The study was approved by the institutional review board at the University of North Carolina at Chapel Hill and designated as exempt from review at Universidad Nacional de Colombia. Prior to participating in the study, participants acknowleged their informed consent. We pre-registered the design, hypotheses, and analytic plan on ClinicalTrials.gov (#NCT04567004).
Study design and procedures
The final labels tested are shown in Figure 1. As the study’s purpose was to inform Colombia’s front-of-package labeling policy, we set out to test front-of-package labels that could be proposed as a result of the policy. Provided this, we decided to test a nutrient warning label, a guideline daily amounts (GDA) label, and a Nutri-Score label as well as a no-label alternative.
We selected the nutrient warning label based on the nutrient warning that performed best in our previous study investigating front-of-package nutrient warning labels. In our previous study, the octagonal nutrient warning elicited the highest perceived message effectiveness (PME) and was the label that most participants selected as discouraging them from purchasing ultra-processed foods and sugary drinks high in nutrients of concern) [20]. The octagonal nutrient warning label was a black octagon that contained a statement about the product containing excess of a nutrient of concern (sugar, sodium, or saturated fat). For example, “EXCESO DE AZÚCAR” (Excess sugar). The octagon also contained “MINSALUD” indicating the message was authorized by the Colombian Ministry of Health and the text “EVITAR SU ALTO CONSUMO” (Avoid high consumption). To determine if a product would receive a nutrient warning label, we used the Chilean Ministry of Health’s third stage cutoff limits for sugar, sodium, and saturated fat [21].
The GDA label included Spanish text above the GDA figure stating the product serving size. Below the serving size, a row of light blue blocks listed the Calories, total fat, saturated fat, sugar, and sodium per serving, as well as percentages indicating what percent of the GDA the serving contained. Underneath the light blue blocks, Spanish text explained the percentages were based on the guideline daily amounts for a 2,000-Calorie diet [22].
The Nutri-Score label system, which is currently used voluntarily in some European countries [23], is a color coded and letter rated (A-E) system. A dark green “A” indicates the best nutritional value and a dark red “E” indicates the worst nutritional value. A product’s letter rating is determined based on a point system. A higher point value indicates a less healthy product. The more calories, sugar, sodium, and saturated fat a product contains, the more points it receives. However, a product can also receive negative points for containing fiber, protein, and fruits and vegetables, which can decrease the product’s total points [24].
Finally, we decided to also test a no-label condition. Previous experiments on nutrient warning labels have used a neutral barcode as a control in order to measure perceptions of and reactions to front-of-package labels [20]. However, in this study, we wanted to test actual policies that could be implemented by the Colombian government. It is possible that the government could decide to not implement a front-of-package labelling system (status quo), so we also tested a no-label condition to measure the outcomes of maintaining the status quo compared to implementing the nutrient warning label. We used the Peruvian warning labeling guidelines to design the size and placement of the label conditions [25].
Product development and applied labels
Images of the products can be found in Figure A1. We selected food and drink products from categories that are commonly consumed in Colombia and may not be commonly identified as products high in nutrients of concern. We modeled the products after real Colombian ultra-processed products that are high in nutrients of concern (sugar, sodium, and saturated fat). We used three products we had previously tested (fruit drink, oatmeal cookies, and sliced bread) [20], and the same graphic designer who developed our previous products helped in the development of three new products: a no-sugar-added fruit drink, breakfast cereal, and strawberry yogurt. The breakfast cereal was slightly different from the other products because it contained excess amounts of both sugar and sodium. Therefore, the breakfast cereal fashioned two nutrient warning labels, while the other products only had one. All products contained fictional brand names to avoid consumer brand loyalty bias.
For each labelling system, the presence or absence of the label (nutrient warnings) or content of the labels (Nutri-score, GDA) depended on the nutritional composition of the product. Thus, we created nutrition profiles for each product, based on similar Colombian products. Table 1 provides each product’s nutritional profile and the corresponding label applied.
