinese population: An agent-based simulation

OBJECTIVE

The aim of this study is to assess network-based weight loss interventions in the Chinese setting using agent-based simulation.

METHODS

An agent-based model incorporating social, environmental and personal influence is developed to simulate the obesity epidemic through an interconnected social network among a population of 2197 individuals from the nationally representative survey. Model parameters are collected from literature and existing database. To ensure the robustness of our findings, the model is validated against empirical observations and sensitivity analyses are performed on calibrated parameters.

RESULTS

When compared with the baseline model, significant weight difference is detected using paired samples t tests for network-based intervention strategies (p<0.05) but no difference is observed for the two conventional intervention strategies including choosing random or high-risk individuals (p>0.05). Targeting the most connected individuals minimizes the average population weight, average BMI, and generates a reduction of 2.70% and 1.38% in overweight and obesity prevalence.

CONCLUSIONS

The simulations shows that targeting individuals on the basis of their social network attributes outperforms conventional targeting strategies. Future work needs to focus on how to further leverage social networks to curb obesity prevalence and enhance interventions for other chronic conditions using agent-based simulation.

Identifying Social Network Conditions that Facilitate Sedentary Behavior Change: The Benefit of Being a "Bridge" in a Group-based Intervention

Using data from one of the first trials to try to leverage social networks as a mechanism for obesity intervention, we examined which social network conditions amplified behavior change. Data were collected as part of a community-based healthy lifestyle intervention in Nashville, USA, between June 2014 and July 2017. Adults randomized to the intervention arm were assigned to a small group of 10 participants that met in person for 12 weekly sessions. Intervention small group social networks were measured three times; sedentary behavior was measured by accelerometry at baseline and 12 months. Multivariate hidden Markov models classified people into distinct social network trajectories over time, based on the structure of the emergent network and where the individual was embedded. A multilevel regression analysis assessed the relationship between network trajectory and sedentary behavior (N = 261). Being a person that connected clusters of intervention participants at any point during the intervention predicted an average reduction of 31.3 min/day of sedentary behavior at 12 months, versus being isolated [95% CI: (−61.4, −1.07), p = 0.04]. Certain social network conditions may make it easier to reduce adult sedentary behavior in group-based interventions. While further research will be necessary to establish causality, the implications for intervention design are discussed.

Promoting Participation in DCD: Physical Activity Levels and the Social Network

Purpose of Review

Physical inactivity is a worldwide problem, also affecting children with motor problems, such as developmental coordination disorder. We try to understand what motivates children to start, continue, and stop having an active lifestyle and explore the role that the social network of the child can have to stimulate an active lifestyle.

Recent Findings

Social network theory is useful for understanding individual and group behavior related to physical activity. Social networks, ranging from peers and parents to teachers and medical professionals were shown to play an important role in bringing about sustainable behavioral change. Up to now, little systematic research has been done into how social networks can be used to keep children with developmental coordination disorder (DCD) physically active and motivated.

Summary

Future studies should more systematically examine and target the social network of the child with DCD. This social network can then be used to develop interventions for a sustained physical active lifestyle leading to increased participation in the society.

Association of social network factors with weight status and weight loss intentions among hispanic adults

Hispanic adults have the highest obesity prevalence in the United States, but little is known about weight-related social network influences. A community-based sample of 610 Hispanic participants completed height/weight and a survey. The proportion of overweight or obese (OW/OB) network members was higher for OW/OB respondents compared to normal weight respondents. Participants with high weight loss intentions reported more positive social norms for weight control, social support, and social cohesion. If most or all of OW/OB participant's social contacts were trying to lose weight, the odds that they were likely to try to lose weight was four times higher than other participants. The relationship between weight loss intentions and number of social contacts trying to lose weight was strongly mediated by social norms for weight control and social support. These results suggest that social contacts and functional network characteristics may impact weight status and weight control intentions among Hispanic adults.

Social networks and obesity among Somali immigrants and refugees

BACKGROUND

Somali immigrants and refugees to the United States are at high risk for obesity and related cardiovascular risk. Social network factors influence health behaviors and are important contributors to the obesity epidemic. The objective of this study was to describe social networks and obesity-related characteristics among adult Somali immigrants in a Minnesota city in order to inform a community-based, participatory, research-derived, social network intervention to decrease obesity rates.

METHODS

Survey data (demographics, general health measures, and sociobehavioral and network measures) and height and weight measures (for calculating body mass index) were collected from adult Somali immigrants by bilingual study team members at community locations. Descriptive statistics were used to report the survey and biometric data. Logistic regression models were used to describe the basic associations of participants and network factors. Network data were analyzed to identify nodes and ties, to visualize the network, and to identify potential interventionists for a future social network intervention.

