Is obesity contagious? Social networks vs. environmental factors in the obesity epidemic

Overweight and obesity in India: policy issues from an exploratory multi-level analysis

This article analyses a nationally representative household dataset-the National Family Health Survey (NFHS-3) conducted in 2005 to 2006-to examine factors influencing the prevalence of overweight/obesity in India. The dataset was disaggregated into four sub-population groups-urban and rural females and males-and multi-level logit regression models were used to estimate the impact of particular covariates on the likelihood of overweight/obesity. The multi-level modelling approach aimed to identify individual and macro-level contextual factors influencing this health outcome. In contrast to most studies on low-income developing countries, the findings reveal that education for females beyond a particular level of educational attainment exhibits a negative relationship with the likelihood of overweight/obesity. This relationship was not observed for males. Muslim females and all Sikh sub-populations have a higher likelihood of overweight/obesity suggesting the importance of socio-cultural influences. The results also show that the relationship between wealth and the probability of overweight/obesity is stronger for males than females highlighting the differential impact of increasing socio-economic status on gender. Multi-level analysis reveals that states exerted an independent influence on the likelihood of overweight/obesity beyond individual-level covariates, reflecting the importance of spatially related contextual factors on overweight/obesity. While this study does not disentangle macro-level 'obesogenic' environmental factors from socio-cultural network influences, the results highlight the need to refrain from adopting a 'one size fits all' policy approach in addressing the overweight/obesity epidemic facing India. Instead, policy implementation requires a more nuanced and targeted approach to incorporate the growing recognition of socio-cultural and spatial contextual factors impacting on healthy behaviours.

Testing and Modeling Dependencies Between a Network and Nodal Attributes

Network analysis is often focused on characterizing the dependencies between network relations and node-level attributes. Potential relationships are typically explored by modeling the network as a function of the nodal attributes or by modeling the attributes as a function of the network. These methods require specification of the exact nature of the association between the network and attributes, reduce the network data to a small number of summary statistics, and are unable provide predictions simultaneously for missing attribute and network information. Existing methods that model the attributes and network jointly also assume the data are fully observed. In this article we introduce a unified approach to analysis that addresses these shortcomings. We use a previously developed latent variable model to obtain a low dimensional representation of the network in terms of node-specific network factors. We introduce a novel testing procedure to determine if dependencies exist between the network factors and attributes as a surrogate for a test of dependence between the network and attributes. We also present a joint model for the network relations and attributes, for use if the hypothesis of independence is rejected, that can capture a variety of dependence patterns and be used to make inference and predictions for missing observations.

Mind the gap: race/ethnic and socioeconomic disparities in obesity

Race/ethnic and socioeconomic status (SES) disparities in obesity are substantial and may widen in the future. We review nine potential mechanisms that recent research has used to explain obesity disparities. Those nine mechanisms fall into three broad groups-health behaviors, biological factors, and the social environment-which incorporate both proximate and upstream determinants of obesity disparities. Efforts to reduce the prevalence of obesity in the US population and to close race/ethnic and SES disparities in obesity will likely require the use of multifaceted interventions that target multiple mechanisms simultaneously. Unfortunately, relatively few of the mechanisms reviewed herein have been tested in an intervention framework.

Social embeddedness in an online weight management programme is linked to greater weight loss

The obesity epidemic is heightening chronic disease risk globally. Online weight management (OWM) communities could potentially promote weight loss among large numbers of people at low cost. Because little is known about the impact of these online communities, we examined the relationship between individual and social network variables, and weight loss in a large, international OWM programme. We studied the online activity and weight change of 22,419 members of an OWM system during a six-month period, focusing especially on the 2033 members with at least one friend within the community. Using Heckman's sample-selection procedure to account for potential selection bias and data censoring, we found that initial body mass index, adherence to self-monitoring and social networking were significantly correlated with weight loss. Remarkably, greater embeddedness in the network was the variable with the highest statistical significance in our model for weight loss. Average per cent weight loss at six months increased in a graded manner from 4.1% for non-networked members, to 5.2% for those with a few (two to nine) friends, to 6.8% for those connected to the giant component of the network, to 8.3% for those with high social embeddedness. Social networking within an OWM community, and particularly when highly embedded, may offer a potent, scalable way to curb the obesity epidemic and other disorders that could benefit from behavioural changes.

The role of social networks in the development of overweight and obesity among adults: a scoping review

BACKGROUND

Although it is increasingly acknowledged that social networks are important to our understanding ofoverweight and obesity, there is limited understanding about the processes by which such networks shapetheir progression. This paper reports the findings of a scoping review of the literature that sought to identify the key processes through which social networks are understood to influence the development of overweight and obesity.

METHODS

A scoping review was conducted. Forty five papers were included in the final review, the findings of which were synthesised to provide an overview of the main processes through which networks have been understood to influence the development of overweight and obesity.

RESULTS

Included papers addressed a wide range of research questions framed around six types of networks: a paired network (one's spouse or intimate partner); friends and family (including work colleagues and people within social clubs); ephemeral networks in shared public spaces (such as fellow shoppers in a supermarket or diners in a restaurant); people living within the same geographical region; peers (including co-workers, fellow students, fellow participants in a weight loss programme); and cultural groups (often related toethnicity). As individuals are embedded in many of these different types of social networks at any one time, the pathways of influence from social networks to the development of patterns of overweight and obesity are likely to be complex and interrelated. Included papers addressed a diverse set of issues: body weight trends over time; body size norms or preferences; weight loss and management; physical activity patterns; and dietary patterns.

