The Effects of Calorie Information on Food selection and Intake

by

Laura Parker Girz

A thesis submitted in conformity with the requirements

for the degree of Master of Arts

Graduate Department of Psychology

University of Toronto

© Copyright by Laura Parker Girz (2009)

ii

The Effects of Calorie Information on Food selection and Intake

Master of Arts, 2009

Laura Parker Girz

Department of Psychology

University of Toronto

Abstract

Proposed legislation in the United States and Canada would require calorie information to

be presented on the menus/menu boards of restaurants. To test the possible impacts of

such legislation, the present study examined the effects of calorie information on the food

selection and intake of restrained and unrestrained eaters. Female students were presented

with a menu containing two items, a salad and a pasta dish, for which calorie information

was either present or absent. Results of the present study indicate that the provision of

calorie information does not alter food choice but does influence the amount people eat.

Although the salad and pasta contained the same number of calories, calorie information

decreased consumption of pasta, but increased consumption of salad.

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Table of Contents

Introduction ……………………………………………………………………………… 1

Method …………………………………………………………………………………. 13

Results ………………………………………………………………………………….. 15

Discussion ……………………………………………………………………………… 16

Tables…………………………………………………………………………………… 19

References ……………………………………………………………………………… 21

1

The Effects of Calorie Information on Food Selection and Intake

The United States and much of the rest of the developed world is currently in the

midst of an obesity epidemic. According to the 2003-2004 National Health and Nutrition

Examination Survey, 32.9% of Americans are obese and another 33.3% are overweight.

While the percentage of overweight Americans has remained relatively constant in the last

thirty years, rates of obesity have increased dramatically. For example, between 1976 and

1980, 32% 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 (Office of the

Surgeon General, 2008).

Despite a great deal of discussion about the obesity epidemic, there does not seem to

be a clear consensus on what is actually causing obesity rates to increase. The two most

popular explanations are that physical activity levels have dropped and that marketing

practices are leading people to eat more, although other possible explanations also exist

(Keith et al., 2006). Even if reduced physical activity and marketing practices are entirely

responsible for the obesity epidemic, we still don’t understand why people are less active or

how exactly marketing practices are encouraging people to overeat. A more specific theory is

that eating frequently in restaurants is contributing to the obesity problem (FDA, 2004). The

number of meals eaten outside the home has increased dramatically over the same time

period during which obesity rates have risen (Lin, Guthrie, & Frazao, 1999). For example

spending on food prepared outside the home almost doubled between 1970 and 2005 (NRA,

2005). There is evidence that eating often in restaurants, particularly fast-food restaurants,

leads to weight gain (Binkley, Eales, & Jekanowski, 2000; Duffey, Gordon-Larsen, Jacobs,

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Williams, & Popkin, 2007; Thompson et al., 2004). This is probably due to that fact that, on

average, people eat more calories when they eat out than when they eat at home (Guthrie,

Lin, & Frazao, 2002).

A few different factors may explain why individuals consume more calories in

restaurants than they do at home. First, the portion sizes have increased since the 1970s so

that typical restaurant portions now contain much more food than the average person needs in

one meal (1100-2300 calories) (Nielsen & Popkin, 2003; Wootan, Osborn, & Malloy, 2006).

There is strong evidence that serving larger portions increases intake. For example, Wansink

and Kim (2005) presented participants attending a movie with either medium or large

buckets of popcorn. Those given large buckets ate 45.3% more than those given medium

buckets. Diliberti, Bordi, Conklin, Roe, and Rolls (2004) found similar results when

participants were presented with either a standard or a large portion of pasta. The participants

given the large portion of pasta ate approximately 43% more than those given the standard

portion.

