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      A Novel Visceral Adiposity Index for Prediction of Type 2 Diabetes and Pre-diabetes in Chinese adults: A 5-year prospective study

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          Abstract

          The Chinese visceral adiposity index (CVAI) is a recently developed indicator of visceral adiposity. We investigated the predictive value of the CVAI for the development of dysglycemia (pre-diabetes and type 2 diabetes) and compared its predictive power with that of the Visceral adiposity index (VAI) and various anthropometric indices. This community-based study included 2,383 participants. We assessed the predictive power of adiposity indices by performing univariate and multivariate binary logistic regression analysis and calculating the area under the receiver-operating characteristic (ROC) curve according to their quartiles. Logistic regression analysis showed that individuals in higher CVAI quartiles at baseline were more likely to develop dysglycemia than those in lower CVAI quartiles. The area under the ROC curve for CVAI was significantly higher than that of other adiposity indices. In addition, among the various adiposity indices tested, the CVAI had the greatest Youden index for identifying dysglycemia in both genders. Our data demonstrate that the CVAI is a better predictor of type 2 diabetes and pre-diabetes than the VAI, BMI, waist circumference, waist-to-hip ratio and waist-to-height ratio in Chinese adults.

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          Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation.

          The classification of diabetes mellitus and the tests used for its diagnosis were brought into order by the National Diabetes Data Group of the USA and the second World Health Organization Expert Committee on Diabetes Mellitus in 1979 and 1980. Apart from minor modifications by WHO in 1985, little has been changed since that time. There is however considerable new knowledge regarding the aetiology of different forms of diabetes as well as more information on the predictive value of different blood glucose values for the complications of diabetes. A WHO Consultation has therefore taken place in parallel with a report by an American Diabetes Association Expert Committee to re-examine diagnostic criteria and classification. The present document includes the conclusions of the former and is intended for wide distribution and discussion before final proposals are submitted to WHO for approval. The main changes proposed are as follows. The diagnostic fasting plasma (blood) glucose value has been lowered to > or =7.0 mmol l(-1) (6.1 mmol l(-1)). Impaired Glucose Tolerance (IGT) is changed to allow for the new fasting level. A new category of Impaired Fasting Glycaemia (IFG) is proposed to encompass values which are above normal but below the diagnostic cut-off for diabetes (plasma > or =6.1 to or =5.6 to <6.1 mmol l(-1)). Gestational Diabetes Mellitus (GDM) now includes gestational impaired glucose tolerance as well as the previous GDM. The classification defines both process and stage of the disease. The processes include Type 1, autoimmune and non-autoimmune, with beta-cell destruction; Type 2 with varying degrees of insulin resistance and insulin hyposecretion; Gestational Diabetes Mellitus; and Other Types where the cause is known (e.g. MODY, endocrinopathies). It is anticipated that this group will expand as causes of Type 2 become known. Stages range from normoglycaemia to insulin required for survival. It is hoped that the new classification will allow better classification of individuals and lead to fewer therapeutic misjudgements.
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            Global estimates of the prevalence of diabetes for 2010 and 2030.

            We estimated the number of people worldwide with diabetes for the years 2010 and 2030. Studies from 91 countries were used to calculate age- and sex-specific diabetes prevalences, which were applied to national population estimates, to determine national diabetes prevalences for all 216 countries for 2010 and 2030. Studies were identified using Medline, and contact with all national and regional International Diabetes Federation offices. Studies were included if diabetes prevalence was assessed using a population-based methodology, and was based on World Health Organization or American Diabetes Association diagnostic criteria for at least three separate age-groups within the 20-79 year range. Self-report or registry data were used if blood glucose assessment was not available. The world prevalence of diabetes among adults (aged 20-79 years) will be 6.4%, affecting 285 million adults, in 2010, and will increase to 7.7%, and 439 million adults by 2030. Between 2010 and 2030, there will be a 69% increase in numbers of adults with diabetes in developing countries and a 20% increase in developed countries. These predictions, based on a larger number of studies than previous estimates, indicate a growing burden of diabetes, particularly in developing countries. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.
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              Prevalence and control of diabetes in Chinese adults.

              Noncommunicable chronic diseases have become the leading causes of mortality and disease burden worldwide. To investigate the prevalence of diabetes and glycemic control in the Chinese adult population. Using a complex, multistage, probability sampling design, we conducted a cross-sectional survey in a nationally representative sample of 98,658 Chinese adults in 2010. Plasma glucose and hemoglobin A1c levels were measured after at least a 10-hour overnight fast among all study participants, and a 2-hour oral glucose tolerance test was conducted among participants without a self-reported history of diagnosed diabetes. Diabetes and prediabetes were defined according to the 2010 American Diabetes Association criteria; whereas, a hemoglobin A1c level of <7.0% was considered adequate glycemic control. The overall prevalence of diabetes was estimated to be 11.6% (95% CI, 11.3%-11.8%) in the Chinese adult population. The prevalence among men was 12.1% (95% CI, 11.7%-12.5%) and among women was 11.0% (95% CI, 10.7%-11.4%). The prevalence of previously diagnosed diabetes was estimated to be 3.5% (95% CI, 3.4%-3.6%) in the Chinese population: 3.6% (95% CI, 3.4%-3.8%) in men and 3.4% (95% CI, 3.2%-3.5%) in women. The prevalence of undiagnosed diabetes was 8.1% (95% CI, 7.9%-8.3%) in the Chinese population: 8.5% (95% CI, 8.2%-8.8%) in men and 7.7% (95% CI, 7.4%-8.0%) in women. In addition, the prevalence of prediabetes was estimated to be 50.1% (95% CI, 49.7%-50.6%) in Chinese adults: 52.1% (95% CI, 51.5%-52.7%) in men and 48.1% (95% CI, 47.6%-48.7%) in women. The prevalence of diabetes was higher in older age groups, in urban residents, and in persons living in economically developed regions. Among patients with diabetes, only 25.8% (95% CI, 24.9%-26.8%) received treatment for diabetes, and only 39.7% (95% CI, 37.6%-41.8%) of those treated had adequate glycemic control. The estimated prevalence of diabetes among a representative sample of Chinese adults was 11.6% and the prevalence of prediabetes was 50.1%. Projections based on sample weighting suggest this may represent up to 113.9 million Chinese adults with diabetes and 493.4 million with prediabetes. These findings indicate the importance of diabetes as a public health problem in China.
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                Author and article information

                Contributors
                towzh713@126.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                23 October 2017
                23 October 2017
                2017
                : 7
                : 13784
                Affiliations
                GRID grid.452206.7, The First Affiliated Hospital of Chongqing Medical University, Department of Endocrinology, ; Chongqing, 400016 China
                Article
                14251
                10.1038/s41598-017-14251-w
                5653832
                29062099
                14f29b5a-35c4-4d33-93b1-077afdcb60eb
                © The Author(s) 2017

                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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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                : 8 February 2017
                : 9 October 2017
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