What drives ingredient-based food fears?

That was the question asked in this article just published in the journal Food Quality and Preference.  The authors, Brian Wansink, Aner Tal, and Adam Brumberg surveyed over 1,000 mothers to study which food ingredients they found fearful, and they consider how such fears can be alleviated.  

The abstract:

“This study investigates food fears that are ingredient-based, focusing on the case of high-fructose corn syrup. The results of a national phone survey of 1008 U.S. mothers offer five preliminary sets of observations: first, consumers with a fear of a specific ingredient – such as high-fructose corn syrup – may exaggerate and overweigh perceived risks. Second, such consumers may often receive more information from the internet than from television. Third, they may be partly influenced by their reference group. Fourth, ingredients associated with less healthy foods mainly hurt evaluation of foods perceived as relatively healthy. Fifth, food fears may be offset when an ingredient’s history, background, and general usage are effectively communicated. These findings suggest new insights for understanding how public health, industry, and consumer groups can more effectively target and address ingredient fears.”

From the conclusions:

“When health risks exist, food fears are merited. In other cases, ingredient fears and avoidance may be wrongly based on the stigmatization of an ingredient or on misinformation. These results offer new preliminary insights about who is most prone to ingredient avoidance, where they receive their information, what types of ingredients are most susceptible to being feared, and how fears might be mitigated.

There appear to be at least two non-mutually exclusive motivating factors behind ingredient avoidance. First, some individuals may overweigh the perceived risks of the avoided ingredient. Second, some individuals who avoid ingredients may have a greater need for social approval among their reference group than those with a more moderate view (though such effects were small in our sample). This is a key contribution to the literature on risk because it underscores a novel potential motivation – akin to the Prius Effect – behind ingredient avoidance. ”

Hypothetical bias - Catcher in the Rye edition

Economists tend to be skeptical of the answers people give on surveys - of people's stated preferences.  It's what we do that drives economic outcomes and well-being.  The trouble is that what we say on surveys often diverges from what we do when shopping.  The standard research finding is that, on average, people say on surveys that they are willing to pay about 2.5 times what they will actually pay when real money is on the line - a phenomenon referred to as hypothetical bias.  I've spent a lot of my career trying to devise survey techniques that get closer to the truth and I think we've made progress, but caution is warranted.

A lot of the research on hypothetical bias started in the 1980s and 90s when survey techniques started being more widely used to ask people to state their willingness-to-pay for environmental amenities.  Thus, you can might imagine my surprise when, recently re-reading Catcher in the Rye (published in 1951) the last chapter contained this clear, concise insight on hypothetical bias. 

A lot of people, especially this one psychoanalyst guy they have here, keeps asking me if I'm going to apply myself when I go back to school next September. It's such a stupid question, in my opinion. I mean how do you know what you're going to do till you do it? The answer is, you don't. I think I am, but how do I know? I swear it's a stupid question.

Does information on relative risks change concerns about growth hormones?

Consumers often express concern about the use of growth promotants in animal agriculture.  In the beef industry, various growth hormones are administered to cattle to improve and speed the rate of growth (and some would say, improve the sustainability of beef production).  Upwards of 90% or more of feedlot cattle in large feedyards are given hormone implants.

Some consumers are fearful about the safety effects.   For example, the EU has banned imports of hormone-treated cattle from the US for over 20 years (a policy which probably has more to do with protectionism than actual safety concerns).  Other people have argued that these are the cause of decreasing puberty age of girls (which the data doesn't support).

As a result, many in the beef industry have have tried to communicate the fact that the risks from hormones are small to non-existent, and are much smaller than the risks from hormones in everyday foods.  The normal comparison is between how much estrogen is in a hamburger from an implanted steer or heifer vs. the amount of estrogen in other foods like soybean oil or cabbage.  Examples of such discussions appear at BeefMyths.org, US Meat Export Federation, the NCBA, and extension facts sheets from Michigan State University, University of Nebraska, University of Georgia, and many others.

Circulating on the web a while back were some discussions of using some visual strategies to communicate the relative risks from estrogen used in cattle implants.  For example, here is one blog discussing the use of M&Ms to convey the risks.  

The question I wanted to know is whether any of these sorts of communications actually has any impact on the people for whom it is intended.  

In the most recent issue of my monthly Food Demand Survey (FooDS), we sought to address this issue.  1,017 respondents were randomly allocated to one of three information groups or treatments.  In the first no-info group, respondents were simply told, “About 90% of feedlot cattle are given added growth hormones to improve the rate of growth.” And then, respondents were asked, “How concerned are you about the use of growth hormones in beef production?”  

