Sodium bicarbonated mineral water decreases postprandial lipaemia in postmenopausal women compared to a low mineral water

The role of bicarbonated mineral waters on lipid metabolism and lipoprotein concentrations in man has scarcely been investigated. The present study aimed to investigate whether drinking sodium bicarbonated mineral water affects postprandial cholesterol and triacylglycerol metabolism in postmenopausal women. In a three-way, randomised, crossover study, eighteen healthy postmenopausal women consumed two sodium bicarbonated mineral waters (bicarbonated mineral water 1 and bicarbonated mineral water 2) and a low mineral water (500 ml of each) with a standard fat-rich meal (4552 kJ; 75.3 g fat). The bicarbonated waters were rich in sodium and bicarbonate and bicarbonated mineral water 1 contained 5.7 times more fluoride than bicarbonated mineral water 2. Fasting blood samples and postprandial blood samples were taken at 30, 60, 120, 240, 360 and 420 min after the end of the meal consumption. Cholesterol and triacylglycerols were determined in serum and chylomicrons. A significant water consumption effect was observed in the total area under the curve (TAUC) of serum and chylomicron triacylglycerols (ANOVA, P=0.008 and P=0.027, respectively). TAUC of serum triacylglycerols for bicarbonated mineral water 2 was significantly lower compared to low mineral water (Bonferroni, P=0.039). Peak concentration of serum triacylglycerols showed a significant water effect (P=0.025). Changes in chylomicron cholesterol were not significantly affected by the type of water. Bicarbonated mineral waters 1 and 2 did not show any significant differences. Drinking sodium bicarbonate-rich mineral waters reduces postprandial lipaemia in healthy postmenopausal women compared to drinking a low mineral water. © The Authors 2005.Peer Reviewe

Does bicarbonated mineral water rich in sodium change insulin sensitivity of postmenopausal women?

Aim: To study the effects of drinking 0.5 L of two sodium-rich bicarbonated mineral waters (BMW-1 and 2), with a standard meal, on postprandial insulin and glucose changes. And to determine, if the effects vary depending on insulin resistance, measured by homeostasis model assessment (HOMA). Methods: In a 3-way randomized crossover study, 18 healthy postmenopausal women consumed two sodiumrich BMWs and a low-mineral water (LMW) with a standard fat-rich meal. Fasting and postprandial blood samples were taken at 30, 60 and 120 min. Serum glucose, insulin, cholesterol and triacylglycerols were determined. Insulin resistance was estimated by HOMA and insulin sensitivity was calculated by quantitative insulin sensitivity check index (QUICKY). Results: Glucose levels did not change. HOMA and QUICKY values were highly inversely correlated (r = -1,000; p < 0.0001). Insulin concentrations showed a significant time effect (p < 0.0001) and a significant water x time interaction (p < 0.021). At 120 min insulin levels with BMW-1 were significantly lower than with LMW (p = 0.022). Postprandial insulin concentrations showed significantly different patterns of mineral water intake depending on HOMA n-tiles (p = 0.016). Conclusion: Results suggests an increase in insulin sensitivity after BMWs consumption. This effect is more marked in the women, who have higher HOMA values. These waters should be considered part of a healthy diet in order to prevent insulin resistance and cardiovascular disease.Peer Reviewe

Atorvastatin versus Bezafibrate in Mixed Hyperlipidaemia : Randomised Clinical Trial of Efficacy and Safety (the ATOMIX Study)

OBJECTIVE: Combined hyperlipidaemia is a common and highly atherogenic lipid phenotype with multiple lipoprotein abnormalities that are difficult to normalise with single-drug therapy. The ATOMIX multicentre, controlled clinical trial compared the efficacy and safety of atorvastatin and bezafibrate in patients with diet-resistant combined hyperlipidaemia. PATIENTS AND STUDY DESIGN: Following a 6-week placebo run-in period, 138 patients received atorvastatin 10mg or bezafibrate 400mg once daily in a randomised, double-blind, placebo-controlled trial. To meet predefined low-density lipoprotein-cholesterol (LDL-C) target levels, atorvastatin dosages were increased to 20mg or 40mg once daily after 8 and 16 weeks, respectively. RESULTS: After 52 weeks, atorvastatin achieved greater reductions in LDL-C than bezafibrate (percentage decrease 35 vs 5; p < 0.0001), while bezafibrate achieved greater reductions in triglyceride than atorvastatin (percentage decrease 33 vs 21; p < 0.05) and greater increases in high-density lipoprotein-cholesterol (HDL-C) [percentage increase 28 vs 17; p < 0.01 ]. Target LDL-C levels (according to global risk) were attained in 62% of atorvastatin recipients and 6% of bezafibrate recipients, and triglyceride levels <200 mg/dL were achieved in 52% and 60% of patients, respectively. In patients with normal baseline HDL-C, bezafibrate was superior to atorvastatin for raising HDL-C, while in those with baseline HDL-C <35 mg/dL, the two drugs raised HDL-C to a similar extent after adjustment for baseline values. Both drugs were well tolerated. CONCLUSION: The results show that atorvastatin has an overall better efficacy than bezafibrate in concomitantly reaching LDL-C and triglyceride target levels in combined hyperlipidaemia, thus supporting its use as monotherapy in patients with this lipid phenotype

Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies

Background Meta-analysis of individual participant time-to-event data from multiple prospective epidemiological studies enables detailed investigation of exposure-risk relationships, but involves a number of analytical challenges. Methods This article describes statistical approaches adopted in the Emerging Risk Factors Collaboration, in which primary data from more than 1 million participants in more than 100 prospective studies have been collated to enable detailed analyses of various risk markers in relation to incident cardiovascular disease outcomes. Results Analyses have been principally based on Cox proportional hazards regression models stratified by sex, undertaken in each study separately. Estimates of exposure-risk relationships, initially unadjusted and then adjusted for several confounders, have been combined over studies using meta-analysis. Methods for assessing the shape of exposure-risk associations and the proportional hazards assumption have been developed. Estimates of interactions have also been combined using meta-analysis, keeping separate within-and between-study information. Regression dilution bias caused by measurement error and within-person variation in exposures and confounders has been addressed through the analysis of repeat measurements to estimate corrected regression coefficients. These methods are exemplified by analysis of plasma fibrinogen and risk of coronary heart disease, and Stata code is made available. Conclusion Increasing numbers of meta-analyses of individual participant data from observational data are being conducted to enhance the statistical power and detail of epidemiological studies. The statistical methods developed here can be used to address the needs of such analyses. © The Author 2010; all rights reserved