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Published on: February 2, 2017
Early-life childhood obesity risk prediction: A Danish register-based cohort study exploring the predictive value of
Torill Alise Rotevatn1, Rikke Nørmark Mortensen2, Line Rosenkilde Ullits1
1Public Health and Epidemiology Group, Department of Health Science and Technology, Aalborg University, Aalborg East, Denmark.
Insights
Adding infancy weight gain data significantly improves childhood obesity risk prediction models. This information enhances model accuracy and correctly identifies more children at risk, aiding early intervention strategies.
Area of Science:
- Pediatric Health
- Epidemiology
- Biostatistics
Background:
- Postnatal weight gain is crucial for predicting future overweight and obesity.
- Current predictive models for childhood obesity often lack comprehensive postnatal data.
- The impact of incorporating infancy weight gain on predictive model performance remains unclear.
Purpose of the Study:
- To evaluate the predictive performance of models for childhood obesity risk.
- To compare models with and without infancy weight gain data.
- To assess the impact of postnatal weight gain on prediction accuracy.
Main Methods:
- A Danish cohort study of 55,041 children born between 2004 and 2011.
- Development of two prediction models for childhood obesity risk at school age.
- Comparison of models using predictors available at birth versus those including first-year weight gain.
Main Results:
- The area under the receiver operating characteristic curve improved from 0.785 to 0.812 with the addition of weight gain data.
- Correct classification rates increased by 30% for children without obesity and 21% for those with obesity.
- Sensitivity improved from 0.42 to 0.48, while specificity remained stable at 0.91.
Conclusions:
- Incorporating infancy weight gain significantly enhances the discrimination and reclassification of childhood obesity risk prediction models.
- The improved sensitivity suggests better identification of at-risk children.
- This finding supports the inclusion of early-life weight gain in comprehensive obesity prediction strategies.
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.
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