Cargando…

Development and validation of a population based risk algorithm for obesity: The Obesity Population Risk Tool (OPoRT)

BACKGROUND: Given the dramatic rise in the prevalence of obesity, greater focus on prevention is necessary. We sought to develop and validate a population risk tool for obesity to inform prevention efforts. METHODS: We developed the Obesity Population Risk Tool (OPoRT) using the longitudinal Nationa...

Descripción completa

Detalles Bibliográficos
Autores principales: Lebenbaum, Michael, Espin-Garcia, Osvaldo, Li, Yi, Rosella, Laura C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5773177/
https://www.ncbi.nlm.nih.gov/pubmed/29346391
http://dx.doi.org/10.1371/journal.pone.0191169
_version_ 1783293518086668288
author Lebenbaum, Michael
Espin-Garcia, Osvaldo
Li, Yi
Rosella, Laura C.
author_facet Lebenbaum, Michael
Espin-Garcia, Osvaldo
Li, Yi
Rosella, Laura C.
author_sort Lebenbaum, Michael
collection PubMed
description BACKGROUND: Given the dramatic rise in the prevalence of obesity, greater focus on prevention is necessary. We sought to develop and validate a population risk tool for obesity to inform prevention efforts. METHODS: We developed the Obesity Population Risk Tool (OPoRT) using the longitudinal National Population Health Survey and sex-specific Generalized Estimating Equations to predict the 10-year risk of obesity among adults 18 and older. The model was validated using a bootstrap approach accounting for the survey design. Model performance was measured by the Brier statistic, discrimination was measured by the C-statistic, and calibration was assessed using the Hosmer-Lemeshow Goodness of Fit Chi Square (HL χ(2)). RESULTS: Predictive factors included baseline body mass index, age, time and their interactions, smoking status, living arrangements, education, alcohol consumption, physical activity, and ethnicity. OPoRT showed good performance for males and females (Brier 0.118 and 0.095, respectively), excellent discrimination (C statistic ≥ 0.89) and achieved calibration (HL χ(2) <20). CONCLUSION: OPoRT is a valid and reliable algorithm that can be applied to routinely collected survey data to estimate the risk of obesity and identify groups at increased risk of obesity. These results can guide prevention efforts aimed at reducing the population burden of obesity.
format Online
Article
Text
id pubmed-5773177
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-57731772018-01-26 Development and validation of a population based risk algorithm for obesity: The Obesity Population Risk Tool (OPoRT) Lebenbaum, Michael Espin-Garcia, Osvaldo Li, Yi Rosella, Laura C. PLoS One Research Article BACKGROUND: Given the dramatic rise in the prevalence of obesity, greater focus on prevention is necessary. We sought to develop and validate a population risk tool for obesity to inform prevention efforts. METHODS: We developed the Obesity Population Risk Tool (OPoRT) using the longitudinal National Population Health Survey and sex-specific Generalized Estimating Equations to predict the 10-year risk of obesity among adults 18 and older. The model was validated using a bootstrap approach accounting for the survey design. Model performance was measured by the Brier statistic, discrimination was measured by the C-statistic, and calibration was assessed using the Hosmer-Lemeshow Goodness of Fit Chi Square (HL χ(2)). RESULTS: Predictive factors included baseline body mass index, age, time and their interactions, smoking status, living arrangements, education, alcohol consumption, physical activity, and ethnicity. OPoRT showed good performance for males and females (Brier 0.118 and 0.095, respectively), excellent discrimination (C statistic ≥ 0.89) and achieved calibration (HL χ(2) <20). CONCLUSION: OPoRT is a valid and reliable algorithm that can be applied to routinely collected survey data to estimate the risk of obesity and identify groups at increased risk of obesity. These results can guide prevention efforts aimed at reducing the population burden of obesity. Public Library of Science 2018-01-18 /pmc/articles/PMC5773177/ /pubmed/29346391 http://dx.doi.org/10.1371/journal.pone.0191169 Text en © 2018 Lebenbaum et al http://creativecommons.org/licenses/by/4.0/ 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 author and source are credited.
spellingShingle Research Article
Lebenbaum, Michael
Espin-Garcia, Osvaldo
Li, Yi
Rosella, Laura C.
Development and validation of a population based risk algorithm for obesity: The Obesity Population Risk Tool (OPoRT)
title Development and validation of a population based risk algorithm for obesity: The Obesity Population Risk Tool (OPoRT)
title_full Development and validation of a population based risk algorithm for obesity: The Obesity Population Risk Tool (OPoRT)
title_fullStr Development and validation of a population based risk algorithm for obesity: The Obesity Population Risk Tool (OPoRT)
title_full_unstemmed Development and validation of a population based risk algorithm for obesity: The Obesity Population Risk Tool (OPoRT)
title_short Development and validation of a population based risk algorithm for obesity: The Obesity Population Risk Tool (OPoRT)
title_sort development and validation of a population based risk algorithm for obesity: the obesity population risk tool (oport)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5773177/
https://www.ncbi.nlm.nih.gov/pubmed/29346391
http://dx.doi.org/10.1371/journal.pone.0191169
work_keys_str_mv AT lebenbaummichael developmentandvalidationofapopulationbasedriskalgorithmforobesitytheobesitypopulationrisktooloport
AT espingarciaosvaldo developmentandvalidationofapopulationbasedriskalgorithmforobesitytheobesitypopulationrisktooloport
AT liyi developmentandvalidationofapopulationbasedriskalgorithmforobesitytheobesitypopulationrisktooloport
AT rosellalaurac developmentandvalidationofapopulationbasedriskalgorithmforobesitytheobesitypopulationrisktooloport