DISCUSSION

Three inter-related processes were identified: social contagion (whereby the network in which people are embedded influences their weight or weight influencing behaviours), social capital (whereby sense of belonging and social support influence weight or weight influencing behaviours), and social selection (whereby a person's network might develop according to his or her weight).

CONCLUSIONS

The findings have important implications for understanding about methods to target the spread of obesity, indicating that much greater attention needs to be paid to the social context in which people make decisions about their weight and weight influencing behaviours.

Discrete dynamics of contagious social diseases: Example of obesity

Modeling contagious diseases needs to incorporate information about social networks through which the disease spreads as well as data about demographic and genetic changes in the susceptible population. In this paper, we propose a theoretical framework (conceptualization and formalization) which seeks to model obesity as a process of transformation of one's own body determined by individual (physical and psychological), inter-individual (relational, i.e., relative to the relationship between the individual and others) and socio-cultural (environmental, i.e., relative to the relationship between the individual and his milieu) factors. Individual and inter-individual factors are tied to each other in a socio-cultural context whose impact is notably related to the visibility of anybody being exposed on the public stage in a non-contingent way. The question we are dealing with in this article is whether such kind of social diseases, i.e., depending upon socio-environmental exposure, can be considered as "contagious". In other words, can obesity be propagated from individual to individual or from environmental sources throughout an entire population?

Social network characteristics associated with weight loss among black and hispanic adults

OBJECTIVE

To examine social network member characteristics associated with weight loss.

METHODS

A cross-sectional examination included egocentric network data from 245 Black and Hispanic adults with BMI ≥ 25 kg/m(2) enrolled in a small change weight loss study. The relationships between weight loss at 12 months and characteristics of helpful and harmful network members (relationship, contact frequency, living proximity, and body size) were examined.

RESULTS

There were 2,571 network members identified. Mean weight loss was -4.8 (±11.3) lbs. among participants with network help and no harm with eating goals vs. +3.4 (±7.8) lbs. among participants with network harm alone. In a multivariable regression model, greater weight loss was associated with help from a child with eating goals (P = 0.0002) and coworker help with physical activity (P = 0.01). Weight gain was associated with having network members with obesity living in the home (P = 0.048) and increased network size (P = 0.002).

CONCLUSIONS

There was greater weight loss among participants with support from children and coworkers. Weight gain was associated with harmful network behaviors and having network members with obesity in the home. Incorporating child and coworker support and evaluating network harm and the body size of network members should be considered in future weight loss interventions.

Peer effects on obesity in a sample of European children

This study analyzes peer effects on childhood obesity using data from the first two waves of the IDEFICS study, which applies several anthropometric and other measures of fatness to approximately 14,000 children aged two to nine participating in both waves in 16 regions of eight European countries. Peers are defined as same-sex children in the same school and age group. The results show that peer effects do exist in this European sample but that they differ among both regions and different fatness measures. Peer effects are larger in Spain, Italy, and Cyprus--the more collectivist regions in our sample--while waist circumference generally gives rise to larger peer effects than BMI. We also provide evidence that parental misperceptions of their own children's weight goes hand in hand with fatter peer groups, supporting the notion that in making such assessments, parents compare their children's weight with that of friends and schoolmates.

A natural experiment of peer influences on youth alcohol use

This study estimates peer effects on alcohol use, drawing from a database of about 2000 randomly-assigned roommates on a college campus. The estimation of peer influences also takes into consideration ego's history of alcohol use and friendship with the peer. College students averaged an additional two-fifths of a binge drinking episode per month and an additional one-half of a drinking episode per month when randomly assigned a roommate who drank in high school than when assigned a roommate who did not drink in high school. An individual's prior history of alcohol use proves important. Peer effects on binge drinking as well as drinking for those who already drank in high school were about twice as large as average peer effects. When one did not have a history of alcohol use, negative peer influences were absent. Also important is the friendship between peers. When a peer is considered a best friend, the step-up effect (or positive interaction effect) increased by 1.25-1.61 drinking episodes per month. However, even when a peer is not considered a best friend, a drinking peer still increased ego's drinking episodes by 0.75-1.00 per month.

Peer effects, fast food consumption and adolescent weight gain

This paper aims at opening the black box of peer effects in adolescent weight gain. Using Add Health data on secondary schools in the U.S., we investigate whether these effects partly flow through the eating habits channel. Adolescents are assumed to interact through a friendship social network. We propose a two-equation model. The first equation provides a social interaction model of fast food consumption. To estimate this equation we use a quasi maximum likelihood approach that allows us to control for common environment at the network level and to solve the simultaneity (reflection) problem. Our second equation is a panel dynamic weight production function relating an individual's Body Mass Index z-score (zBMI) to his fast food consumption and his lagged zBMI, and allowing for irregular intervals in the data. Results show that there are positive but small peer effects in fast food consumption among adolescents belonging to a same friendship school network. Based on our preferred specification, the estimated social multiplier is 1.15. Our results also suggest that, in the long run, an extra day of weekly fast food restaurant visits increases zBMI by 4.45% when ignoring peer effects and by 5.11%, when they are taken into account.

Social Relationships and Obesity: Benefits of Incorporating a Lifecourse Perspective

Social networks reflect the structure of our interpersonal relationships. The effect of social networks on health is a topic of growing interest, particularly in an increasingly connected world. This review provides an overview of how social relations shape obesity risk and the effectiveness of network-based obesity interventions across the life course. The review highlights that, while the literature suggests obesity and related health behaviors are similar between socially-connected individuals, why this is the case and how to effectively intervene remains unclear. In addition, the review outlines methodological gaps limiting our understanding of how social networks shape obesity risk throughout the lifecourse. Several implications for obesity prevention and research are offered, including the need to examine the relationship of social networks and obesity across rather than within life-course stages, continued development of statistical social network analysis methods and the need for new cohort studies, particularly among children and the elderly.

