“Fat is catching” theory exposed
The social networking theory of obesity was skillfully debunked in this month’s issue of the British Medical Journal.
This theory first made the news last year with the release of a paper by Nicholas A. Christakis, M.D., Ph.D., MPH, a medical sociologist from Harvard Medical School, and James H. Fowler, Ph.D., political scientist from the University of California, San Diego. Their study was reported to have shown that you can “catch” obesity from having fat friends and that obesity is so contagious, it can be spread long-distance by email and instant messaging. Even healthcare professionals, who didn’t understand the etiology of true obesity or how statistics can be misused, failed to detect the implausibility of “second-hand obesity.” In fact, some doctors became so enamored with the new “science of networking” they believed it should be a new medical specialty: network medicine.
It’s been long understood that fears, beliefs and ideologies spread among people and social contacts. That’s the core to sales and marketing. There’s no need for a special theory to explain that! And, of course, communicable diseases can spread through contacts. But the notion that you can “catch” a physical trait — like chin dimples or obesity — or a health condition, like diabetes or cancer, from the people you associate with is implausible.
Professors Christakis and Fowler couldn’t give a biologically plausible explanation for their finding that long-distance friendships were more associated with obesity than immediate friends and neighbors, marriage partners, or living with a fat person. However, attempts to point out the flawed methodology used in that study, or to illustrate the fallacies of logic behind it, were called absurd and couldn’t break through the quick popular acceptance of this theory. It seemed to confirm what everyone “knew” — that obesity was spreading like an epidemic and all because of socially undesirable behaviors and attitudes. And obesity interests embraced the “profound policy implications of the study,” as it supported social change to address the obesity epidemic among entire groups of people and whole communities.
A social networking theory of contagious chin dimples might have been understood as implausible, but not so of obesity. While scientists have recognized for more than half a century that “the heritability of obesity is equivalent to that of height and greater than that of almost every other condition that has been studied,” as Dr. Jeffrey Friedman, head of the Laboratory of Molecular Genetics at Rockefeller University in New York, has explained, the science hasn’t broken through the simplistic notion that weight can be controlled proper diet and behavior.
Two researchers prove the flaw
Recognizing the implausibility of the social networking theory of obesity — as well as social networking increasingly being used to explain other implausibly related physical traits and conditions — Jason M. Fletcher, Ph.D., assistant professor at the Yale School of Public Health in New Haven, Connecticut, along with Boston economist, Ethan Cohen-Cole, Ph.D., designed an ingenious study. They selected conditions that no one would seriously believe were spread by social networking and online friendships: height, headaches and acne. They then applied the same standard statistical methods used in Christakis and Fowler’s social networking research to “find” that acne, height and headaches have the same “social network effect.”
Many methods used to estimate social network effects are subject to potentially large biases that result in the increased likelihood of detecting social network effects where none exists. For example, the use of standard econometric methods from literature on peer effects substantially reduces evidence of social network effects in obesity.
As they explained, patterns of association among people can lead to correlations in health conditions between friends that are not caused by direct social network effects at all. The problem of confounding factors plague correlations. For example, people usually choose to become friends with someone who is very similar to themselves. It is also commonly assumed that the variables a researcher selected to control for are the appropriate ones to isolate true network effects. If these problems are neglected, they wrote, “one can improperly interpret the results to imply that true ‘network effects’ exist.”
Noting bias in previous social networking research, the three health outcomes they examined (pimples, headaches and height) could not credibly be caused by social networking, they said. They used the National Longitudinal Study of Adolescent Health (Add Health) database of 4,300 and 5,400 male and female teens, which had followed the teens and their friendships over three waves from 1994 to 2002.
Using the methods common in recent medical literature for detecting “social network effects,” they found effects could be produced where none actually existed. The correlations were actually untenable [“fragile”], but large enough that they would popularly not be rejected as null, even though the true contagion effect is null.
They found increased relative risks of 58% for height, 62% for pimples, and 47% for headaches associated with the social network effect. These are similar, they said, to the 57% increased relative risk for obesity when a friend is obese and the 36% increased relative risk in quitting smoking when a friend quits that had been reported by Christakis and Fowler in their published social networking studies.
“Even truly implausible effects can generate results that support the hypothesis,” they said, and be used to generate premature claims of social network effects.
There is a need for caution when attributing causality to correlations in health outcomes between friends using non-experimental data. Confounding is only one of many empirical challenges to estimating social network effects.
You cannot “catch” fat from associating with a fat person anymore than you can catch tall from having a tall friend. There is no credible evidence.
© 2008 Sandy Szwarc