A Review of Low-Density Lipoprotein-Lowering Diets in the Age of Anti-Sense Technology

This narrative review discusses an important issue, the primary role of diet in reducing low-density lipoprotein cholesterol (LDLc) concentrations in polygenic hypercholesterolemia. Two effective drugs, statins, and ezetimibe, that lower LDLc > 20% are relatively inexpensive and potential competitors to strict dieting. Biochemical and genomic studies have shown that proprotein convertase subtilisin kexin type 9 (PCSK9) plays an important role in low-density lipoprotein (LDL) and lipid metabolism. Clinical trials have demonstrated that inhibitory monoclonal antibodies of PCSK9 dose-dependently lower LDLc up to 60%, with evidence of both regression and stabilization of coronary atherosclerosis and a reduction in cardiovascular risk. Recent approaches using RNA interference to achieve PCSK9 inhibition are currently undergoing clinical evaluation. The latter presents an attractive option of twice-yearly injections. They are, however, currently expensive and unsuitable for moderate hypercholesterolemia, which is largely due to inappropriate patterns of eating. The best dietary approach, the substitution of saturated fatty acids by polyunsaturated fatty acids at 5% energy, yields > 10% lowering of LDLc. Foods such as nuts and brans, especially within a prudent, plant-based diet low in saturates complemented by supplements such as phytosterols, have the potential to reduce LDLc further. A combination of such foods has been shown to lower LDLc by 20%. A nutritional approach requires backing from industry to develop and market LDLc-lowering products before pharmacology replaces the diet option. Energetic support from health professionals is vital.

Using Two Different Approaches to Assess Dietary Patterns: Hypothesis-Driven and Data-Driven Analysis

The use of dietary patterns to assess dietary intake has become increasingly common in nutritional epidemiology studies due to the complexity and multidimensionality of the diet. Currently, two main approaches have been widely used to assess dietary patterns: data-driven and hypothesis-driven analysis. Since the methods explore different angles of dietary intake, using both approaches simultaneously might yield complementary and useful information; thus, we aimed to use both approaches to gain knowledge of adolescents’ dietary patterns. Food intake from a cross-sectional survey with 295 adolescents was assessed by 24 h dietary recall (24HR). In hypothesis-driven analysis, based on the American National Cancer Institute method, the usual intake of Brazilian Healthy Eating Index Revised components were estimated. In the data-driven approach, the usual intake of foods/food groups was estimated by the Multiple Source Method. In the results, hypothesis-driven analysis showed low scores for Whole grains, Total vegetables, Total fruit and Whole fruits), while, in data-driven analysis, fruits and whole grains were not presented in any pattern. High intakes of sodium, fats and sugars were observed in hypothesis-driven analysis with low total scores for Sodium, Saturated fat and SoFAA (calories from solid fat, alcohol and added sugar) components in agreement, while the data-driven approach showed the intake of several foods/food groups rich in these nutrients, such as butter/margarine, cookies, chocolate powder, whole milk, cheese, processed meat/cold cuts and candies. In this study, using both approaches at the same time provided consistent and complementary information with regard to assessing the overall dietary habits that will be important in order to drive public health programs, and improve their efficiency to monitor and evaluate the dietary patterns of populations.