Clustering of multiple risk behaviors among a sample of 18-year-old australians and associations with mental health outcomes: A latent class analysis

Katrina E. Champion*, Marius Mather, Bonnie Spring, Frances Kay-Lambkin, Maree Teesson, Nicola C. Newton

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Introduction: Risk behaviors commonly co-occur, typically emerge in adolescence, and become entrenched by adulthood. This study investigated the clustering of established (physical inactivity, diet, smoking, and alcohol use) and emerging (sedentary behavior and sleep) chronic disease risk factors among young Australian adults, and examined how clusters relate to mental health. Methods: The sample was derived from the long-term follow-up of a cohort of Australians. Participants were initially recruited at school as part of a cluster randomized controlled trial. A total of 853 participants (Mage = 18.88 years, SD = 0.42) completed an online self-report survey as part of the 5-year follow-up for the RCT. The survey assessed six behaviors (binge drinking and smoking in the past 6 months, moderate-to-vigorous physical activity/week, sitting time/day, fruit and vegetable intake/day, and sleep duration/ night). Each behavior was represented by a dichotomous variable reflecting adherence to national guidelines. Exploratory analyses were conducted. Clusters were identified using latent class analysis. Results: Three classes emerged: “moderate risk” (moderately likely to binge drink and not eat enough fruit, high probability of insufficient vegetable intake; Class 1, 52%); “inactive, non-smokers” (high probabilities of not meeting guidelines for physical acti vity, sitting time and fruit/vegetable consumption, very low probability of smoking; Class 2, 24%), and “smokers and binge drinkers” (high rates of smoking and binge drinking, poor fruit/vegetable intake; Class 3, 24%). There were significant differences between the classes in terms of psychological distress (p = 0.003), depression (p < 0.001), and anxiety (p = 0.003). Specifically, Class 3 (“smokers and binge drinkers”) showed higher levels of distress, depression, and anxiety than Class 1 (“moderate risk”), while Class 2 (“inactive, non-smokers”) had greater depression than the “moderate risk” group. Discussion: Results indicate that risk behaviors are prevalent and clustered in 18-year old Australians. Mental health symptoms were significantly greater among the two classes that were characterized by high probabilities of engaging in multiple risk behaviors (Classes 2 and 3). An examination of the clustering of lifestyle risk behaviors is important to guide the development of preventive interventions. Our findings reinforce the importance of delivering multiple health interventions to reduce disease risk and improve mental well-being.

Original languageEnglish (US)
Article number135
Pages (from-to)1-11
Number of pages11
JournalFrontiers in Public Health
Volume6
DOIs
StatePublished - 2018

Keywords

  • Chronic disease
  • Clustering
  • Emerging adulthood
  • Mental health
  • Risk behavior

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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