This study investigated lifestyle factors among Hungarian and international students, utilizing lifestyle medicine principles to enhance overall well-being. Conducted at the University of Debrecen through a cross-sectional survey, we examined selected lifestyle factors, more specifically sleep patterns, weight management, nutrition, physical activity, mental well-being, and alcohol use. Hungarian (N = 122) and international (N = 139) students were compared, revealing significant differences. Hungarian students slept less (p = 0.041), desired weight loss (p = 0.040), ate more fruits and vegetables (p = 0.014), exercised longer (p = 0.002), and reported higher purpose and social support (p = 0.009), with higher alcohol use (p < 0.001). These findings highlight distinct experiences and challenges faced by these student groups including variations in sleep, weight management, diet, exercise, and social support. Targeted interventions and tailored support are essential to address their specific needs. To promote the well-being of both Hungarian and international students, educational programs addressing various facets of a healthy lifestyle are crucial. This study offers valuable insights into lifestyle factors and health outcomes among Hungarian and international students and underscores the importance of addressing the unique needs of each group through tailored interventions.

Background: Body mass index (BMI) is commonly used to assess nutritional status; however, it cannot distinguish between fat and lean tissue. In young adults, this limitation may mask excess adiposity and distort diet–adiposity associations. Bioelectrical impedance analysis (BIA) provides more detailed measures, including percent of body fat (PBF), skeletal muscle mass (SMM), and the visceral fat level. Objectives: To examine how combining BMI with BIA-based classifications of adiposity influences the assessment of diet–body composition associations in young adults. Methods: This cross-sectional study of 285 young adults (median age 18 years, IQR: 18–20) used InBody BIA to classify participants by BMI and PBF. Dietary habits were assessed via food frequency questionnaire covering eight food groups. Group comparisons used Mann–Whitney U tests with Cohen’s d effect sizes; correlations used Spearman’s rank correlation. Results: Thirty-five participants (12.3%) were BMI-Normal but PBF-High (normal BMI with elevated body fat), a phenotype missed by BMI screening; overall BMI-PBF agreement was 75.4%. Physical activity (IPAQ) correlated significantly with body composition markers, PBF (rho = −0.177, p = 0.003) and SMM (rho = +0.186, p = 0.002), but not with BMI (rho = +0.060, p = 0.310). BMI showed an inverse association with self-reported sweets consumption (rho = −0.138, p = 0.020), likely reflecting a reporting bias rather than true intake, as this pattern disappeared when examining actual adiposity (PBF: rho = +0.032, p = 0.591). Conclusions: Combining BIA with BMI may improve the detection of elevated body fat (12.3% prevalence of normal BMI with elevated body fat); BMI-based screening may not identify all individuals with elevated body fat. Physical activity associations support the complementary value of BIA alongside BMI. Apparent diet–BMI associations may be confounded by adiposity misclassification and reporting bias.

Background/Objectives: Primary healthcare in Hungary faces acute physician shortages; in the Heves district, eight general practices are permanently vacant, leaving 11,191 residents without continuous care. In September 2025, the Hungarian Charity Service of the Order of Malta launched the Heves Haziorvosi Pilot (HHP), combining on-site nurse triage with remote telemedicine consultations. This study qualitatively evaluated its implementation and early operation. Methods: Three focus group discussions were held in two rounds, before and after implementation, with all 19 professionals delivering the programme (10 practice nurses, 4 general practitioners, 5 degreed professionals). Verbatim Hungarian transcripts were analysed in NVivo 15 (Lumivero, Denver, CO, USA) using the thematic analysis framework of Braun and Clarke with hybrid deductive-inductive coding by three independent researchers until full consensus. Results: Daily physician availability rose from approximately 2 to 8 h, and one remote physician concurrently supported four practices. Participants reported reduced professional isolation among nurses, longer and more focused consultations, and perceived, though unquantified, decreases in non-urgent ambulance use. Implementation was constrained by duplicate paper and digital documentation, patients’ limited familiarity with triage, and unresolved software interoperability and IT ergonomic problems. Conclusions: The hybrid model was perceived as operationally feasible; national scaling would require nursing curriculum reform, administrative simplification, interoperable medical software, and community health literacy programmes.

