Use of financial incentives and text message feedback to increase healthy food purchases in a grocery store cash back program: a randomized controlled trial

Food Is Medicine: A Presidential Advisory From the American Heart Association

Unhealthy diets are a major impediment to achieving a healthier population in the United States. Although there is a relatively clear sense of what constitutes a healthy diet, most of the US population does not eat healthy food at rates consistent with the recommended clinical guidelines. An abundance of barriers, including food and nutrition insecurity, how food is marketed and advertised, access to and affordability of healthy foods, and behavioral challenges such as a focus on immediate versus delayed gratification, stand in the way of healthier dietary patterns for many Americans. Food Is Medicine may be defined as the provision of healthy food resources to prevent, manage, or treat specific clinical conditions in coordination with the health care sector. Although the field has promise, relatively few studies have been conducted with designs that provide strong evidence of associations between Food Is Medicine interventions and health outcomes or health costs. Much work needs to be done to create a stronger body of evidence that convincingly demonstrates the effectiveness and cost-effectiveness of different types of Food Is Medicine interventions. An estimated 90% of the $4.3 trillion annual cost of health care in the United States is spent on medical care for chronic disease. For many of these diseases, diet is a major risk factor, so even modest improvements in diet could have a significant impact. This presidential advisory offers an overview of the state of the field of Food Is Medicine and a road map for a new research initiative that strategically approaches the outstanding questions in the field while prioritizing a human-centered design approach to achieve high rates of patient engagement and sustained behavior change. This will ideally happen in the context of broader efforts to use a health equity-centered approach to enhance the ways in which our food system and related policies support improvements in health.

The impact of the consumer and neighbourhood food environment on dietary intake and obesity-related outcomes: A systematic review of causal impact studies

BACKGROUND

The food environment has been found to impact population dietary behaviour. Our study aimed to systematically review the impact of different elements of the food environment on dietary intake and obesity.

METHODS

We searched MEDLINE, Embase, PsychInfo, EconLit databases to identify literature that assessed the relationship between the built food environments (intervention) and dietary intake and obesity (outcomes), published between database inception to March 26, 2020. All human studies were eligible except for those on clinical sub-groups. Only studies with causal inference methods were assessed. Studies focusing on the food environment inside homes, workplaces and schools were excluded. A risk of bias assessment was conducted using the CASP appraisal checklist. Findings were summarized using a narrative synthesis approach.

FINDINGS

58 papers were included, 55 of which were conducted in high-income countries. 70% of papers focused on the consumer food environments and found that in-kind/financial incentives, healthy food saliency, and health primes, but not calorie menu labelling significantly improved dietary quality of children and adults, while BMI results were null. 30% of the papers focused on the neighbourhood food environments and found that the number of and distance to unhealthy food outlets increased the likelihood of fast-food consumption and higher BMI for children of any SES; among adults only selected groups were impacted - females, black, and Hispanics living in low and medium density areas. The availability and distance to healthy food outlets significantly improved children's dietary intake and BMI but null results were found for adults.

INTERPRETATION

Evidence suggests certain elements of the consumer and neighbourhood food environments could improve populations dietary intake, while effect on BMI was observed among children and selected adult populations. Underprivileged groups are most likely to experience and impact on BMI. Future research should investigate whether findings translate in other countries.

Effect of Financial Incentives for Process, Outcomes, or Both on Cholesterol Level Change: A Randomized Clinical Trial

Importance

Financial incentives may improve health behaviors. It is unknown whether incentives are more effective if they target a key process (eg, medication adherence), an outcome (eg, low-density lipoprotein cholesterol [LDL-C] levels), or both.

Objective

To determine whether financial incentives awarded daily for process (adherence to statins), awarded quarterly for outcomes (personalized LDL-C level targets), or awarded for process plus outcomes induce reductions in LDL-C levels compared with control.

Design, Setting, and Participants

A randomized clinical trial was conducted from February 12, 2015, to October 3, 2018; data analysis was performed from October 4, 2018, to May 27, 2021, at the University of Pennsylvania Health System, Philadelphia. Participants included 764 adults with an active statin prescription, elevated risk of atherosclerotic cardiovascular disease, suboptimal LDL-C level, and evidence of imperfect adherence to statin medication.