Incorporating Systems Science Principles into the Development of Obesity Prevention Interventions: Principles, Benefits, and Challenges

Systems modeling represents an innovative approach for addressing the obesity epidemic at the community level. We developed an agent-based model of the Baltimore City food environment that permits us to assess the relative impact of different programs and policies, alone and in combination, and potential unexpected consequences. Based on this experience, and a review of literature, we have identified a set of principles, potential benefits, and challenges. Some of the key principles include the importance of early and multilevel engagement with the community prior to initiating model development and continued engagement and testing with community stakeholders. Important benefits include improving community stakeholder understanding of the system, testing of interventions before implementation, and identification of unexpected consequences. Challenges in these models include deciding on the most important, yet parsimonious factors to consider, how to model food source and food selection behavior in a realistic yet transferable manner, and identifying the appropriate outcomes and limitations of the model.

Obesity and health expenditures: evidence from Australia

Rising rates of obesity are a public health concern in every industrialized country. This study investigates the relationship between obesity and health care expenditure in Australia, where the rate of obesity has tripled in the last three decades. Now one in four Australians is considered obese, defined as having a body mass index (BMI, kg/m(2)) of 30 or over. The analysis is based on a random sample survey of over 240,000 adults aged 45 and over that is linked at the individual-level to comprehensive administrative health care claims for the period 2006-2009. This sub-population group has an obesity rate that is nearly 30% and is a major consumer of health services. Relative to the average annual health expenditures of those with normal weight, we find that the health expenditures of those with a BMI between 30 and 35 (obese type I) are 19% higher and expenditures of those with BMI greater than 35 (obese type II/III) are 51% higher. We find large and significant differences in all types of care: inpatient, emergency department, outpatient and prescription drugs. The obesity-related health expenditures are higher for obese type I women than men, but in the obese type II/III state, obesity-related expenditures are higher for men. When we stratify further by age groups, we find that obesity has the largest impact among men over age 75 and women aged 60-74 years old. In addition, we find that obesity impacts health expenditures not only through its link to chronic diseases, but also because it increases the cost of recovery from acute health shocks.

Instrumental variables estimates of peer effects in social networks

Estimating peer effects with observational data is very difficult because of contextual confounding, peer selection, simultaneity bias, and measurement error, etc. In this paper, I show that instrumental variables (IVs) can help to address these problems in order to provide causal estimates of peer effects. Based on data collected from over 4000 students in six middle schools in China, I use the IV methods to estimate peer effects on smoking. My design-based IV approach differs from previous ones in that it helps to construct potentially strong IVs and to directly test possible violation of exogeneity of the IVs. I show that measurement error in smoking can lead to both under- and imprecise estimations of peer effects. Based on a refined measure of smoking, I find consistent evidence for peer effects on smoking. If a student's best friend smoked within the past 30 days, the student was about one fifth (as indicated by the OLS estimate) or 40 percentage points (as indicated by the IV estimate) more likely to smoke in the same time period. The findings are robust to a variety of robustness checks. I also show that sharing cigarettes may be a mechanism for peer effects on smoking. A 10% increase in the number of cigarettes smoked by a student's best friend is associated with about 4% increase in the number of cigarettes smoked by the student in the same time period.

Using Spatial Disease Patterns and Patient-Level Characteristics to Describe Prevalence Elastic Behavior in Treatment for Latent Tuberculosis Infection (LTBI)

OBJECTIVE

Individual adherence to a 9-month regimen of isoniazid (9INH) for treatment of latent tuberculosis infection (LTBI) was hypothesized to reflect a prevalent elastic health behavior pattern, or prevention behavior correlated with relevant disease burden.

METHOD

Log-rank tests were used to compare survival functions among raw prevalence tertiles for diseases including TB, diabetes, and obesity. Own and cross-prevalence elasticities were calculated and spatially characterized behavioral response to diseases that may impact TB re-infection and/or re-activation. Discrete choice models were used to assess the significance of the spatial elasticities among an ethnically diverse clinic population of 552 patients in an urban American county in 2010.

RESULTS

Log-rank results revealed a statistical association between dropout and chronic disease prevalence (p < .01), but not TB prevalence (p = .13). Discrete choice models incorporating spatial elasticities and controlling for patient- and treatment-level characteristics demonstrated significant associations with adherence (p < .01), an effect robust to various alternative treatment definitions.

CONCLUSION

Individual LTBI adherence tracks a prevalence elastic pattern that may represent a potential risk for re-infection and re-activation.

Formalizing the role of agent-based modeling in causal inference and epidemiology

Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry.

Do people desire to be healthier than other people? A short note on positional concerns for health

Contrary to traditional economic postulates, people do not only care about their absolute position but also about their relative position. However, empirical evidence on positional concerns in the context of health is scarce, despite its relevance for health care policy. This paper presents a first explorative study on positional concerns in the context of health. Using a 'two-world' survey method, a convenience sample of 143 people chose between two options (having more in absolute terms or having more in relative terms) in several health and non-health domains. Our results for the non-health domains compare reasonably well to previous studies, with 22-47% of respondents preferring the positional option. In the health domain, these percentages were significantly lower, indicating a stronger focus on absolute positions. The finding that positional concerns are less prominent in the health domain has important implications for health policy, for instance in balancing reduction of socio-economic inequalities and absolute health improvements.

