Estimation of Newborn Risk for Child or Adolescent Obesity: Lessons from Longitudinal Birth Cohorts
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Author
Morandi, Anita
Meyre, David
Lobbens, Stéphane
Kaakinen, Marika
Vatin, Vincent
Gaget, Stefan
Pouta, Anneli
Hartikainen, Anna-Liisa
Laitinen, Jaana
Ruokonen, Aimo
Das, Shikta
Khan, Anokhi Ali
Elliott, Paul
Maffeis, Claudio
Järvelin, Marjo-Riitta
Froguel, Philippe
Note: Order does not necessarily reflect citation order of authors.
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https://doi.org/10.1371/journal.pone.0049919Metadata
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Morandi, Anita, David Meyre, Stéphane Lobbens, Ken Paul Kleinman, Marika Kaakinen, Sheryl Lynn Rifas-Shiman, Vincent Vatin, et al. 2012. Estimation of newborn risk for child or adolescent obesity: Lessons from longitudinal birth cohorts. PLoS ONE 7(11): e49919.Abstract
Objectives: Prevention of obesity should start as early as possible after birth. We aimed to build clinically useful equations estimating the risk of later obesity in newborns, as a first step towards focused early prevention against the global obesity epidemic. Methods: We analyzed the lifetime Northern Finland Birth Cohort 1986 (NFBC1986) (N = 4,032) to draw predictive equations for childhood and adolescent obesity from traditional risk factors (parental BMI, birth weight, maternal gestational weight gain, behaviour and social indicators), and a genetic score built from 39 BMI/obesity-associated polymorphisms. We performed validation analyses in a retrospective cohort of 1,503 Italian children and in a prospective cohort of 1,032 U.S. children. Results: In the NFBC1986, the cumulative accuracy of traditional risk factors predicting childhood obesity, adolescent obesity, and childhood obesity persistent into adolescence was good: AUROC = 0·78[0·74–0.82], 0·75[0·71–0·79] and 0·85[0·80–0·90] respectively (all p<0·001). Adding the genetic score produced discrimination improvements ≤1%. The NFBC1986 equation for childhood obesity remained acceptably accurate when applied to the Italian and the U.S. cohort (AUROC = 0·70[0·63–0·77] and 0·73[0·67–0·80] respectively) and the two additional equations for childhood obesity newly drawn from the Italian and the U.S. datasets showed good accuracy in respective cohorts (AUROC = 0·74[0·69–0·79] and 0·79[0·73–0·84]) (all p<0·001). The three equations for childhood obesity were converted into simple Excel risk calculators for potential clinical use. Conclusion: This study provides the first example of handy tools for predicting childhood obesity in newborns by means of easily recorded information, while it shows that currently known genetic variants have very little usefulness for such prediction.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3509134/pdf/Terms of Use
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