Alcohol and coronary heart disease: a meta-analysis

Addiction. 2000 Oct;95(10):1505-23. doi: 10.1046/j.1360-0443.2000.951015056.x.


Objective: To estimate parameters of the function relating alcohol consumption with the risk of coronary heart disease and to identify the sources of heterogeneity in the parameter estimates.

Methods: A search of the epidemiological literature from 1966 to 1998 was performed using several bibliographic databases. Meta-regression models were fitted to evaluate non-linear effects of alcohol intake on the relative risk. The effects of some characteristics of the studies, including an index of their quality, were considered as putative sources of heterogeneity of the estimates. Publication bias was also investigated.

Findings: Among the 196 initially reviewed articles, 51 were selected. Since qualitative characteristics of the studies were significant sources of heterogeneity, the pooled dose-response functions were based on the 28 cohort studies with higher quality. Risk decreased from 0 to 20 g/day (RR = 0.80; 95% CI: 0.78, 0.83); there was evidence of a protective effect up to 72 g/day (RR = 0.96; 95% CI: 0.92, 1.00) and increased risk above > or = 89 g/day (RR = 1.05; 95% CI: 1.00, 1.11). Lower protective effects and harmful effects were found in women, in men living in countries outside the Mediterranean area and in studies where fatal events were used as the outcome. Evidence of publication bias for moderate intakes and of heterogeneity of the estimates across studies for higher intakes were found.

Conclusions: The degree of protection from moderate doses of alcohol should be reconsidered. Further research investigating the effect of drinking patterns on the risk of coronary heart disease should be performed. Caution in making general recommendations is needed.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alcohol Drinking / adverse effects*
  • Confidence Intervals
  • Coronary Disease / etiology*
  • Dose-Response Relationship, Drug
  • Female
  • Humans
  • Male
  • Mathematical Computing*
  • Odds Ratio
  • Publication Bias
  • Regression Analysis
  • Research Design
  • Risk Factors
  • Sex Factors