ArticlePDF Available

Abstract and Figures

In this era of increasing obesity and increasing threats of legislation and regulation of food marketing practices, regulatory agencies have pointedly asked how "low-fat" nutrition claims may influence food consumption. The authors develop and test a framework that contends that low-fat nutrition labels increase food intake by (1) increasing perceptions of the appropriate serving size and (2) decreasing consumption guilt. Three studies show that low-fat labels lead all consumers--particularly those who are overweight--to overeat snack foods. Furthermore, salient objective serving-size information (e.g., "Contains 2 Servings") reduces overeating among guilt-prone, normal-weight consumers but not among overweight consumers. With consumer welfare and corporate profitability in mind, the authors suggest win-win packaging and labeling insights for public policy officials and food marketers. [ABSTRACT FROM AUTHOR]
Content may be subject to copyright.
Journal of Marketing Research
Vol. XLIII (November 2006), 605–617
© 2006, American Marketing Association
ISSN: 0022-2437 (print), 1547-7193 (electronic)
*Brian Wansink is John S. Dyson Chair of Marketing and of Nutritional
Science, Applied Economics and Management Department, Cornell Uni-
versity (e-mail: Pierre Chandon is Assistant Pro-
fessor of Marketing, INSEAD (e-mail: The
authors thank Brian Zaff at Masterfoods and Shirley Blakely at the Food
and Drug Administration for their cooperation and insights. No industry or
government agency funds sponsored this project.
In this era of increasing obesity and increasing threats of legislation
and regulation of food marketing practices, regulatory agencies have
pointedly asked how “low-fat” nutrition claims may influence food
consumption. The authors develop and test a framework that contends
that low-fat nutrition labels increase food intake by (1) increasing
perceptions of the appropriate serving size and (2) decreasing
consumption guilt. Three studies show that low-fat labels lead all
consumers—particularly those who are overweight—to overeat snack
foods. Furthermore, salient objective serving-size information (e.g.,
“Contains 2 Servings”) reduces overeating among guilt-prone, normal-
weight consumers but not among overweight consumers. With consumer
welfare and corporate profitability in mind, the authors suggest win–win
packaging and labeling insights for public policy officials and food
Can “Low-Fat” Nutrition Labels Lead to
1Following the guidelines of the World Health Organization (WHO),
people are classified as “normal weight” if their body mass index (BMI) is
between 18 kg/m2and 25 kg/m2, as “overweight” if their BMI is greater
than 25 kg/m2, and as “obese” if their BMI is greater than 30 kg/m2. The
BMI is computed as the ratio of weight, measured in kilograms, to squared
height, measured in meters.
Food companies are on trial for contributing to the grow-
ing problem of obesity in the United States and abroad.
They have been threatened with taxes, fines, restrictions,
legislation, and the possibility of being “the tobacco indus-
try of the new millennium” (Nestle 2002). Labeling is an
area of critical concern among regulators such as the U.S.
Food and Drug Administration (FDA). Although much is
known about how nutrition labels influence health beliefs
and purchase intentions (e.g., Moorman et al. 2004), the
pressing issue for the FDA is how relative nutrition claims
(e.g., low fat) influence single-occasion intake (Blakely
2005). A particularly acute concern is that low-fat labels
may lead to the overconsumption of nutrient-poor and
calorie-rich snack foods by the 65% of U.S. consumers who
are already overweight (Hedley et al. 2004).1
Although no food company would want to discourage
consumers from purchasing its products, it may be in the
firm’s interest to use relative nutrition claims to help con-
sumers better control how much they consume on a single
eating occasion (Wansink and Huckabee 2005). Consider
indulgent, hedonic foods, such as candies and snacks.
Single-occasion overconsumption of these foods can lead
not only to weight gain but also to rapid satiation (Inman
2001) and delayed repurchase. Over the long run, helping
consumers better control their consumption not only could
reduce the likelihood of adverse regulations and boycotts
but also could help promote more favorable attitudes toward
the brand and company. This may result in what Rothschild
(1999) refers to as a “win–win” policy-sensitive solution for
both companies and consumers.
This need for a policy-sensitive solution was underscored
in a series of FDA (2003) meetings, which raised three
related questions for companies such as Kraft Foods and
M&M’s/Mars (now Masterfoods): (1) How do relative
nutrition claims (e.g., low fat) influence how much people
consume on a single eating occasion? (2) Do relative nutri-
tion claims influence overweight consumers differently
from normal-weight consumers? and (3) Can serving-size
information eliminate any potential bias? To help managers
and policy makers better address these questions, we pro-
pose a framework that suggests that low-fat nutrition claims
increase consumption because they increase perceptions of
the appropriate serving size and reduce anticipated con-
sumption guilt.
We test this framework in one lab study and two natural
field studies. Study 1 establishes the main finding of the
research in the context of an open-house reception. It shows
that all people—particularly those who are overweight—eat
2Endorsed nutrition claims are those that have been tested, proved, and
ratified by an endorsing entity, such as the FDA or the American Cancer
Association (Geiger 1998). Endorsed claims specifically note the effect of
a targeted ingredient on health (Geiger 1998). These include links between
soy and heart disease, between folic acid and birth defects, or between
fiber and cancer (Wansink 2005).
more calories of snack food when it is labeled as “low fat”
than when it is labeled as “regular.” Study 2 shows that low-
fat nutrition claims lead all consumers in a lab to increase
the amount they believe to be an appropriate serving size,
regardless of whether the snack is relatively hedonic
(chocolate candies) or relatively utilitarian (granola). It fur-
ther demonstrates that low-fat claims reduce guilt, espe-
cially for people who are overweight. Study 3 shows how
relative nutrition claims and objective serving-size informa-
tion jointly influence the consumption of granola by over-
weight and normal-weight moviegoers. Following these
studies, we discuss the implications of our findings for pub-
lic policy officials, responsible food manufacturers,
researchers, and consumers who are interested in better
controlling how much they eat.
When people determine how much to eat, labels can pro-
vide both objective and subjective consumption cues.
Objective consumption cues, such as serving-size informa-
tion, explicitly suggest an amount to eat on a single occa-
sion (Caswell and Padberg 1992). Subjective consumption
cues, such as those provided by endorsed nutrition claims or
by relative nutrition claims (e.g., low fat), do not specify a
serving size.2However, they may influence how much a
person infers to be a reasonable amount to eat, and they
may influence how much pleasure or guilt a person antici-
pates feeling by eating that amount. In the following para-
graphs, we describe a framework that explains how these
key variables influence food intake (illustrated in Figure 1).
Our description foreshadows how this framework may vary
across foods and across people.
Serving-Size Inferences
A consumer’s perceptions of serving size are highly
unreliable and can unknowingly vary by as much as 20%
(Wansink 2004). With discretely packaged items, such as a
12-ounce can of a soft drink or a single-serving candy bar,
the intended serving size is obvious. In many other con-
texts, however, such as a one-pound bag of M&M’s, a large
box of granola, or a full 24-ounce bowl of macaroni and
cheese, the appropriate serving size is more ambiguous. In
the absence of salient, unambiguous serving-size informa-
tion, people must infer what the appropriate serving size is
from other cues. Although such inferences might be based
on prior experience, they might also be made on the basis of
cues that are found on a package or nutrition label.
In some ways, inferences about serving sizes are similar
to inferences made in daily conversations. Because of con-
versational norms, consumers first assume that the informa-
tion communicated to them (e.g., in a conversation or on a
label) is potentially informative and relevant to their deci-
sions (Grice 1975; Schwarz 1996). Therefore, consumers
use the information provided and their intuitive beliefs to
make inferences about missing attributes that are important
for their decision (Broniarczyk and Alba 1994). With nutri-
tion, however, such inferences can result in inappropriate
generalizations (Garretson and Burton 2000; Ippolito and
Mathios 1991; Kozup, Creyer, and Burton 2003; Moorman
and Matulich 1993; Wansink 2004). For example, Andrews,
Netemeyer, and Burton (1998) show that consumers falsely
infer that foods low in cholesterol are also low in fat. Simi-
larly, there is anecdotal evidence that some consumers erro-
neously believe that low-fat nutrition claims indicate fewer
calories (National Institutes of Health 2004). They do not
realize that when the FDA determines whether low-fat
Figure 1
Can “Low-Fat” Nutrition Labels Lead to Obesity? 607
3Although it is true that fat contains more calories per grams than either
carbohydrates or proteins, low-fat foods typically compensate for the
reduction in fat by an increase in carbohydrates (Burros 2004). As a result,
foods labeled as low fat do not, on average, contain significantly fewer
calories per serving than foods without this label (National Institutes of
Health 2004). For example, the low-fat Snackwell’s cookies developed by
Nabisco contain less fat but not fewer calories than regular cookies
because the fat is replaced with high-calorie starches and sugars.
nutrition claims are appropriate, it considers only the
amount of fat, not the number of calories.3
The ambiguity regarding serving sizes and inferential
mechanisms suggest that relative nutrition claims could cre-
ate misleading “health halos” that lead consumers to believe
that the food contains fewer calories and that the acceptable
or appropriate amount to consume is higher when the food
is described as being lower in fat. Therefore, we hypothe-
size that a relative nutrition claim communicated by a low-
fat label increases food intake because it increases a con-
sumer’s serving-size estimate.
Anticipated Consumption Pleasure and Guilt
Cognitive inferences about serving sizes are not the only
factor influencing consumption volume. A lot of research
has shown that emotions and, particularly, anticipation of
consumption pleasures and guilt can play a central role in
determining how much a person eats (Baumeister 2002;
Dhar and Simonson 1999; Shiv and Fedorikhin 1999;
Wertenbroch 1998). For example, King, Herman, and
Polivy (1987) find that people spontaneously categorize
foods in terms of the pleasure-related or guilt-related emo-
tions that they elicit. Although many studies have examined
the role of emotions in food consumption decisions (e.g.,
Andrade 2005; Shiv and Fedorikhin 1999), relatively few
have studied the role of guilt. This is surprising given that
food-related guilt is a particularly prevalent emotion among
U.S. consumers, compared with consumers from Europe or
Japan (Rozin et al. 1999).
Feelings of guilt arise because food consumption deci-
sions frequently entail a conflict between two opposite
goals: the hedonic goal of short-term pleasure gratification
versus the utilitarian goal of long-term health preservation
and enhancement. Kivetz and Keinan (2006) find that con-
sumers making hedonic choices exhibit more guilt than
consumers making utilitarian choices. Other studies show
that high-fat products are considered more hedonic than
low-fat products. For example, Wertenbroch (1998) finds
that consumers expect better taste when potato chips are
labeled as “25% fat” than when they are labeled as “75%
lean” (a frame that is known to reduce perception of fat).
This suggests that low-fat nutrition claims should lead con-
sumers to eat more because it allows them to feel less guilty
while enjoying their food.
