Air pollution may up childhood anxiety, depression

Dear parents, if you want your children to have proper sleep, read this carefully. Joining a growing list of studies that tell parents to shun devices at bed-time, researchers say that children who use devices and decide what time they go to sleep, achieve less sleep and feel more sleepier the following day than their peers.

The study of children in this age-group (aged 11 to 13 years), published in the New Zealand Medical Journal, found most (72 per cent) of the 163 students interviewed by University of Otago researchers achieved recommended guidelines of an average 9 to 11 hours sleep nightly over one week.

"But that also means that almost one in four students did not achieve sleep within these guidelines, which highlights an area for improvement," said study researcher Kate Ford.

However, consistent with previous research in 15 to 17-year-old New Zealanders, the study results show less sleep on the nights where devices are used in the hour before bed.

According to the researchers, students who used devices before going to sleep were also more likely to report that they felt sleepy the following morning. Watching television before bed had no significant effect on sleep length.

There were also some interesting observations over the weekends where students went to bed later but woke later achieving similar sleep length to the school days, the researchers said.

A small group of students (six per cent) who reported less than seven hours of sleep, including a small number reporting not sleeping at all, according to the study,

Therefore, while the average across the week of 72 per cent of students reporting adequate sleep is reassuring, it is far from the goal of every child achieving sleep within the recommended guidelines," Ford said.

Dr Paul Kelly, head of the Sleep Health Service at Canterbury District Health Board, supervised the study and explained that the foundations for good health are based on proper nutrition, regular exercise and good sleep quality.

Sleep quality is often overlooked as a contributory factor to poor health.

"The study findings suggest the need for parental guidance around bedtimings and moderation of the use and availability of electronic devices before bed," Kelly said.

"Respect and protect your sleep, as good daytime functioning is reliant on adequate sleep," Kelly added.

Europe, Jan 11: Researchers have revealed the people who drink tea at least three times a week have healthy years of life and longer life expectancy.

The research was published in the European Journal of Preventive Cardiology, a journal of the European Society of Cardiology (ESC).

Dr Xinyan Wang, who is the author of the study, said: "Habitual tea consumption is associated with lower risks of cardiovascular disease and all-cause death. The favourable health effects are the most robust for green tea and for long-term habitual tea drinkers."
The analysis that was conducted included about 100,902 participants of the China-PAR project2 with no history of heart attack, stroke, or cancer.

Participants were classified into two groups: Habitual tea drinkers and never or non-habitual tea drinkers and followed-up for a median of 7.3 years.

The analyses estimated that 50-year-old habitual tea drinkers would develop coronary heart disease and stroke 1.41 years later and live 1.26 years longer than those who never or seldom drank tea. Compared with never or non-habitual tea drinkers, the habitual tea consumers had a 20 per cent lower risk of incident heart disease and stroke, 22 per cent lower risk of fatal heart disease and stroke, and 15 per cent decreased risk of all-cause death.

The potential influence of changes in tea drinking behaviour was suspected in a subset of 14,081 participants with assessments at two-time points. The average duration between the two surveys was 8.2 years, and the median follow-up after the second survey was 5.3 years.

Habitual tea drinkers who maintained their habit in both surveys had a 39 per cent lower risk of incident heart disease and stroke, 56 per cent lower risk of fatal heart disease and stroke, and 29 per cent decreased risk of all-cause death compared to consistent never or non-habitual tea drinkers.

Senior author Dr Dongfeng Gu said: "The protective effects of tea were most pronounced among the consistent habitual tea drinking group. Mechanism studies have suggested that the main bioactive compounds in tea, namely polyphenols, are not stored in the body long-term. Thus, frequent tea intake over an extended period may be necessary for the cardioprotective effect."

In a subanalysis by type of tea, drinking green tea was linked with approximately 25 per cent lower risks for incident heart disease and stroke, fatal heart disease and stroke, and all-cause death. However, no significant associations were observed for black tea.
Dr Gu noted that a preference for green tea is unique to East Asia.

Two factors may be at play. First, green tea is a rich source of polyphenols which protect against cardiovascular disease and its risk factors including high blood pressure and dyslipidaemia. Black tea is fully fermented and during this process, polyphenols are oxidised into pigments and may lose their antioxidant effects. Second, black tea is often served with milk, which previous research has shown may counteract the favourable health effects of tea on vascular function.

Gender-specific analyses showed that the protective effects of habitual tea consumption were pronounced and robust across different outcomes for men, but only modest for women. Dr Wang said: "One reason might be that 48 per cent of men were habitual tea consumers compared to just 20 per cent of women. Secondly, women had a much lower incidence of, and mortality from, heart disease and stroke. These differences made it more likely to find statistically significant results among men."

She said: "The China-PAR project is ongoing, and with more person-years of follow-up among women the associations may become more pronounced."

In conclusion, the authors have found that randomised trials are required to validate the results and to illustrate nutritional guidelines and advice for lifestyle.

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.