Interventions

Interventions lasted 12 months. All participants received a smart pill bottle to measure adherence and underwent LDL-C measurement every 3 months. In the process group, daily financial incentives were awarded for statin adherence. In the outcomes group, participants received incentives for achieving or sustaining at least a quarterly 10-mg/dL LDL-C level reduction. The process plus outcomes group participants were eligible for incentives split between statin adherence and quarterly LDL-C level targets.

Main Outcomes and Measures

Change in LDL-C level from baseline to 12 months, determined using intention-to-treat analysis.

Results

Of the 764 participants, 390 were women (51.2%); mean (SD) age was 62.4 (10.0) years, 310 (40.6%) had diabetes, 298 (39.0%) had hypertension, and mean (SD) baseline LDL-C level was 138.8 (37.6) mg/dL. Mean LDL-C level reductions from baseline to 12 months were -36.9 mg/dL (95% CI, -42.0 to -31.9 mg/dL) among control participants, -40.0 mg/dL (95% CI, -44.7 to -35.4 mg/dL) among process participants, -41.6 mg/dL (95% CI, -46.3 to -37.0 mg/dL) among outcomes participants, and -42.8 mg/dL (95% CI, -47.4 to -38.1 mg/dL) among process plus outcomes participants. In exploratory analysis among participants with diabetes and hypertension, no spillover effects of incentives were detected compared with the control group on hemoglobin A1c level and blood pressure over 12 months.

Conclusions and Relevance

In this randomized clinical trial, process-, outcomes-, or process plus outcomes-based financial incentives did not improve LDL-C levels vs control.

Trial Registration

ClinicalTrials.gov Identifier: NCT02246959.

Effect of Personalized Incentives on Dietary Quality of Groceries Purchased: A Randomized Crossover Trial

Importance

Many factors are associated with food choice. Personalized interventions could help improve dietary intake by using individual purchasing preferences to promote healthier grocery purchases.

Objective

To test whether a healthy food incentive intervention using an algorithm incorporating customer preferences, purchase history, and baseline diet quality improves grocery purchase dietary quality and spending on healthy foods.

Design, Setting, and Participants

This was a 9-month randomized clinical crossover trial (AB-BA) with a 2- to 4-week washout period between 3-month intervention periods. Participants included 224 loyalty program members at an independent Rhode Island supermarket who completed baseline questionnaires and were randomized from July to September 2018 to group 1 (AB) or group 2 (BA). Data analysis was performed from September 2019 to May 2020.

Intervention

Participants received personalized weekly coupons with nutrition education during the intervention period (A) and occasional generic coupons with nutrition education during the control period (B). An automated study algorithm used customer data to allocate personalized healthy food incentives to participant loyalty cards. All participants received a 5% grocery discount.

Main Outcomes and Measures

Grocery Purchase Quality Index-2016 (GPQI-16) scores (range, 0-75, with higher scores denoting healthier purchases) and percentage spending on targeted foods were calculated from cumulative purchasing data. Participants in the top and bottom 1% of spending were excluded. Paired t tests examined between-group differences.

Results

The analytical sample included 209 participants (104 in group 1 and 105 in group 2), with a mean (SD) age of 55.4 (14.0) years. They were predominantly non-Hispanic White (193 of 206 participants [94.1%]) and female (187 of 207 participants [90.3%]). Of 161 participants with income data, 81 (50.3%) had annual household incomes greater than or equal to $100 000. Paired t tests showed that the intervention increased GPQI-16 scores (between-group difference, 1.06; 95% CI, 0.27-1.86; P = .01) and percentage spending on targeted foods (between-group difference, 1.38%; 95% CI, 0.08%-2.69%; P = .04). During the initial intervention period, group 1 (AB) and group 2 (BA) had similar mean (SD) GPQI-16 scores (41.2 [6.6] vs 41.0 [7.5]) and mean (SD) percentage spending on targeted healthy foods (32.0% [10.8%] vs 31.0% [10.5%]). During the crossover intervention period, group 2 had a higher mean (SD) GPQI-16 score than group 1 (42.9 [7.7] vs 41.0 [6.8]) and mean (SD) percentage spending on targeted foods (34.0% [12.1%] vs 32.0% [13.1%]).

Conclusions and Relevance

This pilot trial demonstrated preliminary evidence for the effectiveness of a novel personalized healthy food incentive algorithm to improve grocery purchase dietary quality.

Trial Registration

ClinicalTrials.gov Identifier: NCT03748056.