Double-blind, randomized feedback control fails to improve the hypocholesterolemic effect of a plant-based low-fat diet in patients with moderately elevated total cholesterol levels.

OBJECTIVE: To determine whether the cholesterol-lowering effect of a plant-based low-fat diet can be improved by a flexible control design that controls the extent of fat reduction based on the individual response of blood cholesterol. DESIGN: Randomized, double-blind intervention study. SETTING: A hotel in Prerow, Germany. SUBJECTS: A total of 32 participants (21 female and 11 male participants) with total cholesterol level > 5.7 mmol/l. INTERVENTION: The control group consumed a plant-based low-fat diet with constantly 20% of energy as fat; the intervention group received a diet with either 20 or 15% of energy as fat, depending on the serum cholesterol response of the preceding week. A flexible control design based on the individual cholesterol response during a run-in period of 1 week was used within a low-fat intervention. RESULTS: During the run-in period, the consumption of a plant-based low-fat diet led to a reduction in total cholesterol by 18+/-6 mmol/l (P < 0.001), in LDL cholesterol by 19+/-9 mmol/l (P < 0.001) and triglycerides by 13+/-3 mmol/l (P < 0.001). During the feedback control period, an additional reduction in total cholesterol by 13+/-8 (P < 0.001) and in LDL cholesterol by 17+/-11 (P < 0.001) was observed compared to 15+/-15 and 7+/-18 in the control group. The effect of an additional feedback control was only marginal and not statistically significant compared to the effect of the low-fat diet alone. CONCLUSIONS: On a level of fat intake already reduced to 20% of energy, the use of a feedback control to adapt the fat content of the diet depending on the individual serum cholesterol response was not more effective in reducing blood cholesterol levels than a plant-based low-fat diet alone.

Fuzzy sets and fuzzy decision making in nutrition.

OBJECTIVE: This paper demonstrates that a nutrient intake can be described in a differentiated way and can be evaluated by employing fuzzy decision making. It also examines whether fuzzy decision making can simplify nutrition education by small individual improvements in food selection behaviour. RESULTS: The recommendations for nutrient intakes are presented as fuzzy sets, so that the intake of each nutrient can be evaluated by an objective fuzzy value. The evaluation of the harmonic minimum allows, for the first time, that the fuzzy value of an individual nutrient can be stated as a total value. On the basis of individual nutrition assessment, fuzzy logic in connection with fuzzy decision making, allows optimization of meals considering individual food preferences. This makes it possible in nutrition counselling to improve the nutrient intake markedly with relative small changes in food choice. CONCLUSION: Fuzzy decision making can simplify and optimize nutrition education.

The use of fuzzy logic in nutrition.

Fuzzy logic is a mathematical approach to deal with systems that can not be defined precisely. Nutrient requirements fall into this category. Dietary intakes of nutrients are such that if a nutrient is given in graded amounts, with all other nutrients constant, there is no definitive border where, for example, one intake is deficient and another, slightly higher intake, adequate. Thus, fuzzy sets were developed that describe the range of intakes of a nutrient, ranging from deficiency to excess. On the basis of these fuzzy sets and the known nutrient composition of the food, an index is derived that reflects how closely the diet of an individual meets all the nutrient requirements set by the German Society of Nutrition. Because this is a computer-based system, alterations in the diet are suggested if the diet does not meet requirements. The suggested dietary alterations are usually small but nevertheless allow the diet to meet recommendations. It is important that the suggested alterations be small because the fewer the suggested changes in a diet, the greater the change a person will accept the changes. Thus nutrient intake can be described and evaluated by using fuzzy decision making. This has present applicability in nutrition education and could possibly be used as a tool in determining recommended dietary allowances.

[Evaluation of nutrient intake using fuzzy sets]. / Bewertung der Nährstoffzufuhr durch Fuzzy Sets.

Fuzzy sets are especially suitable to evaluate the intake of a nutrient. For the evaluation of several components, the harmonic mean of the individual fuzzy values proves to be the best compromise. The mean of all nutrients results in the so called Prerow value, which can be used for the evaluation of the nutrition status. Maximizing the Prerow value is suitable for optimizing nutrition.