Tea drinkers tend to have a longer and healthier life!

Should you let your babies "cry it out" or rush to their side? Researchers have found that leaving an infant to 'cry it out' from birth up to 18 months does not adversely affect their behaviour development or attachment.

The study, published in the Journal of Child Psychology and Psychiatry, found that an infant's development and attachment to their parents is not affected by being left to "cry it out" and can actually decrease the amount of crying and duration.

"Only two previous studies nearly 50 or 20 years ago had investigated whether letting babies 'cry it out' affects babies' development. Our study documents contemporary parenting in the UK and the different approaches to crying used," said the study's researcher Ayten Bilgin from the University of Warwick in the UK.

For the study, the researchers followed 178 infants and their mums over 18 months and repeatedly assessed whether parents intervened immediately when a baby cried or let the baby let it cry out a few times or often.

They found that it made little difference to the baby’s development by 18 months.

The use of parent’s leaving their baby to ‘cry it out’ was assessed via maternal report at term, 3, 6 and 18 months and cry duration at term, 3 and 18 months.

Duration and frequency of fussing and crying was assessed at the same ages with the Crying Pattern Questionnaire.

According to the researchers, how sensitive the mother is in interaction with their baby was video-recorded and rated at 3 and 18 months of age.

Attachment was assessed at 18 months using a gold standard experimental procedure, the strange situation test, which assesses how securely an infant is attached to the major caregiver during separation and reunion episodes.

Behavioural development was assessed by direct observation in play with the mother and during assessment by a psychologist and a parent-report questionnaire at 18 months.

Researchers found that whether contemporary parents respond immediately or leave their infant to cry it out a few times to often makes no difference on the short - or longer term relationship with the mother or the infants behaviour.

This study shows that 2/3 of mum's parent intuitively and learn from their infant, meaning they intervene when they were just born immediately, but as they get older the mother waits a bit to see whether the baby can calm themselves, so babies learn self-regulation.

Washington D.C., May 20: While a dairy-rich diet is helpful in meeting the body's calcium requirement, outcomes of a large international study links eating at least two daily servings of dairy with lower risks of diabetes and high blood pressure.

The dairy-rich diet also proved to lower the cluster of factors that heighten cardiovascular disease risk (metabolic syndrome). The study was published online in journal BMJ Open Diabetes Research & Care.

The observed associations were strongest for full-fat dairy products, the findings indicated.

Previously published research has suggested that higher dairy intake is associated with a lower risk of diabetes, high blood pressure, and metabolic syndrome. But these studies have tended to focus on North America and Europe to the exclusion of other regions of the world.

To see whether these associations might also be found in a broader range of countries, the researchers drew on people taking part in the Prospective Urban Rural Epidemiology (PURE) study.

Participants were all aged between 35 and 70 and came from 21 countries: Argentina; Bangladesh; Brazil; Canada; Chile; China; Colombia; India; Iran; Malaysia; Palestine; Pakistan; Philippines, Poland; South Africa; Saudi Arabia; Sweden; Tanzania; Turkey; United Arab Emirates; and Zimbabwe.

Usual dietary intake over the previous 12 months was assessed by means of Food Frequency Questionnaires. Dairy products included milk, yogurt, yogurt drinks, cheese and dishes prepared with dairy products, and were classified as full or low fat (1-2 percent).

Butter and cream were assessed separately as these are not commonly eaten in some of the countries studied.

Information on personal medical history, use of prescription medicines, educational attainment, smoking and measurements of weight, height, waist circumference, blood pressure and fasting blood glucose were also collected.

Data on all five components of the metabolic syndrome were available for nearly 113,000 people: blood pressure above 130/85 mm Hg; waist circumference above 80 cm; low levels of (beneficial) high-density cholesterol (less than 1-1.3 mmol/l); blood fats (triglycerides) of more than 1.7 mmol/dl; and fasting blood glucose of 5.5 mmol/l or more.

Average daily total dairy consumption was 179 g, with full-fat accounting for around double the amount of low fat: 124.5+ vs 65 g.

Some 46, 667 people had metabolic syndrome--defined as having at least 3 of the 5 components.

Total dairy and full-fat dairy, but not low-fat dairy, was associated with a lower prevalence of most components of metabolic syndrome, with the size of the association greatest in those countries with normally low dairy intakes.

At least 2 servings a day of total dairy were associated with a 24 percent lower risk of metabolic syndrome, rising to 28 percent for full-fat dairy alone, compared with no daily dairy intake.

The health of nearly 190,000 participants was tracked for an average of nine years, during which time 13,640 people developed high blood pressure and 5351 developed diabetes.

At least 2 servings a day of total dairy was associated with a 11-12 percent lower risk of both conditions, rising to a 13-14 percent lower risk for 3 daily servings. The associations were stronger for full fat than they were for low-fat dairy.

This is an observational study, and as such can't establish the cause. Food frequency questionnaires are also subject to recall, and changes in metabolic syndrome weren't measured over time, all of which may have influenced the findings.

Nevertheless, the researchers suggest: "If our findings are confirmed in sufficiently large and long term trials, then increasing dairy consumption may represent a feasible and low-cost approach to reducing [metabolic syndrome], hypertension, diabetes, and ultimately cardiovascular disease events worldwide."

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.