Resilience and patterns of health risk behaviors in California adolescents

University of California, Los Angeles (UCLA) School of Public Health, Department of Health Services, Division of Cancer Prevention and Control Research, USA.
Preventive Medicine (Impact Factor: 3.09). 03/2009; 48(3):291-7. DOI: 10.1016/j.ypmed.2008.12.013
Source: PubMed


Assess whether adolescent health risk behaviors cluster, and whether resiliency factors are associated with observed clusters.
The cross-sectional population-weighted 2003 California Health Interview Survey was used (N=4010). Four gender-specific clusters were based on smoking, alcohol use, low fruit/vegetables consumption, and physical inactivity. Resiliency factors included parental supervision, parental support, role model presence and adolescent mental health. Conditional regression was used to measure the association of individual health risk behaviors and clusters with resiliency factors.
Health risk behaviors clustered as follows: "Salutary Adherents" (no reported health risk behaviors), "Active Snackers" (physically active, low fruit/vegetable consumers), "Sedentary Snackers" (physically inactive, low fruit/vegetable consumers), and "Risk Takers" (smokers, alcohol users, many also physically inactive and low fruit/vegetable consumers). Greater parental supervision was associated with lower odds of being in unhealthful clusters. Among males, having greater parental support reduced odds of being an "Active Snacker" or "Sedentary Snacker." Among females, role model presence reduced odds of being in unhealthful clusters, while depressiveness increased the odds.
Health promoting interventions should address multiple health risk behaviors in an integrated fashion. Gender-specific, ethnically-targeted, family-centered strategies that address parenting, particularly parental supervision would be useful. Addressing depressiveness may be especially important for female adolescents.

