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

Title: Exploring an algorithm to harmonize International Obesity Task Force and World Health Organization child overweight and obesity prevalence rates
Authors: Cole, Tim J; Lobstein, Tim
Source: Pediatric Obesity , Article e12905. (2022) (In press).
Publisher Information: WILEY
Publication Year: 2022
Collection: University College London: UCL Discovery
Subject Terms: Science & Technology; Life Sciences & Biomedicine; Pediatrics; harmonization; IOTF; obesity; overweight; prevalence; WHO; BODY-MASS INDEX; THINNESS; HEIGHT
Description: 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 z A and z B to age-sex-specific BMI cut-offs, then transform the BMIs to z-scores z B , A and z A , B using the opposite reference. These z-scores together define the distance between the two cut-offs as the z-score difference dz A , B = 1 2 z B - z A + z A , B - z B , A . Prevalence in the target group based on cut-off A is then transformed to a z-score, adjusted up or down according to dz A , 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.
Document Type: article in journal/newspaper
File Description: text
Language: English
Relation: https://discovery.ucl.ac.uk/id/eprint/10144938/
Availability: https://discovery.ucl.ac.uk/id/eprint/10144938/1/Pediatric%20Obesity%20-%202022.pdf; https://discovery.ucl.ac.uk/id/eprint/10144938/
Rights: open
Accession Number: edsbas.C544B5E7
Database: BASE