title: Age-period-cohort modelling of alcohol volume and heavy drinking days in the US National Alcohol Surveys: divergence in younger and older adult trends.
abstract: OBJECTIVE
  The decomposition of trends in alcohol volume and heavy drinking days into age, period, cohort and demographic effects offers an important perspective on the dynamics of change in alcohol use patterns in the United States.
  
  
  METHODS
  The present study utilizes data from six National Alcohol Surveys conducted over the 26-year period between 1979 and 2005. Setting United States.
  
  
  METHODS
  Alcohol volume and the number of days when five or more and eight or more drinks were consumed were derived from overall and beverage-specific graduated frequency questions.
  
  
  RESULTS
  Trend analyses show that while mean values of drinking measures have continued to decline for those aged 26 and older, there has been a substantial increase in both alcohol volume and 5+ days among those aged 18-25 years. Age-period-cohort models indicate a potential positive cohort effect among those born after 1975. However, an alternative interpretation of an age-cohort interaction where drinking falls off more steeply in the late 20s than was the case in the oldest surveys cannot be ruled out. For women only, the 1956-60 birth cohort appears to drink more heavily than those born just before or after. Models also indicate the importance of income, ethnicity, education and marital status in determining these alcohol measures.
  
  
  CONCLUSIONS
  Increased heavy drinking among young adults in recent surveys presents a significant challenge for alcohol policy and may indicate a sustained increase in future US alcohol consumption.
authors.affiliation: Alcohol Research Group, Public Health Institute, Emeryville, CA 94608, USA. wkerr@arg.org
authors.forename: William C
authors.initials: WC
authors.lastname: Kerr
authors.forename: Thomas K
authors.initials: TK
authors.lastname: Greenfield
authors.forename: Jason
authors.initials: J
authors.lastname: Bond
authors.forename: Yu
authors.initials: Y
authors.lastname: Ye
authors.forename: Jürgen
authors.initials: J
authors.lastname: Rehm
mesh_terms: D000328:Adult; D017677:Age Distribution; D000428:Alcohol Drinking / Q000453:epidemiology / Q000517:prevention & control / Q000639:trends*; D019973:Alcohol-Related Disorders / Q000453:epidemiology / Q000517:prevention & control*; D000434:Alcoholic Beverages / Q000191:economics; D003132:Commerce / Q000191:economics / Q000331:legislation & jurisprudence / Q000639:trends; D004812:Epidemiologic Methods; D000431:Ethanol / Q000506:poisoning*; D005260:Female; D006801:Humans; D008297:Male; D011634:Public Health / Q000331:legislation & jurisprudence; D017678:Sex Distribution; D014481:United States / Q000453:epidemiology; D055815:Young Adult
chemical_list: D000431:Ethanol