Key result
Three distinct health behavior patterns are linked to differences in LDL, BMI, and perceived stress.
Why the study?
Cardiovascular diseases have a rising prevalence in younger populations, but health behavior patterns and their associations with cardiometabolic and psychological risk indicators in Korean college students are not well characterized.
Cross-Sectional (n=417)
p-value: p=<.001
Health behaviors in young adults cluster into distinct patterns that are significantly associated with cardiovascular risk markers like LDL and BMI, highlighting the need for multi-behavioral interventions.
Health behavior patterns may signal cardiometabolic risks in young adults; hypothesis-generating, needs longitudinal studies before any clinical application.
BACKGROUND: Cardiovascular diseases are a leading cause of mortality, with a rising prevalence in younger populations. OBJECTIVE: In this study, we aimed to identify health behavior patterns among Korean college students using latent class analysis and examine associations with cardiometabolic and psychological risk indicators. METHODS: In this cross-sectional study, we evaluated 417 college students aged 19-29 years from the 2022-2023 Korea National Health and Nutrition Examination Survey. Latent class analysis indicators included sleep duration, physical activity, smoking status, binge drinking, and breakfast consumption. Cardiovascular risk indicators were low-density lipoprotein (LDL), high-density lipoprotein, triglycerides, body mass index (BMI), and perceived stress. Differences across latent classes were tested using the Bolck-Croon-Hagenaars method. RESULTS: Three health behavior patterns were identified: regular-sleep-breakfast-consistent (15.0%), physically active/nonsmoking (70.0%), and multiple-risk behavior groups (15.0%). Significant differences across classes were observed for LDL (P < .001), BMI (P < .001), and perceived stress (P = .048). The regular-sleep-breakfast-consistent group had the most favorable profile, with lower BMI and perceived stress. The multiple-risk behavior group had higher BMI and stress. The physically active/nonsmoking group had relatively higher LDL, despite otherwise favorable behaviors. CONCLUSIONS: Health behaviors clustered into distinct patterns and were differentially associated with biological and psychological risk indicators. These findings emphasize considering co-occurring lifestyle behaviors and incorporating objective biomarkers in cardiovascular risk assessment. Interventions targeting multiple behaviors, including sleep and diet, may be more effective than single-behavior approaches. Campus and primary care nurses may implement integrated behavioral screening and brief interventions, supporting early cardiovascular risk prevention in young adults.
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Kim et al. (2026) conducted a cross-sectional in Cardiovascular risk (n=417). Health behavior patterns vs. Other latent classes was evaluated on Cardiovascular risk indicators (LDL, HDL, triglycerides, BMI, and perceived stress) (p=<.001). Three distinct health behavior patterns in Korean college students were significantly associated with differences in LDL (P<.001), BMI (P<.001), and perceived stress (P=.048).
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