This prediction is supported by studies that show that
guilt leads people to choose lower-fat foods. Consider a
restaurant’s dessert menu. Okada (2005) finds that people
eating at a restaurant were more likely to order “Cheesecake
deLite,” a low-fat dessert, than “Bailey’s Irish Cream
Cheesecake,” a high-fat dessert, when they were presented
side by side on the menu, but they preferred the high-fat
dessert to the low-fat dessert when each item was presented
alone. She attributes these findings to the notion that pre-
senting both options together increased the feelings of guilt
4The distinction between hedonic and utilitarian foods is relative
(Wertenbroch 1998). Among snack foods, those typically assumed to be
hedonic include foods such as potato chips, cookies, cake, candies, ice
cream, and full-calorie soft drinks. Those typically assumed to be utilitar-
ian include granola, main meals, side dishes, cereals, and sports drinks.
associated with the high-fat option. Therefore, we expect
that another way that low-fat nutrition claims increase con-
sumption is by reducing a consumer’s anticipated consump-
tion guilt.
Figure 1 also shows that feelings of guilt may vary across
different types of food and different types of people. People
are more likely to feel guilty about overeating an indulgent,
hedonic food, such as chocolate candies, than they are
about eating a food they view as relatively more utilitarian
and healthy, such as granola (Okada 2005; Wertenbroch
1998).4The guilt of overeating is also likely to be a more
powerful motivator to some people than to others. Indeed,
overweight people have a greater tendency to lose control
when eating and to have lower levels of consumption guilt
(Hays et al. 2002). Therefore, we expect that low-fat nutri-
tion labels have a stronger effect on guilt-free utilitarian
foods and overweight consumers than on guilt-prone hedo-
nic foods and regular-weight consumers. We also expect
that the difference between overweight and regular-weight
consumers is lower for utilitarian foods, which are unlikely
to trigger high levels of guilt, than for hedonic foods, which
are likely to elicit particularly strong levels of guilt among
regular-weight consumers.
Reducing the Effects of Low-Fat Nutrition Labels on
There is often a marked difference between objective
knowledge and subjective knowledge, especially in the
nutrition domain (Brucks 1985; Moorman et al. 2004).
Because of the ambiguity of sensory experience (Deighton
1984; Ha and Hoch 1989), it is unlikely that consumers
realize that they are overconsuming foods with low-fat
nutrition claims. Indeed, a wide range of studies have
shown that consumers are unable to monitor the number of
calories they consume (Livingstone and Black 2003). As a
result, we expect that consumers tend to overeat low-fat
foods but are not aware of this tendency.
A way to reduce this biased tendency to overeat foods
with low-fat labels may be to provide objective serving-size
information (e.g., “This package contains 2 servings” or
“Contains 2 Servings”). When objective serving-size infor-
mation is provided, consumers do not need to rely on low-
fat claims to infer serving size (Feldman and Lynch 1988).
Indeed, although most consumers are skeptical of health
claims, in general, they believe the salient nutrition infor-
mation on most packaging (Wansink and Huckabee 2005).
Therefore, we expect that salient serving-size information
reduces the effects of low-fat nutrition labels on
As we indicate at the bottom of Figure 1, the moderating
influence of serving size should vary depending on the
characteristics of both a food (utilitarian or hedonic) and a
person (normal weight or overweight). For example, objec-
tive serving-size information should be more effective in
reducing the effects of relative nutrition claims for normal-
weight consumers than for overweight ones.
Study 1 examines whether low-fat nutrition labels
increase the actual and estimated consumption of hedonic
chocolate candies by overweight and normal-weight con-
sumers. To achieve this, we asked adult family members
(53% males, 31 years old, 25.3 body mass index [BMI])
participating in a university open house to serve themselves
unusual colors of M&M’s (gold, teal, purple, and white),
which were clearly labeled either as “New Colors of Regu-
lar M&M’s” (regular-label condition) or as “New ‘Low-Fat’
M&M’s” (low-fat-label condition). We then measured how
many calories of M&M’s they served themselves and how
many they thought they served.
Participants were incoming students and their families
who were visiting a university open house to look at infor-
mation, videos, and interactive displays related to food sci-
ence and human nutrition. The open house was from 9:00
A.M. to 4:00 P.M. on a Friday and Saturday, and sign-in
records indicated that at least 361 people visited the area in
which these displays were located. As families entered the
display area, they were greeted by a research assistant who
welcomed them and provided a brief overview of the dis-
play area. Then, each family was taken to one of two
gallon-size serving bowls of M&M’s that had been placed
on either side of the entrance. Each family member was
given a 16-ounce bowl and sanitary gloves and was told to
help him- or herself to the M&M’s. The gallon-size bowls
were placed on separate tables, and participants could only
see the nutrition labels on the M&M’s bowl to which they
had been led. To ensure that participants would pay atten-
tion to the nutrition label, bowls were filled with unusual
colors of M&M’s (gold, teal, purple, and white). Partici-
pants in the regular-label condition saw a gallon bowl with
a professionally designed 8 ×5 inch label that read “New
Colors of Regular M&M’s.” Participants in the low-fat-label
condition saw a gallon bowl with a similar label that read
“New ‘Low-Fat’ M&M’s” (no such low-fat product is cur-
rently available on the market).
Immediately after these open-house guests had taken as
many M&M’s as they wanted, the research assistants asked
them if they wanted to be involved in a series of demonstra-
tions and short surveys about how consumers make choices
and decisions. Of the 361 visitors, 293 claimed to be of legal
age (18 and over), and 269 of these eligible adults agreed to
participate (91.8%). The research assistant then asked per-
mission to weigh their plastic bowls (which contained their
M&M’s) and handed them a half-page survey that asked
their age, gender, height, weight, nutrition knowledge, and
familiarity with M&M’s. Basic nutrition knowledge and
product familiarity were self-assessed on three-point scales
(from low to high). After participants completed the ques-
tionnaire, the research assistant asked them to estimate how
many total calories of M&M’s they had served themselves.
After participants completed the calorie estimation task, the
assistant told them that the M&M’s they had selected were
actually regular (full-calorie) M&M’s. They were then
thanked and given a bookmark, a refrigerator magnet, and a
nutrition tip sheet. Most people then took 15–20 minutes to
read the materials leisurely, visit with others, and watch the
videos before exiting out a far door. Because they had been
told that they could not eat food outside of this display area,
all but 7 (97.3%) participants finished their M&M’s in the
display area.
Following the analysis guidelines of the World Health
Organization (WHO), we classified participants as over-
weight (n = 103) or normal weight (n = 166) depending on
whether their BMI was above or below 25 kg/m2. To facili-
tate the comparison between actual and estimated consump-
tion, we converted the weight measures of the M&M’s into
calories using the information available on the manufac-
turer’s Web site. We used analyses of covariance (ANCO-
VAs) to analyze estimated and actual consumption with the
nutritional label (low fat versus regular), each participant’s
body mass (below versus above 25 kg/m2), and the interac-
tion between nutritional label and body mass. In the analy-
sis, we used each participant’s gender, age, self-assessed
nutrition knowledge, and familiarity with M&M’s as
Actual consumption. As we predicted, the low-fat label
increased consumption of M&M’s (F(1, 251) = 13.1, p<
.001). Participants ate 28.4% more M&M’s when they were
labeled as low fat (M = 244 calories) than when they were
labeled as regular (M = 190 calories). Furthermore, over-
weight participants took 16.7% more M&M’s (M = 237 calo-
ries) than normal-weight participants (M = 203 calories;
F(1, 251) = 4.3, p< .05). As we expected, the interaction
between low-fat labeling and body mass was statistically sig-
nificant (F(1, 251) = 3.9, p< .05). Low-fat labeling encour-
aged greater consumption among overweight participants,
whose intake increased by 90 calories (a 47% increase),
than among normal-weight participants, whose intake
increased by only 30 calories (a 16% increase). Contrast
tests show that the calorie increase due to low-fat labeling
was statistically significant among overweight participants
(F(1, 91) = 9.2, p< .001) but not among normal-weight par-
ticipants (F(1, 156) = 2.2, p= .13). None of the effects of
the covariates were statistically significant (p> .10).
Consumption estimation bias. As Figure 2 illustrates,
calorie estimates were not influenced by the nutrition labels
and were only marginally influenced by a person’s body
mass. In examining consumption bias (estimated less actual
calories), we performed an ANCOVA using the same factors
and covariates as in the previous analysis; this indicated that
participants underestimated the number of calories of
M&M’s by 48% (F(1, 251) = 42.5, p< .001). More impor-
tant, people who saw low-fat labels were more biased in
their calorie estimates (M = –132 calories) than those who
saw regular labels (M = –81 calories; F(1, 251) = 23.9, p<
Although the magnitude of the calorie underestimation
bias was the same for overweight and regular-weight par-
ticipants (F(1, 251) = 1.7, p= .21), the interaction between
body mass and nutrition labeling was statistically signifi-
cant (F(1, 251) = 4.5, p< .05). Low-fat labeling increased
the severity of the calorie underestimation bias by 80 calo-
ries for overweight participants and by 36 calories for
normal-weight participants. The effects of gender, self-
assessed nutrition knowledge, and familiarity were not sta-
tistically significant (p> .10), but the magnitude of the bias
Can “Low-Fat” Nutrition Labels Lead to Obesity? 609
Figure 2
decreased by .7 calories per year of age (F(1, 251) = 3.9,
p< .05), leading older participants (who tended to take
smaller amounts) to be more accurate than younger ones.
Post Hoc Marketplace Study
Because low-fat foods are believe to contain fewer calo-
ries than regular versions, it might be reasonable for a hun-
gry calorie counter to consume more candy when it is
described as low fat than when it is not. The key question
for public health is whether a low-fat claim would lead such
a person to eat so much more that it offsets the potentially
lower-calorie density of low-fat foods. To determine this,
we surveyed the fat and calorie content of all brands of
chocolate candies, bars, cookies, milk drinks, and muffins
with at least a 5% market share.
We found 17 brands that were sold with both a regular
and a low-fat version of the same product. The serving sizes
indicated on the products were similar for both versions (t =
1.08, p= .30). Although, on average, the low-fat versions
contained 59% less fat per serving than regular versions
(3.2 versus 6.7 grams; t = 7.43, p< .001), they contained
only 15% fewer calories (140 versus 170 calories; t = 4.79,
p< .01). If participants in Study 1 had eaten real low-fat
M&M’s (with the market average of 15% fewer calories
than regular chocolate candies), they would have consumed
48% less fat but 9% more total calories. This is a conserva-
tive estimate. In reality, the increase in calories is likely to
be even higher because the ingredients used to replace fat
tend to make people hungrier (Nestle 2002).
There are three key results from Study 1. First, we find
strong support for our hypothesis that low-fat nutrition
claims increase consumption. Participants consumed 28%
more candy (54 calories) when it was described as low fat
than when it was described as regular. Second, low-fat
labeling led overweight consumers to eat dramatically more
than normal-weight consumers. Third, all participants
strongly underestimated the number of calories they con-
sumed, and they were unaware that low-fat labeling influ-
enced their consumption. Therefore, the magnitude of this
calorie underestimation was particularly strong among
overweight participants, the very people for whom calorie
underestimation is most harmful.
