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1ST RESEARCHChanges in energy content of lunchtime purchasesfrom fast food restaurants after introduction of calorie

labelling: cross sectional customer surveysBMJ 2011; 343 doi: 10.1136/bmj.d4464 (Published 26 July 2011)Cite this as: BMJ 2011;343:d4464

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1. Tamara Dumanovsky, independent consultant1,

2. Christina Y Huang, doctoral fellow2,

3. Cathy A Nonas, director of Physical Activity and Nutrition3,

4. Thomas D Matte, professor of Urban Public Health Program4,

5. Mary T Bassett, director of African Health Initiative5,

6. Lynn D Silver, assistant commissioner3

Author Affiliations

1. Correspondence to: T [email protected]

Accepted 6 June 2011

Abstract

Objective To assess the impact of fast food restaurants adding calorie labelling to menu items on the energy content

of individual purchases.

Design Cross sectional surveys in spring 2007 and spring 2009 (one year before and nine months after full

implementation of regulation requiring chain restaurants menus to contain details of the energy content of all menu

items).

Setting 168 randomly selected locations of the top 11 fast food chains in New York City during lunchtime hours.

Participants 7309 adult customers interviewed in 2007 and 8489 in 2009.

Main outcome measuresEnergy content of individual purchases, based on customers register receipts andon

calorie information provided for all items in menus.
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Results For the full sample, mean calories purchased did not change from before to after regulation (828 v846 kcal,

P=0.22), though a modest decrease was shown in a regression model adjusted for restaurant chain, poverty level for

the store location, sex of customers, type of purchase, and inflation adjusted cost (847 v827 kcal, P=0.01). Three

major chains, which accounted for 42% of customers surveyed, showed significant reductions in mean energy per

purchase (McDonalds 829v785 kcal, P=0.02; Au Bon Pain 555 v475 kcal, P


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calories ordered between intervention and control groups.21A third study found an effect on parents food choices for

young children but no effect on the adults choices.22

Other studies used customer receipts or sales data to track changes in calories purchased. Elbel and colleagues

used customer receipts combined with surveys to compare purchasing patterns one month before and two months

after the full enforcement of the New York City regulation in a limited number of fast food stores in four low income

neighbourhoods and found no measurable effect on calories purchased.23A second study combining sales data with

customer surveys at full service restaurants found that customers who used calorie information ordered 75 fewer

kilocalories, on average, than before.24A third study, which used sales data for more than 100 million transactions at

Starbucks, found a 6% decrease in calories per purchase in New York City after the calorie posting regulation went

into effect and no loss of revenue.25A more recent study of the implementation of a similar menu labelling law in

Washington State looked at purchases in one Mexican food restaurant chain only and did not find a change in mean

calories purchased.26While these studies begin to assess the potential impact of calorie labelling on calories

purchased, there is limited research on the effects of repeated exposure to such labelling at a population level orlonger term impacts on consumer purchasing patterns.

The New York City Board of Health first approved a calorie labelling regulation in December 2006. In January 2008,

after a lawsuit had successfully challenged the initial regulation, the city approved a second health code regulation

requiring chain restaurants with 15 or more stores nationwide to provide calorie information prominently on all menus,

menu boards, and item tags.27Calorie information was required for all items with a name and a price, and had to be

adjacent to and at least as prominent as item name or price. This regulation became effective in March 2008, and full

enforcement with fines began in late July 2008.

This paper reports on changes in lunchtime purchases at fast food chains in New York City since the implementation

of the citys calorie labelling regulation. Specifically, this study focuses on two outcomes: change in mean energy

(kcal) purchased by all customers for each food chain (the hypothesised impact was a 5% reduction in mean

kilocalories per purchase), and difference in mean energy per purchase by self reported awareness and use of

calorie information (the hypothesised difference was 10%).

Methods

Sample

The sampling frame consisted of all 1625 licensed store locations from the 13 chains that together accounted for

almost 90% of the locations covered by the 2006 regulation (some smaller chains were excluded). From this list, we

randomly selected 300 locations. Sites that had closed or were located in shopping malls or airports were excluded,

resulting in a total of 275 locations in the 2007 sample. The same locations were revisited in spring 2009. At follow-

up, 22 locations had closed or did not allow data collection, and these were replaced with restaurants of the same

chain in the same or adjacent zip code. Anticipating that customer volume would vary greatly across neighbourhoods,

we set targets for data collection at 55 customers or 2 hours for each location. Because published data needed to
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inform sample size calculations were limited at the time, we estimated the likely mean value and variation in

kilocalories per purchase from a study of adolescents.28Assuming a coefficient of variation in kilocalories purchased of

38% and conservatively assuming a design effect of 4, we would require a sample of 3600 for each survey to have

80% power to detect a 5% reduction in mean energy (kcal) from before to after regulation. To allow for stratified

analyses and ensure sufficient sample sizes by fast food chain, we set the target at 10 000 for each survey.

Of the 13 chains in the study sample, two were coffee chains with 109 locations. Data for these two coffee chains

were excluded from this analysis because purchasing patterns were so different at these chains, with over 60% of

purchases limited to a single drink. Results presented here focus on lunchtime calorie intake for 11 fast food chains

with 168 locations.

