To examine the effects of calorie labeling on food selection and intake in dieters and non-dieters, and to explore whether expectations about food healthfulness moderate these effects.
Participants were presented with a menu containing two items, a salad and a pasta dish. The menu had (a) no calorie information, (b) information that the salad was low in calories and the pasta was high in calories, (c) information that the salad was high in calories and the pasta was low in calories or (d) information that both were high in calories (study 2 only).
Calorie labels influenced food selection for dieters, but not for non-dieters. Dieters were more likely to order salad when the salad was labeled as low in calories and more likely to order pasta, even high-calorie pasta, when the salad was labeled as high in calories. Participants who chose high-calorie foods over low-calorie foods did not eat less in response to calorie information, although non-dieters reduced their intake somewhat when calorie labels were put in the context of recommended daily calories.
The results suggest that the rush to provide calorie information may not prove to be the best approach to fighting the obesity epidemic.
Although the percentage of overweight Americans has remained relatively constant over the last 30 years, rates of obesity have increased dramatically. Roughly one-third of Americans are overweight and another third are obese.1 In contrast, between 1976 and 1980, roughly one-third of Americans were overweight, but only 15% were obese. This increase in obesity is a public-health concern owing to the link between obesity and serious medical conditions, such as type 2 diabetes, heart disease and certain types of cancer.2
One proposed contributor to the rise in obesity rates is the increased frequency with which people eat at restaurants.3 The number of meals eaten outside the home has increased dramatically during the same time period in which obesity rates have risen,4 and eating frequently in restaurants has been linked to weight gain,5, 6, 7, 8 possibly because people eat more calories when they eat out than when they eat at home.9 There is a lack of consistency, however, in the association between eating in restaurants and weight gain, with some studies showing that eating in restaurants is linked to higher weight in men but not women,10, 11 some studies showing that eating in fast-food restaurants, but not full-service restaurants, is associated with higher weight,6, 7 and some showing no association between eating out and weight.12
In an attempt to combat obesity, menu-labeling legislation has now been passed as part of the health-care bill in the United States.13 (A similar bill has recently been proposed in Ontario, Canada). The United States legislation will require all chain restaurants with >20 outlets to provide information about calories next to each item on the menu. A succinct statement concerning suggested daily caloric intake must also be posted.
The assumption behind this legislation appears to be that providing individuals with calorie information will lead them to reduce their caloric intake, and that weight loss will follow such reduced intake. Reduced caloric intake, however, is only one of several possible outcomes. Some people may not even notice the caloric information; others may not care about the calorie information and may ignore it. Among people who do care about calorie information, various responses are possible if the food that they plan to eat is high in calories: they could choose a lower-calorie meal or they could choose to eat less of the original higher-calorie meal. Another possibility is that customers may discover that the high-calorie items that they crave are not that much higher in calories than are the lower-calorie items, and so, given that the lower-calorie choice does not represent much of a savings, they may decide to go for the higher-calorie, more attractive option. Unfortunately, most menu-labeling studies have examined the effects of calorie information on ordering behavior (that is, effects of labeling on item selection), but have failed to measure amount eaten. As it is entirely possible for people to change their orders without altering the total calories that they ingest, or to eat fewer calories without changing their orders, it is not possible, without measuring the amount eaten, to determine whether caloric labeling actually decreases caloric intake.
Only three studies to date have examined the effects of calorie information on amount eaten, and just two of these examined both calories ordered and amount eaten. Findings from Aaron et al.14 and Harnack et al.15 suggest that calorie information may have little effect on the amount that females eat, and may actually increase the males' intake. In contrast, findings from Roberto et al.16 indicate that calorie information may reduce the amount eaten by both males and females. Interestingly, the increased intake of male participants in Harnack et al.15 was not accompanied by an increase in the number of calories ordered, whereas the decreased intake in Roberto et al.16 was accompanied by a decrease in calories ordered.