RESULTS

Of the 646 participants, 50% were overweight or affected by obesity. The network had 1703 nodes with 3583 ties between nodes, and modularity was high (0.75). Compared with respondents of normal weight, participants who were overweight or affected by obesity had more network members who were also overweight or obese (odds ratio [OR], 2.90; 95% CI, 1.11-7.56; P = .03); this was most notable for men (OR, 4.58; 95% CI, 1.22-17.22; P = .02) and suggestive for those 50 years or older (OR, 24.23; 95% CI, 1.55-377.83; P = .03). Weight loss intention among participants who were overweight or affected by obesity was associated with number of family members and friends trying to lose weight, enabling functional network factors (social norms for weight loss, social support for healthy eating, and social cohesion), and less favorable obesogenic social norms.

CONCLUSIONS

In this community sample of Somali immigrants, distinct social networks are clustered by weight status, and social contacts and functional network characteristics are related to individuals' weight loss intentions. These factors should be considered in weight loss interventions and programs. A social network intervention targeting weight loss, within a community-based participatory research framework, is feasible in this vulnerable population.

Social Networks and Sugar-Sweetened Beverage Consumption in a Pediatric Urban Academic Practice

Increased sugar-sweetened beverage (SSB) consumption is linked to childhood obesity. The risk of increased SSB consumption is multifactorial. Limited studies have examined children's SSB consumption and social networks. In order to examine the association between SSB consumption and SSB preferences of a child's social network, a cross-sectional survey was administered to patients aged 8-17 years from June to September 2016. In a questionnaire, subjects completed a beverage consumption recall, identified people important to them along with each person's favorite beverage, and answered questions about habits, environment, and attitudes. Subjects with higher SSB consumption (>16 fl oz) were compared to subjects with lower SSB consumption (≤16 fl oz). 202 surveyed: 55% female, 53% Hispanic, 45% Black, 28% overweight or obese. Children drank an average of 3 cups/day of SSBs, range of 0-15 cups/day. Social networks included caregiver, relative, and friend. Subjects with higher SSB consumption (n = 96) were compared to those with lower SSB consumption (n = 106). We found children with higher SSB consumption had higher odds of reporting a higher number of people in their immediate social networks who prefer SSB, adjusted for habits, environment, and attitudes (aOR 1.41; 95% CI: 1.02-1.99; p < 0.05). Children are more likely to have higher SSB consumption if they list people in their immediate social network who prefer SSB as their favorite drink. Further research is required to explore the influence of social networks on health behaviors of children.

End-user perspectives to inform policy and program decisions: a qualitative and quantitative content analysis of lifestyle treatment recommendations by adolescents with obesity

Background

Lifestyle modifications represent the first line of treatment in obesity management; however, many adolescents with obesity do not meet lifestyle recommendations. Given that adolescents are rarely consulted during health policy development and in the design of lifestyle interventions, their first-hand experiences, preferences, and priorities may not be represented. Accordingly, our purpose was to explore adolescents’ lifestyle treatment recommendations to inform policy and program decisions.

Methods

Conducted from July 2017 to January 2018, this study adhered to a qualitative, crosslanguage, patient-oriented design. We recruited 19 13–17-year-old adolescents (body mass index [BMI] ≥85th percentile) seeking multidisciplinary treatment for obesity in geographically and culturally diverse regions of Canada. Adolescents participated in one-on-one, in-person, semi-structured interviews in English or French. Interviews were audio-recorded, transcribed verbatim, managed using NVivo 11, and analyzed using quantitative and qualitative content analysis by two independent researchers.

Results

Adolescents’ recommendations were organized into five categories, each of which denotes health as a collective responsibility: (i) establish parental support within limits, (ii) improve accessibility and availability of ‘healthy foods’, (iii) limit deceptive practices in food marketing, (iv) improve accessibility and availability of varied physical activity opportunities, and (v) delay school start times. Respect for individual autonomy and decision-making capacity were identified as particularly important, however these were confronted with adolescents’ partial knowledge on nutrition and food literacy.

Conclusions

Adolescents’ recommendations highlighted multi-level, multi-component factors that influenced their ability to lead healthy lifestyles. Uptake of these recommendations by policy-makers and program developers may be of added value for lifestyle treatment targeting adolescents with obesity.