Evolution of social networks: the example of obesity

The present paper deals with the effect of the social transmission of nutrition habits in a social and biological age-dependent context on obesity, and accordingly on type II diabetes and among its complications, the neurodegenerative diseases. The evolution of social networks and inside a network the healthy weight of a person are depending on the context in which this person has contacts and exchanges concerning his alimentation, physical activity and sedentary habits, inside the dominant social network in which the person lives (e.g., scholar for young, professional for adult, home or institution for elderly people). Three successive steps of evolution will be considered for social networks (like for neural one's): initial random connectivity, destruction and consolidation of links following a new transition rule called homophilic until an asymptotic architectural organization and configuration of states. The application of such a network dynamics concerns the sequence overweight/obesity/type II diabetes and neurodegenerative diseases.

The effect of friend selection on social influences in obesity

We present an agent-based model of weight choice and peer selection that simulates the effect of peer selection on social multipliers for weight loss interventions. The model generates social clustering around weight through two mechanisms: a causal link from others' weight to an individual's weight and the propensity to select peers based on weight. We simulated weight loss interventions and tried to identify intervention targets that maximized the spillover of weight loss from intervention participants to nonparticipants. Social multipliers increase with the number of intervention participants' friends. For example, when friend selection was based on a variable exogenous to weight, the weight lost among non-participants increased by 23% (14.3lb vs. 11.6lb) when targeting the most popular obese. Holding constant the number of participants' friends, multipliers increase with increased weight clustering due to selection, up to a point. For example, among the most popular obese, social multipliers when matching on a characteristic correlated with weight (1.189) were higher than when matching on the exogenous characteristic (1.168) and when matching on weight (1.180). Increased weight clustering also implies more obese "friends of friends" of participants, who reduce social multipliers.

Neighborhood effects in a behavioral randomized controlled trial

Randomized controlled trials (RCTs) of interventions intended to modify health behaviors may be influenced by neighborhood effects which can impede unbiased estimation of intervention effects. Examining a RCT designed to increase colorectal cancer (CRC) screening (N=5628), we found statistically significant neighborhood effects: average CRC test use among neighboring study participants was significantly and positively associated with individual patient's CRC test use. This potentially important spatially-varying covariate has not previously been considered in a RCT. Our results suggest that future RCTs of health behavior interventions should assess potential social interactions between participants, which may cause intervention arm contamination and may bias effect size estimation.

Social networks and future direction for obesity research: A scoping review

Despite significant efforts to decrease obesity rates, the prevalence of obesity continues to increase in the United States. Obesity risk behaviors including physical inactivity, unhealthy eating, and sleep deprivation are intertwined during daily life and are difficult to improve in the current social environment. Studies show that social networks-the thick webs of social relations and interactions-influence various health outcomes, such as HIV risk behaviors, alcohol consumption, smoking, depression, and cardiovascular mortality; however, there is limited information on the influences of social networks on obesity and obesity risk behaviors. Given the complexities of the biobehavioral pathology of obesity and the lack of clear evidence of effectiveness and sustainability of existing interventions that are usually focused on an individual approach, targeting change in an individual's health behaviors or attitude may not take sociocontextual factors into account; there is a pressing need for a new perspective on this problem. In this review, we evaluate the literature on social networks as a potential approach for obesity prevention and treatment (i.e., how social networks affect various health outcomes), present two major social network data analyses (i.e., egocentric and sociometric analysis), and discuss implications and the future direction for obesity research using social networks.

Do colleagues influence our lifestyle: the matter of smoking, body mass index and leisure-time physical activity?

OBJECTIVE

Previous research has indicated that health behaviours tend to cluster in social networks, but few have studied the cluster effect in workgroups. We examined the effect of workgroups on current state and change in three indicators of health behaviours (smoking, body mass index (BMI) and physical activity). Further, we examined whether health behaviours of the respondents at group level predicted lifestyle changes.

METHODS

In a prospective cohort (n=4730), employees from 250 workgroups in the Danish eldercare sector answered questionnaires at baseline (2005) and follow-up (2006). Multilevel regression models were used to examine the effect of workgroups.

RESULTS

Workgroups accounted for 6.49% of the variation in smoking status, 6.56% of amount smoked and 2.62% of the variation in current BMI. We found no significant workgroup clustering in physical activity or lifestyle changes. Furthermore, changes in smoking status (cessation) and weight gain were seen in workgroups with high percentage of smokers and high levels of BMI.

CONCLUSION

We found modest evidence for clustering of some health behaviours within workgroups, which could be due to social learning or selection into and out of workgroups. Future health promotion programmes at worksites should recognize the potential clustering of lifestyle behaviours within workgroups.

Estimating the peer effect on youth overweight and inactivity using an intervention study

BACKGROUND

Understanding peer effect is potentially important for finding ways to combat the obesity epidemic. Nevertheless, it is not clear whether a peer effect exists because of the composition of the peer group, because the group members have similar, unobserved individual characteristics, or because of an endogenous effect.

METHODS

This issue is addressed here by using a unique longitudinal data set of 573 schoolchildren attending state schools in the Municipality of Aalborg, Denmark, during 2008-2010. To identify the spillover effect of a targeted intervention on peers, we use a difference-in-differences approach.

RESULTS

A targeted health intervention reduced body mass index (BMI) among overweight, inactive individuals and, more interestingly, that BMI among the nontreated peers was reduced by 1.04%.

CONCLUSIONS

The analysis suggests that individually targeted health intervention has a health benefit beyond the treated individual, which needs to be included when evaluating targeted policies aiming to combat childhood overweight and inactivity.

Examining social norm impacts on obesity and eating behaviors among US school children based on agent-based model

Background

Although the importance of social norms in affecting health behaviors is widely recognized, the current understanding of the social norm effects on obesity is limited due to data and methodology limitations. This study aims to use nontraditional innovative systems methods to examine: a) the effects of social norms on school children’s BMI growth and fruit and vegetable (FV) consumption, and b) the effects of misperceptions of social norms on US children’s BMI growth.

