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. Author manuscript; available in PMC: 2024 Jul 1.
Published in final edited form as: Am J Prev Med. 2023 Apr 17;65(1):101–111. doi: 10.1016/j.amepre.2023.02.007

Online RCT of Icon Added-Sugar Warning Labels for Restaurant Menus

Jennifer Falbe 1,*, Aviva A Musicus 2, Desiree M Sigala 3, Christina A Roberto 4, Sarah E Solar 1, Brittany Lemmon 5, Sarah Sorscher 6, DeAnna Nara 6, Marissa G Hall 7
PMCID: PMC10913691  NIHMSID: NIHMS1951894  PMID: 37344035

Abstract

Introduction:

To reduce added-sugar consumption, jurisdictions are considering requiring restaurant menu labels to identify high-added-sugar items. This study examined effects of added-sugar warning labels on hypothetical choices, knowledge of items’ added-sugar content, and perceptions of high-added-sugar items.

Study design:

The design was an online RCT.

Setting/participants:

National sample of adults (n=15,496) recruited to approximate the U.S. distribution of sex, age, race, ethnicity, and education.

Intervention:

Participants viewed fast-food and full-service restaurant menus displaying no warning labels (control) or icon-only added-sugar warning labels next to high-added-sugar items (containing >50% of the daily recommended limit).

Main outcome measures:

Hypothetical ordering of ≥1 high-added-sugar item; grams of added sugar ordered; and knowledge of items’ added-sugar content assessed in 2021 and analyzed in 2021–22.

Results:

Warning labels reduced the relative probability of ordering ≥1 high-added-sugar item by 2.2% (probability ratio=0.978, 95%CI: 0.964, 0.992; p=0.002), improved knowledge of added-sugar content (p<0.001), and led to a non-statistically significant reduction of 1.5 grams of added sugar ordered, averaged across menus (p=0.07). The label modestly reduced the appeal of high-added-sugar items, increased perceptions that consuming such items often will increase type 2 diabetes risk, increased perceived control over eating decisions, and increased injunctive norms about limiting consumption of high-added-sugar items (p-values<0.001). However, in the warning condition, only 47% noticed nutrition labels, and 21% recalled seeing added-sugar labels. When restricting the warning condition to those who noticed the label, the result for grams of added sugar ordered was significant, with the warning condition ordering 4.9 fewer grams than the controls (95%CI: −7.3, −2.5; p<0.001).

Conclusion:

Added-sugar warning labels reduced the probability of ordering a high-added-sugar menu item and increased participants’ knowledge of whether items contained >50% of the daily value for added sugar. The modest magnitudes of effects may be due to low label noticeability. Menu warning labels should be designed for noticeability.

Registration:

AsPredicted.org #65655

Introduction

Most U.S. children and adults consume added sugar in excess of the Dietary Guidelines for Americans’ recommended limit of 10% of daily calories,1 increasing population risk for cardiometabolic diseases.2–4 Governing bodies worldwide—including U.S. federal agencies and the World Health Organization—have identified reducing added-sugar consumption as a public health priority.1,5,6

Individuals’ ability to reduce added-sugar intake relies largely on the environment in which they make food decisions.1,7,8 Twenty one percent of calories consumed in the U.S. come from restaurants,9,10 and the nutritional quality of restaurant food is lower than that of foods consumed from schools, workplaces, and grocery stores,10 making restaurants an important target for public health intervention. One barrier to informed choice in restaurants is the lack of added-sugar information.11–14 Although the U.S. mandates added-sugar labeling on packaged foods, calorie labeling on chain-restaurant menus, and disclosure of several nutrients upon request in chain restaurants, chain restaurants are not required to disclose added sugar, let alone label high-added-sugar items. For this reason, the New York City (NYC) Council passed a bill in 2021 requiring added-sugar menu labels in chain restaurants to indicate pre-packaged items that exceed the daily recommended limit.15 This policy is similar to NYC and Philadelphia laws requiring sodium labeling in chain restaurants.16,17

