Early-life childhood obesity risk prediction: A Danish register-based cohort study exploring the predictive value of infancy weight gain

Background Information on postnatal weight gain is important for predicting later overweight and obesity, but it is unclear whether inclusion of this postnatal predictor improves the predictive performance of a comprehensive model based on prenatal and birth-related predictors. Objectives To compare performance of prediction models based on predictors available at birth, with and without information on infancy weight gain during the first year when predicting childhood obesity risk. Methods A Danish register-based cohort study including 55.041 term children born between January 2004 and July 2011 with birthweight >2500 g registered in The Children's Database was used to compare model discrimination, reclassification, sensitivity and specificity of two models predicting risk of childhood obesity at school age. Each model consisted of eight predictors available at birth, one additionally including information on weight gain during the first 12 months of life. Results The area under the receiving operating characteristic curve increased from 0.785 (95% confidence interval (CI) [0.773-0.798]) to 0.812 (95% CI [0.801-0.824]) after adding weight gain information when predicting childhood obesity. Adding this information correctly classified 30% more children without obesity and 21% with obesity and improved sensitivity from 0.42 to 0.48. Specificity remained unchanged at 0.91. Conclusion Adding infancy weight gain information improves discrimination, reclassification and sensitivity of a comprehensive prediction model based on predictors available at birth.

Automated summary

This study compared the predictive performance of models based on predictors available at birth with and without information on infant weight gain in the first year for childhood obesity risk prediction. The results showed that adding information on infant weight gain improved the model's discrimination, reclassification, and sensitivity.