Effects of Exercise on Fructose-induced Postprandial Lipemia

Background: Cardiovascular Diseases (CVDs) are the leading causes of death in the world and in Brazil. In 2001, 12.45 million deaths on the globe (21% of the total) were caused by some CVD.

Different studies agree that CVDs can be prevented by reducing risk factors, such as: smoking, inadequate diet (high in fat, simple carbohydrates and salt), physical inactivity, obesity, diabetes mellitus (DM), high levels of Lipids in the blood (dyslipidemia) and hyperglycemia even in the absence of a diagnosis of DM.

The composition of modern man's diet has changed drastically with the industrialization of food, resulting in the transition from a diet rich in fibers and complex carbohydrates to one with a high content of sugars and fats. Since the current dietary pattern is characterized by the consumption of three or more meals a day, containing a quantity of fat in the range of 20 to 70 g, individuals spend a large part of the day in the postprandial state, with continuous fluctuation of lipemia Over 18 hours.

Food intake (postprandial state) is the dynamic, unstable response of the body that refers to rapid hormonal and lipoprotein remodeling. It is well established in the literature that high-fat meals (lipid overload) cause an increase in plasma triglycerides. Hypertriglyceridemia and / or elevated triglyceride-rich lipoproteins (LRT) (chylomicrons, VLDL and their remnants) in the postprandial state induces endothelial dysfunction via increased oxidative stress and is an independent risk factor for CVDs. Therefore, Postprandial Lipemia (PPL) is counted as an early marker of atherosclerotic process, metabolic abnormalities and endothelial dysfunction.

High-carbohydrate (CHO) diets may promote increased LDL-c, TG, VLDL and HDL-c reduction, as well as PPL, generating a lipid profile associated with an increased risk of CVDs. This effect appears to be more pronounced with the inclusion of simple carbohydrates (mono and disaccharides), although it also occurs with diets rich in complex carbohydrates (polysaccharides).

High fructose diets (HFDs) are a known model of induction of insulin resistance, dyslipidemia and DM2 in primates and humans. The chronic effect of fructose consumption has been well studied in the last decades due to its connection with obesity, resistance to Insulin, accumulation of visceral fat and dyslipidemia.

Due to the increase in fructose consumption from beverages and processed foods, changes in lifestyle, mainly related to diet and exercise, should be seen as a means of prevention and first form of treatment of CVDs and changes in lipid metabolism.

Acute and chronic aerobic exercise seems to reduce the risk of atherosclerosis and CVD by reducing lipemia (improvement of TG, CT, LDL-c and HDL-c) and endothelial function. In addition, the exercise when performed the previous day has the ability to prevent the increase of PPL after a hyperlipidic meal, regardless of body mass. This effect may be considered a cardiometabolic protection and seems to occur as a result of the increase in lipoprotein lipase (LPL) activity and / or reduction of VLDL secretion in the liver.

As the consumption of fructose is progressively increasing in society and its chronic exposure can generate a phenotypic effect of dyslipidemia and, consequently, the increased risk of CVDs, prevention and treatment strategies should be seen as an important public health issue . Thus, the objective of this study is to understand the effects of exercise on fat metabolism, since there is a lack of robust evidence about the possible cardioprotective and hypolipemic role of the same on HFD.

Methods: The study was characterized as a crossover randomized clinical trial, with a 7 day washout period. The sample was composed of 12 sedentary men, aged between 20 and 40 years. All volunteers who agreed to participate in the study signed a two-way informed consent form (TCLE). The study protocol followed the recommendations of the Helsinki Declaration. Subjects were invited to perform three (3) protocols, in a randomized fashion, with a minimum period of one week interval (washout period). On day 0, they arrived to the laboratory at the end of the day, between 6 and 7pm, to perform 45min of treadmill exercise at 60% of the VO2peak or rest, depending on randomization. Soon after, he received a Standard Meal (SM; 60% carbohydrate, 20% fat, 20% protein) in the laboratory and was instructed to perform a 12-hour fast. On day 1, they arrived at the laboratory between 7 and 8 a.m and were submitted to basal blood collection. Soon after, they received a High Fat Meal (HFM) which consisted of sandwich with cream and cheese, added to the drink rich in FRUCTose (0.5 g / kg) or DEXtrose (isoenergetic). The meals had the same energy and macronutrients (50% fat, 40% carbohydrate and 10% protein) and should be consumed in 10 minutes. Blood samples were collected from 1 to 4 h after the meal consumption to analyze the postprandial parameters. Subsequently the subject was released to perform his daily activities outside the laboratory. On the same day, between 6 pm and 7 pm, the subject returned to the laboratory to remain at rest and receive a SM again and be instructed to perform 12 hours of fasting. On day 2, subjects reached the laboratory between 7 and 8 a.m. and again submitted to baseline blood collection. Soon after, they received HFM with a drink rich in DEXtrose (0.5g / kg). Blood samples were collected from 1 to 4 hours after eating the meal. A 24h food record was done to control subject's diet. Body composition was evaluated before intervention. The data were analyzed using the statistical package IBM SPSS statistics (Statistical Package for Social Sciences) version 20.0 (IBM, USA) for Windows. The distribution of all variables was analyzed using the Shapiro-Wilk test, and the analysis sphericity by the Mauchly test. In cases where the data did not pass the normality tests, the respective nonparametric tests were performed. Data from the experimental groups were treated by two-way ANOVA for repeated measurements (2 x 5). If necessary, the Bonferroni post-hoc was used to identify differences. Incremental and total area under the curve were analyzed by trapezoidal method. The difference between AUC was verified by one-way ANOVA with post-hoc Bonferroni. All results were expressed as mean and standard deviation, or median, where appropriate, and the accepted level of significance was 5%.