Data collection

Data collection was conducted for nine weeks in spring 2007 and spring 2009, from late March through early June.

Three-person data collection teams were stationed in front of the sampled locations during weekdays, for 122 pm at

fast food chains and 24 pm at the two coffee chains. Adult customers were approached as they entered the

restaurant and asked to provide their register receipts when exiting and to complete a brief survey; a $2 Metrocard (a

public transport pass) was offered as an incentive. In addition to collecting their receipts, the teams asked customers

to confirm that the purchase was for themselves only and to describe their purchase, including any customisations

they requested. All were asked if they saw calorie information in the restaurant and, if so, whether the information

affected their purchase. The teams recorded each customers sex based on observation. In 2009, customers were

also asked their age and residential zip code. Surveys were conducted in English only. The institutional review board

of the citys health department determined that the study did not require ethical approval as it was an evaluation of a

public health intervention.

Data entry

Each item purchased was entered as it appeared on the customers receipt. Additional information obtained through

the customer survey was also entered (that is, extra items, condiments, order modifications, and diet (low

calorie) vnon-diet beverage). We used the calorie information posted on the websites of each restaurant chain at 1

March 2007 and 1 March 2009 to ascribe a value to each item, including extras or customisations (such as extra

cheese, sauce, or salad dressing). If the customer did not provide details about added items (for example, not

specifying the type of salad dressing or dipping sauce), we assigned the lowest caloric value within that category.

Data were aggregated by customer to calculate total kilocalories per purchase.

Measures and statistical analyses

The two outcomes of interest were: (1) change in mean energy content (kcal) per purchase before and after

regulation, and (2) mean energy content (kcal) purchased among customers who said that they used the calorie

information when deciding what to order. The second outcome is limited to the period after regulation, when all food

chains labelled menu items with calorie information. All analyses adjusted for the clustered sample design, a first
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stage random sample of stores and second stage of customers within stores. Two tailed ttests with


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of receipts came from stores in high poverty neighbourhoods. Purchasing patterns were similar in the two time

periods; however, slightly fewer customers purchased a beverage in 2009 (54%, compared with 58% in 2007,

P


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42% of all customers in our study. One chain, Subway, showed a significant increase in mean energy content per

purchase (749 v882 kcal, P130 kcal compared with other customers. The reduction was significant at six chains and overall (P


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Difference in mean energy content of purchase by use of calorie information

The two models presented in table 5compare energy content per purchase between customers who reported using

the calorie information in 2009 with all other customers in 2009. After adjustment for restaurant chain, neighbourhood

poverty, age, and sex, the customers who reported using calorie information purchased an average of 96 fewer

kilocalories compared with customers who didnt use the information (model 1). After further adjustment for purchase

type, including number of items, beverage purchase, and cost, customers who reported using calorie information

purchased 78 fewer kilocalories than those who did not (782 v859 kcal, P


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Changes in the mean energy content of purchases from chains with low customer volume in the sample could not be

accurately assessed. Despite this variability across chains, the data show a modest 20 kcal decrease for the sample

as a whole when sex, neighbourhood poverty, items purchased, and cost are held constant. The unadjusted data did

not show a significant change in mean calories purchased; however, there was an increase in mean cost, and fewer

diners purchased a beverage. While these changes may be outcomes of calorie labelling, they could also be

confounders indicating a change in the customer profile over the two years. Either model is plausible, and both are

presented.

Importantly, self reported use of calorie information was associated with lower calorie purchases. One in six

customers reported using the calorie information when making their fast food purchase; compared with other

customers, these customers purchased an average of 96 fewer kilocalories overall after adjustment for

demographics; this translates to 11% lower energy content for these customers. While these numbers may be small,

an 11% reduction in energy content per meal for one in six fast food purchases could have a substantial public health

impact. Further, no negative unintended consequences of calorie labelling were identified.

Although fast food customers in the high poverty neighbourhoods were less likely to report using the calorie

information, those who did so in these neighbourhoods showed reductions in kilocalories purchased similar to those

in wealthier neighbourhoods, contrary to the findings of Elbel et al.23If the proportion of calorie aware consumers

were raised through education, prominent labelling of energy content of groceries, or other public campaigns to

complement the regulation, it is possible that the proportion of customers using calorie information effectively might

also increase. Likewise, as the new national calorie labelling regulation is implemented, we expect that there will be

additional pressures on chain restaurants to offer and promote lower calorie items.As more people rely on foods prepared outside the home, there is a strong and growing consensus that consumers

want to know what they are eating so that they can make informed choices. Requiring that fast food chains supply

calorie information provides a valuable resource for those customers who choose to use it. Although public opinion on

the measure was not assessed in this study, high levels of support (84%) have been reported.33

On the industry side, there is growing evidence that this regulation may provide an incentive to companies to offer

healthier options or reformulate their most popular products. It is worth noting that the industry initially opposed the

regulation but eventually reversed its position and supported the legislation that created the new national requirement

in the US; some of these companies have pledged to provide the information voluntarily in the United Kingdom.