Online experiments have found that restaurant menu sodium warnings and multi-nutrient warnings (like Chile’s octagon-shaped nutrient labels) on food-ordering websites reduced hypothetical ordering of labeled items,18,19 but there is a lack of research on added-sugar menu warning labels. The only study to examine such warnings found that, compared to a control label, icon-only and icon-plus-text added-sugar warning labels were perceived as more effective and increased knowledge about items’ added-sugar content with both label types performing similarly.20 However, research with behavioral outcomes is needed to better understand potential effectiveness of added-sugar menu labels. The goal of this study was to examine the effect of icon-only added-sugar warning labels displayed next to restaurant menu items high in added sugar on: 1) ordering ≥1 high-added-sugar item in a menu ordering task; 2) grams of added sugar ordered in that task; and 3) knowledge about menu items’ added-sugar content. A secondary objective was to examine warning-label effects on perceptions predictive of behavior.

Methods

Study Sample

A national sample of 15,496 U.S. adults (Figure 1) was recruited to match 2018 American Community Survey (ACS) 5-year estimates21 for age (18–34, 35–54, ≥55 years), sex, race/ethnicity (Hispanic [any race], non-Hispanic Asian, non-Hispanic Black, non-Hispanic White, and non-Hispanic Multiracial), and education (<some college, some college, ≥bachelor’s degree) from Dynata’s panels.22 Participants were told that “restaurant menus” were the study topic; neither warnings nor sugar were mentioned. After participants provided informed consent, a screener assessed eligibility: English-speaking, living in the U.S., age 18–99, purchasing from restaurants ≥1 time/month prior to the pandemic, and passing a task distinguishing humans from bots. Participants received incentives worth ~$1.25-$1.50 for the 10–15 minute Qualtrics questionnaire (questionnaire in Appendix) and an extra $1 to incentivize real-world behavior.

Figure 1.

Figure 1.

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CONSORT Diagram

a Reported purchasing from restaurants <1 time/month prior to the pandemic.

b A challenge-response test to determine a human user.

c The 1,212 (7% of eligible individuals) excluded were more likely than the analytic sample to be age 18–34 (37% vs. 29%), have a bachelor’s degree (25% vs. 19%), and identify as non-Hispanic Black (22% vs. 14%) and were less likely to be age 55+ (30% vs. 40%), have attained some college (28% vs. 32%), and identify as non-Hispanic White (chi-square p-values<0.001).

d Attention check question assessed the current month.

e Completion time <30% of the median completion time.

CAPTCHA—Completely Automated Public Turing test to tell Computers and Humans Apart.

Data were collected May-June 2021 and analyzed July 2021-February 2022. This study was approved by the UC Davis IRB and pre-registered with AsPredicted.org (Appendix).

Intervention

In a between-subjects randomized controlled trial, a simple allocation ratio was used to assign participants (via Qualtrics randomizer) to view restaurant menus containing either (1) no added-sugar warning labels (control) or (2) icon-only added-sugar warning labels (upside-down triangle with exclamation mark over a spoon) next to high-added-sugar items (i.e., containing >50% daily recommended limit [>25 grams])(Figure 2). The label design was based on results of an online randomized experiment20 that used a validated scale of perceived message effectiveness23 (but not behavioral outcomes) to test 6 icons against one-another and a control label. The icons were perceived as significantly more effective than the control label and increased knowledge about items’ added-sugar content. Because the 6 icons performed similarly,20 this study tested the icon most complementary to but also distinguishable from NYC and Philadelphia’s sodium warning label (triangle with salt shaker).16,17 All menus contained prices and calorie information as mandated by federal law for chain restaurants (P.L 111–148). Prices and calories were obtained from the chains’ websites and apps. In the warning condition, the top of menus displayed a disclosure statement: “[icon] SUGAR WARNING: Item exceeds half the Daily Value for added sugars based on a 2,000 calorie diet. The U.S. Dietary Guidelines advises limiting added sugars.” The icon size and placement in this study were consistent with NYC’s sodium labeling requirements16 because if adopted, an added-sugar warning policy would likely be similar (e.g., icon height equaled the height of the largest letter in an item’s name; combo meals were labeled if any combo option was high in added sugar).

Figure 2.

Figure 2.

