Reduction of excessive alcohol consumption still remains a significant challenge to the actions in the scope of public health of European citizens. The aim of this study is to present the prevalence of alcohol consumption and to estimate the occurrence of risky drinking among college students from the Polish, Slovak, Romanian, and Ukrainian parts of the Carpathian Euroregion, taking social contexts into account. The consumption of alcohol was estimated on the basis of the respondents' statements regarding the quantity and frequency of their consumption of beer, wine, and vodka. The study included people from the first year of undergraduate studies. The analysis used the Chi-square independence test and odds ratios (ORs). There were significant differences in the frequency of alcohol consumption, as well as the individual types consumed, among the respondents from the analyzed countries. Of the examined college students, 70% admit to occasional drinking. The pattern of dangerous alcohol consumption occurs in the case of approximately every seventh person. Risky drinking occurs with much greater frequency among male students rather than their female counterparts. In Romania, a very small percentage of female students engage in risky drinking. The analysis did not show statistically significant differences in the frequency of risky drinking between countries. The coexistence of other adverse health behaviors, such as smoking and alcohol abuse, was confirmed.

This study presents mathematical models for predicting VO2max based on a 20 m shuttle run and anthropometric parameters. The research was conducted with data provided by 308 young healthy people (aged 20.6 ± 1.6). The research group includes 154 females (aged 20.3 ± 1.2) and 154 males (aged 20.8 ± 1.8). Twenty-four variables were used to build the models, including one dependent variable and 23 independent variables. The predictive methods of analysis include: the classical model of ordinary least squares (OLS) regression, regularized methods such as ridge regression and Lasso regression, artificial neural networks such as the multilayer perceptron (MLP) and radial basis function (RBF) network. All models were calculated in R software (version 3.5.0, R Foundation for Statistical Computing, Vienna, Austria). The study also involved variable selection methods (Lasso and stepwise regressions) to identify optimum predictors for the analysed study group. In order to compare and choose the best model, leave-one-out cross-validation (LOOCV) was used. The paper presents three types of models: for females, males and the whole group. An analysis has revealed that the models for females ( RMSE C V = 4.07 mL·kg−1·min−1) are characterised by a smaller degree of error as compared to male models ( RMSE C V = 5.30 mL·kg−1·min−1). The model accounting for sex generated an error level of RMSE C V = 4.78 mL·kg−1·min−1.

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Carpathian Euroregion gathers the population of 5 countries, including Poland, Slovakia, Hungary and Romania- the European Union members, as well as Ukraine. Young women are statistically less involved in high-intensity physical activity than young men. The objective of this work was to assess the relation between physical activity of young women aged 18-21 years old and BMI and conditioning factors. The study was conducted between 2010 and 2011 among 2339 women. The Minnesota Leisure Time Physical Activity Questionnarie (MLTPAQ) was applied. It results from the study that 74,2% of young women is considered to have the proper BMI rate (18,5-24,9). As many as 16,2% is considered underweight and almost 10% have higher BMI rate and are overweight. More than one third of respondents did not gain the level of physical activity of 1000 kcal/week, and that is the minimum recommended amount of leisure physical activity time per week. In case of women with low level of physical activity (<1000 kcal), as many as 52% of week activity considered low-intensity activity EEPAlight. The character of changes of the BMI index with reference to the level of physical activity is very similar in the women from towns/cities and the women from villages. An increase of BMI along with the total physical activity was related among all to the increase of free fat mass FFM despite of the level of physical.