Researchers have speculated that a disclosure regulation could initiate a virtuous cycle, where changes in New York

Citys fast food restaurants may spur change in other regions or food sectors.34Since the New York City regulation

took effect, various news media have reported changes to menus by affected establishments. For example, the

sandwich chain Cosis has switched to using a low fat mayonnaise in its sauces,35saving 350 calories on some

sandwiches; Starbucks switched from whole milk to 2% fat milk as its default36; and Applebees has a menu of
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choices under 550 calories.37More changes in menu offerings may be expected as calorie labelling becomes effective

nationwide in 2010 and 2011.

Strengths and limitations of the study

This study is among the first to assess the population level effects of a calorie labelling regulation. By analysing

customer purchases for a random sample of the most common fast food chains in New York City, the data represent

the average fast food weekday lunchtime purchase.

Despite its advantages, this study has several limitations. First, the data are limited to New York City, and the

external validity of the findings is as yet unknown. Furthermore, customers may be eating fast food more or less

often; which would not be captured by this study design. Customers who saw and used calorie information may have

been differently motivated from those who did not, and certain chains are likely to attract customers who may be

more inclined to use calorie information. However, it may be the case that posting calories increases awareness for

all customers, and we might expect the percentage of customers who use calorie information to increase over time.

Our objective data represent energy (kcal) purchased, not consumed. We had to rely on customers reporting as to

whether they used the calorie information and whether the food was for themselves alone, and these could be subject

to reporting bias. Although it is possible that customers did not consume everything they bought, research suggests

that availability is a strong predictor of calories consumed.3839

Because the lunchtime street intercept method limited the amount of data that could be collected, demographic

information and data on customers frequency of fast food consumption were limited, especially in the baseline

period. It was therefore not possible to assess differences between those exposed to the information more or less

frequently or those belonging to different demographic groups. The use of a lunchtime only sample also precluded

analysis of the effects of calorie labelling at other mealtimes.

This analysis does not attempt to distinguish between the multiple potential mechanisms by which calorie labelling

could affect the energy content of purchases, such as changes in menu offerings, more informed consumer choice, or

differences in pricing or promotion; nor does it seek to isolate the effects on consumer choice alone. Each one of

these mechanisms can and should be an object of separate study.

The study design does not include a control group, so secular trends that may have affected the results could not be

isolated. Because the adoption of the citys calorie labelling regulation was delayed, the time between the two data

collection periods was extended from one to two years, potentially encompassing more variability than anticipated.

Intervening factors, including the severe economic downturn, may have affected customer purchasing patterns in

2009, such as by seeking greater perceived value for their money or by increasing or reducing patronage.

Conclusions and policy implications
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Results from this study suggest that there is a positive effect of calorie labelling on energy intake at some major

chains, and that use of the information is clearly associated with lower calorie purchases across chains. However, a

clear reduction in energy intake across the full sample was not found. A strong research agenda is needed for

nutrition interventions. It will be particularly important to assess the energy content of fast food purchases periodically

as restaurant chains reformulate menu items or change their menu offerings in response to the national legislation.

Systematic tracking of changes to fast food menus would also be useful, in terms of energy, nutrients, and pricing, to

examine the industry response to policy requirements. Calorie labelling is only one part of a framework to address the

obesity epidemic. Additional strategies are needed to reduce energy intake on a population basis. Special attention

should be focused on educating consumers on how to interpret and use nutrition information. Definitive assessments

of the full impact and effectiveness of calorie labelling will require a long term perspective as calorie labelling goes

national and expands to other countries and chains have greater incentives to modify their menus.

What is already known on this topic

In January 2008 New York City fully implemented a regulation requiring chain restaurants to provide calorie

information prominently for all items on menus and menu boards

Limited data are available on the effectiveness of calorie labelling to reduce the energy content of purchased meals,

and the results are conflicting

What this study adds

Between 2007 (before the regulation) and 2009 (after its implementation) the energy content of lunchtime purchases

in New York City declined significantly at three major fast food chains, but not across the entire sample, and it

increased at one chain when large portions were heavily promoted

After regulation, one in six lunchtime customers used the calorie information provided, and these customers made

lower energy choices

Notes

Cite this as:BMJ2011;343:d4464

Footnotes

We thank Joe Egger and Kevin Konty for their review of the data analyses and the members of the Robert Wood

Johnson Foundation Menu Labeling Working Group for their continuing collaboration. We also thank all of the data

collectors who worked on this project.

Funding: This research was funded by the City of New York and by the Robert Wood Johnson Foundation Healthy

Eating Research Program (grant No 65839). All research was conducted independently of the external funder.

Competing interests: All authors have completed the Unified Competing Interest form

atwww.icmje.org/coi_disclosure.pdf(available on request from the corresponding author) and declare that (1) TD,
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CYH, CAN, and LDS had outside support for the submitted work through a grant from the Robert Wood Johnson

Foundation awarded to the New York City Department of Health and Mental Hygiene; (2) no authors have

relationships that might have an interest in the submitted work in the previous 3 years; (3) their spouses, partners, or

children have no financial relationships that may be relevant to the submitted work; and (4) no authors have non-

financial interests that may be relevant to the submitted work.

Ethical approval: Not required.

