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Updated: Oct 2, 2025
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Exploring an algorithm to harmonize International Obesity Task Force and World Health Organization child overweight
Tim J Cole1, Tim Lobstein2,3
1Population, Policy and Practice Research and Teaching Programme, University College London Great Ormond Street Institute of Child Health, London, UK.
Insights
This study developed an algorithm to harmonize child overweight and obesity prevalence rates using International Obesity Task Force (IOTF) and World Health Organization (WHO) body mass index (BMI) cut-offs. The algorithm accurately adjusts prevalence data, improving comparability across different references.
Area of Science:
- Pediatric Endocrinology
- Public Health Nutrition
- Biostatistics
Background:
- International Obesity Task Force (IOTF) and World Health Organization (WHO) body mass index (BMI) cut-offs are standard for assessing child overweight and obesity.
- Discrepancies in prevalence rates arise when applying IOTF and WHO criteria to the same pediatric populations.
- This inconsistency complicates accurate global and regional comparisons of childhood obesity trends.
Purpose of the Study:
- To develop a novel algorithm for harmonizing child overweight and obesity prevalence rates.
- To ensure comparability between prevalence data derived from IOTF and WHO BMI references.
- To provide a standardized method for analyzing childhood BMI trends across different datasets.
Main Methods:
- The algorithm harmonizes prevalence rates by back-transforming z-scores to BMI cut-offs and then re-transforming using the alternative reference.
- It calculates a z-score difference to adjust prevalence estimates between the IOTF and WHO standards.
- Validation involved testing the algorithm on 74 diverse pediatric groups across 14 European countries.
Main Results:
- The developed algorithm demonstrated strong performance in harmonizing prevalence rates.
- The standard deviation of the difference between paired prevalence rates was 6.6% (n=604).
- The algorithm explained 88% of the baseline variance, with a residual standard deviation of 2.3% for observed versus predicted prevalence.
Conclusions:
- The algorithm effectively addresses the challenge of harmonizing child overweight and obesity prevalence data.
- It offers a valuable tool for researchers and public health officials working with children aged 2-18.
- Improved data harmonization facilitates more reliable tracking of childhood obesity epidemics globally.
Background:
The International Obesity Task Force (IOTF) and World Health Organization (WHO) body mass index (BMI) cut-offs are widely used to assess child overweight, obesity and thinness prevalence, but the two references applied to the same children lead to different prevalence rates.
Objectives:
To develop an algorithm to harmonize prevalence rates based on the IOTF and WHO cut-offs, to make them comparable.
Methods:
The cut-offs are defined as age-sex-specific BMI z-scores, for example, WHO +1 SD for overweight. To convert an age-sex-specific prevalence rate based on reference cut-off A to the corresponding prevalence based on reference cut-off B, first back-transform the z-score cut-offs and to age-sex-specific BMI cut-offs, then transform the BMIs to z-scores and using the opposite reference. These z-scores together define the distance between the two cut-offs as the z-score difference . Prevalence in the target group based on cut-off A is then transformed to a z-score, adjusted up or down according to and back-transformed, and this predicts prevalence based on cut-off B. The algorithm's performance was tested on 74 groups of children from 14 European countries.
Results:
The algorithm performed well. The standard deviation (SD) of the difference between pairs of prevalence rates was 6.6% (n = 604), while the residual SD, the difference between observed and predicted prevalence, was 2.3%, meaning that the algorithm explained 88% of the baseline variance.
Conclusions:
The algorithm goes some way to addressing the problem of harmonizing overweight and obesity prevalence rates for children aged 2-18.
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