Article

Features of the Metabolic Syndrome predict higher risk of diabetes and impaired glucose tolerance

International Diabetes Institute, Melbourne, Victoria, Australia.
Diabetes Care (Impact Factor: 8.57). 10/2000; 23(9):1242-8. DOI: 10.2337/diacare.23.9.1242
Source: PubMed

ABSTRACT To assess the independent and joint effects of the components of the metabolic syndrome, including leptin, which is a recently proposed addition to this syndrome, in predicting the cumulative incidence of impaired glucose tolerance (IGT) and diabetes among individuals with normal glucose tolerance.
This prospective study involved 2,605 residents of Mauritius with normal glucose tolerance who were followed for 5 years for IGT or diabetes onset in relation to total and regional adiposity (BMI, waist-to-hip ratio [WHR]), fasting and 2-h 75-g oral glucose load glucose and insulin, total and HDL cholesterol, blood pressure, serum uric acid, triglyceride, and leptin levels.
A multivariate logistic regression model adjusted for age, sex, ethnicity, and diabetes family history showed a significantly higher linear increase in risk of IGT and diabetes in association with the following variables only: fasting glucose (odds ratio 1.89 [95% CI 1.51-2.34]), 2-h glucose (1.68 [1.50-1.88]), WHR (1.30 [1.10-1.52]), BMI (1.04 [1.00-1.08]), and serum uric acid (1.37 [1.20-1.57]). However, a nonlinear increase was seen with serum triglyceride and plasma leptin concentrations. No risk factors resulted in joint effects that were greater than expected from combining individual effects.
Metabolic syndrome features independently predict a higher risk of diabetes or IGT in normoglycemic subjects but in combination confer no higher-than-expected risk of these outcomes. At higher concentrations of triglycerides and leptin, risk plateaus and even declines slightly.

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    • "Metabolic syndrome (Mts) is defined by a cluster of metabolic risk factors including: central obesity, hypertension (HT), impaired fasting glucose (IFG) or impaired glucose tolerance (IGT), diabetes mellitus (DM), and dyslipidemia (DLD), which predispose an individual to develop cardiovascular disease and type 2 diabetes [1] [2] [3]. Mts is important because recent advances in science and technology have brought significant changes to the environment, social behaviour and lifestyle. "
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    • "Insulin resistance impairs tissue energy utilization and elicits metabolic derangement during the early phase of atherosclerosis [1] [2]. Metabolic syndrome clusters together and had strong enhancement with the risk of diabetes [3] [4]. Incidences of diabetes increased progressively globally, espe* Corresponding author. "
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    • "ated with incident T2DM in models that included MetS in the San Antonio Heart Study ( Lorenzo et al . 2003 ) , nor were features of MetS in a multi - ethnic sample of residents of Mauritius ( Boyko et al . 2000 ) . Given the above sex differences in the prediction of CVD , but not in all - cause mortality or T2DM , it is apparent that further research is necessary to understand the role of MetS in the aetiology and pathophysiology of each disease . One striking example of this is two analyses from the same co - hort of the Framingham Offspring"
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    ABSTRACT: The metabolic syndrome (MetS) is a cluster of cardiovascular risk factors that are associated with increased risk of diabetes, cardiovascular disease (CVD), and all-cause mortality; however, it is clear that considerable variation exists in these relationships. Given that the prevalence of MetS increases with age, is higher in men than in women, and varies with race and ethnicity, a number of questions about the clinical application of MetS in predicting morbidity and mortality in diverse populations remain unanswered. Thus, in this review, we compare the ability of MetS to predict health risk across age, sex, race, and ethnicity, and in primary versus secondary prevention subgroups to explore these relationships. Furthermore, as there is currently no universal MetS criteria, we also discuss differences in the prediction of morbidity and mortality in studies that used different criteria to define MetS. At present, further research is necessary to examine the health risks associated with (i) different combinations of MetS components in diverse populations, (ii) the relative importance of each MetS component in predicting different health outcomes, and (iii) the independent contribution of MetS in predicting risk of morbidity and mortality beyond that incurred by other risk factors.
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