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Associations of Trunk Fat Depots with Insulin Resistance, β Cell Function and Glycaemia - A Multiple Technique Study

OBJECTIVE: Central (truncal) adiposity is associated strongly with insulin resistance and diabetes. There are very few reports comparing methods of trunk fat measurement in their ability to predict glycaemia and insulin resistance. We report a comparative analysis of different trunk fat measurements...

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Detalles Bibliográficos
Autores principales: Ganpule-Rao, Anjali, Joglekar, Charudatta, Patkar, Deepak, Chinchwadkar, Manoj, Bhat, Dattatreya, Lubree, Himangi, Rege, Sonali, Uradey, Bhagyashree, Yajnik, Chittaranjan, Yudkin, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3792935/
https://www.ncbi.nlm.nih.gov/pubmed/24116041
http://dx.doi.org/10.1371/journal.pone.0075391
Descripción
Sumario:OBJECTIVE: Central (truncal) adiposity is associated strongly with insulin resistance and diabetes. There are very few reports comparing methods of trunk fat measurement in their ability to predict glycaemia and insulin resistance. We report a comparative analysis of different trunk fat measurements in predicting glycaemia and insulin resistance in middle aged Indian men. MATERIALS AND METHODS: Trunk fat measurements were performed using anthropometry, magnetic resonance imaging (MRI), dual-energy X-ray absorptiometry (DXA) and computed tomography (CT) on 128 men. Additional measurements were taken to characterise insulin resistance (Matsuda index) and beta cell function (Insulinogenic Index), glycaemia (fasting and 120 min glucose concentrations). Using residual approach we compared the ability of different trunk fat measurement techniques to predict insulin resistance, beta cell function and glycaemia. RESULTS: There was a strong association between trunk fat measures from each technique with glycaemia and insulin resistance indices but not with the Insulinogenic Index. Insulin resistance and glycaemia, were best predicted using anthropometric measurements, notably by waist circumference and subscapular skinfold thickness. Neither MRI measures of trunk or visceral fat nor DXA trunk fat added significantly. CT liver density contributed to some extent to predict insulin resistance and 120 min glucose after anthropometric measurements. CONCLUSIONS: Our results suggest that, in Indian men, anthropometric measurements are good predictors of glycaemia and insulin resistance. Other complex measurements such as MRI, DXA and CT make only a small addition to the prediction. This finding supports the application of anthropometry for determining trunk fat in clinical and epidemiological settings.