Can traffic-light labels and better shelf positions help people make healthier decisions?

This article was originally published on The Psych Report before it became part of the Behavioral Scientist in 2017.

Over the last three decades obesity rates have doubled for adults and tripled for children. Today, over 35% of adults and 17% of children are considered obese, with the percentage of obese adults expected to rise to 50% by 2030.

The health risks and financial costs associated with obesity are well-documented, however, for both individuals and society, improving health and finding solutions for obesity has been anything but straightforward.

A recent survey found that nearly all American adults hope to improve at least one aspect of their dietary habits. The same survey, however, also found that about half of Americans felt their taxes were easier to understand than figuring out how to eat healthier food.

Recently, a group of researchers set out to see if people would indeed make healthier choices if making those choices were easier. A new study, published in the American Journal of Preventive Medicines, suggests they would.

At Massachusetts General Hospital, a team of researchers led by Anne Thorndike evaluated the long-term impact of two strategies designed to increase the likelihood of healthier food and beverage purchases in the hospital’s cafeteria. Thorndike and her team implemented a traffic-light label system for all food and drinks in the cafeteria (green = healthy, yellow = less healthy, red = unhealthy). In addition, they  placed healthier food and drink options in more prominent and accessible places on the shelf, in what is known as a choice architecture intervention.

Both the traffic-light labels and choice architecture intervention are based on the idea that simple changes to the environment in which food and drink choices are made can increase the likelihood that people will pick healthier options, even if the overall selection of food and drinks remains unchanged.

These healthier choices occurred without altering the selection of food and drinks available for purchase in the cafeteria.

In this case, the purpose of traffic-light labels was to convey the nutrition information of food and drinks simply and efficiently. Previous work has shown that lack of nutrition knowledge can lead to unhealthy decisions (1,2), and although standard nutrition labels present relevant information, not many would be able to use them to build a healthy meal (3). So, using the 2005 USDA My Pyramid* guidelines, the authors rated all food and drinks in the hospital’s cafeteria on five criteria: three positive (fruit or vegetable, whole grain, low-fat dairy or lean protein as the primary ingredient) and 2 negative (caloric count and saturated fat). Food and drinks with more positive than negative attributes were labeled green**, those with equal attributes were labeled yellow, and those with more negative than positive attributes were labeled red.

The purpose of the choice architecture intervention was to increase the visibility and accessibility of healthier food and drink choices. Previous research has shown that convenience and visibility play a large role in how people choose food (4,5). In this case, the authors placed green beverages and sandwiches at eye-level, while they moved red beverages and sandwiches to lower shelves. They also positioned healthier items, like salads, near less healthy ones, like pizza, and made bottled water available throughout the cafeteria.

The authors’ previous research at the cafeteria revealed that traffic-light labels and favorable placement of healthy options helped promote healthier choices for cafeteria customers and hospital employees over a six month time period (6,7). However, the question remained whether these healthy choices would persist over a longer period of time, or if patrons and employees would acclimate to the interventions and revert to their previous behavior. In the present study, Thorndike and her team analyzed the impact of the interventions after two years in order to answer this question.

Consistent with their previous work, Thorndike and her colleagues found significant increases in the proportion of healthy food and drinks purchased and significant decreases in the proportion of unhealthy food and drinks purchased at the cafeteria. For all cafeteria purchases, green items increased from 41% to 46%, while red items decreased from 24% to 21%. For cold beverages, which constituted about twenty-percent of the cafeteria sales, green increased from 52% to 60%, while red decreased from 27% to 18%. While these changes may seem small, they indicate a trend towards healthier buying habits for all users of the cafeteria.

