Is Obesity Contagious??

     

Introduction

     While it is obvious that diseases like cold, AIDS and other STDs are spread through social networks, an interesting study reveals that the same may be true for obesity too!! Research conducted by the Framingham Heart Study, a longitudinal study focusing on health and weight, reveals that obesity tends to cluster in social networks. It is not surprising that obese people tend to from groups, but what's interesting is that the Framingham study  shows is if someone becomes fat in a given interval, their friends have an increased chance of becoming fat too! 

Reasons

     Possible reasons for this could be that friends may simultaneously adopt similar lifestyle choices such as diet, exercise or smoking, which could effect their weight. There could also be changing attitudes towards weight that could spread through social networks and make one more or less inclined to gain/lose weight because of social pressures. Similar effects were seen among siblings, where if one gained weight, another sibling is also likely to gain weight. The effects both among siblings and friends are strongest among same sex relationships. They also depend primarily on social distance, ie. closer friends have stronger impacts, and the effects appear to be independent of geographic distance.

Analysis Methods

   The Framingham Heart Study evaluated a densely interconnected social network of 12,067 people assessed repeatedly from 1971 to 2003. The body-mass index was available for all subjects. We used longitudinal statistical models to examine whether weight gain in one person was associated with weight gain in his or her friends, siblings, spouse, and neighbors.

Results

Figure 1

Figure 1 denotes the Largest Connected Subcomponent of the Social Network in the Framingham Heart Study in the Year 2000. Each circle (node) represents one person in the data set. There are 2200 persons in this subcomponent of the social network. Circles with red borders denote women, and circles with blue borders denote men. The size of each circle is proportional to the person's body-mass index. The interior color of the circles indicates the person's obesity status: yellow denotes an obese person (body-mass index, ≥30) and green denotes a nonobese person. The colors of the ties between the nodes indicate the relationship between them: purple denotes a friendship or marital tie and orange denotes a familial tie.

Figure 2 illustrates the spread of obesity between adjoining nodes in a part of the network over time.

Figure 3

Figure 3A characterizes clusters within the entire network more formally. To quantify these clusters, we compared the whole observed network with simulated networks with the same network topology and the same overall prevalence of obesity as the observed network, but with the incidence of obesity randomly distributed among the nodes (in what we call “random body-mass–index networks”). If clustering is occurring, then the probability that an alter will be obese, given that an ego is known to be obese, should be higher in the observed network than in the random body-mass–index networks. What we call the “reach” of the clusters is the point, in terms of an alter's degree of separation from any given ego, at which the probability of an alter's obesity is no longer related to whether the ego is obese. In all of the examinations (from 1971 through 2003), the risk of obesity among alters who were connected to an obese ego (at one degree of separation) was about 45% higher in the observed network than in a random network. The risk of obesity was also about 20% higher for alters' alters (at two degrees of separation) and about 10% higher for alters' alters' alters (at three degrees of separation). By the fourth degree of separation, there was no excess relationship between an ego's obesity and the alter's obesity. Hence, the reach of the obesity clusters was three degrees.

Figure 3B  indicates that the effect of geographic distance is different from the effect of social distance. Whereas increasing social distance appeared to decrease the effect of an alter on an ego, increasing geographic distance did not. The obesity of the most geographically distant alters correlated as strongly with an ego's obesity as did the obesity of the geographically closest alters. These results suggest that social distance plays a stronger role than geographic distance in the spread of behaviors or norms associated with obesity.

Figure 4

The extent of interpersonal association in obesity was evaluated with the use of regression analysis. The models account for homophily by including a time-lagged measurement of the alter's obesity. The possible role of unobserved contemporaneous events was evaluated by separately analyzing models of subgroups of the data involving various ego–alter pairings. Figure 4 summarizes the associations

Interpretation of Results

Discernible clusters of obese persons (body-mass index [the weight in kilograms divided by the square of the height in meters], ≥30) were present in the network at all time points, and the clusters extended to three degrees of separation. These clusters did not appear to be solely attributable to the selective formation of social ties among obese persons. A person's chances of becoming obese increased by 57%  if he or she had a friend who became obese in a given interval. Among pairs of adult siblings, if one sibling became obese, the chance that the other would become obese increased by 40% . If one spouse became obese, the likelihood that the other spouse would become obese increased by 37%. These effects were not seen among neighbors in the immediate geographic location. Persons of the same sex had relatively greater influence on each other than those of the opposite sex. The spread of smoking cessation did not account for the spread of obesity in the network.

Conclusion

Social network provides an important resource in treating obesity as well and social support groups could perhaps be a helpful strategy. It seems so human ecological to say it, but issues like obesity and other public health problems, need to be addressed on many levels, and the hierarchy of networks provides a model for how those levels interact. Researchers have found that obesity is socially contagious across three degrees of separation (so, for example, a friend of a friend who is obese also has an increased risk of obesity). 

So now you know what to keep in mind while making a new friend!!

References:

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