"I Did Not Believe You Could Get Better"-Reversal of Diabetes Risk Through Dietary Changes in Older Persons with Prediabetes in Region Stockholm

Diabetes risk can be controlled and even reversed by making dietary changes. The aim of this study was to improve the understanding of how older persons with a high risk of developing Type 2 diabetes manage and relate to information about diabetes risk over a ten-year period. Fifteen qualitative interviews were conducted among participants from the Stockholm Diabetes Prevention Program (SDPP). The participants were asked to recall the health examinations conducted by the SDPP related to their prediabetes and to describe their experiences and potential changes related to diet and physical activity. Data were analyzed using qualitative content analysis. The main theme found was that T2D (type 2 diabetes) risk is not perceived as concrete enough to motivate lifestyle modifications, such as changing dietary patterns, without other external triggers. Diagnosis was recognized as a reason to modify diet, and social interactions were found to be important for managing behavior change. Diagnosis was also a contributing factor to lifestyle modification, while prognosis of risk was not associated with efforts to change habits. The results from this study suggest that the potential of reversing prediabetes needs to be highlighted and more clearly defined for older persons to serve as motivators for lifestyle modification.

The influence of the maternal peer group (partner, friends, mothers' group, family) on mothers' attitudes to obesity-related behaviours of their children

BACKGROUND

Relationships with others can have an impact on the attitudes of new mums to the obesity-related behaviours of their children. The aim of this study was to understand the degree to which other new mums (from their mothers' group), friends, partners, and other family members have an influence on maternal attitudes to child feeding, physical activity and television viewing behaviours in order to more accurately target obesity prevention interventions.

METHODS

In a retrospective cohort study design using data from the InFANT randomized controlled trial, first-time mothers (n = 307) from Melbourne, Australia were asked in 2012-13 how much of an influence their partner, friends, mothers' group and family were on their attitudes to their pre-school aged child's feeding, physical activity and television viewing behaviours. The level of influence was examined using chi-square tests, t-tests, and analysis of variance, stratified by maternal education, age and body weight. We also examined associations between the influence of others on maternal attitudes and actual behaviours including breastfeeding duration, age at introduction of solid food and time their child spent outside.

RESULTS

Mothers rated partners as having the strongest influence on their attitudes toward all obesity-related behaviours. The percentage reporting partners as a major influence were 28.7% (95% CI 23.8,34.0), 33.1% (28.0, 38.6) and 24.2% (19.6, 29.3) for child feeding, physical activity and television viewing, respectively. More highly educated mothers rated social connections as more influential than less educated mothers. The influence of partners on attitudes toward child feeding was associated with longer breastfeeding duration.

CONCLUSIONS

Mothers rated partners as a powerful influence on their attitudes toward the obesity-related behaviours of their pre-school children, suggesting that partners could be an important target of obesity-prevention initiatives. Since less educated mothers reported peers and family as a much weaker influence on their attitudes to obesity-related behaviours than more educated mothers, equity should be taken into consideration when contemplating obesity-prevention interventions that target mothers' groups.

Microsimulation model of child and adolescent overweight: making use of what we already know

BACKGROUND

New Zealand has high rates of child overweight and obesity when compared with other countries. Despite an abundance of research documenting the problem, it is unclear what the most effective policy changes or interventions are, and how policy changes might unfold over time within complex systems.

METHODS

We use estimates derived from meta-analyses to create a dynamic microsimulation model of child overweight (including obesity). Using census records we created a synthetic birth cohort of 10,000 children. Information on parental education, ethnicity and father's socio-economic position at birth were taken from census records. We used the New Zealand Health Survey to estimate population base rates for the prevalence of overweight and obesity. Information on other modifiers (such as maternal smoking, breastfeeding, preterm birth, regular breakfast consumption and so forth) were taken from three birth cohorts: Christchurch Health and Development Study, The Dunedin Multidisciplinary Health and Development Study and the Pacific Islands Families Study. Published intervention studies were used to derive plausible estimates for changes to modifiers.

RESULTS

Reducing the proportion of mothers classified as overweight and obesity (-3.31(95% CI -3.55; -3.07) percentage points), reducing the proportion of children watching two or more hours of TV (-3.78(95% CI -4.01; -3.54)), increasing the proportion of children eating breakfast regularly (-1.71(95% CI -1.96; -1.46)), and reducing the proportion of children born with high birth weights (-1.36(95% CI -1.61; -1.11)), lead to sizable decreases in the estimated prevalence of child overweight (including obesity). Reducing the proportion of mothers giving birth by caesarean (-0.23(95% CI -0.49; -0.23)) and increasing parental education (-0.07(95% CI -0.31; 0.18)) did not impact upon child overweight rates.

CONCLUSIONS

We created a working simulation model of New Zealand children that can be accessed by policy makers and researchers to determine known relationships between predictors and child overweight, as well as potential gains from targeting specific pathways.

