Friday April 3, 2020

Hour-long afternoon naps may increase risk of diabetes: Study

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London: While taking a short nap may be good for your health, extending it to an hour or more significantly increases risk of developing diabetes, says a new study. “Excessive daytime sleepiness and taking longer naps were associated with increased risk of Type-2 diabetes, with a short nap not increasing this risk,” the study said.

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www.express.co.uk

The research by Tomohide Yamada from University of Tokyo in Japan analysed studies published till November 2014 on the association between daytime sleepiness, nap, and diabetes. After examining over 600 hundred studies including 261,365 people from Asian and Western countries, the research found that excessive daytime sleepiness increased the risk of diabetes by 56 percent, while a longer daytime nap of 60 minutes or more increased the risk by 46 percent. In contrast, a shorter nap (60 mins or less per day) did not increase the risk of diabetes.

The analysis showed there was no effect of napping up to about 40 minutes per day, after which risk began to increase sharply. “Daytime napping might be a consequence of night-time sleep disturbance such as obstructive sleep aponea (OSA), the study noted. Several studies have demonstrated the beneficial effects of taking short naps less than 30 minutes in duration, which help to increase alertness and motor skills. “A short nap finishes before the onset of deep slow-wave sleep.

“Entering deep slow-wave sleep and then failing to complete the normal sleep cycle can result in a phenomenon known as sleep inertia, in which a person feels groggy, disoriented, and even sleepier than before napping” Dr Tomohide Yamada said.

“Although the mechanisms by which a short nap might decrease the risk of diabetes are still unclear, such duration-dependent differences in the effects of sleep might partly explain our findings,” Yamada noted. The findings were presented at the annual meeting of the European Association for the Study of Diabetes (EASD) in Stockholm, Sweden.

(IANS)

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Can AI Predict Diabetes Accurately? Find it Out Here

AI to predict future diabetes cases with 94% accuracy

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AI diabetes
Researchers have revealed that with the help of artificial intelligence (AI) their trained computer model predicted the future incidence of diabetes. Pixabay

Researchers have revealed that with the help of artificial intelligence (AI) their trained computer model predicted the future incidence of diabetes with an overall accuracy of 94.9 per cent.

Artificial intelligence (AI) is the development of computer systems able to perform tasks that normally require human intelligence. Diabetes is linked to increased risks of severe health problems, including heart disease and cancer. Preventing diabetes is essential to reduce the risk of illness and death.

“Currently, we do not have sufficient methods for predicting which generally healthy individuals will develop diabetes,” said study lead author Akihiro Nomura from Kanazawa University in Japan. “Using machine learning, it could be possible to precisely identify high-risk groups of future diabetes patients better than using existing risk scores,” Nomura added.

For the findings, published in the Journal of the Endocrine Society, the researchers investigated the use of a type of artificial intelligence called machine learning in diagnosing diabetes.

AI diabetes
Artificial intelligence (AI) is the development of computer systems able to perform tasks that normally require human intelligence. Pixabay

Machine learning is a type of AI that enables computers to learn without being explicitly programmed. The research team analysed 509,153 nationwide annual health checkup records from 139,225 participants from 2008 to 2018 in the city of Kanazawa in Japan.

Among them, 65,505 participants without diabetes were included. The data included physical exams, blood and urine tests and participant questionnaires.

Patients without diabetes at the beginning of the study who underwent more than two annual health checkups during this period were included.

New cases of diabetes were recorded during patients’ checkups, the researchers said.

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The researchers identified a total of 4,696 new diabetes patients (7.2 per cent) in the study period. Their computer model predicted the future incidence of diabetes with an overall accuracy of 94.9 per cent.

According to the authors, the next plan is to perform clinical trials to assess the effectiveness of using statins to treat groups of patients identified by the machine learning model as being at high risk of developing diabetes. (IANS)