Alcohol consumption and erectile dysfunction: meta-analysis of population-based studies


Alcohol is long regarded as a risk factor for erectile dysfunction (ED), but epidemiological evidence has been equivocal. We aimed to investigate the ED risk associated with various levels of alcohol consumption by meta-analysis. We searched for population-based studies on ED through Medline, PubMed, PsychInfo, and scanned through reference lists. Eleven cross-sectional studies were included and analyzed with random effects model. We reviewed the results from one cross-sectional study and two cohort studies. Regular alcohol consumption was negatively associated with ED (odds ratio (OR)=0.79; 99% confidence interval (CI), 0.67–0.92; P<0.001). Consumption of 8 or more drinks/week significantly reduced the risk of ED (OR=0.85; 99% CI, 0.73–0.99; P=0.007), but consumption of less alcohol (1–7 drinks/week) was not significant (OR=0.73; 99% CI, 0.44, 1.20; P=0.101). Begg's test and Egger's test detected no significant publication bias. Our estimates (in sensitivity analyses) were rendered nonsignificant when International Index of Erectile Function definition was used and when statistical adjustment was made only for age. Meta-analysis of cross-sectional studies yielded a protective association of alcohol on ED, but the two cohort studies did not demonstrate any significant findings for alcohol consumption. More research is needed to confirm whether alcohol is protective or is unrelated to ED development.


Alcohol is long regarded as a risk factor for erectile dysfunction (ED), whether in textbooks,1, 2 review articles3, 4 or clinical teachings. It was a long-held empirical observation that acute alcohol intoxication increases sexual desire but inhibits sexual performance (Macbeth, Act 2, Scene 3, ‘What three things does drink especially provoke… lechery, sir, it provokes, and unprovokes; it provokes the desire, but it takes away the performance’). The scientific explanation is that alcohol is a central nervous system depressant2, but it also leads to disinhibition and increases sexual desire.

Epidemiological studies have demonstrated numerous risk factors for ED, such as age,5 variables related to diabetes,6 depression,7 hypertension6 and smoking.8 With more accumulating evidence, the risk of alcohol consumption in ED seemed more equivocal. ED has also been said to be the harbinger of cardiovascular events.9 Endothelial dysfunction has been hypothesized to result from cardiovascular risk factors such as hypertension or diabetes, which in turn leads to ED, myocardial infarction and stroke.10 As evidence accumulates to support the similarity in cardiovascular risk factor profiles11 of ED and cardiovascular diseases, it was fair to hypothesize that alcohol may demonstrate a J-shaped (or inverse) relationship with ED, with moderate alcohol consumption conferring the lowest risk of ED. Furthermore, considering the scale of the studies done on cardiovascular diseases and that of ED, it was not surprising that perhaps ED studies were simply not large enough to delineate the risk of ED associated with alcohol consumption.

It was the aim of this paper to use meta-analysis to pool the risk of regular alcohol consumption associated with ED.


We searched for population-based studies on ED published between 1990 to April 2006. We searched through Medline, PubMed, PsychInfo, and scanned through reference lists. We used keywords to search for our disease of interest (for example, ED, impotence, sexual dysfunction) and the type of studies that were of relevance (for example, prevalence, epidemiology, incidence), and used the ‘AND’ search string to narrow down the search to overlapping studies. Whole texts were retrieved and read.

Studies were included if they were population-based studies on ED, and provided age-adjusted ORs for alcohol. If multivariate (including age-adjusted) ORs were provided they were used for statistical analysis in preference to the univariate age-adjusted ORs. Since our preliminary search identified mainly cross-sectional studies, we added the cross-sectional design as an inclusion criteria.

No established quality assessment guidelines were available on cross-sectional studies, and the assessment instrument designed for prevalence study by Prins et al.12 was adapted, expanded for this study. We added to the quality assessment a number of risk factors that were commonly adjusted for in various population-based prevalence studies. Note that the subscale score for ‘statistical adjustments for odds ratios’ was not the total number of variables adjusted for in the original article, the actual number adjusted for is found in Table 1 or in the parentheses in Figures 1, 2 and 3.

Table 1 An overview of the eligible studies
Figure 1

Forest plot for regular alcohol consumption (yes/no).

Figure 2

Forest plot for consuming 1–7 drinks/day.

Figure 3

Forest plot for consuming 8 or more drinks/day.

Two of the investigators (CJ and KJ) independently rated and extracted data from each study, and any disagreements were resolved through discussion to obtain a consensus before including data in the analysis.

