Every trainer has heard a version of the phrase “Food is medicine.”
Sometimes it’s a thoughtful statement. Sometimes it’s a marketing hook. And sometimes it’s a client trying to make sense of conflicting advice after one too many late-night “wellness” rabbit holes.
In Article 1 of this series, we focused on why adults often struggle to evaluate online health and nutrition information—even when they feel confident doing so (Dissen et al., 2021; Mohamed et al., 2023; Quinn et al., 2017). That matters here because the food-as-medicine movement increasingly lives at the intersection of clinical care and digital delivery(Kim et al., 2023; Quinn et al., 2017).
This article takes the next step.
Specifically, we’ll look at what the peer-reviewed literature supports about food-as-medicine approaches, where the evidence is strong, where it’s still emerging, and what it means for trainers who coach behavior in the real world.
Food as Medicine Is a Framework—Not a Slogan
The food-as-medicine movement reflects a shift in preventive healthcare: dietary patterns and nutrition interventions are being positioned as tools for disease prevention, health promotion, and chronic disease management (Landry, 2015).
This is not one program or one diet. It is a broad umbrella of approaches that range from dietary pattern counseling to structured meal interventions delivered through healthcare and community systems.
In the current literature, food-as-medicine most commonly shows up as a few overlapping categories:
- Medically tailored meals (MTMs): condition-specific meals delivered to individuals with complex medical needs
- Medically tailored groceries (MTGs): structured grocery support often paired with nutrition education
- Produce prescriptions (PRx): “prescribed” fruits and vegetables, frequently subsidized or voucher-based
- Dietary pattern interventions: Mediterranean-style, DASH, and plant-forward patterns
- Culinary medicine: cooking skill education integrated with nutrition science
These models differ in intensity, cost, delivery systems, and population targets, which is one reason the evidence base can look uneven when you zoom out (Lee et al., 2014).
Why the Movement Has Momentum: Diet-Related Disease Burden
The public health rationale is straightforward.
Dietary patterns are consistently linked to major chronic diseases, including cardiovascular disease, type 2 diabetes, obesity, and certain cancers, and a poor diet is repeatedly identified as a leading modifiable risk factor for morbidity and mortality (Landry, 2015).
At the population level, this translates into substantial healthcare costs and preventable disability burden, which is why clinicians, insurers, and policymakers have increased interest in food-based preventive strategies (Landry, 2015).
This is the “why now” behind food-as-medicine.
But momentum does not automatically mean maturity. Evidence quality and implementation barriers still matter (Lee et al., 2014).
How Food Acts Like Medicine: Mechanisms That Support the Concept
Food-as-medicine is often framed as a philosophy, but the movement’s modern credibility is tied to biological mechanisms that connect dietary intake to disease processes.
Nutrient–gene interactions and metabolic signaling
Nutrigenomics describes how dietary components interact with the genome and influence gene expression and metabolic pathways (Kim et al., 2023). This includes effects on inflammation, oxidative stress, and epigenetic regulation—mechanisms that are repeatedly implicated in chronic disease development (Kim et al., 2023).
The key point for trainers is not that clients need to memorize nutrigenomics.
It’s that dietary patterns can plausibly influence health outcomes through multiple pathways—not just “calories in, calories out” (Kim et al., 2023).
The gut microbiome as a mediator
The gut microbiome is increasingly described as a mechanism linking diet to inflammation and metabolic health. Fiber-rich, plant-forward patterns support microbial diversity and short-chain fatty acid production, whereas ultra-processed, low-fiber patterns are associated with dysbiosis and systemic inflammation (Kim et al., 2023).
This matters because chronic low-grade inflammation is a shared feature across many chronic diseases (Kim et al., 2023).
Anti-inflammatory and antioxidant effects
Whole foods—fruits, vegetables, legumes, nuts, seeds, and whole grains—contain bioactive compounds with anti-inflammatory and antioxidant activity, and dietary patterns that reduce inflammatory markers are increasingly viewed as clinically meaningful preventive strategies (Kim et al., 2023).
As a result, mechanisms support plausibility, and clinical outcomes determine practice.
What the Clinical Evidence Supports (and Where It’s Still Developing)
Dietary pattern interventions
Mediterranean-style and DASH patterns have strong support for cardiovascular risk reduction and blood pressure control, and the literature often treats these as cornerstone dietary frameworks within preventive approaches (Landry, 2015).
