As more consumers become interested in personalized nutrition, providing an evidence-base for your products can establish trust and differentiate your personalized health business.

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Recently, our CEO and Founder, Josh Anthony, spoke at the F&A Next Conference on personalized nutrition’s role in supporting consumers in making better choices. He noted that Victor Friedberg (Founder and Managing Partner at New Epoch Capital; Founder and Chairman of FoodShot Global) underscored the need for efficacy to drive industry growth. Investors seek proof that personalized nutrition products deliver meaningful health and functional benefits. Companies need to go beyond secondary sources of data to support their products.  

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In this newsletter, we will explore evidence supporting more personalized approaches to nutrition and health, as well as opportunities for innovation.  

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The Current State Landscape

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Personalized nutrition has shown potential to help prevent or manage chronic conditions such as diabetes, cardiovascular disease, and obesity.  

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Research indicates personalized dietary interventions can lead to better outcomes compared to generalized dietary guidelines. For instance, the PREDICT study demonstrated different individual post-meal triglyceride and glucose levels that were informative for metabolic dysfunction and cardiovascular disease risk assessment. This suggests that personalized nutrition can play a significant role in disease prevention and management.  

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In diabetes management, personalized nutrition approaches, considering individual genetic makeup and metabolic responses, have led to improved glycemic control. Similarly, tailoring diets to reduce specific biomarkers, such as total cholesterol, triglycerides, LDL cholesterol, and blood pressure, has shown promise in cardiovascular diseases. Personalized nutrition has the potential to help in body composition management by addressing individual metabolic differences and behavior, leading to more effective and sustainable weight loss strategies.

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Part of the reason personalized approaches to chronic lifestyle diseases have been effective is that validated and predictive biomarkers are used to support recommendations.  

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Clinical biomarkers such as blood glucose, cholesterol, blood pressure, and anthropometrics (e.g., body weight, waist and hip circumferences, lean body mass, and body fat) have been central to nutritional studies. These biomarkers provide evidence-based, defined, and accepted ranges that link eating patterns to health outcomes and, ultimately, behavior change. Using these in a systems-based approach can help support personalized recommendations and health outcomes.  

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Technological advancements have refined the measurement of these markers, offering more precise data. For example, continuous glucose monitoring (CGM) devices allow real-time tracking of blood glucose levels in response to dietary intake. These tools can help tailor dietary recommendations to individual metabolic responses, enhancing the effectiveness of personalized nutrition plans. While CGMs have become popular ways of supporting recommendations in individuals without diabetes, more research is needed to validate the effectiveness of this approach.  

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True personalization is not just an individual’s biology; it requires understanding their lifestyle behaviors and supporting positive behavior changes.  

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Although limited, behavior change techniques have been successfully employed in personalized nutrition programs. This behavior change model was exemplified in the highly successful Diabetes Prevention Program, administered to over 1,000 participants and resulted in a 58% decrease in the incidence of type 2 diabetes. Behavior change was guided by trained lifestyle coaches who frequently contacted participants and provided personalized behavior change coaching sessions. A 10-week study of over 100 personalized nutrition program participants that included behavior change coaching by registered dietitian nutritionists reported improved lifestyle habits. A recent study of over 2000 participants in a personalized nutrition program employed a virtual coach to support behavior change. It showed improved healthy eating habits, weight loss, and glycemic control after two months. Sustainable behavior change is the key to user success and engagement in personalized nutrition programs.

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What Does the Future Hold for Personalized Nutrition?

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‍Our research study of 3,000 U.S. consumers interested in and/or participating in personalized nutrition plans suggests that consumers are looking for benefits outside chronic lifestyle disease prevention. The results from our study show the top benefits consumers seek include sleep, energy, feeling generally well/healthy, quality of life, and emotional health. Yet, 38% are unsure what to do to be healthy, which was reported more by younger consumers. Consistently, the National Sleep Foundation’s 2024 Sleep in America® Poll found that 80% of teens (13-17 years of age) do not get enough sleep, and nearly 75% report their emotional well-being is negatively impacted when they sleep less than usual. This data underscores the importance and opportunity of developing and promoting products supporting these benefits.

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There is an opportunity to establish and evaluate new biomarkers of health, performance, and well-being, moving away from the absence of disease. Using challenge-based methodologies (e.g., meal or exercise challenges) combined with multi-omics (multiple biological measures) can help detect changes before disease onset. Combining that with large data sets of individuals will help define what optimal health may look like. The human gut microbiome and other biomes (oral and skin) change because of various environmental factors and hold promise to help support health by optimizing host-biome interactions.

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Personalizing information and behavioral inputs to align with individual goals is what will drive adherence to personalized nutrition interventions. This level of detail is challenging to achieve but essential for the full potential of personalized nutrition. Artificial intelligence and machine learning are emerging as promising tools to handle the vast amount of data required for true personalization. These technologies can integrate data from various sources to create highly individualized dietary recommendations. The role of AI will continue to grow to provide relevant, cost-effective, and just-in-time support by helping to predict biological needs in response to the environment. This will merge to deliver relevant advice to support desired behaviors and improved health outcomes.  

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In closing, the evidence to support the use of personalized nutrition programs in improving health outcomes and behavior change is building. Future innovation in personalized nutrition products should continue to focus on delivering meaningful and evidenced-based benefits. Opportunities exist around new benefit areas, establishing biomarkers of health, and incorporating AI in developing personalized nutrition products and services.

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