Data were extracted according to a fixed protocol: year of study, definition of ED, response rate, sample size, OR, variables adjusted for OR. Two different meta-analyses were formed, one that defined alcohol consumption as having two categories (yes or no), and another that defined them as having three categories (none, 1–7 drinks, 7 or more drinks). If an included study used a three-category definition of alcohol, a pooled estimate would be calculated for the two categories, and the estimate would represent ‘above average alcohol consumption’ and be used in the meta-analysis for the two-category analysis. On the other hand, if a study used a two-category definition, the resulting OR would not be included in the meta-analysis for the three-category analysis.

Weighted average of ORs were calculated using the inverse variance method for random effects models. Adjusted ORs were converted to the logarithmic scale for statistical calculation and anti-logged for final results.

Representative data in the absence of publication bias should (1) follow a symmetrical distribution around the true value (for example, OR) and (2) the variability of the data should increase as the standard error of the data increases. Hence, when representative data are plotted against their standard errors, they should form a symmetrical funnel, and any asymmetries in a funnel plot could be caused by publication bias (unrepresentativeness). We used Begg's test and Egger's test to test for publication bias based on the symmetry assumption described.

Heterogeneity between studies and in the meta-analysis estimates was evaluated by the χ2 test (I2 indicates variation in OR attributable to heterogeneity and τ2 the variance between the included studies).

A wider 99% confidence interval (CI) was used for each estimate to allow for multiple comparisons. All statistical calculations were performed by STATA version 8.0.


Our initial search identified 221 articles, but only 11 cross-sectional studies13, 14, 15, 16, 17, 18, 19, 20, 21, 22 documented the adjusted OR for alcohol, another cross-sectional study23 and a prospective cohort24 from the same study population provided adjusted relative risks (RR), one cohort study25 provided adjusted OR. Only the 11 cross-sectional studies that provided adjusted ORs will be included in the meta-analysis, since the other two cohort studies were of different study design, and the RR reported by the cross-sectional and cohort studies were derived with a different statistical method (Mantel–Haenszel rather than logistic regression). Relevant findings will be summarized below for the three latter studies. An overview of the studies is provided in Table 1. An overview of the quality appraisal is shown in Tables 2 and 3. A significant level of heterogeneity was found between studies (P<0.001), and the random effects model was used and its results are included below.

Table 2 Year published and quality assessment of selected studies
Table 3 Criteria for the methodology quality assessment of prevalence studies. (Adapted and expanded from Prins et al.)

Two-category response model for alcohol

Regular alcohol consumption was negatively (protective effect) associated with ED (odds ratio (OR)=0.79; 99% CI, 0.67–0.92; P<0.001) (heterogeneity χ2=43.12, P<0.001; I2=76.8%; τ2-statistic=0.0243) (Figure 1).

Three-category response model for alcohol

Having ‘1–7 drinks/week’ (OR=0.73; 99% CI, 0.44–1.20; P=0.101) (heterogeneity χ2=44.34, P<0.001; I2=91.0%; τ2-statistic=0.1607) (Figure 2) and ‘8 drinks or more/week’ (OR=0.85; 99% CI, 0.73–0.99; P=0.007) (heterogeneity χ2=2.66, P=0.265; I2=24.7%; τ2 statistic=0.0034) (Figure 3) were negatively associated with ED.

Bias, influence and robustness

A funnel plot is shown in Figure 4. Begg's test (P=0.533) and Egger's (P=0.157) test did not detect significant publication bias.

Figure 4

Funnel plot for publication bias.

Influence analysis for the random effects model did not demonstrate any large changes to the summary estimates due to the omission of any one study.

Sensitivity analysis (Figure 5) demonstrated statistical significance for both random effects model (OR=0.79; 99% CI, 0.67–0.92; P<0.001) and fixed effects model (OR=0.86; 99% CI, 0.81–0.91; P<0.001), but they did not differ significantly (P=0.2117). Only the self-reported single question ED definition yielded a statistically significant summary estimate (OR=0.73; 99% CI, 0.61–0.88; P<0.001), but not the International Index of Erectile Function (IIEF) definition (OR=0.95; 99% CI, 0.65–1.40; P=0.739), and they did not differ significantly (P=0.1057). Summary estimates for sample sizes less than 2000 (OR=0.62; 99% CI, 0.43–0.88; P=0.001) and more than 2000 (OR=0.85; 99% CI, 0.73–0.99; P=0.007) differed significantly (P=0.0400). Only statistical adjustments for ‘age and other variables’ demonstrated statistically significant OR (OR=0.84; 99% CI, 0.72–0.97; P=0.002), but not age adjustment alone (OR=0.74; 99% CI, 0.50–1.09; P=0.047), and the estimates did not differ significantly.