Study 1 established that low-fat labels can lead people to
eat more without realizing that they are doing so. However,
these results do not establish why this might occur or why
this tendency is so much stronger among overweight people.
In Study 2, we examine the role of two possible mediators of
this label–consumption relationship (perceived serving size
and anticipated consumption guilt), and we do so for hedo-
nic foods (M&M’s) and more utilitarian foods (granola).
We recruited 74 adults (44% males, 38.3 years old, 24.8
BMI) on a major university campus for a study that they
were told addressed visual illusions and volume percep-
tions. In exchange for free movie coupons, each participant
was told that they would be asked about various snack
foods. Two transparent measuring cups (20-ounce capacity)
were placed in each of two separate rooms. In each room,
one cup contained 10 ounces of M&M’s (1380 calories),
and the other contained 10 ounces of regular granola (1330
calories). Half of the participants were assigned to the first
room and saw a measuring cup labeled as “Regular
M&M’s” and another labeled as “Regular Granola.” The
other half were assigned to the other room and saw one
measuring cup labeled as “Low-Fat M&M’s” and another
labeled as “Low-Fat Granola.” We chose the two snacks on
the basis of pretests, which indicated that though both foods
have similar calorie density (135–140 calories per ounce),
granola is perceived as more nutritious, more healthy, and
less hedonic than M&M’s.
Participants were given a two-page questionnaire. On the
first page, they were asked to evaluate serving sizes by esti-
mating (1) the number of ounces of the snack that would be
appropriate for a typical person to eat during a 90-minute
movie and (2) the number of ounces that would be appro-
priate for them to eat in the same situation. To help them
calibrate their estimates, there were ounce markings on the
side of each measuring cup. They were also asked to esti-
mate the total number of calories contained in each measur-
ing cup and to rate how guilty they would feel after con-
suming two ounces of each snack. The sequence of these
four questions was systematically rotated across the partici-
pants to avoid an order bias. On the back of the question-
naire, participants recorded their gender, height, and weight
and were asked to guess the purpose of the study. Using the
BMI cutoff of 25 kg/m2established by the WHO, we classi-
fied 52 participants as being normal weight and 16 as being
overweight. We then thanked the participants and debriefed
them. No one guessed the purpose of the study.
To increase the reliability of the serving-size estimates,
we analyzed the two measures of serving sizes using a
repeated measure analysis of variance. In this analysis, two
different foods (granola versus M&M’s) were within-
subjects factors and the nutritional label (low fat versus
regular), each person’s BMI (under 25 kg/m2versus above
25 kg/m2), and the nutrition label ×body mass interaction
were between-subjects factors. Participants who saw a food
labeled as low fat believed that the appropriate serving size
was 25.1% larger (F(1, 60) = 6.0, p< .01) than those who
saw the same food labeled as regular. There were no differ-
ences between overweight and normal-weight participants
(F(1, 60) = .4, p= .55), and there were no significant inter-
actions between food type (granola or M&M’s) and any of
the between-subjects factors. On average, participants esti-
mated that the appropriate consumption amount was one
ounce higher in the low-fat-label condition than in the
regular-label condition.
Serving-size estimates were the inverse of their calorie
density estimates. Participants who saw a food labeled as
low fat believed that it was much lower in calories
(F(1, 69) = 4.1, p< .05), regardless of their BMI (F(1, 69) =
2.9, p= .10). As we show in Table 1, low-fat labels
decreased calorie estimates by an average of 260 calories,
and the amount of the reduction was similar across both
M&M’s and granola (–292 versus –229 calories) and across
both low- and high-BMI groups (–254 versus –272 calo-
ries). In summary, low-fat labeling increased perceived
serving sizes and decreased perceived number of calories
across food and consumer types.
Did low-fat labeling lessen participants’ anticipation of
consumption guilt? All participants anticipated that they
would feel less guilty in the low-fat-label condition (M =
3.1 on a nine-point scale anchored by 1 = “not guilty” and
9 = “guilty”) than in the regular-label condition (M = 3.9;
F(1, 69) = 3.8, p< .05). In general, overweight participants
anticipated less guilt (M = 2.8) than regular-weight partici-
pants (M = 3.7), though the effect was only marginally sta-
tistically significant (F(1, 69) = 3.7, p< .06). As Table 1
shows, the interaction between food type and BMI was
statistically significant (F(1, 69) = 5.0, p< .05). Relatively
hedonic M&M’s elicited more guilt among normal-weight
participants (M = 4.6) than among overweight participants
(M = 3.1; F(1, 69) = 5.4, p< .05). In contrast, relatively
utilitarian granola elicited little guilt by either normal-
weight participants (M = 2.9) or overweight participants
(M = 2.5; F(1, 69) = .6, p= .44). Finally, Table 1 shows that
low-fat labels reduced the guilt among everyone associated
with consuming granola. With the more indulgent M&M’s,
however, low-fat labels reduced guilt only among over-
weight participants. In summary, consumption guilt is influ-
enced by low-fat nutrition claims but also varies with the
hedonic and utilitarian nature of the food studied and with
people’s BMI.
Building on Study 1, Study 2 provides three additional
insights: (1) Low-fat labels decrease the perception of calo-
rie density, (2) low-fat labels increase the perception of the
appropriate serving size, and (3) low-fat labels make people
feel less guilty about how much they eat. Consumers expect
that low-fat M&M’s contain 20% fewer calories than their
regular counterparts, and they expect that low-fat granola
contains 25% fewer calories. Importantly, as a result, they
expect that comparable increases in serving sizes are justi-
fied for both foods when they are labeled as low fat (21%
for M&M’s and 18% for granola). The pattern of results
regarding feelings of guilt suggests that normal-weight par-
ticipants in Study 1 responded less strongly to low-fat label-
ing than overweight participants because of their unwaver-
ing guilt. In essence, regular-weight participants behaved as
if the M&M’s remained indulgently hedonic, regardless of
whether they were labeled as low fat or regular. In contrast,
overweight participants, whose guilt is lower to begin with,
viewed the low-fat M&M’s as basically guilt free. In total,
Study 2 provides important evidence as to the mechanism
of how low-fat foods might influence food intake; we test
the mediation analysis itself in Study 3.
Ta b l e 1
Normal-Weight Participants Overweight Participants
(BMI < 25) (BMI > 25)
Regular Low-Fat Regular Low-Fat
Mediator Product Label Label Label Label
Perceived serving size M&M’s 5.8 6.5 4.3 7.1
(2.2) (3.3) (1.2) (2.3)
Granola 5.3 6.4 5.5 5.9
(1.7) (3.3) (3.0) (1.0)
Perceived calorie density
M&M’s 1545 1320 1377 942
(819) (676) (624) (578)
Granola 1013 732 765 626
(562) (458) (373) (281)
Anticipated consumption guilt
M&M’s 4.7 4.5 3.6 2.7
(3.0) (2.1) (2.4) (2.4)
Granola 3.6 2.3 3.1 1.9
(2.3) (1.5) (2.2) (1.2)
Notes: We measured perceived serving size as the number of ounces appropriate to eat during a 90-minute movie. We measured perceived calorie density
as the estimated number of calories in a ten-ounce cup. We measured anticipated consumption guilt by asking respondents to rate how they would feel after
eating two ounces of the product on a nine-point scale (1 = “not guilty,” 9 = “guilty”).
Can “Low-Fat” Nutrition Labels Lead to Obesity? 611
A purposeful limitation of Study 2 is that we did not
measure consumption. This was necessary to avoid contam-
ination between the measures of consumption and the
measures of the mediators. For example, someone might
report a small serving size and a low level of guilt to justify
high consumption. This raises the question whether provid-
ing objective serving-size information can help prevent
people from overeating when they see a low-fat label. We
address this question in Study 3. Another issue is that the
difference between overweight and regular-weight partici-
pants might have been exacerbated by the social nature of
Study 1, in which participants served themselves in the
presence of the research assistant and family members. If
anticipated guilt influences how much of a product a person
consumes, we should find little difference between over-
weight and normal-weight consumers when they are eating
a food about which they feel low levels of guilt. We exam-
ine this in Study 3 using low-fat granola.
Study 3 directly examines whether low-fat labels increase
consumption because they increase what people believe is
the appropriate serving size. We test whether providing
objective serving-size information can prevent people from
overeating a food with low-fat labels. To explore the role of
anticipated consumption guilt further, Study 3 examines the
consumption of granola (which is less hedonic than
M&M’s) in a context in which people are given large pre-
portioned quantities and in which their consumption is
unobserved by others. This also enables us to test the pre-
diction that low-fat labels had a stronger influence on over-
weight consumers in Study 1 because they felt less guilty
about overserving themselves. In this context, we expect
that low-fat labels increase consumption equally for over-
weight and regular-weight consumers.
Study 3 uses a 2 (regular versus low-fat label) ×3 (no
serving label, “Contains 1 Serving” label, “Contains 2 Serv-
ings” label) between-subjects design. We recruited 210 uni-
versity staff, undergraduates, and graduate students (49%
males, 28.7 years old, 25.1 BMI) at a large university cam-
pus to be part of a study in which they would evaluate a pilot
episode for a television show. In exchange, they were given a
free ticket to an upcoming movie, a coupon for a free dessert
at a local cafeteria, four chances to win $100 gift certificates
to a campus bookstore, and free snacks to eat during the
viewing. The study was conducted over ten sessions that
lasted from 3:30 to 5:00 P.M. on each of ten days (Tuesdays
and Thursdays for five nonconsecutive weeks). On arriving
at the dimly lit theater, participants were seated in every
other seat and asked to watch and rate a series of made-for-
television movie previews and a 60-minute pilot show called
“Hazard County.” They were also told that because it was
late in the afternoon, they would be given a cold 24-ounce
bottle of water and a bag of granola from a respected cam-
pus restaurant called The Spice Box. They were told to enjoy
as much or as little of it as they wanted.
On the basis of a pretest involving 79 similar consumers,
we selected a brand of granola mix that was well liked, and
we chose a realistic amount that was sufficient to ensure
that no one would eat all the granola within a 90-minute
period. Each participant received 640 calories (160 grams)
of granola in ziplock bags that were labeled with an attrac-
tive 3.25 ×4 inch color label. Depending on the condition,
the granola was described as either “Regular Rocky Moun-
tain Granola” or “Low-Fat Rocky Mountain Granola.
Below this, the label indicated Contains 1 Serving or Con-
tains 2 Servings, or it provided no serving-size information.
Following the completion of the previews and the show
(approximately 75 minutes), participants were given an
evaluation sheet that was consistent with the cover story.
Because we were concerned about contamination among
the ten sessions if too many questions were asked about the
granola, such questions were limited to estimations of how
many calories they believed they had eaten and to measures
of weight, height, and gender. As participants left the
theater, we weighed their granola bag while they selected a
free coupon for an upcoming movie along with a dessert
coupon. As their bag was being weighed out of their sight,
we asked them how many serving sizes they believed their
bag contained. Following this, they were thanked and dis-
missed; there was no debriefing at that time. Participants
who were interested in learning more about the study
signed an e-mail roster and were e-mailed a debriefing later
that semester after all the sessions were completed.