Second, people generally have a very difficult time estimating the caloric value of

foods that they are served while eating out. It seems that people can estimate the calories in

small portions of lower calorie foods fairly accurately, but their estimates of the calories in

both large portions and high calorie foods are usually far too low. For example, Burton,

Creyer, Kees, and Huggins (2006) asked participants to estimate the number of calories in

typical restaurant meals. Seventy-three percent of participants underestimated the calories in

the lower-calorie meals, such as a turkey sandwich or pot roast. The calorie estimates for

these meals were only slightly low, however (500 estimated calories compared to 543 actual

calories per meal). Ninety percent of participants underestimated the calories in the higher-

3

calorie items, such as a chef salad or hamburger and French fries. The calorie estimates for

these items were much too low (694 estimated calories compared to 1336 mean calories per

meal). In addition, the researchers included a very-high-calorie item, cheese fries with ranch

dressing, and found that 99% of participants underestimated its caloric value. The average

estimate was off by over 2000 calories (869 estimated calories compared to 3010 actual

calories).

Even individuals who are knowledgeable about nutrition have trouble estimating

calories. Chandon and Wansink (2007a) asked participants to estimate calories in a number

of meals ranging in size from small to large. Participants who reported paying attention to

nutrition information were no better at this task than were participants who reported ignoring

nutrition information. Likewise, a study of professional nutritionists showed that they

underestimated the calories in large portions of high-calorie foods by 200 to 600 calories

(Backstrand, Wootan, Young, & Hurley, 1997).

These findings are significant in that the underestimation of calories in large portions

of food may represent a more general lack of awareness about how excessively large these

portions actually are. If so, then it is plausible that an accurate knowledge of the calories in

restaurant servings could lead people to eat less when portions are large.

Third, there is evidence that people are overly influenced by health claims when

nutrition information is absent. Chandon and Wansink (2007b) asked participants to estimate

the number of calories in meals from Subway and McDonald’s. Although the meals were

equivalent in calories, estimates for Subway meals were consistently lower than were those

for McDonald’s meals. For a large meal averaging 1327 calories, mean estimates were 843

calories for food from McDonald’s, but only 646 calories for food from Subway. The authors

4

speculate that underestimates for Subway food may represent a halo effect – since Subway is

seen as healthy, everything from Subway must be low in calories. In separate study, Wansink

and Chandon (2006) found a similar pattern when participants were given granola to eat and

told that it was either low-fat or regular. Participants who were told the granola was low-fat

ate 50.1% more than did participants told that the granola was regular. Although actual low-

fat granola is somewhat lower in calories than is regular granola, had the participants actually

been given low-fat granola they would have still consumed 33% more calories than those

who were correctly told they were eating regular granola. Likewise, Provencher, Polivy, and

Herman (2009) found that participants who were asked to taste and rate oatmeal-raisin

cookies ate approximately 35% more when the cookies were described as “healthy” as when

they were described as “gourmet”.

Despite the large portion sizes served in the United States and the evidence that

people have trouble estimating calories in the food that they are served, most restaurants do

not provide nutrition information for their menu items (Wootan, Osborn, & Malloy, 2006).

As of 2004, only 44% of the top 300 chain restaurants in the United States made nutrition

information available to their customers. In addition, 86% of the time, the nutrition

information was available to customers only on the company website.

To remedy this problem, there is now proposed legislation in the United States called

the Menu Education and Labeling Act. In addition, a similar bill has recently been introduced

in Ontario. This legislation would require all chain restaurants with more than twenty outlets

to provide information about calories, saturated fat, trans fat, and sodium next to each item

on the menu. Restaurants with a menu board rather than a menu would provide calorie

information next to each item on the board. The United States legislation also mandates the

5

provision of “information, specified by the Secretary by regulation, designed to enable the

public to understand, in the context of a total daily diet, the significance of the nutrition

information that is provided” (H.R. 3895). The assumption behind this legislation seems to

be that providing individuals with calorie information will lead them to make healthier

selections. However, there are actually a few different outcomes possible. Some people may

not care about the calorie information and may ignore it. Those who do care about calorie

information could respond in two different ways if they find the food they were planning 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.

