10 reasons you can't afford to be obese

[email protected] (Health Me Up)
August 29, 2014

ObeseObesity is by definition excess of fat storage rather than weight. Men with more than 25% of total body fat and women with more than 30% total body fat are considered obese.

There are many different ways to classify obesity. In accordance with endocrine and pathogen of the metabolic disease, obesity can be divided into simple obesity, secondary obesity and drug-induced obesity. Obesity, a growing health problem, is the door to a lot of illness and life threatening conditions that can make your life a living hell. Dr Ramen Goel, Head, Bariatric Surgery, Nova Specialty Surgery, Tardeo Mumbai, explains 10 reasons why obesity is bad for your health.

Type 2 diabetes

Obesity is one of the major causes of type 2 diabetes. Studies suggest that higher than normal body weight greatly increases the risk of getting diabetes. Uncontrolled diabetes in return leads to all serious complications such as high BP, heart attacks, brain strokes, blindness, kidney failures and nerve damages with amputations.

Heart attack

Obesity and overweight are linked to several factors that increase one's risk for cardiovascular disease (heart attack). Abdominal obesity or pot belly is said to be one of the major risk factors that can lead to heart ailments.

High blood pressure

Weight gain and hypertension are interconnected as increased weight raises the risk of developing high blood pressure. Weight reduction can actually help normalize the blood pressure. No wonder doctors recommend those suffering from hypertension to exercise and maintain their body weight.

Obstructive sleep apnea

Obesity results in obstructive sleep apnea where the person is not able to sleep well and snores, while remaining drowsy during the day. It is a respiratory problem in which breathing is stopped intermittently during sleep. Besides problem of sleep this results in high BP, heart failure etc.

Gout

An obese person is four times as likely to develop gout- a medical problem that affects joints, as someone with a normal body weight. In gout people have increased uric acid levels which results in painful, red and inflamed joints. With weight loss, the uric acid levels in the blood can decrease.

High cholesterol

One of the major risks in being overweight is the development of high cholesterol. Obesity increases the levels of triglycerides and bad cholesterol (LDL) in the body. Obese people generally have low levels of good cholesterol (HDL). High level of LDL and low level of HDL are major causes of atherosclerosis which results in narrowing of blood vessels leading to heart attack.

GERD

Recent research suggests that obesity is driving rise in people suffering from acid reflux. Obesity increases reflux because abdominal fat puts pressure on the ring of muscle at the bottom of the oesophagus - the 10-inch tube connecting the throat to the stomach - which normally prevents stomach acid from flowing back. The condition leads to heartburn.

Osteoarthritis

Being overweight puts extra stress on the joints, such as the knees, and consequently is a risk factor for developing osteoarthritis. Increased body weight puts more stress on joint surfaces causing damage.

Cancer

Medical research suggests that obesity plays an important role in cancer and that the lifetime risk of cancers is more among obese individuals. Obese people have higher chances of getting bowel, breast and esophageal cancers.

Heart failure

Worldwide research suggests that increased body-mass index is associated with an increased risk of heart failure.

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News Network
February 4,2020

Toronto, Feb 4: People who text while walking face a higher risk of an accident than those listening to music or talking on the phone, a study has found.

The study, published in the journal Injury Prevention, found that smartphone texting is linked to compromised pedestrian safety, with higher rates of 'near misses', and failure to look left and right before crossing a road.

Researchers from the University of Calgary in Canada call for a more thorough approach to exploring the impact of distracted pedestrian behaviours on crash risk.

Worldwide, around 270,000 pedestrians die every year, accounting for around a fifth of all road traffic deaths, according to the researchers.

'Pedestrian distraction' has become a recognised safety issue as more and more people use their smartphones or hand held devices while walking on the pavement and crossing roads, they said.

The researchers looked for published evidence to gauge the potential impact on road safety of hand-held or hands-free device activities.

This included talking on the phone, text messaging, browsing and listening to music.

From among 33 relevant studies, they pooled the data from 14 -- involving 872 people -- and systematically reviewed the data from another eight.

The analysis showed that listening to music wasn't associated with any heightened risk of potentially harmful pedestrian behaviours.

Talking on the phone was associated with a small increase in the time taken to start crossing the road, and slightly more missed opportunities to cross the road safely.

The researchers found that text messaging emerged as the potentially most harmful behaviour.

It was associated with significantly lower rates of looking left and right before or while crossing the road, and with moderately increased rates of collisions, and close calls with other pedestrians or vehicles, they said.

Texting also affected the time taken to cross a road, and missed opportunities to cross safely, but to a lesser extent, according to the researchers.

The review of the eight observational studies revealed that the percentage of pedestrians who were distracted ranged from 12 to 45 per cent, they said.

It also found behaviours were influenced by several factors, including gender, time of day, solo or group crossing, and walking speed.

The researchers acknowledge "a variety of study quality issues" which limit the generalisability of the findings.

"Given the ubiquity of smartphones, social media, apps, digital video and streaming music, which has infiltrated most aspects of daily life, distracted walking and street cross will be a road safety issue for the foreseeable future," the researchers noted.

"And as signage and public awareness campaigns don't seem to alter pedestrian behaviour, establishing the relationship between distracted walking behaviour and crash risk is an essential research need," they said.

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News Network
July 10,2020

Toronto, Jul 10: Pasteurising breast milk at 62.5 degrees Celsius for 30 minutes inactivates the SARS-CoV-2 virus that causes Covid-19, making it safe for consumption by babies, a study claims.

According to the research published in the Canadian Medical Association Journal, current advice for women with Covid-19 is to continue to breastfeed their own infants.

In Canada, it is standard care to provide pasteurised breast milk to very-low-birth-weight babies in hospital until their own mother's milk supply is adequate, the researchers said.

"In the event that a woman who is Covid-19-positive donates human milk that contains SARS-CoV-2, whether by transmission through the mammary gland or by contamination through respiratory droplets, skin, breast pumps and milk containers, this method of pasteurisation renders milk safe for consumption," said Sharon Unger, a professor at the University of Toronto in Canada.

The Holder method, a technique used to pasteurise milk in all Canadian milk banks at 62.5 degrees Celsius for 30 minutes, is effective at neutralising viruses such as HIV, hepatitis and others that are known to be transmitted through human milk, the researchers said.

In the latest study, the researchers spiked human breast milk with a viral load of SARS-CoV-2 and tested samples that either sat at room temperature for 30 minutes or were warmed to 62.5 degrees Celsius for 30 minutes.

They then measured for active virus, finding that the virus in the pasteurised milk was inactivated after heating.

More than 650 human breast milk banks around the world use the Holder method to ensure a safe supply of milk for vulnerable infants, the researchers said.

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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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