We eliminated some participants from analysis for the
following reasons: not staying until the end of the show (n =
7), refusing to eat granola because of dietary restrictions or
political principles (n = 4), spilling their granola on the
floor (n = 3), emptying their granola bags into their pockets
(n = 3), and failing to provide height and weight informa-
tion (n = 14). No participant consumed all the granola in the
bag while watching the show. As in Study 1, for the analy-
ses, we converted consumption volume into calories to
facilitate comparison with calorie estimates. Of the remain-
ing 179 participants, we classified 110 in the normal-weight
group and 69 in the overweight group, using the WHO 25
Do low-fat labels increase consumption of granola? To
benchmark with Study 1, we analyzed consumption in the
control condition, in which no serving-size information was
available, using an ANCOVA with three factors (nutrition
label, body mass group, and nutrition label ×body mass
group interaction) and gender as a covariate. Consistent
with our earlier findings, people who were given granola
labeled as low fat consumed 50.1% more granola than
people who were given granola labeled as regular (249 ver-
sus 165 calories; F(1, 62) = 7.8, p< .01). As in Study 1,
overweight participants consumed more granola than
normal-weight participants (256 versus 174 calories;
F(1, 62) = 8.5, p< .01). As we expected on the basis of the
guilt results from Study 2, the interaction between label and
body mass was not statistically significant (F(1, 62) = .3,
p= .59), and the increase in consumption was similar for
overweight and regular-weight participants (see Figure 3).
To examine whether perceived serving size mediates the
effects of low-fat labeling on consumption, we conducted a
mediation analysis using data from the control condition
(Baron and Kenny 1986). We first regressed the number of
calories eaten by the nutrition label and the two control
Figure 3
A: Normal-Weight Consumers (BMI < 25)
B: Overweight Consumers (BMI > 25)
Can “Low-Fat” Nutrition Labels Lead to Obesity? 613
variables (body mass group and gender). We found that
low-fat labels increased consumption by 73.9 calories after
we controlled for the effects of body mass and gender (B =
73.9, t = 3.0, p< .01). We then regressed the mediator (the
estimated number of servings in the bag) on the same
variables and found that low-fat labeling reduced the esti-
mated number of servings contained in the bag (B = –.61,
t = –3.3, p< .01). None of the other coefficients were statis-
tically significant (p> .10). Next, we regressed the depend-
ent variable on the mediator and the same control variables.
The coefficient of the variable measuring the perceived
number of servings was negative and statistically significant
(B = –65.9, t = –4.3, p< .01), indicating that people who
believed there were more servings in the bag tended to eat
In the last regression of the mediation analysis, we
regressed the number of calories eaten on low-fat labeling,
the estimated number of servings, and the control variables.
When we included the mediator in the regression, the coef-
ficient of low-fat labeling became statistically insignificant
(B = 40.5, t = 1.6, p= .11), whereas the influence of esti-
mated number of servings was significant (B = –55.1, t =
–3.4, p< .01). A Sobel (1982) test indicated that the media-
tion effect was statistically significant (z = 2.69, p< .01).
Overall, these results suggest that the estimated number of
servings mediates the effects of low-fat labeling on con-
sumption. However, because we measured serving-size esti-
mations at the end of the study, it is possible that they were
contaminated by consumption decisions. To better test the
mediating role of serving-size information, we now turn to
the analysis of the experimental manipulation of objective
serving-size information.
How does serving-size information influence consump-
tion? As a manipulation check, we examined participants’
estimates of the number of servings contained in the bag in
the two conditions in which serving-size information was
available. Their estimations were accurate when they were
given a bag with a Contains 1 Serving label (M = 1.05; t =
1.7, p= .08) or when they were given one with a Contains 2
Servings label (M = 1.92; t = –1.6, p= .10). The estimated
number of servings in these two conditions was not influ-
enced by low-fat labeling (F(1, 114) = .5, p= .48) or by the
participant’s body mass (F(1, 114) = .1, p= .76). Partici-
pants who were provided with serving-size information
knew the number of servings purported to be in their bag
and were not influenced by nutrition labels.
To examine the moderating effects of serving-size infor-
mation on consumption, we used an ANCOVA with four
factors (Contains 1 Serving, Contains 2 Servings, body
mass group, and serving-size information), all two- and
three-way interactions, and one control variable (gender).
The use of two factors for the serving-size manipulation
(Contains 1 Serving and Contains 2 Servings) was neces-
sary to examine the effects of each of the two serving-size
labels compared with the control condition. The main
effects of low-fat labeling, Contains 2 Servings condition,
and body mass group were all statistically significant
(F(1, 167) = 12.1, p< .001; F(1, 167) = 11.8, p< .001; and
F(1, 167) = 13.4, p< .001, respectively), as was the three-
way interaction among them (F(1, 167) = 4.6, p< .05). No
other interaction was statistically significant, and gender
was not significant as a covariate (p> .10). To facilitate the
discussion of the results, we conducted separate ANCOVAs
for normal-weight and overweight participants; we discuss
their results separately.
For normal-weight participants, when bags of granola
were labeled as Contains 2 Servings, consumption was
reduced by 50 calories compared with the control condition
in which no serving-size information was provided
(F(1, 103) = 4.7, p< .05). When the bags were labeled as
Contains 1 Serving, however, there were no differences
compared with the control condition (F(1, 103) = .6, p=
.44). With these normal-weight participants, the main effect
of labeling the granola as low fat was not statistically sig-
nificant (F(1, 103) = 2.2, p= .14), but its interaction with
the Contains 2 Servings manipulation was significant
(F(1, 103) = 4.3, p< .05), and its interaction with the Con-
tains 1 Serving manipulation was directionally significant
(F(1, 103) = 3.1, p= .08). We illustrate these important
interactions in Figure 3, Panel A, which focuses on normal-
weight participants. In the control condition, low-fat labels
increased consumption by 62% (F(1, 36) = 6.8, p< .01),
but this effect disappeared when granola was labeled as
Contains 1 Serving (F(1, 36) = .3, p= .85) or as Contains 2
Servings (F(1, 36) = .13, p= .72). There was no influence
of gender (p> .10). Therefore, providing objective serving-
size information was effective in eliminating the effects of
low-fat labeling on normal-weight participants.
For overweight participants, again, labeling the bag of
granola as Contains 2 Servings reduced consumption by 74
calories compared with the control condition (F(1, 62) =
7.0, p< .01), but labeling them as Contains 1 Serving had
no effect (F(1, 62) < .1, p= .88). In contrast to normal-
weight participants, however, the main effect of low-fat
labeling was statistically significant (F(1, 62) = 11.4, p<
.001), and there was no interaction with the factors that cap-
tured the Contains 1 Serving manipulation (F(1, 62) < .1,
p= .96) or the Contains 2 Servings manipulation
(F(1, 62) = 1.4, p= .23). Overweight consumers ate more
granola when it was labeled as low fat, regardless of the
serving-size information that was provided or their gender
(p> .10).
How do low-fat labels and serving-size information bias
consumption estimates? Consistent with Study 1, we exam-
ined the dissociation between actual and estimated calorie
consumption by conducting an ANCOVA with the differ-
ence between the estimated and the actual number of calo-
ries as the dependent variable and the same factors and
covariates as in the analysis of actual consumption. As in
Study 1, participants underestimated their consumption (by
45 calories or 18%; F(1, 167) = 11.4, p< .001), and this
underestimation was larger when they saw a low-fat label
than when they saw a regular label (–69 versus –21 calories;
F(1, 167) = 38.5, p< .001). This calorie underestimation
bias was also larger among overweight participants than
among normal-weight participants (–61 versus –30 calories;
F(1, 167) = 5.5, p< .05). The interaction between low-fat
labels and body mass indicated that the biased influence of
low-fat labels was even stronger among overweight partici-
pants (F(1, 167) = 3.8, p< .05). Finally, calorie underesti-
mation was also stronger in the control condition than in the
Contains 2 Servings condition (–55 versus –26 calories;
F(1, 167) = 5.5, p< .05), in which participants tended to
reduce their consumption. None of the other interactions
were statistically significant.
Post Hoc Marketplace Study
When no serving-size information was given to partici-
pants, the results of Study 3 replicated those of Study 1.
Low-fat nutrition labels increased granola consumption by
48% (80 calories). Again, an important question is whether
this increase in consumption volume overcompensates for
the reduced calorie in the low-fat granola. To determine
this, we conducted a market survey of the fat and calorie
content of regular and low-fat granola bars and cereals, and
we found 14 brands with at least a 5% market share and
sold with both a low-fat and a regular version.
Serving sizes were almost identical across both versions
(t = .99, p= .34). Although low-fat granola contained 56%
less fat per serving than regular versions (2.3 versus 5.9
grams; t = 4.0, p< .001), it contained only 10% fewer calo-
ries per serving than regular versions (196 versus 173 calo-
ries; t = 3.3, p< .01). If participants in Study 3 had eaten
real low-fat granola and if the low-fat granola had the aver-
age level of fat and calories for the category, participants
would have consumed 35% less fat from the low-fat granola
but would have consumed 33% more total calories. This is a
conservative estimate. As we noted previously, the calorie
increase would have probably been even higher because the
ingredients used to replace fat tend to make people hungrier
(Nestle 2002).
By measuring and manipulating serving sizes, Study 3
further contributes to understanding why low-fat labeling
increases consumption and what can be done to control it
more effectively. The mediation analyses show that when
no objective serving-size information was available, how
much a person ate was influenced by how many serving
sizes he or she thought was in the bag. Although this would
lead us to believe that putting salient serving-size informa-
tion on packaging would eliminate the biasing influence of
low-fat labeling, this appeared to influence only normal-
weight people. Overweight participants ate increased
amounts of granola labeled as low fat, regardless of the
serving size on the label.
This difference cannot be explained by overweight par-
ticipants not paying attention to serving-size information.
First, the manipulation checks showed that all participants
accurately identified the number of servings in the two con-
ditions in which serving-size information was provided on
the label. Second, overweight participants reduced their
overall consumption when the granola bags mentioned
Contains 2 Servings compared with the control condition in
which no serving-size information was available, indicating
that they indeed responded to serving-size information.
A more likely explanation can be found in the low levels
of guilt triggered by consuming granola. Even in the Con-
tains 2 Servings condition, when overweight participants
knew that the quantity of granola in the bag was higher than
what most people consume, they did not restrain their con-
sumption. This is consistent with the findings from Study 2,
which show that consumption creates less guilt among
overweight people than among normal-weight people.
Compared with Study 1, these effects were compounded by
normal-weight participants not being able to serve them-
selves less food, a common self-control mechanism
(Wertenbroch 1998), and therefore they ended up overeat-
ing in response to low-fat labels as much as overweight
As in Study 1, participants were unaware that low-fat
labeling increased their consumption. In the control condi-
tion, participants accurately estimated their calorie con-
sumption when the granola was labeled as regular (they
underestimated consumption only by 17 calories, or 10%).
