University of Pennsylvania
Philadelphia, Pennsylvania, 19104, United States
Location status: Recruiting
Location contact
Christina Roberto, PhD
PRINCIPAL_INVESTIGATOR
Eva Fabian, MPH
CONTACT
Julianna Catania, MPH
CONTACT
NCT Number: NCT07422922
Unhealthy diets significantly contribute to major preventable chronic diseases including type 2 diabetes, obesity, heart disease and stroke, which disproportionally impact racial/ethnic minority groups and those with lower income [1-3]. Although taxes and warning labels targeting sugar-sweetened beverages (SSB) have been successful at shifting behavior [4-7], there are many other ultra-processed food products that contribute to unhealthy diets [8]. What is less well-known is whether a suite of healthy food policies that are expanded to target a range of ultra-processed foods can shift dietary choices and intake in meaningful ways. Our research team's long-term goal is to identify and understand the degree to which combinations of healthy food policies can improve nutrition security and reduce nutrition-related diseases.
Interested in participating?
Request Info18 year and older
All sexes
Interventional
Not applicable
Philadelphia, Pennsylvania, 19104, United States
Location status: Recruiting
Christina Roberto, PhD
PRINCIPAL_INVESTIGATOR
Eva Fabian, MPH
CONTACT
Julianna Catania, MPH
CONTACT
To advance our understanding of policies needed to support nutrition security and health, our overall objective is to examine the degree to which a suite of healthy food policies in online food retailers can increase the purchase and intake of healthy foods and beverages while reducing the purchase and intake of unhealthy ultra-processed foods and beverages.
To accomplish this objective, we will use an innovative online grocery store and restaurant platforms to randomize participants to either: 1) control (no taxes, warning labels, or healthy checkout regulations on any products); or 2) a suite of healthy food policies (ultra-processed food and beverage taxes, front-of-pack nutrition labeling, and healthy check out regulations that restrict the promotion of ultra-processed products on the checkout page). We will recruit 300 adults with lower income across Houston and San Antonio, TX, and Philadelphia, PA to shop once per week for six weeks in both our online grocery store and restaurant. Week 1 will be a baseline (control) week without interventions, followed by three weeks of the interventions. In the last two study weeks, we will introduce unhealthy food marketing (e.g., banner ads) into the online platforms to mimic what we expect industry will do to counter public health policy efforts.
A key aim of the study is to simulate how food companies will respond to healthy eating policies if they were to be implemented in the real world. For that reason, we will increase the intensity of non-checkout advertisements for unhealthy foods during the last two weeks of the intervention period because this is likely how industry would respond in the real-world if the U.S. adopted any of the policies we are testing. Therefore, we are trying to measure the extent to which that advertising would undermine the policy effects. This is a critical component of our study because many nutrition policy experiments look at the impact of a policy in a static situation that does not account for a likely industry response. The advertisements we are using will mimic what's normally seen in delivery/grocery apps such as ads for sugar-sweetened beverages like Coke or Pepsi.
Participants will be given money to spend in these online platforms and purchases will be delivered to them via a real food retail store and restaurant. Participants will complete surveys at baseline and after 6 weeks of shopping and will complete two dietary recalls administered over the phone during the baseline week and during the fourth week (4 recalls total). The rationale underlying the proposed research is based on our work showing that beverage taxes and warning labels greatly reduce SSB purchases.
The specific aims of the study are:
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
For participants living in the Houston or San Antonio areas, their household income must be greater than 165% of the federal poverty level, but less than the Texas state median household income (based on the 2023 American Community Survey) for their household size [11].
For participants living in the Philadelphia area, their income must be greater than 200% of the federal poverty level, but less than the Pennsylvania state median household income (based on the 2023 American Community Survey) for their household size [11].
Exclusion criteria
A suite of healthy food policies in an online restaurant and grocery store including ultra-processed food and beverage taxes, front-of-pack nutrition labeling, and healthy check out regulations that restrict the promotion of ultra-processed products on the checkout pages.