Identifying Influence Agents That Promote Physical Activity Through the Simulation of Social Network Interventions: Agent-Based Modeling Study

BACKGROUND

Social network interventions targeted at children and adolescents can have a substantial effect on their health behaviors, including physical activity. However, designing successful social network interventions is a considerable research challenge. In this study, we rely on social network analysis and agent-based simulations to better understand and capitalize on the complex interplay of social networks and health behaviors. More specifically, we investigate criteria for selecting influence agents that can be expected to produce the most successful social network health interventions.

OBJECTIVE

The aim of this study was to test which selection criterion to determine influence agents in a social network intervention resulted in the biggest increase in physical activity in the social network. To test the differences among the selection criteria, a computational model was used to simulate different social network interventions and observe the intervention's effect on the physical activity of primary and secondary school children within their school classes. As a next step, this study relied on the outcomes of the simulated interventions to investigate whether social network interventions are more effective in some classes than others based on network characteristics.

METHODS

We used a previously validated agent-based model to understand how physical activity spreads in social networks and who was influencing the spread of behavior. From the observed data of 460 participants collected in 26 school classes, we simulated multiple social network interventions with different selection criteria for the influence agents (ie, in-degree centrality, betweenness centrality, closeness centrality, and random influence agents) and a control condition (ie, no intervention). Subsequently, we investigated whether the detected variation of an intervention's success within school classes could be explained by structural characteristics of the social networks (ie, network density and network centralization).

RESULTS

The 1-year simulations showed that social network interventions were more effective compared with the control condition (beta=.30; t100=3.23; P=.001). In addition, the social network interventions that used a measure of centrality to select influence agents outperformed the random influence agent intervention (beta=.46; t100=3.86; P<.001). Also, the closeness centrality condition outperformed the betweenness centrality condition (beta=.59; t100=2.02; P=.046). The anticipated interaction effects of the network characteristics were not observed.

CONCLUSIONS

Social network intervention can be considered as a viable and promising intervention method to promote physical activity. We demonstrated the usefulness of applying social network analysis and agent-based modeling as part of the social network interventions' design process. We emphasize the importance of selecting the most successful influence agents and provide a better understanding of the role of network characteristics on the effectiveness of social network interventions.

Overweight/obesity among social network members has an inverse relationship with Baltimore public housing residents' BMI

The American Heart Association has encouraged networks research focused on cardiovascular disease and its risk factors, such as obesity. However, little network research has focused on minorities or low-income populations. Our objective was to characterize the relationship between body mass index (BMI) with social network overweight/obesity among public housing residents in Baltimore, MD - a predominantly black, low-income group. We conducted a cross-sectional survey of randomly selected public housing residences (8/2014-8/2015). Adults had their height and weight measured and reported their network members' weight statuses using pictograms. Our dependent variable was respondents' BMI, and independent variable was perceived exposure to overweight/obesity in the social network. We also explored network exposure to overweight/obesity among 1) family members and 2) friends. We used multivariable linear regression adjusted for significant covariates. Our sample included 255 adults with mean age of 44.4 years, 85.5% women, 95.7% black, and mean BMI of 33.2 kg/m2. Most network members were overweight/obese (56.1%). For every 1% increase in network exposure to overweight/obesity, individuals' BMI decreased by 0.05 kg/m2 (p = 0.06). As network exposure to overweight/obesity among friends increased, individuals' BMI significantly decreased by 0.06 kg/m2 (p = 0.04). There was no significant relationship between BMI and network exposure to overweight/obesity among family members. In conclusion, among Baltimore public housing residents, a statistically significant, inverse association existed between individuals' BMI and overweight/obesity among friends in their social networks. Our results differ from relationships seen in prior studies of other populations, which may be due to racial and/or contextual differences between studies.

Lose your weight with online buddies: behavioral contagion in an online weight-loss community

Purpose

A question of interest is whether online social networks are effective in promoting behavioral changes and weight loss. The purpose of this paper is to examine the contagion effect of an online buddy network on individuals’ self-monitoring behavior.

Design/methodology/approach

This study collects data from an online weight-loss community and constructs an online buddy network. This study compares the effects of the network structure of the buddy network and the actor attributes when predicting self-monitoring performance by employing the auto-logistic actor attribute models.

Findings

This study confirms the contagion effect on weigh-in behavior in the online buddy network. The contagion effect is significantly predictive when controlling for actor attribute and other network structure effects.

Originality/value

There is limited evidence that one’s weight-related behavior can be affected by online social contacts. This study contributes to the literature on peer influence on health by examining the contagion effect on weight-related behavior between online buddies. The findings can assist in designing peer-based interventions to harness influence from online social contacts for weight loss.

A social-network behavioral health program on sustained long-term body weight and glycemic outcomes: 2-year follow-up of a 4-month Microclinic Health Program in Jordan

The burden of chronic diseases like diabetes and obesity is rapidly increasing in low and lower-middle income countries. This work assesses the long-term efficacy of a social-network based community health program for the management and prevention of type 2 diabetes.

