Is Obesity Caused by Calorie Underestimation? A Psychophysical Model of Meal Size Estimation

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Key Takeaways

Pierre Chandon and Brian Wansink

Executive Summary
Sixty-five percent of U.S. adults are either obese or overweight. Many policy makers and concerned consumer groups have alleged that this epidemic is being fueled by a combination of increasing portion sizes in restaurant meals coupled with a virtual absence of intuitive understanding that larger portions contribute more calories. Indeed, a large body of research in nutrition and epidemiology has shown that overweight people are more likely to underestimate their food intake than regular-weight people. Because of the scale of this issue, the food industry in general and fast-food restaurants in particular are being increasingly threatened by litigation, taxes, and restrictions that promise to make it "the tobacco industry of the new millennium." The general questions being asked are, Is obesity really caused by the underestimation of the number of calories contained in large fast-food meals? and What can policy makers, food companies, and health professionals do about it?

In this research, the authors develop and test a psychophysical model of meal size estimation and use it to show that the association between body mass and biases in calorie estimations is a spurious consequence of the tendency of overweight people to consume larger meals. In three laboratory studies and in one field study, the authors find that meal size estimations follow a compressive power function of actual meal size. In other words, these estimations exhibit diminishing sensitivity to meal size changes as the size of the meal increases. They further show that the estimations of people with a low and a high body mass index (BMI) follow the exact same psychophysical function, whether they are made before or after intake, for self-selected or randomly selected meals. As a result, the estimations of low- and high-BMI people are identical, after the size of the meal is controlled for or after the natural association between meal size and body mass is eliminated. Calorie underestimation is caused by meal size, not by body size.

The authors also test two other predictions derived from the psychophysical model. The first prediction is that a piecemeal decomposition estimation procedure should reduce psychophysical biases because it replaces the estimation of a whole meal (a large quantity, which is likely to be underestimated) with multiple estimations of the size of each component of the meal (smaller quantities, which are likely to be more accurately estimated). As predicted, the authors find that the piecemeal decomposition estimation reduces psychophysical biases not only among regular consumers but also among certified dieticians. In comparison, a common debiasing manipulation—informing consumers about the bias and motivating them to be accurate—does not improve people’s sensitivity to meal size changes (though it leads to a general increase in calorie estimations). The second prediction is that when a representative sample of consumers and consumption occasions is surveyed, the mean estimated consumption is lower than the mean observed consumption. This prediction is derived from the nonlinear shape of the psychophysical function, which leads to stronger underestimations of large quantities than overestimations of small quantities. This prediction explains why most studies, which use a representative sample, find an average underestimation bias, whereas the few studies focusing on small consumption magnitudes (e.g., studying children or low-BMI people) find an average overestimation bias.

The final analyses address the public health implications of psychophysical biases in meal size estimations by studying the estimations, forecasts, and consumption decisions of professional dieticians. The authors find evidence that psychophysical biases affect even highly educated expert dieticians, though to a lesser extent than regular consumers. More worryingly, they find that dieticians inaccurately expect that high-BMI people underestimate meal size compared with low-BMI people. Finally, the authors find that a piecemeal decomposition also improves dieticians’ own calorie estimations, which leads them to select smaller fast-food meals.

Pierre Chandon is Assistant Professor of Marketing at INSEAD, Fontainebleau, France, which he joined in 1999. In 2005–2006, he was Visiting Assistant Professor of Marketing in the Wharton School at University of Pennsylvania, and in 2004–2005, he was Visiting Assistant Professor of Marketing in the Kellogg School of Management at Northwestern University. Pierre Chandon holds a PhD in Marketing from HEC Paris and an MBA from ESSEC. Professor Chandon’s research focuses on how estimation and perceptual biases influence food consumption decisions, attention and consideration decisions at the point of purchase, and the validity of marketing surveys. He has published articles in leading academic journals, including Journal of Marketing Research, Journal of Marketing, and Journal of Consumer Research. He is a member of the editorial boards of Journal of Marketing and of Recherche et Applications en Marketing, the journal of the French Marketing Association. In 2003, he won the Stellner Distinguished Scholar Award for his achievements and contributions to the field of marketing. In 1998, his dissertation won the Best Interdisciplinary Dissertation Award, given by the Foundation HEC. Pierre Chandon teaches Marketing Management and Brand Management in the MBA, executive MBA, and in various open-enrolment and company-specific executive education programs. His multimedia case "Unilever in Brazil, Marketing Strategies for Low-Income Consumers" won the 2004 EFMD Best Marketing Case Award. His work has been the subject of media coverage in Europe and the United States by, among others, ABC 20/20, International Herald Tribune, France Inter, L'Expansion, Les Echos, Le Figaro, and Marketing News.

Brian Wansink is John S. Dyson Chair of Marketing and of Nutritional Science in the Applied Economics and Management Department at Cornell University. Brian Wansink’s teaching and research interests are on how advertising, packaging, and personality traits influence the usage frequency and usage volume of healthy foods. Along with more than 75 journal articles, he has written the books Marketing Nutrition, Consumer Panels, Asking Questions, and Mindless Eating. In addition to being a professor, he is the director of the Cornell Food and Brand Lab, which focuses on the psychology behind what people eat and how often they eat it. A primary focus of the lab is in helping companies develop "win–win" ways in which they can help people eat more nutritiously and better control how much they eat. The lab’s work has won national and international awards for its relevance to consumers. His research has been widely featured on 20/20, BBC News, The Learning Channel, and all news networks and has appeared multiple times on the front pages of The Wall Street Journal and The New York Times.

Journal of Marketing Research, Vol. XLIV, No. 1, February 2007
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