Personalized Nutrition Better Than Popular 'Healthy Diets'
There is no "healthy for all" food type. Researchers from the Weizmann Institute of Science in Israel explain that responses to food can differ from person to person. Hence, what is healthy for one is not necessarily so for everyone.
So far, the glycemic index (GI), is a standard that has placed food types at different blood glucose levels, in order to make up healthy diets for patients. However, those who showed diverse blood glucose responses to food showed gaps in the use of GI grading system.
The Personalized Nutrition Project showed the researchers focusing on the effect of foods in the blood glucose levels of 800 participants for a week. They could analyse the effects for 46,898 meals, finding that the participants showed different responses to the same food, although the individual responses were the same everyday.
"Most dietary recommendations that one can think of are based on one of these grading systems; however, what people didn't highlight, or maybe they didn't fully appreciate, is that there are profound differences between individuals - in some cases, individuals have opposite response to one another, and this is really a big hole in the literature," study author Eran Segal from Weizmann's Department of Computer Science and Applied Math said in a press release.
For instance, a woman who suffered from pre-diabetes and obesity ate tomatoes as part of a "healthy diet," but then found that they led to a rise in her blood glucose. The different responses to food was shown to be due to the "uniqueness" of her gut bacteria.
"In contrast to our current practices, tailoring diets to the individual may allow us to utilize nutrition as means of controlling elevated blood sugar levels and its associated medical conditions," Eran Elinav, study coauthor from Weizmann's Department of Immunology, said in the press release.
To customise the food to different persons, the researchers developed an algorithm predicting a person's blood glucose response to specific food types, factoring each person's lifestyle, gut bacteria and medical background. They then tested the accuracy of the algorithm in a subsequent study that involved 100 volunteers. The algorithm was discovered to accurately predict the blood glucose responses to various food types.
"After seeing this data, I think about the possibility that maybe we're really conceptually wrong in our thinking about the obesity and diabetes epidemic," Segal said. "The intuition of people is that we know how to treat these conditions, and it's just that people are not listening and are eating out of control - but maybe people are actually compliant but in many cases we were giving them wrong advice."
The study was published in the Nov. 19 issue of Cell.