Researchers Develop Method To Predict Risk Of Obesity At Birth
November 29, 2012

Researchers Develop Method To Predict Risk Of Obesity At Birth

Lawrence LeBlond for - Your Universe Online

Researchers from Imperial College London say they have found a way to predict a baby´s chance of being obese using a simple formula combining several known factors, such as birth weight, parents´ body mass index and whether or not the mother smoked during pregnancy.

Other factors include professional status of the mother, with children of less qualified parents more likely to become obese, and size of household, with children from smaller families being at greater risk of becoming overweight.

The authors of the study, published in the journal PLoS ONE, hope their prediction method will be used to help identify infants that are at high risk for becoming overweight and obese and help families take steps to prevent their children from putting on too much weight. With childhood obesity being the leading cause of early Type 2 diabetes and heart and circulatory disease, researchers are doing everything in their power to find ways to reverse a growing problem that has become increasingly more common in developed countries.

The formula was developed using data from a 1986 study following some 4000 children born in Finland. The researchers initially investigated whether obesity risk could be predicted using genetic profiles, but the test they developed based on common genetic variations failed to give accurate measurements. However, the team discovered that non-genetic information readily available at the time of birth was enough to make accurate predictions on risk of obesity.

The team posted the checklist of factors online, hoping for health and social workers to use them in their quest to prevent childhood obesity.

"This test takes very little time, it doesn't require any lab tests and it doesn't cost anything," said study leader Professor Philippe Froguel, from the School of Public Health at Imperial College London. "All the data we use are well-known risk factors for childhood obesity, but this is the first time they have been used together to predict from the time of birth the likelihood of a child becoming obese."

The researchers said the 20 percent of children predicted to have the highest risk at birth make up 80 percent of obese children.

"Once a young child becomes obese, it's difficult for them to lose weight, so prevention is the best strategy, and it has to begin as early as possible," said Froguel. "Unfortunately, public prevention campaigns have been rather ineffective at preventing obesity in school-age children. Teaching parents about the dangers of over-feeding and bad nutritional habits at a young age would be much more effective."

The researchers note that the message is quite simple. “All at-risk children should be identified, monitored and given good advice.”

However, like everything, this costs money.

Professor Paul Gately, a specialist in childhood obesity at Leeds Metropolitan University, said a toll such as this one would be extremely helpful for the National Health Service (NHS), allowing for targeting specific people at risk rather than the conventional “one-size-fits-all” method, which has been largely unsuccessful.

"Rather than spending money on a huge number of people, we can be more specific and spend appropriately. We may not save money in the short-term but it will be spent more wisely and could reduce [obesity-related] NHS bills in the future,” Gately told the BBC´s Melissa Hogenboom.

“We've done a great job of outlining that obesity is a serious issue but we have made the general public paranoid that everyone is at risk,” he said. “Tools like this will help change that attitude. Once we use the tool, we need intervention [programs] for children at a greater risk.”

Although the researchers failed to find genetic variations that could predict childhood obesity at birth, they did note that about one in 10 cases of obesity are caused by rare mutations that seriously affect appetite regulation. Tests for these mutations could become available to doctors in the next few years as the cost of DNA sequencing technology falls.