Methods

We built an agent-based model (ABM) in a utility maximization framework and parameterized the model based on empirical longitudinal data collected in a US nationally representative study, the Early Childhood Longitudinal Study – Kindergarten Cohort (ECLS-K), to test potential mechanisms of social norm affecting children’s BMI growth and FV consumption.

Results

Intraclass correlation coefficients (ICC) for BMI were 0.064-0.065, suggesting that children’s BMI were similar within each school. The correlation between observed and ABM-predicted BMI was 0.87, indicating the validity of our ABM. Our simulations suggested the follow-the-average social norm acts as an endogenous stabilizer, which automatically adjusts positive and negative deviance of an individual’s BMI from the group mean of a social network. One unit of BMI below the social average may lead to 0.025 unit increase in BMI per year for each child; asymmetrically, one unit of BMI above the social average, may only cause 0.015 unit of BMI reduction. Gender difference was apparent. Social norms have less impact on weight reduction among girls, and a greater impact promoting weight increase among boys. Our simulation also showed misperception of the social norm would push up the mean BMI and cause the distribution to be more skewed to the left. Our simulation results did not provide strong support for the role of social norms on FV consumption.

Conclusions

Social norm influences US children’s BMI growth. High obesity prevalence will lead to a continuous increase in children’s BMI due to increased socially acceptable mean BMI. Interventions promoting healthy body image and desirable socially acceptable BMI should be implemented to control childhood obesity epidemic.

The impact of public housing on social networks: a natural experiment

OBJECTIVES

We assessed whether 2 types of public housing-scattered among market-rate housing developments or clustered in small public housing projects-were associated with the perceived health and health behaviors of residents' social networks.

METHODS

Leveraging a natural experiment in Montgomery County, Maryland, in which residents were randomly assigned to different types of public housing, we surveyed 453 heads of household in 2011. We asked residents about their own health as well as the perceived health of their network members, including their neighbors.

RESULTS

Residents in scattered-site public housing perceived that their neighbors were more likely to exercise than residents of clustered public housing (24.7% of network members vs 14.0%; P < .001). There were no significant differences in the proportion of network members who were perceived to have major health problems, depressed mood, poor diet, or obesity. Having more network members who smoked was associated with a significantly higher likelihood of smoking.

CONCLUSIONS

Different types of public housing have a modest impact on the health composition of one's social network, suggesting the importance of housing policy for health.

Measuring social networks for medical research in lower-income settings

Social networks are believed to affect health-related behaviors and health. Data to examine the links between social relationships and health in low- and middle-income country settings are limited. We provide guidance for introducing an instrument to collect social network data as part of epidemiological surveys, drawing on experience in urban India. We describe development and fielding of an instrument to collect social network information relevant to health behaviors among adults participating in a large, population-based study of non-communicable diseases in Delhi, India. We discuss basic characteristics of social networks relevant to health including network size, health behaviors of network partners (i.e., network exposures), network homogeneity, network diversity, strength of ties, and multiplexity. Data on these characteristics can be collected using a short instrument of 11 items asked about up to 5 network members and 3 items about the network generally, administered in approximately 20 minutes. We found high willingness to respond to questions about social networks (97% response). Respondents identified an average of 3.8 network members, most often relatives (80% of network ties), particularly blood relationships. Ninety-one percent of respondents reported that their primary contacts for discussing health concerns were relatives. Among all listed ties, 91% of most frequent snack partners and 64% of exercise partners in the last two weeks were relatives. These results demonstrate that family relationships are the crux of social networks in some settings, including among adults in urban India. Collecting basic information about social networks can be feasibly and effectively done within ongoing epidemiological studies.

Bi-national Social Networks and Assimilation: A Test of the Importance of Transnationalism

While the concept of transnationalism has gained widespread popularity among scholars as a way to describe immigrants' long-term maintenance of cross-border ties to their origin communities, critics have argued that the overall proportion of immigrants who engage in transnational behavior is low and that, as a result, transnationalism has little sustained effect on the process of immigrant adaptation and assimilation. In this paper, we argue that a key shortcoming in the current empirical debate on transnationalism is the lack of data on the social networks that connect migrants to each other and to non-migrants in communities of origin. To address this shortcoming, our analysis uses unique bi-national data on the social network connecting an immigrant sending community in Guanajuato, Mexico, to two destination areas in the United States. We test for the effect of respondents' positions in cross-border networks on their migration intentions and attitudes towards the United States using data on the opinions of their peers, their participation in cross border and local communication networks, and their structural position in the network. The results indicate qualified empirical support for a network-based model of transnationalism; in the U.S. sample we find evidence of network clustering consistent with peer effects, while in the Mexican sample we find evidence of the importance of cross-border communication with friends.

Leveraging social influence to address overweight and obesity using agent-based models: the role of adolescent social networks

The prevalence of adolescent overweight and obesity (hereafter, simply "overweight") in the US has increased over the past several decades. Individually-targeted prevention and treatment strategies targeting individuals have been disappointing, leading some to propose leveraging social networks to improve interventions. We hypothesized that social network dynamics (social marginalization; homophily on body mass index, BMI) and the strength of peer influence would increase or decrease the proportion of network member (agents) becoming overweight over a simulated year, and that peer influence would operate differently in social networks with greater overweight. We built an agent-based model (ABM) using results from R-SIENA. ABMs allow for the exploration of potential interventions using simulated agents. Initial model specifications were drawn from Wave 1 of the National Longitudinal Study of Adolescent Health (Add Health). We focused on a single saturation school with complete network and BMI data over two waves (n = 624). The model was validated against empirical observations at Wave 2. We focused on overall overweight prevalence after a simulated year. Five experiments were conducted: (1) changing attractiveness of high-BMI agents; (2) changing homophily on BMI; (3) changing the strength of peer influence; (4) shifting the overall BMI distribution; and (5) targeting dietary interventions to highly connected individuals. Increasing peer influence showed a dramatic decrease in the prevalence of overweight; making peer influence negative (i.e., doing the opposite of friends) increased overweight. However, the effect of peer influence varied based on the underlying distribution of BMI; when BMI was increased overall, stronger peer influence increased proportion of overweight. Other interventions, including targeted dieting, had little impact. Peer influence may be a viable target in overweight interventions, but the distribution of body size in the population needs to be taken into account. In low-obesity populations, strengthening peer influence may be a useful strategy.

