Abstract

Aim. The aim of the study was to establish relationships between the body types of 17–23-year-old female students (n = 131) of the University of Tartu and the amount of main nutrients and food energy in their 24- hour menus.
Methods. In the nutritional study, the students were asked to submit 24-hour menus of a regular working day. To analyse the data, the Micro-Nutrica software and a food composition database were used and the content of food energy (kcal), proteins, fats and carbohydrates (g) in individual 24-hour menus was calculated.  The students were also measured anthropometrically according to the classical method of Martin: altogether 32 body measurements and 12 skinfolds were taken. The students were classified into different body types according a 5 SD height-weight classification based on mean height and weight and their standard deviation. Five classes were established (small, medium, large, pyknomorph, leptomorph). The students were grouped into classes according to their individual height and weight. Class averages for the other 29 measurements that showed significant correlations with nutrition, and  for proteins, fats, carbohydrates and food energy intake were calculated. Statistical analysis was performed using the SAS system.
Results. The analysis revealed statistically significant differences between the classes in all body measurements and intake of carbohydrates, fats and food energy per 1 kg of body weight. The indicators of food intake were the highest for the class of small subjects and decreased towards the medium and large classes. Leptomorphs surpassed considerably pycnomorphs. The average  values of body mass index (BMI) did not differ significantly between the classes of small and leptomorphous subjects.
Conclusions. Body mass index characterizes only obesity and can not have the same significance for subjects of different height. Therefore, in nutritional studies, classification of subjects should not be based solely on BMI but body build should be presented in at least a bivariate classification, using either height and weight, or height and BMI.