Prevalence and clustering of health behaviours and the association with socio-demographics and mental well-being in Dutch university students

Prev Med Rep. 2023 Jul 4:35:102307. doi: 10.1016/j.pmedr.2023.102307. eCollection 2023 Oct.

Abstract

The college years represent a vulnerable period for developing health-risk behaviours (e.g., physical inactivity/unhealthy eating habits/substance use/problematic internet use/insufficient sleep). This study examined current health behaviour levels (RQ1), health behaviour classes (RQ2) and between-class differences in socio-demographics (RQ3) and mental well-being (RQ4) among Dutch university students (n = 3771). Participants (Mage = 22.7 (SD = 4.3); 71.2% female/27.3% male/1.5% other) completed an online survey (Oct-Nov 2021). Descriptive statistics (RQ1), Latent Class Analysis (RQ2), and Kruskal-Wallis/Chi-square tests (RQ3-4) were used. RQ1: Prevalence rates suggest that a subsequent proportion of the student sample engages in health-risk behaviours. RQ2: Four classes were identified: class 1 (n = 862) "Licit substance use health-risk group", class 2 (n = 435) "Illicit and licit substance use health-risk group", class 3 (n = 1876) "Health-protective group" and class 4 (n = 598) "Non-substance use health-risk group". RQ3: Class 1 represents relatively more international students and students in a steady relationship. Class 2 represents relatively more older/male/(pre-)master students and students living with roommates/in a steady relationship/with more financial difficulty. Class 3 represents relatively more younger/female students and students living with family/with lower Body Mass Index (BMI)/less financial difficulty. Class 4 represents relatively more younger/non-Western/international/bachelor students and students living with children/single/part of LGBTIQ+ community/with higher BMI. RQ4: Class 3 has significantly higher mental well-being while class 4 has significantly lower mental well-being, relative to the other classes. Above findings provide new insights which can help educational institutes and governments better understand the clustering of students' health behaviours and between-class differences in socio-demographics and mental well-being.

Keywords: Health behaviour; Latent Class Analysis; Mental well-being; Prevention; Socio-demographics; University students.