Experimental evidence of massive-scale emotional contagion through social networks

Emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. Emotional contagion is well established in laboratory experiments, with people transferring positive and negative emotions to others. Data from a large real-world social network, collected over a 20-y period suggests that longer-lasting moods (e.g., depression, happiness) can be transferred through networks [Fowler JH, Christakis NA (2008) BMJ 337:a2338], although the results are controversial. In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred. These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks. This work also suggests that, in contrast to prevailing assumptions, in-person interaction and nonverbal cues are not strictly necessary for emotional contagion, and that the observation of others' positive experiences constitutes a positive experience for people.

Identification of direct and indirect social network effects in the pathophysiology of insulin resistance in obese human subjects

OBJECTIVE

The aim of the present study was to examine to what extent different social network mechanisms are involved in the pathogenesis of obesity and insulin-resistance.

DESIGN

We used nonparametric and parametric regression models to analyse whether individual BMI and HOMA-IR are determined by social network characteristics.

SUBJECTS AND METHODS

A total of 677 probands (EGO) and 3033 social network partners (ALTER) were included in the study. Data gathered from the probands include anthropometric measures, HOMA-IR index, health attitudes, behavioural and socio-economic variables and social network data.

RESULTS

We found significant treatment effects for ALTERs frequent dieting (p<0.001) and ALTERs health oriented nutritional attitudes (p<0.001) on EGO's BMI, establishing a significant indirect network effect also on EGO's insulin resistance. Most importantly, we also found significant direct social network effects on EGO's insulin resistance, evidenced by an effect of ALTERs frequent dieting (p = 0.033) and ALTERs sport activities (p = 0.041) to decrease EGO's HOMA-IR index independently of EGO's BMI.

CONCLUSIONS

Social network phenomena appear not only to be relevant for the spread of obesity, but also for the spread of insulin resistance as the basis for type 2 diabetes. Attitudes and behaviour of peer groups influence EGO's health status not only via social mechanisms, but also via socio-biological mechanisms, i.e. higher brain areas might be influenced not only by biological signals from the own organism, but also by behaviour and knowledge from different human individuals. Our approach allows the identification of peer group influence controlling for potential homophily even when using cross-sectional observational data.

Development and validation of a short scale to measure how social relationships support the continuous and conscious endeavour to lose weight

This paper reports the development of a short scale (ten items) entitled 'Social Relationships to Prevent Obesity' (SRPO), which examines how social relationships support the continuous and conscious endeavour to lose weight. The construct and criterion validity of this scale were ascertained in this study. Factor structure and reliability were examined using data from a randomized controlled trial. A confirmatory factor analysis of the SRPO revealed three relevant factors. The results suggest that the SRPO has both validity and clinical utility and can thus be used as a screening tool in weight-loss interventions and to assess the degree of, and trends in, self-control for weight loss in individuals. The scale can also be used to examine the environmental and self-control problems faced by obese people--factors that should be considered when conducting weight-loss interventions.

Siblings, friends, course-mates, club-mates: how adolescent health behavior homophily varies by race, class, gender, and health status

Many unhealthy behaviors develop during adolescence, and these behaviors can have fundamental consequences for health and mortality in adulthood. Social network structure and the degree of homophily in a network affect how health behaviors and innovations are spread. However, the degree of health behavior homophily across different social ties and within subpopulations is unknown. This paper addresses this gap in the literature by using a novel regression model to document the degree of homophily across various relationship types and subpopulations for behaviors of interest that are related to health outcomes. These patterns in health behavior homophily have implications for which behaviors and ties should be the subjects of future research and for predicting how homophily may shape health programs focused on specific subpopulations (gender, race, class, health status) or a specific social context (families, peer groups, classrooms, or school activities).

Cross-gender social normative effects for violence in middle school: do girls carry a social multiplier effect for at-risk boys?

A social multiplier effect is a social interaction in which the behavior of a person in a social network varies with the normative behavior of others in the network, also known as an endogenous interaction. Policies and intervention efforts can harness social multiplier effects because, in theory, interventions on a subset of individuals will have "spillover effects" on other individuals in the network. This study investigates potential social multiplier effects for violence in middle schools, and whether there is evidence for a social multiplier effect transmitted from girls to boys. Three years of longitudinal data (2003-2005) from Project Northland Chicago were used to investigate this question, with a sample consisting of youth in Grades 6 through 8 in 61 Chicago Public Schools (N = 4,233 at Grade 6, N = 3,771 at Grade 7, and N = 3,793 at Grade 8). The sample was 49.3% female, and primarily African American (41.9%) and Latino/a (28.7%), with smaller proportions of whites (12.9%), Asians (5.2%) and other ethnicities. Results from two sets of regression models estimating the effects of 20th (low), 50th (average), and 80th (high) percentile scores for girls and boys on levels of violence in each gender group revealed evidence for social multiplier effects. Specifically, boys and girls were both influenced by social multiplier effects within their own gender group, and boys were also affected by normative violence scores among girls, typically those of the best-behaved (20th percentile) girls. The finding that girls may have positive social influence on boys' levels of violent behavior extends prior findings of beneficial social effects of girls on boys in the domains of education and risky driving. Further, this social normative effect presents a potential opportunity to improve school-based intervention efforts for reducing violence among youth by leveraging girls as carriers of a social multiplier effect for reduced violence in the middle school environmental context, particularly among boys, who are at greater risk.

