Big Data for Personalized Diets

A recent commentary in the NY Times discusses the future of personalized diets.  Along the way, the commentary notes how little we know about the best diet and how difficult nutrition research is to complete.

The A.I. Diet by Eric Topol who is the author of the forthcoming “Deep Medicine,” from which this essay is adapted

An excerpt:

It turns out, despite decades of diet fads and government-issued food pyramids, we know surprisingly little about the science of nutrition. It is very hard to do high-quality randomized trials: They require people to adhere to a diet for years before there can be any assessment of significant health outcomes…

Meanwhile, the field has been undermined by the food industry, which tries to exert influence over the research it funds.

Now the central flaw in the whole premise is becoming clear: the idea that there is one optimal diet for all people…

Only recently, with the ability to analyze large data sets using artificial intelligence, have we learned how simplistic and naïve the assumption of a universal diet is. It is both biologically and physiologically implausible: It contradicts the remarkable heterogeneity of human metabolism, microbiome and environment, to name just a few of the dimensions that make each of us unique. A good diet, it turns out, has to be individualized.

My take: Dr. Topol makes some important observations and he is right that there is not a simple diet solution for everyone.  Nevertheless, in the near future, personalized medicine is not coming to our dinner tables and we have to rely on what we know right now –don’t eat too much sugar, do eat more fruits and vegetables, and don’t eat too much.

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