Search

Despite growing interest in the protective role that dietary antioxidant vitamins may have in the development of type 2 diabetes (T2D), little epidemiological evidence is available in non-Western populations especially about the possible mediators underlying in this role. The present study aimed to investigate the association of vitamin C and vitamin E intakes with T2D risk in Chinese adults and examine the potential mediators. 178 incident T2D cases among 3483 participants in the Harbin People Health Study (HPHS), and 522 newly diagnosed T2D among 7595 participants in the Harbin Cohort Study on Diet, Nutrition and Chronic Non-communicable Diseases (HDNNCDS) were studied. In the multivariable-adjusted logistics regression model, the relative risks (RRs) were 1.00, 0.75, and 0.76 (Ptrend = 0.003) across tertiles of vitamin C intake in the HDNNCDS, and this association was validated in the HPHS with RRs of 1.00, 0.47, and 0.46 (Ptrend = 0.002). The RRs were 1.00, 0.72, and 0.76 (Ptrend = 0.039) when T2D diagnosed by haemoglobin A1c in the HDNNCDS. The mediation analysis discovered that insulin resistance (indicated by homeostasis model assessment) and oxidative stress (indicated by plasma total antioxidative capacity) partly mediated this association. But no association was evident between vitamin E intake and T2D. In conclusion, our research adds further support to the role of vitamin C intake in reducing the development of T2D in the broader population studied. The results also suggested that this association was partly mediated by inhibiting or ameliorating oxidative stress and insulin resistance.

There is no diabetes risk model that includes dietary predictors in Asia. We sought to develop a diet-containing noninvasive diabetes risk model in Northern China and to evaluate whether dietary predictors can improve model performance and predictive ability. Cross-sectional data for 9,734 adults aged 20-74 years old were used as the derivation data, and results obtained for a cohort of 4,515 adults with 4.2 years of follow-up were used as the validation data. We used a logistic regression model to develop a diet-containing noninvasive risk model. Akaike's information criterion (AIC), area under curve (AUC), integrated discrimination improvements (IDI), net classification improvement (NRI) and calibration statistics were calculated to explicitly assess the effect of dietary predictors on a diabetes risk model. A diet-containing type 2 diabetes risk model was developed. The significant dietary predictors including the consumption of staple foods, livestock, eggs, potato, dairy products, fresh fruit and vegetables were included in the risk model. Dietary predictors improved the noninvasive diabetes risk model with a significant increase in the AUC (delta AUC = 0.03, P

The evidence about the effect of dietary patterns on blood cholesterol from cohort studies was very scarce. The study was to identify the association of dietary patterns with lipid profile, especially cholesterol, in a cohort in north China. Using a 1-year food frequency questionnaire, we assessed the dietary intake of 4515 adults from the Harbin People's Health Study in 2008, aged 20-74 years. Principle component analysis was used to identify dietary patterns. The follow-up was completed in 2012. Fasting blood samples were collected for the determination of blood lipid concentrations. Logistic regression models were used to evaluate the association of dietary patterns with the incidence of hypercholesterolemia, hypertriglyceridemia, and low-HDL cholesterolemia. Five dietary patterns were identified ("staple food", "vegetable, fruit and milk", "potato, soybean and egg", "snack", and "meat"). The relative risk (RR) between the extreme tertiles of the snack dietary pattern scores was 1.72 (95% CI = 1.14, 2.59, P = 0.004) for hypercholesterolemia, 1.39 (1.13, 1.75, P = 0.036) for hypertriglyceridemia, after adjustment for age, sex, education, body mass index, smoking, alcohol consumption, energy intake, exercise and baseline lipid concentrations. There was a significant positive association between the snack dietary pattern scores and fasting serum total cholesterol (SRC (standardized regression coefficient) = 0.262, P = 0.025), LDL-c (SRC = 0.324, P = 0.002) and triglycerides (SRC = 0.253, P = 0.035), after adjustment for the multiple variables above. Moreover, the adjusted RR of hypertriglyceridemia between the extreme tertiles was 0.73 (0.56, 0.94, P = 0.025) for the vegetable, fruit and milk dietary pattern, and 1.86 (1.33, 2.41, P = 0.005) for the meat dietary pattern. The snack dietary pattern was a newly emerged dietary pattern in northern Chinese adults. It appears conceivable that the risk of hypercholesterolemia can be reduced by changing the snack dietary pattern.

Diet and nutrition have been reported to be associated with many common chronic diseases and blood-based assessment would be vital to investigate the association and mechanism, however, blood-based prospective studies are limited. The Harbin Cohort Study on Diet, Nutrition and Chronic Non-communicable Diseases was set up in 2010. From 2010 to 2012, 9,734 participants completed the baseline survey, including demographic characteristics, dietary intake, lifestyles and physical condition, and anthropometrics. A re-survey on 490 randomly selected participants was done by using the same methods which were employed in the baseline survey. For all participants, the mean age was 50 years and 36% of them were men. Approximately 99.4 % of cohort members donated blood samples. The mean total energy intake was 2671.7 kcal/day in men and 2245.9 kcal/day in women, the mean body mass index was 25.7 kg/m2 in men and 24.6 kg/m2 in women, with 18.4% being obese (≥ 28 kg/m2), 12.7% being diabetic, and 29.5% being hypertensive. A good agreement was obtained for the physical measurements between the baseline survey and re-survey. The resources from the cohort and its fasting and postprandial blood samples collected both at baseline and in each follow-up will be valuable and powerful in investigating relationship between diet, nutrition and chronic diseases and discovering novel blood biomarkers and the metabolism of these biomarkers related to chronic diseases.

Mangiferin has been shown to have the effect of improving dyslipidemia. Plasma free fatty acids (FFA) are closely associated with blood lipid metabolism as well as many diseases including metabolic syndrome. This study is to investigate whether mangiferin has effects on FFA metabolism in hyperlipidemic rats. Wistar rats were fed a high-fat diet and administered mangiferin simultaneously for 6 weeks. Mangiferin (50, 100, 150 mg/kg BW) decreased dose-dependently FFA and triglycerides (TG) levels in plasma, and their accumulations in liver, but increased the β-hydroxybutyrate levels in both plasma and liver of hyperlipidemic rats. HepG2 cells were treated with oleic acid (OA, 0.2 mmol/L) to simulate the condition of high level of plasma FFA in vitro, and were treated with different concentrations of mangiferin simultaneously for 24 h. We found that mangiferin significantly increased FFA uptake, significantly decreased intracellular FFA and TG accumulations in HepG2 cells. Mangiferin significantly increased AMP-activated protein kinase (AMPK) phosphorylation and its downstream proteins involved in fatty acid translocase (CD36) and carnitine palmitoyltransferase 1 (CPT1), but significantly decreased acyl-CoA: diacylgycerol acyltransferase 2 (DGAT2) expression and acetyl-CoA carboxylase (ACC) activity by increasing its phosphorylation level in both in vivo and in vitro studies. Furthermore, these effects were reversed by Compound C, an AMPK inhibitor in HepG2 cells. For upstream of AMPK, mangiferin increased AMP/ATP ratio, but had no effect on LKB1 phosphorylation. In conclusion, mangiferin decreased plasma FFA levels through promoting FFA uptake and oxidation, inhibiting FFA and TG accumulations by regulating the key enzymes expression in liver through AMPK pathway. Therefore, mangiferin is a possible beneficial natural compound for metabolic syndrome by improving FFA metabolism.