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.

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:

• Aims 1: To evaluate the effects of three healthy food policies (ultra-processed food and beverage taxes, front-of-pack nutrition warning labels, and healthy checkout regulations) on purchases across online grocery store and restaurant settings.
• Aim 2: To evaluate the effects of three healthy food policies (ultra-processed food taxes, front-of-pack nutrition warning labels, and healthy checkout regulations) on dietary quality.
• Aim 3: To understand the degree to which unhealthy food marketing counters the effects of a suite of healthy food policies.

Inclusion Criteria:

• ≥18 years old
• Not currently eligible for or participating in SNAP or another government program that automatically qualifies the person for SNAP (e.g., WIC, TANF)
• Meets the following income eligibility requirements:

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].

• Reports consuming food from McDonald's or a similar fast-food chain at least once a month
• Does most of the grocery shopping for the household
• Can adhere to the study schedule (e.g., receive a lunch on a Wednesday)
• Has regular internet access
• Has a smart phone that can take pictures
• Resident of Houston, TX, San Antonio, TX or Philadelphia, PA or the surrounding areas and plans to be there for the next six weeks
• Household size of six or fewer people
• Have an address eligible for receiving Grubhub+ and Walmart+ deliveries

Exclusion Criteria:

• Does not meet all of the inclusion criteria
• Cognitive impairment; per PIs discretion
• Participant is under 18 years old
• Does not speak English or Spanish

De-identified data available for public use and associated documentation will be available to the research community free of charge through the Data Sharing for Demographic Research (DSDR) data repository hosted at ICPSR. Data and datasets will be kept and available to share for at least three years following completion of the project, in accordance with NIH regulations. Datasets in DSDR will be findable and identifiable through a study digital object identifier (DOI) minted by ICPSR.