Tracking drinking behaviour from age 15-19 years

Addiction. 2003 Nov;98(11):1505-11. doi: 10.1046/j.1360-0443.2003.00496.x.


Aims: The aim of this paper was to assess (1) changes in drinking behaviour over time among Danish adolescents and (2) use of which alcoholic beverages and what drinking patterns would have the strongest predictive effect on later alcohol consumption.

Design, setting, participants: The population was a random sample of 15-year-olds (baseline 1990, response rate 86%, n= 847) with a first follow-up 4 years later (response rate 85%, n= 729).

Measurements: Alcohol intake was assessed by experience of drunkenness, quantity and frequency of consumption. Thresholds recommended by the Danish National Board of Health were used to discriminate high from low intake.

Findings: At 19 years of age at least 80% drank alcohol monthly, and 24% of the men and 11% of the women had an alcohol intake above the recommended national limits, i.e. 21 weekly units of alcohol for men and 14 for women. Consumption of alcoholic beverages at age 15 increased the risk of drinking alcohol weekly at the age of 19 [odds ratio (OR)-values from 1.11 to 3.53]. Drunkenness among the 15-year-old boys and the use of spirits of the 15-year-old girls showed the strongest predictive relationship with excessive consumption at age 19 [OR = 2.44, confidence interval (CI): 1.38-4.29, respectively, OR = 1.97, CI: 1.15-3.38].

Conclusions: Alcohol consumption as early as the age of 15 predicted weekly alcohol consumption and alcohol intake exceeding the recommended amount 4 years later. Young teenagers' high alcohol consumption was not just a passing phenomenon. It was a behaviour that tracked into young adulthood, leaving the adolescents at increased risk of being long-term, large-scale consumers.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Age of Onset
  • Alcohol Drinking / epidemiology*
  • Alcoholic Beverages / statistics & numerical data*
  • Alcoholic Intoxication / epidemiology*
  • Denmark / epidemiology
  • Female
  • Humans
  • Logistic Models
  • Longitudinal Studies
  • Male
  • Multivariate Analysis
  • Prevalence
  • Surveys and Questionnaires