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      Cumulative increased risk of incident type 2 diabetes mellitus with increasing triglyceride glucose index in normal-weight people: The Rural Chinese Cohort Study

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          Abstract

          Background

          Risk of type 2 diabetes mellitus (T2DM) is increased in metabolically obese but normal-weight people. However, we have limited knowledge of how to prevent T2DM in normal-weight people. We aimed to evaluate the association between triglyceride glucose (TyG) index and incident T2DM among normal-weight people in rural China.

          Methods

          We included data from 5706 people with normal body mass index (BMI) (18.5–23.9 kg/m 2) without baseline T2DM in a rural Chinese cohort followed for a median of 6.0 years. A Cox proportional-hazard model was used to assess the risk of incident T2DM by quartiles of TyG index and difference in TyG index between follow-up and baseline (TyG-D), estimating hazard ratios (HRs) and 95% confidence intervals (CIs). A generalized additive plot was used to show the nonparametric smoothed exposure–response association between risk of T2DM and TyG index as a continuous variable. TyG was calculated as ln [fasting triglyceride level (mg/dl) × fasting plasma glucose level (mg/dl)/2].

          Results

          Risk of incident T2DM was increased with quartiles 2, 3 and 4 versus quartile 1 of TyG index (adjusted HR [aHR] 2.48 [95% CI 1.20–5.11], 3.77 [1.83–7.79], and 5.30 [2.21–12.71], P trend < 0.001 across quartiles of TyG index). Risk of incident T2DM was increased with quartile 4 versus quartile 1 of TyG-D (aHR 3.91 [2.22–6.87]). The results were consistent when analyses were restricted to participants without baseline metabolic syndrome and impaired fasting glucose level. The generalized additive plot showed cumulative increased risk of T2DM with increasing TyG index.

          Conclusions

          Risk of incident T2DM is increased with increasing TyG index among rural Chinese people, so the index might be an important indicator for identifying people at high risk of T2DM.

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          Most cited references36

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          Metabolic and body composition factors in subgroups of obesity: what do we know?

          Obesity is thought to be a heterogeneous disorder with several possible etiologies; therefore, by examining subtypes of obesity we attempt to understand obesity's heterogeneous nature. The purpose of this review was to investigate the roles of metabolic, body composition, and cardiovascular disease risk in subtypes of obesity. We briefly consider two subtypes of obesity that have been identified in the literature. One subset of individuals, termed the metabolically healthy, but obese (MHO), despite having large amounts of fat mass compared with at risk obese individuals shows a normal metabolic profile, but remarkably normal to high levels of insulin sensitivity. Preliminary evidence suggests that this could be due at least in part to lower visceral fat levels and earlier onset of obesity. A second subset, termed the metabolically obese, but normal weight (MONW), present with normal body mass index, but have significant risk factors for diabetes, metabolic syndrome, and cardiovascular disease, which could be due to higher fat mass and plasma triglycerides as well as higher visceral fat and liver content. We also briefly consider the potential role of adipose and gastrointestinal hormonal profiles in MHO and MONW individuals, which could lead to a better understanding of potential factors that may regulate their body composition. This information will eventually be invaluable in helping us understand factors that predispose to or protect obese individuals from metabolic and cardiovascular disease. Collectively, a greater understanding of the MHO and MONW individual has important implications for therapeutic decision making, the characterization of subjects in research protocols, and medical education.
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            Triglyceride Glucose-Body Mass Index Is a Simple and Clinically Useful Surrogate Marker for Insulin Resistance in Nondiabetic Individuals

            Background Insulin resistance (IR) and the consequences of compensatory hyperinsulinemia are pathogenic factors for a set of metabolic abnormalities, which contribute to the development of diabetes mellitus and cardiovascular diseases. We compared traditional lipid levels and ratios and combined them with fasting plasma glucose (FPG) levels or adiposity status for determining their efficiency as independent risk factors for IR. Methods We enrolled 511 Taiwanese individuals for the analysis. The clinical usefulness of various parameters—such as traditional lipid levels and ratios; visceral adiposity indicators, visceral adiposity index (VAI), and lipid accumulation product (LAP); the product of triglyceride (TG) and FPG (the TyG index); TyG with adiposity status (TyG-body mass index [BMI]) and TyG-waist circumference index [WC]); and adipokine levels and ratios—was analyzed to identify IR. Results For all lipid ratios, the TG/high-density lipoprotein cholesterol (HDL-C) ratio had the highest additional percentage of variation in the homeostasis model assessment of insulin resistance (HOMA-IR; 7.0% in total); for all variables of interest, TyG-BMI and leptin-adiponectin ratio (LAR) were strongly associated with HOMA-IR, with 16.6% and 23.2% of variability, respectively. A logistic regression analysis revealed similar patterns. A receiver operating characteristic (ROC) curve analysis indicated that TG/HDL-C was a more efficient IR discriminator than other lipid variables or ratios. The area under the ROC curve (AUC) for VAI (0.734) and TyG (0.708) was larger than that for TG/HDL-C (0.707). TyG-BMI and LAR had the largest AUC (0.801 and 0.801, respectively). Conclusion TyG-BMI is a simple, powerful, and clinically useful surrogate marker for early identification of IR.
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              [Predictive values of body mass index and waist circumference to risk factors of related diseases in Chinese adult population].