In light of these contradictory findings, further research examining the impact of caloric labeling on food selection and intake is clearly warranted. One aspect of caloric labeling that has yet to be explored is whether expectations about the healthfulness of foods moderate the impact of caloric labels. It is conceivable that calorie information affects food selection only when the calorie information does not match expectations. For example, restaurant patrons may be surprised to discover that a salad is high in calories, and this information may dissuade them from ordering the salad, whereas finding out that a plate of pasta is high in calories may come as no surprise and thus fail to alter ordering behavior. By the same token, patrons may be more likely to order ‘unhealthful’ foods when these foods are lower in calories than expected. Therefore, examining whether calorie information affects ordering or intake of ‘healthy’ vs ‘unhealthy’ foods differently might resolve some of the ambiguity in the previous findings.
The present research examined the effects of calorie information on food selection and intake in restrained and unrestrained eaters. The relation between calorie information and eating behavior was explored both for foods that match expectations (for example, low-calorie ‘healthy’ foods) and for foods that do not match expectations (for example, high-calorie ‘healthy’ foods).
Study 1 was designed to examine whether providing calorie information alters food selection of healthy and less healthy food (salad and pasta), and if so, in whom (all eaters, or only in restrained eaters/chronic dieters). Study 1 was also designed to examine whether providing calorie information (that the menu item contains 600 or 1200 calories) alters the amount of salad or pasta eaten.
Participants and methods
Participants were 149 female students enrolled in the introductory psychology subject pool. The mean age of participants was 19.11 (s.d.=1.82). The Restraint Scale17 was used to categorize participants as restrained eaters (scoring 15 or higher) or unrestrained eaters (scoring below 15).
In order to standardize hunger levels, all participants were told to refrain from eating for 3 h before participating in the study. After consenting to participate in the study, participants were told that they would be rating a potential new menu item for a local restaurant. They were presented with a menu containing two items, a salad and a pasta dish, each with a short description. The salad consisted of cucumber, carrot, tomato, avocado and cheddar cheese mixed with an oil-and-vinegar dressing. The pasta dish consisted of rotini mixed with commercial pasta sauce and mozzarella cheese. The two dishes contained the same number of calories (approximately 1200 per serving) and the same energy density (1.6 calories per gram), but the information provided to participants about the content of each dish was varied across conditions.
In the control condition (no calorie information), there was no additional information on the menu beyond the following descriptions: House salad—crunchy cucumbers, shredded carrots and diced tomato tossed with fresh cheddar and avocado in our signature house dressing and Pasta Marinara—rotini tossed with our signature marinara sauce and topped with fresh mozzarella. In the first experimental condition (low-calorie salad/high-calorie pasta), the same ingredient information was presented as in the control condition, but the salad was described as containing 600 calories and the pasta was described as containing 1200 calories. In the second experimental condition (high-calorie salad/low-calorie pasta), the salad was described as containing 1200 calories, whereas the pasta was described as containing 600 calories.
Participants were told that they should select either the salad or the pasta for lunch. While waiting for the food to be prepared, participants filled out several questionnaires. After the food was served, participants were given 15 min to complete their meal and to fill out a short taste-rating form. The experimenter instructed participants to approach the meal as they would a meal in an actual restaurant rather than as merely a taste test.
After eating, participants were asked to fill out a series of questionnaires including the Restraint Scale.17 In order to probe for suspicion or to determine whether the participant was able to guess the actual purpose of the study, participants were asked what they thought the true purpose of the study was before they were debriefed.
Means and s.d. for food chosen are presented in Table 1. To examine whether calorie information altered food selection, we conducted a binary logistic regression with Condition, Restraint and Condition × Restraint as the independent variables and food selected (pasta vs salad) as the dependent variable. A main effect was found for Restraint, X2(1)=4.39, P=0.036, with unrestrained eaters being more likely to choose pasta than were restrained eaters. No Condition, X2(2)=2.34, P=0.31, or Condition × Restraint, X2(2)=0.67, P=0.72, effects were found.
Notwithstanding these insignificant findings, Table 1 shows that restrained eaters in the low-calorie salad/high-calorie pasta condition chose salad more often than pasta whereas participants in all other conditions chose pasta more often than salad. Indeed, restrained eaters in the low-calorie salad/high-calorie pasta condition were much more likely to choose salad instead of pasta than was a pooled group of all other study participants, X2(1)=6.44, P=0.011.