However, they strongly underestimated actual consumption
(by 94 calories, or 38%) when the granola was labeled as
low fat. The convergence between the results of Study 1
(which were obtained preintake) and Study 3 (which were
obtained postintake) shows the robustness of our finding that
low-fat labeling increases the calorie underestimation bias.
The United States is a country of low-fat foods and high-
fat people. In this obesity-inducing environment, a priority
of the FDA is to examine whether relative nutrition claims,
such as low fat, lead to the overconsumption of high-calorie
snack foods by “at-risk” (overweight) consumers. We
develop and test a framework that shows that foods that are
labeled as low fat increase food intake by increasing per-
ceived serving sizes and by reducing anticipated consump-
tion guilt. This helps explain why the influence of relative
nutrition claims differs according to the factors associated
with guilt, such as whether a person is of a normal weight
and whether the food is hedonic. We test the predictions of
the framework in one lab study and two field experiments in
natural environments. Our key results are as follows:
•Labeling snacks as low fat increases food intake during a
single consumption occasion by up to 50%. This is robust
across both hedonic and utilitarian snacks, across young and
old consumers, across self-reported nutrition experts and
novices, in public and private consumption settings, and
regardless of whether people serve themselves or not.
•For normal-weight people, low-fat labeling increases con-
sumption most with foods that are believed to be relatively
•For overweight people, low-fat labeling increases their con-
sumption of all foods.
•Objective serving-size information prevents normal-weight
people from overeating foods labeled as low fat. It does not
influence overweight people.
The focus of these studies has been on low-fat nutrition
claims. There are many others claims or labels that might
provide similar health halos and are critical to investigate.
These can include relative nutrition claims, such as “reduced
calorie” or “low carbs,” and manufacturer-developed labels,
such as “Sensible Snacking” (Nabisco/Kraft), “Smart Spot”
(PepsiCo), and “Healthy Living” (Unilever). They can also
involve production or process-related labels, including
“organic,” “natural,” and “vitamin fortified.
Implications for Public Policy Officials
Agencies such as the FDA have created specific guide-
lines for nutrition labels and claims. These guidelines have
guaranteed that nutrition information and claims are consis-
tently accurate, and they have resulted in high public trust
in nutrition information. Yet because of the robust influence
of these health halos from labels, our findings indicate that
Can “Low-Fat” Nutrition Labels Lead to Obesity? 615
truthful labels and claims may not be sufficient to improve
eating behavior. In light of this, what can the FDA do to
prevent consumers from making erroneous inferences that
lead them to overeat?
One solution is to make serving sizes and calorie infor-
mation more salient. This would be useful for packaged
goods, whose serving-size labels are not always inspected.
Indeed low-fat labels and other nutrition-related claims are
often used on the front of a package or in the advertising
and are more salient than (and often divorced from) the
nutritional information that is on the back of the label
(Wansink, Sonka, and Hasler 2004). Increasing the salience
of serving sizes would be even more useful for the fast-food
industry, in which relative nutrition claims (e.g., low fat,
reduced calorie, low carbs) are widespread and may be par-
ticularly misleading given that nutrition labels are not
mandatory. For example, one Subway advertisement shows
that a Subway Sweet Onion Chicken Teriyaki foot-long sub
has only 10 grams of fat, whereas a Big Mac contains 33
grams of fat. In the advertisement, the Subway spokesman,
Jared Fogle, states that this means “You can eat another and
another over the course of three different meals and still not
equal the fat content of one Big Mac.” Yet the advertisement
fails to mention that the Sweet Onion Chicken Teriyaki
foot-long sub contains more calories (740 versus 600 calo-
ries) and more cholesterol (100 versus 85 milligrams) than
the Big Mac. Thus, eating three Subway subs would pro-
vide 1620 more calories and 215 more milligrams of cho-
lesterol than eating one Big Mac.
A second solution for regulators would be to increase the
threshold for relative nutrition claims. For example, to
claim “reduced calories,” the food might need to contain
33% fewer calories than the reference food rather than only
25% fewer (which is currently the case). This would
increase the likelihood that total calorie intake does not end
up being unintentionally higher for people eating low-fat
foods than for those eating regular (higher-fat) foods. In
general, it would be important to account for such health
halos when forming future guidelines or endorsements for
foods (e.g., for low carbohydrates or low sodium).
A third, and possibly the most thorough, reform would be
to change the definition of serving sizes so that it is higher
for foods that make relative nutrition claims. Currently, the
FDA (2003, pp. 29–30) defines serving sizes as “an amount
of food customarily consumed per eating occasion by per-
sons 4 years of age or older, which is expressed in a com-
mon household measure that is appropriate to the food.”
Measures of the amount of food customarily eaten per eating
occasion are obtained from the Nationwide Food Consump-
tion Surveys conducted by the U.S. Department of Agricul-
ture. The key problem is that these reference amounts are
measured for all the foods in a category, regardless of their
nutrition claims. They do not reflect how much is overeaten
because of a relative nutrition claim. Increasing serving sizes
in the case of relative nutrition claims (e.g., low fat) would
correspondingly increase the number of calories per serving
mentioned in the label for these foods. Doing so would have
a double advantage: (1) It would more accurately describe
the actual amount of food consumed, and (2) it would deter
people (at least those of normal weight) from eating signifi-
cantly more than the serving size.
Implications for Food Manufacturers
These findings also have useful implications for responsi-
ble food manufacturers. Manufacturers could consider
being more explicit and should provide more information
when defining something as low fat. This could be in the
form of the percentage reduction over the regular version
along with information on the absolute calorie level per
serving or per container. Because people infer the appropri-
ate serving size of a food from various external cues, a
manufacturer could also help consumers better control their
consumption by making packaging changes that alter their
perception of the appropriate serving size. One potentially
profitable approach may be to manufacture multipacks of
products with smaller individual servings (or subpackag-
ing). This would provide break points at which a person
would need to reassess whether he or she is going to con-
tinue eating.
Another option for food manufacturers would be to con-
sider manufacturing smaller, premium-priced packages.
Although they would not be priced competitively (per unit)
compared with the larger packages, they would satisfy the
person who was willing to trade-off value for self-control
(Wertenbroch 1998). Although such packaging would
increase production costs, the $12 billion per year diet
industry would suggest that there is a portion-predisposed
segment that would be willing to pay a premium for pack-
aging that enabled them to eat less of a food in a single
serving and to enjoy it more (Zaff 2004). For example, a
loyalty program survey of current customers of a Kraft
product indicated that 57% of them would be willing to pay
up to 15% more for portion-controlled packaging (Wansink
and Huckabee 2005).
Implications for Researchers
In marketing, much of the best nutrition research has
been focused on how nutrition labels influence health
beliefs and purchase intentions (Andrews, Netemeyer, and
Burton 1998; Balasubramanian and Cole 2002; Ford et al.
1996; Keller et al. 1997; Kozup, Creyer, and Burton 2003;
Moorman 1990, 1996; Moorman et al. 2004; Wansink and
Cheney 2005). By showing that relative nutrition claims
influence consumption, our findings open up new areas for
nutrition research. Because of the interest of the FDA and
of companies such as Kraft, Masterfoods, PepsiCo, and
Unilever, we focused on the effects of low-fat nutrition
labels. Pilot studies with other nutrition labels (e.g., reduced
calorie) showed similar results. It may be that a general
health halo can be caused by simple nutrition facts (e.g.,
100-calorie portions), by health-related claims (e.g.,
organic, high fiber), and even by general health claims (e.g.,
those made by PepsiCo’s Smart Spot icons). It would be
worthwhile to study whether these other claims influence
food intake on any given occasion, as we found for low-fat
labels, and whether they can also influence the frequency of
consumption, as previous studies of the effects of product
stockpiling have found (Chandon and Wansink 2002). Any
increase in consumption frequency would have important
implications for the obesity debate because it is often
argued that the rising obesity rates in the United States are
caused by increasing consumption frequency more than by
increasing consumption quantity per intake (Cutler, Glaeser,
and Shapiro 2003).
Another extension would be to study how these claims
influence what else a person eats. For example, there is
early evidence that consuming a food with a relative health
claim (e.g., a low-fat sandwich) can lead some consumers
to indulge in a calorie-rich dessert. As a result, consumers
may end up eating more total daily calories when going to
“healthy” restaurants than to restaurants that do not make
such claims. Because such unintended overeating might
even operate with vague claims (e.g., Subway’s “Eat fresh”
campaign), it would be difficult for the FDA to regulate. Yet
the health halos that are inferred by relative claims on labels
may offer an important conceptual tool to help investigate
the single-occasion consumption of nonfood products that
the FDA is also concerned with, such as medicines, supple-
ments, and personal care products.
Another important area for further research is to under-
stand whether the influence of relative nutrition claims on
consumption might also be related to their influence on the
taste of a food. Raghunathan, Walker, and Hoyer (2006) find
that labeling food as “healthy” reduces consumers’ taste
expectations and even reduces their postintake taste experi-
ence. Could this mean that relative nutrition claims increase
consumption because consumers trade off taste reductions
for increased consumption? According to Raghunathan,
Walker, and Hoyer, this is unlikely; they find that lower per-
ceived taste (caused by “healthy” labels) actually decreases
consumption. Still, they obtained these results by manipulat-
ing taste perceptions while the food itself was unchanged. In
reality, the ingredients used to replace the fat in low-fat
foods may leave more of a watered-down taste, which con-
sumers may try to offset by consuming more. Therefore, it
would be important to study the joint effects of nutrition
claims and actual nutrition content.
Finally, it would be useful to extend these results to addi-
tional consumer segments, additional product categories,
and additional consumption contexts. More research is nec-
essary to understand why overweight and regular-weight
consumers may respond differently to nutrition claims. For
example, studies have shown that overweight and regular-
weight consumers have similar estimations of portion sizes
(Chandon and Wansink 2007). This implies that emotional
differences rather than cognitive ones may underlie the dif-
ferent behavior of these two groups. In general, the effects
of the message are also influenced by consumers’ motiva-
tion and ability to process nutrition information (Moorman
et al. 2004). Poor nutrition knowledge might lead some con-
sumers to focus exclusively on fat content rather than on
calorie or other nutrient information. This could lead them
to believe that they can safely eat more when the product is
labeled as low fat. Conversely, not all consumers have nutri-
tion or weight-loss as an objective in their lives, and heavy-
handed regulation and nutrition education programs could
increase the current consumer backlash against diet and
nutrition messages (Patterson et al. 2001). To make matters
even more difficult, recent research on willful ignorance
indicates that even highly involved consumers may actively
ignore nutrition information to avoid the negative emotions
that may arise if the food is less nutritious than they had
thought (Ehrich and Irwin 2005).
Given these concerns and the generally disappointing
results of educational efforts aimed at increasing con-
sumers’ objective knowledge of nutrition, a provocative
idea might be to enhance consumers’ subjective nutrition
knowledge (i.e., their perception of how knowledgeable
they are about nutrition). In a series of studies, Moorman
and colleagues (2004) manipulate subjective nutrition
knowledge through biased feedback on objective knowl-
edge tests. They find that because of the desire for self-
consistency, high levels of subjective nutrition knowledge
led people to restrict their search to products within health-
ful product categories.
