Exploring an algorithm to harmonize International Obesity Task Force and World Health Organization child overweight and obesity prevalence rates

Pediatr Obes. 2022 Jul;17(7):e12905. doi: 10.1111/ijpo.12905. Epub 2022 Feb 22.

Abstract

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 zA and zB to age-sex-specific BMI cut-offs, then transform the BMIs to z-scores zB,A and zA,B using the opposite reference. These z-scores together define the distance between the two cut-offs as the z-score difference dzA,B=12zB-zA+zA,B-zB,A . Prevalence in the target group based on cut-off A is then transformed to a z-score, adjusted up or down according to dzA,B 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.

Keywords: IOTF; WHO; harmonization; obesity; overweight; prevalence.

MeSH terms

  • Algorithms
  • Body Mass Index
  • Child
  • Female
  • Humans
  • Male
  • Obesity* / epidemiology
  • Overweight* / epidemiology
  • Prevalence
  • World Health Organization