The study aim was to investigate differences in nutritional, cardiovascular and lifestyle status of ‘health conscious’ subjects. In a partial ‘lock-down’ during the COVID-19 pandemic period, we performed a web-based, cross-sectional study. We compared 80 self-selected subjects (51 vegans, 67% females, and 29 non-vegans, 55% females, p = 0.344). Nutritional status was assessed by bio-electrical impedance and standardized food frequency questionnaires (i.e., contribution of nutrients from foods and supplementation, combined and separate). Serum lipid concentrations and blood pressure (BP) were assessed from annual or initial examination reports, while sociodemographic, economic, and lifestyle statuses were obtained by standardized questionnaires. Finally, a multivariate linear regression model was used to estimate the relationship between total fiber and saturated fatty acid (SFA) intake and low-density lipoprotein cholesterol (LDL cholesterol) values. The vegans had a significantly lower body mass index (22.8 ± 2.4 vs. 26.6 ± 3.6 kg/m², p < 0.001) and body fat % (19.3 ± 7.3 vs. 25.8 ± 8.2%, p < 0.001) than the non-vegans. There were significant differences between vegans and non-vegans in energy intake, and most macronutrient (10/12) and micronutrient (15/23) intakes in units/day. Both diets were well designed, with high fiber and low SFA and free sugar intake but remained insufficient in n-3 long chain polyunsaturated fatty acids (for vegans), vitamin D, calcium, sodium (for vegans) and iodine. Vegans also had a significantly lower lipid profile and BP than non-vegans, except for high-density lipoprotein cholesterol. However, both groups met targeted recommendations. Furthermore, fiber and SFA intake and age explained 47% of the variance in LDL cholesterol. In conclusion, ‘health conscious’ vegans and non-vegans with comparable lifestyle statuses had significant differences in dietary intake, body composition and cardiovascular health status.

Objective. Nutritional status is important for health and competitive achievement. This area remains understudied among elite-level female athletes and is appropriate for research. We examined nutritional status and cardiovascular health markers of two groups of female athletes of the same age and competition period, involved in weight-bearing and a non-weight-bearing sport: gymnasts (n = 17) and swimmers (n = 14); mean age 17.4 and 16.6 years. Methods. Body composition and dietary intake were assessed by bioelectrical impedance and Food Frequency Questionnaire. The concentrations of serum micronutrients (B₁₂, 25-hydroxyvitamin D (25 (OH) D), calcium, magnesium, phosphorus, potassium, and iron), blood lipids, and blood pressure (BP) were measured. Setting and Participants. A cross-sectional study of 31 athletes from Slovenia. Results. Gymnasts had higher body mass index (21.5 vs. 20.1 kg/m², ) and lower fat free mass (42.4 vs. 46.6 kg, ) than swimmers and comparable body fat percentage (22.5 vs. 22.8%). Both groups had low intake of carbohydrates, fibre, polyunsaturated fats, protein (only gymnasts), and micronutrients (11/13 micronutrients gymnasts and 4/13 swimmers) and high intake of free sugars and saturated fats. Both groups also had significantly lower-than-recommended serum levels of 25 (OH) D. All cardiovascular risk factors were within recommended ranges. Gymnasts had higher LDL cholesterol (2.7 vs. 2.2 mmol/L, ), and swimmers had higher systolic BP (126 vs. 107 mmHg, ). Conclusions. Dietary intake especially in gymnasts was suboptimal, which may reflect in anthropometric and cardiovascular marker differences between gymnasts and swimmers.

Purpose: The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.Design/methodology/approach: Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.Findings: The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.Research limitations/implications: The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.Originality/value: The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

The paper studies user-generated evaluations of hotels in three types of destinations in Slovenia (skiing, sea and spa). Using a broad dataset of user-generated evaluations for 28 different hotels and a combination of text mining and standard statistical methods we show how this data provides rich decision-making information. Although numerical evaluations of different destination types can hardly be directly compared due to different guest structure, the results show that guests in general evaluate in their texts primarily the "basics" (room, food/drink, staff). Using a combination of sentiment and novel aspect-based sentiment, hotels can monitor their competitiveness in time, across different types or brands, and use content analysis to further determine sources of competitive advantages in order to enhance performance. The article is the first comprehensive evaluation of Slovenian tourism using on-line peer reviews and provides a toolkit for similar applied analyses.

