Introduction:

young university students face a social dynamics that has generated complex lifestyles and, especially, an imbalance in the intake of macro and micronutrients, characterized by having a high caloric density intake, which results in significant excess of weight. It is unknown if these consumption patterns are related to body composition. This research aimed to determine the relationship between pattern of food consumption and body composition in university students.

Method:

an observational, descriptive, cross-sectional study with a sample of 189 students. Sociodemographic variables obtained by a survey, body composition variables obtained by bioimpedance, and food groups and their categories obtained via a 24-hour reminder method were included. A multinomial logistic regression model was performed to explain body composition according to consumption of food groups.

Results:

statistically significant associations were obtained between food consumption and body composition for visceral fat and consumption of eggs, meats, sausages and grains (p = 0.024), and consumption of sugars with bone mass (p = 0.029) and muscle mass (p = 0.013). The multiple regression model showed that sugar consumption increases the risk of having visceral fat (OR = 2.71), and increases the probability of being classified as an obese person (OR = 2.55). Consumption of eggs, meats, sausages, and grains favors an acceptable percentage of visceral fat (OR = 0.14). The consumption of fruits and vegetables increases the risk of having a high percentage of water (OR = 5.41), and low fat percentage (OR = 3.60).

Conclusions:

the consumption of sugars seems to have a close relationship with variables of body composition such as visceral fat, bone mass, and muscle mass. The consumption of fruits and vegetables was related to a low percentage of fat; however, their consumption is proportionally related to high levels of body water. Studies to establish associations between body composition and food consumption should be carried out taking into account specific intakes in order to establish a more accurate association.

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