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An improved algorithm to harmonize child overweight and obesity prevalence rates
Tim J Cole1, Tim Lobstein2,3
1University College London Great Ormond Street Institute of Child Health, London, UK.
Pediatric Obesity
|August 23, 2022
Summary
An improved algorithm harmonizes child overweight and obesity prevalence rates using different BMI references. This new method significantly enhances accuracy in estimating prevalence across diverse populations.
Area of Science:
- Pediatrics
- Public Health
- Biostatistics
Background:
- Child overweight and obesity prevalence varies with Body Mass Index (BMI) references and cut-offs.
- Previous algorithms could convert prevalence rates between references but required improvement.
Purpose of the Study:
- To enhance an existing algorithm for converting child overweight and obesity prevalence rates.
- To improve accuracy by incorporating both overweight and obesity prevalence data.
Main Methods:
- Developed a revised algorithm using paired prevalence rates of overweight and obesity.
- The algorithm estimates a group-specific z-score adjustment factor.
- Prevalence is transformed to z-score, adjusted, and back-transformed to predict prevalence using a different cut-off.
Main Results:
- The revised algorithm demonstrated superior performance compared to the original.
- Reduced the standard deviation of residuals to 0.8% (from 4.3% for original prevalence pairs).
- Explained 96.7% of baseline variance, a significant improvement over the original algorithm's 88.2%.
Conclusions:
- The enhanced algorithm effectively harmonizes child overweight and obesity prevalence rates across different references.
- Provides a more accurate and reliable method for comparing global child obesity data.
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