Where does the Evidence for Personalized Nutrition Stand? Nlumn Nsights 2024 Vol 2. Issue 5.

Thought Leadership


Team Nlumn

In our recent newsletter, we explored the current evidence supporting more personalized approaches to nutrition. Read on as we continue our discussion, looking toward the future of personalized nutrition and opportunities for innovation.

What Does the Future Hold For Personalized Nutrition?

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.

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.

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.  

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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