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Excerpts of restaurant menus viewed in the control and added-sugar warning label conditions. The menus were designed by the research team and based on restaurant websites and apps.

Measures

In a menu ordering task, all participants were asked to imagine they were ordering dinner for themselves from a fast-food menu and full-service restaurant menu, labeled according to condition and shown in random order. For each menu, participants clicked on the items they wanted to order (up to 4 food/combo items and 2 beverages per menu). Menus included a variety of items available at the U.S.’ highest-grossing fast-food chain and second-highest-grossing full-service chain due to its high number of locations and wide geographic distribution.24 To incentivize selection of items participants would actually purchase, participants were told they would receive a $1 coupon for an item selected. In reality, they received an additional Dynata incentive worth $1.

The first primary outcome from the menu ordering task was ordering ≥1 high-added-sugar item from either menu. Note that all combo meals on the fast-food menu were labeled in the warning condition because some combo beverage options (but not mains or fries) were high in added sugar. However, a combo meal was only classified as high in added sugar if the version ordered met that criterion (e.g., regular soda). Thus, a combo meal without a high-added-sugar beverage was not classified as high in added sugar.

The second primary outcome from the menu ordering task was grams of added sugar ordered, averaged across menus. Grams of added sugar were approximated for items containing naturally-occurring sugars because the FDA does not require restaurants to disclose added sugar. For these items, added-sugar content was estimated based on items’ total-sugar content, items’ ingredients, and the added-sugar content of similar packaged foods and foods listed in the National Cancer Institute’s Automated Self-Administered 24-Hour Dietary Assessment Tool database (Appendix). Because warning efficacy may vary by restaurant type, ordering outcomes were examined by menu. We also explored differences by item category (i.e., beverage, main, dessert), which was not pre-registered but provided upon reviewer request.

The other primary outcome was knowledge about menu items’ added-sugar content, defined as the percent of items participants correctly classified as high in added sugar. Knowledge was measured because the stated goal of governmental labeling policies is typically to promote public understanding and knowledge.25 Participants were shown 4 pairs of items: entrées, beverages, desserts, and combo meals (one with an SSB, which was labeled, and one with a non-SSB, which was not labeled). Five of the 8 items were high in added sugar and labeled in the warning condition: one entrée, one dessert, one combo meal, and both beverages. Participants were asked to indicate the item(s) that had “more than half of the daily value for added sugars,” and could select either item, “both,” or “neither.” Knowledge was operationalized as the percent of the 5 high-added-sugar items correctly identified. However, because warnings can also help consumers identify items not high in added sugar, this study also examined (not pre-registered) percent of the 3 not high-added-sugar items correctly identified, and the percent of all 8 items correctly classified.

To assess the secondary outcomes of perceptions and behavioral intention, participants were shown 3 high-added-sugar items (soda, chicken salad, and fudge sundae) one at a time and rated each product on perceived healthfulness (response options: 1–7), appeal (1–7), risk perceptions regarding type 2 diabetes (1–5), and injunctive norms (1–5; Appendix contains items and response scales). For each construct, a continuous composite score was created by averaging individuals’ responses for the 3 menu items. To assess perceived control over eating decisions, participants were asked, “Did the information on the menu make you feel…” (“Less in control of making eating decisions,” “Neither less nor more in control of making eating decisions,” or “More in control of making eating decisions” (dichotomized into 1=more or 0=less/neither).26 Intention was assessed by, “I intend to reduce my consumption of added sugars in the next month” (1–5),27 treated as a continuous variable.

To assess whether participants noticed the labels (a process measure), participants were asked, “Think back to the beginning of this survey when you imagined you were ordering from a menu. Did you notice any nutrition labels (other than the calories) next to the menu items?” (dichotomized: 1=“yes” or 0=“no”/“don’t know”). Those in the warning condition who answered “yes” were asked, “What did the nutrition label tell you about?” (“sodium”, “added sugars”, “trans fats”, “fiber”, “calcium”, “healthy items”, “none of these options”, or “I don’t know”). The other process measures—perceived knowledge gain28 and label use (“yes” or “no”)—were also assessed among those who noticed added-sugar labels.

