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Published on: February 2, 2017
Validation of Variables for Use in Pediatric Obesity Risk Score Development in Demographically and Racially Diverse
Castle J Funatake1, Marcos Armendáriz1, Stephen Rauch2
1Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, University of California, San Francisco, San Francisco, CA.
Insights
Validated childhood obesity prediction models using five easily obtainable clinical variables performed well across diverse US cohorts. These models effectively identify children at high risk for early obesity, aiding timely intervention.
Area of Science:
- Pediatric Health
- Public Health
- Biostatistics
Background:
- Childhood obesity is a significant public health concern in the United States.
- Early identification of at-risk children is crucial for timely intervention.
- Existing prediction models require validation across diverse populations and settings.
Purpose of the Study:
- To evaluate the performance of previously validated childhood obesity prediction models.
- To assess model utility using easily obtainable clinical variables from medical records.
- To test models in four independent, demographically diverse US cohorts.
Main Methods:
- Utilized data from four prospective cohorts: Latinx, Eating, and Diabetes; Stress in Pregnancy Study; Project Viva; and Center for the Health Assessment of Mothers and Children of Salinas.
- Applied a validated risk model using five clinical variables: maternal age, maternal prepregnancy body mass index, birth weight Z-score, weight-for-age Z-score change, and breastfeeding.
- Employed multivariable logistic regression and assessed model performance using discrimination (Area Under the Curve) and predictive accuracy.
Main Results:
- Risk models demonstrated excellent discrimination across all four cohorts (AUCs ranging from 0.79 to 0.86).
- High specificity (≥ 90%) and negative predictive values (≥ 80%) were consistently achieved.
- Positive predictive values ranged from 62% to 86%, with sensitivity varying from 12% to 53% at the 50th percentile threshold.
Conclusions:
- The validated risk models performed effectively in independent and diverse US cohorts.
- The five selected clinical variables are useful for identifying children at high risk for early obesity.
- These findings support the clinical utility of these variables for early childhood obesity risk assessment.
Objective:
To evaluate the performance of childhood obesity prediction models in four independent cohorts in the United States, using previously validated variables obtained easily from medical records as measured in different clinical settings.
Study Design:
Data from four prospective cohorts, Latinx, Eating, and Diabetes; Stress in Pregnancy Study; Project Viva; and Center for the Health Assessment of Mothers and Children of Salinas were used to test childhood obesity risk models and predict childhood obesity by ages 4 through 6, using five clinical variables (maternal age, maternal prepregnancy body mass index, birth weight Z-score, weight-for-age Z-score change, and breastfeeding), derived from a previously validated risk model and as measured in each cohort's clinical setting. Multivariable logistic regression was performed within each cohort, and performance of each model was assessed based on discrimination and predictive accuracy.
Results:
The risk models performed well across all four cohorts, achieving excellent discrimination. The area under the receiver operator curve was 0.79 for Center for the Health Assessment of Mothers and Children of Salinas and Project Viva, 0.83 for Stress in Pregnancy Study, and 0.86 for Latinx, Eating, and Diabetes. At a 50th percentile threshold, the sensitivity of the models ranged from 12% to 53%, and specificity was ≥ 90%. The negative predictive values were ≥ 80% for all cohorts, and the positive predictive values ranged from 62% to 86%.
Conclusion:
All four risk models performed well in each independent and demographically diverse cohort, demonstrating the utility of these five variables for identifying children at high risk for developing early childhood obesity in the United States.
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