People are at a point of development in which much of
the incremental improvement in their life span, and espe-
cially in their quality of life, is likely to come more from
behavioral changes in lifestyle than from new medical treat-
ments (Wansink 2006). When it comes to contributing to
the life span and quality of life in the next generations,
well-intentioned marketers can help lead the movement
toward behavior change. Obesity is a good place to start.
Andrade, Eduardo B. (2005), “Behavioral Consequences of
Affect: Combining Evaluative and Regulatory Mechanisms,”
Journal of Consumer Research, 32 (3), 355–62.
Andrews, J. Craig, Richard G. Netemeyer, and Scot Burton
(1998), “Consumer Generalization of Nutrient Content Claims
in Advertising,Journal of Marketing, 62 (October), 62–75.
Balasubramanian, Siva K. and Catherine Cole (2002), “Con-
sumers’ Search and Use of Nutrition Information: The Chal-
lenge and Promise of the Nutrition Labeling and Education
Act,” Journal of Marketing, 66 (July), 112–27.
Baron, Reuben M. and David A. Kenny (1986), “The Moderator-
Mediator Variable Distinction in Social Psychological Research:
Conceptual, Strategic, and Statistical Considerations,Journal
of Personality and Social Psychology, 51 (6), 1173–82.
Baumeister, Roy F. (2002), “Yielding to Temptation: Self-Control
Failure, Impulsive Purchasing, and Consumer Behavior,” Jour-
nal of Consumer Research, 28 (4), 670–76.
Blakely, Shirley R. (2005), Personal correspondence, Food and
Drug Administration, Rockville, MD (June 2).
Broniarczyk, Susan M. and Joseph W. Alba (1994), “The Role of
Consumers’ Intuitions in Inference Making,Journal of Con-
sumer Research, 21 (3), 393–407.
Brucks, Merrie (1985), “The Effects of Product Class Knowledge
on Information Search Behavior,Journal of Consumer
Research, 12 (June), 1–16.
Burros, Marian (2004), “Eating Well; New ‘Low-Carb’ Foods
Aren’t All-You-Can-Eat,” The New York Times, (April 14), B1.
Caswell, Julie A. and Daniel I. Padberg (1992), “Toward a More
Comprehensive Theory of Food Labels,American Journal of
Agricultural Economics, 74 (2), 460–68.
Chandon, Pierre and Brian Wansink (2002), “When Are Stock-
piled Products Consumed Faster? A Convenience–Salience
Framework of Postpurchase Consumption Incidence and Quan-
tity,Journal of Marketing Research, 39 (August), 321–35.
——— and ——— (2007), “Is Obesity Caused by Calorie Under-
estimation? A Psychophysical Model of Fast-Food Meal Size
Estimation,” Journal of Marketing Research, 44 (February),
Cutler, David, Edward Glaeser, and Jesse Shapiro (2003), “Why
Have Americans Become More Obese?” Journal of Economic
Perspectives, 17 (3), 93–118.
Deighton, John (1984), “The Interaction of Advertising and Evi-
dence,” Journal of Consumer Research, 11 (3), 763–70.
Dhar, Ravi and Itamar Simonson (1999), “Making Complemen-
tary Choices in Consumption Episodes: Highlighting Versus
Balancing,” Journal of Marketing Research, 36 (February),
Can “Low-Fat” Nutrition Labels Lead to Obesity? 617
Ehrich, Kristine R. and Julie R. Irwin (2005), “Willful Ignorance
in the Request for Product Attribute Information,Journal of
Marketing Research, 42 (August), 266–77.
FDA (2003), “Exploring the Link Between Weight Management
and Food Labels and Packaging,” public workshop held at the
National Institutes of Health, Bethesda, MD (November 20).
Feldman, Jack M. and John G. Lynch Jr. (1988), “Self-Generated
Validity and Other Effects of Measurement on Belief, Attitude,
Intention, and Behavior,Journal of Applied Psychology, 73 (3),
Ford, Gary T., Manoj Hastak, Anusree Mitra, and Debra Jones
Ringold (1996), “Can Consumers Interpret Nutrition Informa-
tion in the Presence of a Health Claim? A Laboratory Investiga-
tion,” Journal of Public Policy & Marketing, 15 (Spring),
Garretson, Judith A. and Scot Burton (2000), “Effects of Nutrition
Facts Panel Values, Nutrition Claims, and Health Claims on
Consumer Attitudes, Perceptions of Disease-Related Risks, and
Trust, Journal of Public Policy & Marketing, 19 (Fall),
Geiger, Constance J. (1998), “Health Claims: History, Current
Regulatory Status, and Consumer Research,Journal of the
American Dietetic Association, 98 (11), 1312–22.
Grice, H.P. (1975), “Logic and Conversation,” in Syntax and
Semantics: Speech Acts, Vol. 3, P. Cole and J.L. Morgan, eds.
New York: Academic Press, 41–58.
Ha, Young-Won and Stephen J. Hoch (1989), “Ambiguity, Pro-
cessing Strategy, and Advertising-Evidence Interactions,” Jour-
nal of Consumer Research, 16 (3), 354–60.
Hays, Nicholas P., Gaston P. Bathalon, Megan A. McCrory,
Ronenn Roubenoff, Ruth Lipman, and Susan B. Roberts (2002),
“Eating Behavior Correlates of Adult Weight Gain and Obesity
in Healthy Women Aged 55-65 Y,American Journal of Clini-
cal Nutrition, 75 (3), 476–83.
Hedley, Allison A., Cynthia L. Ogden, Clifford L. Johnson, Mar-
garet D. Carroll, Lester R. Curtin, and Katherine M. Flegal
(2004), “Prevalence of Overweight and Obesity Among U.S.
Children, Adolescents, and Adults, 1999-2002,” Journal of the
American Medical Association, 291 (23), 2847–50.
Inman, J. Jeffrey (2001), “The Role of Sensory-Specific Satiety in
Attribute-Level Variety Seeking,” Journal of Consumer
Research, 28 (1), 105–20.
Ippolito, Pauline M. and Alan D. Mathios (1991), “Health Claims
in Food Marketing: Evidence on Knowledge and Behavior in
the Cereal Market,” Journal of Public Policy & Marketing, 10
(Spring), 15–32.
Keller, Scott B., Mike Landry, Jeanne Olson, Anne M. Velliquette,
Scot Burton, and J. Craig Andrews (1997), “The Effects of
Nutrition Package Claims, Nutrition Facts Panels, and Motiva-
tion to Process Nutrition Information on Consumer Product
Evaluations,Journal of Public Policy & Marketing, 16 (Fall),
King, G.A., C. Peter Herman, and Janet Polivy (1987), “Food Per-
ception in Dieters and Non-Dieters,” Appetite, 8 (2), 147–58.
Kivetz, Ran and Anat Keinan (2006), “Repenting Hyperopia: An
Analysis of Self-Control Regrets,Journal of Consumer
Research, 33 (September), 273–82.
Kozup, John C., Elizabeth H. Creyer, and Scot Burton (2003),
“Making Healthful Food Choices: The Influence of Health
Claims and Nutrition Information on Consumers’ Evaluations
of Packaged Food Products and Restaurant Menu Items,Jour-
nal of Marketing, 67 (April), 19–34.
Livingstone, M. Barbara E. and Alison E. Black (2003), “Markers
of the Validity of Reported Energy Intake,” Journal of Nutrition,
133 (3), 895S–920S.
Moorman, Christine (1990), “The Effects of Stimulus and Con-
sumer Characteristics on the Utilization of Nutrition Informa-
tion,” Journal of Consumer Research, 17 (3), 362–74.
——— (1996), “A Quasi Experiment to Assess the Consumer and
Informational Determinants of Nutrition Information,” Journal
of Public Policy & Marketing, 15 (Spring), 28–44.
———, Kristin Diehl, David Brinberg, and Blair Kidwell (2004),
“Subjective Knowledge, Search Locations, and Consumer
Choice,” Journal of Consumer Research, 31 (3), 673–80.
——— and Erika Matulich (1993), “A Model of Consumers’ Pre-
ventive Health Behaviors: The Role of Health Motivation and
Health Ability,Journal of Consumer Research, 20 (2),
National Institutes of Health (2004), “Diet Myths,” NIH Publica-
tion No. 04-4561, Bethesda, MD, (March), (accessed February
2, 2006), [available at
Nestle, Marion (2002), Food Politics: How the Food Industry
Influences Nutrition and Health. Berkeley: University of Cali-
fornia Press.
Okada, Erica Mina (2005), “Justification Effects on Consumer
Choice of Hedonic and Utilitarian Goods,” Journal of Market-
ing Research, 42 (February), 43–53.
Patterson, Ruth E., Jessie A. Satia, Alan R. Kristal, Marian L. Neu-
houser, and Adam Drewnowski (2001), “Is There a Consumer
Backlash Against the Diet and Health Message?” Journal of the
American Dietetic Association, 101 (1), 37–41.
Raghunathan, Rajagopal, Rebecca E. Walker, and Wayne D. Hoyer
(2006), “The Unhealthy = Tasty Intuition and Its Effects on
Taste Inferences, Enjoyment, and Choice of Food Products,”
Journal of Marketing, 70 (October), 170–84.
Rothschild, Michael L. (1999), “Carrots, Sticks, and Promises: A
Conceptual Framework for the Management of Public Health
and Social Issue Behaviors,Journal of Marketing, 63 (Octo-
ber), 24–37.
Rozin, Paul, C. Fischler, S. Imada, A. Sarubin, and A. Wrzes-
niewski (1999), “Attitudes to Food and the Role of Food in Life
in the U.S.A., Japan, Flemish Belgium and France: Possible
Implications for the Diet-Health Debate,” Appetite, 33 (2),
Schwarz, Norbert (1996), Cognition and Communication: Judg-
mental Biases, Research Methods and the Logic of Conversa-
tion. Hillsdale, NJ: Lawrence Erlbaum Associates.
Shiv, Baba and Alexander Fedorikhin (1999), “Heart and Mind in
Conflict: The Interplay of Affect and Cognition in Consumer
Decision Making,” Journal of Consumer Research, 26 (Decem-
ber), 278–92.
Sobel, Michael E. (1982), “Asymptotic Confidence Intervals for
Indirect Effects in Structural Equation Models,” in Sociological
Methodology, S. Leinhart, ed. San Francisco: Jossey-Bass,
Wansink, Brian (2004), “Environmental Factors that Increase the
Food Intake and Consumption Volume of Unknowing Con-
sumers,” Annual Review of Nutrition, 24, 455–79.
——— (2005), Marketing Nutrition. Champaign: University of
Illinois Press.
——— (2006), Mindless Eating: Why We Eat More Than We
Think. New York: Bantam-Dell.