Plant-forward dietary patterns have also been associated with reduced type 2 diabetes risk and improved glycemic control, with improvements in insulin sensitivity and body weight commonly mediating these effects (Landry, 2015).
These patterns matter because they are teachable, scalable, and behaviorally coherent—especially when coaching focuses on pattern consistency rather than “perfect” execution (Landry, 2015).
Medically tailored meals
Medically tailored meal programs are one of the most direct clinical expressions of food-as-medicine. The literature reports associations with reduced hospitalizations, fewer emergency department visits, improved dietary quality, and lower healthcare costs in medically complex populations (Landry, 2015).
That said, the broader evidence landscape remains heterogeneous in study design and outcome selection, which complicates the ability to draw definitive conclusions and achieve guideline-level precision (Lee et al., 2014).
Produce prescription programs
Produce prescription programs frequently show improvements in fruit and vegetable intake and reductions in food insecurity among low-income participants, with some studies reporting improvements in clinical biomarkers such as HbA1c and blood pressure (Landry, 2015).
But the evidence base is also described as heterogeneous. Differences in program design, target populations, and outcome measures make it harder to generalize across programs (Lee et al., 2014).
Culinary medicine
Culinary medicine combines cooking instruction with nutrition science and has been associated with improvements in dietary quality, cooking self-efficacy, and nutrition knowledge (Cho et al., 2018).
It has also been integrated into medical education as a strategy to address persistent gaps in nutrition training, which affects clinician confidence in dietary counseling (Cho et al., 2018; Landry, 2015).
The Hidden Determinant: Nutrition Literacy
Even the best program fails if the participant cannot understand or apply the guidance.
Nutrition literacy is the capacity to obtain, process, and understand nutrition information in order to make appropriate dietary decisions (Landry, 2015).
This is where the equity piece becomes unavoidable.
Populations at higher risk for low health literacy—older adults, low-income individuals, racial/ethnic minorities, and individuals with limited formal education—are also disproportionately affected by diet-related chronic disease (Landry, 2015; Quinn et al., 2017). That creates a compounding vulnerability that food-as-medicine programs must address intentionally (Landry, 2015).
In short, food access is necessary but not sufficient.
Digital Delivery Changes the Rules: eHealth Literacy as a Gatekeeper
Food-as-medicine programs increasingly use digital tools—such as apps, patient portals, telehealth, and online education—to deliver nutrition guidance and support (Quinn et al., 2017).
That introduces a gatekeeper variable: eHealth literacy.
eHealth literacy is the ability to seek, locate, evaluate, and apply electronically sourced health information (Quinn et al., 2017). It relies on multiple literacies, including health literacy, information literacy, media literacy, and computer literacy (Dominick et al., 2009).
And the literature is clear that evaluation skills are often inadequate.
Dissen et al. (2021) found that even digitally experienced undergraduate students struggled to accurately distinguish credible from non-credible online health information. Mohamed et al. (2023) similarly emphasized that users frequently rely on superficial cues when judging credibility rather than evaluating the quality of the evidence.
That continuity from Article 1 matters here because digital food-as-medicine tools can unintentionally exclude those most at risk if they require strong evaluation skills, high digital competence, or complex navigation (Dissen et al., 2021; Mohamed et al., 2023).
Kim et al. (2023) further noted that digital health literacy is multidimensional and context-dependent, meaning the same person may perform well in one digital environment and poorly in another.
Digital reach is not the same as digital access.
Equity, Access, and the Risk of “Medicalizing” Food
Food-as-medicine intersects with food insecurity and broader social determinants of health. Programs such as food pharmacies and medically tailored groceries are often designed to address these barriers directly (Landry, 2015).
However, the literature also cautions against overly medicalizing food while ignoring structural determinants like poverty, housing instability, and systemic barriers that shape food access (Landry, 2015).
This is why equity needs to be a design feature, not a talking point.
Digital platforms, paperwork requirements, travel burden, and language complexity can all become access barriers, especially for populations with lower health literacy and eHealth literacy (Quinn et al., 2017; Mohamed et al., 2023).
Lee et al. (2014) also highlighted that interventions aimed at improving consumers’ ability to find reliable online health information vary considerably and often rely on self-reported outcomes, which can overestimate their real-world impact.
Scope Boundaries for Trainers
This movement can tempt trainers into roles that aren’t theirs.
Staying in scope protects your clients and your credentials.
What trainers CAN do?
You can reinforce evidence-informed dietary patterns and behaviors that support training outcomes (Landry, 2015). You can help clients improve nutrition literacy by clarifying terminology, supporting consistency, and encouraging practical skill-building (Landry, 2015).