Figure 5

Sensitivity analysis. Solid line indicates OR=1.

Cross-sectional and cohort studies with RR (HPFS)

The Health Professionals Follow-up Study (HPFS)23, 24 provided much evidence on the influence of lifestyle factors on the development of ED.

The HPFS cross-sectional study23 involved 31 742 men aged 53–90 and was probably the largest cross-sectional study on ED to date. The multivariate-adjusted RR for ED were decreased with moderate levels of alcohol consumption. The RRs were 1.0 (0.9–1.2), 0.9 (0.8–1.0), 0.8 (0.7–1.0) and 1.0 (0.8–1.2) for 0.1–4.9, 5.0–14.9, 15–29.9, 30.0 g/day of alcohol consumption respectively (using 0 g/day as reference), after adjustments for comorbidity, medication, smoking status, physical activity, television watching, body mass index (BMI) and other factors.

The HPFS prospective cohort study24 demonstrated the independent effects of physical activity (RR 0.7, 95% CI, 0.7–0.8), obesity (multivariate RR 1.9, 95% CI, 1.6–2.2) and smoking (RR 1.5, 95% CI, 1.3–1.7) on the development of ED. Around 51 529 health professional men were recruited at baseline, after inclusion of those who were healthy at baseline and exclusion of those lost to follow-up, 22 086 men were computed in the analysis. No significant difference in risk of developing ED was found in all categories of alcohol consumption: multivariate adjusted RR 1.0 (0.9–1.1), 1.0 (0.9–1.1), 1.0 (0.9–1.1) and 1.1 (1.0–1.2), for 0.1–4.9, 5.0–14.9, 15–29.9, 30.0 g/day of alcohol consumption respectively (using 0 g/day as reference). Statistical adjustments were made for age, marital status, smoking, alcohol and BMI.

ED was defined as having poor or very poor ability in the previous 3 months to have and maintain an erection adequate for intercourse. Mantel–Haenszel statistics was used in both papers to calculate RR, rather than logistic regression.

Cohort study (MMAS)

The Massachusetts Male Aging Study (MMAS)25 involved a baseline cohort of 1709 men, but the analysis was restricted to only 513 men without ED at baseline. The adjusted incidence for ED was 16% (95% CI, 12–22), 16% (11–23) and 15% (8–24) in those with <1 drink/day, 1–3 drinks/day and 4 drinks/day of alcohol consumption respectively. This incidence figure was adjusted for age, active and passive smoking, overweight, hypertension, physical activity, cholesterol, fat intake, testosterone, depression and antihypertensive medication intake. It is also found that the OR (adjusted for the same variables) for ED was 0.95 (95% CI, 0.54–1.67) and 0.87 (0.41–1.86) in those with 1–3 drinks/day and 4 drinks/day of alcohol consumption respectively, using <1 drink/day as reference, although the result was not statistically significant.

ED was defined according to NIH consensus as not ‘being able to get and keep an erection that is rigid enough for satisfactory sexual activity.’


A handful of studies26, 27, 28 have documented the harmful effects of chronic alcohol consumption on sexual functioning but hardly any study found potential beneficial effects of alcohol on ED. We have demonstrated through meta-analysis the possible beneficial effects of alcohol on ED.

The relationship between alcohol and ED was complex from the data: consuming 1–7 drinks/week appeared to confer the lowest risk (OR=0.73; P=0.101) but it was not statistically significant, and only 8 or more drinks/week was significant (OR=0.85; P=0.007). It appears that alcohol consumption, much similar to its relationship with cardiac survival, is related to sexual function in a J-shaped manner, with moderate consumption conferring highest protection and higher consumption conferring less benefits.

Considering that ED and heart diseases share similar cardiovascular risk factors, and the well-known chronic cytotoxic effects of alcohol on general health,29 hepatic function30 and immune function,31 general health might be a mediator between the association of high alcohol consumption and ED. This J-shaped relationship finding might explain why studies have shown harmful effects of heavy alcoholism on sexual function, that is alcoholism entails excessive drinking and carries the increased risk of ED at the tail of the J curve. However, caution has to be exercised in the extrapolation, as our results did not show a statistically significant OR for consuming 1–7 drinks/week, and did not demonstrate any harmful effects of alcohol on sexual function. In fact, three large studies9, 16, 18 have demonstrated progressively smaller ORs of ED for increasing levels of alcohol consumption.

