Genes affecting levels of physical activity, according to survey – Vida Actual – latest news updates from Uruguay and the World



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The research, developed by the Oxford University's Great Data Institute, includes, for example, the time we go to; sit, sleep or not; move with our gene, one of the most complete jobs in this area.

The specialists made an "automatic learning tool" program to make a difference in non-active and active life (and several intermediate levels) to carry 200 volunteers and a two-day handbag , monitors the activity every 20 seconds.

Then, they compared that information with 91,105 registered people in the Biobank UK database that had the same type of beekeeper for a week in previous times.

"It's not and how we move to hang on a gene but we will recognize the space they play to know our causes and the effects of their activity develop corporate, "said director of her & This project, Aiden Doherty, in a statement.

By simply studying large amounts of data, he said, "able to determine" complex genetic foundations "on some of the most fundamental actions," such as moving, relaxing or sleeping. "

WHO recommends that adults have at least 150 minutes of weekly weekly physical activity. Picture: Pixabay
Picture: Pixabay

As well as identifying 14 related genetic sections, seven of them new, scientists have seen for their & The first time, with great data, is that "the increase in physical activity can reduce blood pressure independently".

In addition, the genetic study revealed that there was "an increase" between neurodegenerative diseases, mental health and brain structure, which demonstrates the importance of the strange system in physical activity and sleep.

Physical non-activity, according to experts, is a danger to public health in the world, with a wide range of diseases related to unmarried lifestyles, such as obesity, diabetes or cardiovascular problems.

In addition, there are changes in sleep related to heart and metabolic diseases and mental disorders.

Experts from the study stressed that the use of the "automatic learning tool" to make a significant amount of health data rapidly progresses and that is; Situation of the type of studies that can be developed.

"We have designed toolkit tools to teach tools to analyze complex tasks, such as activity," explained Karl Smith-Byrne, one of the partners in this work.

"They could help us, for example, to verify whether an activity is a cause of obesity or a result of obesity," said Michael Holmes, from Oxford University's British Heart Foundation.

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