Impulsive behaviour linked to sleep and screen time: Study

Washington D.C., Jan 12: Disruption in one night's sleep can lead to getting Alzheimer's disease, a recent study has stated.

The interruption in the sound sleep for a single night aggravates the level of tau protein in any young male's body, thus gives rise to the chances of developing the disease.

According to CNN, the report was published on Wednesday in neurology, the medical journal of the American Academy of Neurology.

"Our study focuses on the fact that even in young, healthy individuals, missing one night of sleep increases the level of tau in blood suggesting that over time, such sleep deprivation could possibly have detrimental effects," says study author Dr Jonathan Cedernaes, a neurologist at Uppsala University in Sweden.

As defined by the Alzheimer's Association, tau is the name of a protein that helps in stabilizing the internal structure of the brain's nerve cells. An abnormal build-up of tau protein in the body can end up in causing interior cells to fall apart and eventually developing Alzheimer's.

"When you get more of that deep sleep and you get the REM sleep in the normal amounts, that improves clearance of abnormal proteins which we think is good," said Mayo Clinic neurologist Dr Donn Dexter, not the study author but a fellow of the American Academy of Neurology.

Earlier studies have also shown that getting deprived of sleep can allow higher tau development and accumulation. Thus that poor sleep can hasten the development of cognitive issues.

Researchers caution that the study is small and inconclusive, and acknowledged they were not able to determine what the increased levels might mean.

"This study raises more questions than answers," agreed Dexter on a concluding note, sharing, "What this is telling us is that we have to dig more deeply. Despite something we do for a third of our lives, we know so little about sleep and we're learning every day, particularly when it comes to sleep and dementia."

Birmingham, Feb 7: According to a new study, social media users are more likely to eat healthy or junk food after getting influenced by their peer group.

The research published in the scientific journal 'Appetite' found that study participants ate an extra fifth of a portion of fruit and vegetables themselves for every portion they thought their social media peers ate. So, if they believed their friends got their 'five a day' of fruit and veg, they were likely to eat an extra portion themselves.

On the other hand, Facebook users were found to consume an extra portion of unhealthy snack foods and sugary drinks for every three portions they believed their online social circles did.
The findings suggested that people eat around a third more junk food if they think their friends also indulge in the same.

The Aston University researchers said the findings provide the first evidence to suggest our online social circles could be implicitly influencing our eating habits, with important implications for using 'nudge' techniques on social media to encourage healthy eating.

Researchers asked 369 university students to estimate the amount of fruit, vegetables, 'energy-dense snacks' and sugary drinks their Facebook peers consumed on a daily basis.

The information was cross-referenced with the participants' own actual eating habits and showed that those who felt their social circles 'approved' of eating junk food consumed significantly more themselves. Meanwhile, those who thought their friends ate a healthy diet ate more portions of fruit and veg. Their perceptions could have come from seeing friends' posts about the food and drink they consumed, or simply a general impression of their overall health.

There was no significant link between the participants' eating habits and their Body Mass Index (BMI), a standard measure of healthy weight, however. The researchers said the next stage of their work would track a participant group over time to see whether the influence of social media on eating habits had a longer-term impact on weight.

The most recent figures from the NHS's Health Survey for England showed that in 2018 only 28 percent of adults were eating the recommended five portions of fruit and vegetables per day. In Wales, this was 24 percent, in Scotland 22 percent and in Northern Ireland around 20 percent. Children and young people across the UK had even lower levels of fruit and veg consumption.

Aston University health psychology Ph.D. student Lily Hawkins, who led the study alongside supervisor Dr. Jason Thomas, said: "This study suggests we may be influenced by our social peers more than we realize when choosing certain foods. We seem to be subconsciously accounting for how others behave when making our own food choices. So if we believe our friends are eating plenty of fruit and veg we're more likely to eat fruit and veg ourselves. On the other hand, if we feel they're happy to consume lots of snacks and sugary drinks, it can give us a license to overeat foods that are bad for our health. The implication is that we can use social media as a tool to 'nudge' each other's eating behavior within friendship groups, and potentially use this knowledge as a tool for public health interventions."

"With children and young people spending a huge amount of time interacting with peers and influencers via social media, the important new findings from this study could help shape how we deliver interventions that help them adopt healthy eating habits from a young age and stick with them for life," said professor Claire Farrow.

A dietitian called Aisling Pigott further mentioned that "Research such as this demonstrates how we are influenced by online perceptions about how others eat. The promotion of positive health messages across social media, which are focused on promoting healthy choices and non-restrictive relationships with food and body, could nudge people into making positive decisions around the food they eat."

"We do have to be mindful of the importance of 'nudging' positive behaviors and not 'shaming' food choices on social media as a health intervention. We know that generating guilt around food is not particularly helpful when it comes to lifestyle change and maintenance," Aisling added.

New York, Feb 26:  A new wearable sensor that works in conjunction with artificial intelligence (AI) technology could help doctors remotely detect critical changes in heart failure patients days before a health crisis occurs, says a study.

The researchers said the system could eventually help avert up to one in three heart failure readmissions in the weeks following initial discharge from the hospital and help patients sustain a better quality of life.

"This study shows that we can accurately predict the likelihood of hospitalisation for heart failure deterioration well before doctors and patients know that something is wrong," says the study's lead author Josef Stehlik from University of Utah in the US.

"Being able to readily detect changes in the heart sufficiently early will allow physicians to initiate prompt interventions that could prevent rehospitalisation and stave off worsening heart failure," Stehlik added.

According to the researchers, even if patients survive, they have poor functional capacity, poor exercise tolerance and low quality of life after hospitalisations.

"This patch, this new diagnostic tool, could potentially help us prevent hospitalizations and decline in patient status," Stehlik said.

For the findings, published in the journal Circulation: Heart Failure, the researchers followed 100 heart failure patients, average age 68, who were diagnosed and treated at four veterans administration (VA) hospitals in Utah, Texas, California, and Florida.

After discharge, participants wore an adhesive sensor patch on their chests 24 hours a day for up to three months.

The sensor monitored continuous electrocardiogram (ECG) and motion of each subject.

This information was transmitted from the sensor via Bluetooth to a smartphone and then passed on to an analytics platform, developed by PhysIQ, on a secure server, which derived heart rate, heart rhythm, respiratory rate, walking, sleep, body posture and other normal activities.

Using artificial intelligence, the analytics established a normal baseline for each patient. When the data deviated from normal, the platform generated an indication that the patient's heart failure was getting worse.

Overall, the system accurately predicted the impending need for hospitalization more than 80 per cent of the time.

On average, this prediction occurred 10.4 days before a readmission took place (median 6.5 days), the study said.