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. 2018 May 7:6:135.
doi: 10.3389/fpubh.2018.00135. eCollection 2018.

Clustering of Multiple Risk Behaviors Among a Sample of 18-Year-Old Australians and Associations With Mental Health Outcomes: A Latent Class Analysis

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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 et al. Front Public Health. .

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 activity, 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.

Keywords: chronic disease; clustering; emerging adulthood; mental health; risk behavior.

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Figures

Figure 1
Figure 1
Estimated response probabilities of lifestyle risk behaviors in each latent class.

References

    1. Australian Institute of Health and Welfare. Australian Burden of Disease Study: Impact and Causes of Illness and Death in Australia 2011. Canberra: Australian Institute of Health and Welfare; (2016).
    1. World Health Organisation. Global Status Report on Noncommunicable Diseases 2014. Geneva: World Health Organisation; (2014).
    1. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the global burden of disease study 2010. Lancet (2012) 380:2224–60. 10.1016/S0140-6736(12)61766-8 - DOI - PMC - PubMed
    1. Ezzati M, Riboli E. Behavioral and dietary risk factors for noncommunicable diseases. N Engl J Med (2013) 369:954–64. 10.1056/NEJMra1203528 - DOI - PubMed
    1. Dietz WH, Douglas CE, Brownson RC. Chronic disease prevention: tobacco avoidance, physical activity, and nutrition for a healthy start. JAMA (2016) 316:1645–6. 10.1001/jama.2016.14370 - DOI - PubMed

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