DIET&FITNESS Published December24, 2015 By Milafel Hope Dacanay

Genome: The Ultimate Secret to Weight Loss

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Slimming Exercises
(Photo : Douglas Miller | Hulton Archive)

How do you intend to lose weight? According to a new report, it might not take long before we start factoring in genes.

In a paper published in Obesity by the researchers of University of Texas, genome sequencing may be the future of weight loss programs, as it can significantly increase the likelihood of positive outcomes.

According to the head of the working group Molly Bray, the university's geneticist, within the next five years, genome sequencing will be used to individualize weight management programs. The data will then be combined with other information that can be obtained by automated sensors like smart watches to understand further weight-related factors such as environment and stress.

In the present, many people still succeed losing weight, but the achievement is not for the long term as many regain their previous weight or even more.

Previously, University of Pennsylvania clinical director Gary Foster, PhD, shared that more than 60% of those who dieted went back to their old weight within the next three years. The statistics could become worse among those who experienced rapid weight loss as only 5% of them might be able to maintain their weight.

A huge part of the struggle in maintaining the success is the weak understanding of the role of other factors to weight loss, including biological.

Many studies have already shown that certain genes can increase the predisposition of an individual to obesity, a metabolic condition wherein the body stores a lot of fat. There's a gene that can trick the body into storing fat rather than burning it.

In the future, people who need to undergo weight management may have to provide saliva samples for genetic sequencing, and the data will be complemented by other digital information. This may not be far-fetched, the researchers believe, as the costs of the procedure have become cheaper over the years. Nevertheless, the challenge is a tool that can be used for overall data analysis.

 

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