The first option, choosing a “healthier” meal when nutrition information is provided,

has been explored in both the nutrition and marketing literature. Several studies have

examined the effects of nutrition information on reported purchase intentions. Yamamoto,

Yamamoto, Yamamoto, and Yamamoto (2005) presented adolescents with menus from

McDonald’s, Panda Express, and Denny’s and asked them to choose the item that they would

order for dinner from each menu. After making their selections, the participants were again

given menus from the same three restaurants, but calorie and fat information was now

presented next to each item on the menu. Participants were once again asked to indicate

which item they would order for dinner at each restaurant. Only 31 of the 106 participants

changed orders for at least one of their three meals after viewing the nutrition information.

For the orders that were changed, 80% contained fewer calories than did the original order

and 20% contained more calories than did the original order. Overall, the addition of calorie-

and-fat information to the menu significantly reduced the calories and fat in selections at

McDonald’s and Panda Express, but not at Denny’s. Despite the significant reductions in fat

6

and calories at these restaurants, however, the differences were the result of order changes by

only 20% of participants.

Gerend (2009) also examined the effects of calorie information on reported purchase

intentions. Undergraduate students were presented with either a regular fast-food menu or a

menu with added calorie information and were asked to select the items they would order.

Women who received menus with calorie information ordered fewer calories per meal and

ordered lower-calorie items, but did not order fewer items. The calorie information had no

effect on men. It is difficult to draw any conclusions based on the findings of this or the

Yamamoto et al. study, however, because the data in both studies were based on reports of

predicted behavior rather than on actual behavior. It is unclear whether these self-reports

would actually match orders in a restaurant setting.

Several other studies have addressed this problem by tracking orders in restaurants

and cafeterias before and after the presentation of nutrition information.

Cranage, Conklin, and Lambert (2004) looked at the impact of displaying nutrition

information, including calorie counts, on sales in an on-campus café. Sales of the higher fat,

higher calorie entrees dropped from 67% to 47% after nutrition information was displayed on

a card next to each item. In addition, sales of vegetables, fruits, and side salads increased

while sales of French fries and desserts decreased.

In a similar study, Cinciripini (1984) examined the effects of calorie information on

sales in a university cafeteria. The display of calorie information on large signs at the

entrance of the cafeteria reduced the selection of carbohydrates and red meat for all

participants. Normal weight males and females also selected fewer regular dairy products

after calorie information was provided. In addition, calorie information led obese females to

7

increase their selection of salads, vegetables, soups, fruits, and low-fat dairy and to decrease

their selection of high-fat foods, desserts, and sauces.

Balfour, Moody, and Wise (1996) examined the effects of nutrition information on

food choices in a cafeteria. Men and women entering a workplace cafeteria were invited to

use a computer system to analyze the composition of the meal they were about to order. The

computer program provided participants with an analysis of the calorie and nutrient

information for their chosen meal as a percentage of suggested daily intake. Of the

approximately 45% of the participants who chose to use the computer program, 17% of

females and 15% of males decided to change their first choice after receiving feedback.

Among those who changed their first choice, 69% of females and 54% of males chose meals

with fewer calories. In addition, the initial meals chosen by participants who decided to

change their first choice were significantly higher in calories than were the meals chosen by

those who did not change their first choice, but the second choice meals were not

significantly higher in calories.

Many studies looking at the effects of nutrition information on food selection provide

participants with some indication that given foods were low in calories, heart healthy, or

“nutritious” rather than providing calorie information. For example, Dubbert, Johnson,

Schlundt, and Montague (1984) tracked food purchases in a cafeteria before and after low-

calorie entrées, vegetables, and salads were identified with a sign reading “lower calorie

selection”. Vegetables and salads labeled “low calorie” were significantly more likely to be

selected during the intervention than during the baseline. In contrast, the “low calorie” labels

did not increase selection of entrées. In addition, the mean calories ordered per meal did not

8

change, so it seems that choosing lower-calorie vegetables and salads lead participants to

select higher-calorie entrées.

