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Alcohol Consumption and Acute Myocardial Infarction: A Benefit of Alcohol Consumed With Meals?

Augustin, Livia S.A.*†; Gallus, Silvano; Tavani, Alessandra; Bosetti, Cristina; Negri, Eva; La Vecchia, Carlo‡§

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doi: 10.1097/01.ede.0000142146.36594.9a
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Alcohol consumption has been associated with a reduced risk of acute myocardial infarction (MI) in several studies worldwide.1 This inverse relation has been seen for wine, beer, and spirits2–5 and for regular drinking, whereas binge drinking seems to exert an unfavorable effect on the risk of heart disease.6

The relation of acute MI risk with drinking during or outside of meals has rarely been investigated. In the Health Professional Study, no difference in the effect on risk of MI was shown for alcohol consumed mostly outside of meals (≥75% of the times) or mostly during meals (≥75% of the times), but the number of cases among drinkers of 30 g/day of alcohol or more was limited.3

The lower risk of coronary heart disease among drinkers may be partly accounted for by changes in glucose and insulin metabolism,7 hence the importance of considering the relation between alcohol drinking during and outside of meals. Italy offers a good opportunity for such studies because of its large proportion of alcohol drinkers. In this case-control study, we analyzed the risk of nonfatal acute MI in relation to alcohol drinking during or outside of meals.


The data were derived from a case-control study of nonfatal acute MI, conducted between 1995 and 1999 in the greater Milan area, in northern Italy.5 Cases were 507 patients (378 men and 129 women) with a first episode of nonfatal acute MI (International Classification of Disease [ICD-9]: 410) admitted to a network of general hospitals in the area. Controls were 478 patients (297 men and 181 women) from the same geographic areas and admitted to the same network of hospitals for a wide spectrum of acute conditions unrelated to known or potential risk factors for MI. In particular, patients were excluded if they had had a previous MI or if they had been admitted to the hospital for neoplastic, metabolic, and smoking- or alcohol-related conditions. Among controls, 34% had been admitted for trauma, 30% had nontraumatic orthopedic disorders, 14% had acute surgical conditions, and 22% had miscellaneous illnesses (such as eye, ear, nose, throat, and dental disorders). The median age of cases was 61 years (range, 25–79 years) and of controls it was 59 years (range, 25–79 years). The study was approved by the ethical committee and informed consent was obtained from study participants. Fewer than 5% of cases and controls who were approached refused to participate.

All interviews were conducted in hospitals using a structured questionnaire that obtained information on sociodemographic factors, anthropometric variables, physical activity, smoking and other lifestyle habits, medical history, a validated food frequency section, and history of cardiovascular disease in first-degree relatives.

The section on alcohol drinking included questions on number of drinking days per week and on the weekly number of drinks for each type of alcoholic beverage consumed: wine (125 mL); beer (330 mL); “grappa,” “amari,” and “digestives” (Italian liquors consumed after meals, 30 mL); and spirits (30 mL). Each of these drinks includes approximately 12–15 g of ethanol. Patients were also asked their age at starting and stopping each category of alcoholic beverages and whether they drank only during meals, only outside meals, or both. Total alcohol intake was calculated as the sum of all alcoholic beverages reported. Nondrinkers included lifelong abstainers from any type of alcoholic drinks, as well as subjects who had stopped drinking alcohol at least 1 year previously. Binge drinkers were subjects who drank at least 4 drinks per week on one occasion or at least 8 drinks per week on 2 occasions. There was a satisfactory level of reproducibility and validity of the pattern of alcoholic consumption.8

Odds ratios (ORs) of acute MI, and the corresponding 95% confidence intervals (CIs), were derived using unconditional multiple logistic regression models fitted by the method of maximum likelihood. These models included terms for age, sex, education, body mass index, coffee and tobacco consumption, total calorie intake, physical activity, serum cholesterol level, and history of diabetes, hypertension and hyperlipidemia.


Table 1 shows the relation between acute MI risk and alcohol drinking pattern. Compared with nondrinkers, alcohol drinking only during meals was associated with a reduced risk of MI (for 3 or more drinks per day OR = 0.50, 95% CI = 0.30–0.82). The OR for an increment of 1 drink per day was 0.91 (0.84–0.98). The age- and sex-adjusted OR for drinkers of 3 or more drinks per day only during meals was 0.59 (0.38–0.91), and the multivariate fully adjusted OR when exdrinkers were excluded was 0.39 (0.22–0.68). No consistent trend in risk was observed among subjects drinking during and outside meals or outside meals only (for 3 or more drinks per day OR = 0.98; 0.49–1.96), and the OR for an increment of 1 drink per day was 1.01 (0.92−1.1). The age- and sex-adjusted OR for drinkers of 3 or more drinks per day during and outside of meals or outside of meals only was 1.02 (0.57–1.83), and the multivariate adjusted OR when exdrinkers were excluded was 0.72 (0.32–1.64). Comparing the trends (excluding nondrinkers) for alcohol during meals only and alcohol outside and during meals or outside meals only, we found a χ12 for interaction of 6.2 (P value = 0.01). For wine drinkers only, the ORs were 0.51 for drinkers of 2 or more drinks per day during meals and 0.75 for those drinking also outside meals.

