Derivation and Validation of a Prediction Rule for Identifying Heavy Consumers of Alcohol

Michael J. Lichtenstein, M. Candice Burger, John W.G. Yarned, Peter C. Elwood, Peter M. Sweetnam

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Using two population‐based cohorts of men aged 45‐59, we sought to derive and validate a prediction rule for identifying heavy consumers of alcohol. Eighty‐five percent of eligible men on electoral rolls in Caerphilly, Wales (derivation set, N = 2512) and 90% of eligible men on the practice lists of 16 Speedwell, England, general practitioners participated (validation set, N = 2348). Alcohol consumption was assessed by questionnaire with heavy alcohol consumption defined as the top 10% of the Caerphilly population's alcohol usage (>525 cc ethanol per week). The prediction rule, Score = (mean corpuscular volume × 1.00) + (body mass index × 0.31) + (systolic blood pressure × 0.08) + HDL‐cholesterol × 9.24) + (fasting triglyceride × 2.20) was derived by multiple linear regression in the Caerphilly cohort and validated in the Speedwell cohort. Comparing the lower 20% of the Score distribution with the upper 5%, likelihood ratios increased from 0.15 to 5.29 and 0.06 to 7.42 in the Caerphilly and Speedwell cohorts, respectively. Having a score of 136.30 or greater yielded a relative risk of being a heavy drinker of 23.1 (95% CI = 10.1‐53.0) in Caerphilly and 99.3 (95% CI = 12.8‐769.5) in Speedwell. The derived prediction rule is a valid diagnostic aid to help clinicians identify heavy alcohol consumers.

Original languageEnglish (US)
Pages (from-to)626-630
Number of pages5
JournalAlcoholism: Clinical and Experimental Research
Issue number5
StatePublished - Oct 1989
Externally publishedYes

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Toxicology
  • Psychiatry and Mental health


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