Three-year changes in adult risk drinking behavior in relation to the course of alcohol-use disorders.

Laboratory of Epidemiology and Biometry, Division of Intramural Clinical and Biological Research, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9304, USA.
Journal of studies on alcohol and drugs (Impact Factor: 2.27). 11/2008; 69(6):866-77.
Source: PubMed

ABSTRACT This study examines the associations between the course of alcohol-use disorder (AUD) and changes in average daily volume of ethanol intake, frequency of risk drinking, and maximum quantity of drinks consumed per day over a 3-year follow-up interval in a sample of U.S. adults.
Data were taken from a longitudinal study of a nationally representative sample of U.S. adults, who were 18 years of age and older (mean age = 46.4) when initially interviewed in 2001-2002 and successfully reinterviewed approximately 3 years later (n = 22,245 baseline drinkers). The time reference period for the drinking measures was the 12 months preceding the interview. Changes in consumption reflect differences between Wave 1 and Wave 2 measures for individuals with nonmissing values at both Waves (n = 22,003 for volume of intake, 22,132 for frequency of risk drinking and 21,942 for maximum quantity of drinks).
There were positive changes in all consumption measures associated with developing an AUD and negative changes associated with remission of an AUD, even among individuals who continued to drink. Increases and decreases associated with onset and offset of dependence exceeded those associated with onset/ offset of abuse only, and the decreases associated with full remission from dependence exceeded those associated with partial remission. There were few changes in consumption among individuals whose AUD status did not change. Interactions of AUD transitions with other factors indicate that development of an AUD is associated with a greater increase in consumption among men, possibly reflecting their greater total body water and lower blood alcohol concentration in response to a given dose of ethanol, and among individuals with high baseline levels of consumption.
Changes in consumption associated with onset and offset of AUD are substantial enough to have important implications for the risk of associated physical and psychological harm.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This study examined changes in alcohol drinking patterns (DP) and associated variables in a Mediterranean country. Changes in DP between baseline (2008-2010) and follow-up (2012-2013) were examined on a Spanish population-based cohort of 2254 adults (18-59 years) using multinomial logistic regression. Heavy consumption was defined as ≥40g/day of alcohol in men (≥24g/day in women) and binge drinking (BD) as the intake of ≥80g of alcohol in men (≥60g in women) on one occasion in the previous month. Six patterns were defined: (1) non-drinkers; (2) ex-drinkers; (3) moderate drinkers without BD (MNB); (4) moderate drinkers with BD (MB); (5) heavy drinkers without BD (HNB); and (6) heavy drinkers with BD (HB). Overall, 45.2% of participants changed DP during follow-up. Over 24% of non-drinkers and 19.4% of ex-drinkers at baseline qualified as MNB at follow-up. The largest flow was from HNB to MNB (57.1%). Light-drinking patterns experienced the largest gains (ex-drinkers: 37.5% and MNB: 66.7%) by absorbing individuals lost by heavy-drinking patterns (MB: 50.8% and HNB: 48.4%). Men, younger individuals, and current smokers were more likely to report heavy-drinking patterns at one or both assessments. Being married or employed increased the likelihood of reporting light-drinking patterns at both surveys (p<0.05). Improving physical quality of life and exercise were associated with a shift from light- to heavy-drinking pattern during follow-up (p<0.05). DP in Spain changed over 3 years with a tendency to "regress" toward moderate patterns. Repeated measures of alcohol intake may reduce classification errors and biased results when examining the impact of alcohol on health.
    Drug and alcohol dependence 04/2014; DOI:10.1016/j.drugalcdep.2014.04.006 · 3.60 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Alcohol-induced brain damage likely contributes to the dysfunctional poor decisions associated with alcohol dependence. Human alcoholics have a global loss of brain volume that is most severe in the frontal cortex. Neuroimmune gene induction by binge drinking increases neurodegeneration through increased oxidative stress, particularly NADPH oxidase-induced oxidative stress. In addition, HMGB1-TLR4 and innate immune NF-κB target genes are increased leading to persistent and sensitized neuroimmune responses to ethanol and other agents that release HMGB1 or directly stimulate TLR receptors and/or NMDA receptors. Neuroimmune signaling and glutamate excitotoxicity are linked to alcoholic neurodegeneration. Models of adolescent alcohol abuse lead to significant frontal cortical degeneration and show the most severe loss of hippocampal neurogenesis. Adolescence is a period of high risk for ethanol-induced neurodegeneration and alterations in brain structure, gene expression, and maturation of adult phenotypes. Together, these findings support the hypothesis that adolescence is a period of risk for persistent and long-lasting increases in brain neuroimmune gene expression that promote persistent and long-term increases in alcohol consumption, neuroimmune gene induction, and neurodegeneration that we find associated with alcohol use disorders.
    International Review of Neurobiology 01/2014; 118C:315-357. DOI:10.1016/B978-0-12-801284-0.00010-5 · 2.46 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Background: Routine screening for unhealthy alcohol use is widely recommended in primary care settings. However, the validity of repeat screening among patients who have previously screened negative remains unknown. This study aims to evaluate the performance of a clinical alcohol screen compared to a confidential comparison alcohol screen among patients with previous negative alcohol screens. Methods: This study included four nested samples of Veteran Health Administration (VA) outpatients with at least one (N=18,493) and up to four (N=714) prior negative annual clinical AUDIT-C screens who completed the AUDIT-C the following year, both in a VA clinic (clinical screen) and on a confidential mailed survey (comparison screen). AUDIT-C screens were categorized as either negative (0-3 points men; 0-2 women) or positive (>= 4 men; >= 3 women). For each sample, the performance of the clinical screen was compared to the comparison screen, the reference measure for unhealthy alcohol use. Results: The sensitivity of clinical screens decreased as the number of prior negative screens in a sample increased (40.0-17.4%) for patients with 1-4 negative screens. The positive predictive value also decreased as the number of prior negative screens in a sample increased (67.7-33.3%) while specificity was consistently high for all samples (>= 97.8%). Conclusions: Repeat clinical alcohol screens became progressively less sensitive for identifying unhealthy alcohol use among patients who repeatedly screened negative over several years. Alternative approaches for assessing unhealthy alcohol use may be needed for these patients. Published by Elsevier Ireland Ltd.
    Drug and Alcohol Dependence 06/2014; 142. DOI:10.1016/j.drugalcdep.2014.06.017 · 3.28 Impact Factor


Available from