Risks of alcohol use disorders related to drinking patterns in the U.S. general population

J Stud Alcohol Drugs. 2014 Mar;75(2):319-27. doi: 10.15288/jsad.2014.75.319.


Objective: The purpose of this study was to examine the relations between drinking (mean quantity and heavy drinking patterns) and alcohol use disorders (AUDs) in the U.S. general population.

Method: Data from three telephone National Alcohol Surveys (in 2000, 2005, and 2010) were pooled, with separate analyses for men and women restricted to current drinkers (ns = 5,922 men, 6,270 women). Predictors were 12-month volume (mean drinks per day), rates of heavy drinking (5+/4+ drinks in a day for men/women), and very heavy drinking (8+, 12+, and 24+ drinks in a day). Outcomes were negative alcohol-related consequences constituting abuse (1+ of 4 DSM-IV-based domains assessed by 13 items) and alcohol dependence (symptoms in 3+ of 7 DSM-IV-based domains), together taken to indicate an AUD. Segmentation analyses were used to model risks of problem outcomes from drinking patterns separately by gender.

Results: In the general population, men and women who consumed ≤1 drink/day on average with no heavy drinking days did not incur substantial risks of an AUD (<10%). Men who drank from 1 to 2 drinks/day on average but never 5+ incurred a 16% risk of reporting an AUD (3.5% alcohol dependence). At higher volumes, men and women who indicated higher rates of drinking larger amounts per day and/or involving 8+ and 12+ drinks/day (and even 24+ drinks/day for men) showed much higher risks of experiencing AUDs.

Conclusions: The findings provide quantitative guidance for primary care practitioners who wish to make population-based recommendations to patients who might benefit by reducing both overall intake and amounts per occasion in an effort to lower their risks of developing AUDs.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Alcohol Drinking / epidemiology*
  • Alcohol-Related Disorders / diagnosis
  • Alcohol-Related Disorders / epidemiology*
  • Cross-Sectional Studies
  • Data Collection* / methods
  • Female
  • Humans
  • Male
  • Population Surveillance* / methods
  • Risk Factors
  • Self Report*
  • United States / epidemiology