To better understand how the interventions impacted frequent visitors to the cafeteria, Thorndike and her team analyzed the purchase behavior of over two-thousand hospital employees. The authors found a similar pattern of results: an increase in green purchases and a decrease in red purchases. Most striking, however, was the change in employee red beverage purchases, which decreased from 23% to 14%–a relative decrease of 39%. This means, after two years, employees purchased red beverages 39% less often than they did prior to the implementation of the interventions. Given the documented link between unhealthy beverages and obesity, these interventions could be crucial in reducing obesity and obesity-related diseases, such as heart disease and type 2 diabetes.

Employees at the hosptial purchased unhealthy beverages 39% less often than they did prior to the implementation of the interventions.

Furthermore, for employees, the authors observed the same trend of healthier food and beverage purchases over the two year time period, regardless of their age, gender, ethnicity, occupation, or full or part-time employment status.

It is important to note that these healthier choices occurred without altering the selection of food and drinks available for purchase in the cafeteria. In other words, patrons of the cafeteria, given the same choices, made healthier decisions when there was a simple labeling system in place and when healthier options were more prominent. Furthermore, sales data from the cafeteria showed that these changes occurred without a decrease in sales. In fact, the data show a slight increase in sales for the cafeteria.

It is also worthwhile to distinguish between what the study measured and what the study implies. The current study measured changes in how often people purchased healthy and unhealthy items, and not changes in actual health. Whether fewer calories were consumed or people lost weight as a result of the interventions was not studied. While the changes in purchase behavior are encouraging signs that health may have improved, further research is needed to clarify the impact of the purchase interventions on actual metrics of individual and community health.

Overall, the work of Thorndike and her colleagues highlights two possible interventions that have the potential to improve public health without diminishing individual choice or harming economic viability. Recall Mayor Bloomberg’s attempt to limit soda size to 16 ounces. His proposed law set-off a heated debate about the government’s role in public health. Some saw his actions as a positive step towards reducing obesity and improving health, while others saw his actions as an affront to freedom and democracy. Americans, especially those in public policy and public health, face a tough question: Is it possible to improve public health, while maintaining individual freedom?

In other words, is it possible for Americans to have their cake and it eat too? Thorndike’s work suggests it is possible. However, as the study reveals, Americans may not choose the cake.

*In 2011, the USDA replaced My Pyramid with My Plate
**”Water and diet beverages with 0 calories…were labeled green despite having no positive criteria.”

References (as cited in Thorndike et al. 2014)

1. Krukowski, R. A., Harvey-Berino, J., Kolodinsky, J., Narsana, R. T., & DeSisto, T. P. (2006). Consumers may not use or understand calorie labeling in restaurants. Journal of the American Dietetic Association, 106(6), 917-920. (Full Study)

2. Elbel B. Consumer estimation of recommended and actual calories at fast food restaurants. Obesity (Silver Spring). 2011 Oct;19(10):1971-8. (Full Study)

3. Rothman, R. L., Housam, R., Weiss, H., Davis, D., Gregory, R., Gebretsadik, T., … & Elasy, T. A. (2006). Patient understanding of food labels: the role of literacy and numeracy. American journal of preventive medicine, 31(5), 391-398. (Full Study)

4. Rozin, P., Scott, S., Dingley, M., Urbanek, J. K., Jiang, H., & Kaltenbach, M. (2011). Nudge to nobesity I: Minor changes in accessibility decrease food intake. Judgment and Decision Making, 6(4), 323-332. (Full Study)

5. Dayan, E., & Bar-Hillel, M. (2011). Nudge to nobesity II: Menu positions influence food orders. Judgment and Decision Making, 6(4), 333-342. (Full Study)

6. Thorndike, A. N., Sonnenberg, L., Riis, J., Barraclough, S., & Levy, D. E. (2012). A 2-phase labeling and choice architecture intervention to improve healthy food and beverage choices. American Journal of Public Health, 102(3). (Full Study)

7. Levy, D. E., Riis, J., Sonnenberg, L. M., Barraclough, S. J., & Thorndike, A. N. (2012). Food choices of minority and low-income employees: a cafeteria intervention. American Journal of Preventive Medicine, 43(3), 240-248. (Full Study)