METHODS

The 4-month Microclinic Social Network Behavioral Health Program in Jordan (J-MCP) was an intervention for obesity and diabetes prevention and management conducted in the Kingdom of Jordan. Weight and HbA1c were collected at baseline, end of the 4-month program, and then 12 and 24 months after baseline. Multi-level longitudinal repeated measures analysis estimated the long-term change in metabolic outcomes, and estimated the intra-class correlations (ICCs) for assessing the degree of clustering that different social network levels, of microclinic group vs. classroom group vs. clinic geographic location vs. cohort temporal wave, contributed to body weight and glycemic changes.

RESULTS

Of 315 participants, 83.2% completed the J-MCP program, with 90% followup at 12-months, and 70% at 24-months. At the end of the 4-month program, participants experienced a -2.8 kg (95% CI: -3.6 to -2.1) mean body weight decrease, a corresponding -1.1 kg/m2 (-1.3 to -0.8) BMI decrease, and a -0.5% reduction in HbA1c (-0.6 to -0.3). At year 1, we observed significant mean weight reduction of -1.8 kg (-2.7 to -0.9), a corresponding -0.7 kg/m2 (-1.0 to -0.4) reduction in BMI, as well as a -0.4% (-0.6 to -0.3) sustained reduction in HbA1c. At 2 years, participants sustained mean weight loss of -1.6 kg (-2.6 to -0.5), a -0.42 kg/m2 (-0.8 to -0.04) reduction in BMI, and an absolute -1.0% (-1.1 to -0.8) sustained reduction in HbA1c. Analyzing different social network levels, classroom group explained ~50% of total clustering of total weight loss and 22% of HbA1c trajectories during the short 4 month intervention. However, during 12 and 24 month followup, microclinic social group clustering explained ~75% to 92% of long-term weight loss trajectories, and 55% of long-term HbA1c trajectories. The pattern of 1-2 year sustainability of the weight and HbA1c decreases was largely attributed to the microclinic social network clusters.

CONCLUSION

Results demonstrate that the 4-month J-MCP behavioral intervention yielded important 2-year sustained weight and HbA1c reductions, which were mostly attributed to microclinic social groups.

Contributions of personality to social influence: Contingent associations between social network body size composition and BMI

Social influence is a key determinant of health behaviors and outcomes. Research in the social network tradition emphasizes social structural mechanisms like network content (i.e., the degree to which particular attitudes, attributes, or behaviors are present in the network) and social proximity (i.e., opportunities for social interaction). In contrast, psychologists are oriented toward the individual, identifying how personality traits like self-monitoring affect susceptibility to peer pressure. Here, we integrate social network and personality approaches, examining social influence on body size using surveys of 379 adults with dependent children. Our findings suggest that the association between social network body size composition and respondent BMI is contingent on both individual susceptibility to influence (i.e., high self-monitoring) and social proximity (i.e., opportunities for co-eating). These results indicate that individuals embedded in social networks bring unique sets of social skills and orientations to interactions, potentially influencing the flow of content across networks.

Applications of systems modelling in obesity research

Obesity is a complex system problem involving a broad spectrum of policy, social, economic, cultural, environmental, behavioural, and biological factors and the complex interrelated, cross-sector, non-linear, dynamic relationships among them. Systems modelling is an innovative approach with the potential for advancing obesity research. This study examined the applications of systems modelling in obesity research published between 2000 and 2017, examined how the systems models were developed and used in obesity studies and discussed related gaps in current research. We focused on the applications of two main systems modelling approaches: system dynamics modelling and agent-based modelling. The past two decades have seen a growing body of systems modelling in obesity research. The research topics ranged from micro-level to macro-level energy-balance-related behaviours and policies (19 studies), population dynamics (five studies), policy effect simulations (eight studies), environmental (10 studies) and social influences (15 studies) and their effects on obesity rates. Overall, systems analysis in public health research is still in its early stages, with limitations linked to model validity, mixed findings and its actual use in guiding interventions. Challenges in theory and modelling practices need to be addressed to realize the full potential of systems modelling in future obesity research and interventions.