Participants in the warning condition were shown the labels again in the context of a menu excerpt and asked: “.…How much does this label grab your attention?” (1–5);29 “How likely are you to talk about this label with others?” (1–5);30 and “How much does this label make you think about added sugars?” (1–5).31

To assess support for an added-sugar warning label policy, both conditions were shown the warning and asked, “Some cities are considering a law that requires that chain restaurants display this label next to items that are high in added sugars. Would you…?” (1=“Strongly support this law” to 5=“Strongly oppose this law”).

Other measures included an attention check item asking participants to select the current month and items assessing sociodemographic characteristics (e.g., household income), height and weight, and health behaviors and conditions. Total dollar amounts of menu orders were calculated (not pre-registered but provided upon reviewer request).

The a-priori planned sample size of 15,500 was estimated to provide 90% power to detect a very small effect size (Cohen’s d=0.024). Of 16,708 eligible participants, 16,134 provided complete data on primary outcomes. According to the pre-registered analysis plan, participants who failed the attention check (n=536) or completed the survey in <30% of the median time20 (n=96; i.e., “speeders”) were excluded from the main analysis. Although all panelists were prescreened as living in the U.S., 6 reported living elsewhere and were excluded, yielding an analytic sample of n=15,496 (Figure 1). Differences between the analytic sample and excluded eligible participants are described in the Figure 1 footnote.

Statistical Analysis

Chi-square and independent t-tests were used to compare differences in participant characteristics between conditions. Bivariate linear models regressed continuous outcomes on a warning label indicator. For dichotomous outcomes, bivariate Poisson regression with a robust error variance32 was used to estimate the probability ratio (PR) comparing the warning to the control condition, and the number needed to treat (NNT)33 was calculated. Analyses were not adjusted for covariates per CONSORT guidelines.34 Percentages and mean responses were calculated for process measures.

The Holm-Bonferroni procedure35 was used to adjust for multiple comparisons within two families of outcomes: primary menu ordering outcomes (≥1 high-added-sugar item selected and grams of added sugar ordered) and secondary perception and behavioral intention outcomes. Results include unadjusted p-values and specify when statistical significance changed after the Holm-Bonferroni procedure.

Non-pre-registered sensitivity analyses were conducted. First, for grams of added sugar, 47 outliers with studentized residuals>|3| were excluded. Second, for all primary outcomes, effects were examined among those who noticed the warning by restricting the sample to those in the warning condition who reported noticing an added-sugar warning (n=1,603 [21%]) and comparing them to all controls (n=7,761). In these analyses, the following variables that were significantly (p<0.05) and meaningfully (PR>1.01 or PR<0.99) associated with both noticing the label in the warning group (Appendix Table 1) and with the primary outcomes were included as covariates: age, ordering frequency from full-service restaurants, household income, and dietary restrictions. Although trying to reduce added-sugar consumption was also associated with noticing, it was not included due to the uncertain direction of causality. Third, analyses included speeders and those who failed the attention check. Fourth, analyses additionally included those with incomplete ordering outcomes with zeros imputed. Fifth, additional ordering thresholds were examined as dichotomous outcomes (i.e., ≥2 and ≥3 high-added-sugar items ordered).

Although this study was not powered to assess moderation, potential differences in label effects were explored by income and education. These moderating variables were selected given the higher prevalence of diet-related diseases in lower socioeconomic status groups.36 The goal was to understand whether this labeling approach would produce equitable outcomes. Because labels could have a bigger effect among those trying to reduce added-sugar consumption, moderation by this variable was also examined (not pre-registered). The same models for the primary outcomes were used with the addition of a(n) indicator(s) for level of a potential moderator and a(n) interaction term(s) between the warning condition and level of a moderator. Separate models were run for each moderation analysis.

All tests (two-sided alpha=0.05) were conducted using Stata/MPv15.1 (StataCorp LLC, College Station, TX).

Results

Appendix Table 2 shows participant characteristics. The distribution of race, Hispanic ethnicity, gender (measured in this study vs. sex measured by the ACS), and education were similar to 2018 ACS estimates. For annual household income before taxes, 27% reported ≤$35,000; 27% reported $35,001-$65,000; 18% reported $65,001-$95,000; and 28% reported >$95,000. There were no significant differences by condition.