Obesogenic environmental influences on young adults: evidence from college dormitory assignments

This study utilizes a natural experiment-conditionally random dormitory assignments of first-year US college students-to investigate the influence of obesogenic environmental factors in explaining changes in weight and exercise behavior during the 2009-2010 academic year. The design addresses potential selection biases resulting from the likelihood that individuals sort into built environments that match their preferences for exercise and healthy eating. We find some evidence that the food environment, specifically access to campus dining, significantly affected the weight of female students in our study. Females assigned to dormitories where the nearest campus dining hall was closed on the weekends gained about 1lb less over the course of the year than females assigned to dormitories near dining halls that were open 7 days a week. We also find some evidence that female who lived in close proximity to a grocery store gained less weight over the course of the year. Finally, females who lived closer to campus gym reported more frequent exercise over the course of the year. We do not find significant effects of the built environment on weight changes of males in our sample, but we are cautious to draw strong conclusions from this because the male weight change in our sample was quite small.

A Co-Evolution Model for Dynamic Social Network and Behavior

Individual behaviors, such as drinking, smoking, screen time, and physical activity, can be strongly influenced by the behavior of friends. At the same time, the choice of friends can be influenced by shared behavioral preferences. The actor-based stochastic models (ABSM) are developed to study the interdependence of social networks and behavior. These methods are efficient and useful for analysis of discrete behaviors, such as drinking and smoking; however, since the behavior evolution function is in an exponential format, the ABSM can generate inconsistent and unrealistic results when the behavior variable is continuous or has a large range, such as hours of television watched or body mass index. To more realistically model continuous behavior variables, we propose a co-evolution process based on a linear model which is consistent over time and has an intuitive interpretation. In the simulation study, we applied the expectation maximization (EM) and Markov chain Monte Carlo (MCMC) algorithms to find the maximum likelihood estimate (MLE) of parameter values. Additionally, we show that our assumptions are reasonable using data from the National Longitudinal Study of Adolescent Health (Add Health).

Weight perceptions, weight control and income: an analysis using British data

The aim of this paper is to better understand one of the mechanisms underlying the income-obesity relationship so that effective policy interventions can be developed. Our approach involves analysing data on approximately 9000 overweight British adults from between 1997 and 2002. We estimate the effect of income on the probability that an overweight individual correctly recognises their overweight status and the effect of income on the probability that an overweight individual attempts to lose weight. The results suggest that high income individuals are more likely to recognise their unhealthy weight status, and conditional on this correct weight perception, more likely to attempt weight loss. For example, it is estimated that overweight high income males are 15 percentage-points more likely to recognise their overweight status than overweight low income males, and overweight high income males are 10 percentage-points more likely to be trying to lose weight. An implication of these results is that more public education on what constitutes overweight and the dangers associated with being overweight is needed, especially in low income neighbourhoods.

Breaking Up is Hard to Do, Unless Everyone Else is Doing it Too: Social Network Effects on Divorce in a Longitudinal Sample

Divorce represents the dissolution of a social tie, but it is also possible that attitudes about divorce flow across social ties. To explore how social networks influence divorce and vice versa, we exploit a longitudinal data set from the long-running Framingham Heart Study. The results suggest that divorce can spread between friends. Clusters of divorces extend to two degrees of separation in the network. Popular people are less likely to get divorced, divorcees have denser social networks, and they are much more likely to remarry other divorcees. Interestingly, the presence of children does not influence the likelihood of divorce, but each child reduces the susceptibility to being influenced by peers who get divorced. Overall, the results suggest that attending to the health of one's friends' marriages may serve to support and enhance the durability of one's own relationship, and that, from a policy perspective, divorce should be understood as a collective phenomenon that extends beyond those directly affected.

Ethical Standards to Guide the Development of Obesity Policies and Programs Comment on "Ethical Agreement and Disagreement about Obesity Prevention Policy in the United States"

The recent report by Barnhill and King about obesity prevention policy raises important issues for discussion and analysis. In response, this article raises four points for further consideration. First, a distinction between equality and justice needs to be made and consistently maintained. Second, different theories of justice highlight one additional important source of disagreement about the ethical propriety of the proposed obesity prevention policies. Third, another point of contention arises with respect to different understandings of the principle of respect for autonomy due to its often-mistaken equation with simple, unfettered freedom. Finally, based on a more robust definition of autonomy, the key issues in obesity prevention policies can be suitably re-framed in terms of whether they advance just social conditions that enable people to realize human capabilities to the fullest extent possible.

Peer similarity and influence for weight-related outcomes in adolescence: a meta-analytic review

Weight-related problems, including obesity and disordered eating, have emerged as major public health concerns for adolescents. To address these deviations from healthy eating and weight regulation, prevention and intervention efforts have targeted the influence of peers. Yet, evidence that peers influence weight-related outcomes, often inferred from similarity among peers, is inconsistent. This meta-analytic review evaluated peer similarity and influence not only for body size and symptoms of disordered eating, but also for key determinants of obesity (food intake and physical activity levels) and eating pathology (body dissatisfaction and weight control strategies). For each of the six outcomes, data was summarized from 9 to 24 independent studies. Results revealed significant, non-trivial similarity among peers across outcome variables, with the exception of disordered eating. Findings indicated that resemblances among peers were unlikely to be solely the reflection of cognitive biases or the selection of alike friends, but may be partially due to influence. To better understand the influence of peers, further longitudinal research is needed, particularly focusing on the factors that moderate susceptibility to conformity.

