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Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study

AIMS/HYPOTHESIS: We compared the ability of genetic (established type 2 diabetes, fasting glucose, 2 h glucose and obesity variants) and modifiable lifestyle (diet, physical activity, smoking, alcohol and education) risk factors to predict incident type 2 diabetes and obesity in a population-based p...

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Autores principales: Poveda, Alaitz, Koivula, Robert W., Ahmad, Shafqat, Barroso, Inês, Hallmans, Göran, Johansson, Ingegerd, Renström, Frida, Franks, Paul W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4742501/
https://www.ncbi.nlm.nih.gov/pubmed/26625858
http://dx.doi.org/10.1007/s00125-015-3818-y
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author Poveda, Alaitz
Koivula, Robert W.
Ahmad, Shafqat
Barroso, Inês
Hallmans, Göran
Johansson, Ingegerd
Renström, Frida
Franks, Paul W.
author_facet Poveda, Alaitz
Koivula, Robert W.
Ahmad, Shafqat
Barroso, Inês
Hallmans, Göran
Johansson, Ingegerd
Renström, Frida
Franks, Paul W.
author_sort Poveda, Alaitz
collection PubMed
description AIMS/HYPOTHESIS: We compared the ability of genetic (established type 2 diabetes, fasting glucose, 2 h glucose and obesity variants) and modifiable lifestyle (diet, physical activity, smoking, alcohol and education) risk factors to predict incident type 2 diabetes and obesity in a population-based prospective cohort of 3,444 Swedish adults studied sequentially at baseline and 10 years later. METHODS: Multivariable logistic regression analyses were used to assess the predictive ability of genetic and lifestyle risk factors on incident obesity and type 2 diabetes by calculating the AUC. RESULTS: The predictive accuracy of lifestyle risk factors was similar to that yielded by genetic information for incident type 2 diabetes (AUC 75% and 74%, respectively) and obesity (AUC 68% and 73%, respectively) in models adjusted for age, age(2) and sex. The addition of genetic information to the lifestyle model significantly improved the prediction of type 2 diabetes (AUC 80%; p = 0.0003) and obesity (AUC 79%; p < 0.0001) and resulted in a net reclassification improvement of 58% for type 2 diabetes and 64% for obesity. CONCLUSIONS/INTERPRETATION: These findings illustrate that lifestyle and genetic information separately provide a similarly high degree of long-range predictive accuracy for obesity and type 2 diabetes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00125-015-3818-y) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
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spelling pubmed-47425012016-02-16 Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study Poveda, Alaitz Koivula, Robert W. Ahmad, Shafqat Barroso, Inês Hallmans, Göran Johansson, Ingegerd Renström, Frida Franks, Paul W. Diabetologia Article AIMS/HYPOTHESIS: We compared the ability of genetic (established type 2 diabetes, fasting glucose, 2 h glucose and obesity variants) and modifiable lifestyle (diet, physical activity, smoking, alcohol and education) risk factors to predict incident type 2 diabetes and obesity in a population-based prospective cohort of 3,444 Swedish adults studied sequentially at baseline and 10 years later. METHODS: Multivariable logistic regression analyses were used to assess the predictive ability of genetic and lifestyle risk factors on incident obesity and type 2 diabetes by calculating the AUC. RESULTS: The predictive accuracy of lifestyle risk factors was similar to that yielded by genetic information for incident type 2 diabetes (AUC 75% and 74%, respectively) and obesity (AUC 68% and 73%, respectively) in models adjusted for age, age(2) and sex. The addition of genetic information to the lifestyle model significantly improved the prediction of type 2 diabetes (AUC 80%; p = 0.0003) and obesity (AUC 79%; p < 0.0001) and resulted in a net reclassification improvement of 58% for type 2 diabetes and 64% for obesity. CONCLUSIONS/INTERPRETATION: These findings illustrate that lifestyle and genetic information separately provide a similarly high degree of long-range predictive accuracy for obesity and type 2 diabetes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00125-015-3818-y) contains peer-reviewed but unedited supplementary material, which is available to authorised users. Springer Berlin Heidelberg 2015-12-01 2016 /pmc/articles/PMC4742501/ /pubmed/26625858 http://dx.doi.org/10.1007/s00125-015-3818-y Text en © The Author(s) 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Poveda, Alaitz
Koivula, Robert W.
Ahmad, Shafqat
Barroso, Inês
Hallmans, Göran
Johansson, Ingegerd
Renström, Frida
Franks, Paul W.
Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study
title Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study
title_full Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study
title_fullStr Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study
title_full_unstemmed Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study
title_short Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study
title_sort innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the glacier study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4742501/
https://www.ncbi.nlm.nih.gov/pubmed/26625858
http://dx.doi.org/10.1007/s00125-015-3818-y
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