Network Meta-analysis of the Therapeutic Effects of Hypoglycemic Drugs and Intensive Lifestyle Modification on Impaired Glucose Tolerance

Postprandial Hyperlipidemia: Its Pathophysiology, Diagnosis, Atherogenesis, and Treatments

Postprandial hyperlipidemia showing postprandial increases in serum triglyceride (TG) is associated with the development of atherosclerotic cardiovascular disease (ASCVD). To diagnose postprandial hyperlipidemia, the oral fat loading test (OFLT) should be performed; however, this test is very time-consuming and is difficult to perform. Elevated serum TG levels reflect an increase in TG-rich lipoproteins (TRLs), such as chylomicrons (CM), very low-density lipoproteins (VLDL), and their remnants (CM remnants [CMRs] and VLDL remnants [VLDLRs]). Understanding of elevation in CMR and/or VLDLR can lead us to understand the existence of postprandial hyperlipidemia. The measurement of apo B48, which is a constituent of CM and CMR; non-fasting TG, which includes TG content in all lipoproteins including CM and CMR; non-high-density lipoprotein cholesterol (non-HDL-C), which includes TRLs and low-density lipoprotein; and remnant cholesterol are useful to reveal the existence of postprandial hyperlipidemia. Postprandial hyperlipidemia is observed in patients with familial type III hyperlipoproteinemia, familial combined hyperlipidemia, chronic kidney disease, metabolic syndrome and type 2 diabetes. Postprandial hyperlipidemia is closely related to postprandial hyperglycemia, and insulin resistance may be an inducing and enhancing factor for both postprandial hyperlipidemia and postprandial hyperglycemia. Remnant lipoproteins and metabolic disorders associated with postprandial hyperlipidemia have various atherogenic properties such as induction of inflammation and endothelial dysfunction. A healthy diet, calorie restriction, weight loss, and exercise positively impact postprandial hyperlipidemia. Anti-hyperlipidemic drugs such pemafibrate, fenofibrate, bezafibrate, ezetimibe, and eicosapentaenoic acid have been shown to improve postprandial hyperlipidemia. Anti-diabetic drugs including metformin, alpha-glucosidase inhibitors, pioglitazone, dipeptidyl-peptidase-4 inhibitors and glucagon-like peptide 1 analogues have been shown to ameliorate postprandial hyperlipidemia. Although sodium glucose cotransporter-2 inhibitors have not been proven to reduce postprandial hyperlipidemia, they reduced fasting apo B48 and remnant lipoprotein cholesterol. In conclusion, it is important to appropriately understand the existence of postprandial hyperlipidemia and to connect it to optimal treatments. However, there are some problems with the diagnosis for postprandial hyperlipidemia. Postprandial hyperlipidemia cannot be specifically defined by measures such as TG levels 2 h after a meal. To study interventions for postprandial hyperlipidemia with the outcome of preventing the onset of ASCVD, it is necessary to define postprandial hyperlipidemia using reference values such as IGT.

Dietary pattern scores in relation to pre-diabetes regression to normal glycemia or progression to type 2 diabetes: a 9-year follow-up

BACKGROUND

We aimed to assess potential associations of habitual dietary pattern scores in relation to the risk of pre-diabetes (Pre-DM) progression to type 2 diabetes mellitus (T2DM) or the chance of returning to normal glycemia.

METHODS

This cohort study included 334 Pre-DM individuals (mean age of 49.4 years, and 51.5% men) who participated in the third phase of the Tehran Lipid and Glucose Study (2006-2008) and followed up for a median of 9 years. A validated food frequency questionnaire at baseline assessed usual intakes of the participants. Major dietary patterns were identified using principal component analysis. The DASH score and Mediterranean diet score (MDS) were also calculated. Multinomial logistic regression analysis was used to estimate the odds ratios (95% confidence intervals (CIs)) of developing T2DM and returning to normal glycemia in relation to dietary pattern scores.

RESULTS

During the study follow-up, 39.8% progressed to T2DM, and 39.8% returned to normal glycemia. Three following major dietary patterns, including Western-style (with a higher load of red meats, hydrogenated fats, sodium, and total fat intakes), healthy pattern (with a higher load of whole grains, vegetables, and dairy products), and processed-foods pattern (with a higher load of processed-meats, fast-foods, salty snakes, and sweets and candies) were identified. The Western-style dietary pattern increased the risk of progressing to T2DM by 38% (OR = 1.38; 95% CI = 1.00 to 1.89, P = 0.050). Other dietary pattern scores were not related to regression or progression from Pre-DM.

CONCLUSION

The Western-style dietary pattern (characterized by higher load of red meats, hydrogenated fats, sodium intake, and high-GI foods) may accelerate the progression of Pre-DM to T2DM.

Study on the Association of Dietary Fatty Acid Intake and Serum Lipid Profiles With Cognition in Aged Subjects With Type 2 Diabetes Mellitus

Background

The correlation between dietary fatty acid (FA) intake and serum lipid profile levels with cognition in the aged population has been reported by previous studies. However, the association of dietary FA intake and serum lipid profile levels with cognition in subjects with type 2 diabetes mellitus (T2DM) is seldom reported.

Objective

A cross-sectional study was conducted to explore the correlation between dietary FA intake and serum lipid profiles with cognition in the aged Chinese population with T2DM.

Methods

A total of 1,526 aged Chinese subjects were recruited from communities. Fasting blood samples were collected for parameter measurement. The food frequency questionnaire (FFQ) method was applied for a dietary survey. Cognition was assessed using the Montreal Cognitive Assessment (MoCA) test. Dietary FA intake and serum lipid levels were compared between subjects with T2DM and control subjects. A logistic regression analysis was carried out for analyzing the association of FA intake and serum lipid levels with the risk of mild cognitive impairment (MCI) in subjects with T2DM and control subjects.

Results

There was a significant difference in the serum lipid level between the T2DM group and the control group. Results of the logistic regression analysis demonstrated the potential associations of serum total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), and dietary n-3 polyunsaturated fatty acids (PUFAs) intake with the risk of MCI in subjects with T2DM, but the associations were not observed in control subjects.

Conclusion

The T2DM phenotype might affect the relationship between dietary FA intake, circulating lipids, and cognitive performance. Large prospective cohort studies are needed to uncover the underlying mechanism of how dietary FA intake and serum lipid levels affect cognition in aged subjects with T2DM.