Waist circumference adjusted for body mass index and intra-abdominal fat mass.

<h4>Background</h4>The association between waist circumference (WC) and mortality is particularly strong and direct when adjusted for body mass index (BMI). One conceivable explanation for this association is that WC adjusted for BMI is a better predictor of the presumably most harmful i...

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Autores principales: Tina Landsvig Berentzen, Lars Ängquist, Anna Kotronen, Ronald Borra, Hannele Yki-Järvinen, Patricia Iozzo, Riitta Parkkola, Pirjo Nuutila, Robert Ross, David B Allison, Steven B Heymsfield, Kim Overvad, Thorkild I A Sørensen, Marianne Uhre Jakobsen
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Publicado: Public Library of Science (PLoS) 2012
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spelling oai:doaj.org-article:5fcc11e265054ad0aadab2d3128efd732021-11-18T07:26:48ZWaist circumference adjusted for body mass index and intra-abdominal fat mass.1932-620310.1371/journal.pone.0032213https://doaj.org/article/5fcc11e265054ad0aadab2d3128efd732012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22384179/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>The association between waist circumference (WC) and mortality is particularly strong and direct when adjusted for body mass index (BMI). One conceivable explanation for this association is that WC adjusted for BMI is a better predictor of the presumably most harmful intra-abdominal fat mass (IAFM) than WC alone. We studied the prediction of abdominal subcutaneous fat mass (ASFM) and IAFM by WC alone and by addition of BMI as an explanatory factor.<h4>Methodology/principal findings</h4>WC, BMI and magnetic resonance imaging data from 742 men and women who participated in clinical studies in Canada and Finland were pooled. Total adjusted squared multiple correlation coefficients (R(2)) of ASFM and IAFM were calculated from multiple linear regression models with WC and BMI as explanatory variables. Mean BMI and WC of the participants in the pooled sample were 30 kg/m(2) and 102 cm, respectively. WC explained 29% of the variance in ASFM and 51% of the variance in IAFM. Addition of BMI to WC added 28% to the variance explained in ASFM, but only 1% to the variance explained in IAFM. Results in subgroups stratified by study center, sex, age, obesity level and type 2 diabetes status were not systematically different.<h4>Conclusion/significance</h4>The prediction of IAFM by WC is not improved by addition of BMI.Tina Landsvig BerentzenLars ÄngquistAnna KotronenRonald BorraHannele Yki-JärvinenPatricia IozzoRiitta ParkkolaPirjo NuutilaRobert RossDavid B AllisonSteven B HeymsfieldKim OvervadThorkild I A SørensenMarianne Uhre JakobsenPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 2, p e32213 (2012)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Tina Landsvig Berentzen
Lars Ängquist
Anna Kotronen
Ronald Borra
Hannele Yki-Järvinen
Patricia Iozzo
Riitta Parkkola
Pirjo Nuutila
Robert Ross
David B Allison
Steven B Heymsfield
Kim Overvad
Thorkild I A Sørensen
Marianne Uhre Jakobsen
Waist circumference adjusted for body mass index and intra-abdominal fat mass.
description <h4>Background</h4>The association between waist circumference (WC) and mortality is particularly strong and direct when adjusted for body mass index (BMI). One conceivable explanation for this association is that WC adjusted for BMI is a better predictor of the presumably most harmful intra-abdominal fat mass (IAFM) than WC alone. We studied the prediction of abdominal subcutaneous fat mass (ASFM) and IAFM by WC alone and by addition of BMI as an explanatory factor.<h4>Methodology/principal findings</h4>WC, BMI and magnetic resonance imaging data from 742 men and women who participated in clinical studies in Canada and Finland were pooled. Total adjusted squared multiple correlation coefficients (R(2)) of ASFM and IAFM were calculated from multiple linear regression models with WC and BMI as explanatory variables. Mean BMI and WC of the participants in the pooled sample were 30 kg/m(2) and 102 cm, respectively. WC explained 29% of the variance in ASFM and 51% of the variance in IAFM. Addition of BMI to WC added 28% to the variance explained in ASFM, but only 1% to the variance explained in IAFM. Results in subgroups stratified by study center, sex, age, obesity level and type 2 diabetes status were not systematically different.<h4>Conclusion/significance</h4>The prediction of IAFM by WC is not improved by addition of BMI.
format article
author Tina Landsvig Berentzen
Lars Ängquist
Anna Kotronen
Ronald Borra
Hannele Yki-Järvinen
Patricia Iozzo
Riitta Parkkola
Pirjo Nuutila
Robert Ross
David B Allison
Steven B Heymsfield
Kim Overvad
Thorkild I A Sørensen
Marianne Uhre Jakobsen
author_facet Tina Landsvig Berentzen
Lars Ängquist
Anna Kotronen
Ronald Borra
Hannele Yki-Järvinen
Patricia Iozzo
Riitta Parkkola
Pirjo Nuutila
Robert Ross
David B Allison
Steven B Heymsfield
Kim Overvad
Thorkild I A Sørensen
Marianne Uhre Jakobsen
author_sort Tina Landsvig Berentzen
title Waist circumference adjusted for body mass index and intra-abdominal fat mass.
title_short Waist circumference adjusted for body mass index and intra-abdominal fat mass.
title_full Waist circumference adjusted for body mass index and intra-abdominal fat mass.
title_fullStr Waist circumference adjusted for body mass index and intra-abdominal fat mass.
title_full_unstemmed Waist circumference adjusted for body mass index and intra-abdominal fat mass.
title_sort waist circumference adjusted for body mass index and intra-abdominal fat mass.
publisher Public Library of Science (PLoS)
publishDate 2012
url https://doaj.org/article/5fcc11e265054ad0aadab2d3128efd73
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