We can do better than last place: improving the health of us women

Life expectancy for US women lags behind that for women in other countries. Factors contributing to inequitable health for women are complex and include policy, community, healthcare access, and the interaction between the patient and her healthcare provider working within the healthcare system. We propose a societal pyramid of health accounting for the effects of these different factors and their impact on prevention, screening, diagnosis, and management of disease using the examples of smoking and obesity, two of the most important yet modifiable risk factors for chronic disease and death among US women.

Effects of household composition and income security on body weight in working-age men

OBJECTIVE

Many recent studies have provided evidence suggesting that increases in body weight may spread via social networks. The mechanism(s) by which this might occur have become the subject of much speculation, but to date little direct evidence has been available. Building on evidence from economics, anthropology, and behavioral biology, within-household peers might influence body weight via implicit provision of income security was hypothesized.

DESIGN AND METHODS

Using a sample of 2,541 working-age men from the National Longitudinal Survey of Youth (1979), the effect of cohabitation on weight gain over a 6-year period was estimated. The potential confound caused by the joint determination of economic insecurity and cohabitation status with instrumental variables that exploit variation in local and state-level macroeconomic conditions and the presence of children in the home was addressed.

RESULTS

The marginal effect of cohabitation with adults on body weight is negative. Moreover, the magnitude of the effect is more than six times greater when the cohabitant is engaged in paid employment.

CONCLUSIONS

Income insecurity may play an important role in peer-to-peer transmission of weight gain.

Social contagion of mental health: evidence from college roommates

From a policy standpoint, the spread of health conditions in social networks is important to quantify, because it implies externalities and possible market failures in the consumption of health interventions. Recent studies conclude that happiness and depression may be highly contagious across social ties. The results may be biased, however, because of selection and common shocks. We provide unbiased estimates by using exogenous variation from college roommate assignments. Our findings are consistent with no significant overall contagion of mental health and no more than small contagion effects for specific mental health measures, with no evidence for happiness contagion and modest evidence for anxiety and depression contagion. The weakness of the contagion effects cannot be explained by avoidance of roommates with poor mental health or by generally low social contact among roommates. We also find that similarity of baseline mental health predicts the closeness of roommate relationships, which highlights the potential for selection biases in studies of peer effects that do not have a clearly exogenous source of variation. Overall, our results suggest that mental health contagion is lower, or at least more context specific, than implied by the recent studies in the medical literature.

Are network-based interventions a useful antiobesity strategy? An application of simulation models for causal inference in epidemiology

Recent research suggests that social networks may present an avenue for intervention against obesity. By using a simulation model in which artificial individuals were nested in a social network, we assessed whether interventions targeting highly networked individuals could help reduce population obesity. We compared the effects of targeting antiobesity interventions at the most connected individuals in a network with those targeting individuals at random. We tested 2 interventions, the first "preventing" obesity among 10% of the population at simulation outset and the second "treating" obesity among 10% of the obese population yearly, each in 2 separate simulations. One simulation featured a literature-based parameter for the network spread of obesity, and the other featured an artificially high parameter. Interventions that targeted highly networked individuals did not outperform at-random interventions in simulations featuring the literature-based parameter. However, in simulations featuring the artificially high parameter, the targeted prevention intervention outperformed the at-random intervention, whereas the treatment intervention implemented at random outperformed the targeted treatment intervention. Results were qualitatively similar across network topologies and intervention scales. Although descriptive studies suggest that social networks influence the spread of obesity, policies targeting well-connected individuals in social networks may not improve obesity reduction. We highlight and discuss the potential applications of counterfactual simulations in epidemiology.

Analysis of Friendship Network and its Role in Explaining Obesity

We employ Add Health data to show that friendship networks, constructed from mutual friendship nominations, are important in building weight perception, setting weight goals and measuring social marginalization among adolescents and young adults. We study the relationship between individuals' perceived weight status, actual weight status, weight status relative to friends' weight status and weight goals. This analysis helps us understand how individual weight perceptions might be formed, what these perceptions do to the weight goals, and how does friends' relative weight affect weight perception and weight goals. Combining this information with individuals' friendship network helps determine the influence of social relationships on weight related variables. Multinomial logistic regression results indicate that relative status is indeed a significant predictor of perceived status, and perceived status is a significant predictor of weight goals. We also address the issue of causality between actual weight status and social marginalization (as measured by the number of friends) and show that obesity precedes social marginalization in time rather than the other way around. This lends credence to the hypothesis that obesity leads to social marginalization not vice versa. Attributes of friendship network can provide new insights into effective interventions for combating obesity since adolescent friendships provide an important social context for weight related behaviors.

Peer effects in adolescent BMI: evidence from Spain

This paper extends the recent literature on the influence of peers on adolescent weight on three new fronts. First, based on a survey of secondary school students in Spain in which peers are formed by nominated classmate friends, we find a more powerful positive and significant causal effect of friends' mean BMI on adolescent BMI than previous US-based research. These results are in line with international data, which show that peer group contact tends to vary across countries. Our findings cover a large set of controls, fixed effects, the testing of correlated unobservables, contextual influences and instrumental variables. Second, social interactions are identified through the property of intransitivity in network relationships. Finally, we report evidence of a strong, positive effect of peer pressure on several subgroups of adolescents in an attempt to study their vulnerability to social influences.