We attempted to identify the cutoff level of alcohol consumption where risks outweigh benefits, by identifying the ‘number of drinks/week’ that has an OR closest to 1. To our surprise, the category ‘8 or more drinks/week’ generated an OR that barely missed the unity and was statistically significant. Although we were unable to pinpoint the level of alcohol consumption where risks (OR>1) outweigh benefits (OR<1), we were at least able to say that ‘8 or more drinks/week’ is likely to be a cutoff where the OR for ED becomes less than 1. Whether consuming more or less alcohol would yield a smaller OR was indeterminate.

The results from the two cohort studies complicated the picture even further: they did not show any significant effects of alcohol consumption on ED. The cross-sectional analysis of the HPFS data demonstrated a protective association of alcohol on ED, much in a J-shaped manner, but after follow-up of the subjects the cohort analysis did not find any significant associations between alcohol consumption and ED. Since the level of evidence from a cohort study is generally higher than from a cross-sectional study, due to less confounding and recall bias, the evidence from the HPFS cohort should weigh more heavily in our analysis. This suggests that the apparent protective association of alcohol consumption on ED was probably due to confounding (since recall, selection, observer and volunteer biases were less likely in the selected population-based cross-sectional studies). However, the sensitivity analysis demonstrated a significant protective association of alcohol consumption with higher level of statistical adjustments (less confounding), not with age adjustment alone (more confounding), and suggests that with better statistical adjustments (reduction of confounding) the demonstration of protective association might be possible. The sensitivity analysis on study sample size found that smaller studies demonstrated larger effects than larger studies, and might suggest that the estimate obtained from larger studies would be more reliable (effect towards null), although their estimates did not differ significantly. The relative importance of each study with regard to their sample sizes was taken care of by the differential weighting of the random effects model.

A major limitation of previous population-based studies was their relatively small sample sizes, and we sought to overcome this sample size problem by pooling data across studies, although we suspected that the OR for ‘1–7 drinks/week’ was not statistically significant due to inadequate sample size.

The meta-analyses had four limitations, (1) confounding, (2) definitions of ED and alcohol consumption, (3) weak causal inference and (4) heterogeneity.

Limitation 1

Confounding can reduce the internal validity of a study, and since ED is a multifactorial disorder, the association between alcohol and ED as demonstrated could be confounded by some other factors not adjusted for. First, the effect size for alcohol consumption was not large, and the significant effect could be due to residual confounding. Second, we obtained pooled estimates based on ORs that were adjusted for different numbers of variables from different studies, and therefore each included study had a different level of confounding. Our minimum requirement for inclusion was that the ORs had to be age-adjusted, other than this if more variables were adjusted for the better. However referring to Figure 1, if confounding was a problem, one would find ORs that were adjusted for more variables to lie closer to unity (that is, no effect) and those that were only age-adjusted to be closer to zero (that is, protective association), but this did not appear to be the case.

Limitation 2

Alcohol consumption was assessed in many ways, one by grams of alcohol, and most by the number of drinks/week, but the categories were different. We took a conservative approach in pooling the data, for example, if the categories in Millett et al.'s17 study were none/1–4/4 drinks/week, we excluded the OR for the ‘open-ended’ 4 drinks/week and only included the OR for 1–4 drinks/week into our final 1–7 drinks/week category, and likewise we only included the OR for 3–4 drinks/week from Cho et al.'s21 study in the 1–7 drinks/week category. We believe that this conservative approach in pooling the results should ensure the reliability of our results.

The included studies used two broad definitions of ED, one that was based on IIEF-5 or IIEF-15, and the other that was based on a single self-reporting question. Sensitivity analysis showed that the summary estimates based on each definition were different, and only the self-reported one was significant (OR=0.73; 99% CI, 0.61–0.88; P<0.001) but not the IIEF one (OR=0.95; 99% CI, 0.65–1.40; P=0.739), and the latter was not statistically significant. This finding raises serious doubts to the use of single question self-reported composite measures of ED, which many studies worldwide used, since it appears that the summary estimate for each definition was different. However, since the estimates did not differ significantly (P=0.1057), this difference could be due to chance.