You can also coach eHealth literacy behaviors at a basic level—helping clients slow down, cross-check claims, and avoid misinformation traps (Dissen et al., 2021; Mohamed et al., 2023). That aligns directly with the themes from Article 1.
What trainers should NOT do
You should not prescribe medically tailored meals, treat disease, or replace clinical providers (Landry, 2015). You should not interpret lab values, recommend medical nutrition therapy, or advise dietary changes for diagnosed conditions without referral (Landry, 2015).
A simple rule: If the intervention requires diagnosis or clinical nutrition therapy, it belongs with an RD/MD team.
Practical Coaching Tool: Four Questions to Ground “Food as Medicine” Conversations
When a client brings food-as-medicine content into your session, run it through four questions.
1) Is this a dietary pattern or a branded protocol?
- Evidence-based patterns tend to have broader support than tightly marketed “systems” (Landry, 2015).
2) Is this integrated into healthcare—or built for clicks?
- Digital delivery isn’t bad, but credibility and accountability matter (Mohamed et al., 2023).
3) Is it accessible and sustainable?
- Programs that ignore access barriers often fail the people who need them most (Quinn et al., 2017).
4) Does the client understand it well enough to apply it?
- Nutrition literacy and eHealth literacy determine whether guidance becomes behavior (Landry, 2015; Quinn et al., 2017).
This keeps the conversation grounded without turning you into the nutrition police.
Key Takeaways
Food-as-medicine approaches are supported by a growing body of peer-reviewed literature, particularly on evidence-based dietary patterns and structured food interventions (Landry, 2015).
At the same time, the evidence base remains heterogeneous, especially for programmatic interventions, and long-term scalability remains a challenge (Lee et al., 2014).
Nutrition literacy and eHealth literacy are not “nice to have.” They are determinants of access, engagement, and effectiveness—especially as programs shift toward digital delivery (Dominick et al., 2009; Dissen et al., 2021; Kim et al., 2023; Mohamed et al., 2023; Quinn et al., 2017).
For trainers, the opportunity is not to practice medicine. It’s to coach the behaviors that make evidence-based nutrition approaches usable, sustainable, and aligned with performance.
References
Cho, H., Han, K., & Park, B. (2018). Associations of eHealth literacy with health‐promoting behaviours among hospital nurses: A descriptive cross‐sectional study. Journal of Advanced Nursing, 74(7), 1618–1627. https://doi.org/10.1111/jan.13575
Dissen, A., Qadiri, Q., & Middleton, C. (2021). I read it online: Understanding how undergraduate students assess the accuracy of online sources of health information. American Journal of Lifestyle Medicine, 16(5), 641–654. https://doi.org/10.1177/1559827621990574
Dominick, G., Friedman, D., & Hoffman‐Goetz, L. (2009). Do we need to understand the technology to get to the science? A systematic review of the concept of computer literacy in preventive health programs. Health Education Journal, 68(4), 296–313. https://doi.org/10.1177/0017896909349289
Kim, J., Livingston, M., Jin, B., Watts, M., & Hwang, J. (2023). Fundamentals of digital health literacy: A scoping review of identifying core competencies to use in practice. Adult Learning, 35(3), 131–142. https://doi.org/10.1177/10451595231178298
Landry, K. (2015). Using eHealth to improve health literacy among the patient population. Creative Nursing, 21(1), 53–57. https://doi.org/10.1891/1078-4535.21.1.53
Lee, K., Hoti, K., Hughes, J., & Emmerton, L. (2014). Interventions to assist health consumers to find reliable online health information: A comprehensive review. PLOS ONE, 9(4), e94186. https://doi.org/10.1371/journal.pone.0094186
Manganello, J. (2007). Health literacy and adolescents: A framework and agenda for future research. Health Education Research, 23(5), 840–847. https://doi.org/10.1093/her/cym069
Mohamed, H., Salsberg, J., & Kelly, D. (2023). An integrative review protocol on interventions to improve users’ ability to identify trustworthy online health information. PLOS ONE, 18(4), e0284028. https://doi.org/10.1371/journal.pone.0284028
Quinn, S., Bond, R., & Nugent, C. (2017). Quantifying health literacy and eHealth literacy using existing instruments and browser-based software for tracking online health information seeking behavior. Computers in Human Behavior, 69, 256–267. https://doi.org/10.1016/j.chb.2016.12.032