Levin (1996) conducted a similar study, but focused on fat content rather than

calories. Purchases were tracked before and after three entrées were labeled with a heart-

shaped sign reading, “Look for the heart for your low-fat entrée selection”. The purchases in

the experimental cafeteria were compared to those at a control cafeteria. Purchases of

targeted items did not increase at the control cafeteria over the course of the study, but

increased significantly in the experimental cafeteria after the signs were posted. Further, sales

of the labeled items increased over the course of the intervention, with the number of entrées

sold in weeks 28 and 29 (14.1% of total sales) significantly greater than the number sold in

weeks one and two (9.5% of total sales) or in weeks three and four (11.9 percent of total

sales).

Albright, Flora, and Fortmann (1990) explored the effects of nutrition information in

a restaurant setting rather than in a cafeteria. Foods low in fat and cholesterol were labeled

with signs reading “good for health” at four family-style restaurants with very similar menus.

The same entrees were labeled at each restaurant, but only two of the restaurants experienced

a significant increase in sales of the labeled items. For these two restaurants, sales of labeled

items increased by 18-40% as compared to baseline levels. The authors were unable to

explain why the intervention was effective in only two of the restaurants, but commented that

it was difficult for restaurant managers to comply with all experimental procedures.

The preceding studies show mixed findings with regard to whether providing

nutrition information increases selection of “healthy” items. One problem is that many

different types of nutrition information are used. Given the evidence discussed earlier that

9

people underestimate the calories in foods thought of as healthy, it is possible that when

interventions lead people to order “healthier” items they actually end up eating more than

they normally would. Specific calorie information may, therefore, have a different impact

than labeling items as “low calorie” or “low fat”. In addition, there is some evidence that

calorie information does not affect everyone to the same extent, but who is affected by such

information and how this information changes behavior for different groups remains unclear.

Furthermore, these studies address only one of the two options available to restaurant patrons

interested in lowering their caloric intake. Such individuals not only have the option of

switching to a “healthier” order, but also the option of eating less of their original order.

Surprisingly, few studies have addressed this second option.

Kirschenbaum and Tomarken (1982) looked at effects of calorie information on food

intake by preloading restrained and unrestrained eaters with a milkshake and then presenting

them with ice cream in nine small bowls or three large bowls. In one condition the bowls

were labeled with accurate calorie information, while in the other condition no calorie

information was provided. Overall, the subjects who received calorie information ate less,

but there were differences between restrained and unrestrained eaters. Participants high in

restraint ate more than did unrestrained participants in the small-bowl-unlabeled condition

and the large-bowl-labeled condition, but the two groups ate the same amount in the small-

bowl-labeled (166.7g) and large-bowl-unlabeled conditions (256.8g).

Kral, Roe, and Rolls (2002) also examined the effects of calorie information on intake

by having normal-weight undergraduate students eat all meals in the laboratory on three

separate days. The energy density of foods served was kept consistent within each day but

was varied between days. In addition, one group of participants was provided with calorie

10

information while the other group received no calorie information. Participants ate

approximately 22% more on the high energy density day than on the low energy density day,

but no overall differences were found between the participants who received calorie

information and those who did not. Calorie information did seem to have different impacts

on restrained and unrestrained eaters, however. Among the participants who did not receive

calorie information, restrained participants ate less than unrestrained participants when

served low energy-density food. However, among the participants who did receive calorie

information, restraint was not related to food intake.

These two studies suggest that calorie information has different effects on restrained

and unrestrained eaters, but the nature of these effects remains unclear. The findings of the

Kral et al. study indicate that calorie information may affect restrained eaters when foods are

low in energy density, but it is hard to interpret the findings of the Kirschenbaum and

Tomarken study since the addition of a preload and the manipulation of bowl size obscure

the results.

In addition, participants in both studies were given no choice of which foods they

were served. As stated earlier, in an actual restaurant setting people could respond to calorie

information by changing their selections or by reducing their intake, but the studies reviewed

so far have only examined one of these two options. Only two studies to data have examined

both food choices and intake simultaneously.

