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Review Obesity
EPIDEMIOLOGY/GENETICS
ASystematic Review of Calorie Labeling
and Modified Calorie Labeling Interventions:
Impact on Consumer and Restaurant Behavior
1 2 3 1 4
Sara N. Bleich , Christina D. Economos , Marie L. Spiker , Kelsey A. Vercammen , Eric M. VanEpps ,
5 6 7 8
Jason P. Block , Brian Elbel , Mary Story , and Christina A. Roberto
Objective: Evidence on the effects of restaurant calorie labeling on consumer and restaurant behavior is
mixed. This paper examined: (1) consumer responses to calorie information alone or compared to modi-
fied calorie information and (2) changes in restaurant offerings following or in advance of menu labeling
implementation.
Methods: Searches were conducted in PubMed, Web of Science, Policy File, and PAIS International to
identify restaurant calorie labeling studies through October 1, 2016, that measured calories ordered, con-
sumed, or available for purchase on restaurant menus. The reference lists of calorie labeling articles were
also searched.
Results: Fifty-three studies were included: 18 in real-world restaurants, 9 in cafeterias, and 21 in labora-
tory or simulation settings. Five examined restaurant offerings.
Conclusions: Because of a lack of well-powered studies with strong designs, the degree to which menu
labeling encourages lower-calorie purchases and whether that translates to a healthier population are
unclear. Although there is limited evidence that menu labeling affects calories purchased at fast-food res-
taurants, some evidence demonstrates that it lowers calories purchased at certain types of restaurants
and in cafeteria settings. The limited data on modified calorie labels find that such labels can encourage
lower-calorie purchases but may not differ in effects relative to calorie labels alone.
Obesity (2017) 00, 00–00. doi:10.1002/oby.21940
Introduction needs vary.” The hope is such information will encourage consumers
to choose, and restaurants to offer, lower-calorie items.
Obesity is associated with adverse health consequences (1-4) and sub-
stantial health care costs (5). Overconsumption of calories has been a This paper synthesizes the evidence on the effectiveness of menu
key driver of rising obesity (6,7), and dining out is thought to play a labeling. Although we identified nine prior menu labeling reviews
significant role. Because people substantially underestimate the calo- (13-21), we extend this research by reviewing the following: (1)
ries in prepared food (8), restaurant menu labeling was implemented newer studies; (2) research across restaurant, cafeteria, and labora-
in several cities and states (9,10) and is included in the 2010 Afford- tory settings; (3) studies comparing responses to calorie information
able Care Act (11,12). Chain restaurants, grocery stores, and other (e.g., 400 calories) relative to modified calorie information or nutri-
food retail establishments with 20 or more locations must post calorie tion symbols (e.g., traffic light labels); and (4) studies of menu
information on their menus by May 2018 along with the statement offerings following local menu labeling regulations and in advance
“2,000 calories a day is used for general nutrition advice, but calorie of national regulations.
1 Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA. Correspondence: Sara N. Bleich
(sbleich@hsph.harvard.edu) 2 ChildObesity180, Friedman School of Nutrition Science and Policy, Tufts University, Medford, Massachusetts, USA
3 Department of International Health, John Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA 4 VA Center for Health Equity
Research and Promotion, Philadelphia, Pennsylvania, USA 5 Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care
Institute, Boston, Massachusetts, USA 6 Department of Population Health, New York University School of Medicine and Wagner School of Public Service,
New York, New York, USA 7 Duke Global Health Institute, Duke University, Durham, North Carolina, USA 8 Department of Medical Ethics & Health
Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Funding agencies: This work was partially supported by ChildObesity180. CAR is supported by the National Institute on Aging of the National Institutes of Health under
Award Number P30AG034546.
Disclosure: The authors declared no conflict of interest.
Additional Supporting Information may be found in the online version of this article
Received: 12 December 2016; Accepted: 25 June 2017; Published online 00 Month 2017. doi:10.1002/oby.21940
www.obesityjournal.org Obesity | VOLUME 00 | NUMBER 00 | MONTH 2017 1
Obesity AReview of Menu Labeling Bleich et al.
two using cross-sectional designs to compare labeled versus unla-
Methods
beled locations (38,39). Three of these studies included children
We searched PubMed, Web of Science, Policy File, and PAIS Inter- and/or adolescents (27,30,33).
national for all articles published through October 1, 2016, using a
combination of the terms “restaurant,” “cafeteria,” “food service,”
“fast-food,” “labeling,” “calories,” and “energy.” (See Supporting RCTs. Ellison et al. (22) reported no difference in calories ordered
Information for search details). We also examined reference lists of after randomizing a sample of 138 customers of a full-service uni-
calorie labeling articles. After removing duplicate studies, one versity campus restaurant to menus with either no calorie informa-
author (KV) screened titles and abstracts and reviewed the full text tion, calorie labels, or calorie labels plus traffic lights, but the small
for inclusion. Another author (SB) confirmed inclusion of these cell size greatly limits the statistical power of the study.
