Impacts of Prolonged Exposure to Added Sugar Warning Labels on Explicit Weight Bias: a Randomized Controlled Trial
Phase: NA
Conditions: Nutrition, Diet Interventions
Sponsor: University of North Carolina, Chapel Hill

Complete Title: Impacts of Prolonged Exposure to Added Sugar Warning Labels on Explicit Weight 
Bias: a Randomized Controlled Trial 
Protocol Date: Jan 27th, 2026 
NCT #: 07346001 
 
Study Principal Investigator:  
Aline D’Angelo Campos 
University of North Carolina 
email: adangelo-campos@unc.edu 
 
 
  
 
 

Study Protocol 
 
Study title 
Impacts of prolonged exposure to added sugar warning labels on explicit 
weight bias: a randomized controlled trial 
Funder 
N/A 
Study rationale 
• 
Interventions are needed to address sugar-sweetened beverage 
(SSB) consumption, which is a top source of added sugar in the 
United States 
• 
Weight stigma is harmful and should be avoided in public health 
and nutrition interventions  
• 
“HIGH IN ADDED SUGAR” warnings have been implemented in 10+ 
countries to help address high SSB consumption, but it is unclear 
whether these warnings may impact weight stigma 
Study objectives 
• 
Evaluate whether “HIGH IN ADDED SUGAR” warning labels on SSBs 
impact explicit weight bias body weight attributional judgements 
• 
Evaluate whether the impact of “HIGH IN ADDED SUGAR” warning 
labels on explicit weight bias body weight attributional judgements 
varies by length of exposure to the warning labels 
• 
Evaluate whether the impact of “HIGH IN ADDED SUGAR” warning 
labels on explicit weight bias body weight attributional judgements 
varies by demographic characteristics 
Study design 
 
Randomized clinical trial 
Number of 
participants  
~543 participants 
Study duration 
Each participant is in the trial for ~3 weeks (for a total of 4 store visits 
spaced one week apart). The trial enrollment period is expected to last ~24 
months. 
Study phases 
  
The trial will have two phases: 
(1) Screening: screening for eligibility and obtaining consent  
(2) Intervention: intervention/experimental treatment 
Study arms and 
interventions 
• 
Control label arm: the control label will display a neutral, square-
shaped barcode; labels will be placed on the front of SSB 
containers in the experimental store 
• 
Added sugar warning arm: the added sugar warning will be octagon-
shaped and will state “HIGH IN ADDED SUGAR”; warnings will be 
placed on the front of SSB containers in the experimental store 
Primary 
outcomes 
• 
Explicit weight bias, mean score: measured by survey (post 
shopping visit) through seven items. Items will present participants 
with pairs of antonyms and ask that they select the box between 
antonyms that they feel best describes their feelings and beliefs 
about people with obesity: (1) lazy - hard-working, (2) no will power - 
has will power, (3) good self - control - poor self-control, (4) active - 
inactive, (5) self-indulgent – self-sacrificing, (6) dislikes food - likes 
food, (7) undereats - overeats. Response options, which will be 

presented as 5 boxes between antonyms, will be coded in a 
categorical 1-5 range, where higher scores represent higher 
endorsement of a stereotype that contributes to weight bias. Each 
participant's responses to each item will then be averaged across 
the seven items to obtain their final score on the outcome in a 1-5 
range, where higher scores represent higher explicit weight bias. 
• 
Body weight attributional judgements, mean score: measured by 
survey (post shopping visit) through two items. Items will ask 
participants how much they agree with two statements: (1) People 
with obesity are responsible for their weight; (2) People with obesity 
are to blame for their weight. Response options will be on a 5-point 
scale from strongly disagree to strongly agree, with higher scores 
representing higher agreement. Each participant's responses to 
each item will be averaged to obtain their final score on the 
outcome in a 1-5 range, where higher scores represent higher 
attribution of personal responsibility for body weight. 
 
 
Statistical Analysis Plan 
 
Hypotheses 
We hypothesize that “HIGH IN ADDED SUGAR” warning labels will not lead to greater explicit weight 
bias and body weight attributional judgements. 
 
Main Analyses 
Analyses will include all participants who attended Visit 1. We will use complete case analysis to 
handle any missing data. Analyses will employ a critical alpha of 0.05 and two-tailed tests. 
First, we will verify that outcomes exhibit sufficient internal reliability (Cronbach’s alpha ≥0.7) and 
average responses across measure items. If internal reliability is not sufficient, we will drop items 
as needed to improve reliability or treat items as separate constructs. 
To examine the impact of trial arm on each outcome, we will fit mixed-effects linear regression 
models, treating the intercept as random to account for repeated measures within participants. 
Models will regress each outcome on indicator variables for labeling condition (omitting the control 
arm as the reference), study visit (i.e., visit 1 or 4, omitting visit 1 as the reference), and the 
interaction between the indicator variables for the warning label arm and visit 4. If the interaction 
term is statistically significant, we will probe it and report the average differential effect (ADE) -i.e., 
differences in predicted means between study arms – of the warning label on the outcomes at each 
study visit. On the other hand, if the interaction term is not significant, we will drop it from the 
model and report the ADE the warning label on the outcomes across study visits. 
Exploratory Analyses 
We will examine whether participant characteristics (i.e., gender, age, race/ethnicity, and perceived 
weight status) and SSB purchase during the shopping task (yes/no) moderate the effect of the 
warning label on the primary outcome. If there are no significant interactions between labeling 
condition and study visit in the main analyses, we will fit a series of mixed-effects linear models 

(one for each moderator) to regress each outcome on indicator variables for labeling condition, 
study visit, the moderator, and two-way interaction(s) between labeling condition and the 
moderator. If, alternatively, the main analyses reveal significant interactions between labeling 
condition and study visit, we will fit separate moderation models for visit 1 and visit 4. We will 
consider moderation to be supported if the interaction term(s) between labeling condition and the 
moderator (in either scenario) is/are statistically significant (for categorical moderators with more 
than 2 categories, we will use Wald tests to determine the joint statistical significance of the 
interactions post model estimation). If moderation is supported, we will probe the interaction(s) by 
calculating the marginal effect of the warning label on the outcome at different levels of the 
moderator. 
Sample size needs  
This study will occur in a survey that will follow a parent study in the experimental store, which will 
examine the impact of the “HIGH IN ADDED SUGAR” warning labels on SSB purchases. The total 
sample size (~543 participants) was calculated based on the primary outcomes of the parent study. 
Using G*Power3.1.9.4 and specifying a between-subjects ANOVA (which should most closely 
approximate the first proposed mixed linear model), 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, two conditions, and two repeated measures, we would be able to 
detect an effect of f=0.104 (equivalent to d=0.21, considered a small effect) or larger for the “HIGH 
IN ADDED SUGAR” warning labels.  
Interim Analysis 
No interim analyses are planned.