Latent Class Analysis of Multiple Health Risk Behaviors among Australian University Students and Associations with Psychological Distress

Abstract

University students have high rates of health risk behaviors and psychological distress. This study explores patterns of health behaviors among a sample of Australian university students, and determines whether patterns of health behaviors are associated with psychological distress and demographic characteristics. Cross-sectional data from the University of Newcastle Student Healthy Lifestyle Survey 2019 were analyzed. Fruit and vegetable intake, sugar-sweetened beverage intake, physical activity, sitting time, smoking, alcohol intake, drug use, sleep and psychological distress were assessed. Latent class analysis (LCA) was used to identify patterns of health risk behaviors, and latent class regression to explore associations between psychological distress and demographic characteristics with health behavior classes. Analysis included 1965 students (mean age 25.8 ± 8.6 years, 70.7% female). Three patterns of health behaviors were identified: healthier (48.6%), moderate (40.2%) and unhealthy (11.2%) lifestyle classes. Students in the moderate and unhealthy lifestyle classes had higher odds of moderate (OR 1.43 and 2.37) and high/very high psychological distress risk (OR 2.71 and 11.69). Students in the unhealthy and moderate lifestyle classes had a higher odds of being male, younger, enrolled in transition to university and English language courses, Aboriginal or Torres Strait Islander descent and to report some financial difficulty. Study findings may be used to inform the design of mental health interventions for university students that target key health risk behaviors.

Is Alcohol Consumption Related to Lifestyle Factors in Romanian University Students?

“…Students have been reported to drink at higher levels than non-student peers, given the negative social and health consequences of excessive alcohol intake and the link with other unhealthy behaviors (e.g., cigarette smoking and recreational drug use) [18]. Previous studies have shown that factors influencing students' drinking are unstructured time, living situation (on campus, off-campus, and peers), moving away from home, and university life [19], [20].…”

Clustering of chronic disease risks among people accessing community mental health services

“…Clustering of such risks is supported by previous research suggesting that physical activity impacts diet and weight ( Beaulieu et al, 2016 , Fenton et al, 2021 , Höchsmann et al, 2020 ), a potentially more salient association for people with a mental health condition due to health promoting barriers such as medication induced cravings and low motivation ( Bailey et al, 2018 , Scott and Happell, 2011 ). The probability of tobacco smoking in Cluster 3 (0.46) is typically higher than previous studies which have identified ‘unhealthy’ clusters that are not characterised by smoking (probabilities ranging from 0.04 to 0.29) ( Atorkey et al, 2021b , Hutchesson et al, 2021 , Oftedal et al, 2019 , Pettigrew et al, 2021 ), evidence of tobacco smoking being a particularly prevalent risk among this population group, likely due to the perceived role of tobacco smoking in mental illness symptom management ( Bailey et al, 2018 , Keller-Hamilton et al, 2019 ).…”

“…Although identified as the ‘healthier’ cluster, Cluster 1 nevertheless evidenced considerable levels of risk with > 0.5 probability of three risks and almost 0.5 probability of tobacco smoking. In comparison, previous studies using cluster analysis in general population samples have reported ‘healthy’ clusters characterised by zero or one risks ( Meader et al, 2016 , Noble et al, 2015 , Whitaker et al, 2021 ), and the probability of tobacco smoking is typically < 0.1 in such clusters ( Hutchesson et al, 2021 , Oftedal et al, 2019 , Pettigrew et al, 2021 ). Additionally, studies in the Netherlands and Australia with general population and University samples report ‘healthy’ clusters to account for the largest proportion (54–80%) of the sample ( Vermeulen-Smit et al, 2015 , Oftedal et al, 2019 , Di Benedetto et al, 2019 ).…”

Interaction between physical activity and outdoor time on allostatic load in Chinese college students

“…Most college students range in age from approximately 18 to 22 years, and college is therefore a transitional period from adolescence to adulthood. This age-span is a critical period for the development of healthy lifestyles and behaviors that are important throughout the lifespan [ 2 ]. However, under the double burden of study and life, the life style of college students has changed, which is characterized by less physical activities (PA), especially outdoor activities [ 2 ].…”

“…This age-span is a critical period for the development of healthy lifestyles and behaviors that are important throughout the lifespan [ 2 ]. However, under the double burden of study and life, the life style of college students has changed, which is characterized by less physical activities (PA), especially outdoor activities [ 2 ]. According to the latest World Health Organization (WHO) survey, about 80 per cent of adolescents worldwide do not meet the recommended level of PA per day [ 3 ].…”