studies, and a third author (CR) adjudicated differences. Included
studies had to examine the effects of calorie information displayed In two quasi-real-world RCTs, Wisdom and colleagues (23) app-
on menus using calories offered, ordered, purchased, or consumed roached 638 customers entering a fast-food sandwich restaurant to
as an outcome. Studies of menu offerings included research con- complete a survey in exchange for a free meal. Using a 23233
ducted before and after local menu labeling regulations were imple- design, participants were randomized to either a daily calorie recom-
mented and in advance of national calorie labeling implementation. mendation statement or not, item calorie information or not, and
We did not examine the effect of labeling on intake of other conditions that made healthy sandwiches more or less convenient to
nutrients, although some study menus displayed other nutrition order (healthy sandwiches were featured on an initial page and
information (e.g., sodium). We also included studies that compared patrons had to open a sealed or unsealed menu to view the remain-
calorie information to modified presentations of calorie information ing sandwiches). The two studies only varied in the strength of the
such as traffic light labels, total recommended daily calorie state- healthy sandwich convenience manipulation so were combined for
ments, and physical activity labels (presenting the amount of time analysis. Statistically significantly fewer calories were ordered in
one would have to exercise to burn off the calories eaten). We both the calorie label and daily calorie recommendation conditions
included studies conducted among adults, adolescents, and children. compared to the no information group. The combination of both cal-
Studies were excluded for the following reasons: (1) did not report orie labels and daily calorie recommendations led to a 100-calorie
calories offered, ordered, purchased, or consumed as an outcome; reduction.
(2) did not use restaurant-like menus or used menus with a small
number of items (<6 items) that may not generalize to typical res- Natural experiment with comparison site(s). The natural
taurant settings; (3) only compared self-reported calorie label users experiment with the strongest design and largest sample size was
to nonusers; (4) evaluated nutrition labels on packaged foods; (5) conducted by Bollinger et al. (24). They analyzed more than 100
studied another intervention (e.g., price changes, educational ses- million transactions before and after the implementation of the New
sions) in combination with calorie information such that the calorie York City (NYC) menu labeling law at multiple Starbucks locations,
label effect could not be isolated; or (6) tested whether participants including control sites in Boston and Philadelphia. There was a stat-
changed menu orders after being asked to immediately reorder from istically significant 6% decrease in mean calories per transaction (15
the same menu containing calorie information. calories on average) in NYC locations driven by changes in food,
Tables 1–4 present details of each study’s design, methods, and out- not beverage, calories.
comes based on setting. We summarize each study below based on Another natural experiment with a large sample size and strong
setting (restaurant, cafeteria, or laboratory/simulation) and grouped design was conducted by Finkelstein and colleagues (25). They saw
by study design (e.g., randomized controlled trial [RCT]). Finally,
we describe studies of changes in restaurant offerings after enacted no effect of menu labeling over 1 year when evaluating pre/post
or anticipated menu labeling regulations. Results reported as kilo- transaction data from seven locations of a Mexican fast-food chain
joules have been converted to calories. in King County, Washington (labeled), compared to seven locations
adjacent to King County (unlabeled).
Elbel et al. (26) reported no change in calories ordered based on
Results 1,156 surveys of customers exiting fast-food restaurants in low-
income neighborhoods of NYC (labeled) versus Newark, New Jersey
Our search yielded 3,384 citations across four databases (see Sup- (unlabeled), before and 4 weeks after labeling. Although they
porting Information for PRISMA flow diagram). After removal of reported no decrease in calories ordered among children and adoles-
duplicates (n5568), 2,816 titles and abstracts were screened and cents (n5349) (27), the small sample size (e.g., Newark n549
2,737 were excluded. Following full-text review, 53 articles were pre and n534 post labeling) makes it difficult to draw conclusions.
included. A5-year follow-up study in the same cities found no effect of label-
ing among adults at four fast-food restaurant chains (28). Elbel and
Real-world restaurant settings colleagues also observed no decrease in calories ordered in a similar
Eighteen of forty-eight studies evaluated calorie information in real- study in which they collected 2,083 surveys outside of McDonald’s
world restaurant settings (Table 1). There was one RCT (22), one and Burger King locations in Philadelphia (labeled) compared to
quasi-real-world RCT (23), seven natural experiments evaluating Baltimore (unlabeled) 2 months before and 4 months after labeling
menu labeling before and after implementation and compared to (29). Although these studies have strong designs, they were powered
control locations (24-30), seven studies evaluating labeling before to detect only large effects of calorie labeling (i.e., the first NYC
and after implementation without a control comparison (31-37), and evaluation had 80% power to detect a 125-kcal reduction).
2 Obesity | VOLUME 00 | NUMBER 00 | MONTH 2017 www.obesityjournal.org
Review Obesity
EPIDEMIOLOGY/GENETICS
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www.obesityjournal.org Obesity | VOLUME 00 | NUMBER 00 | MONTH 2017 3
Obesity AReview of Menu Labeling Bleich et al.
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4 Obesity | VOLUME 00 | NUMBER 00 | MONTH 2017 www.obesityjournal.org
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