Fruit and vegetable (FV) intake decrease the risk of type 2 diabetes (T2D) and is important for T2D management but is difficult to achieve in adequate amounts for those with a low- income. Produce Prescription (PPR) projects are an intervention aligned with the social determinants of health that help individuals with a low-income purchase FV by providing an incentive. The impacts of PPR projects on populations with T2D and a low-income is less understood. The Multi-level evaluation of Produce Prescription Projects on type 2 diabetes- related outcomes: A pathway to policy change by addressing social determinants of health study will determine the impact of PPR projects on hemo-globin A1c (HbA1c; primary outcome), fruit and vegetable intake (FVI), food security, and related behaviors among a diverse sample of PPR participants diagnosed with T2D and low-income (Aim 1), and will conduct a cost and cost-effective analysis of PPR projects (Aim 2), and a mixed methods process evaluation to understand feasibility and best practices for PPR projects for people with/at risk for T2D (Aim 3). We hypothesize that PPR participants will see greater declines in HbA1c and improvements in other health and food-related behaviors, compared to the Standard of Care. We will recruit five GusNIP PPR projects, whose healthcare partners serve patients with T2D, and who have participating and matched non-participating control populations. We will collect data at baseline and post-intervention using validated, survey modules, clinical measures, and cost data. Five types of data will be used for this project: 1.Health and healthcare utilization data from the EHR or point-of-care, 2.Participant survey data, 3.Qualitative data, 4.Program cost data (NOT human subjects), and 5.Process data (NOT human subjects). Information extracted from medical records includes HbA1c, weight, and blood pressure and will be collected at 2 time points (months 0,6), following their standard of care protocols. Staff will also extract healthcare utilization data (e.g., #primary care and #ER visits) from the EHR at each of site. Primary analyses will use an intention to treat strategy. Analysis will include a linear mixed-effect model to the HbA1c with an interaction between group and time to examine whether there is a difference in HbA1c trajectories between intervention and control groups. Similar models will be used to determine impact on each of the secondary outcomes (e.g., healthcare utilization, BMI).
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Hemoglobin A1c
Timeframe: Months 0,6