Point of consumption nutritional awareness
“Is better understanding the quality, safety and impact of food at consumption”
Unless you produce the food you eat, you likely poorly understand it (1).
Increasing food production scale, diversity and human biological diversity, are leading the food system to be disproportionally disordered relative to the purpose it should serve (2). Pronounced in marginalized populations and key food groups (UPCs).
This does not mean the food you are eating is unsafe, modern food systems are well evolved and long standing.
With emerging technologies though, where can these systems go, what can they be?
One day, there will be no debate about the impact of the food you eat, on your body, when you consume it.
Given; genetics, gut microbiome, production method, geolocation, packaging, seasonality, additives … these dimensions go on.
Luckily AI is perfect for solving multi-dimensional problems, with low latency inference… as if at point of consumption.
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Existing mechanisms driving nutritional awareness, are unfortunately broken.
Because;
The average person is not educated enough on nutrition (3)(4)
Nutritional choices are heavily influenced by social media, misinformation is frequent (5) (6)
The only consumer point of contact raising nutritional awareness is the food label (7)(8)
In a world where;
Some food products drive addictive behavior (9)(10)
Attention is saturated (11)(12)
Humans are genetically diverse
Context and awareness matters, quite a lot. Particularly over time.
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Take three random people;
Persons A, B and C all buy the same loaf of bread.
Person A is well suited to metabolizing bread.
Person B is not metabolically suited to eating bread, they do not know it.
Person C is not metabolically suited to eating bread, they know it.
If Person A, B and C eat this same loaf of bread, the length of time it’s consumed determines the metabolic impact (13)(14).
Over time person A thrives, while B and C, are incrementally impacted. We all know people in groups 1, 2 and 3.
“Point of consumption nutritional awareness” informs people on food impact, at consumption, given dimension x, y, z affecting person p at time t.
It’s helping marginalized groups and those unaware understand nutritional impact, such that the value (nodal) of information (i) at time (t) is proportional to the time behavior (b) occurs.
It is about improving food quality, by stopping consumers making poor nutritional choices.
株式会社TiviTi is building technologies to solve this problem. Contact us to find out how!
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Readings
(1) University of Minnesota College of Food, Agricultural and Natural Resource Sciences (CFANS). (2022, March 3). Bridging the food trust gap. University of Minnesota. https://cfans.umn.edu/news/bridging-food-trust-gap University of Minnesota+1
(2) Organisation for Economic Co-operation and Development (OECD). (2021, July). Overcoming Evidence Gaps on Food Systems (OECD Food, Agriculture and Fisheries Paper No. 163). OECD. https://www.oecd.org/content/dam/oecd/en/publications/reports/2021/07/overcoming-evidence-gaps-on-food-systems_c80c306e/44ba7574-en.pdf OECD+1
(3) Persoskie, A., Hennessy, E., & Nelson, W. L. (2017, September 28). US Consumers’ Understanding of Nutrition Labels in 2013: The Importance of Health Literacy. Preventing Chronic Disease (CDC). https://www.cdc.gov/pcd/issues/2017/17_0066.htm Centers for Disease Control and Prevention+1
(4) Kraemer, M. V. S., Fernandes, A. C., Chaddad, M. C. C., Uggioni, P. L., Bernardo, G. L., & Proença, R. P. C. (2023, October 25). Is the List of Ingredients a Source of Nutrition and Health Information in Food Labeling? A Scoping Review. Nutrients (MDPI). https://www.mdpi.com/2072-6643/15/21/4513 Nutrients+1
(5) Cheikh Ismail, L., Osaili, T. M., Naja, F., et al. (2024, August 15). The association of social media with dietary behaviors among adults in the United Arab Emirates. Heliyon. https://www.sciencedirect.com/science/article/pii/S2405844024116052 Elsevier+1
(6) Denniss, E., et al. (2023, July). Quality and accuracy of online nutrition-related information: a systematic review of content analysis studies. Public Health Nutrition, 26(7), 1345–1357. Cambridge University Press / The Nutrition Society. https://www.cambridge.org/core/journals/public-health-nutrition/article/quality-and-accuracy-of-online-nutritionrelated-information-a-systematic-review-of-content-analysis-studies/4E28F7A056AA8CB4A19F9E5DF0B095C2 Cambridge University Press+1
(7) U.S. Food and Drug Administration. (2024, March 5). 2019 Food Safety and Nutrition Survey Report. U.S. Food and Drug Administration. https://www.fda.gov/food/social-and-behavioral-science-research-food/2019-food-safety-and-nutrition-survey-report
(8) International Food Information Council. (2024, May 24). Front-Of-Package (FOP) Nutrition Labeling: Front & Center Food Information To Encourage Healthy Choices. International Food Information Council (IFIC). https://ific.org/wp-content/uploads/2025/07/IFIC-FOP-Nutrition-Labeling-Consumer-Study-Report.pdf
(9) Pereira, T., Mocellin, M. C., Curioni, C., et al. (2024, December 20). Association between ultraprocessed foods consumption, eating disorders, food addiction and body image: a systematic review. BMJ Open, 14(12), e091223. https://doi.org/10.1136/bmjopen-2024-091223 BMJ Group+1
(10) LaFata, E. M., Allison, K. C., Audrain-McGovern, J., & Forman, E. M. (2024, May 18). Ultra-Processed Food Addiction: A Research Update. Current Obesity Reports, 13(2), 214–223. https://doi.org/10.1007/s13679-024-00569-w Springer Nature+1
(11) Castelo, N., Kushlev, K., Ward, A. F., Esterman, M., & Reiner, P. B. (2025, February). Blocking mobile internet on smartphones improves sustained attention, mental health, and subjective well-being. PNAS Nexus (Oxford Academic / Oxford University Press). https://academic.oup.com/pnasnexus/article/4/2/pgaf017/8016017
(12) Turner, G., Ferguson, A. M., Katiyar, T., Palminteri, S., & Orben, A. (2025, May 15). Old Strategies, New Environments: Reinforcement Learning on Social Media. Biological Psychiatry (Elsevier / Society of Biological Psychiatry). https://www.sciencedirect.com/science/article/pii/S0006322324018201
(13) Li, B., Yan, J., Jiang, S., et al. (2023, March 15). Consumption of sugar sweetened beverages, artificially sweetened beverages and fruit juices and risk of type 2 diabetes, hypertension, cardiovascular disease, and mortality: A meta-analysis. Frontiers in Nutrition. https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2023.1019534/full Frontiers+1
(14) Lane, M. M., Gamage, E., Du, S., et al. (2024, February 28). Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses. The BMJ. https://www.bmj.com/content/384/bmj-2023-077310 BMJ+1
