OBJECTIVE: A low level of response (LR) to alcohol was originally established through evidence of less alcohol-related change in several parameters at a given blood alcohol level. This is a genetically influenced phenotype associated with an increased risk for alcoholism. When measured by a retrospective questionnaire (the Self-Rating of the Effects of Alcohol [SRE] scale), a lower LR (here indicated by a report that more drinks were historically needed for various effects) correlates with a family history of alcoholism and numerous alcohol use-related variables. The current analyses address the questions of how higher SRE scores (as indicators of a low LR) relate to alcohol use and problems across different age groups and when considered in the context of demography (e.g., age, gender, and weight), as well as the number of items endorsed on the questionnaire. METHOD: SRE data (scores and numbers of items endorsed), demography, and alcohol-related variables (quantity, frequency, and problems) were evaluated in two populations. The first population included 334 12-year-old children from the Avon Longitudinal Study of Parents and Children, and the second included more than 400 35-year-old men from the San Diego Prospective Study. In each group, Pearson correlations were established among all variables, and items that were significantly linked to alcohol-related outcomes were entered into regression analyses as predictors of these outcomes. RESULTS: In both samples, SRE scores correlated with all alcohol-related outcomes, with the highest values for the maximum quantity of alcohol consumed. Relationships between the SRE score and alcohol-related variables remained robust in both populations when entered into regression analyses incorporating demography and the number of SRE items answered by subjects. CONCLUSIONS: The SRE score appears to perform relatively similarly across the two populations regarding relationships with alcohol quantity, frequency, and problems. The most consistent results were observed for the maximum quantity of alcohol consumed.
OBJECTIVE: A low level of response (LR) to alcohol was originally established through evidence of less alcohol-related change in several parameters at a given blood alcohol level. This is a genetically influenced phenotype associated with an increased risk for alcoholism. When measured by a retrospective questionnaire (the Self-Rating of the Effects of Alcohol [SRE] scale), a lower LR (here indicated by a report that more drinks were historically needed for various effects) correlates with a family history of alcoholism and numerous alcohol use-related variables. The current analyses address the questions of how higher SRE scores (as indicators of a low LR) relate to alcohol use and problems across different age groups and when considered in the context of demography (e.g., age, gender, and weight), as well as the number of items endorsed on the questionnaire. METHOD: SRE data (scores and numbers of items endorsed), demography, and alcohol-related variables (quantity, frequency, and problems) were evaluated in two populations. The first population included 334 12-year-old children from the Avon Longitudinal Study of Parents and Children, and the second included more than 400 35-year-old men from the San Diego Prospective Study. In each group, Pearson correlations were established among all variables, and items that were significantly linked to alcohol-related outcomes were entered into regression analyses as predictors of these outcomes. RESULTS: In both samples, SRE scores correlated with all alcohol-related outcomes, with the highest values for the maximum quantity of alcohol consumed. Relationships between the SRE score and alcohol-related variables remained robust in both populations when entered into regression analyses incorporating demography and the number of SRE items answered by subjects. CONCLUSIONS: The SRE score appears to perform relatively similarly across the two populations regarding relationships with alcohol quantity, frequency, and problems. The most consistent results were observed for the maximum quantity of alcohol consumed.
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: Jacqueline M Otto; Ian R Gizer; Joseph D Deak; Kimberly A Fleming; Bruce D Bartholow Journal: Alcohol Clin Exp Res Date: 2017-04-10 Impact factor: 3.455
Authors: Kimberly A Fleming; Bruce D Bartholow; Joseph Hilgard; Denis M McCarthy; Susan E O'Neill; Douglas Steinley; Kenneth J Sher Journal: Alcohol Clin Exp Res Date: 2016-03-25 Impact factor: 3.455
Authors: Marc A Schuckit; Tom L Smith; Ryan Trim; Jon Heron; Jeremy Horwood; John M Davis; Joseph R Hibbeln Journal: Addiction Date: 2008-09-04 Impact factor: 6.526
Authors: Marc A Schuckit; Tom L Smith; Jon Heron; Matthew Hickman; John Macleod; Glyn Lewis; John M Davis; Joseph R Hibbeln; Sandra Brown; Luisa Zuccolo; Laura L Miller; George Davey-Smith Journal: Alcohol Clin Exp Res Date: 2011-07-18 Impact factor: 3.455
Authors: Marc A Schuckit; Tom L Smith; Ryan S Trim; Jon Heron; Jeremy Horwood; John Davis; Joseph Hibbeln Journal: Alcohol Alcohol Date: 2008-10-08 Impact factor: 2.826