Background: Health-related behaviors often cluster during young adulthood, potentially increasing the risk of long-term adverse health outcomes. Understanding how lifestyle risk behaviors co-occur among university students is essential for developing targeted health promotion strategies. Objective: This study aimed to identify lifestyle risk profiles among university students based on the co-occurrence of smoking behavior, alcohol consumption, sedentary behavior, and body weight status. Methods: A cross-sectional study was conducted with 147 university students enrolled in a physical education and sport undergraduate program (mean age: 20.58 ± 2.94 years; 80.3% male). Physical activity and sedentary behavior were assessed using the International Physical Activity Questionnaire–Short Form (IPAQ-SF), while smoking and alcohol consumption were self-reported. Body mass index was used to classify weight status. Lifestyle risk profiles were identified using two-step cluster analysis based on regular smoking, alcohol consumption, sedentary behavior, and overweight/obesity. Differences in cluster distribution according to sex and federated athlete status were examined using chi-square tests. A two-step cluster analysis based on the Bayesian Information Criterion (BIC) and silhouette measure was used to identify lifestyle risk profiles. Results: Overall, 46.9% of participants had experimented with tobacco, 11.6% were current smokers, and 74.8% reported alcohol consumption. Participants accumulated an average of 3772.25 ± 1957.99 MET-min/week of physical activity. Three distinct lifestyle risk profiles were identified. Cluster 1 (46.9%), labeled the alcohol profile, was characterized by alcohol consumption without smoking and no prevalence of being overweight. Cluster 2 (20.4%), the multiple-risk profile, included participants who reported regular smoking, with nearly half presenting sedentary behavior and overweight/obesity. Cluster 3 (32.7%), the overweight profile, was characterized by overweight/obesity combined with alcohol consumption but no smoking. No significant differences were observed in the distribution of lifestyle profiles according to sex (p = 0.111) or federated athlete status (p = 0.087). Conclusions: Lifestyle risk behaviors cluster into distinct profiles among university students, with alcohol consumption appearing across multiple profiles and smoking concentrated in a specific high-risk group. These findings highlight the need for targeted health promotion strategies addressing multiple co-occurring behaviors within university populations.
Santos et al. (2026) studied this question.