Means and s.d. for calories eaten are presented in Table 2 and Figure 1. To examine whether calorie information affected the amount of salad or pasta that participants ate, we conducted a Condition × Food Chosen × Restraint analysis of variance with calories eaten as the dependent variable. A Kolmogorov–Smirnov test indicated that the calorie data fit a normal distribution, Z=0.730, P=0.662, and Levene's test indicated that variance was equal across groups, F(11,135)=4.10, P=0.95. A main effect of Food Chosen, F(1,135)=4.41, P=0.038, and a Condition-by-Food Chosen interaction, F(2,135)=4.80, P=0.01, were found. Participants who chose pasta ate more than those who chose salad in the no calorie information condition (P<0.001), but amount eaten did not differ between those who chose pasta and those who chose salad in the other two conditions. In addition, among participants who chose salad, those in the no calorie information condition ate less than did those in the high-calorie salad/low-calorie pasta condition (P=0.029).
Calorie information influenced food selection among restrained eaters, but not among unrestrained eaters. It appears that participants generally preferred pasta to salad, but that restrained eaters set aside this preference and tended to order salad when they thought that the pasta was much higher in calories than the salad.
With regard to amount eaten, the provision of accurate calorie information did not alter intake for participants who chose pasta. Among participants who chose salad, however, those who received no calorie information ate much less than those who received accurate calorie information. Expectations about the healthfulness of salad and pasta may account for these findings. Pasta is not generally viewed as a low-calorie food, so it is likely that participants who chose pasta expected it to be high in calories regardless of whether or not they received calorie information. As these participants were willing to choose a high-calorie option in the first place, they were probably not overly concerned with restricting the amount they ate. On the other hand, participants who chose salad after receiving no calorie information may have done so because they were interested in eating lightly and believed that the salad was a low-calorie option. The same interest in eating lightly may also have also been the reason that they ate a relatively small amount. In contrast, participants who chose salad after being informed that it contained 1200 calories probably did not order salad in order to eat lightly, but rather because they especially enjoy salad. Thus, these participants probably ate the amount they desired rather than attempting to restrict their intake.
There were several limitations of the study that may have influenced the results. First, although menu-labeling legislation requires that a statement indicating suggested daily intake be posted on the menu or menu board, no such statement was included on our study menu. It is possible that calorie information has a different effect on food selection and eating behavior when such information is put in the context of a daily calorie allotment. Second, men were not included in the study, so it is not possible to determine whether men respond differently to calorie information than do women.
Study 2 was designed to address these limitations and to extend the findings of study 1. To better simulate menu labeling as it is described in the current legislation, a menu condition was added in which suggested daily calorie intake was included on the menu. In addition, both males and females participated in study 2 so that potential sex differences in response to caloric labeling could be explored. Furthermore, the label for the lower calorie food was changed from 600 to 400 calories to ensure that participants viewed this as a truly low-calorie option. The analyses for amount eaten were also altered; rather than examining the effects of food choice (salad vs pasta) on amount eaten as was done in study 1, amount eaten was examined as a function of whether participants received no calorie information, calorie labels or calorie labels plus information about recommended daily caloric intake to determine the effects of labeling per se.
Participants and methods
Participants were 254 undergraduate students (138 females and 116 males) enrolled in the introductory psychology subject pool. The mean age of female participants was 18.69 (s.d.=2.87) and the mean age of male participants was 18.71 (s.d.=1.79). As in study 1, the Restraint Scale17 was used to categorize participants as either restrained eaters or unrestrained eaters.
The procedures used in study 2 mirrored those in used in study 1. The descriptions for salad and pasta were also identical to those from study 1, however, the calorie information provided for each menu condition was altered for study 2.