Appendix Table 3 shows the number of items ordered by restaurant and item category. Figures 3A and 3B and Appendix Table 4 show primary ordering outcomes. In total, 81.5% in the warning condition ordered ≥1 high-added-sugar item from either menu, compared to 83.4% in the control condition, for an absolute difference of −1.9 percentage points (pp) and relative difference of −2.2% (PR=0.978, 95%CI: 0.964, 0.992; p=0.002; NNT=53). Effects were larger for the full-service compared to the fast-food menu (−2.7% vs. −1.3%; PR=0.973, 95%CI: 0.953, 0.994 vs. PR=0.987, 95%CI: 0.966, 1.008; NNT=53 vs. NNT=112).

Figure 3.

Figure 3.

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(A) percent of participants who ordered ≥1 high-added-sugar (HAS) item, (B) added sugar ordered, and (C) percent of items correctly classified as HAS or not

***p<0.001, **p<0.01, *p<0.05, ap<0.10 from (A) Poisson regression models with robust standards errors and (B, C) linear regression models in which the outcome was regressed on an indicator for the warning label condition. Means and 95% confidence intervals (indicated by error bars) were generated using the Stata margins command.

Note: Sample size=15,496 (control=7,761, warning label=7,735)

HAS—high-added-sugar

Though not a statistically significant difference, the amount of added sugar ordered, averaged across menus, was lower in the warning condition by 1.5 grams (95%CI: −3.0, 0.1; p=0.07), a relative difference of 2.1%. Though also not significant, label effect sizes for grams of added sugar ordered were similar by restaurant menu (fast-food=−1.4 vs. full-service=−1.5 grams) and larger for beverages than mains or desserts when averaged across menus (−0.7 vs. −0.3 and −0.4 grams; Appendix Table 4).

In the sensitivity analysis excluding 47 outliers for grams of added sugar ordered (Appendix Table 5), results were statistically significant: The warning group ordered 1.6 fewer average grams of added sugar than the controls (95%CI: −3.1, −0.03; p=0.046). Second, in adjusted analyses that restricted the warning group to participants who reported noticing added-sugar warnings (Appendix Table 6), effect sizes for ordering outcomes were stronger than in the full sample, and results for grams of added sugar ordered were statistically significant. The relative percent of participants who ordered ≥1 high-added-sugar item was lower by 4.1% (3.4 pp) among those who noticed the warning relative to controls (PR=0.959, 95%CI: 0.935, 0.984; p=0.001), and the amount of added sugar ordered was significantly lower by 4.9 grams (6.8%) among those who noticed the warning compared to the controls (95%CI: −7.3, −2.5 grams; p<0.001). Results for both ordering outcomes were robust to the inclusion of speeders, those who failed the attention check, and those without complete ordering data (Appendix Table 7). Lastly, there were no significant warning effects when examining other dichotomous ordering thresholds for high-added-sugar items (Appendix Table 8).

For the knowledge outcomes, participants’ ability to correctly identify the 5 high-added-sugar items did not differ between conditions (Figure 3C). However, compared to controls, warning group participants correctly classified a significantly higher percentage of the 3 not high-added-sugar items (3.5 pp [(95%CI: 2.5, 4.5; p<0.001]) and all 8 menu items by their added-sugar content (1.4 pp [95%CI: 0.8, 2.1; p<0.001]). In sensitivity analyses restricting warning group participants to those who noticed the added-sugar warnings (Appendix Table 6), associations were stronger. For example, warning group participants who noticed warnings correctly classified 6.9 pp more of the 8 items by added-sugar content compared to controls (95% CI: 5.8, 8.0 pp; p<0.001). Warning effects on knowledge were also robust to the inclusion of speeders and those who failed the attention check or did not complete the ordering task (Appendix Table 7).

