A calorie-restricted diet with nuts favourably raises plasma high-density lipoprotein-cholesterol in overweight and obese patients with stable coronary heart disease: A randomised controlled trial

Tree Nut and Peanut Consumption and Risk of Cardiovascular Disease: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Cardiovascular disease (CVD) is the leading cause of death globally. Habitual consumption of tree nuts and peanuts is associated with cardioprotective benefits. Food-based dietary guidelines globally recommend nuts as a key component of a healthy diet. This systematic review and meta-analysis were conducted to examine the relationship between tree nut and peanut consumption and risk factors for CVD in randomized controlled trials (RCTs) (PROSPERO: CRD42022309156). MEDLINE, PubMed, CINAHL, and Cochrane Central databases were searched up to 26 September, 2021. All RCT studies that assessed the effects of tree nut or peanut consumption of any dose on CVD risk factors were included. Review Manager software was used to conduct a random effect meta-analysis for CVD outcomes from RCTs. Forest plots were generated for each outcome, between-study heterogeneity was estimated using the I2 test statistic and funnel plots and Egger's test for outcomes with ≥10 strata. The quality assessment used the Health Canada Quality Appraisal Tool, and the certainty of the evidence was assessed using grading of recommendations assessment, development, and evaluation (GRADE). A total of 153 articles describing 139 studies (81 parallel design and 58 cross-over design) were included in the systematic review, with 129 studies in the meta-analysis. The meta-analysis showed a significant decrease for low-density lipoprotein (LDL) cholesterol, total cholesterol (TC), triglycerides (TG), TC:high-density lipoprotein (HDL) cholesterol, LDL cholesterol:HDL cholesterol, and apolipoprotein B (apoB) following nut consumption. However, the quality of evidence was "low" for only 18 intervention studies. The certainty of the body of evidence for TC:HDL cholesterol, LDL cholesterol:HDL cholesterol, and apoB were "moderate" because of inconsistency, for TG were "low," and for LDL cholesterol and TC were "very low" because of inconsistency and the likelihood of publication bias. The findings of this review provide evidence of a combined effect of tree nuts and peanuts on a range of biomarkers to create an overall CVD risk reduction.

Use of machine learning to identify risk factors for coronary artery disease

Coronary artery disease (CAD) is the leading cause of death in both developed and developing nations. The objective of this study was to identify risk factors for coronary artery disease through machine-learning and assess this methodology. A retrospective, cross-sectional cohort study using the publicly available National Health and Nutrition Examination Survey (NHANES) was conducted in patients who completed the demographic, dietary, exercise, and mental health questionnaire and had laboratory and physical exam data. Univariate logistic models, with CAD as the outcome, were used to identify covariates that were associated with CAD. Covariates that had a p<0.0001 on univariate analysis were included within the final machine-learning model. The machine learning model XGBoost was used due to its prevalence within the literature as well as its increased predictive accuracy in healthcare prediction. Model covariates were ranked according to the Cover statistic to identify risk factors for CAD. Shapely Additive Explanations (SHAP) explanations were utilized to visualize the relationship between these potential risk factors and CAD. Of the 7,929 patients that met the inclusion criteria in this study, 4,055 (51%) were female, 2,874 (49%) were male. The mean age was 49.2 (SD = 18.4), with 2,885 (36%) White patients, 2,144 (27%) Black patients, 1,639 (21%) Hispanic patients, and 1,261 (16%) patients of other race. A total of 338 (4.5%) of patients had coronary artery disease. These were fitted into the XGBoost model and an AUROC = 0.89, Sensitivity = 0.85, Specificity = 0.87 were observed (Fig 1). The top four highest ranked features by cover, a measure of the percentage contribution of the covariate to the overall model prediction, were age (Cover = 21.1%), Platelet count (Cover = 5.1%), family history of heart disease (Cover = 4.8%), and Total Cholesterol (Cover = 4.1%). Machine learning models can effectively predict coronary artery disease using demographic, laboratory, physical exam, and lifestyle covariates and identify key risk factors.

Nuts and Metabolic Syndrome: Reducing the Burden of Metabolic Syndrome in Menopause

Menopause imposes a dramatic fall in estrogens, which is followed by an increase in the proportion of fat. The rising androgen/estrogen ratio along the menopause transition favors the accumulation of central fat, which contributes to insulin resistance and a series of concatenated effects, leading to a higher incidence of metabolic syndrome. The modulatory effect of diet on the metabolic syndrome phenotype has been shown for the Mediterranean diet, and nuts are key determinants of these health benefits. This review of the impact of nuts on the risk factors of the metabolic syndrome cluster examined studies—prioritizing meta-analyses and systemic reviews—to summarize the potential benefits of nut ingestion on the risk of metabolic syndrome associated with menopause. Nuts have a general composition profile that includes macronutrients, with a high proportion of unsaturated fat, bioactive compounds, and fiber. The mechanisms set in motion by nuts have shown different levels of efficacy against the disturbances associated with metabolic syndrome, but a beneficial impact on lipids and carbohydrate metabolism, and a potential, but minimal reduction in blood pressure and fat accumulation have been found.

The Effect of Dietary Interventions on Hypertriglyceridemia: From Public Health to Molecular Nutrition Evidence

Approximately 25–50% of the population worldwide exhibits serum triglycerides (TG) (≥150 mg/dL) which are associated with an increased level of highly atherogenic remnant-like particles, non-alcoholic fatty liver disease, and pancreatitis risk. High serum TG levels could be related to cardiovascular disease, which is the most prevalent cause of mortality in Western countries. The etiology of hypertriglyceridemia (HTG) is multifactorial and can be classified as primary and secondary causes. Among the primary causes are genetic disorders. On the other hand, secondary causes of HTG comprise lifestyle factors, medical conditions, and drugs. Among lifestyle changes, adequate diets and nutrition are the initial steps to treat and prevent serum lipid alterations. Dietary intervention for HTG is recommended in order to modify the amount of macronutrients. Macronutrient distribution changes such as fat or protein, low-carbohydrate diets, and caloric restriction seem to be effective strategies in reducing TG levels. Particularly, the Mediterranean diet is the dietary pattern with the most consistent evidence for efficacy in HTG while the use of omega-3 supplements consumption is the dietary component with the highest number of randomized clinical trials (RCT) carried out with effective results on reducing TG. The aim of this review was to provide a better comprehension between human nutrition and lipid metabolism.