Contributors: At the time of this research, all authors were with the New York City Department of Health and Mental

Hygiene. TD led the study and is the guarantor for the paper. LDS, MTB, and CAN led the implementation of the

calorie labelling policy. MTB, TDM, LDS, and TD had the idea for the research. TD and CYH led the data collection,

undertook the analysis, and drafted the article. All authors participated in the interpretation of results, revision, and

approval of the final draft. TD and CYH had full access to the data and can take responsibility for the integrity of the

data and the accuracy of the data analysis.

Data sharing: No additional data available.

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial

License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited,

the use is non commercial and is otherwise in compliance with the license.

See:http://creativecommons.org/licenses/by-nc/2.0/andhttp://creativecommons.org/licenses/by-nc/2.0/legalcode.

SECOND RESEARCH:

Initial Study of Fast Food LabelingShows No Effect on ConsumersBy RICK NAUERT PHD Senior News EditorReviewed by John M. Grohol, Psy.D. on January 18, 2011
http://creativecommons.org/licenses/by-nc/2.0/http://creativecommons.org/licenses/by-nc/2.0/http://creativecommons.org/licenses/by-nc/2.0/http://creativecommons.org/licenses/by-nc/2.0/legalcodehttp://creativecommons.org/licenses/by-nc/2.0/legalcodehttp://creativecommons.org/licenses/by-nc/2.0/legalcodehttp://psychcentral.com/news/2011/01/18/nutritional-labeling-of-fast-food-off-to-slow-start/22731.htmlhttp://psychcentral.com/news/2011/01/18/nutritional-labeling-of-fast-food-off-to-slow-start/22731.htmlhttp://psychcentral.com/news/2011/01/18/nutritional-labeling-of-fast-food-off-to-slow-start/22731.htmlhttp://psychcentral.com/news/2011/01/18/nutritional-labeling-of-fast-food-off-to-slow-start/22731.htmlhttp://creativecommons.org/licenses/by-nc/2.0/legalcodehttp://creativecommons.org/licenses/by-nc/2.0/


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Informing individuals of the nutritional and caloric

content of fast food menus did not change consumer behavior during the first year of a newstudy.

The intervention was implemented in King County, Wash., which includes Seattle andenvirons.

Researchers are still hopeful that improved knowledge of the health content of fast foodswill lower consumption or steer individuals toward healthier food choices.

King County imposed a mandatory menu labeling regulation on all restaurant chains with 15or more locations beginning in January 2009. Restaurants had to disclose calorieinformation at the point of purchase.

Researchers found, in the 13 months after the legislation went into effect, food-purchasing

behavior at the Taco Time locations in King County was identical to that in Taco Timelocations where menu boards remained unchanged.

The total number of sales and average calories per transaction were unaffected by the menulabeling.

Given the results of prior studies, we had expected the results to be small, but we weresurprised that we could not detect even the slightest hint of changes in purchasing behavior

as a result of the legislation, said lead author Eric Finkelstein, Ph.D.

The results suggest that mandatory menu labeling, unless combined with otherinterventions, may be unlikely to significantly influence the obesity epidemic.

As part of health care reform, the federal government has plans for a nationwide launch of

mandatory nutrition information at the point of purchase for fast-food chains with 20 ormore outlets.

However, it may be that detailed nutritional information is not the best way to convey thehealth content of fast foods, said co-author Kiersten Strombotne.

For example, if you know a store offers diet and regular soda, does showing how manycalories are in regular soda really offer any relevant information? Those who want a lowercalorie drink already know to drink the diet soda.


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Finkelstein said that the lack of effects at Taco Time may be because the restaurant was

already identifying the healthier options via Healthy Highlights logos on the menu boardbefore the legislation went into effect.

A simple logo identifying which foods are healthiest may be all it takes to convey that

information to those consumers who wish to choose a healthier alternative, Finkelstein

said. The additional information appears not to have made a difference.

Finkelstein pointed out that the obesity epidemic continued to increase after the NutritionFacts Panel was required nationally for pre-packaged foods. He suggested that further

studies should be done to quantify which sources of information are most likely toencourage consumers to switch to healthier options.

Such information, however, would be too late for the U.S. Food and Drug Administration touse because its regulations on fast-food menu labeling are due out by March 23, 2011, hesaid.

The study was published in the February issue of theAmerican Journal for Preventive

Medicine .

Source:Duke Medicine New
http://www.dukehealth.org/health_library/news/20110117120044716http://www.dukehealth.org/health_library/news/20110117120044716http://www.dukehealth.org/health_library/news/20110117120044716http://www.dukehealth.org/health_library/news/20110117120044716


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3RD RESEARCH:

Weighing in on Fast Food Consumption: The Effects of Meal and Calorie Disclosures on

Consumer Fast Food Evaluations

1. ANDREA HEINTZ TANGARI2,

2. SCOT BURTON1,

3. ELIZABETH HOWLETT1,

4. YOON-NA CHO3,

5. ANASTASIA THYROFF3

Article first published online: 8 SEP 2010

DOI: 10.1111/j.1745-6606.2010.01177.x

Copyright 2010 by The American Council on Consumer Interests

Issue

Journal of Consumer Affairs

Volume 44, Issue 3, pages 431

462, Fall 2010

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1. The authors gratefully acknowledge support for this research from the Center for Retailing Excellence in the Sam M. Walton

College of Business and the Mark and Dayna Sutton Faculty Support Fund.