Table 1 displays perception and behavioral intention results. Warnings modestly reduced perceived healthfulness and appeal of high-added-sugar items (p-values<0.001) and increased the relative probability of feeling “more in control of eating decisions” by 6% (PR=1.06, 95%CI: 1.03, 1.10; p<0.001). The warnings did not significantly affect intentions to reduce added-sugar consumption in the next month. The warning group was also modestly more likely to agree that people who are important to them would want them to limit consumption of high-added-sugar items (i.e., injunctive norm) and that consuming such items often would increase type 2 diabetes risk (p-values<0.001).

Table 1.

Perception, intention, and process outcomes from a randomized experiment of added-sugar menu warning labels

Outcomes Control group (n=7,761), Mean (SE) or n (%) Added-sugar warning label group (n=7,735), Mean (SE) or n (%) Difference or PR comparing the warning group to the control group (95% CI)
Perception and behavioral intention outcomes a
 Perceived healthfulness of HAS menu itemsb (1=very unhealthy to 7=very healthy) 3.75 (0.02) 3.63 (0.02) −0.12 (−0.16, −0.08) ***
 Perceived appeal of HAS menu itemsb (1=very unappealing to 7=very appealing) 5.23 (0.01) 5.15 (0.01) −0.08 (−0.12, −0.04) ***
 Injunctive norm regarding HAS menu itemsb (1=strongly disagree to 5=strongly agree) 3.42 (0.01) 3.50 (0.01) 0.08 (0.05, 0.10) ***
 Perceived risk of type 2 diabetes associated with HAS menu itemsb (1=strongly disagree to 5=strongly agree) 3.43 (0.01) 3.53 (0.01) 0.09 (0.07, 0.12) ***
 Intention to reduce added-sugar consumption (1=strongly disagree to 5=strongly agree) 3.69 (0.01) 3.71 (0.01) 0.01 (−0.02, 0.05)
 Increased feeling in control over eating decisions 3,650 (47%) 3,872 (50%) PR=1.06 (1.03, 1.10) *** c
Process outcomes
 Reported noticing nutrition label other than calories 2,616 (34%)d 3,617 (47%)e PR=1.39 (1.33, 1.44) *** c
  Recalled that the label was for added sugarsf,g - 1,603 (21%)e -
   Perceived knowledge gain from warning labelsf,g - 1,265 (79%)h -
   Reported use of warning labelsf,g - 877 (55%)h
 Reported that warning label grabbed attention “quite a bit” or “a great deal”f - 3,923 (51%)e -
 Anticipated social interaction about warning label: “Very” or “extremely” likely to talk about it with othersf - 2,889 (38%)e -
 Reported that warning label caused one to think about added sugars “quite a bit” or “a great deal”f - 3,942 (51%)e
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a

Holm-Bonferroni correction was used for determining significance among the 6 perception outcomes.

b

Individuals’ average across all 3 high-added-sugar items, used as continuous outcome in OLS regression.

c

PR=Probability ratio from Poisson regression with robust standard errors.

d

Control participants were not shown any nutrition labels other than calories, so these participants erroneously reported noticing nutrition labels.

e

Denominator is all participants in the warning condition who answered the “noticed” question and did not have missing data for the process outcome (7,660 to 7,682).

f

Assessed only in the warning condition.

g

Indented items indicate a skip pattern in which the question was only asked of those who correctly answered the prior question.

h

Denominator is the 1,603 warning group participants who recalled seeing a label for added sugars.

***

P<0.001 and statistically significant, including after the Holm-Bonferroni correction.

HAS—high-added-sugar; OLS—ordinary least squares; PR—probability ratio.

Bold font indicates statistically significant effect of the warning label.

Table 1 shows process outcomes. Forty-seven percent of participants in the warning condition (n=3,617) reported noticing nutrition labels other than calories, and 21% of the warning group (44% of the 47% who noticed nutrition labels, n=1,603) correctly recalled that the labels were for added sugar. Among those who noticed added-sugar warnings, 79% (n=1,265) reported perceived knowledge gain, and 55% (n=877) reported using the labels when ordering. Upon viewing the label again, 51% of the warning group (n=3,923) perceived that the label grabbed attention and caused them to think about added sugar “quite a bit” or “a great deal.” A total of 38% (n=2,889) reported being “very” or “extremely” likely to talk about the labels with others.

