What if you could predict whether a baby is likely to become an obese kid (and, later, an obese teenager) as soon as he or she is born?
A simple new formula might enable physicians to do just that. Research conducted at Imperial College London and published Wednesday in the online journal PLOS One suggests that a handful of already recognized risk factors for childhood obesity can be used to calculate a specific child’s risk. The formula, easy to use and free to access via computer, could help doctors determine which babies and their families might benefit most from interventions aimed at preventing future overweight.
The study observes that public-health efforts to encourage weight loss among already-obese children and adults have yielded disappointing results, leading many experts to believe that identifying and adopting strategies to prevent people from becoming obese in the first place is key to battling population-wide obesity.
The research team in England analyzed 39 potential risk factors, including several genetic variants associated with obesity, for their accuracy in predicting obesity among 4,032 children in a Finnish database. Through that process, they determined that only a few of those factors were of much value in making such predictions. Interestingly, the genetic factors did not prove very useful in that regard.
The team then built a formula around those risk factors that they’d found best predicted which of the Finnish infants would be obese at age 7 or at age 16. Those key factors included the baby’s birth weight, the body mass index of the parents, the number of people in the household, the mother's professional status and whether she smoked during pregnancy – all of which information, the study notes, is readily available to physicians.
They then tested the formula on two other databases, one including 1,503 children in Italy, where the prevalence of childhood overweight and obesity is similar to that in Finland but where cultural circumstances that could affect a child’s weight were quite different, and another including 1,032 children in the U.S., cultural differences are also marked but where childhood overweight and obesity are far more prevalent than in Finland. The formula held up well among both populations, doing a fine job of pinpointing which babies would go on to become overweight children and teens.
The authors note that such a formula if used in common practice could help physicians allocate health-care resources by steering those kids who most need help toward nutrition and psychological counseling. They further note, though, that their formula should not be used to stigmatize some families or to falsely reassure other families that their babies are not at risk of becoming overweight in the future.
The study suggests that use of a formula such as the one it posits could be a key strategy in combating childhood overweight and obesity because it supports a preventative approach. “Employing focused strategies involving newborns whose risk is high according to diverse factors beyond social parameters, could lead to earlier, more effective prevention of overweight/obesity in children,” the authors conclude.