In the control condition, no calorie information was included on the menu. In the first experimental condition (low-calorie salad/high-calorie pasta), the salad was described as containing 400 calories and the pasta dish was described as containing 1200 calories. In the second experimental condition (high-calorie salad/low-calorie pasta), the salad was described as containing 1200 calories and the pasta dish was described as containing 400 calories. In the final experimental condition (high-calorie salad/high-calorie pasta), both the salad and the pasta were described as containing 1200 calories, and the recommended caloric intake of the average male and female was presented at the bottom of the menu (2000 calories for females and 2400 calories for males).
Means and s.d. for food chosen are presented in Table 3. As in study 1, female restrained eaters in the low-calorie salad/high-calorie pasta condition were more likely to choose salad/less likely to choose pasta than a pooled group of all other study participants (P=0.027, for two-sided Fisher's exact test).
Predictors of food selection were examined using a binary logistic regression with Condition, Restraint, Gender, Condition × Restraint, Condition × Gender, Restraint × Gender and Condition × Restraint × Gender as the independent variables and food selected (pasta vs salad) as the dependent variable. A main effect was found for Gender, X2(1)=6.48, P=0.011, with males being more likely to choose pasta than were females. A Condition × Restraint interaction was also found, X2(3)=8.94, P=0.03. Condition had no effect on food selected for unrestrained eaters, X2(3)=1.92, P=0.59, but was a significant predictor of food selected for restrained eaters, X2(3)=9.37, P=0.025. Restrained eaters in the high-calorie salad/high-calorie pasta condition were 4.94 times more likely to choose pasta over salad compared with restrained eaters in the no calorie information condition, X2(1)=5.96, P=0.015, and 3.67 times more likely to choose pasta over salad compared with restrained eaters in the low-calorie salad/high-calorie pasta condition, X2(1)=3.98, P=0.046. Furthermore, restrained eaters in the high-calorie salad/low-calorie pasta condition were 4.41 times more likely to choose pasta over salad compared with restrained eaters in the no calorie information condition, X2(1)=5.10, P=0.024.
Means and s.d. for calories eaten are presented in Table 4 and Figure 2. A Condition × Food Chosen × Restraint analysis of variance could not be conducted because too few participants chose salad in some cells. Therefore, before conducting the analyses for calories eaten, the low-calorie salad/high-calorie pasta and high-calorie salad/low-calorie pasta conditions were combined to create a ‘calorie labels’ condition. We compared this ‘calorie labels’ condition with the ‘no calorie information’ condition and the ‘calorie labels plus framing information’ condition. To examine whether calorie information affected the amount eaten, a Condition × Restraint × Gender analysis of variance was then conducted with calories eaten as the dependent variable. A Kolmogorov–Smirnov test indicated that the calorie data fit a normal distribution, Z=0.765, P=0.602 and Levene's test indicated that variance was equal across groups, F(11,242)=1.434, P=0.158. A main effect of Gender was found, with men eating more than women, F(1,242)=88.96, P<0.001. No other main effects or interactions were significant. All P-values were above 0.2. In order to test the effects of menu-labeling legislation more directly, a second analysis was conducted to compare participants in the no calorie information condition with those in the calorie labels plus framing information condition. A main effect of Gender, F(1,118)=50.79, P<0.001, and a marginal Condition × Restraint effect, F(1,118)=3.07, P=0.082, were found. Post hoc tests revealed that restrained eaters ate marginally less than did unrestrained eaters in the no calorie information condition, P=0.082, but not in the calorie labels plus framing information condition, P=0.461. In addition, unrestrained eaters ate marginally less in the calorie labels plus framing information condition than in the no calorie information condition, P=0.083, but the amount eaten by restrained eaters did not vary between the two conditions, P=0.46. Eight participants reported that they did not notice the calorie information. The analyses for food selected and calories eaten were repeated with these participants omitted. All results remained essentially the same.
Study 2 provides evidence that restrained eaters are responsive to calorie labels when selecting among menu options, although the information just seems to move them away from healthier but less preferred salads when the salad is seen accurately as highly caloric. There was no difference in selection of salad between the salad labeled (falsely) as low calorie and the unlabeled salad, so the effect of caloric labels on salad ordering was only to decrease the extent to which restrained eaters chose salad. More importantly, only unrestrained eaters responded to calorie labels with respect to actual intake.
