Whether you live or eat, you may know what is happening deeply inside your ghut.
At least that is what scientists have received from the Mayo Clinic from a new research on the effectiveness of the use of data of human gib myopyroid to verify the healthiest food hats for individuals.
A study published on 8 February in the Journal of the American Medical Association reinforces an area that is still emerging in diet science which indicates how best to manage nutrient health or to build a personal diet. For a long time, people are trying to build diet based on the nutritional compositions of the foods they eat. Think about the US government food pyramid, which recommended daily checks, meat, vegetables, fruits and grain to maintain good health. But as science and nutrition technology has emerged, we have a greater insight into what's happening at a chemical level inside our bodies. As a result, some scientists, diet and food companies are starting to focus away from the general properties of individual foods, and how our individual bodies process them.
The new research of Mayo Clinic gives evidence of the viability of this approach in terms of managing blood sugar levels. The researchers took a model to predict how different foods go to human blood sugar levels, and set out to test that model. They found that human viruses, age, level of physical exercise, and other factors, were analyzed, and could accurately predict how the body reacts to food; more than that if they tried to do so by counting calories or carbs.
"As clinics, the same patients did not find the same foods respond in the same way – it does not seem that every weight diet works for everyone the same," said Heidi Nelson, one of the authors the study, in a statement.
As part of their research, the scientists followed 327 healthy people for six days. Everyone put samples into logs so that the scientists could discover the unique microbial materials of their engines. They also kept diaries on what they ate every day, caring for them to observe the exercise and the rest they received. They were also outfitted to monitor blood-glucose that trace their glycemic responses to food. When these data collected these data, they tested the results against the model they were designed for predicting glycemic reactions on foods.
According to the study, the model was able to make changes predetermined by 62% of the blood sugar time. Previously, when only carbs or calorie intake were based on predicting, they were able to accurately report 40% and 32% of the time.
"With our personalized model, people have to bring up all foods within a particular category," said researcher Purna Kashyap, in a statement. "It allows them to choose specific foods within certain categories that contribute well to their microbiology."
One participant in the study described how he learned he did not need to give up all carbohydrates to cut their blood sugar levels. The data collected by the model showed that they needed to eat less grain and rice grain while eating more eggs and cottage cheese.
"And I'm staying away from breakfast cereals and sugary yogurt," he wrote on Mayo Clinic released. "I have a little weight loss and I feel more energetic."
The work supports the results of a similar study from 2015 by the Weizmann Institute of Science in Israel. As a body develops evidence in the field of personalized nutrition, they are likely to be interrupted into new products made by food companies. Nestlé, the largest food company in the world, is testing a personal diet in Japan, as part of the long-term vision of the company that kills the line between food and pharma.