What’s the best diet? The best diet will someday be individualized. Artificial intelligence may be leading the way.
Is There a Best Diet?
Every year we see rankings of the best and healthiest diets. While we understand the broad parameters of the components of a healthy diet—an emphasis on plant based foods and eating from all healthy food groups—we are still quite far from understanding how to make individualized food recommendations. What I’ve learned from coaching hundreds of clients over the years is that bodies are not all the same. The diet plan that works for one person does not work for another. We know from studies that bodies metabolize the same foods quite differently.
What We Know About the Best Diet
Here’s the state of the reputable research on recommended diets. It’s still quite preliminary.
- 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.
- The largest ever — which found that the “Mediterranean diet” lowered the risk for heart attacks and strokes — had to be retracted and republished with softened conclusions. But, I still think this is the healthiest lifestyle diet.
- Most studies are observational, relying on food diaries or the shaky memories of participants.
- There are many such studies, with over a hundred thousand people assessed for carbohydrate consumption, or fiber, salt or artificial sweeteners, and the best we can say is that there might be an association, not anything about cause and effect.
- Perhaps not surprisingly, these studies have serially contradicted one another.
- Meanwhile, the field has been undermined by the food industry, which tries to exert influence over the research it funds.
The Central Flaw in the Whole Premise Is Becoming Clear
The flaw is 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 best 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.
We’re still a long way from knowing what this means in practice, however. A number of companies have been marketing “nutrigenomics,” or the idea that a DNA test can provide guidance for what foods you should eat. For a fee, they’ll sample your saliva and provide a rudimentary panel of some of the letters of your genome, but they don’t have the data to back their theory up.
Coming up with a truly personalized diet would require crunching billions of pieces of data about each person. In addition to analyzing the 40 trillion bacteria from about 1,000 species that reside in our guts, it would need to take into account all of the aspects of that person’s health, including lifestyle, family history, medical conditions, immune system, anatomy, physiology, medications and environment. This would require developing an artificial intelligence more sophisticated than anything yet on the market.
Perhaps Artificial Intelligence Will Help Identify the Best Diet
The first major development in this field occurred a few years ago when Eran Segal, Eran Elinav and their colleagues at the Weizmann Institute of Science in Israel published in the journal Cell a landmark paper titled “Personalized Nutrition by Prediction of Glycemic Responses.”
Spikes in blood-glucose levels in response to eating are thought to be an indicator of diabetes risk, although we don’t know yet if avoiding them changes that risk. These spikes are only one signature for our individualized response to food. But they represent the first objective proof that we do indeed respond quite differently to eating the same foods in the same amounts.
- The study included 800 people without diabetes.
- The data for each person included the time of each meal, food and beverage amount and content, physical activity, height, weight and sleep.
- The participants had their blood and gut microbiome inhabitants assessed and their blood glucose monitored for a week.
- They ate more than 5,000 standardized meals provided by the researchers, which contained popular items like chocolate and ice cream, as well as nearly 47,000 meals that consisted of their usual food intake.
- In total, there were more than 1.5 million glucose measurements made.
- Using machine learning, a subtype of artificial intelligence, the billions of data points were analyzed to see what drove the glucose response to specific foods for each individual. In that way, an algorithm was built without the biases of the scientists.
Results of Artificial Intelligence Trial
Here are the results of using AI to identify the best individualized diet.
- More than a hundred factors were found to be involved in glycemic response, but notably food wasn’t the key determinant.
- Instead it was the gut bacteria.
- Here were two simultaneous firsts in nutritional science.
- One, the discovery that our gut microbiome plays such a big role in our unique response to food intake.
- And that this discovery was made possible by artificial intelligence (A.I.)
These studies and others have confirmed not only our microbiome’s importance but also that a substantial proportion of healthy people have high glucose levels after eating.
Current State of Research on Individualized Diets
This study is an interesting first step on the path to a personalized diet. There is now a commercial version of this test, based on the research of Dr. Segal and Dr. Elinav, though it is much more limited: It only analyzes a gut microbiome sample, without monitoring glucose or what you eat.
There are other efforts underway in the field as well. In some continuing nutrition studies, smartphone photos of participants’ plates of food are being processed by deep learning, another subtype of A.I., to accurately determine what they are eating. This avoids the hassle of manually logging in the data and the use of unreliable food diaries (as long as participants remember to take the picture).
What we really need to do is pull in multiple types of data — activity, sleep, level of stress, medications, genome, microbiome and glucose — from multiple devices, like skin patches and smartwatches. With advanced algorithms, this is eminently doable. In the next few years, you could have a virtual health coach that is deep learning about your relevant health metrics and providing you with customized dietary recommendations.
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