Time frame: Change between baseline and Weeks 2-4 (Aim 1) and Weeks 5-6 (Aim 3)
We will sum the number of kcals from ultra-processed food products purchased in the online grocery store and divide that by the number of people in the household and 7 days per week. We will then add that to the number of kcals from ultra-processed foods purchased from the online restaurant to calculate total kcals from ultra-processed foods purchased per study participant per day. We will also examine these outcomes separately in the grocery store and restaurant context.
Time frame: Change between baseline and Weeks 2-4 (Aim 1) and Weeks 5-6 (Aim 3)
Using the same approach as our primary outcome, our secondary behavioral outcomes will be the average sodium, saturated fat, and added sugars purchased per participant per day. We will also examine these outcomes separately in the grocery store and restaurant context.
Time frame: Change between baseline and Weeks 2-4 (Aim 1) and Weeks 5-6 (Aim 3)
We will create this outcome using the same approach as our primary outcome, except we will look at all foods and beverages purchased, not just ultra-processed foods and beverages. We will also examine these outcomes separately in the grocery store and restaurant context.
Time frame: Change between baseline and Weeks 2-4 (Aim 1) and Weeks 5-6 (Aim 3)
To create this outcome for each week of the study, we will divide the number of dollars spent on targeted ultra-processed products by the total dollars spent and multiply by 100.
Time frame: Baseline to Week 6
We will sum together the total amount of dollars spent on food and beverages purchased outside the study using outside receipts submitted by the participants.
Time frame: Baseline to Week 6
Total dollars spent on sugar sweetened beverages, candy, and fast food purchased outside the study using outside receipts submitted by the participants.
Time frame: Change between baseline and Week 4
The HEI is a tool to assess how well a participant's diet aligns with the 2015-2020 Dietary Guidelines for Americans and can be used to measure the efficacy of nutrition interventions [9]. We will average intake estimates from the two 24-hour dietary recall interviews conducted at baseline and again at follow up (Week 4).
Time frame: Change between baseline and Week 4
We will average intake estimates from the two NDSR 24-hour dietary recall interviews conducted at baseline and again at follow up (Week 4) [10].
Time frame: Final survey (administered Week 7)
During the final survey (Week 7), participants will view four ultra-processed products. Those in the intervention group will see those products with any applicable warning labels and those in the control group will see the same products without any warning labels. Participants will then rate how healthy or unhealthy they believe the product to be.
Time frame: Final survey (administered Week 7)
During the final survey (Week 7), participants will also be asked about their knowledge of different nutrients of concern, and we will determine whether they provide the correct answer or not. They will view the same four ultra-processed products as the food and beverage product perceptions questions and be asked whether or not the product has low, medium, or high amounts of calories, sodium, saturated fats, and added sugars.
Time frame: Final survey (administered Week 7)
At the end of the final study survey (Week 7), participants will be shown the warning labels used in the study and asked about perceived message effectiveness.
Time frame: Final survey (administered Week 7)
During the final survey (Week 7), participants will also answer four questions about their support or opposition for the suite of healthy food policies.
Time frame: Final survey (administered Week 7)
We will assess the acceptability of the online grocery store and restaurant (e.g., overall difficulty of using the grocery store/restaurant, satisfaction with number of options) and realism of the online grocery store and restaurant (e.g., extent to which participants' selections are similar to usual purchases, extent to which it felt real).
Contact information is provided by the study sponsor or research team.
Eva Fabian, MPH
CONTACT
Julianna Catania, MPH
CONTACT
University of Pennsylvania
Other
A Longitudinal, Randomized-Controlled Experiment of Healthy Food Policies in Online Retail Settings
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
Published trials that share one or more normalized conditions with this study.
NCT07718334
Behavior, Chronic Disease
Gamasa, Dakahlia Governorate, Egypt
View Trial DetailsNCT06925373
Chronic Disease, Disease Attributes
Birmingham, Alabama, United States
View Trial DetailsNCT06748118
Behavior, Chronic Disease
Angers, France
View Trial DetailsNCT07441655
Behavior, Chronic Disease
Albany, Georgia, United States
View Trial Details