Subjective Response to Alcohol Challenge: A Quantitative Review
Article first published online: 20 JUL 2011
Copyright © 2011 by the Research Society on Alcoholism
Alcoholism: Clinical and Experimental Research
Volume 35, Issue 10, pages 1759–1770, October 2011
How to Cite
Quinn, P. D. and Fromme, K. (2011), Subjective Response to Alcohol Challenge: A Quantitative Review. Alcoholism: Clinical and Experimental Research, 35: 1759–1770. doi: 10.1111/j.1530-0277.2011.01521.x
- Issue published online: 26 SEP 2011
- Article first published online: 20 JUL 2011
- Received for publication July 19, 2010; accepted February 7, 2011.
- Subjective Response to Alcohol;
- Level of Response;
- Differentiator Model;
Background: Individual differences in subjective response to alcohol, as measured by laboratory-based alcohol challenge, have been identified as a candidate phenotypic risk factor for the development of alcohol-use disorders (AUDs). Two models have been developed to explain the role of subjective response to alcohol, but predictions from the 2 models are contradictory, and theoretical consensus is lacking.
Methods: This investigation used a meta-analytic approach to review the accumulated evidence from alcohol-challenge studies of subjective response as a risk factor. Data from 32 independent samples (total N = 1,314) were aggregated to produce quantitative estimates of the effects of risk-group status (i.e., positive family history of AUDs or heavier alcohol consumption) on subjective response.
Results: As predicted by the Low Level of Response Model (LLRM), family history–positive groups experienced reduced overall subjective response relative to family history–negative groups. This effect was most evident among men, with family history–positive men responding more than half a standard deviation less than family history–negative men. In contrast, consistent with the Differentiator Model (DM), heavier drinkers of both genders responded 0.4 standard deviations less on measures of sedation than did the lighter drinkers but nearly half a standard deviation more on measures of stimulation, with the stimulation difference appearing most prominent on the ascending limb of the blood alcohol concentration curve.
Conclusions: The accumulated results from 3 decades of family history comparisons provide considerable support for the LLRM. In contrast, results from typical consumption comparisons were largely consistent with predictions of the DM. The LLRM and DM may describe 2 distinct sets of phenotypic risk, with importantly different etiologies and predictions for the development of AUDs.