Estimation of newborn risk for child or adolescent obesity: lessons from longitudinal birth cohorts

Anita Morandi1, David Meyre, Stéphane Lobbens

  • 1Unité Mixte de Recherche 8199, Centre National de Recherche Scientifique (CNRS) and Pasteur Institute, Lille, France. anita.morandi@voila.fr

Plos One
|December 5, 2012
PubMed

Insights

This study developed simple tools to predict childhood obesity risk in newborns using easily recorded information. These tools are crucial for early intervention against the growing global obesity epidemic.

Area of Science:

  • Pediatrics
  • Genetics
  • Public Health

Background:

  • Obesity prevention is critical, starting from early life.
  • Early identification of obesity risk in newborns is needed for targeted interventions.
  • The global obesity epidemic requires proactive strategies.

Purpose of the Study:

  • To create clinically useful predictive equations for later obesity in newborns.
  • To develop tools for early obesity risk assessment in infants.
  • To aid in the prevention of childhood and adolescent obesity.

Main Methods:

  • Analysis of the Northern Finland Birth Cohort 1986 (NFBC1986) with traditional risk factors and a genetic score.
  • Development of predictive equations for childhood and adolescent obesity.
  • Validation of predictive models in Italian and U.S. pediatric cohorts.

Main Results:

  • Traditional risk factors accurately predicted childhood and adolescent obesity (AUROC 0.75-0.85).
  • Adding a genetic score showed minimal improvement (≤1%) in prediction accuracy.
  • Predictive equations demonstrated good accuracy in independent validation cohorts and were converted into risk calculators.

Conclusions:

  • The study provides the first practical tools for predicting childhood obesity risk in newborns using readily available data.
  • Currently known genetic variants have limited utility in predicting childhood obesity.
  • These tools can facilitate early, focused interventions against childhood obesity.
Abstract

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