Upon viewing the warning, the majority (72%) of participants supported a law requiring warning labels on chain-restaurant menus (39% strongly and 33% somewhat supported), whereas 19% had no opinion, and 9% opposed the law (4% strongly and 5% somewhat opposed). Lastly, there were no significant differences between control and warning groups in dollar amounts of orders (i.e., amount of money hypothetically spent) from fast-food ($12.78 vs. $12.64; p=0.16) or full-service ($25.21 vs. $25.19; p=0.93) menus.

The only outcome for which there was significant moderation was knowledge: the warning was more effective in helping lower-income (≤$35K and >$35–65K/year) than high-income participants (>$95K/year) correctly classify high-added-sugar items (p-values=0.02; Appendix Table 9).

Discussion

To the authors’ knowledge, this is the first study to test the effect of restaurant menu added-sugar warning labels on hypothetical orders. This online randomized controlled trial found that added-sugar warnings significantly reduced the relative probability of ordering ≥1 high-added-sugar item by 2.2% (absolute difference: 1.9 percentage points [control=83.4% vs. warning=81.5%]). Warnings also led to a non-significant 1.5 gram (2%) reduction in average added sugar ordered across both menus and a statistically significant 1.6 gram reduction after excluding outliers. Given the frequency of restaurant food consumption, these relatively small effects may lead to meaningful changes in intake at the population level. Such warnings might also motivate restaurants to reduce the added-sugar content of menu items.37,38 These effect sizes are within the range of those for calorie labeling,38–40 and the direction of effects are consistent with other experiments testing sugar-related warnings on packages and signage.41–46 These results are also consistent with experiments testing sodium and multi-nutrient warnings on food-ordering websites.18,19 For instance, Musicus et al. found that icon-only sodium warnings reduced the percent of participants ordering ≥1 high-sodium item by 2.4 pp and reduced sodium ordered by 25 mg or 2%, though effects were not statistically significant, potentially due to sample size.18 However, the icon-plus-text sodium warnings examined in that study resulted in larger and statistically significant results compared to the icon-only label: 4.1–6.4 pp reduction in ordering ≥1 high-sodium item and 46–68 fewer mg (3–5%) of sodium ordered.18 Thus, it is possible that icon-plus-text added-sugar warnings could result in larger effects than observed in this study for icon-only added-sugar warnings.

Results also found that added-sugar warnings increased participants’ knowledge of whether menu items contained >50% of the added-sugar daily recommended limit and modestly reduced perceptions of healthfulness and appeal for high-added-sugar items. They also increased perceptions that eating such items frequently would increase type 2 diabetes risk, and they shifted norms about consuming high-added-sugar items. Support was high (72%) for a law that would require chain restaurants to display added-sugar warnings on menus. Lastly, there were no warning effects on (hypothetical) dollar amounts of orders.

The observed effects on primary outcomes may be modest because only 47% of the warning group reported noticing a nutrition label (similar to a prior finding for sodium icons),18 and only 21% of the warning group reported noticing an added-sugar warning. When analyses were restricted to those who noticed the added-sugar warning, the adjusted effect sizes were significant and larger than in the full sample. The relative probability of ordering ≥1 high-added-sugar item was lower by 4.1%; average added sugar ordered was lower by 4.9 grams; and the percent of items correctly classified by added-sugar intake was higher by 6.9 pp. The icon-only label that was tested was black, the same size as the menu-item text, and not the more commonly used warning triangle shape. Larger warning size, bright and contrasting colors,47–50 and icon-plus-text warnings18 could increase noticeability and efficacy.

The icon-only warning in this study had a much smaller effect on knowledge compared to a prior study that examined 6 icon-only added-sugar warnings, including the icon in this study. This may be because the prior study20 first assessed perceived message effectiveness,23 which drew attention to the labels, or because the knowledge tasks differed. In the prior study, participants were presented with 8 items on a single menu and asked to click the items that had more than half the daily added-sugar limit. In the present study, only 2 items were presented at a time, and there may have been more items that participants typically associate with high-added-sugar content.

