The aim of this study was to investigate lifestyle habits in health and non-health science students from the University of Split, Croatia, and to evaluate their association with perceived stress and psychological well-being. We surveyed 783 students during February–March 2021. Hierarchical multiple regression analysis was used in the analysis. Health science students spent less time using screens, were sitting less, slept less, but also showed better compliance with the Mediterranean diet compared to non-health science students (10.6% vs. 5.9%). There were no differences in stress and well-being perception between the two study groups. Female gender, lack of sleep, less daily sitting time, anxiety, and lower optimism were associated with higher stress in non-health science students, while anxiousness and more sitting were found to be significant among health students. Well-being among health science students was positively associated with BMI, having had COVID-19, being refreshed after waking up during working days, Mediterranean diet adherence, health perception, optimism, and quality of life, and negatively with TV time and anxiousness. Shorter sleep duration on non-working days, feeling refreshed after waking up on non-working days, higher quality of life and optimism, and lower anxiousness were associated with higher well-being among non-health students. Identifying unhealthy lifestyle habits in students is essential for implementing targeted interventions to better their health outcomes.

This review aims to provide a comprehensive framework for implementing precision sports medicine, integrating genetics, pharmacogenomics, digital health solutions, and multi-omics data. Literature review was conducted using MEDLINE, EMBASE, Web of Science, and Cochrane Library databases (January 2018–April 2024), focusing on precision medicine applications in sports medicine, utilizing key terms including “precision medicine”, “sports medicine”, “genetics”, and “multi-omics”, with forward and backward citation tracking. The review identified key gene variants affecting athletic performance: endurance (AMPD1, PPARGC1A), power (ACTN3, NOS3), strength (PPARG), and injury susceptibility (COL5A1, MMP3), while also examining inherited conditions like cardiomyopathies (MYH7, MYBPC3). Pharmacogenomic guidelines were established for optimizing common sports medications, including NSAIDs (CYP2C9), opioids (CYP2D6), and cardiovascular drugs (SLCO1B1, CYP2C19). Digital health technologies, including wearables and predictive analytics, showed potential for enhanced athlete monitoring and injury prevention, while multi-omics approaches integrated various molecular data to understand exercise capacity and injury predisposition, enabling personalized assessments, training regimens, and therapeutic interventions based on individual biomolecular profiles. This review provides sports medicine professionals with a framework to deliver personalized care tailored to each athlete’s unique profile, promising optimized performance, reduced injury risks, and improved recovery outcomes.

Background: Diabetic retinopathy (DR) is the most common microvascular complication of type 2 diabetes mellitus (T2DM). Catestatin (CST) has been implicated in cardiovascular physiology and autonomic modulation, but its role in diabetic microvascular disease remains unclear. Methods: In this cross-sectional study, serum CST levels were compared between healthy controls (n = 59) and patients with T2DM (n = 91), and further between T2DM patients with (n = 63) and without DR (n = 28). Results: CST levels did not differ between T2DM and healthy controls (16 vs. 14 ng/mL; p = 0.693). Among normotensive individuals, healthy controls had the lowest CST levels (6 ng/mL), whereas normotensive T2DM participants showed significantly higher concentrations (11 ng/mL; p = 0.004). Participants with DR exhibited significantly higher CST than those without DR (14 vs. 10 ng/mL; p = 0.034). In the total cohort, arterial hypertension (AH) was the strongest independent predictor of CST (B = 0.562; p < 0.001). In the multivariable model restricted to T2DM patients, DR emerged as the sole independent determinant of CST (B = 0.251; p = 0.028), whereas AH was no longer significant (p = 0.581). Conclusions: Circulating catestatin levels were not associated with the presence of T2DM itself but were significantly elevated in patients with DR. These findings suggest that CST may reflect microvascular and neurovascular stress rather than metabolic status and could represent a biomarker of diabetic microangiopathy.