Mahmood R Gohari1, Joel A Dubin1,2, Richard J Cook2, Scott T Leatherdale1. 1. School of Public Health and Health Systems, University of Waterloo, Waterloo, Ontario, Canada. 2. Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada.
Abstract
INTRODUCTION: Despite evidence indicating a rapid progression in use of alcohol during adolescence, little is known about the ways patterns of drinking develop over time. This study investigated patterns of alcohol use within a cohort of youth in Ontario and Alberta and the probability of changes between patterns. METHODS: The sample consists of two-year linked longitudinal data (school year 2013/14 to 2014/15) from 19 492 students in Grades 9 to 12 in 89 secondary schools across Ontario and Alberta, Canada, who participated in the COMPASS study. The latent class analysis used two self-reported items about the frequency of drinking (measured as none, monthly, weekly, or daily use) and the frequency of binge drinking (measured as none, less than or once a month, 2-4 times a month, or more than once week) to characterize patterns of alcohol use. The effects of gender, ethnicity and cannabis and cigarette use on alcohol use patterns were examined. RESULTS: The study identified four drinking patterns: non-drinker, periodic drinker (reported monthly drinking and no binge drinking), low-risk drinker (reported monthly drinking and limited binge drinking) and high-risk regular drinker (reported drinking 1-3 times a week and binge drinking 2-4 times a month). Non-drinker was the most prevalent pattern at baseline (55.1%) and follow-up (39.1%). Periodic drinkers had the highest likelihood of an increase in alcohol consumption, with 40% moving to the low-risk pattern. A notable proportion of participants returned to a lower severity pattern or transitioning out of drinking. CONCLUSION: There are four distinct youth alcohol-use patterns. The high probability of transitioning to drinking during the secondary school years suggests the need for preventive interventions in earlier stages of use, before drinking becomes habitual.
INTRODUCTION: Despite evidence indicating a rapid progression in use of alcohol during adolescence, little is known about the ways patterns of drinking develop over time. This study investigated patterns of alcohol use within a cohort of youth in Ontario and Alberta and the probability of changes between patterns. METHODS: The sample consists of two-year linked longitudinal data (school year 2013/14 to 2014/15) from 19 492 students in Grades 9 to 12 in 89 secondary schools across Ontario and Alberta, Canada, who participated in the COMPASS study. The latent class analysis used two self-reported items about the frequency of drinking (measured as none, monthly, weekly, or daily use) and the frequency of binge drinking (measured as none, less than or once a month, 2-4 times a month, or more than once week) to characterize patterns of alcohol use. The effects of gender, ethnicity and cannabis and cigarette use on alcohol use patterns were examined. RESULTS: The study identified four drinking patterns: non-drinker, periodic drinker (reported monthly drinking and no binge drinking), low-risk drinker (reported monthly drinking and limited binge drinking) and high-risk regular drinker (reported drinking 1-3 times a week and binge drinking 2-4 times a month). Non-drinker was the most prevalent pattern at baseline (55.1%) and follow-up (39.1%). Periodic drinkers had the highest likelihood of an increase in alcohol consumption, with 40% moving to the low-risk pattern. A notable proportion of participants returned to a lower severity pattern or transitioning out of drinking. CONCLUSION: There are four distinct youth alcohol-use patterns. The high probability of transitioning to drinking during the secondary school years suggests the need for preventive interventions in earlier stages of use, before drinking becomes habitual.
Authors: Kirsty E Scholes-Balog; Sheryl A Hemphill; Tracy J Evans-Whipp; John W Toumbourou; George C Patton Journal: Addict Behav Date: 2015-09-21 Impact factor: 3.913
Authors: Marc A Schuckit; Tom L Smith; George P Danko; Kathleen K Bucholz; Arpana Agrawal; Danielle M Dick; John I Nurnberger; John Kramer; Michie Hesselbrock; Gretchen Saunders; Victor Hesselbrock Journal: J Stud Alcohol Drugs Date: 2014-01 Impact factor: 2.582
Authors: Patrycia Sarah Martins Arruda; Aline Natália Silva; Ana Elisa Madalena Rinaldi; Luciana Saraiva da Silva; Catarina Machado Azeredo Journal: Int J Public Health Date: 2022-06-02 Impact factor: 5.100