Impact of Front-of-package Labels on Weight Bias Among Latine and Limited English Proficiency Populations
Phase: NA
Conditions: Weight Prejudice
Sponsor: University of North Carolina, Chapel Hill

Study Protocol and Analytic Plan 
 
Title: Impact of Front-of-Package Labels on Weight Bias Among Latines 
Date: April 29th 2024 
NCT #: NCT06293937 
 
Introduction 
The goal of the analysis described in this document is to use data to be collected 
through an online experiment with a sample of Latine and low English proficiency adults 
to examine the effects on explicit weight bias of a selection task using 4 different types 
of front-of-package food labels. 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 during a product selection task: numerical label, 
interpretive text-only label, interpretive label containing a magnifying glass icon, or 
separated interpretive labels containing a magnifying glass icon. Participants will first 
view their assigned label on 3 sets of products (with 3 products per set) and select the 
product they believe is most and least healthy and the product they most want to 
purchase. After this selection task, participants will answer questions measuring explicit 
weight bias and attribution of personal responsibility of body weight. 
Hypotheses 
Explicit weight bias (primary outcome): We hypothesize that there will be no difference 
in weight bias between participants in the 4 arms (H1).  
Attribution of personal responsibility for body weight (secondary outcome): We 
hypothesize that there will be no difference in attribution of personal responsibility for 
body weight between participants in the 4 arms (H2). 
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. 
To prepare the data, we will verify that Cronbach’s alpha for the explicit weight bias 
scale is sufficient (≥0.7) and, if so, we will average items to create a mean score on this 
scale for each participant. If Cronbach’s alpha is not sufficient (<0.7), we will drop items 
as necessary to improve reliability or treat items as separate constructs. We will also 
examine the Spearman Brown coefficient for the two-item scale used to measure 
attribution of personal responsibility for body weight and create a mean score on this 
scale for each participant. 

We will descriptively report unadjusted means for the primary and secondary outcomes 
for each experimental arm. To test H1 and H2, we will fit separate linear regression 
models including indicator variables for label type and specifying the numerical label as 
the referent type. We will additionally use these models to estimate the effects of text-
only vs. magnifying glass, text-only vs. exclamation point, and magnifying glass vs. 
exclamation point. We will not adjust the p-value for each label type compared to the 
numerical label, but will adjust for multiple tests for the three additional pairwise 
comparisons using the Bonferroni-Holm correction. 
Exploratory Analyses 
We may examine how demographic characteristics (i.e., gender, age, race, education, 
English proficiency, percentage of life spent in the US, and perceived weight status) 
correlate to weight bias among participants. We will fit a linear model including these 
characteristics as independent variables. If the main analysis reveals a significant effect 
of the experimental arms on explicit weight bias, we will also include label type in the 
model as an independent variable. 
Sample Size and Power 
This study will follow a parent study examining the effects of a selection task using the 
aforementioned label types on participants’ desire to purchase and ability to identify the 
healthiest product in each product set. The total sample size (~4,000 participants) was 
calculated based on the primary outcomes of the parent study. 
Using G*Power3.1 (ANOVA: fixed effects, omnibus, one-way) we determined the 
minimum effect size we would be able to detect on our primary outcome with this pre-
determined sample size. With 80% power, a critical alpha of 0.05, and 4 groups, we 
would be able to detect an effect of f=0.066 (equivalent to d=0.13). Given that a 
previous study to analyze the effect of FOPLs on weight bias obtained an effect size of 
d=0.16 comparing warning labels to control labels, this study’s sample should be 
sufficiently large to detect similar effects. 
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.