if you ate too much during the holiday season, you may be thinking about a healthy diet diet plan by 2022. But as anyone who has ever dieted knows, there are countless options out there. Right now, we’re in the middle of a revolutionary time to understand the human body, so the question arises: can new science tell us which diet plan is best for weight loss?
Many diets originate from a system of rating foods based on the effect they have on our blood sugar levels. This way of characterizing food comes from research led by David Jenkins at the University of Toronto in 1981.
Each type of food was given a score according to how much it raised blood sugar levels, with sugar as the benchmark, scoring out of 100. Honey scored 87, sweet corn scored 59, tomato 38, and so on.
Today, every conceivable edible thing has been analyzed in this way and countless diet plans have been based on this way of classifying foods. In general, those looking to lose weight are advised to avoid foods that cause blood sugar levels to rise.
But we’ve all come across someone who seems to maintain a healthy weight no matter how much cake, chocolate, or wine they consume. And here, the differences between us, is where vital breakthroughs are now being made, leading us to a new understanding of what the best diet plan really is.
In 2015, Eran Elinav and Eran Segal at the Weizmann Institute of Science in Israel conducted a fascinating study. They recruited 800 participants, and instead of measuring glucose multiple times over the course of a few hours, as was done in 1981, they measured each participant’s blood sugar level every five minutes for seven days, using a small sensor developed for people with diabetes.
In addition to this, each participant answered a detailed medical questionnaire, was subjected to a variety of physical assessments, such as measurements of their height and hip circumference, and had their stool tested for the types of bacteria they contain.
It turned out that glucose levels increased exactly in accordance with previous research. But crucially, this was only the case on average. The variation from person to person was enormous.
For any given food, some people’s glucose levels increased dramatically, while others barely seemed to react. This could not be explained as a random fluctuation because the same person responded in a similar way every time they ate that particular food. For a middle-aged woman, for example, her blood glucose level spiked every time she ate tomatoes. Another person shot up especially hard after eating bananas.
Segal’s wife, Keren, was especially stunned. As a dietitian, she had been trained to guide countless people on what they should and should not eat.
Now her husband had evidence that his dietary advice might not always have been helpful. The fact that some people’s post-meal sugar levels rose more in response to rice than ice cream was shocking to her.
It occurred to him that he might even have directed some of his patients to a type of food that, while beneficial on average, was not suitable for them personally.
A machine learning algorithm (a type of artificial intelligence) was used to figure out what factors needed to be taken into account to generate the most accurate forecast of a person’s post-meal glucose response. One factor stood out as the biggest contributor by far: the types of bacteria found in your stool, reflecting your gut microbiome.
Finding the Right Diet: Exquisitely Complex
So what does this mean? It means that there is no single best diet plan – it’s all personal. What constitutes a healthy diet plan depends on who is eating it: their genetics, their lifestyle, their microbiome, perhaps even the state of their immune system, their history of infections, and more. Each of which is exquisitely complex in its terms, and how they interact further.
Our understanding of the details, what makes a diet work or not work for an individual, is still in its infancy. But soon, with the help of computer algorithms and big data analytics, we are sure to be in for a revolution in the science of diet and nutrition.
If it becomes clear that personalized nutrition would have a major impact on human health, the question will be raised: should an analysis of a person’s blood and microbiome to produce a personalized diet plan become part of preventive health care? routine, paid for with taxes? ?
In fact, where would we draw the line between a nutritional product, a dietary plan, and a drug? As any science matures, new policies must be developed. This will be especially important when it comes to such a vital part of our daily lives: what eat and drink.
This article was originally published on The conversation for Daniel Davis at the University of Manchester. Read the original article here.
