Literature DB >> 23499056

Individual- and community-level correlates of cigarette-smoking trajectories from age 13 to 32 in a U.S. population-based sample.

Bernard Fuemmeler1, Chien-Ti Lee, Krista W Ranby, Trenette Clark, F Joseph McClernon, Chongming Yang, Scott H Kollins.   

Abstract

BACKGROUND: Characterizing smoking behavior is important for informing etiologic models and targeting prevention efforts. This study explored the effects of both individual- and community-level variables in predicting cigarette use vs. non-use and level of use among adolescents as they transition into adulthood.
METHODS: Data on 14,779 youths (53% female) were drawn from the National Longitudinal Study of Adolescent Health (Add Health); a nationally representative longitudinal cohort. A cohort sequential design allowed for examining trajectories of smoking typologies from age 13 to 32 years. Smoking trajectories were evaluated by using a zero-inflated Poisson (ZIP) latent growth analysis and latent class growth analysis modeling approach.
RESULTS: Significant relationships emerged between both individual- and community-level variables and smoking outcomes. Maternal and peer smoking predicted increases in smoking over development and were associated with a greater likelihood of belonging to any of the four identified smoking groups versus Non-Users. Conduct problems and depressive symptoms during adolescence were related to cigarette use versus non-use. State-level prevalence of adolescent smoking was related to greater cigarette use during adolescence.
CONCLUSIONS: Individual- and community-level variables that distinguish smoking patterns within the population aid in understanding cigarette use versus non-use and the quantity of cigarette use into adulthood. Our findings suggest that efforts to prevent cigarette use would benefit from attention to both parental and peer smoking and individual well-being. Future work is needed to better understand the role of variables in the context of multiple levels (individual and community-level) on smoking trajectories.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Add health; LCGA; National Longitudinal Study of Adolescent Health; Smoking trajectories; Zero-inflated Poisson (ZIP)

Mesh:

Year:  2013        PMID: 23499056      PMCID: PMC3701734          DOI: 10.1016/j.drugalcdep.2013.02.021

Source DB:  PubMed          Journal:  Drug Alcohol Depend        ISSN: 0376-8716            Impact factor:   4.492


  38 in total

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2.  Developmental trajectories of cigarette use from early adolescence into young adulthood.

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4.  Identifying trajectories of adolescent smoking: an application of latent growth mixture modeling.

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Review 5.  An ecological approach to understanding youth smoking trajectories: problems and prospects.

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Review 8.  Cigarette smoking and psychiatric comorbidity in children and adolescents.

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9.  Integrating person-centered and variable-centered analyses: growth mixture modeling with latent trajectory classes.

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  22 in total

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3.  Latent Trajectories and Profiles of Commercial Cigarette Smoking Frequency From Adolescence to Young Adulthood Among North American Indigenous People.

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Journal:  Soc Sci Res       Date:  2015-06-19

5.  Similarities and differences in alcohol trajectories: Testing the catch-up effect among biracial black subgroups.

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6.  Cigarette use trajectories in young adults: Analyses of predictors across system levels.

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Journal:  Drug Alcohol Depend       Date:  2018-05-22       Impact factor: 4.492

7.  Trajectories of Cigarette Smoking From Teens to Young Adulthood: 2000 to 2013.

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8.  Proactive telephone counseling for adolescent smokers: Comparing regular smokers with infrequent and occasional smokers on treatment receptivity, engagement, and outcomes.

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Journal:  Drug Alcohol Depend       Date:  2016-06-20       Impact factor: 4.492

9.  Tobacco Use Trajectories in Young Adults: Analyses of Predictors Across Systems Levels.

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10.  The longitudinal, bidirectional relationships between parent reports of child secondhand smoke exposure and child smoking trajectories.

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