With 41 Million Obese, India Third After US, China

June 7, 2014

Obese nationIndia is the 3rd most obese nation in the world. The country houses at least 41 million overweight people.

India being a third world and rather poor country wouldn’t be high on people’s mind when it comes to obesity.

When India is mentioned, people mostly think of malnutrition and poverty. Though it is still true in most cases, but with increasing affluence at least in metros and their suburbs and the newly acquired wealth, there is an increasing middle class in the making.

Some people claim that this middle class is already 200 million strong. Though this may not be true right now but there is no denying the fact that a part of the population is indeed a lot better and can afford decent living.

It will be a revelation of sorts for most people that there are as many as 41 million obese people in the country. After United States, China this is the third highest number and the Indian government should devise a workable plan to fight this menace, a latest study says.

The report that has been titled rather too long says that along with China and the US the trio makes around 15 percent of world’s total obese population. The study has been titled as “Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Christopher Murray, director of IHME says that “In the last three decades, not one country has achieved success in reducing obesity rates, and we expect obesity to rise steadily as incomes rise in low and middle income countries in particular, unless urgent steps are taken to address this public health crisis”. The study has concluded that the number of overweight and obese individuals globally has increased from 857 million in 1980 to 2.1 billion in 2013. This is one third of the world’s total population.

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News Network
February 26,2020

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.

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Agencies
March 3,2020

Taking multiple courses of antibiotics within a short span of time may do people more harm than good, suggests new research which discovered an association between the number of prescriptions for antibiotics and a higher risk of hospital admissions.

Patients who have had 9 or more antibiotic prescriptions for common infections in the previous three years are 2.26 times more likely to go to hospital with another infection in three or more months, said the researchers.

Patients who had two antibiotic prescriptions were 1.23 times more likely, patients who had three to four prescriptions 1.33 times more likely and patients who had five to eight 1.77 times more likely to go to hospital with another infection.

"We don't know why this is, but overuse of antibiotics might kill the good bacteria in the gut (microbiota) and make us more susceptible to infections, for example," said Professor Tjeerd van Staa from the University of Manchester in Britain.

The study, published in the journal BMC Medicine, is based on the data of two million patients in England and Wales.

The patient records, from 2000 to 2016, covered common infections such as upper respiratory tract, urinary tract, ear and chest infections and excluded long term conditions such as cystic fibrosis and chronic lung disease.

The risks of going to hospital with another infection were related to the number of the antibiotic prescriptions in the previous three years.

A course is defined by the team as being given over a period of one or two weeks.

"GPs (general physicians) care about their patients, and over recent years have worked hard to reduce the prescribing of antibiotics,""Staa said.

"But it is clear GPs do not have the tools to prescribe antibiotics effectively for common infections, especially when patients already have previously used antibiotics.

"They may prescribe numerous courses of antibiotics over several years, which according to our study increases the risk of a more serious infection. That in turn, we show, is linked to hospital admissions," Staa added.

It not clear why hospital admissions are linked to higher prescriptions and research is needed to show what or if any biological factors exist, said the research team.

"Our hope is that, however, a tool we are working for GPs, based on patient history, will be able to calculate the risks associated with taking multiple courses of antibiotics," said Francine Jury from the University of Manchester.

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Agencies
June 22,2020

A team of scientists has produced first open source all-atom models of full-length COVID-19 Spike protein that facilitates viral entry into host cells – a discovery that can facilitate a faster vaccine and antiviral drug development.

The group from Seoul National University in South Korea, University of Cambridge in the UK and Lehigh University in the US produced the first open-source all-atom models of a full-length S protein.

The researchers say this is of particular importance because the S protein plays a central role in viral entry into cells, making it a main target for vaccine and antiviral drug development.

"Our models are the first full-length SARS-CoV-2 spike (S) protein models that are available to other scientists," said Wonpil Im, a professor in Lehigh University.

"Our team spent days and nights to build these models very carefully from the known cryo-EM structure portions. Modeling was very challenging because there were many regions where simple modeling failed to provide high-quality models," he wrote in a paper published in The Journal of Physical Chemistry B.

Scientists can use the models to conduct innovative and novel simulation research for the prevention and treatment of Covid-19.

Though the coronavirus uses many different proteins to replicate and invade cells, the Spike protein is the major surface protein that it uses to bind to a receptor.

The total number of global COVID-19 cases was nearing 9 million, while the deaths have increased to over 467,000, according to the Johns Hopkins University.

With 2,279,306 cases and 119,967 deaths, the US continues with the world's highest number of COVID-19 infections and fatalities, according to the CSSE.

Brazil comes in the second place with 1,083,341 infections and 50,591 deaths.

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