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Ignoring regression to the mean leads to unsupported conclusion about obesity

Childhood obesity remains a substantial health concern for our population and thoughtful attempts to develop and evaluate the utility of programs to reduce childhood obesity levels are needed. Unfortunately, we believe the conclusion by Burke et al. that the HealthMPowers program produces positive c...

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Autores principales: Skinner, Asheley Cockrell, Heymsfield, Steven B, Pietrobelli, Angelo, Faith, Myles S, Allison, David B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4427929/
https://www.ncbi.nlm.nih.gov/pubmed/25948534
http://dx.doi.org/10.1186/s12966-015-0212-6
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author Skinner, Asheley Cockrell
Heymsfield, Steven B
Pietrobelli, Angelo
Faith, Myles S
Allison, David B
author_facet Skinner, Asheley Cockrell
Heymsfield, Steven B
Pietrobelli, Angelo
Faith, Myles S
Allison, David B
author_sort Skinner, Asheley Cockrell
collection PubMed
description Childhood obesity remains a substantial health concern for our population and thoughtful attempts to develop and evaluate the utility of programs to reduce childhood obesity levels are needed. Unfortunately, we believe the conclusion by Burke et al. that the HealthMPowers program produces positive change in body composition is incorrect because the results obtained are likely due to regression to the mean (RTM), a well-known threat to the validity of studies that is often overlooked. Using empirical data, we demonstrate that RTM is likely to be the cause for the changes reported. A more reasonable conclusion than the one of effectiveness the authors offered would be that the results did not support the effectiveness of the intervention. Public health officials, parents, school leaders, community leaders, and regulators need and deserve valid evidence free from spin on which they can base decisions.
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spelling pubmed-44279292015-05-13 Ignoring regression to the mean leads to unsupported conclusion about obesity Skinner, Asheley Cockrell Heymsfield, Steven B Pietrobelli, Angelo Faith, Myles S Allison, David B Int J Behav Nutr Phys Act Commentary Childhood obesity remains a substantial health concern for our population and thoughtful attempts to develop and evaluate the utility of programs to reduce childhood obesity levels are needed. Unfortunately, we believe the conclusion by Burke et al. that the HealthMPowers program produces positive change in body composition is incorrect because the results obtained are likely due to regression to the mean (RTM), a well-known threat to the validity of studies that is often overlooked. Using empirical data, we demonstrate that RTM is likely to be the cause for the changes reported. A more reasonable conclusion than the one of effectiveness the authors offered would be that the results did not support the effectiveness of the intervention. Public health officials, parents, school leaders, community leaders, and regulators need and deserve valid evidence free from spin on which they can base decisions. BioMed Central 2015-05-07 /pmc/articles/PMC4427929/ /pubmed/25948534 http://dx.doi.org/10.1186/s12966-015-0212-6 Text en © Skinner et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Commentary
Skinner, Asheley Cockrell
Heymsfield, Steven B
Pietrobelli, Angelo
Faith, Myles S
Allison, David B
Ignoring regression to the mean leads to unsupported conclusion about obesity
title Ignoring regression to the mean leads to unsupported conclusion about obesity
title_full Ignoring regression to the mean leads to unsupported conclusion about obesity
title_fullStr Ignoring regression to the mean leads to unsupported conclusion about obesity
title_full_unstemmed Ignoring regression to the mean leads to unsupported conclusion about obesity
title_short Ignoring regression to the mean leads to unsupported conclusion about obesity
title_sort ignoring regression to the mean leads to unsupported conclusion about obesity
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4427929/
https://www.ncbi.nlm.nih.gov/pubmed/25948534
http://dx.doi.org/10.1186/s12966-015-0212-6
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