Future research should explore whether the effectiveness of added-sugar warnings can be increased by including bright colors, making the warning larger relative to menu text, changing the label text (e.g., added-sugar warning vs. sugar warning), and adding text next to icons. It is also worth exploring whether the placement of labels (e.g., on the left side of item names) or grouping labeled items together or near an unlabeled counterpart to increase salience and attract attention51 could boost label effectiveness. It would also be valuable to investigate the effects of different added-sugar warning thresholds, alternative labeling approaches for combo meals, and the potential interactive effects of added-sugar warnings, sodium warnings, and calorie labels. Real-world policy evaluations should also examine whether added-sugar warnings spur reformulation. Further, requiring chain restaurants to disclose added-sugar content would facilitate implementation and enforcement of added-sugar labeling policies.

Study strengths include recruiting a large national sample, basing the label design on results of a prior experiment testing multiple warning designs,20 and examining warnings on fast-food and full-service menus.

Limitations

Limitations include measuring hypothetical, not actual, behavior (although incentives were offered to try to increase realistic decision-making), the possibility for social desirability bias (which was likely small given participant anonymity), and the potential that, although the sample was recruited to match the U.S. distribution of sex, age, race, Hispanic ethnicity, and education, there may have been differences in other characteristics that limit generalizability. Online convenience samples do, however, typically produce internally-valid experimental results.52–54 Additionally, because the FDA does not require restaurants to disclose added sugar, the added-sugar content of many items had to be estimated. Lastly, the study examined only one-time label exposure. Research on repeated exposures, especially in real-world settings, is needed to understand long-term effects.

Conclusion

Added-sugar warnings on restaurant menus modestly reduced the probability of ordering a high-added-sugar item, increased knowledge of whether items contained more than half the daily value for added sugar, and influenced perceptions that precede behavior change. Further, label effects were larger among the one-fifth of participants who noticed the warnings. Research is needed to design and test the effects of more noticeable restaurant menu added-sugar warnings.

Supplementary Material

Appendix

Acknowledgements

The content is solely the responsibility of the authors and does not necessarily represent the official views or policy of Bloomberg Philanthropies, Center for Science in the Public Interest (CSPI), the NIH, or the USDA. This study was funded by Bloomberg Philanthropies (2019-71208) directly and through a subaward from CSPI. Dr. Falbe is supported by NIH/NIDDK K01DK113068 and USDA/NIFA Hatch project 1016627. Dr. Sigala is supported by the NIH/NHLBI Postdoctoral Diversity Supplement R01HL137716. Dr. Hall is supported by NIH/NHLBI K01HL147713. Dr. Musicus is supported by grants T32HL098048 and T32CA057711 from the National Institutes of Health. Bloomberg Philanthropies played no role in the study design, label design, analytic plan, data collection, data curation or analysis, or in the drafting or revising of the manuscript. CSPI, a non-profit organization, played no role in the data collection, experimental design, or analysis of the data. UC Davis IRB approval number: 1641776.

Sarah Sorscher and DeAnna Nara are employed by CSPI and contributed to the study conceptualization, label design, and reviewing and editing the manuscript.

No other financial disclosures were reported by the authors of this paper.

Footnotes

CRediT author statement

Jennifer Falbe: Conceptualization, Data curation, Funding acquisition, Methodology, Supervision, Formal analysis, Writing – original draft, Writing – review & editing. Aviva A. Musicus: Conceptualization, Methodology, Visualization, Writing – review & editing. Desiree M. Sigala: Methodology, Writing – review & editing. Christina A. Roberto: Conceptualization, Methodology, Writing – review & editing. Sarah E. Solar: Methodology, Data curation, Writing – review & editing. Brittany Lemmon: Data curation, Visualization, Formal analysis, Writing – review & editing. Sarah Sorscher: Conceptualization, Writing – review & editing. DeAnna Nara: Conceptualization, Writing – review & editing. Marissa G. Hall: Conceptualization, Methodology, Writing – review & editing.

Contents from this article were previously presented at the 2022 American Public Health Association Annual Meeting.

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Supplementary Materials

Appendix
NIHMS1951894-supplement-Appendix.pdf (11.4MB, pdf)

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