Prediction of insulin resistance with anthropometric measures: lessons from a large adolescent population

William K Wedin,1 Lizmer Diaz-Gimenez,1 Antonio J Convit1,21Department of Psychiatry, NYU School of Medicine, New York, NY, USA; 2Nathan Kline Institute, Orangeburg, NY, USAObjective: The aim of this study was to describe the minimum number of anthropometric measures that will optimally predict insu...

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Autores principales:	Wedin WK, Diaz-Gimenez L, Convit AJ
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2012
Materias:	Specialties of internal medicine RC581-951
Acceso en línea:	https://doaj.org/article/055b0123283d41309d9efc9d2660c35d
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spelling	oai:doaj.org-article:055b0123283d41309d9efc9d2660c35d2021-12-02T01:31:26ZPrediction of insulin resistance with anthropometric measures: lessons from a large adolescent population1178-7007https://doaj.org/article/055b0123283d41309d9efc9d2660c35d2012-07-01T00:00:00Zhttp://www.dovepress.com/prediction-of-insulin-resistance-with-anthropometric-measures-lessons--a10476https://doaj.org/toc/1178-7007William K Wedin,1 Lizmer Diaz-Gimenez,1 Antonio J Convit1,21Department of Psychiatry, NYU School of Medicine, New York, NY, USA; 2Nathan Kline Institute, Orangeburg, NY, USAObjective: The aim of this study was to describe the minimum number of anthropometric measures that will optimally predict insulin resistance (IR) and to characterize the utility of these measures among obese and nonobese adolescents.Research design and methods: Six anthropometric measures (selected from three categories: central adiposity, weight, and body composition) were measured from 1298 adolescents attending two New York City public high schools. Body composition was determined by bioelectric impedance analysis (BIA). The homeostatic model assessment of IR (HOMA-IR), based on fasting glucose and insulin concentrations, was used to estimate IR. Stepwise linear regression analyses were performed to predict HOMA-IR based on the six selected measures, while controlling for age.Results: The stepwise regression retained both waist circumference (WC) and percentage of body fat (BF%). Notably, BMI was not retained. WC was a stronger predictor of HOMA-IR than BMI was. A regression model using solely WC performed best among the obese II group, while a model using solely BF% performed best among the lean group. Receiver operator characteristic curves showed the WC and BF% model to be more sensitive in detecting IR than BMI, but with less specificity.Conclusion: WC combined with BF% was the best predictor of HOMA-IR. This finding can be attributed partly to the ability of BF% to model HOMA-IR among leaner participants and to the ability of WC to model HOMA-IR among participants who are more obese. BMI was comparatively weak in predicting IR, suggesting that assessments that are more comprehensive and include body composition analysis could increase detection of IR during adolescence, especially among those who are lean, yet insulin-resistant.Keywords: BMI, bioelectrical impedance analysis, waist circumference, HOMA, insulin resistance, type 2 diabetesWedin WKDiaz-Gimenez LConvit AJDove Medical PressarticleSpecialties of internal medicineRC581-951ENDiabetes, Metabolic Syndrome and Obesity: Targets and Therapy, Vol 2012, Iss default, Pp 219-225 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Specialties of internal medicine RC581-951
spellingShingle	Specialties of internal medicine RC581-951 Wedin WK Diaz-Gimenez L Convit AJ Prediction of insulin resistance with anthropometric measures: lessons from a large adolescent population
description	William K Wedin,1 Lizmer Diaz-Gimenez,1 Antonio J Convit1,21Department of Psychiatry, NYU School of Medicine, New York, NY, USA; 2Nathan Kline Institute, Orangeburg, NY, USAObjective: The aim of this study was to describe the minimum number of anthropometric measures that will optimally predict insulin resistance (IR) and to characterize the utility of these measures among obese and nonobese adolescents.Research design and methods: Six anthropometric measures (selected from three categories: central adiposity, weight, and body composition) were measured from 1298 adolescents attending two New York City public high schools. Body composition was determined by bioelectric impedance analysis (BIA). The homeostatic model assessment of IR (HOMA-IR), based on fasting glucose and insulin concentrations, was used to estimate IR. Stepwise linear regression analyses were performed to predict HOMA-IR based on the six selected measures, while controlling for age.Results: The stepwise regression retained both waist circumference (WC) and percentage of body fat (BF%). Notably, BMI was not retained. WC was a stronger predictor of HOMA-IR than BMI was. A regression model using solely WC performed best among the obese II group, while a model using solely BF% performed best among the lean group. Receiver operator characteristic curves showed the WC and BF% model to be more sensitive in detecting IR than BMI, but with less specificity.Conclusion: WC combined with BF% was the best predictor of HOMA-IR. This finding can be attributed partly to the ability of BF% to model HOMA-IR among leaner participants and to the ability of WC to model HOMA-IR among participants who are more obese. BMI was comparatively weak in predicting IR, suggesting that assessments that are more comprehensive and include body composition analysis could increase detection of IR during adolescence, especially among those who are lean, yet insulin-resistant.Keywords: BMI, bioelectrical impedance analysis, waist circumference, HOMA, insulin resistance, type 2 diabetes
format	article
author	Wedin WK Diaz-Gimenez L Convit AJ
author_facet	Wedin WK Diaz-Gimenez L Convit AJ
author_sort	Wedin WK
title	Prediction of insulin resistance with anthropometric measures: lessons from a large adolescent population
title_short	Prediction of insulin resistance with anthropometric measures: lessons from a large adolescent population
title_full	Prediction of insulin resistance with anthropometric measures: lessons from a large adolescent population
title_fullStr	Prediction of insulin resistance with anthropometric measures: lessons from a large adolescent population
title_full_unstemmed	Prediction of insulin resistance with anthropometric measures: lessons from a large adolescent population
title_sort	prediction of insulin resistance with anthropometric measures: lessons from a large adolescent population
publisher	Dove Medical Press
publishDate	2012
url	https://doaj.org/article/055b0123283d41309d9efc9d2660c35d
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_version_	1718402996201586688

Prediction of insulin resistance with anthropometric measures: lessons from a large adolescent population

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