——— and Matthew M. Cheney (2005), “Leveraging FDA Health
Claims,” Journal of Consumer Affairs, 39 (2), 386–98.
——— and Mike Huckabee (2005), “De-Marketing Obesity,”
California Management Review, 47 (4), 6–18.
———, Steven T. Sonka, and Clare M. Hasler (2004), “Front-
Label Health Claims: When Less Is More,Food Policy, 29 (6),
Wertenbroch, Klaus (1998), “Consumption Self-Control via Pur-
chase Quantity Rationing,” Marketing Science, 17 (4), 317–37.
Zaff, Brian D. (2004), Personal correspondence, M&M’s/Master-
foods, Hackensack, NJ, (May 5).
... Within associated emotions, positive and negative are considered important emotions in healthy food consumption contexts since consumers generally have two conflicting food consumption values: the utilitarian value of staying healthy and the hedonic value of enjoyment [28][29][30]. Negative emotions arise during an unpleasant emotional state. For example, feelings of guilt and/or worry stem from the belief that one thinks that he/she is doing something wrong or undesirable [28]. ...
... Conversely, positive emotions (e.g., pleasure, joy, desire, satisfaction) are part of a pleased, happy, and delighted emotional state. In a food consumption context, these emotions can stem from the oro-sensory stimulation of eating food (e.g., taste or palatability), satisfying one's hunger [32], or achieving one's diet goals, especially in a health priming consumption context [30]. Although the role of emotion in consumer behaviour and marketing is well-documented (see [19,33] for an overview), there is limited research that combines emotions with the stated preferences (e.g., discrete choice experiments). ...
... Thus, in a healthy food consumption context, associated positive emotions from health benefits are more important than taste. These associated emotions may influence which actions to take [23,30], resulting in positive behavioural intentions (e.g., purchase intentions or choice). ...
p>This work examines the associated emotions of consumers transmitted from extrinsic attributes (fat‐related nutrition claims (full‐fat, low‐fat, and fat‐free) and ingredient features (plain, berries, and double chocolate chunk)) labelled on yoghurt packages. It differentiates by consumption context (health versus indulgent) at the time of the survey and studies the relationship between the associated emotions (e.g., positive versus negative) attached to extrinsic attributes and the actual choices. The research was conducted in the Netherlands in 2019, with 209 regular consumers of yoghurt. Participants were divided into two treatments according to each consumption context and a control group (no context); they were instructed to imagine purchasing yoghurt to consume it as a healthy snack or as a dessert or received no instructions. After choosing their preferred option from a discrete choice experiment, participants indicated how the choice made them feel from a list of emotions. The results revealed significant differences between positive emotional profiles for choosing healthy (low‐fat) yoghurts with berries and negative profiles for choosing less healthy alternatives (full‐fat) with double chocolate chunk sensory features. The findings from a random parameter logit model showed that participants who continuously chose the same type of yoghurt in all choice tasks selected mostly positive rather than negative emotions. The overall findings suggest that the associated emotions affect yoghurt choices. However, the emotions were mainly affected by the consumption context.</p
... Growing evidence also shows that Health and Nutrition (H&N) claims have become increasingly important for consumers' decision-making in the past 20 years. These claims have been increasing encountered on food product packaging, and increasing reported of these claims as an information source for consumers has been reported when engaged in making purchase decisions (Garretson and Burton, 2000;Kozup, Creyer and Burton, 2003;Wansink and Chandon, 2006;Bublitz, Peracchio and Block, 2010). ...
... Table 1 summarises the gaps identified in the extant literature. Among all the research on the frames of H&N claims, there is a lack of research to investigate the new marketing phrases in framing H&N claims -Absence of quantitative empirical evidence on the interaction of maximiser and H&N claims -Future research is invited for more in-depth research on different types of nutrition claims and their effect on food purchase and intake -Future research is invited to identify the conditions under which purchase intention carrying different types of claims increases or decreases (André, Chandon and Haws, 2019) (Wansink and Chandon, 2006) (Belei et al., 2012) (Finkelstein and Fishbach, 2010) Language intensity -Absence of a combined linguistic and psychological perspective to understand the effect of language intensity on consumer's responses - ...
... It is important to acknowledge that even with government restrictions and regulations, the design and choices of food labels displayed on food packaging can be unintentionally misleading. FOP food labels can make the benefits more salient by drawing customers full attention to only one attribute of the food, rather than a holistic overview of the food product's nutritional content, which as a result causes consumers to overlook the food product's negative attributes and consume more than they should (Wansink and Chandon, 2006;Kessler, 2010;Swinburn et al., 2011;Chandon, 2013;Nestle and Nesheim, 2019). This is particularly true for consumers that either have busy lifestyles or those consumers that do not have the skills, knowledge or motivation to choose healthier food products (Kees, Burton and Andrews, 2015). ...
This thesis explores the use and effects of maximisers when included within Health and Nutrition (H&N) claims on food product packaging, with direct relevance for industry practice. Four separate studies were carried out in support of this thesis, one field study and three online experimental studies. The effects of the maximiser language device were investigated through an online field experiment, conducted through the Facebook Ads Manager platform, with the results demonstrating that the use of maximisers has a positive effect on product likeability among Facebook users. The first online experimental study then demonstrated the informality features of maximisers, and highlighted the importance of consumer perceived congruence bet ween the language used in advertising a product and the retail environment in which the product is encountered. Results from this study showed that the used of maximisers in H&N claims has a positive direct effect on product likeability. The second online experimental study extended on the concept of perceived congruence from the first online study, investigating the congruence between the use of language and customer comments and reviews, and its effect on perceptions of and purchase intentions towards a product. The study demonstrated the sincerity and affirmation features of maximisers, and showed the interaction of these features with online reviews, with the presence of maximisers having a moderating influence of product perceptions when bad reviews are present. The third and final online experimental study tested the effect of maximisers in a realistic setting, investigating the effects of cognitive load on evaluations of and purchase intentions towards a product. The findings showed maximisers work effectively when consumers are cognitively available, with a reversed effect apparent when consumers are subjected to a high cognitive load. The findings from the experimental studies have potential for impact in industry practice in the marketing and advertising of food products, and for the design of food packaging, as well as for policy-makers aiming to protect consumers and consumer interests related to food advertising.
... Guilt elicits positive consumer responses to marketing communication related to charities (Hibbert et al. 2007), fair trade products (Hwang and Kim 2018), sustainability (Muralidharan and Sheehan 2018), green consumption (Chang 2012), and cause-related marketing (Coleman et al. 2020). Guilt is also associated with self-regulation and consumption experience, which has significant implications for marketing strategy and tactics (Wansink and Chandon 2006;Kivetz and Keinan 2006;Hagtvedt and Patrick 2016). For instance, consumers feel guilty while consuming luxury brands (Hagtvedt and Patrick 2016), hedonic products (Baghi and Antonetti 2017), and vice products (Chen and Sengupta 2014). ...
... All these articles appear in the clusters in the co-citation analysis, validating their influence on the sample. Wansink and Chandon (2006) is the most impactful article with 498 GC. However, it has not impacted the sample of articles drawn for this study, as revealed by the low LC (6 citations). ...
As a self-conscious moral emotion, guilt is a motivational force behind internalized moral standards that cause moral behavior. Marketers have been harnessing the strength of this motivational force to elicit positive consumer responses through guilt appeal in marketing communication. Guilt also affects the self-regulation of consumers and hence influences their consumption decisions. Literature on guilt in marketing has accumulated in these two subdomains in the last few decades. This study attempts to consolidate past literature by deciphering the intellectual structure. In the extant literature, information on the research landscape covering the most productive and impactful nations, institutions, journals, authors, and articles that have made significant contributions to the field is missing and constitutes a critical research gap. We want to identify these and fill the gap through this study. To achieve these objectives, we applied bibliometric techniques to 199 articles systematically drawn from the Scopus database that appeared between the years 1983 to 2021. This study identifies the most productive and impactful nations, institutions, journals, authors, and articles that have made significant contributions to the field. Further, it also deciphers the intellectual structure through the article co-citation analysis that reveals three clusters. Cluster 1 deals with foundational work on guilt; Cluster 2 explores consumption guilt in intrapersonal and interpersonal contexts; Cluster 3 investigates the guilt appeal in marketing communication.
... Instead, impaired control diminished with the health cue while the expected consumption increased. These results could be explained by the fact that health cues would artificially create a feeling of control over consumption, which would lead individuals to be more indulgent (Chandon & Wansink, 2007;Chernev, 2011;Provencher et al., 2009;Wansink & Chandon, 2006). ...
Full-text available
Research on food psychology demonstrates that epicurean eating tendencies (i.e., esthetic appreciation of the sensory and symbolic value of food), similar to health concerns, tend to be associated with more regulated eating behaviors. Given that wine is already a product that is more pleasure-oriented, the question to be addressed here is whether such epicurean tendencies exert a similar effect in terms of moderating wine consumption. Two online studies demonstrate that, contrary to this suggestion, people with epicurean drinking tendencies in fact report drinking wine more frequently, and in larger quantities, than those with health beliefs. That said, when such pleasure is explicitly emphasized through textual cues, it appears to promote more regulated wine consumption. Impaired control mediates the effects of drinking tendencies as well as the effects of cueing on wine consumption. These results highlight how stressing epicurean pleasure might prove to be an effective strategy for those marketers and public authorities wanting to promote responsible wine consumption. Success in this regard might depend on whether it is the perception of the product that is cued rather than the consumers' self-perceived wine consumption.
... (Burton, Cook, Howlett and Newman 2014;Chandon and Wansink 2007;Mariotti, Kalonji, Huneau and Margaritis 2010)  Health claims can mislead people into choosing less healthy food or increasing energy intake. (Talati et al. 2018;Wansink and Chandon 2006)  The effects of health claims vary across products, based on the taste and healthiness inferences made. (André, Chandon and Haws 2019;Kiesel and Villas-Boas 2013) The effects of specific health claims vary across counties. ...
Full-text available
Health claims on food packaging can focus on the presence of good (vs. the absence of bad) and the preservation of nature (vs. nutritional improvements). We study the frequency of use of four resulting types of claims (“clean,” “whole,” “diet,” and “enriched”) in three categories over the past ten years and contrast it with the preferences and associations of American and French consumers. Focusing on breakfast cereals, we find a strong match in France but a mismatch in the United States, where marketers’ claim use is negatively correlated with consumers’ claim preferences. The mismatch arises from the underuse of presence-focused and nutrition-based “enriched” claims (e.g., “added calcium”) and the overuse of absence-focused and nutrition-based “diet” claims (e.g., “low fat”). The mismatch is more pronounced among privately-owned companies than among public companies, which tend to claim that their products are healthy in the way that consumers prefer.
... Consumer researchers devote significant efforts to examination of food-related consumer habits and attitudes. Previous studies show a devotion of consumer psychology studies to better understand nutrition labels and the effect of misunderstanding nutrition claims on consumer behavior (Suher et al., 2016;Wansink & Chandon, 2006). Consumer confusion has also been researched along with its causes and consequences in food and nutrition aspect; confusion's effects on nutrition literacy and consumer behavior have been of special interest to researchers (Hall-Phillips & Shah, 2017;Spiteri Cornish & Moraes, 2015). ...
