How scientists transformed the search with one discovery

if you eat A lot during the holiday season, you probably think of a healthy diet plan for 2022. But as anyone who’s been on a diet knows, there are endless options. Right now, we’re in the midst of a revolutionary era of understanding the human body, and so the question arises: Can new science tell us which diet plan is best for weight loss?

Many diets originate in a system of classifying foods according to their effect on blood sugar level. This method of describing food came from research conducted by David Jenkins at the University of Toronto in 1981.

They gave each food a score according to how much it raised blood sugar levels, with sugar as a standard, a score of 100. Honey scored 87, sweet corn scored 59, tomato soup scored 38, and so on.

Today, everything conceivable to eat this way has been analyzed and countless diet plans are built on this method of food categorization. In general, those seeking to lose weight are advised to avoid foods that cause high blood sugar levels.

But we’ve all come across someone who seems to be at a healthy weight no matter how much cake, chocolate, or wine they consume. And this – the differences between us – is where vital progress is being made now, leading us to a new understanding of what the best diet plan really is.

In 2015, Eran Elinav and Iran Segal of the Weizmann Institute of Science in Israel conducted a fascinating study. They recruited 800 participants, and instead of taking glucose measurements multiple times over a few hours, as was done in 1981, each participant’s blood glucose level was measured every five minutes over seven days, using a small sensor developed for people with diabetes .

In addition, each participant answered a detailed medical questionnaire, underwent a variety of physical assessments, such as height and hip circumference measurements, and their stool was analyzed for the types of bacteria it contained.

It turns out that glucose levels rose exactly as per previous research. But crucially, this was only the case on average. The difference from person to person was enormous.

For any food, some people’s glucose levels may rise dramatically, while others seem to barely react at all. This cannot be interpreted as a random fluctuation because the same person responded similarly every time they ate that particular food. For a middle-aged woman, for example, her blood glucose level rose the more she ate a tomato. Another person rose especially strongly after eating a banana.

One woman’s blood glucose was rising every time she ate a tomato.stock struggle

Segal’s wife, Keren, was particularly surprised. As a dietitian, she has been trained to instruct countless people on what they should and should not eat.

Now her husband has evidence that her nutritional advice may not always have been helpful. She was shocked by the fact that some people’s sugar levels after eating rose in response to rice more than ice cream.

It dawned on her that she might have directed some of her patients to a type of food that, though useful on average, was wrong for them personally.

A machine learning algorithm (a type of artificial intelligence) was used to figure out what factors should be considered to generate the most accurate predictions of a person’s post-meal glucose response. One factor has emerged as the most significant contributor to date: the types of bacteria present in the stool, which reflect the gut microbiome.

Finding the right diet: Too complicated

So what does this mean? This means that there is no best diet plan – it is all subjective. What constitutes a healthy diet plan depends on who eats it: their genes, their lifestyle, their microbiome, perhaps even the state of their immune system, their history of infections, and more. Each is wonderfully complex on their own terms, and how they interact is more than that.

Our understanding of the details – what makes a diet work or not for an individual – is still in its infancy. But soon, with the help of computer algorithms and big data analysis, we are certainly due to a revolution in the science of diet and nutrition.

If it becomes clear that personalized nutrition will have a significant impact on human health, the question will arise: Should analyzing a person’s blood and microbiome to produce a personalized diet plan become part of routine preventive health care, paid for by taxes?

Indeed, where do we draw the line between a food product, a food 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 life: what we eat and drink.

This article was originally published Conversation by Daniel M Davis at the University of Manchester. Read the original article here.

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