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Abstract

An analysis of consumers' Weblogs and two experiments address: (1) the differences in evaluations of menu

items when consumers areversus are notprovided with meal calorie information, and (2) their perception of

calorie levels of different types of meals. Consumers provided their calorie estimates for specific meals

offered by four different fast food restaurants, and an experiment assessed effects on consumer evaluations

for calorie disclosures for actual items from two of these restaurants. Results show the complex relationship

between consumer perceptions regarding the restaurants, the meals and the food items that can influence

consumers' calorie estimates and evaluations of meals in restaurants.

Given the extensive health-related risks associated with being overweight or obese, a multifaceted approach to

reduce their increasing prevalence has been suggested (Centers for Disease Control and Prevention 2009). Although

policymakers and consumer advocates have addressed this critical health issue from a number of different

perspectives, the relationship between rising obesity rates and the increased level of away-from-home food

consumption has generated a particularly high level of interest. In the last 30 years, the percentage of money spent

on food purchases outside the home has risen to 25% and now accounts for nearly one-half of Americans' total yearly

food expenditures (ERS/USDA 2009;NRA 2009). Consumers now spend almost $600 billion annually at fast food

and table-service restaurants (NRA 2009). The fast food industry, in particular, has been frequently criticized for

contributing to the national obesity problem by selling foods high in calories, saturated fat and sodium, often in

relatively large portions (Bates et al. 2009;Binkley 2006;Wansink and Chandon 2006). A documentary film, Super

Size Me by Morgan Spurlock, was nominated for an Academy Award and brought considerable national attention to

the public about the relationship between fast food choices and increases in bodyweight and diet-related health

problems. In addition, significant relationships have been found between the frequency of fast food restaurant visits

and increases in bodyweight and insulin resistance, the two primary risk factors for type 2 diabetes (Pereira et al.

2005).

Although the Nutrition Labeling and Education Act (NLEA) required standardized nutrition labels on most packaged

food products, food prepared for immediate consumption has been exempt from this legislation. (However, the NLEA

has required that relevant calorie and nutrient information be made available when a nutritional claim is made for a
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menu item.) Recent calorie disclosure mandates for restaurant chains have been passed or implemented in New

York City, Seattle, Philadelphia, Maine, Massachusetts, Oregon and California. More importantly, the US health care

reform legislation signed into law on March 23, 2010, will require calorie labeling on menus, menu boards and drive

through windows for all restaurant chains with twenty or more outlets nationally. The Food and Drug administration

was given 1 year from the date of signing of the legislation to propose specific guidelines for the national labeling of

restaurant items. A key presumption of these legislative initiatives is that a change in nutrition information on menus

in restaurants will be associated with changes in consumer choice at the point-of-purchase. Specifically, increasing

consumer awareness of the calorie levels of the less healthful food items, which are typically underestimated, may

result in more accurate product evaluations and, in turn, healthier choices. Although there have been a myriad of

recent studies examining the potential effects of labeling using different methodologies and outcome variables

(Bassett Mary et al. 2008;Burton et al. 2006;Chandon and Wansink 2007a, 2007b;Elbel et al. 2009;Harnack et al.

2008,Hassan, Shiu, and Michaelidou 2010), results have been mixed.Harnack and French (2008), in their review of

point-of-purchase calorie labeling, note that while there is some evidence of favorable effects on consumer choices,results suggest the effect may be weak or inconsistent (p. 1).

Given the high level of recent legislative activity and the inconsistent findings of recent restaurant nutrition labeling

studies (Chandon and Wansink 2007b;Elbel et al. 2009;Harnack and French 2008;Howlett et al. 2009;Kozup et al.

2003;Wansink and Chandon 2006), this research attempts to clarify the relationship between nutrition information

provision and consumer evaluations in a fast food restaurant context. Generally, there have been several recent

studies that address consumers' reactions to nutrition information disclosures for less healthy restaurant items (Bates

et al. 2009;Burton et al. 2006;Chandon and Wansink 2007b), but little research for items that are so low in calories

that consumers potentially may overestimate calorie levels. Similarly, while some studies have examined factors such

as the perceived healthiness of a restaurant that may have a halo effect on calorie estimates(Chandon and

Wansink 2007b), there has not been research, to our knowledge, that addresses how factors such as perceptions of

the healthfulness of the restaurant, meal type category (salads vs. sandwiches) and the meal calorie levels all

combine to impact consumers' calorie estimates. Drawing from the theories related to economics of information and

consumers' judgment and decision-making processes (Bettman, Johnson, and Payne 1991;Darby and Karni

1973;Ford, Smith, and Swasy 1990), we extend recent research related to potential effects of calorie provision for

restaurant meals. Our findings will help better inform public policy discussions as the pros and cons of menu nutrition

labeling are debated.

