Click & Pick Study

Official title

A Longitudinal, Randomized-Controlled Experiment of Healthy Food Policies in Online Retail Settings

Overview

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.

Detailed description

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.

Interventions

• Behavioral Suite of healthy food policies
  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.

Primary outcome measures

• Average kcals purchased per participant per day from unhealthy ultra-processed food products that are targeted by our suite of healthy food policies [Time frame: Change between baseline and Weeks 2-4 (Aim 1) and Weeks 5-6 (Aim 3)]

Secondary outcome measures (12)

• Average sodium, saturated fat, and added sugars purchased per participant per day from unhealthy ultra-processed food products that are targeted by our suite of policies [Time frame: Change between baseline and Weeks 2-4 (Aim 1) and Weeks 5-6 (Aim 3)]
• Average overall kcals, sodium, saturated fat, and added sugars from all foods purchased in the online grocery store and restaurant per participant per day [Time frame: Change between baseline and Weeks 2-4 (Aim 1) and Weeks 5-6 (Aim 3)]
• Percentage of total dollars per order spent on products targeted by our suite of healthy food policies [Time frame: Change between baseline and Weeks 2-4 (Aim 1) and Weeks 5-6 (Aim 3)]
• Total dollars spent on food and beverage products purchased outside of the study grocery store and restaurant [Time frame: Baseline to Week 6]
• Total dollars spent on sugar sweetened beverages, candy, and fast food purchased outside of the study grocery store and restaurant [Time frame: Baseline to Week 6]
• Healthy Eating Index Score (HEI-2020) [Time frame: Change between baseline and Week 4]
• Change in usual intake for: energy (kcals), discretionary calories, SSB servings per day, total fruit servings/day, total vegetable servings/day, daily intake of key macronutrients, and daily intake of whole grains [Time frame: Change between baseline and Week 4]
• Food and beverage product perceptions [Time frame: Final survey (administered Week 7)]
• Nutrient content knowledge [Time frame: Final survey (administered Week 7)]
• Warning label perceptions [Time frame: Final survey (administered Week 7)]
• Policy opinions [Time frame: Final survey (administered Week 7)]
• Online store perceptions [Time frame: Final survey (administered Week 7)]

Eligibility criteria

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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation

Randomized

Model

Parallel assignment

Masking

Open label

Primary purpose

Prevention

Study locations

United States · 1 center

• University of Pennsylvania — Philadelphia

Publications

• US Burden of Disease Collaborators; Mokdad AH, Ballestros K, Echko M, Glenn S, Olsen HE, Mullany E, Lee A, Khan AR, Ahmadi A, Ferrari AJ, Kasaeian A, Werdecker A, Carter A, Zipkin B, Sartorius B, Serdar B, Sykes BL, Troeger C, Fitzmaurice C, Rehm CD, Santomauro D, Kim D, Colombara D, Schwebel DC, Tsoi D, Kolte D, Nsoesie E, Nichols E, Oren E, Charlson FJ, Patton GC, Roth GA, Hosgood HD, Whiteford PMID 29634829
• Centers for Disease Control. Type 2 Diabetes. Centers for Disease Control. Published December 16, 2021. Accessed September 30, 2022. https://www.cdc.gov/diabetes/basics/type2.html#:~:text=Healthy%20eating%20is%20your%20recipe,them%20have%20type%202%20diabetes.
• Centers for Disease Control. Adult obesity facts. Centers for Disease Control. Published May 17, 2022. Accessed September 30, 2022. https://www.cdc.gov/obesity/data/adult.html
• Andreyeva T, Marple K, Marinello S, Moore TE, Powell LM. Outcomes Following Taxation of Sugar-Sweetened Beverages: A Systematic Review and Meta-analysis. JAMA Netw Open. 2022 Jun 1;5(6):e2215276. doi: 10.1001/jamanetworkopen.2022.15276. PMID 35648398
• An R, Liu J, Liu R, Barker AR, Figueroa RB, McBride TD. Impact of Sugar-Sweetened Beverage Warning Labels on Consumer Behaviors: A Systematic Review and Meta-Analysis. Am J Prev Med. 2021 Jan;60(1):115-126. doi: 10.1016/j.amepre.2020.07.003. Epub 2020 Oct 12. PMID 33059917
• Clarke N, Pechey E, Kosite D, Konig LM, Mantzari E, Blackwell AKM, Marteau TM, Hollands GJ. Impact of health warning labels on selection and consumption of food and alcohol products: systematic review with meta-analysis. Health Psychol Rev. 2021 Sep;15(3):430-453. doi: 10.1080/17437199.2020.1780147. Epub 2020 Jul 2. PMID 32515697
• Grummon AH, Hall MG. Sugary drink warnings: A meta-analysis of experimental studies. PLoS Med. 2020 May 20;17(5):e1003120. doi: 10.1371/journal.pmed.1003120. eCollection 2020 May. PMID 32433660
• Dong D, Bilger M, van Dam RM, Finkelstein EA. Consumption Of Specific Foods And Beverages And Excess Weight Gain Among Children And Adolescents. Health Aff (Millwood). 2015 Nov;34(11):1940-8. doi: 10.1377/hlthaff.2015.0434. PMID 26526253

Identifiers

NCT: NCT07422922 · 855856 · 1R01DK136779-01

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