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Waist-to-height ratio and metabolic phenotype compared to the Matsuda index for the prediction of insulin resistance

Current screening algorithms for type 2 diabetes (T2D) rely on fasting plasma glucose (FPG) and/or HbA1c. This fails to identify a sizeable subgroup of individuals in early stages of metabolic dysregulation who are at high risk for developing diabetes or cardiovascular disease. The Matsuda index, a...

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Autores principales: Lechner, Katharina, Lechner, Benjamin, Crispin, Alexander, Schwarz, Peter E. H., von Bibra, Helene
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050044/
https://www.ncbi.nlm.nih.gov/pubmed/33859227
http://dx.doi.org/10.1038/s41598-021-87266-z
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author Lechner, Katharina
Lechner, Benjamin
Crispin, Alexander
Schwarz, Peter E. H.
von Bibra, Helene
author_facet Lechner, Katharina
Lechner, Benjamin
Crispin, Alexander
Schwarz, Peter E. H.
von Bibra, Helene
author_sort Lechner, Katharina
collection PubMed
description Current screening algorithms for type 2 diabetes (T2D) rely on fasting plasma glucose (FPG) and/or HbA1c. This fails to identify a sizeable subgroup of individuals in early stages of metabolic dysregulation who are at high risk for developing diabetes or cardiovascular disease. The Matsuda index, a combination of parameters derived from a fasting and postprandial insulin assay, is an early biomarker for metabolic dysregulation (i.e. insulin resistance/compensatory hyperinsulinemia). The aim of this analysis was to compare four widely available anthropometric and biochemical markers indicative of this condition [waist-to-height ratio (WHtR), hypertriglyceridemic-waist phenotype (HTW), triglycerides-to-HDL-C ratio (TG/HDL-C) and FPG] to the Matsuda index. This cross-sectional analysis included 2231 individuals with normal fasting glucose (NFG, n = 1333), impaired fasting glucose (IFG, n = 599) and T2D (n = 299) from an outpatient diabetes clinic in Germany and thus extended a prior analysis from our group done on the first two subgroups. We analyzed correlations of the Matsuda index with WHtR, HTW, TG/HDL-C and FPG and their predictive accuracies by correlation and logistic regression analyses and receiver operating characteristics. In the entire group and in NFG, IFG and T2D, the best associations were observed between the Matsuda index and the WHtR (r = − 0.458), followed by HTW phenotype (r = − 0.438). As for prediction accuracy, WHtR was superior to HTW, TG/HDL-C and FPG in the entire group (AUC 0.801) and NFG, IFG and T2D. A multivariable risk score for the prediction of insulin resistance was tested and demonstrated an area under the ROC curve of 0.765 for WHtR and its interaction with sex as predictor controlled by age and sex. The predictive power increased to 0.845 when FPG and TG/HDL-C were included. Using as a comparator the Matsuda index, WHtR, compared to HTW, TG/HDL-C and FPG, showed the best predictive value for detecting metabolic dysregulation. We conclude that WHtR, a widely available anthropometric index, could refine phenotypic screening for insulin resistance/hyperinsulinemia. This may ameliorate early identification of individuals who are candidates for appropriate therapeutic interventions aimed at addressing the twin epidemic of metabolic and cardiovascular disease in settings where more extended testing such as insulin assays are not feasible.
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spelling pubmed-80500442021-04-16 Waist-to-height ratio and metabolic phenotype compared to the Matsuda index for the prediction of insulin resistance Lechner, Katharina Lechner, Benjamin Crispin, Alexander Schwarz, Peter E. H. von Bibra, Helene Sci Rep Article Current screening algorithms for type 2 diabetes (T2D) rely on fasting plasma glucose (FPG) and/or HbA1c. This fails to identify a sizeable subgroup of individuals in early stages of metabolic dysregulation who are at high risk for developing diabetes or cardiovascular disease. The Matsuda index, a combination of parameters derived from a fasting and postprandial insulin assay, is an early biomarker for metabolic dysregulation (i.e. insulin resistance/compensatory hyperinsulinemia). The aim of this analysis was to compare four widely available anthropometric and biochemical markers indicative of this condition [waist-to-height ratio (WHtR), hypertriglyceridemic-waist phenotype (HTW), triglycerides-to-HDL-C ratio (TG/HDL-C) and FPG] to the Matsuda index. This cross-sectional analysis included 2231 individuals with normal fasting glucose (NFG, n = 1333), impaired fasting glucose (IFG, n = 599) and T2D (n = 299) from an outpatient diabetes clinic in Germany and thus extended a prior analysis from our group done on the first two subgroups. We analyzed correlations of the Matsuda index with WHtR, HTW, TG/HDL-C and FPG and their predictive accuracies by correlation and logistic regression analyses and receiver operating characteristics. In the entire group and in NFG, IFG and T2D, the best associations were observed between the Matsuda index and the WHtR (r = − 0.458), followed by HTW phenotype (r = − 0.438). As for prediction accuracy, WHtR was superior to HTW, TG/HDL-C and FPG in the entire group (AUC 0.801) and NFG, IFG and T2D. A multivariable risk score for the prediction of insulin resistance was tested and demonstrated an area under the ROC curve of 0.765 for WHtR and its interaction with sex as predictor controlled by age and sex. The predictive power increased to 0.845 when FPG and TG/HDL-C were included. Using as a comparator the Matsuda index, WHtR, compared to HTW, TG/HDL-C and FPG, showed the best predictive value for detecting metabolic dysregulation. We conclude that WHtR, a widely available anthropometric index, could refine phenotypic screening for insulin resistance/hyperinsulinemia. This may ameliorate early identification of individuals who are candidates for appropriate therapeutic interventions aimed at addressing the twin epidemic of metabolic and cardiovascular disease in settings where more extended testing such as insulin assays are not feasible. Nature Publishing Group UK 2021-04-15 /pmc/articles/PMC8050044/ /pubmed/33859227 http://dx.doi.org/10.1038/s41598-021-87266-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Lechner, Katharina
Lechner, Benjamin
Crispin, Alexander
Schwarz, Peter E. H.
von Bibra, Helene
Waist-to-height ratio and metabolic phenotype compared to the Matsuda index for the prediction of insulin resistance
title Waist-to-height ratio and metabolic phenotype compared to the Matsuda index for the prediction of insulin resistance
title_full Waist-to-height ratio and metabolic phenotype compared to the Matsuda index for the prediction of insulin resistance
title_fullStr Waist-to-height ratio and metabolic phenotype compared to the Matsuda index for the prediction of insulin resistance
title_full_unstemmed Waist-to-height ratio and metabolic phenotype compared to the Matsuda index for the prediction of insulin resistance
title_short Waist-to-height ratio and metabolic phenotype compared to the Matsuda index for the prediction of insulin resistance
title_sort waist-to-height ratio and metabolic phenotype compared to the matsuda index for the prediction of insulin resistance
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050044/
https://www.ncbi.nlm.nih.gov/pubmed/33859227
http://dx.doi.org/10.1038/s41598-021-87266-z
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