Table 1. Product nutrition details as well as label applied to each product
Product
|
Nutrition profile
|
GDA Label (% of GDA)
|
Nutri-Score Label
|
Nutrient Nutrient warning Label
|
No-sugar added fruit drink
|
Calories: 33.8
Fat: 0g
Saturated Fat: 0g
Sugars: 15.8g
Sodium: 33.8mg
|
Calories: 2%
Fat: 0%
Saturated fat: 0%
Sugars: 18%
Sodium: 1%
|
B
|
None
|
Fruit drink
|
Calories: 168.8
Fat: 0g
Saturated Fat: 0g
Sugars: 39.4g
Sodium: 28.1mg
|
Calories: 8%
Fat: 0%
Saturated Fat: 0%
Sugars: 44%
Sodium: 0%
|
B
|
Excess sugar
|
Strawberry yogurt
|
Calories: 170
Fat: 5g
Saturated Fat: 3g
Sugars: 24g
Sodium: 75mg
|
Calories: 9%
Fat: 7%
Saturated Fat: 15%
Sugars: 27%
Sodium: 1%
|
B
|
Excess sugar
|
Oatmeal cookies
|
Calories: 700
Fat: 35g
Saturated Fat: 15g
Sugars: 15g
Sodium: 200mg
|
Calories: 35%
Fat: 50%
Saturated Fat: 75%
Sugars: 17%
Sodium: 3%
|
C
|
Excess saturated fat
|
Sliced bread
|
Calories: 100
Fat: 2g
Saturated Fat: 1g
Sugars: 0g
Sodium:180mg
|
Calories: 5%
Fat: 3%
Saturated Fat: 5%
Sugars: 0%
Sodium: 3%
|
B
|
Excess salt/sodium
|
Cereal
|
Calories: 130
Fat: 2.5g
Saturated Fat: 0g
Sugars: 6g
Sodium: 135mg
|
Calories: 7%
Fat: 4%
Saturated Fat: 0%
Sugars: 7%
Sodium: 2%
|
C
|
Excess sugar; Excess salt/sodium
|
Participants
In October 2020, we recruited an online national convenience sample of 8,061 adults in Colombia to participate in an experiment. We recruited participants through Offerwise, a market research company with over 300,000 panel participants in Colombia. Inclusion criteria included presently residing in Colombia and being older than 18 years old and younger than 65 years old. We excluded panel members that participated in a previous study of ours investigating the efficacy of different front-of-package nutrient warning labels [20]. We set sample quotas for gender to reflect the Colombian population and for education level (half high school graduate or less, half college degree or higher) to ensure our sample was powered to detect differences in the primary outcome by education level. Participants earned a pre-determined amount of points from Offerwise for completing the study. Participants are able to convert points into money once they accumulate a specified amount.
Procedures
Participants completed an online survey programmed in Spanish using Qualtrics survey software. After providing informed consent, participants were randomized to one of the four front-of-package label conditions: nutrient warning label, Nutri-Score label, GDA label, or a no-label condition. They first completed a selection task, where they were asked a series of questions about two fruit drinks, one of which was healthier (no added sugar) and one of which was less healthy (contained 39.4 grams of sugar). The fruit drinks were displayed according to their randomly assigned condition.
Next, participants completed single product assessment tasks. They viewed a prompt that read: “The next questions are about food products. You will look at a few different products and answer questions about each one. Please keep in mind that this study seeks to evaluate your survey responses and not the sale of the product.” Then, they answered a series of questions about the yogurt, cookies, and sliced bread, which showed their assigned label on them. The participants answered all questions about one product at a time (displayed in random order). After these three products, the participants answered one more set of questions about the breakfast cereal. The breakfast cereal was always displayed last as the nutrient warning label condition contained two labels.
Finally, the participants were randomly assigned to see the yogurt, cookies, or sliced bread again (one product only). However, this time, the product did not include a label. Instead, the three label types were listed underneath the product and the participant was asked questions about the labels. The study ended with standard demographic questions.