ANALYSES OF CONSUMER WEBLOG RESPONSES

The analysis of consumers' Weblogs assesses consumer reaction to a query regarding how choice behaviors are

likely to be affected if restaurants provide calorie information on menus and menu boards. Previous focus groups

have suggested that consumers are interested in having nutrition information easily available (even though it may not

always be used on every occasion), and such conclusions are consistent with findings from various polls suggesting
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consumers' favorable attitudes toward labeling (CSPI 2009b;Lando and Labiner-Wolfe 2007). Yet to our knowledge, a

qualitative approach to the potential effects of menu nutrition labeling, using a large number of respondents, has not

been previously conducted. In contrast to these methodologies, our analysis uses a type of netnography to extend

and supplement prior findings. Compared with traditional qualitative research (i.e., focus groups, depth interviews), a

netnography can be more naturalistic and unobtrusive (i.e., no participant awareness or exposure to the researcher).

In addition, by using information from various online forums that are publicly available on the Internet, netnographies

can access a much larger number of participants than more conventional qualitative methodologies (Kozinets 2002).

Specifically, 411 consumer responses were compiled from Weblog (blog) of comments posted on the New York

TimesWeb site. Although obviously not a random sample of consumer views, they could be seen as representing

readers who are aware and care about the issue. The blog noted that New York City may require calorie information

to be posted on menus or menu boards in the future, pending the Court's response to litigation by the New York

Restaurant Association to prevent the initiative. The article highlighted several menu items from popular restaurants

that have a relatively high number of calories. The article also noted that many restaurateurs were not in favor of theidea, arguing that labeling would be operationally cumbersome, extremely expensive and that labeling would be

ineffective in fighting America's obesity problem in the long term.

Data and Coding Procedures

The specific question posed to consumers was Would calorie labels affect what you order at restaurants? Following

recommended coding procedures for unstructured verbatim responses (Sonquist and Dunkelberg 1977), data were

coded by two independent coders trained by the researchers. The proportional reduction in loss reliability between

two coders for the 411 posts was greater than .90 (Rust and Cooil 1994). Discrepancies between the coders were

resolved by the two judges who met and decided on the most appropriate coding. The coders were aware of the

question asked in the blog, but not the specific nature of the research.

In addition to the potential consumer consequence associated with calorie disclosure, we were also interested in how

consumers evaluated the idea of presenting calorie information on menus and menu boards. Other than these two

primary questions of interest, the analysis revealed other relevant secondary themes. Given the additional themes,

responses were coded into seven categories based on the verbatim comments expressed in the blog. Some of the

secondary themes included how calorie labeling might affect the overall frequency of restaurant dining and how

calorie labeling might impact the nutrition content of foods offered by restaurants (Table 1).

Positive (Yes) Negative (No) To

1. Note: A total of 411 total unique bloggers posted on the blog. Responses in the table refer to the number of unique comments mad

the specific theme.

Primary themes

Calorie labels would affect what I order at a restaurant 179 43
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Positive (Yes) Negative (No) To

Calorie information should be available at restaurants 113 9

Secondary themes

Surprised by how many calories certain food items have

Calorie labels at restaurants would allow me to go out more often

It would force the restaurants to make healthier dishes

Calorie information would be helpful to have information due to health issues

I would like to see other ingredient and nutrition information

Table 1. Summary of Blog Comments

Consumer Opinions and Beliefs

The results from the blog analysis are shown inTable 1. In response to the question would calorie labels affect what

you order at restaurants, 179 out of 222 responses who addressed thisquestion in the blog answered affirmatively.

As respondents #25 and #47 mention, calorie labels would be important when making decisions at restaurants.

Respondent #25: Calorie labels would completely command what I order at a restaurant. With plans such as Weight

Watchers, it was really hard to eat out because I didn't know the point value of most foods, but if they were provided I

would feel much more comfortable knowing what I am eating.

Respondent #47: Yes, absolutely. I am very careful about my weight, having lost 60 pounds a few years back. I am

very careful to limit the foods I eat in restaurants without nutrition labeling. Having calorie labeling enables me to

branch out and eat other things. As a result, I find myself looking forward to a trip to Applebee's, which has 8 or 10

entrees with nutrition information. I'd like to see them get some competition!

In addition to responding to the main question, more than nine out of ten respondents thought that restaurants should

provide calorie information. Respondent #39 believes that including nutrition information would help address obesity

and benefit the health of the general public.

Respondent #39: I like the idea of posting nutritional facts, not only for my own knowledge, but for the general public.

In combination with more public health education (which I feel is very badly needed in this country), this move will

raise awareness about what we are eating and could definitely help with the obesity epidemic.
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Nine respondents who did not want restaurants to include calorie labels on menus or menu boards often mentioned

that they wanted to enjoy themselves at a restaurant and did not want to know about the calorie information.

Respondent #401 stated the following:

Respondent #401: I think this is a difficult situation. The consumer may be interested in what they are about to intake

in their meal, but they may be turned off by the idea of knowing how many calories they are going to consume in one

sitting. I am pretty health conscious especially at home, but when it comes to eating out I don't want to know. I just

want to enjoy my meal.

The New York Timesarticle mentioned several menu items from different restaurants that had high calorie counts.

Some respondents (twenty-seven) were surprised by the amount of calories that the menu items had. Respondent

#143 was surprised by how many calories a Caesar salad had and thought that restaurants should post calorie

information so that they start taking some responsibility.

