Nutritional status is a series of related parameters collected using different available methods. In order to determine the nutritional status of elderly populations and ensure nutritional support based on an individual approach, the implementation of the increasingly used foodomics approach is available; this approach plays a key role in personalized diets and in the optimization of diets for a population group, such as an elderly population. The Mini Nutritional Assessment (MNA) method and the Nottingham Screening Tool (NST) form were used on 50 users in a home for the elderly in northwest Croatia. A loss of body mass (BM) was statistically significantly higher for those who had the following: decreased food intake in the last week and users who had complete and partial feeding autonomy. Additionally, the obtained data on drug intake, fluid, individual nutrients, and physical activity are based on an individual approach. The available documentation provides insight into nutritional values and food preparation in an attempt to satisfy a holistic approach in the evaluation of exposure while trying to achieve as many elements of foodomics as possible.

Motor skills in students can be developed or improved through regular physical activity such as walking in nature, Nordic walking, hiking, cycling and swimming. This study aimed to examine the relationship between motor skills and various anthropometric and health-related factors, and to appraise any differences in motor performance and body mass index (BMI) on a sample of university students from Croatia. A total of 122 students (73 of them in health programs and 49 in non-health programs) aged 18 to 44 years participated in the study. Motor abilities were evaluated using standardized motor tests, while body composition was assessed via bioelectrical impedance analysis, which measured fat tissue, muscle and bone mass, metabolic age, degree of obesity, total body water, and BMI. While the groups were similar in terms of BMI and weight, students in non-health-related study programs had significantly higher values across a wide array of detailed body composition measures, particularly related to fat and muscle mass. Significant negative correlations were observed between body fat percentage and trunk lift performance (r = −0.55, p < 0.01), as well as between metabolic age and trunk lift performance (r = −0.44, p < 0.01) in health students. In non-health students, the strongest negative correlation was found between body fat percentage and flexibility (r = −0.47, p < 0.01). Higher muscle mass was a positive predictor of motor performance while higher fat mass and metabolic age were significant negative predictors. These findings underscore the impact of body composition on motor performance, particularly strength and flexibility, and highlight the need for targeted preventive strategies among university students. The study supports the implementation of early interventions promoting physical activity and healthy body composition to preserve motor abilities and long-term functional health in this critical age group—especially since lifestyle habits formed during university years tend to persist into adulthood.

Motor skills in students can be developed or improved through regular physical activity such as walking in nature, Nordic walking, hiking, cycling and swimming. This study aimed to examine the relationship between motor skills and various anthropometric and health-related factors, and to appraise any differences in motor performance and body mass index (BMI) on a sample of university students from Croatia. A total of 122 students (73 of them in health programs and 49 in non-health programs) aged 18 to 44 years participated in the study. Motor abilities were evaluated using standardized motor tests, while body composition was assessed via bioelectrical impedance analysis, which measured fat tissue, muscle and bone mass, metabolic age, degree of obesity, total body water, and BMI. While the groups were similar in terms of BMI and weight, students in non-health-related study programs had significantly higher values across a wide array of detailed body composition measures, particularly related to fat and muscle mass. Significant negative correlations were observed between body fat percentage and trunk lift performance (r=–0.547, p<0.01), as well as between metabolic age and trunk lift performance (r=–0.444, p<0.01) in health students. In non-health students, the strongest negative correlation was found between body fat percentage and flexibility (r=–0.467, p<0.01). Multiple linear regression analysis revealed that higher muscle mass was a positive predictor of motor performance (β=0.565, p<0.001), while higher fat mass and metabolic age were significant negative predictors (β=–0.858, p=0.049; β=–0.911, p=0.003, respectively). Students with excessive body weight consistently exhibited higher fat mass, metabolic age, as well as poorer motor outcomes. These findings underscore the impact of body composition on motor performance, particularly strength and flexibility, and highlight the need for targeted preventive strategies among university students. The study supports the implementation of early interventions promoting physical activity and healthy body composition to preserve motor abilities and long-term functional health in this critical age group – especially since lifestyle habits formed during university years tend to persist into adulthood.

The study investigates exposure to stress by respondents working in an Intensive Care Unit (ICU) and differences in using three instruments to measure stress. The survey was conducted from September to October 2018 in Dubrava Clinical Hospital in...

Objective: This study aimed to examine the associations between dietary consumption patterns, physical activity level, and body composition among students of biomedical sciences, and to determine whether dietary consumption patterns and body composition differed according to physical activity level. Methods: A cross-sectional study involved 187 ungraduated university students. The study was conducted among undergraduate physiotherapy students at University North, Varaždin, Croatia, with all measurements performed in the Physiotherapy Laboratory of the Department of Physiotherapy. Assessment of body composition was carried out using Body Composition Analyzer Tanita MC 780, nutritional status using the Food Frequency Questionnaire, and the physical activity using the International Physical Activity Questionnaire-long version. Results: The frequency of consumption of each category of food did not significantly differ between participants, with low, moderate and high levels of physical activity. Weak positive correlations were observed between the frequency of milk and milk product consumption and muscle mass (r = 0.153), and between sugar consumption and body fat (r = 0.189). No statistically significant differences were observed in dietary consumption patterns across physical activity levels or in body composition across physical activity groups. Conclusions: The findings provide descriptive information on dietary patterns, physical activity, and body composition among biomedical sciences students and may help identify areas for future health-promotion interventions and comparative studies in university populations.