For the second group text-only group, written text was added to convey relative risks of hormone use.  Prior to being asked level of concern, subjects were told, “About 90% of feedlot cattle are given added growth hormones to improve the rate of growth.  The added hormones add about 3 extra nanograms (a billionth of a gram) to a 3 oz serving of beef.  For comparison purposes, the amount of estrogen that naturally occurs in 3 oz of the following foods is: potatoes (225 nanograms), peas (340 nanograms), cabbage (2,000 nanograms), soybean oil (170,000 nanograms).”  

Finally, the third visual+text group was given the same written text but was also shown the above visual illustration using M&Ms allocated to different jars.  

Participants in all three groups answered with their level of concern on a five-point scale (1 = very unconcerned; 5=very concerned).

Information on relative risks caused a small but statistically significant reduction in the level of concern.  The mean levels of concern, on the 5-point scale, were 3.93, 3.71, and 3.66 for the no-info, text-only, and text+visual information groups.  

Without any information on relative risks, over 71% of respondents indicated that they were either concerned or very concerned.  Textual information reduced that frequency to 66%, and visual+text information further reduced the percentage of concerned respondents to 63.6%.   

What we think about a label may be as important as the label itself

What believe about a food's ingredients may have a biological effect on our bodies above and beyond the actual nutrient content.

That is the conclusion from a study published in the journal Health Psychology, which was recently covered by Alix Spiegel at the NPR Health blog.

The authors conducted an experiment in which they fed the same 380 calorie milk shake to two different groups of subjects.  The first group was lied to, and were told (via a label) that the shake was a "sensible" 140 calories.  The second group was also lied to, but in the opposite manner: they were told (via a label) that the shake was an "indulgent" 620 calories.  

The researchers measured the levels of a hormone, ghrelin, before during and after the label experiment.  Ghrelin levels are particularly interesting to monitor because they regulate metabolism and help signal hunger or satiety.  After eating a big meal, ghrelin levels fall, signalling us to stop eating.  Eat a light meal, and ghrelin levels remain high, signaling us to eat more.

The authors found that people consuming the "indulgent" labeled shake experienced a significant increase in ghrelin just before consumption (in anticipation) and then a significant decline in ghrelin after consumption.  The change, the authors argue, is consistent with that typically observed after eating a big meal.  By contrast, the level of ghrelin was flat before and after eating the "sensible" shake.   All this is in spite of the fact that the two shakes were exactly the same in every way except for the labels!  

The authors were quoted as saying:

Labels are not just labels; they evoke a set of beliefs

and that labels might

actually affect the body's physiological processing of the nutrients that are consumed.

One way to interpret the results is to place them in the category with other "behavioral biases" in the behavioral economics literature: another piece of evidence that people do not behave rationally.  I see it a bit differently.  The results suggest a kind of "extra" rationality.  Mind over matter.  What we think might well trigger how our body responds.  Marketers might influence what we think about foods, but we have some control over the process too.  

Now, if I can just fool myself into believing that small lunch salad is actually one of the Carl's Jr. "Indulgent Salads", I'll feel fuller and lose more weight! 

The study's sample size was small (N=46), probably because to measure ghrelin they had to insert an intravenous catheter to draw blood at repeated intervals.  So one proceed with caution until more work of this sort is done.  Still, very interesting nonetheless.

Effects of restaurant menu labels

Brenna Ellison, David Davis, and I have a paper forthcoming in the journal Economic Inquiry and that is finally available online.

Here's are the study objectives:

The overall purpose of this research is to perform an in-depth examination of menu labeling and pricing policies in a full-service, sit-down restaurant. Specifically, this research determines: (1) whether caloric labels in a fullservice restaurant influence food choice, (2) whether symbolic calorie labels are more/less influential than numeric calorie labels, (3) how effective menu labels are relative to “fat taxes” and “thin subsidies” at reducing calories ordered, and (4) the economic value of menu labels.

Our projections of the short-run effects of different policies (numeric label, symbolic label, 10% tax on high calorie items, or 10% subsidy on low calorie items) on the number of calories ordered at the restaurant we studied are as follows:

The only policy option which resulted in a statistically significant change in calories (where the 95% confidence interval on the change didn't include zero) was a "symbolic" calorie label - essentially a traffic light label with a red dot next t the highest calorie items, a yellow dot next to medium calorie items, and a green dot next to lowest calorie items.  We put the point estimate on the value of the symbolic label at about $0.13/person/meal.

It is important to note that the symbolic label policy option was also the one that had the most detrimental effect on restaurant revenues (these results are in Brenna's dissertation).  Also, curiously enough, Brenna's surveys suggest most people say they don't want the symbolic label.  Here's what we wrote in a different paper discussing a post-meal survey conducted with some of the diners:

Interestingly, despite the calorie+traffic light label’s effectiveness at reducing calories ordered, it was not the labeling format of choice. When asked which labeling format was preferred, only 27.5% of respondents wanted to see the calorie+traffic light label on their menus. Surprisingly, 42% preferred the calorie-only label which had virtually no influence on ordering behavior.