Quantifying the propagation of distress and mental disorders in social networks

Heterogeneity of human beings leads to think and react differently to social phenomena. Awareness and homophily drive people to weigh interactions in social multiplex networks, influencing a potential contagion effect. To quantify the impact of heterogeneity on spreading dynamics, we propose a model of coevolution of social contagion and awareness, through the introduction of statistical estimators, in a weighted multiplex network. Multiplexity of networked individuals may trigger propagation enough to produce effects among vulnerable subjects experiencing distress, mental disorder, which represent some of the strongest predictors of suicidal behaviours. The exposure to suicide is emotionally harmful, since talking about it may give support or inadvertently promote it. To disclose the complex effect of the overlapping awareness on suicidal ideation spreading among disordered people, we also introduce a data-driven approach by integrating different types of data. Our modelling approach unveils the relationship between distress and mental disorders propagation and suicidal ideation spreading, shedding light on the role of awareness in a social network for suicide prevention. The proposed model is able to quantify the impact of overlapping awareness on suicidal ideation spreading and our findings demonstrate that it plays a dual role on contagion, either reinforcing or delaying the contagion outbreak.

Assessing Social Contagion in Body Mass Index, Overweight, and Obesity Using a Natural Experiment

IMPORTANCE

Little is known about whether the substantial clustering of obesity and overweight within social and geographic networks results from causal pathways, such as social contagion and shared environments, or from self-selection.

OBJECTIVES

This study aimed to determine whether exposure to communities with higher rates of obesity increases the body mass index (BMI) of individuals, calculated as weight in kilograms divided by height in meters squared, and their risk of being overweight or obese, and whether social contagion, shared environments, or self-selection can account for identified differences.

DESIGN, SETTING, AND PARTICIPANTS

This natural experiment study used the routine assignment of military service members to installations as a source of exogenous variation in exposure to communities with higher vs lower rates of obesity. The study, which used data collected by the Military Teenagers' Environments, Exercise, and Nutrition Study, examined families from 38 military installations around the United States to determine if individuals had higher BMI and greater odds of overweight and obesity when assigned to installations in counties with higher rates of obesity. The study also examined if the relationship persisted after controlling for shared built environments. The participants included 1 parent and 1 child aged 12 or 13 years from 1519 families of Army-enlisted personnel. Data analysis was completed from November 2016 to October 2017.

EXPOSURES

Adult obesity rate in the county where the assigned installation of the service member was located. Time at installation and location of residence (on-installation vs off-installation) were used to measure the degree of exposure.

MAIN OUTCOMES AND MEASURES

For parents, outcomes were BMI, overweight/obesity (BMI, ≥25) and obesity (BMI, ≥30). For children, outcomes were BMI z score, overweight/obesity (BMI percentile for age and sex, ≥85), and obesity (BMI percentile for age and sex, ≥95). These outcomes were based on self-reports for parents, self-reports and parent reports for all children, and anthropometric measurements for a subsample of children.

RESULTS

Members of 1519 families participated, including 1314 adults (of whom 740, or 56%, were fathers) and 1111 children (of whom 576, or 52%, were boys); anthropometric measurements were performed on 458 children. The sample was 40% white, 22% black, 24% Hispanic, and 14% other races/ethnicities. A 1-percentage point higher county obesity rate was associated with a higher BMI (a difference of 0.08; 95% CI, 0.02-0.13) and greater odds of obesity (adjusted odds ratio [aOR], 1.05; 95% CI, 1.02-1.08) in parents, and a higher BMI z score (0.01; 95% CI, 0.003-0.02) and greater odds of overweight/obesity (aOR, 1.04; 95% CI, 1.01-1.06) in children. The evidence supported stronger associations among families with more time at installation and off-installation residence. Associations persisted even after controlling for shared built environments.

CONCLUSIONS AND RELEVANCE

Exposure to counties with higher rates of obesity was associated with higher BMI and higher odds of overweight and/or obesity in parents and children. There was no evidence to support self-selection or shared built environments as possible explanations, which suggests the presence of social contagion in obesity.

Perceived Diet and Exercise Behaviors Among Social Network Members With Personal Lifestyle Habits of Public Housing Residents

Our objective was to characterize the relationship between public housing residents' diet/exercise habits with similar behaviors among their social network. We conducted a cross-sectional survey of randomly selected households in Baltimore, Maryland, from August 2014 to August 2015. Adult heads of household completed questions on diet, exercise, and perceived habits among network members. Our dependent variables were high added sugar intake (≥39.9 teaspoons/day), high fruit/vegetable intake (≥6.1 servings/day), and being physically active (≥moderately activity). Our network exposures were proportion of members perceived to daily consume (1) sugar-sweetened beverages, (2) sweets, (3) fruits, and (4) vegetables, as well as to weekly exercise (1) vigorously or (2) moderately. We used multivariate logistic regression to examine associations between habits with relevant network exposures. Our sample included 266 adults with mean age of 44.5 years, 86.1% women and 95.5% African American. We found a statistically significant association between study participants' high daily intake of added sugar with perceived network exposure to daily sugar-sweetened beverages (odds ratio [OR] = 1.10, 95% confidence interval [CI] [1.02, 1.20]) and daily sweets (OR = 1.10, 95% CI [1.02, 1.20]). Greater network exposure to weekly vigorous exercise was significantly associated with personally being physically active (OR = 1.15, 95% CI [1.04, 1.28]), but not network exposure to weekly moderate exercise. Among public housing residents, associations exist between individuals' and perceived networks' lifestyle habits of high added sugar foods consumption and vigorous exercise, which may hold promise for future social network interventions.

