Eating too quickly linked to obesity and increased risk of heart disease, diabetes and stroke

The quicker you eat, the more likely you are to overeat

Rachel Hosie
Wednesday 15 November 2017 11:28 EST
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Eating slowly could make you less likely to become obese or develop metabolic syndrome, according to preliminary research.

This is likely because eating quickly may cause fluctuations in your blood sugar, which can lead to insulin resistance.

Metabolic syndrome is a combination of disorders that multiply a person’s risk for heart disease, diabetes and stroke.

It occurs when someone has any of three risk factors that include abdominal obesity, high fasting blood sugar, high blood pressure, high triglycerides and/or low HDL cholesterol.

According to research presented at the American Heart Association’s Scientific Sessions 2017, eating more slowly could be the key to keeping your health and body in check.

A team from Hiroshima University in Japan evaluated 642 men and 441 women with an average age of 51.2 years, none of whom had metabolic syndrome, in 2008.

The participants were divided into three categories based on how they described their usual eating speed: slow, normal or fast.

Five years later, the researchers reassessed the participants.

They found that the fast eaters were more likely (11.6 per cent) to have developed metabolic syndrome than normal eaters (6.5 per cent) and slow eaters (2.3 per cent).

Eating quickly was also linked to more weight gain, larger waistline and higher blood glucose.

Taking the time to consciously chew your food and eat slowly allows for your brain to receive fullness signals, so you're more likely to stop eating earlier.

“Eating more slowly may be a crucial lifestyle change to help prevent metabolic syndrome,” said Takayuki Yamaji, M.D., study author and cardiologist at Hiroshima University in Japan.

“When people eat fast they tend not to feel full and are more likely to overeat. Eating fast causes bigger glucose fluctuation, which can lead to insulin resistance. We also believe our research would apply to a U.S. population.”

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