Obesity

Obesity Epidemic?

Today on Slate there is a nice little GIF (that originally appeared on The Atlantic) that shows how obesity rates have changed over time by state. Slate seems to suggest that the geographic progression of obesity rates might indicate some sort of social contagion. But, ss many others (and here) before me have pointed out, we have to be very careful when trying to draw inferences about social contagion. If we take a look at a map of household income by state, we see that there is a lot of overlap between the poorest states and those with the highest obesity rates.

Household Income

There are lot's of potential causal connections here. For example, income might affect the types of stores and restaurants available, which in turn affects obesity rates. For a more careful look at some data on the social contagion of obesity, have a look at our paper that examines obesity rates, screen time, and social networks in adolescents.

 

As a side note, it's interesting to compare the map of the "obesity epidemic" to a map of something we know spreads through person to person contagion, like the swine flu (image from the New York Times).

H1N1

Unlike the obesity epidemic, swine flu jumps all over the place, which obviously has to do with air travel.

in Contagion / Modeling / Networks / Research  by pj 1 comments

New paper on social contagion of obesity

Along with a team of researchers led by epidemiologist David Shoham from Loyola University, I recently published a paper in PLoS One examining the social contagion of obesity. As many of you know, this is a hotly debated topic of research that was kicked off by work of James Fowler and Nicholas Christakis published in the New England Journal of Medicine.  (See this post for my two cents on the debate.) The central criticism of this research surrounds the issue of separating friendship selection from influence, which in some sense was laid to rest by Cosma Shalizi and Andrew Thomas.

One alternative approach is to use a "generative model," which is exactly what my coauthors and I do. Specifically, we use the SIENA program developed by Tom Snijders and colleagues. Essentially, this model assumes that people make choices about their friendships and behavior just like economists and marketers assume people make choices about where to live or what car to buy.

In our paper, we apply the model to data from two high schools from the AddHeath study. We use the model to understand social influences on body size, physical activity, and "screen time" (time spent watching TV, playing video games, or on the computer). In short, here's what we find:

  • In both schools students are more likely to select friends that have a similar BMI (body mass index), that is there is homophily on BMI.
  • In both schools there is evidence that students are influenced by their friends' BMI.
  • There is no evidence for homophily on screen time in either school, and there is evidence that students are subject to influence from their friends'  on screen time in only one of the two schools.
  • In one of the two schools there was evidence for homophily on playing sports, but in both schools there was evidence that students influenced their friends when it comes to playing sports.
in Contagion / Modeling / Networks / Research  by pj 1 comments

The Christakis and Fowler Social Networks Influence Brouhaha

Recently there has been a spirited conversation kicked off by the publication of an article, "The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis," by Russell Lyons regarding the well-publicized work of Nicholas Christakis and James Fowler on social contagion of obesity, smoking, happiness, and divorce.  The discussion has been primarily confined to the specialized circle of social network scholars, but now that conversation has spilled out into the public arena in the form of an article by Dave Johns in Slate (Dave Johns has written about the Christakis-Fowler work in Slate before).  Christakis and Fowler's work has received a huge amount of attention, appearing on the cover of the New York Times magazine, on the Colbert Report TV program, and a ton of other places (see James's website for more links).  Many others have made detailed comments on Lyon's article and on the original Christakis-Fowler papers.  I wish to address some of the related issues raised in Slate about scientists in the media

The article seems to criticize Christakis and Fowler for their media appearances, as though this publicity is inappropriate for scientists who should be diligently but silently working in the background, leaving it up to policy makers and the media to make public commentary and recommendations.  I think this criticism is not only wrong, but dangerous.  Many if not most researchers do work silently in the background, shunning the spotlight and scrutiny of the media, not out of shyness or fear of embarrassment, but because of a pervasive misunderstanding of scientific uncertainty.  Hard science is simply much softer than many people realize.

ALL scientific conclusions — from physics to sociology come with uncertainty (this does not apply to mathematics, which is actually not a science).  A "scientific truth" is actually something that we're only pretty sure is true.  But we'll never be definitely 100% sure, that's just how science works.  When one scientist says to another, we have observed that X causes Y, it is understood that what is meant is, the probability that the observed relationship between X and Y is due to chance is very small.  But, statements like that don't make for good news stories.  Not only are they uninteresting, but for most people they're unintelligible (which is not to say that the public is stupid — the concepts of uncertainty and statistical significance are extremely subtle and often misunderstood even by well-trained scientists).  So, many scientists avoid the media because we're asked to make definitive statements where no definitive statements are possible, or we make statements that include uncertainty that are ignored or misunderstood.

But we need scientists in the media.  Only a fraction of Americans believe the planet is warming and 40% of Americans believe in creationism.  Scientists in the media can help correct these misperceptions and guide public policy.  And, maybe even more importantly, scientists in the media can make science sexy.  We already live in a world where science and politics are often at odds, and in which scientists that avoid the media are often overruled by politicians that seek it out.  Scientists are already wary of making public statements that implicitly contain uncertainty for fear of them being interpreted as definitive. Christakis and Fowler have done us a great service by taking the risk of making statements and recommendations in the public arena based on the best of their knowledge, by raising public awareness of the science of networks, and by making science fun, interesting, and relevant.

in Contagion / Networks / Research  by pj 2 comments