Measures
Our study had two primary outcomes, 1) selection of the less healthy fruit drink as the fruit drink the participant would rather buy and 2) correctly identifying which fruit drink was higher in sugar. Secondary outcomes included objective understanding, or the ability to correctly identify the less healthy fruit drink, ability to correctly identify if the products contained excess of nutrients of concern, perceived message effectiveness (PME), intentions to purchase the products, and the most discouraging label. All measures were cognitively tested with Colombians of different education levels to make sure the measures were properly adapted to the Colombian context and accessible to all education levels [26].
For the selection task, participants were asked to select one of the two fruit drinks for the following questions:“Which of these products is MOST unhealthy?”, “Which of these products is higher in sugar?”, and “Which of these products would you rather buy?” Both the order of the three questions and the position of each fruit drink (left or right) were randomized.
Next, for the questions about the yogurt, cookies, and sliced bread, we measured objective understanding, or whether participants could correctly identify if the product contained excess of the nutrient of concern (sugar, sodium, or saturated fat respectively) (yes/no?), and we measured the participants’ likelihood of wanting to purchase the product in the next week if it were available (range from “very much” (coded as 5) to “not at all” (coded as 1)).
We also measured PME of the labels, using three items from the UNC perceived message effectiveness scale [27, 28]which read: “How much does the label…” “make you worried about the health consequences of consuming this product?” (range from “very much” (coded as 5) to “not at all” (coded as 1)), “make consuming this product seem unpleasant to you?” (range from “very much” (coded as 5) to “not at all” (coded as 1)), and “discourage you from wanting to consume this product?” (range from “very much” (coded as 5) to “not at all” (coded as 1)) . Because PME is specifically about labels, we did not measure PME for the no-label condition. For the breakfast cereal, we measured participants’ ability to correctly identify if the product contained excess of the nutrients of concern (sugar and sodium), and we measured PME.
Finally, when participants viewed all three label types below one of the randomly selected products (yogurt, cookies, bread), they were asked to select which label would most discourage them from wanting to consume the product.
Analyses
All analyses were conducted in STATA version 16.0. A two-sided critical alpha of 0.05 was used to assess statistical significance. Using G.Power 3.1.9.4, we estimated that with a sample of ~8,000, alpha of 0.05, and 80% power, we could detect an effect of f=0.036. We excluded participants from analysis if they were duplicate responders (dropped all responses except first), completed the study in less than two minutes, or if they did not answer at least one primary or secondary outcome (see Figure 2).
We calculated unadjusted means (and standard deviations) and percentages for the primary and secondary outcomes. For our secondary outcome, PME, we took the average of the 3 items for each product type (Cronbach's alpha for each product type>.70). We then assessed whether primary and secondary outcomes varied by condition compared to the nutrient warning label. Because the breakfast cereal contained excess of two nutrients of concern, we examined whether the breakfast cereal outcomes exhibited the same pattern prior to adding them to the overall reported measures. We used linear regression for continuous outcomes (including PME) and logistic regression for binary outcomes. For outcomes that were assessed using repeated measures for multiple product types, we used mixed models treating the intercept as random at the respondent level to account for repeated measures. These models included the between-subjects factor (i.e., label type), the within-subjects factor (i.e., product type), and their interaction. We conducted pairwise comparisons of the predicted means or predicted percentages between each label type. We applied Holm’s sequentially rejective procedure [29] to the primary outcomes, objective understanding, the ability to identify if the products contained excess of nutrients of concern, and the likelihood of purchasing the product if it were available to account for multiple comparisons.
To evaluate the most discouraging label, we examined the proportion of participants that selected each label type as the one that most discouraged them from consuming products high in sugar, sodium, or saturated fat.
Finally, to assess whether the effect of label type on the primary outcomes differed by education, we tested for an interaction of nutrient warning with education level specified as low (high school diploma or less) vs. high (college degree or higher) and used a Wald chunk test to determine the joint interaction. We conducted pairwise comparisons to predict percentages by label type and education level.