Autism spectrum disorder (ASD) has been associated with disruptions in tryptophan (TRP) metabolism, affecting the production of key neuroactive metabolites. Investigating these metabolic pathways could yield valuable biomarkers for ASD severity and progression. We included 44 children with ASD and 44 healthy children, members of the same family. The average age in the ASD group was 10.7 years, while the average age in the control group was 9.4 years. Urinary tryptophan metabolites were quantified via liquid chromatography—mass spectrometry operating multiple reaction monitoring (MRM). Urinary creatinine was analyzed on an Advia 2400 analyzer using the Jaffe reaction. Statistical comparisons were made between ASD subgroups based on CARS scores. Our findings indicate that children with ASD have higher TRP concentrations (19.94 vs. 16.91; p = 0.04) than their siblings. Kynurenine (KYN) was found at higher levels in children with ASD compared to children in the control group (82.34 vs. 71.20; p = 0.86), although this difference was not statistically significant. The ASD group showed trends of higher KYN/TRP ratios and altered TRP/ indole-3-acetic acid (IAA) and TRP/5-hydroxyindoleacetic acid (5-HIAA) ratios, correlating with symptom severity. Although the numbers of the two groups were different, our findings suggest that mild and severe illnesses involve separate mechanisms. However, further comprehensive studies are needed to validate these ratios as diagnostic tools for ASD.

Body fat and muscle mass showed opposing associations with mortality. The results of research on the effectiveness of popular body mass (BM) loss diets in obese subjects showed 20 to 30% loss of muscle mass within the total BM loss; conversely, when the subjects used a whole-food, plant-based (WFPB) diet, the loss was up to 42%. Therefore, we suggest an improvement. The aim of this retrospective analysis of data was to examine the assessment of changes in the body composition of 217 participants from all over Slovenia who joined our ongoing, community-based WFPB lifestyle programme from 2016 to 2021 and underwent two successive measurements of medically approved bioelectrical impedance. The WFPB lifestyle programme consisted of (i) nutrition, (ii) physical activity (PA) and (iii) a support system. The primary outcomes included the (vector of) change of body fat mass (BFM) per body height (BH), fat-free mass (FFM) per BH and whole-body phase angle (PhA) from the initial values to the first follow-up (FU) of the whole sample and for both sexes. Further, we examined the FFM change within the total BM loss according to their BMI classification and depending on how much BM they lost (5 kg < BM ≥ 5 kg) within the FU time (103.6 ± 89.8 day). Participants experienced a decrease in BFM per BH (−0.02 ± 0.02 kg/cm, p < 0.001), no change in FFM and an increase in PhA (0.2 ± 0.7°, p < 0.001). Importantly, the participants in the obesity BMI class achieved only partial FFM preservation (−1.5 ± 3.6 kg, p = 0.032 of FFM loss (20%) within −7.5 ± 6.1 kg, p < 0.001 of BM loss). However, the participants who lost BM < 5 kg had a significantly increased FFM (0.8 ± 3.2 kg, p = 0.001 of FFM (57%) within −1.4 ± 1.8 kg, p < 0.001 of BM loss), whereas the participants who lost BM ≥ 5 kg experienced a decrease in FFM (−2.2 ± 3.9 kg, p < 0.001 of FFM (−25%) within −8.8 ± 5.2 kg, p < 0.001 of BM loss). To conclude, the WFPB lifestyle, on average, effectively preserved FFM during BM and/or BFM loss among the normal and pre-obesity BMI classes but only partially among the obese BMI class and those who lost ≥ 5 kg of BM. Importantly, a customized PA strategy is needed for obese BMI class participants, where general resistance training is not possible or safe in order to preserve their muscle mass more effectively. In addition, muscle mass preservation is important for further improvements of BM, body composition and visual body image.