A Fit-Fat Index for Predicting Incident Diabetes in Apparently Healthy Men: A Prospective Cohort Study

dc.contributor.author Sloan, Robert
dc.contributor.author Lee, Duck-Chul
dc.contributor.author Haaland, Benjamin
dc.contributor.author Sawada, Susumu
dc.contributor.author Lee, I-Min
dc.contributor.author Sui, Xuemei
dc.contributor.author Lee, Duck-Chul
dc.contributor.author Ridouane, Yassine
dc.contributor.author Riemenschneider, Falk Muller-
dc.contributor.author Blair, Steven
dc.contributor.department Kinesiology
dc.date 2018-02-19T01:51:14.000
dc.date.accessioned 2020-06-30T05:45:29Z
dc.date.available 2020-06-30T05:45:29Z
dc.date.copyright Fri Jan 01 00:00:00 UTC 2016
dc.date.issued 2016-01-01
dc.description.abstract <p><h3>Background</h3></p> <p>The purpose of this study was to examine the impact of combined cardiorespiratory fitness and waist-to-height ratio in the form of a fit-fat index on incident diabetes risk. Additionally, the independent predictive performance of cardiorespiratory fitness, waist-to-height ratio, and body mass index also were estimated and compared. <h3>Methods</h3></p> <p>This was a prospective cohort study of 10,381 men who had a normal electrocardiogram and no history of major chronic disease at baseline from 1979 to 2005. Random survival forest models and traditional Cox proportional hazards models were used to predict diabetes at 5-, 10-, and 15-year incidence horizons. <h3>Results</h3></p> <p>Overall, 4.8% of the participants developed diabetes. Receiver operating characteristic curve analyses for incidence risk demonstrated good discrimination using random survival forest models across fitness and fatness measures; Cox models were poor to fair. The differences between fitness and fatness measures across horizons were clinically negligible. Smoothed random survival forest estimates demonstrated the impact of each fitness and fatness measure on incident diabetes was intuitive and graded. <h3>Conclusions</h3></p> <p>Although fitness and fatness measures showed a similar discriminative ability in predicting incident diabetes, unique to the study was the ability of the fit-fat index to demonstrate a better indication of incident risk when compared to fitness or fatness alone. A single index combining cardiorespiratory fitness and waist-to-height ratio may be more useful because it can indicate improvements in either or both of the measures.</p>
dc.description.comments <p>This article is published as sloan RA, Haaland BA, Sawada SS, Lee I-Min, Sui X, Lee DC, Ridouane Y, MüllerRiemenschneider F, Blair SN. A fit-fat index for predicting incident diabetes in apparently health men: A prospective cohort study. PLOS ONE. 2016;11(6):e0157703. <a href="http://dx.doi.org/10.1371" target="_blank">10.1371/journal.pone.0157703</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/kin_pubs/21/
dc.identifier.articleid 1018
dc.identifier.contextkey 11020263
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath kin_pubs/21
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/52502
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/kin_pubs/21/2016_LeeDC_FitFatIndex.PDF|||Fri Jan 14 22:33:04 UTC 2022
dc.source.uri 10.1371/journal.pone.0157703
dc.subject.disciplines Biomechanics
dc.subject.disciplines Exercise Science
dc.subject.disciplines Expeditionary Education
dc.subject.disciplines Kinesiology
dc.subject.disciplines Psychology of Movement
dc.title A Fit-Fat Index for Predicting Incident Diabetes in Apparently Healthy Men: A Prospective Cohort Study
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 4b9a255a-7593-4589-b7fa-5bdb5817d9d7
relation.isOrgUnitOfPublication f7b0f2ca-8e43-4084-8a10-75f62e5199dd
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