Vadiveloo MK, Parker HW, Thorndike AN. Participant Characteristics Associated with High Responsiveness to Personalized Healthy Food Incentives: a Secondary Analysis of the Randomized Controlled Crossover Smart Cart Study.
J Nutr 2023;
152:2913-2921. [PMID:
36040345 PMCID:
PMC11530363 DOI:
10.1093/jn/nxac197]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 08/09/2022] [Accepted: 08/26/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND
Personalized dietary behavioral interventions could be enhanced by understanding factors accounting for individual variability in dietary decisions.
OBJECTIVE
This study was a secondary analysis of the Smart Cart randomized controlled trial to determine whether participant characteristics predicted high responsiveness to personalized grocery incentives for purchasing healthy food.
METHODS
This secondary analysis of a 9-mo crossover study included 192 regular shoppers (86%) from a Rhode Island supermarket. To analyze whether health, behavioral, and/or sociodemographic characteristics predicted responsiveness to a personalized grocery incentive intervention, participants were divided into 3 categories [high (n = 47), moderate (n = 50), and unresponsive (n = 95)] based on percentage changes in their Grocery Purchase Quality Index scores during the intervention versus control period calculated from sales data. We tested whether participant characteristics, including individual, household, and intervention-related factors, differed across responsiveness groups using ANOVA and whether they predicted the likelihood of being high responsive versus unresponsive or moderate responsive using logistic regression.
RESULTS
Participants had a mean (SD) age of 56.0 (13.8) y and were 89% female. Education, self-reported BMI, income, diet-related medical condition, food insecurity, cooking adequacy, and value consciousness differed across responsiveness categories (P < 0.1). High versus moderate and unresponsive participants increased their percentage of spending on targeted foods (P < 0.0001) and purchased fewer unique items (P = 0.01). In multinomial adjusted models, the odds of being high versus unresponsive or moderate responsive were lower for participants with a BMI (in kg/m2) <25 versus ≥25 (OR: 0.41; 95% CI: 0.19, 0.90) and higher with a diet-related medical condition present (OR: 3.75; 95% CI: 1.20, 11.8). Other characteristics were not associated with responsiveness.
CONCLUSIONS
Findings demonstrated that a BMI ≥25 and having a diet-related medical condition within the household predicted high responsiveness to a personalized grocery purchasing intervention, suggesting that personalized dietary interventions may be particularly effective for households with higher health risk. This trial is registered at www.clinicaltrials.gov as NCT03748056.
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