Simple Formula Predicts Child Obesity at Birth

Elementary health metrics such as a mother's body weight and whether she smokes have helped researchers build a formula that predicts childhood obesity rates with 80 percent success.

 Orion Jones
30 November, 2012

What's the Latest Development?

Simple health metrics like a mother's body weight and whether she smokes can be used to effectively predict whether a child will become obese, according to researchers at Imperial College London who conducted a study of more than 6,500 children. "The equation is based on data everyone can obtain from a newborn, and we found it can predict around 80% of obese children," said the researchers. "Unfortunately, public prevention campaigns have been rather ineffective at preventing obesity in school-age children. Teaching parents about the dangers of overfeeding and bad nutritional habits at a young age would be much more effective."

What's the Big Idea?

The simplicity of the new formula is at odds with current research that emphasized the role of a person's genes in determining whether they would become overweight. "Previously it had been thought that genetic factors would give bigger clues to later weight problems, but only about one in 10 cases of obesity is the result of a rare gene mutation that affects appetite. ... The risk factors for obesity are already well known, but this is the first time these factors have been put together in a formula." Prof Philippe Froguel from Imperial College London, who led the study, said that prevention was the best strategy.

Photo credit: Shutterstock.com

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