              B. Zhou, (2002)
              For prevention of obesity in Chinese population, it is necessary to define the optimal range of healthy weight and the appropriate cut-off points of body mass index (BMI) and waist circumference for Chinese adults. The Working Group on Obesity in China (WGOC) under the support of International Life Sciences Institute Focal point in China organized a meta-analysis on the relation between BMI, waist circumference and risk factors of related chronic diseases. All together 13 population studies met the criteria for enrollment, with data of 239 972 adults (20 - 70 year) surveyed in the 1990s. Data on waist circumference was available for 111 411 persons and data on serum lipids and glucose were available for more than 80 000. The study populations located in 21 provinces, municipalities and autonomous regions in mainland China as well as in Taiwan. Each enrolled study group provided data according to a common protocol and uniform format. The center for data management in the Department of Epidemiology, Fu Wai Hospital was responsible for statistical analysis. The prevalence of hypertension, diabetes, dyslipidemia and clustering of risk factors all increased with increasing levels of BMI or waist circumference. BMI at 24 with best sensitivity and specificity for identification of the risk factors, was recommended as the cut-off point for overweight since and BMI at 28 which might identify the risk factors with specificity around 90% to be recommended as the cut-off point for obesity. Waist circumference beyond 85 cm for men and beyond 80 cm for women were recommended as the cut-off points for central obesity. Analysis of population attributable risk percent illustrated that reducing BMI to normal range ( /= 28) with drugs could prevent 15% - 17% clustering of risk factors. Control the waist circumference under 85 cm for men and under 80 cm for women, could prevent 47% - 58% clustering of risk factors.
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                Author and article information

                Contributors
                zhangming@szu.edu.cn
                wangby95@163.com
                hannahly@szu.edu.cn
                xizhuomd@163.com
                lxp2005@szu.edu.cn
                tjwcj2005@126.com
                lilinlin@zzu.edu.cn
                zhanglu9128@126.com
                ryc12@sina.com
                zhaomiemie@126.com
                zhouzhengmei0913@126.com
                cyhan666666@126.com
                zhao_jingzhi@126.com
                +86-755-86671951 , hud@szu.edu.cn
                Journal
                Cardiovasc Diabetol
                Cardiovasc Diabetol
                Cardiovascular Diabetology
                BioMed Central (London )
                1475-2840
                1 March 2017
                1 March 2017
                2017
                : 16
                : 30
                Affiliations
                [1 ]ISNI 0000 0001 0472 9649, GRID grid.263488.3, Department of Preventive Medicine, , Shenzhen University Health Sciences Center, ; 3688 Nanhai Avenue, Nanshan District, Shenzhen, 518060 Guangdong People’s Republic of China
                [2 ]The Affiliated Luohu Hospital of Shenzhen University Health Sciences Center, Shenzhen, Guangdong People’s Republic of China
                [3 ]ISNI 0000 0001 2189 3846, GRID grid.207374.5, Department of Epidemiology and Health Statistics, College of Public Health, , Zhengzhou University, ; Zhengzhou, Henan People’s Republic of China
                [4 ]Department of Prevention and Health Care, Military Hospital of Henan Province, Zhengzhou, Henan People’s Republic of China
                Article
                514
                10.1186/s12933-017-0514-x
                5333419
                28249577
                f68a2efa-8b4d-4bf8-8dd5-1221423d1994
                © The Author(s) 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 18 December 2016
                : 22 February 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81373074
                Award ID: 81402752
                Award ID: 81673260
                Award Recipient :
                Funded by: Science and Technology Development Foundation of Shenzhen
                Award ID: JCYJ20140418091413562
                Award ID: JCYJ2016030715570
                Award Recipient :
                Categories
                Original Investigation
                Custom metadata
                © The Author(s) 2017

                Endocrinology & Diabetes
                triglyceride glucose index,type 2 diabetes mellitus,normal weight,insulin resistance,cohort study

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