#HealthRisk–Behaviours #MentalHealth

Article Summary: Patterns of Multiple Health Risk–Behaviours in University Students and Their association with Mental Health: Application of Latent Class Analysis


The article is introduced by a quick justification to the reasons behind the choice of university and college students as participants to address the health of young adults systematically. The university and college students mirror the entire youth population, and it would of great importance to assess and understand the behavioral patterning in a broader way as evident in the life stages, most of which take effect during college and university periods. The aim and objective of the research were therefore established and aimed at inspecting the connection between mental health outcomes and identified clusters with the help of Canadian university samples.


The method of data collection involved a National College Health Assessment survey. The survey was conducted among 837 undergraduate students within an average age of 21 years. The survey was made of about 300 items, inclusive of assessments related health-risk behaviors, mental health behaviors, and student health status. The method used in identifying the patterning was the latent class analysis, which is a group of method for identifying latent, or unobservable, subdivisions within a population. The method is used to divide categorical data to some forms of classes through the probability model. The criteria for selection of the model judges and defines the extent by which the model paroxysms the data. The latent class analysis was thus used to detect patterning depending on eight health-risk behaviors, including; risky sex, poor diet, use of marijuana, usage of other illicit drugs, physical inactivity, binge drinking, and lack of enough sleep.

Results and Findings

The research established that based on the identified health-risk behaviors, all of which were twisted depending on the place of residence, year of study, place of residence, or sex, a three-class technique of undergraduate students showed the showed the best fit of the model. The classes include; moderately healthy, high-risk, and typical classes. The probabilities of the responses for the class, which simply depicted the likelihood of participating in all the health-risk behaviors, were represented in a bar graph, as shown below.

Item-response probabilities

From the bar graph, it is clear that fruit and vegetable consumption (FVC), sleep, and moderate-to-vigorous physical activity (MVPA) were upturned coded in such a way that the lower likelihoods of participating in these behaviors mirrored higher threats. Typical students represented the highest percentage, about 65.7%, followed by high-risk students, about 19.8%, and lastly the temperately healthy students, at about 14.55, of the entire population sample. Moreover, the results also established that the high-risk learners reported considerably higher stress levels than typical students.

Discussions and Conclusion

The study surveyed amendable mental health and health-risk behaviors among the Canadian university students and established that those with the highest probability of participating in various health-risk behaviors exhibit poorer mental health, more so upon relation to stress levels. However much it would be of great significance to construe the findings with caution given the 28% rate of response, it still advocates for interventions that target specific groups with identical multiple health-risk patterning in behavior. Moreover, a greater prominence should be established regarding supporting physical activity, health-protecting diet behaviors, and sleep.

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