The present research examined the effects of calorie information on the selection and intake of salad and pasta in a restaurant-like setting. Across both studies, calorie labels influenced food selection for restrained eaters, but not for unrestrained eaters. Overall, restrained eaters were more likely to order salad when the salad was either unlabeled, or labeled as low in calories and more likely to order pasta, even high-calorie pasta, when the salad was labeled as high in calories. Presumably, then, many restrained eaters order salad primarily to maintain their diets, and are no longer interested in eating salad when they find out it is high in calories.
Calorie information also influenced the amount that participants ate. In study 1, participants who were informed that the salad contained 1200 calories ate more salad than participants who received no calorie information (mainly due to the minimal amount eaten by the restrained eaters who chose salad in the no calorie information, thinking it was low in calories and thus maintaining their diets), whereas participants who were informed that the pasta contained 1200 calories ate the same amount as those who received no calorie information, possibly because this information fit their expectations about the caloric value of the pasta dish. The results of study 2 showed that restrained participants who received calorie information plus information about daily caloric intake ate the same amount as those who received no calorie information. However, unrestrained participants who received calorie information plus information about daily caloric intake ate marginally less than those who received no calorie information.
These findings differ somewhat from those of the three previous studies that examined the effects of calorie information on amount eaten. Harnack et al.15 found that calorie information increased males' intake, and Aaron et al.14 found that calorie information increased both males' and unrestrained eaters' intake, whereas Roberto et al.16 found that calorie information decreased overall intake regardless of sex or restraint. These discrepant findings may be due, at least in part, to the fact that, except for study 1 in the present paper, none of the previous studies specifically examined how expectations about food healthfulness affect the amount eaten. Calorie information that matches participants' expectations may not alter amount eaten, whereas calorie information that does not match expectations could affect the amount eaten in either direction. When dieters expect a food to be low calorie and find out that it is not, they may eat more than when it is described as low in calories (encouraging them to maintain their diets by eating less). Conversely, if they find out that a food is less fattening than they believed, they may maintain their diets and eat less of it. It is, therefore, entirely possible that amount eaten differed across studies because of both the specific types of foods served in a particular study and participant expectations about the healthfulness of these foods. More consistent patterns may emerge in future studies if amount eaten is analyzed separately based on the type of food that participants select.
With regard to food selection, these findings differ from those of Harnack et al.15, and accord partially with those of Roberto et al.16 Whereas Harnack et al.15 found no effect of calorie information on calories ordered, Roberto et al.16 found that calorie information decreased the number of calories ordered. Results from study 2 may help to explain these mixed findings. Restrained eaters in this study altered their ordering behavior in response to calorie information only when the calorie labels violated expectations about the healthfulness of the foods. Thus, giving caloric information that indicates that a food usually regarded as low calorie actually is low calorie does not change behavior, but pointing out that such foods are actually not low calorie just leads dieters to order the less healthy (and more preferred) high-calorie option. Participant expectations about the foods served from McDonald's in Harnack et al.15 may have differed from expectations about foods served from Au Bon Pain in Roberto et al.16 Foods from McDonald's are generally not regarded as healthful, so calorie information for these menu items may not have surprised participants. In contrast, some of the seemingly healthful items from Au Bon Pain may have contained more calories than participants expected. For example, many sandwiches from Au Bon Pain contain more calories than a McDonald's Big Mac.
Several limitations of this study should be noted. First, although the study setting was designed to simulate a restaurant, it was conducted in a laboratory and the menu was limited to two options. Second, because participants ate alone, it was not possible to explore whether the effects of calorie information are different when people eat in the company of others. People eating with others may be driven by self-presentation motives, for example, to appear ‘healthy,’ which could lead them to alter both the foods that they select and how much they eat.
