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An improved algorithm to harmonize child overweight and obesity prevalence rates
BACKGROUND: Prevalence rates of child overweight and obesity for a group of children vary depending on the BMI reference and cut‐off used. Previously we developed an algorithm to convert prevalence rates based on one reference to those based on another. OBJECTIVE: To improve the algorithm by combini...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10078258/ https://www.ncbi.nlm.nih.gov/pubmed/35997305 http://dx.doi.org/10.1111/ijpo.12970 |
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author | Cole, Tim J. Lobstein, Tim |
author_facet | Cole, Tim J. Lobstein, Tim |
author_sort | Cole, Tim J. |
collection | PubMed |
description | BACKGROUND: Prevalence rates of child overweight and obesity for a group of children vary depending on the BMI reference and cut‐off used. Previously we developed an algorithm to convert prevalence rates based on one reference to those based on another. OBJECTIVE: To improve the algorithm by combining information on overweight and obesity prevalence. METHODS: The original algorithm assumed that prevalence according to two different cut‐offs A and B differed by a constant amount [Formula: see text] on the z‐score scale. However the results showed that the z‐score difference tended to be greater in the upper tail of the distribution and was better represented by [Formula: see text] , where [Formula: see text] was a constant that varied by group. The improved algorithm uses paired prevalence rates of overweight and obesity to estimate [Formula: see text] for each group. Prevalence based on cut‐off A is then transformed to a z‐score, adjusted up or down according to [Formula: see text] and back‐transformed, and this predicts prevalence based on cut‐off B. The algorithm's performance was tested on 228 groups of children aged 6–17 years from 20 countries. RESULTS: The revised algorithm performed much better than the original. The standard deviation (SD) of residuals, the difference between observed and predicted prevalence, was 0.8% (n = 2320 comparisons), while the SD of the difference between pairs of the original prevalence rates was 4.3%, meaning that the algorithm explained 96.7% of the baseline variance (88.2% with original algorithm). CONCLUSIONS: The improved algorithm appears to be effective at harmonizing prevalence rates of child overweight and obesity based on different references. |
format | Online Article Text |
id | pubmed-10078258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100782582023-04-07 An improved algorithm to harmonize child overweight and obesity prevalence rates Cole, Tim J. Lobstein, Tim Pediatr Obes Original Research BACKGROUND: Prevalence rates of child overweight and obesity for a group of children vary depending on the BMI reference and cut‐off used. Previously we developed an algorithm to convert prevalence rates based on one reference to those based on another. OBJECTIVE: To improve the algorithm by combining information on overweight and obesity prevalence. METHODS: The original algorithm assumed that prevalence according to two different cut‐offs A and B differed by a constant amount [Formula: see text] on the z‐score scale. However the results showed that the z‐score difference tended to be greater in the upper tail of the distribution and was better represented by [Formula: see text] , where [Formula: see text] was a constant that varied by group. The improved algorithm uses paired prevalence rates of overweight and obesity to estimate [Formula: see text] for each group. Prevalence based on cut‐off A is then transformed to a z‐score, adjusted up or down according to [Formula: see text] and back‐transformed, and this predicts prevalence based on cut‐off B. The algorithm's performance was tested on 228 groups of children aged 6–17 years from 20 countries. RESULTS: The revised algorithm performed much better than the original. The standard deviation (SD) of residuals, the difference between observed and predicted prevalence, was 0.8% (n = 2320 comparisons), while the SD of the difference between pairs of the original prevalence rates was 4.3%, meaning that the algorithm explained 96.7% of the baseline variance (88.2% with original algorithm). CONCLUSIONS: The improved algorithm appears to be effective at harmonizing prevalence rates of child overweight and obesity based on different references. John Wiley & Sons, Inc. 2022-08-23 2023-01 /pmc/articles/PMC10078258/ /pubmed/35997305 http://dx.doi.org/10.1111/ijpo.12970 Text en © 2022 The Authors. Pediatric Obesity published by John Wiley & Sons Ltd on behalf of World Obesity Federation. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Original Research Cole, Tim J. Lobstein, Tim An improved algorithm to harmonize child overweight and obesity prevalence rates |
title | An improved algorithm to harmonize child overweight and obesity prevalence rates |
title_full | An improved algorithm to harmonize child overweight and obesity prevalence rates |
title_fullStr | An improved algorithm to harmonize child overweight and obesity prevalence rates |
title_full_unstemmed | An improved algorithm to harmonize child overweight and obesity prevalence rates |
title_short | An improved algorithm to harmonize child overweight and obesity prevalence rates |
title_sort | improved algorithm to harmonize child overweight and obesity prevalence rates |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10078258/ https://www.ncbi.nlm.nih.gov/pubmed/35997305 http://dx.doi.org/10.1111/ijpo.12970 |
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