How family socioeconomic status, peer behaviors, and school-based intervention on healthy habits influence adolescent eating behaviors

Psychologists in schools can play an important role in developing policies and programs to promote healthy eating habits. This study analyses the contributions of family socioeconomic status, peer influence (schoolmates’ food consumption), and school-based nutrition interventions to explain adolescent eating behaviors. Data were obtained from the 2014 Health behaviour in school-aged children survey in Spain, with a sample of 6,851 adolescents (11- to 16-years-old). The results suggest that school-based healthy-eating programs could improve by considering parental education level and by implementing interventions focused on the peer social network. Policies that limit access to unhealthy products in schools – rather than simply offering healthy foods alongside unhealthy products – could be more effective.

The statistical mechanics of human weight change

Over the past 35 years there has been a near doubling in the worldwide prevalence of obesity. Body Mass Index (BMI) distributions in high-income societies have increasingly shifted rightwards, corresponding to increases in average BMI that are due to well-studied changes in the socioeconomic environment. However, in addition to this shift, BMI distributions have also shown marked changes in their particular shape over time, exhibiting an ongoing right-skewed broadening that is not well understood. Here, we compile and analyze the largest data set so far of year-over-year BMI changes. The data confirm that, on average, heavy individuals become lighter while light individuals become heavier year-over-year, and also show that year-over-year BMI evolution is characterized by fluctuations with a magnitude that is linearly proportional to BMI. We find that the distribution of human BMIs is intrinsically dynamic-due to the short-term variability of human weight-and its shape is determined by a balance between deterministic drift towards a natural set point and diffusion resulting from random fluctuations in, e.g., diet and physical activity. We formulate a stochastic mathematical model for BMI dynamics, deriving a theoretical shape for the BMI distribution and offering a mechanism that may explain the right-skewed broadening of BMI distributions over time. An extension of the base model investigates the hypothesis that peer-to-peer social influence plays a role in BMI dynamics. While including this effect improves the fit with the data, indicating that correlations in the behavior of individuals with similar BMI may be important for BMI dynamics, testing social transmission against other plausible unmodeled effects and interpretations remains the subject of future work. Implications of our findings on the dynamics of BMI distributions for public health interventions are discussed.

Simulating drinking in social networks to inform alcohol prevention and treatment efforts

Adolescent drinking influences, and is influenced by, peer alcohol use. Several efficacious adolescent alcohol interventions include elements aimed at reducing susceptibility to peer influence. Modeling these interventions within dynamically changing social networks may improve our understanding of how such interventions work and for whom they work best. We used stochastic actor-based models to simulate longitudinal drinking and friendship formation within social networks using parameters obtained from a meta-analysis of real-world 10th grade adolescent social networks. Levels of social influence (i.e., friends affecting changes in one's drinking) and social selection (i.e., drinking affecting changes in one's friendships) were manipulated at several levels, which directly impacted the degree of clustering in friendships based on similarity in drinking behavior. Midway through each simulation, one randomly selected heavy-drinking actor from each network received an "intervention" that either (a) reduced their susceptibility to social influence, (b) reduced their susceptibility to social selection, (c) eliminated a friendship with a heavy drinker, or (d) initiated a friendship with a nondrinker. Only the intervention that eliminated targeted actors' susceptibility to social influence consistently reduced that actor's drinking. Moreover, this was only effective in networks with social influence and social selection that were at higher levels than what was found in the real-world reference study. Social influence and social selection are dynamic processes that can lead to complex systems that may moderate the effectiveness of network-based interventions. Interventions that reduce susceptibility to social influence may be most effective among adolescents with high susceptibility to social influence and heavier-drinking friends. (PsycINFO Database Record

Behavioral lifestyle interventions for the primary prevention of type 2 diabetes and translation to Hispanic/Latino communities in the United States and Mexico

Lifestyle behaviors in overweight and obese individuals are closely linked to the development, course, and outcomes of type 2 diabetes and multiple comorbid health conditions. Behavior change theory and many randomized controlled studies offer strong support for screening and identifying adults at increased cardiometabolic risk and for providing early intervention to mitigate risk factors to prevent or delay the onset of disease. The current article reviews key lifestyle intervention efficacy and dissemination trials conducted with individuals deemed to be at increased risk for diabetes and describes the rationale for training teams of professionals and community health workers (e.g., promotores [in Spanish]) to implement comprehensive programs, with fidelity, in a variety of medical care and community settings. This evidence-based road map may be used to facilitate the design and implementation of strategies for structured behavioral diabetes risk reduction programs in the public and private healthcare sectors and other relevant community-based platforms serving individuals of Hispanic/Latino origin in the United States and Mexico.