Aaron, Evans, and Mela (1995) examined the effects of calorie information on food

intake in a cafeteria setting. Individuals who ate lunch regularly in a campus cafeteria were

asked to participate in the study as an experimental group. The amount that each individual

ate was measured both during a baseline week and during a week in which calorie

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information, including the percentage of calories from fat, was posted next to each food. A

control group, consisting of individuals who did not eat regularly in the campus cafeteria,

was asked to eat in a separate cafeteria for the two weeks during which the study took place.

The only measure that increased significantly for the control group between weeks one and

two was the percent of energy from carbohydrate (46.1% to 48.4%). In the experimental

group, intake did not differ between weeks one and two for restrained eaters or for females.

Unrestrained eaters and males, however, consumed significantly more calories, fat, and

carbohydrate and significantly less protein after the calorie information was posted. Men tend

to report lower restraint scores than do women, so it is unclear whether unrestrained men and

unrestrained women both altered their intake or whether this restraint effect was driven

primarily by the male participants.

In a recent study, Harnack et al. (2008) examined the impact of calorie information on

the selection and intake of fast-food. Adolescents and adults who frequented fast-food

restaurants were presented with a menu describing fast-food items on which calorie

information was either present or absent. All participants were asked to select items from the

menu and the amount eaten by each participant was recorded. The provision of calorie

information did not alter intake or nutrient composition for females but was found to increase

intake in males.

As these studies were conducted to examine cafeteria and fast-food choices, it is not

clear that we could extrapolate from the results of either study to predict the effects of calorie

information on food intake or selection in a restaurant setting. However, these two studies do

provide a preliminary indication that calorie information may have little effect on the intake

of females but may actually increase intake in males. The results with respect to food

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selection are less clear. Although both studies examined changes in the nutrient composition

of foods consumed, they did not look specifically at whether calorie information influenced

which foods were ordered. This is an important omission since it is possible for food

selections to change without altering average calorie composition of a meal.

Overall, it seems that prior research has produced mixed findings as to the impacts of

providing nutrition information on eating behavior. Furthermore, research has focused on

either the effects of nutrition information on food selection or the effects of nutrition

information on food intake, but the two have not been fully examined simultaneously. If

calorie information were to be provided in a restaurant setting, consumers who care about

this information would have both options open to them; they could either select a different

food or alter their intake. Since prior research has not adequately addressed this situation, it is

unclear how calorie information would affect eating behavior in a restaurant setting. In fact, a

recent statement by the Dieticians of Canada concludes that more research is needed to

determine the impacts of menu labeling in full-service chain restaurants and to explore

possible unintended negative consequences of such labeling (Dieticians of Canada, 2009).

The present study 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 (“healthy” foods that are

low in calories) and for foods that do not match expectations (“healthy” foods that are high in

calories). Restrained eaters were expected to choose salad more often than unrestrained

eaters in the control and 600-calorie salad conditions, but not in the 1200-calorie salad

condition. Expectations for the amount of food consumed were less clear, but the following

outcomes were considered possible. Restrained eaters who choose to eat the 1200-calorie

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pasta may reduce the amount they eat in order to maintain their diets. Alternately, the 1200-

calorie label may disinhibit restrained eaters who choose pasta and thus increase their intake.

It is also possible that restrained eaters in the control condition assume that the pasta is high

in calories. In this case restrained eaters who choose to eat pasta may eat an equivalent

amount in the control and 1200-calorie conditions. Unrestrained eaters who choose the 1200-

calorie pasta condition may reduce their intake in response to the high calorie value of the

pasta. However, if unrestrained eaters do not care about calorie information then their intake

may not change. Restrained and unrestrained eaters who choose 600-calorie pasta may not

alter the amount they eat if this calorie amount does not differ from their expectations.

However, if this calorie amount is lower than expected, then they may increase their intake.

Both restrained and unrestrained eaters who choose the 1200-calorie salad may

reduce the amount they eat in response to this high calorie value. If participants in the control

condition assume that salad has less than 600 calories, then both restrained and unrestrained

eaters may also eat less in the 600-calorie salad condition as compared to the control

condition. However, if salad is assumed to have approximately 600 calories then intake may

not differ from the control condition. It is also possible that salad is seen as healthy

regardless of the calories it contains and, therefore, calorie labels may have no impact on

salad intake.