Respondent #143: Though I hold the belief that we are all responsible for our own weight, it's increasingly difficult to

make informed choices about what were putting into our bodies. I mean, come on, 1,010 calories in a chicken

Caesar salad! It's beyond belief! That's a petite person's DAILY calorie intake and I would bet most people who order

that are eating at least 2 other meals a day. No wonder were all so fat! It may take some extra effort, but restaurants

need to start taking some responsibility. Bottom line: if a restaurant can serve a salad or any other single meal that

contains thousands of calories, then yes, weve gotten to the point where we need labels.

A number of respondents (thirty-two) mentioned how having the label information would allow them to eat out more

often because they would better understand how the meal fits into their overall diet. Another theme present in a

number of posts was that posting the calorie information probably would make restaurateurs more likely to create

healthier meals (nineteen). Respondent #123 mentioned both of these themes in his/her post.

Respondent #123: Yes!!! Put in the calorie count! I agree with everyone who has said that it would actually allow you

to eat out MORE OFTEN because you'd know what youre getting in your diet. (Maybe this would helpentice

restaurants to make the change.) I try to make smart choices when I eat out, but I'd probably choose the salad over

the steak or the chicken sandwich over the burger and apparently I'd be wrong!

Based on the blog comments, there seems to be strong public support for posting calorie information on menus and

menu boards. The blog comments, prior experimental research (Howlett et al. 2009;Wansink and Chandon 2006)

and consumer surveys (CSPI 2009b) all suggest that people, in general, have difficulty in accurately estimating the

number of calories associated with many restaurant meals. The blog responses indicated that respondents were

particularly surprised by the calorie content of menu items such as some salads and chicken sandwiches, which at

times are much less healthful than consumers expect. There are concerns that limit the generalizability of these

qualitative findings and restrict the implications that can be drawn. Thus, the next step was to conduct two
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experiments to contribute to our understanding of whether changes in menu labeling options impact consumer

responses. Experiment 1 examines how accurately consumers estimate calorie content across different restaurants

and menu choices, and we examined how prior positioning and perceptions influence consumers' calorie estimates

across both fast food restaurants and specific food item categories.

EXPERIMENT 1

As noted above, consumers mentioned that while salads from fast food restaurants are often assumed to be among

the more healthful selections, many were surprised by the high-calorie content of some Caesar salads. In Experiment

1 we examine the accuracy of consumers' calorie estimates across different fast food restaurants and meals that vary

in perceived healthfulness. If consumers' meal calorie estimates are inaccurate, and if this accuracy varies across

different meal categories (i.e., more vs. less healthful options of actual fast food salads and chicken sandwiches) and

restaurants, then this would tend to support the argument that most typical consumers would potentially benefit from

calorie information on menus to help make more informed choices.

In this experiment we address the following two questions. First, will consumers more accurately estimate the calorie

content of more healthful versus less healthful meals (potentially overestimating calories for meals that are very low in

calories while substantiallyunderestimating higher-calorie meals)? Second, how will the accuracy of consumers'

calorie estimates vary across both restaurants and meal categories for which consumers' initial perceptionsof

healthfulness vary? In addition to main effects, we propose that there is a complex interaction between the factors of

food categories (salads vs. chicken sandwiches), the meal healthfulness (more vs. less healthful versions of actual

fast food salads and chicken sandwiches) and restaurant (those perceived as offering more vs. less healthful fare).

Theoretical Rationale and Predictions

Drawing from the economics of information literature, it can be argued that specific levels for calories or nutrients

such as fat and sodium are credence attributes (Darby and Karni 1973;Ford, Smith, and Swasy 1990). That is,

typical consumers will not have accurate knowledge levels for these calories and nutrients even after repeated

consumption of the product because even trained nutritionists generally do not have the expertise needed to estimate

these levels accurately (Backstrand et al. 1997). Unless restaurants make this information easily available at the point

of purchase, it can be argued that the marginal costs of obtaining the information substantially exceed the perceived

benefits for most consumers (Nelson 1974).

Given the lack of specific information accessible in memory and the extreme difficulty of the estimation task for most

consumers, available cues will be utilized in the estimation task (Bettman, Johnson, and Payne 1991;Burton and

Blair 1991). These cues would include perceptions related to the healthfulness of the restaurant (e.g., due to its

promotion, Subway [SW] may be considered more healthy than Burger King [BK]) and meal item type (salads are

viewed as lower in calories than large hamburgers). Such informational cues are then combined with any available

calorie information (e.g., most adults should consume around 2000 calories a day) to derive estimates (Burton et al.
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2006). For these estimates, an anchoring and adjustment process seems likely (Hogarth 1980;Tversky and

Kahneman 1974). In this process, an initial starting point is determined and then, based on this anchor, subsequent

adjustments are made based on the other available cues (e.g., healthfulness of the restaurant and meal type).

Generally, because restaurant meals, in general, have been shown to be higher in calories than consumers anticipate

(Burton et al. 2006;Wansink and Chandon 2006), it may be inferred that adjustments generally are made from an

initial anchoring point that is too low. This may be due to past experiences from nutrition labeling on food product

packaging. Because the serving sizes on packages are standardized and far smaller than the average portions

served in restaurants (Bryant and Dundes 2005;Jacobson and Hurley 2002), consumers' reference points for calorie

and nutrient levels of restaurant menu items are likely to be too low.