... According to existing research, the process of calorie content estimation is still under discussion. Calorie content estimation is usually done in a largely heuristic way, and it is influenced by many factors, including package shape [1], ingredient lists [25], perceived healthiness [26,27], type of food, and food volume. For example, Koo and Suk [1] suggested that the shape of packaging influenced consumers' estimation of calorie content by its visual image. ...
Full-text available
Whether for improving health or keeping in shape, consumers are beginning to pay attention to calorie intake. However, although a growing number of studies have focused on the impact of food attributes on consumers, the sensory correspondence between food shape and calorie estimation is an underresearched topic. This review, therefore, reports on three studies investigating the effect of food shape on calorie content estimation, whereby participants perceived food in a square shape to have a higher calorie content than food in a circular shape. Perceived food weight plays a mediating role in the relationship between food shape and calorie estimation. Moreover, the more mindful participants were about calorie intake, the weaker the mediation effect of perceived weight. Conversely, the mediation effect of perceived weight was stronger for people who did not care about their calorie intake. These findings break novel ground by presenting food shape as a relevant factor for calorie content estimation. It not only pays attention to the information brought by the visual sense of food, but also complements the relevant literature in the field of food marketing, and has implications for marketing management.
... Moreover, there is evidence that NCs and HCs may increase food intake. For example, Wansink and Chandon (2006) discover that participants consumed more snack food when it was labelled as 'low-fat'. ...
This systematic literature review collected and summarized research on consumer preferences and the purchase behaviour of food products with nutritional claims (NCs) and health claims (HCs), to reconcile, and expand upon, the findings of previous studies. First, considering that consumer behaviour is affected by a wide range of factors, to narrow the research we used a theoretical framework and divided the determinants of the effects of NCs and HCs on consumers’ preferences and purchasing behaviour into consumer characteristics, product characteristics, and consumers’ personal processes, using the quality perception process. Second, since most studies were conducted within the European Union (EU), we collected the scientific literature from 2006, when the law on NCs and HCs was harmonized in the EU, until September 2020. This same period was used to scan for other studies outside EU who used similar terminology on NCs and HCs. In total, 125 articles were found to be relevant for further analysis. The results showed that consumer characteristics such as familiarity, nutritional knowledge, motivation, and demographics affected choices. Extrinsic product characteristics, such as price, brand, colour, packaging shape and NCs and HCs, affected purchase decisions. Taste was the most important intrinsic characteristic, and consumers are not willing to sacrifice the pleasure of sensory function for health benefits. Perceived healthiness, understanding of the claims, liking and use were important factors that affected consumers’ personal processes in purchasing food with NCs and HCs. A challenge for future research is to consider exploiting new technologies and more realistic experimental methods to provide information that represents as close as possible consumers’ behaviour in real-life situations.
... The final correlation to be mentioned in this article concerns IPA and willingness to buy (WB). According to Wansink and Chandon (2006), nutrition content claims influence customer behaviour. Roberto et al. (2012) obtained similar results. ...
Purpose The objective of the study is to explain how health orientation influences attitude towards paying attention to nutrition claims (NCs), intention to pay attention to NCs, and willingness to buy products containing NCs. Design/methodology/approach In the first study, conducted amongst 770 respondents using the CAWI (Computer-Assisted Web Interview) method, the authors investigated the role of health orientation in explaining intention to pay attention to NCs and willingness to buy products with NCs. The theory of planned behaviour was used as the main theoretical framework. In the second online experiment, carried out amongst 485 respondents, the impact of health orientation on attitude towards the label containing NC and on NC product purchase intention was studied. Findings The authors revealed that health orientation plays a significant (direct and indirect) role in explaining attitude towards paying attention to NCs, and intention to pay attention to NCs, as well as NC product purchase intention. Originality/value Health orientation appeared to be an important determinant of selecting products with NCs. Consumers' intent to choose products containing claims is mainly determined according to their attitudes driven by health orientation and outcome expectancy. Consequently, intention to pay attention to NCs is strongly related to intention to buy products containing claims.
Public health agencies have designed and implemented interventions to control the global obesity epidemic using healthfulness messaging and policy changes such as taxation. These changes in the policy environment and marketplace dynamics have shifted consumer trends and have challenged food producers in the industry. The following questions are considered in the food industry in such a context: (i) Should firms offer similar or very different quality offerings?, (ii) How should a firm's positioning strategies change as consumers' perceptions of healthful messaging and taxation change?, and (iii) How do these factors impact firm profits and social welfare? Using an analytical model of duopolistic competition, we highlight that both firm profits as well as social welfare could increase when the importance of healthfulness messaging to consumers increases. Furthermore, we show that increased taxation could reduce the quality gap between alternatives in the market, forcing firms to lower prices. In contrast, when healthfulness messaging becomes more important to consumers, the quality gap between both firms increases. Our results provide important implications for public policy as well as firm profits as a consequence of the strategic decisions of firms in a health policy context. This article is protected by copyright. All rights reserved
Full-text available
In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators. (46 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Full-text available
The authors report the results of a laboratory experiment that investigates whether consumers can evaluate nutrition information in the presence of a health claim. Results show that both health claims and nutrition information influence beliefs about product healthfulness. However, health claims do not influence the processing of nutrition information on a food label. Rather, health claims and nutrition information have independent effects on consumer beliefs. The authors discuss the implications of these findings for the Food and Drug Administration policy on limiting health claims.
Although most research on consumer decision making has focused on individual choices, the majority of products are purchased and consumed with other products (e.g., an appetizer, an entree, and a dessert) as part of the same purchase and/or consumption episode (e.g., a meal). The authors investigate consumption episode effects, whereby the attribute levels of one component affect the chosen levels of another component (e.g., the effect of consuming a tasty, unhealthy entree on the experience and likelihood of choosing a tasty, unhealthy dessert). Building on a distinction between goals and resources, the authors propose that (1) in episodes involving a tradeoff between a goal (e.g., pleasure) and a resource (e.g., money), consumers tend to highlight either goal fulfillment or resource conservation by selecting similar attribute levels for items consumed in the same episode (e.g., a tasty, expensive appetizer and a tasty, expensive entree on one occasion and less tasty, less expensive items on another occasion) and (2) if each choice involves a tradeoff between two goals (e.g., pleasure and good health), consumers tend to balance attribute levels (e.g., in each episode have one tasty item and one healthy item). These predictions are supported in a series of studies, with a total of approximately 2650 respondents, that also examined rival explanations and the boundaries of consumption episode effects. The authors discuss the theoretical and practical implications of the findings.
The author presents a framework that considers public health and social issue behaviors and is based on self-interest, exchange, competition, free choice, and externalities. Targets that are prone, resistant, or unable to respond to the manager's goal behave on the basis of their motivation, opportunity, and ability and on a manager's use of the strategies and tactics inherent in education, marketing, and law.
Although considerable research exists on consumer processing of nutrition labeling and package claims, less is known about consumer interpretation of nutrient content claims in advertising. This is important because product advertising often provides a significant first step for consumers in learning new nutrition information. Yet, unlike package claims, Nutrition Facts Panels are often not available for consumers during the processing of such advertising claims. Therefore, the authors examine the following research questions: (1) Do consumers misinterpret (i.e., overgeneralize) common nutrient content claims in advertising? If so, under what conditions does this occur? and (2) Can various types of disclosure statements remedy this problem? To address these questions, the authors interview a total of 365 primary food shoppers in three geographically dispersed malls in the United States in a between-subjects experiment. Misleading generalizations, beyond those of control ad claims, are found for general and specific nutrient content claims. Ad disclosure type, ad claim type, and nutrition knowledge all separately influence nutrient content and disease risk measures. Evaluative disclosures reduce misleading generalizations to a greater extent than do absolute or relative disclosures. The authors offer implications for public policy and food marketers.
The author presents a framework that considers public health and social issue behaviors and is based on self-interest, exchange, competition, free choice, and externalities. Targets that are prone, resistant, or unable to respond to the manager's goal behave on the basis of their motivation, opportunity, and ability and on a manager's use of the strategies and tactics inherent in education, marketing, and law.
In a laboratory experiment using a between-subjects design, the authors examine the effects on nutrition and product evaluations of nutrition claims made (e.g., “99% fat free; ” “low in calories ”) on a product package, product nutrition value levels, and enduring motivation to process nutrition information. Enduring motivation is shown to moderate the effects of product nutrition value on consumer evaluations. Also, nutrition claims interact with product nutrition value in affecting consumer perceptions of manufacturer credibility. Given the availability of nutrient levels in the Nutrition Facts panel on the back of the mock package, nutrition claims on the front of the package generally did not affect positively consumers’ overall product and purchase intention evaluations. The authors discuss some implications of these findings, suggestions for further research, and study limitations. ¹ 1. The generalizability of the findings from this laboratory study may be restricted because the mock package used as the stimulus was examined outside of an actual in-store purchase environment. Because consumers in store settings may spend less time and care examining Nutrition Facts panels and are subject to a variety of other influences (Cole and Balasubramanian 1992), findings from this study may not generalize to such settings.
This study examines the ready-to-eat cereal market during a period in which producers were initially prohibited from advertising cereals’ health benefits but were later permitted to make health claims. Results indicate that producer health claims led to significant increases in consumer knowledge of the fiber-cancer relationship, in fiber cereal consumption and in product innovation. Government and general information sources had limited impact on fiber cereal choices in the years prior to the advertising, despite the accumulation of scientific evidence linking fiber to colon cancer. Most segments of the population increased their fiber cereal consumption once health claims were added to the market, but some informationally disadvantaged segments that had responded less to government and other sources of information responded disproportionately to health claims compared to other segments. These findings suggest that policies governing producers’ use of health claims should be evaluated not only on how well they control deceptive or misleading claims, but also on how well they encourage producers to disseminate evolving health information to consumers.
The author reports a longitudinal quasi experiment that uses the implementation of the Nutrition Labeling and Education Act (NLEA) to examine the consumer and information determinants of nutrition information processing activities. Over 1000 consumers from balanced demographic, geographic, and site categories and across 20 different product categories were observed and surveyed within a supermarket setting. Findings suggest that consumers acquired and comprehended more nutrition information following the introduction of the new labels. The NLEA did not, however, always influence these outcomes irrespective of individual consumer differences. Specifically, the new nutrition labels were comprehensible to consumers with varying levels of motivation and most types of nutrition knowledge. However, the new labels appeared to widen consumer differences in terms of how much nutrition information was actually acquired - more motivated consumers and less skeptical consumers acquired more information after the NLEA was passed. Finally, consistent with the NLEA's apparent ability to reduce comprehension differences, the new labels narrowed comprehension differences across healthy and unhealthy products. In contrast, the NLEA widened differences in nutrition information acquisition in favor of unhealthy product categories. These results have implications for public health gains, as well as for the degree to which nutrition may become the basis for competition in unhealthy product categories.