Method

Participants were 147 female students from the introductory psychology subject pool

at the University of Toronto Mississauga. The Restraint Scale (Herman & Polivy, 1980) was

used to categorize participants as restrained eaters (scoring 15 or higher) or unrestrained

eaters (scoring below 15).

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All participants were first asked to fill out several questionnaires including a form

assessing liking of various foods, the Janis-Field Self-Esteem Scale as modified by Pliner

(Pliner, Chaiken, & Flett, 1990), and a visual analog scale measuring desire to eat, hunger,

fullness, and the amount participants felt they could eat at that time.

The participants were then told they would be rating potential new menu items 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 Prego pasta sauce and mozzarella cheese. The two dishes contained the same

number of calories (approximately 1250 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, 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; Pasta

Marinara - Rotini tossed with our signature marinara and topped with fresh mozzarella. In the

first experimental condition, the same information was presented as in the control condition,

but the salad was described as having 600 calories and the pasta dish was described as having

1200 calories. In the second experimental condition the salad was described as having 1200

calories, while the pasta dish was described as having 600 calories. Participants selected

either the salad or the pasta dish from the menu and were given 15 minutes to complete their

meal.

15

After eating, participants were asked to fill out a series of questionnaires including the

same visual analog scale that was presented before eating, a meal evaluation form, a

shortened version of the Food Healthfulness Questionnaire (Carels, Harper, & Konrad,

2006), the Restraint Scale (Herman & Polivy, 1980), a measure of Dieter-Identity (Polivy),

the Three-Factor Eating Questionnaire (Stunkard & Messick, 1985), and the Dutch Eating

Behavior Questionnaire (Van Strien, Frijters, Bergers, & Defares, 1986).

Results

Although participants were instructed to eat as they would during a normal meal and

not merely to taste-test the food, four participants ate minimally (less than 50 grams) and

were dropped from the analyses. Two of these participants were restrained and two were

unrestrained. Three were in the control condition and one was in the 600 calorie salad/1200

calorie pasta condition. Two chose salad and two chose pasta.

Independent samples t-tests showed no difference in taste-ratings for the salad and the

pasta, t (88.42) = -0.91, p = 0.365.

Means and standard deviations for food chosen are presented in Table 1. The food

selected (pasta vs. salad) was submitted to a Condition x Restraint ANOVA. A main effect

was found for Restraint, with restrained eaters being more likely to chose salad than were

unrestrained eaters, F (1, 137) = 3.949, p < 0.05, but no Condition main effect or Condition x

Restraint interaction was found.

Means and standard deviations for grams eaten are presented in Table 2. Separate

Condition x Restraint ANOVAs were then conducted for the participants who chose pasta

and for those who chose salad. Main effects of Condition were found for both pasta, F (2, 84)

= 3.646, p < 0.05, and salad, F (2, 47) = 3.679, p < 0.05, but no Restraint main effects or

16

Condition x Restraint interactions were found. For participants who chose pasta, t-tests

indicate that those in the 600-calorie, t (60) = 2.138, p < 0.05, and 1200-calorie, t (55) =

3.119, p < 0.01, pasta conditions ate less than those in the control condition. For participants

who chose salad, those in the 1200-calorie salad condition ate significantly more than those

in the control condition, t (29) = -2.825, p < 0.01, but no other significant differences were

found between conditions.

Discussion

The present study examined the effects of calorie information on the selection and

intake of salad and pasta in a restaurant-like setting. Results indicate that the provision of

calorie information does not alter food choice but does influence the amount people eat.

Interestingly, although the salad and pasta contained the same number of calories, calorie

information decreased consumption of pasta, but increased consumption of salad. The

reasons for this discrepancy are not clear. It is possible that salad is regarded as a non-

fattening food regardless of its calorie content, but this does not explain why intake increased

when the salad was labeled as high in calories. Perhaps a high-calorie label for the salad

legitimized it as a main dish rather than a side dish and thus increased intake. Additional

studies are warranted to determine whether this pattern of consumption replicates and to

explore possible reasons for it.