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    • "Of the studies that identified clusters of health risk behaviours, only a few examined the relationship with mental health. These studies mainly focused on adolescents (Hallfors et al., 2004: Mistry et al., 2009; Dodd et al., 2010). Those studies which were performed among adults generally address (symptoms of) depression in relation to clusters of the " big-four " modifiable health behaviours (smoking, heavy drinking, physical inactivity and unhealthy diet) (Verger et al., 2009; Conry et al., 2011). "
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    ABSTRACT: Background: Health risk behaviours tend to co-occur and are found to be related to mental health symptoms. This is the first study to identify health behaviour clusters in relation to mental disorders. Methods: Data were used from the second wave of the Netherlands Mental Health Survey and Incidence Study (NEMESIS-2), a nationally representative sample of adults (n=5303). Latent class analysis was performed to identify clusters based on four health risk behaviours (smoking, heavy drinking, physical inactivity, and unhealthy diet). Concurrently, we examined the relationship between the identified clusters and a range of DSM-IV diagnoses, assessed with the Composite International Diagnostic Interview 3.0. Results: Four distinct health behaviour clusters were identified: most healthy (mainly non-smokers, moderate drinkers, active, healthy diet; class 1: 79.3%); smokers, moderate drinkers, inactive, unhealthy diet (class 2: 13.2%); smokers, heavy episodic drinkers, active, unhealthy diet (class 3: 3.8%); Smokers, frequent heavy drinkers, active, low fruit (class 4: 3.6%). Despite their different lifestyles, individuals in all three unhealthy clusters had double the risk of depression. Unhealthy behaviour clusters were strongly associated with drug dependence (classes 2 and 3), alcohol abuse and dependence (classes 3 and 4), and social phobia (class 4). Limitations: Due to the cross-sectional design, no conclusions about the causality of the relationship between HRB clusters and mental disorders can be drawn from the current study. Conclusions: Health behaviour clusters are strongly associated with mental disorders. This co-existence of behaviours and disorders emphasises the importance of an integrative approach in the prevention of mental illnesses.
    Journal of Affective Disorders 09/2014; 171C:111-119. DOI:10.1016/j.jad.2014.09.031 · 3.38 Impact Factor
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    • "Nearly 12% of the girls in our study had problems with psychosocial or lifestyle issues including physical inactivity, sedentary behavior, and short sleeping times. The accumulation of multiple risk factors is a prevalent phenomenon among adolescents [60,61], and associations of female gender [61,62], depressiveness [63], low self-esteem [64], high anxiety scores [60], and smoking cigarettes [21] with the presence of the multiple health-related risk factors previously acknowledged lend support to our observations. It is likely that some underlying factors, perhaps related to the social environment, for example, the habits of family and friends [60,64], have influenced the concentration of several behaviors. "
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    ABSTRACT: Background Adolescent’psychosocial problems associate with unhealthy behaviors, but data on co-occurring patterns is sparse. We investigated 1) whether adolescents could be categorized into meaningful subgroups with respect to psychosocial and lifestyle factors, 2) whether the prevalence of physical inactivity, overweight and smoking vary within the subgroups and 3) whether these unhealthy behaviors persist in a two-year follow-up. Methods The study was based on a subgroup of the 1986 Northern Finland Birth Cohort, which consisted of adolescents who replied to a postal questionnaire at 16 years (n = 6792) and a subgroup of this sample at 18 years (n = 1552). Latent class analysis (LCA) was performed to establish clusters at 16 years. Results Smoking co-existed with emotional and behavioral problems in both genders. Boys with the most inactive lifestyle slept poorly, whereas multiple problems co-occurred among girls. Those with a high body mass index (BMI) separated as groups of their own. Different combinations of adverse lifestyle and emotional and behavioral problems were relatively common in both sexes as only 51% of boys and 67% of girls belonged to the reference cluster with low probability for these findings. Physical inactivity, high BMI and smoking tended to persist over the two-year follow-up. Conclusions It seems that lifestyle and psychosocial factors divide adolescents into distinct subgroups in which unhealthy lifestyle patterns remain between the ages of 16 and 18. This may indicate problems in other life areas and expose them to an increased risk of future health problems.
    BMC Public Health 06/2014; 14(1):542. DOI:10.1186/1471-2458-14-542 · 2.26 Impact Factor
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    • "Van Nieuwenhuizen et al. for example also showed a strong correlation of substance use related behaviors and sexual behavior with factor analysis techniques, yet due to the different scope of included behaviors these results were only partly comparable to those of the current study [12]. No major differences in behavioral patterns from the study of Van Nieuwenhuizen or other previous studies were found [9,12-15,49]. "
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    ABSTRACT: Recent studies show several health-related behaviors to cluster in adolescents. This has important implications for public health. Interrelated behaviors have been shown to be most effectively targeted by multimodal interventions addressing wider-ranging improvements in lifestyle instead of via separate interventions targeting individual behaviors. However, few previous studies have taken into account a broad, multi-disciplinary range of health-related behaviors and connected these behavioral patterns to health-related outcomes. This paper presents an analysis of the clustering of a broad range of health-related behaviors with relevant demographic factors and several health-related outcomes in adolescents. Self-report questionnaire data were collected from a sample of 2,690 Dutch high school adolescents. Behavioral patterns were deducted via Principal Components Analysis. Subsequently a Two-Step Cluster Analysis was used to identify groups of adolescents with similar behavioral patterns and health-related outcomes. Four distinct behavioral patterns describe the analyzed individual behaviors: 1- risk-prone behavior, 2- bully behavior, 3- problematic screen time use, and 4- sedentary behavior. Subsequent cluster analysis identified four clusters of adolescents. Multi-problem behavior was associated with problematic physical and psychosocial health outcomes, as opposed to those exerting relatively few unhealthy behaviors. These associations were relatively independent of demographics such as ethnicity, gender and socio-economic status. The results show that health-related behaviors tend to cluster, indicating that specific behavioral patterns underlie individual health behaviors. In addition, specific patterns of health-related behaviors were associated with specific health outcomes and demographic factors. In general, unhealthy behavior on account of multiple health-related behaviors was associated with both poor psychosocial and physical health. These findings have significant meaning for future public health programs, which should be more tailored with use of such knowledge on behavioral clustering via e.g. Transfer Learning.
    BMC Public Health 12/2013; 13(1):1118. DOI:10.1186/1471-2458-13-1118 · 2.26 Impact Factor
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