Such conceptual arguments are consistent with recent research indicating that consumers often underestimate

calories, but estimates tend to be more accurate for lower-calorie meals from dinner house restaurants (Burton et al.

2006). Also, several other studies have found that as portion sizes increase, the extent to which consumers

underestimate calories increases as well (Chandon and Wansink 2007a, 2007b;Wansink and Chandon 2006). Basedon the past research, we offer H1a as a replication hypothesis, predicting greater underestimation of calories for less

healthful meals (meals that have relatively high-calorie content), compared with more healthful meals (meals with

relatively low-calorie content).

H1a: Consumers will underestimate calories more for unhealthful meals than healthful meals.

Most studies that have measured consumers' calorie estimates have used food items that have typically ranged from

300 calories to well over 1,500 calories (Burton et al. 2006;Chandon and Wansink 2007a, 2007b;Wansink and

Chandon 2006). These studies generally found that calorie estimates are more accurate as the calorie levels

decrease; misestimation typically follows a fairly linear pattern at intermediate levels, but responses become

nonlinear as actual calories reach extreme levels. This suggests that for verylow-calorie meals (e.g., meals less than

300 calories), consumers will overestimate calories once the level falls below a specific threshold.

Range theory (Volkmann 1951) indicates that people will make estimates within a range that is based on past

experiences or reference points. The anchoring and adjustment heuristic indicates that consumers will anchor on a

point based on their own experiences, and estimates will be biased toward that anchor or reference point (Tversky

and Kahneman 1974). Drawing from range theory as well as anchoring and adjustment, we propose that there is a

perceived range of calories and that the range is centered around an anchor point that consumers view as

appropriate for fast food items in general, and for specific categories of fast food items. Based on the pattern of

findings from the blog and other research, consumers tend to underestimate calories more substantially for foods that

are at the high end of actual calorie range. (This underestimation may be exacerbated for food categories perceived

as healthful, where the consumers' upper range is limited.) We anticipate for items that are extremely low in calories

that overestimation becomes more likely as consumers lack awareness of items that fall below their expectation

range, suggesting our H1b prediction.

H1b: Consumers will overestimate calories in very low-calorie meals.
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As suggested above, consumers often categorize food-related objects based on their perceived healthfulness (Oakes

and Slotterback 2005). For example, restaurants may be perceived as varying in the overall healthfulness of their

fare, and this in turn may impact the perceived healthfulness of their specific product offerings. In a pretest,Chandon

and Wansink (2007b)showed that consumers perceived food from SW to be significantly more healthful than food

from McDonald's. Subsequent studies showed that for meals equal in calories, consumers estimated fewer calories

for SW meals relative to comparable McDonald's meals (Chandon and Wansink 2007b). The results imply that

consumers will give relatively lower-calorie estimates to meals from restaurants that are perceived as more healthful

compared with restaurants perceived as less healthful. Consumers appear to project this healthful or unhealthful

restaurant image to the menu items. Also, some substantial differences in both actual calories consumed and

estimated calorie levels across a number of fast food restaurants have been reported (Burton, Howlett, and Tangari

2009). To extend these findings, we examine calorie estimates for items from Panera and SW (restaurants perceived

as more healthful), as well as BK and McDonald's (restaurants perceived as less healthful).1

Therefore, drawing from tenets concerning biases related to range theory and the influence of internal referencepoints on consumer estimates, we would expect that for restaurants that are perceived as healthful (unhealthful),

consumers will have lower (higher)-calorie estimates which may not be accurate. Restaurants that may be

misperceived are of particular interest. Given that consumers will have lower-calorie estimates for restaurants

perceived as more healthful, we predict that for restaurants that may be less healthful than they are perceived to be

(i.e., Panera), consumers' relatively low-calorie estimates will combine with the higher actual calorie levels to lead to a

more substantial underestimation of calories.2

H2: Accuracy of consumers' calorie estimates will differ across restaurants. Consumers will underestimate calories

more for meals from restaurants where their perceptions of healthfulness are less accurate (Panera), relative to

meals at restaurant where consumers have more accurate perceptions of the healthfulness (SW) or unhealthfulness

(McDonald's, BK) of meals.

We also propose an interaction between the restaurants, the food category and the healthfulness of the meals. First,

consider salads, which are categorized by most consumers as healthy but actually can contain a broad range of

calorie levels (Oakes and Slotterback 2005). Drawing from range theory, anchoring and adjustment, and the findings

ofChandon and Wansink (2007b), we predict that for the less healthful salads (those which do not match general

expectations for the food category), consumers will underestimate calories more for healthful than for less healthful

restaurants (H3a). In this case the healthy perceptions of the menu item and restaurant bias are not consistent with

the higher-calorie nature of the item, resulting in greater underestimation. Conversely, for restaurants perceived as

less healthful, the objective value of the less healthful salad is consistent with the restaurant perception, resulting in

more accurate perceptions.

H3a: For unhealthful salad meals, consumers will underestimate calories more for restaurants that are perceived as

more healthful (Panera and SW) than for those perceived as less healthful (McDonald's and BK).
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