Background/Objectives: Antimicrobial resistance (AMR) represents one of the most pressing global public health challenges, with inappropriate antibiotic prescribing being a major contributor. In Hungary, general practitioners (GPs) account for over 70% of all antibiotic prescriptions, yet limited research has examined the complex relationship between patient expectations and physician prescribing behavior. This study explores general practitioners’ antibiotic prescribing practices and their perceptions of patient expectations. Methods: A cross-sectional study was conducted among 181 GPs in Hungary from March 2024 to April 2025. The sample is representative of the northeastern region of Hungary. Participants completed anonymous paper-based questionnaires assessing their self-reported professional knowledge, perceived patient expectations, prescribing behavior, and antibiotic stewardship practices. Results: Most respondents recognized antimicrobial resistance as a significant public health issue (81.7%, n = 147); however, only 52.2% (n = 94) felt capable of effectively taking action against it. While 80.6% (n = 145) reported that patients expect antibiotic prescriptions and 71.1% (n = 128) experienced conflicts over prescribing refusals at least once within the previous six months, 87.2% (n = 157) stated they do not yield to patient pressure. Concerning patterns emerged: 56.1% (n = 101) reported completing patient-initiated antibiotic courses, 36.1% (n = 65) admitted to “just-in-case” prescribing at least once within the past six months, and 38.9% (n = 70) encountered self-medication despite regulations restricting antibiotics to prescription-only use. Only 17.8% (n = 32) regularly monitored their antibiotic prescribing indicators. Physicians with multiple specialty qualifications reported less frequent patient education and more conflicts (p = 0.010). Conclusions: General practitioners demonstrate resilience despite substantial patient pressure; however, self-medication and defensive prescribing practices reveal important gaps in antimicrobial stewardship. Targeted, multifaceted interventions addressing both prescriber behavior and systemic vulnerabilities are needed to strengthen stewardship efforts.

The structural integrity of the Hungarian healthcare system is threatened by a systemic shortage of General Practitioners (GPs), with 1021 districts remaining vacant as of March 2026. This study assessed demographic characteristics, perceived career attributes, and temperament and character traits of 144 medical students and 72 practicing GPs, achieving an overall response rate of 91.5%, using the TCI-55 inventory to identify factors influencing professional pathways. Statistical analysis utilized Mann–Whitney U, Chi-square, and Fisher’s exact tests. Results showed only 6 students indicated family medicine as their first choice, compared to 49 GPs (p < 0.001). Students frequently perceived the field as “boring” (82 students vs. 1 GP, p < 0.001) and burdened by “trivial patient problems” (44 students vs. 7 GPs, p = 0.001), while GPs highlighted “stress” (15 GPs vs. 4 students, p < 0.001) as a primary disadvantage. Students scored significantly higher in the temperament dimensions of Novelty Seeking (p < 0.001) and Reward Dependence (p < 0.001). Addressing these educational misperceptions and urgently mitigating the structural drivers of occupational stress and workforce fatigue are critical public health priorities required to ensure the sustainability of primary care, maintain the continuity of preventive services, and safeguard equitable population health outcomes.

Body mass index (BMI) does not capture fat distribution or muscle–fat heterogeneity, so adverse patterns go undetected. We present a methodological framework—not a validated prediction tool—combining three laboratory-free constructs: an Office-Based Framingham cardiovascular risk score, a modified proxy-based FINDRISC, and a direct segmental multi-frequency bioelectrical impedance analysis (DSM-BIA)-derived Metabolically Unhealthy Obesity (MUO) index, with a weighted patient similarity network. We tested six predefined hypotheses in 1684 young adults (mean age 22.5 ± 8.3 years; 50.2% female). Framingham was applied off-label below 30 years, so its outputs give only relative within-cohort ordering; unavailable FINDRISC items were scored zero, so standard FINDRISC categories do not apply. BMI-defined obesity occurred in 6.9%, high visceral fat in 21.7%, high MUO in 21.8%, a BIA-defined TOFI (thin outside, fat inside)-like phenotype in 5.2%, and a sarcopenic-obesity-like phenotype in 9.9%. Visceral fat correlated with percent body fat (r = 0.855). The network resolved nine interpretable communities (modularity Q = 0.63; permutation p = 0.005), including a BIA-defined TOFI-like community (cross-validated AUC = 0.93); k-means, hierarchical, PCA and UMAP clustering recovered convergent axes. All hypotheses were supported, indicating internal construct consistency, not external validation. Laboratory, imaging and longitudinal validation is required before any diagnostic or prognostic claim.