Feasibility of a Friendship Network-Based Pediatric Obesity Intervention

BACKGROUND

There is growing evidence supporting social network-based interventions for adolescents with obesity. This study's aim was to determine the feasibility of a social network-based intervention by assessing adolescents' friendship networks, willingness to involve friends in treatment, and how these factors influence enjoyment.

METHODS

Adolescents (N = 42) were recruited from a tertiary care obesity clinic. Participants gave a list of closest friends, friendship characteristics, and which of their friends they would involve in treatment. A subset (N = 14) participated in group treatment, were encouraged to bring friends, and invited to a second interview.

RESULTS

Participants nominated a mean of 4.0 (standard deviation [SD] = 1.6) friends and were more likely to nominate closer friends (p = 0.003). Friends who attended group sessions were more likely to have multiple friendships in common with the participant's own network (p = 0.04).

CONCLUSIONS

Involving friends in treatment is feasible and desired by adolescents and may be a novel approach for augmenting obesity treatment outcomes.

Comparing methods of targeting obesity interventions in populations: An agent-based simulation

Social networks as well as neighborhood environments have been shown to effect obesity-related behaviors including energy intake and physical activity. Accordingly, harnessing social networks to improve targeting of obesity interventions may be promising to the extent this leads to social multiplier effects and wider diffusion of intervention impact on populations. However, the literature evaluating network-based interventions has been inconsistent. Computational methods like agent-based models (ABM) provide researchers with tools to experiment in a simulated environment. We develop an ABM to compare conventional targeting methods (random selection, based on individual obesity risk, and vulnerable areas) with network-based targeting methods. We adapt a previously published and validated model of network diffusion of obesity-related behavior. We then build social networks among agents using a more realistic approach. We calibrate our model first against national-level data. Our results show that network-based targeting may lead to greater population impact. We also present a new targeting method that outperforms other methods in terms of intervention effectiveness at the population level.

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While behavioral interventions exist for obesity, uncertainty remains about how best to target those interventions to maximize population-level impact.

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Agent-based models are simulation tools that can be used to evaluate different targeting strategies to help policy makers.

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Targeting intervention resources using social networks may lead to greater population impact of behavioral interventions compared to traditional methods of targeting.

A social contagious model of the obesity epidemic

Obesity has been recognized as a global epidemic by WHO, followed by many empirical evidences to prove its infectiousness. However, the inter-person spreading dynamics of obesity are seldom studied. A distinguishing feature of the obesity epidemic is that it is driven by a social contagion process which cannot be perfectly described by the infectious disease models. In this paper, we propose a novel belief decision model based on the famous Dempster-Shafer theory of evidence to model obesity epidemic as the competing spread of two obesity-related behaviors: physical inactivity and physical activity. The transition of health states is described by an SIS model. Results reveal the existence of obesity epidemic threshold, above which obesity is quickly eradicated. When increasing the fading level of information spread, enlarging the clustering of initial obese seeds, or introducing small-world characteristics into the network topology, the threshold is easily met. Social discrimination against the obese people plays completely different roles in two cases: on one hand, when obesity cannot be eradicated, social discrimination can reduce the number of obese people; on the other hand, when obesity is eradicable, social discrimination may instead cause it breaking out.

Income differences in social control of eating behaviors and food choice priorities among southern rural women in the US: A qualitative study

The role of social influences on rural women's food choice is not well understood. Rural adults experience high rates of obesity and poor diet quality prompting exploration of how social factors influence food choice in this population. Semi-structured qualitative interviews were conducted with 20 women in rural North Central Florida. Women were purposively sampled and stratified by race and income. Lower income was defined as household income at or below 185% of the federal poverty level (FPL). Women at or below 185% poverty level (BPL) experienced direct social control of their eating behaviors, which occurred when social network members explicitly regulated or otherwise sanctioned eating behaviors or food choices. Women above 185% of the federal poverty level (APL) internalized social norms and self-regulated their eating behaviors to maintain healthy habits. APL women described choosing foods for health reasons whereas BPL women offered a variety of reasons including taste, convenience, family history, price, health, and routine. Findings suggest that women in different income groups have different social influences working to help them regulate eating behaviors as well as diverse priorities influencing their food choices. Future interventions to promote healthy eating may be more effective by incorporating social network members and framing intervention messages so they are consistent with priorities.