What predicts the occurrence of the metabolic syndrome in a population-based cohort of adult healthy subjects?
ABSTRACT Metabolic syndrome (MS), the concurrence of hyperglycaemia, dyslipidaemia, hypertension and visceral obesity, increases cardiovascular risk and mortality. Predictors of MS were previously evaluated in patients without the full syndrome, but with some of its traits. This might confound the resulting associations.
The relationship between baseline variables and MS development was evaluated in healthy middle-aged subjects without any MS component at baseline, over a 4.5-year follow-up.
From a population-based cohort of 1658 subjects, 241 individuals showed no MS components and 201 (83.4%) of them participated in a follow-up screening. At baseline, patients who developed the MS (n = 28/201; 13.9%) showed significantly higher Homeostasis Model Assessment-Insulin Resistance score (HOMA-IR) and C-reactive protein (CRP) values, and lower exercise level than subjects who did not. In a multiple logistic regression analysis, after multiple adjustments, the only baseline variable significantly (p < 0.01) associated with the MS was CRP (OR = 4.05; 95% CI 2.23-7.38; p < 0.001). Results did not change after adjusting for weight gain. The area under the receiver-operating curve was 0.83 for CRP after multiple adjustments. The optimal cut-off point of baseline CRP values was 2.1 mg/L, with 86% (95% CI 81-90) sensitivity and 75% (69-81) specificity in predicting the MS. Baseline CRP resulted associated with after-study glucose values in a multiple regression model (beta = 0.14; 0.08-0.20; p < 0.001).
Higher baseline CRP values confer a significant increased risk of developing the MS in healthy subjects, independently of weight gain.
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ABSTRACT: Metabolic syndrome (MetS) is a clustering of cardiovascular risk factors which places individuals at increased risk for cardiovascular morbidity and mortality. In addition to obesity and insulin resistance, inflammation is emerging as a potential etiologic factor of the syndrome. One hypothesis suggests that obesity contributes to insulin resistance through increased production of adipose-derived inflammatory cytokines. Currently, lifestyle change is the first line of treatment for MetS. Only recently, however, have studies begun exploring the effect of lifestyle interventions on the mediation of inflammation in individuals with MetS. This review summarizes the strongest evidence (i.e. randomized controlled trial data) for a role of lifestyle interventions (diet and/or exercise) on the improvement of inflammatory biomarkers in people with MetS. Of six studies assessed, lifestyle interventions were consistently successful at improving the inflammatory and metabolic profiles. Interestingly, improvements in the inflammatory profile were found to be largely independent of obesity. Data currently suggest that alterations in dietary composition may be the most effective lifestyle change, although there is a need for more research in this area.Frontiers in bioscience (Scholar edition) 01/2011; 3:168-77.
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ABSTRACT: Polycystic Ovary Syndrome (PCOS) is a common reproductive endocrine disorder in women that is highly associated with obesity. Whether obesity is intrinsic to the disorder or is a result of different lifestyle and environmental concerns is unclear, however obesity influences the risks of PCOS with respect to fertility complications, pregnancy complications and cardiovascular risk. Polycystic ovary syndrome is known to be associated with insulin resistance in both lean and obese individuals. Insulin resistance in fact is felt to be a key feature in the reproductive and metabolic dysfunction of PCOS. There are numerous studies reporting the benefits of insulin sensitizing therapy, specifically metformin and thiazolidinediones, on the features of PCOS and emerging evidence on the impact of these agents on the risk and management of obesity. Weight loss and maintenance of weight reduction has been seen in women and adolescents treated with metformin therapy. Most studies indicate a synergy of metformin with lifestyle therapy in the general population but there are limited data in PCOS.Current Obesity Reports. 12/2012; 1(4).
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ABSTRACT: Using 24-hour dietary recall data from the National Health and Nutrition Examination Survey 1999 to 2006, the possible link between fruit and vegetable intake and chronic disease risk was assessed. C-reactive protein (CRP), low-density lipoprotein cholesterol, high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG), total cholesterol, and glycosylated hemoglobin were selected as biomarkers for chronic disease risk. It is hypothesized that individuals who consume more fruits and vegetables will have reduced chronic disease risk because of the healthful benefits of these foods. The objective of this study was to examine the relationship between fruit and vegetable consumption on selected biomarkers for chronic disease risk. Although some associations were significant for FPG, HDL-C, and low-density lipoprotein cholesterol in some of the models, no trend was present. After adjusting for demographic factors, socioeconomic factors, lifestyle factors, body mass index, total energy intake, and the presence of at least 1 of our 5 predetermined comorbidities, no associations of reduced or increased risk were observed in any quartiles of combined fruit and vegetable intake. Fruit and vegetable intakes were weakly associated with an increased HDL-C level and decreased FPG, glycosylated hemoglobin, and C-reactive protein levels in some of the models; however, no association was observed in the final model. Because selected biomarkers of future disease risk remained in reference ranges at both high and low intake and no significance was observed in the final model, no protective association was observed between fruit and vegetable intake and biomarkers for chronic disease risk. However, fruit and vegetable consumption is recommended as part of an overall healthy diet and to displace other energy-dense foods for weight maintenance, which can lead to a decrease in future disease risk.Nutrition research 08/2011; 31(8):616-24. · 2.59 Impact Factor