Gallup on Obesity Causes

Yesterday the Gallup organization recently released the results of some analysis they conducted using survey data from 139,000 Americans.  ​Here are their key results:

As is easy to see, obesity is correlated with a bunch of bad stuff: not exercising, not eating healthy, not having a dentist, being poor (as reflected in the "food struggles" question), and being depressed.  It's also correlated with at least one positive outcome: not smoking.  

Interesting correlations.  The problem are the inferences Gallup draws from these data.  Here are their recommendations:​

To reduce the costs associated with obesity, employers can start by helping employees improve on the behavior with the strongest link to obesity -- infrequent exercise. Employers can consider opening an office gym or offering gym membership discounts to incentivize frequent exercise and provide a safe place for employees to work out. Gallup research also finds that engaged employees exercise more frequently and also eat healthier than those who are not engaged or are actively disengaged. Therefore, employers who prioritize employee engagement may see a double benefit of healthier and happier workers.

​The problem is that their data support no such claims.  Does lack of exercise cause obesity? Yes, it probably has some role.  But, if you're already obese, chances are you're probably not much interested in exercising (i.e., it is probably the case that obesity is also causing a lack of exercise).  It's the same with many of the other issues in the above table.  Does obesity cause depression.  Or, does depression demotivate people to eat well and exercise, leading to obesity?  

There are a number of randomized-controlled-trial type studies that have been conducted looking at the effects of targeted interventions ​in the workplace.  Some appear to have some promise.  Many appear to have no long term impact.  That's the kind of research one would need to review and draw from to make the kind of recommendations Gallup does.  No matter how big the sample, we shouldn't interpret correlations to imply anything meaningful about the effectiveness of interventions by private companies or governments.     

Who to Blame for Obesity?

The journal Appetite ​just accepted a paper I wrote with Brenna Ellison at the University of Illinois.  The paper reports on a survey we conducted with about 800 Americans,  whom we asked who they though was primarily, somewhat, or not to blame for obesity.  

From the abstract:

Respondents were asked to place each of seven entities (food manufacturers,grocery stores, restaurants, government policies, farmers, individuals, and parents) into three categories: primarily, somewhat, and not to blame for the rise in obesity. Eighty percent said individuals were primarily to blame for the rise in obesity. Parents were the next-most blameworthy group, with 59% ascribing primary blame. Responses fell along three dimensions related to individual responsibility, agribusiness responsibility, and government-farm policy. A number of individual-specific factors were associated with perceptions of blame. For example, individuals with a more statist score on the economic political ideology scale were more likely to blame the government and agribusiness for obesity.

​Here are a few quotes from the literature-review section of the paper.

A criticism of the personal-responsibility perspective is that it can potentially lead to the stigmatization of the obese and result in depression and other psychological and physical problems . . .

yet, because research shows that the overweight have some of the most negative opinions about overweightedness . . .​

the very people purportedly being stigmatized are also among the same group of people responsible for the alleged stigmatizing.

and

Although individual-blame beliefs can produce adverse consequences related to stigmatization, less widely acknowledged is that viewing obesity as a result of a toxic food environment or other non-individual factors can lead to perceptions of victimization, which can be de-motivating and lead its own set of psychological problems. For example, Wang and Coups (2010) showed that individuals who felt genetics (a non-controllable factor) were a significant cause of obesity were less likely to exercise and eat fruits and vegetables as compared to those who felt individual lifestyle behaviors had “a lot to do” with causing obesity.

What 2000 Calories Looks Like

An entertaining video on how you can meet your recommended daily caloric ​intake.

The Making of the Obesitiy Epidemic

That was the title of this really interesting article by Helen Lee.

She starts with something I don't recall ever having previously read: ​researchers at meetings of the American Public Health Association hand-wringing over obesity - in 1952!

​Read the whole thing, but here is a bit that matches very closely with some of the major themes in my book The Food Police (coming out in only 2 weeks!)

. . . more than a few pundits, philanthropists, and advocates have homed in on the idea that the proliferation of fast, cheap, and unhealthy foods had a significant impact on the rise of obesity; that the industrialization and subsidization of agriculture had made foods artificially inexpensive, and food companies responded by supersizing and vastly expanding snack and beverage options. Like the tobacco industry before it, the food industry­­ was profiting by selling slickly marketed products that were dangerously addictive, particularly for the poor, who lacked grocery stores offering healthier food options. Much of the American public health and medical establishment came to believe that one of the most powerful ways to overcome the epidemic was to radically remake our school and neighborhood food environments­­, reducing­­ access to unhealthy foods and increasing access to healthy ones.

But in their rush to condemn corporate agribusiness, food marketers, and neighborhood food environments, public health advocates have too often allowed their policy and ideological preferences to race ahead of the science. This has fostered a reductive story about obesity that appeals to liberal audiences but doesn’t comport particularly well with much of what we know about why people choose to eat unhealthy foods, what the health consequences of being overweight or obese actually are, or why health outcomes associated with obesity are so much worse among some populations than others.

Against the current popular discourse, obesity is better understood as an unintended consequence of affluence than as a disease epidemic.

Do Scientists Mislead?

"Yes" seems to be the unfortunate conclusion that stems from this paper by Mark Cope and David Allison published in the International Journal of Obesity.  ​Scientists may not (or may) distort their own research findings, but Cope and Allison show, pretty convulsively, that there is a general pattern of distorting the findings of others.   

They attribute this to a "white hat bias":​

which we define to be bias leading to distortion of research-based information in the service of what may be perceived as righteous ends.

Cope and Allison found two studies related to soda consumption that:

had both statistically and non-statistically significant results on body-weight, body mass index (BMI) or overweight/obesity status which allowed future writers to potentially choose which results to cite, and were also widely cited, permitting quantitative analysis of citations.

​Then, they looked at how other scientists subsequently cited the findings in their published papers.  Did they focus on the negative findings (that soda doesn't affect weight, etc.) or the positive findings (that soda does affect weight, etc.): ​

The majority, 84.3% for [2] and 66.7% for [3], described results in a misleadingly positive way to varying degrees (i.e., exaggerating the strength of the evidence that [nutritively-sweetened beverage] reduction showed beneficial effects on obesity outcomes). Some were blatantly factually incorrect in their misleading statements, describing the result as showing an effect for a continuous obesity outcome whereas no statistically significant effect for continuous obesity outcomes was observed. In contrast, only four papers (3.5%) were negatively misleading (i.e., underplayed the strength of evidence) for [2] and none were negatively misleading for [3]. Only 12.7% and 33% of the papers accurately described complete overall findings related to obesity outcomes from [2] and [3], respectively.

​

They went on to document a similar pattern for studies on the effects of breastfeeding. They ​conclude:

Evidence presented herein suggests that at least one thing has been demonized ([nutritively-sweetened beverage] consumption) and another sanctified (Breastfeeding), leading to bias in the presentation of research literature to other scientists and to the public at large, a bias sufficient to misguide readers. Interestingly, while many papers point out what appear to be biases resulting from industry funding, we have identified here, perhaps for the first time, clear evidence that white-hat biases can also exist in opposition to industry interests.