Jun 22, 2018 | Updated: 09:54 AM EDT

The ‘DNA’ Diet: The Perfect Way To Lose Weight

Jan 11, 2016 12:40 AM EST


Losing weight has always been one of the most common problems of plus-sized and heavy eaters around the world. But recently, a new form of diet emerged and is believed to be the most effective one yet.

The 'DNA' diet was formed by various researchers all over the country. It is a weight management plan that centers on the study of genetics and its integration on obesity and weight of people. The team of researchers stated that even though genetics has long been used as the basis for body composition, additional factors such as family members can also contribute to someone's weight gain or loss.

Molly Bray, the study leader and a professor of nutritional science at the University of Texas, believes that within the next five years or so, people will finally be able to use a combination of genetic, behavioral and other important data to develop the perfect weight management plan specifically for themselves.

In order to fully understand how the diet works and affects the body, the genome's overriding process in the body must first be understood. A genome is a complete set of DNA of an organism. It also contains all the components and features that are important in maintaining the particular organism it belongs to.

Bray also predicted that in the future, it will take a saliva sample in order for someone to carry out gene sequencing. This particular process will then be integrated into a set of computer algorithm where it will be used to get information and give patients specific recommendations in order for them to reach their diet goals. She further added that as a nutritionist, she was already able to help a lot of people lose weight quickly. But in the long run, the chances of those people getting fat again will solely be based on the person's attitude and on how they treat their body. In a statement published in the journal called 'obesity,' the genetic-based 'DNA' diet plan will be available for use by the year 2020.

©2017 ScienceTimes.com All rights reserved. Do not reproduce without permission. The window to the world of science times.
Real Time Analytics