In conclusion, results of this study indicate that the provision of calorie information does not alter food selection among unrestrained eaters, but may lead restrained eaters to order ‘healthful’ items such as salad less frequently when these foods contain more calories than expected, and to order typically higher-calorie foods such as pasta more often when these foods are lower in calories than expected. The effects of calorie information on amount eaten are less clear. Although unrestrained eaters may eat somewhat less when calorie labels are given along with information about recommended daily caloric intake levels, there is no indication that participants who choose high-calorie foods over low-calorie food eat less in response to calorie information. The rush to provide calorie information may not prove to be the best approach to fighting the obesity epidemic.
Flegal KM, Carroll MD, Ogden CL, Curtin LR . Prevalence and trends in obesity among US adults, 1999-2008. JAMA 2010; 303: 235–241.
U.S.Department of Health and Human Services. Office of the Surgeon General. Overweight and Obesity: Health Consequences 2010. Available at: http://www.surgeongeneral.gov/topics/obesity/calltoaction/fact_consequences.html.
FDA/CFSAN (Food and Drug Administration/Center for Food Safety & Applied Nutrition). Counting Calories: Report of the Working Group on Obesity 2004. Available at: http://www.cfsan.fda.gov/∼dms/owg-rpthtml#v.
Lin B, Guthrie J, Frazao E . Away-from-Home Foods Increasingly Important to Quality of American Diet. USDA, Economic Research Service, Agriculture Information Bulletin: Washington, DC, 1999, p 749.
Binkley JK, Eales J, Jekanowski M . The relation between dietary change and rising US obesity. Int J Obes 2000; 24: 1032–1039.
Duffey KJ, Gordon-Larsen P, Jacobs DR, Williams OD, Popkin BM . Differential association of fast food and restaurant food consumption with 3-y change in body mass index: the Coronary Artery Risk Development in Young Adults Study. Am J Clin Nutr 2007; 85: 201–208.
Thompson OM, Ballew C, Resnicow K, Must A, Bandini LG, Cyr H et al. Food purchased away from home as a predictor of change in BMI z-score among girls. Int J Obes 2004; 28: 282–289.
Ma Y, Bertone ER, Stanek EJ, Reed GW, Hebert JR, Cohen NL et al. Association between eating patterns and obesity in a free-living US adult population. Am J Epidomiol 2003; 158: 85–92.
Guthrie JF, Lin B, Frazao E . Role of food prepared away from home in the American diet, 1977-78 versus 1994-96: changes and consequences. J Nutr Educ Behav 2002; 34: 140–150.
Naska A, Orfanos P, Trichopoulou A, May AM, Overvad K, Jakobsen MU et al. Eating out, weight, and weight gain. A Cross-sectional and prospective analysis in the context of the EPIC-PANACEA study. Int J Obes 2011; 35: 416–426.
Bezerra IN, Sichieri R . Eating out of home and obesity: a Brazilian nationwide survey. Public Health Nutr 2009; 12: 2037–2043.
Anderson M, Matsa DA . Are restaurants really supersizing America? Am Eco J 2011; 3: 152–188.
HR 3962, Section 2572. Affordable Health Care for America Act 2010. Available at: http://www.govtrack.us/congress/bill.xpd?bill=h111-3962&tab=summary.
Aaron JI, Evans RE, Mela DJ . Paradoxical effects of a nutrition labelling scheme in a student cafeteria. Nutr Res 1995; 15: 1251–1261.
Harnack LJ, French SA, Oakes JM, Story MT, Jeffrey RW, Rydell SA . Effects of calorie labeling and value size pricing on fast food meal choices: Results from an experimental trial. Int J Behav Nutr Phys Act 2008; 5: 63.
Roberto CA, Larsen PD, Agnew H, Baik J, Brownell KD . Evaluating the impact of menu labeling on food choices and intake. Am J Public Health 2010; 100: 312–318.
Herman CP, Polivy J, Silver R . Effects of an observer on eating behavior: the induction of ″sensible″ eating. J Pers 1979; 47: 85–99.
The authors declare no conflict of interest.
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Cite this article
Girz, L., Polivy, J., Herman, C. et al. The effects of calorie information on food selection and intake. Int J Obes 36, 1340–1345 (2012). https://doi.org/10.1038/ijo.2011.135
- food selection
- food intake
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