Association of Drinking Pattern With Acute Myocardial Infarction, Northern Italy, 1995–1999

When subjects drinking outside meals were further split among those drinking both during and outside meals (76 cases and 68 controls) or those drinking only outside meals (17 cases and 13 controls), no heterogeneity could be demonstrated statistically, although the OR was above unity (OR = 2.88; 0.61–13.58) for heavy drinkers (2 or more drinks per day) drinking outside meals only.

Binge drinkers represented a small proportion of this population (10 cases and 7 controls), and the OR for binge drinkers, compared with nondrinkers, was 1.20 (0.36–3.97).


In our study, alcohol drinking during meals was inversely related to acute MI risk, whereas alcohol drinking during and outside meals or outside meals only was not related to risk. In Italy, wine is the most common alcoholic beverage consumed, but we saw no difference by type of alcoholic beverage on the risk of MI.2,5 The results for wine drinkers who consume wine only during meals were similar to those for total alcohol consumed only during meals. It is difficult to make any inference for subjects drinking wine outside of meals, because risk estimates are based on a small number of subjects. However, the OR for increasing 1 drink of wine daily outside of meals was close to 1.0. In the 12-year follow up of the male Health Professional Cohort study, the relative risks for drinkers of ≥30 g/day of total alcohol were 0.57 (0.32–1.03) when less than 25% of total alcohol intake was consumed with meals, 0.51 (0.15–1.77) when 25% to 74%, and 0.33 (0.09–1.27) when 75% or more of total alcohol intake was consumed with meals.3 Although the point estimates for high levels of alcohol drinking agree with our findings, there was no consistent pattern of risk according to the proportion of alcohol consumed with meals.

Alcohol consumed in moderation is thought to reduce the risk of heart disease1 by improving blood lipids, coagulation factors, and blood pressure.9 An additional mechanism could be the hypoglycemic and hypoinsulinemic effects of alcohol when consumed with food.10 Wine has been shown to reduce by approximately 35% the glycemic response of a high-glycemic index food such as white bread.10 High levels of glucose11 and insulin11,12 are known risk factors for heart disease, and alcohol consumption has been associated with a reduced risk of diabetes,13 lower fasting insulin,14 improved glucose,7 and insulin sensitivity,7,14,15 the latter being shown also in a randomized clinical trial.16 Alcohol dose may be important in determining glucose and insulin response, and the ethanol's effect on the blood glucose concentration depends both on the ethanol dose and total glucose flux.17 Moreover, alcohol may have antiinflammatory properties, because moderate alcohol consumption has been associated with lower C-reactive protein concentrations than no or occasional alcohol intake, independently of alcohol-related effects on lipids,18 although the role of pattern of drinking on antiinflammatory parameters remains unclear. Alcohol consumption outside meals results in a faster absorption of ethanol, which could have detrimental effects on blood pressure, mainly in binge drinkers19; in contrast, ingestion of 250 mL of red wine during the noon meal reduced blood pressure of centrally obese hypertensive subjects.20 These vasodilating properties may be important in explaining alcohol effects on insulin action.21

This study was not population-based, but cases and controls were interviewed in the same hospitals and came from the same geographic area. Participation was more than 95% complete. We excluded from the comparison group patients admitted for chronic conditions potentially associated with tobacco smoking and alcohol drinking, as well as diseases related to known or potential risk factors for MI. When traumatic conditions were excluded from controls, the OR for drinkers of 3 or more drinks per day only during meals was 0.53 (0.30–0.93). The potential relation of alcohol drinking and drinking pattern with the risk of MI was unknown to the interviewers and to patients. The similarity of interview setting provided further reassurance against potential information bias. Underreporting of drinking may have occurred, but these alcohol data had satisfactory validity and reproducibility,8,22 and alcohol drinking is socially accepted in Italy. Furthermore, the potential confounding effect of several covariates was taken into account in the analyses.


We thank Ivana Garimoldi for editorial assistance.


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