These findings differ somewhat from those of the two previous studies that examined

both food selection, at least in terms of nutrient composition, and food intake. Aaron et al.

(1995) and Harnack et al. (2008) found that the intake of female participants and the nutrient

composition of the foods they chose was unaffected by the provision of calorie information.

With regard to the effects of calorie information on food selection, if changes in nutrient

17

composition are taken to mean differences in food selection then these findings are similar to

those of the present study. However, it is important to note that other studies (e.g., Balfour, et

al., 1996; Cinciripini, 1984) have found that calorie information does alter food selection.

One reason for these disparate findings may be the settings in which each study took place.

The majority of previous studies have examined the effects of nutrition information on food

selection in either cafeterias or fast-food restaurants, but chain-style restaurants have largely

been neglected. It is possible that the provision of calorie information has a different effect in

chain-style restaurants than it does in cafeterias or fast-food restaurants. Preliminary support

for this idea comes from Yamamoto et al. (2005), which showed that calorie information

influenced reported purchase intentions at Panda Express and McDonald’s but not at

Denny’s. These results suggest that our findings may apply only to chain-style restaurants,

not to fast-food restaurants or cafeterias.

With regard to the effects of calorie information on the amount of food consumed,

neither Aaron et al. (1995) nor Harnack et al. (2008) showed the pattern of increased

consumption of some foods and decreased consumption of others found in the present study

study. As previous studies have not examined intake across different types of foods, it is

possible that decreased intake of certain foods has been offset by increased intake of other

foods, thus producing what appear to be null findings. Rather than measuring consumption as

an aggregate of all foods eaten, future studies should explore how calorie information affects

the intake of specific types of food.

Overall, these results tentatively suggest that posting calorie information on menus

may have the unintended consequence of increasing the consumption of certain foods,

possibly those that are regarded as “non-fattening”. However, several limitations of the

18

present 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. Future

studies should be conducted in actual restaurants with the full range of menu items. Second,

only female university students were examined so it is unclear how demographic variables

such as gender, age, and education level influence responses to calorie information in

restaurants. Third, 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

may be driven by self-presentation motives, for example to appear “healthy”, which could

lead them to alter both the foods they select and how much they eat.

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Table 1. Means and Standard Deviations for Food Chosen (Pasta = 1, Salad = 2).

Menu Condition Unrestrained Restrained

No cal info M = 1.34

SD = 0.48

N = 29

M = 1.41

SD = 0.51

N = 17

600 cal salad, 1200 cal pasta M = 1.31

SD = 0.47

N = 26

M = 1.58

SD = 0.50

N = 24

1200 cal salad, 600 cal pasta M = 1.24

SD = 0.44

N = 29

M = 1.39

SD = 0.50

N = 18

Total M = 1.30

SD = 0.46

N = 84

M = 1.47

SD = 0.50

N = 59

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Table 2. Means and Standard Deviations for Amount Eaten (Grams)

Chose pasta Chose salad

No calorie info M = 346.44

SD = 130.11

N = 19

M = 185.89

SD = 87.92

N = 10

600 cal salad,

1200 cal pasta

M = 217.41

SD = 104.09

N = 18

M = 198.98

SD = 132.01

N = 8

Unrestrained

1200 cal salad,

600 cal pasta

M = 270.90

SD = 112.85

N = 22

M = 311.33

SD = 124.16

N = 7

No cal info M = 336.25

SD = 139.93

N = 10

M = 164.90

SD = 110.43

N = 7

600 cal salad,

1200 cal pasta

M = 284.33

SD = 123.43

N = 10

M = 252.18

SD = 100.93

N = 14

Restrained

1200 cal salad,

600 cal pasta

M = 272.28

SD = 169.87

N = 11

M = 251.20

SD = 193.31

N = 7

21

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