Predictors of drinking patterns in adolescence: a latent class analysis

BACKGROUND: Uni-dimensional measures of alcohol consumption may be unable to fully capture the complexity of adolescent drinking and experience of alcohol-related harms. Latent class analysis provides an empirical method to understand different adolescent drinking patterns.

METHODS: Latent class analysis was used to create typologies of drinking among the 5018 current drinkers in the national Youth '07 survey. Determinants of drinking patterns were identified using multinomial logistic regression.

RESULTS: Four latent classes were identified, demonstrating an overall increase in risk of alcohol-related outcomes from increasing consumption. One class strongly deviated from this pattern, having moderate consumption patterns but disproportionately high levels of alcohol-related problems. Multinomial logistic regression found that the strongest predictors of belonging to high-risk drinking typologies were having a positive attitude to regular alcohol use, buying own alcohol, peers using alcohol, and obtaining alcohol from friends and/or other adults. Other significant predictors included being male, having a strong connection to friends, having parents with a low level of knowledge of their daily activities and poor connection to school. Class membership also varied by ethnicity.

CONCLUSION: The latent class approach demonstrated variability in alcohol-related harms across groups of students with different drinking patterns. Longitudinal studies are necessary to determine the causes of this variability in order to inform the development of targeted policy and preventative interventions. Legislative controls, such as increasing the legal purchase age and reducing the commercial availability of alcohol, will continue to be important strategies for reducing harm in young people.

Additional Info

  • Authors:

    Jackson,N.; Denny,S.; Sheridan,J.; Fleming,T.; Clark,T.; Teevale,T.; Ameratunga,S.

  • Issue: Drug Alcohol Depend. / pages 133-139 / volume 135
  • Published Date: 2014/2/1
  • More Information:

    For more information about this abstract, please contact
    This email address is being protected from spambots. You need JavaScript enabled to view it. at the Deutsche Weinakademie GmbH

Read 2019 times

Disclaimer

The authors have taken reasonable care in ensuring the accuracy of the information herein at the time of publication and are not responsible for any errors or omissions. Read more on our disclaimer and Privacy Policy.