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The combination of insulin resistance and visceral adipose tissue estimation improves the performance of metabolic syndrome as a predictor of type 2 diabetes

dc.rights.licensehttp://creativecommons.org/licenses/by/4.0es_MX
dc.creatorNeftali Eduardo Antonio Villaes_MX
dc.creatorOMAR YAXMEHEN BELLO CHAVOLLAes_MX
dc.creatorARSENIO VARGAS VAZQUEZes_MX
dc.creatorROOPA PRAVIN MEHTAes_MX
dc.creatorCARLOS ALBERTO AGUILAR SALINASes_MX
dc.date2020
dc.date.accessioned2021-10-25T23:17:14Z
dc.date.available2021-10-25T23:17:14Z
dc.identifier.urihttp://repositorio.inger.gob.mx/jspui/handle/20.500.12100/17270
dc.descriptionAims To assess the performance of metabolic syndrome as a predictor of type 2 diabetes in a model that also includes both a measure of insulin resistance and a metabolic score for visceral fat, and to propose a novel metabolic syndrome definition. Methods In a prospective Metabolic Syndrome Cohort (n=6143), we evaluated improvements in type 2 diabetes risk prediction using International Diabetes Federation‐defined and Adult Treatment Panel III‐defined metabolic syndrome, after inclusion in the model of updated homeostatic model assessment of insulin resistance and a metabolic score for visceral fat. We also developed a modified metabolic syndrome construct, 'MS‐METS', which used the metabolic score for visceral fat instead of waist circumference to evaluate improved predictive performance for risk of developing type 2 diabetes. Results Participants who had metabolic syndrome as defined by both the Adult Treatment Panel III and the International Diabetes Federation criteria had a higher risk of type 2 diabetes compared to participants who did not meet these criteria. Addition of updated homeostatic model assessment of insulin resistance and metabolic score for visceral fat to both metabolic syndrome definitions increased predictive performance for type 2 diabetes risk. Homeostatic model assessment of insulin resistance was the only additional predictor of type 2 diabetes in participants without metabolic syndrome. Conversely, in participants with metabolic syndrome, the use of the metabolic score for visceral fat was the stronger added predictor for type 2 diabetes. When evaluating participants using the MS‐METS definition we observed the largest improvement in predictive ability for type 2 diabetes risk and a significant reduction in risk overestimation compared to evaluation using metabolic syndrome defined according to the International Diabetes Federation and Adult Treatment Panel III criteria alone. Conclusion Inclusion of updated homeostatic model assessment of insulin resistance and metabolic score for visceral fat increases performance of metabolic syndrome in prediction of type 2 diabetes. Assessment of insulin resistance could be more useful than conventional metabolic syndrome and assessment of visceral adipose tissue could be more useful in people with metabolic syndrome. Metabolic syndrome as defined using our modified MS‐METS construct improved the accuracy of type 2 diabetes prediction.es_MX
dc.formatAdobe PDFes_MX
dc.languageenges_MX
dc.publisherWiley & Diabetes UKes_MX
dc.relationhttps://onlinelibrary.wiley.com/doi/abs/10.1111/dme.14274es_MX
dc.relation.requiresSies_MX
dc.rightsAcceso Abiertoes_MX
dc.sourceDiabetic Medicine (1464-5491) Vol. 37 (2020)es_MX
dc.subjectMEDICINA Y CIENCIAS DE LA SALUDes_MX
dc.subjectCiencias médicases_MX
dc.subjectCiencias clínicases_MX
dc.subjectEnfermedades metabólicases_MX
dc.subjectTrastornos del metabolismo de la glucosaes_MX
dc.subjectDiabetes mellituses_MX
dc.subjectDiabetes mellitus tipo 2es_MX
dc.subjectMetabolic diseaseses_MX
dc.subjectGlucose metabolism disorderses_MX
dc.subjectDiabetes Mellitus, Type 2es_MX
dc.titleThe combination of insulin resistance and visceral adipose tissue estimation improves the performance of metabolic syndrome as a predictor of type 2 diabeteses_MX
dc.typeArtículoes_MX
dc.audienceResearcherses_MX
dc.creator.idCA1343917es_MX
dc.creator.idBECO920925HDFLHM05es_MX
dc.creator.idVAVA940920HGRRZR01es_MX
dc.creator.idMEXR720429MNEHXP03es_MX
dc.creator.idAUSC611116HDFGLR00es_MX
dc.creator.nameIdentifiercaes_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercurpes_MX
dc.creator.nameIdentifiercurpes_MX


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