@article{discovery10155184,
            year = {2022},
           title = {An improved algorithm to harmonize child overweight and obesity prevalence rates},
       publisher = {WILEY},
         journal = {Pediatric Obesity},
           month = {August},
            note = {{\copyright} 2022 The Authors. Pediatric Obesity published by John Wiley \& Sons Ltd on behalf of World Obesity Federation. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/).},
             url = {https://doi.org/10.1111/ijpo.12970},
          author = {Cole, Tim J and Lobstein, Tim},
        abstract = {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  dz \$\$ dz \$\$  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  b {$\times$} dz \$\$ b{$\backslash$}times dz \$\$  , where  b \$\$ b \$\$  was a constant that varied by group. The improved algorithm uses paired prevalence rates of overweight and obesity to estimate  b \$\$ b \$\$  for each group. Prevalence based on cut-off A is then transformed to a z-score, adjusted up or down according to  b {$\times$} dz \$\$ b{$\backslash$}times dz \$\$  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.},
        keywords = {CDC, harmonization, IOTF, obesity, overweight, prevalence, WHO}
}