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Health & Medicine Formula to Predict New Born's Chances Of Being Obese

Formula to Predict New Born's Chances Of Being Obese

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First Posted: Nov 30, 2012 12:25 AM EST
Formula to Predict New Born's Chances Of Being Obese
Is your child getting enough rest? (Photo : Reuters)

Obesity is a chronic medical condition, which can seriously affect a person's health and well-being. Childhood obesity is a grave concern for both parents and pediatricians. A team of researchers has devised a model to predict whether a new born will be obese when it grows based on various factors.

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Childhood obesity is a leading cause of early type 2 diabetes, heart and circulatory diseases and is common in developed countries. School canteens are supposedly the main culprits as they mostly provide high calorie junk food.  According to National Health Figures, 17 percent of boys and 15 percent of girls aged two to 15 in England are classified as obese.

Intake of high calorie junk food and lack of physical exercise are the major factors that cause obesity in a child. But what if parents can calculate the chance of whether their new born is at a risk of becoming obese?

Researchers from the School of Public Health at Imperial College London have devised a simple formula that can predict whether the baby will be obese when it grows.

A team of researchers from Imperial College in collaboration with colleagues at the University of Oulu, Finland, Harvard University in the US and the University of Verona, Italy, has devised an online calculator that estimates a child's obesity risk based on factors such as birth weight, body mass index of the parents, the number of people in a household, the mother's professional status and most importantly whether the mother smoked during pregnancy.

The researchers hope that this new discovery will help parents identify infants who are at a high risk of becoming obese so that they can take necessary steps in order to curb this chronic problem.

This formula was developed using data from a study set up in 1986 following 4000 children born in Finland. Initially the researchers tried to analyze whether obesity risk could be assessed using genetic profiles. Unfortunately this was not a success, as the test they developed, based on common genetic variations, failed to make accurate predictions.

Rather, they discovered that non-genetic information readily available at the time of birth was enough to predict which children would become obese. The formula proved accurate not just in the Finnish cohort, but in further tests using data from studies in Italy and the U.S.

"This test takes very little time, it doesn't require any lab tests and it doesn't cost anything," said Professor Philippe Froguel, from the School of Public Health at Imperial College London, who led the study.

"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."

On testing their formula on the participants, they noticed that nearly 20 percent of the children marked as the highest risk at birth made up 80 percent of obese children.

The researchers suggest that those families whose infants are at high risk of obesity should be offered the assistance of a dietitians and psychologists that would guide the families in tackling this problem and prevent excess weight gain.

"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 Professor 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."

Although common genetic variants did not prove to be helpful in predicting childhood obesity, the researchers say about one in 10 cases of obesity are caused by rare mutations that seriously affect appetite regulation. 

The obesity risk calculator is available online at http://files-good.ibl.fr/childhood-obesity/ .

This study is published in the open access journal PLOS ONE.

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