Centering Equity in FDA Regulation: Front-of-package Food Label Effects in Latine and Limited English Proficiency Populations
Phase: NA
Conditions: Diet, Healthy
Sponsor: University of North Carolina, Chapel Hill

Centering equity in FDA regulation: Front-of-package 
food label effects in Latiné and limited English 
proficiency populations 
NCT number NCT06293963 
Document Date 07/26/2024 

Study Protocol and Analytic Plan 
Title: Centering equity in FDA regulation: Front-of-package food label effects in Latiné and 
limited English proficiency populations 
NCT #: NCT06293963 
Introduction 
This study aims to determine the front-of-package label design that is most effective at helping 
Latiné consumers identify healthier products and to explore whether the benefits of front-of-
package label design differ by English proficiency. This document pre-specifies our planned 
analytic approach prior to data collection. 
Study Protocol 
Participants will complete an online randomized experiment programmed in Qualtrics. After 
providing informed consent, participants will be randomly assigned to view 1 of 4 types of front-
of-package nutrient labels: numerical label, interpretive text-only label, interpretive label 
containing a magnifying glass icon, or separated interpretive labels containing a magnifying 
glass icon. Participants will view 3 sets of similar products (with 3 products per set) displaying 
their assigned label type and will answer selection questions about the products. These 
selection questions will be repeated 3 times, once for each food product. The survey will also 
ask questions about reactions to the labels and demographics in the online survey. 
Hypotheses 
Correct identification of healthiest product (co-primary outcome): We predict that correct 
identification of the healthiest product will be highest for participants assigned to the separated 
interpretive magnifying glass icon label, followed by the interpretive magnifying glass icon label, 
the interpretive text-only label, and the numerical label (H1). 
Correct identification of least healthy product (co-primary outcome): We predict that correct 
identification of the least healthy product will be highest for participants assigned to the 
separated interpretive magnifying glass icon label, followed by the interpretive magnifying glass 
icon label, the interpretive text-only label, and the numerical label (H2). 
Correct identification of products high in nutrients (secondary outcome): We predict that correct 
identification of which products are high in nutrients of concern will be highest for participants 
assigned to the separated interpretive magnifying glass icon label, followed by the interpretive 
magnifying glass icon label, the interpretive text-only label, and the numerical label (H3). 
Selection of healthiest product for purchase (secondary outcome): We predict selection of the 
healthiest product will be highest for participants assigned to the separated interpretive 
magnifying glass icon label, followed by the interpretive magnifying glass icon label, the 
interpretive text-only label, and the numerical label (H4). 
Main Analyses 
We will use a two-sided critical alpha of 0.05 to conduct all statistical tests. All confidence 
intervals presented will use a 95% confidence level. Analyses of the primary and secondary 
outcomes will include all participants according to the trial arm to which they were randomized. 

For all of the selection tasks, participants will have a time limit to simulate real-world conditions 
where people make shopping decisions quickly. We will recode missing data as “no” or 
“incorrect” for all 4 selection outcomes. The healthiest product is defined as the one that is high 
in the fewest number of nutrients of concern (i.e., only 1 nutrient). The least healthy product is 
defined as the one that is high in the highest number of nutrients of concern (i.e., 3 nutrients). 
Correct identification of products high in nutrients is defined as identifying the products having 
20% or more of the daily value of the nutrient or labeled with “high in,” per FDA’s guidance 
around “high” levels of nutrients of concern. The responses to these three correct identification 
tasks will be dichotomized as correct vs. incorrect. For the selection outcome, we will 
dichotomize the outcome to selection of the healthiest product vs. selection of either of the other 
two products. 
We will descriptively report unadjusted means for the primary and secondary outcomes for each 
experimental arm. To test H1-H4, analyses will use mixed effects logistic regression models to 
examine the impact of label arm on the outcomes, accounting for repeated measures within 
participants. Models will regress the outcome on indicator variables for the labeling arm 
(excluding the numerical label as the referent) and indicator variables for product category, 
treating the intercept as random. Analyses will calculate average differential effects for each 
interpretative label compared to the numerical label, representing the differences in predicted 
probabilities by label type. We will also compare each interpretive label to each other. We will 
not adjust the p-value for each label type compared to the numerical label. We will adjust for 
multiple tests for the three additional pairwise comparisons (within each family of outcomes) 
among interpretive labels using a Bonferroni-Holm correction. 
Exploratory Analyses 
In exploratory analyses, we plan to report the impact of label type on the primary and secondary 
outcomes when stratifying by product type. 
To examine whether the impacts of front-of-package label design on the co-primary outcomes 
differ by English proficiency, we will regress outcomes on label type, product type, English 
proficiency (high vs. limited), and the interaction between label type and English proficiency. 
These analyses will use linear probability models (rather than logistic regression) to aid in 
interpretation, as recommended for examining moderation for binary outcomes. We will use the 
same approach to determine whether the impacts of front-of-package label design differs by 
parental status. 
Additionally, the survey will display 4 types of icon labels in random order, asking participants 
which label best signals when foods are high in sodium, saturated fat, and added sugars and 
which label most discourages purchasing of foods high in these nutrients. To assess which icon 
designs are most promising for front-of-package nutrition labels, we will calculate the proportion 
of participants who selected each label as best signaling when foods are high in sodium, 
saturated fat, and added sugars and the proportion who selected each label as most 
discouraging of purchasing foods high in these nutrients. 
Sample Size and Power 
We used G*Power 3 to estimate sample size needs. To be conservative, we powered the study 
to detect a difference in the co-primary outcomes between the 2 label designs that we anticipate 
will be most similar (i.e., the interpretative magnifying glass icon and interpretative text-only 
label). Power analyses assumed 55% of participants in the interpretative magnifying glass icon 

condition would correctly identify the least healthy and healthiest products (based on a prior 
study using similar methods) and a two-tailed critical alpha of 0.017 (0.05 divided by 3 to correct 
for multiple comparisons). Under these assumptions, a sample of 1,000 per condition (4,000 
total) yields 80% power to detect effects of OR=1.16 or larger between any 2 label designs for 
each primary outcome. This is a conservative estimate of effect size based on prior studies 
showing effect sizes of 1.10–1.80 between similar labels. This would be considered a small 
effect size, equivalent to Cohen’s d=0.08. 
Interim Analysis 
No interim analyses are planned. 
Exclusions and Outliers 
We will exclude participants who complete the survey implausibly quickly (defined as <1/3 of the 
median completion time). We will exclude participants who complete less than 90% of the 
survey.