Limitation 3

Causal inference from the cross-sectional design is weak. The alternatives for better causal inference are either a cohort study or a randomized controlled trial, but in either case few studies have been done. We sought to support our meta-analysis results with the research findings from cohort studies (MMAS and HPFS), but the cohorts did not demonstrate any significant relationships between alcohol consumption and risk of ED. The cross-sectional HPFS supported our meta-analysis results of the cross-sectional studies in demonstrating a significant protective association, but the cohort HPFS did not, and this suggests that the protective association demonstrated in cross-sectional studies might have resulted from confounding. Another possible explanation was that men who developed ED opted not to drink alcohol, whereas men without ED continued to drink alcohol. As a result, an apparent ‘harmful effect’ of not drinking alcohol was found, which was the inverse of protective association of drinking alcohol in terms of ORs. Since the cohort study design has better causal inference, the results from the two cohort studies suggest that alcohol neither causes nor prevents ED from developing. Also, the statistical association was found after pooling a large number of studies, and may have limited biological significance for an individual drinker.

Limitation 4

We found significant heterogeneity in two of the three meta-analysis estimates. In general, there can be many sources of heterogeneity in meta-analysis, and we can only surmise the sources in this study, which may include varying number of controlled confounders, different definitions of ED and alcohol consumption and the diverse populations included. We used the random effects model that is preferred to the fixed effects model when significant heterogeneity exists.

The geographical regions covered in this meta-analysis include South America (Brazil), Europe (Italy, Belgium), Africa (Egypt, Nigeria), Middle East (Turkey) and Asia-Pacific (Australia, China, Japan, Korea, Malaysia, Pakistan). Therefore our results have limited generalizability to other regions (for example, North America).

Two reasons might have propagated the myth that alcohol consumption is a risk factor for ED. First, that alcohol consumption enhanced sexual desire but impaired sexual performance is perhaps a short-lived effect of alcohol and will not cause ED permanently. Second, that severe alcoholism impairs sexual functions may be an extreme example and is confounded by underlying deterioration of general health, and unless it is excessive it is unlikely to cause ED permanently. More research has to be done to assess the association between acute (we did not investigate) and chronic (which we investigated) alcohol consumption and development of ED, particularly using large-scale cohorts since randomized controlled trials may be unethical.

This is the first study that systematically reviewed and meta-analyzed the association between alcohol consumption and ED. Our meta-analysis found a significant protective association of regular (chronic) alcohol consumption on ED in cross-sectional studies, in particular for the consumption of 8 or more drinks/week. Evidence from large cohort studies suggests that regular alcohol consumption is not significantly associated with ED development. Therefore this study has demonstrated, in the least, that chronic alcohol consumption is not a risk factor for ED. We hope to demonstrate with the results of this study that the association between alcohol consumption and development of ED might not be as straightforward as it seemed, and the undue popularity of alcohol being labeled as a risk factor for ED was probably unjustified since there was little research evidence to support it.


  1. 1

    Rosen RC, Goldstein I . Sexual dysfunction. In: Warrell DA, Cox TM, Firth JD, Benz EJ (eds), Oxford Textbook of Medicine, 4th edn Oxford University Press: Oxford, 2003.

    Google Scholar 

  2. 2

    Sadock VA . Normal human sexuality and sexual dysfunctions. In: Sadock BJ, Sadock VA (eds), Kaplan & Sadock's Comprehensive Textbook of Psychiatry, 8th edn Lippincott Williams & Wilkins: Philadelphia, PA, 2005.

    Google Scholar 

  3. 3

    Carbone Jr DJ, Seftel AD . Erectile dysfunction. Diagnosis and treatment in older men. Geriatrics 2002; 57: 18–24.

    PubMed  PubMed Central  Google Scholar 

  4. 4

    Hutter Jr AM . Role of the cardiologist: clinical aspects of managing erectile dysfunction. Clin Cardiol 2004; 27 (Suppl 1): I3–I7.

    Article  Google Scholar 

  5. 5

    Nicolosi A, Moreira Jr ED, Shirai M, Bin Mohd Tambi MI, Glasser DB . Epidemiology of erectile dysfunction in four countries: cross-national study of the prevalence and correlates of erectile dysfunction. Urology 2003; 61: 201–206.

    Article  Google Scholar 

  6. 6

    Seftel AD, Sun P, Swindle R . The prevalence of hypertension, hyperlipidemia, diabetes mellitus and depression in men with erectile dysfunction. J Urol 2004; 171 (6 Part 1): 2341–2345.

    Article  Google Scholar 

  7. 7

    Seidman SN . The aging male: androgens, erectile dysfunction, and depression. J Clin Psychiatry 2003; 64 (Suppl 10): 31–37.

    PubMed  Google Scholar 

  8. 8

    Lam TH, Abdullah AS, Ho LM, Yip AW, Fan S . Smoking and sexual dysfunction in Chinese males: findings from men's health survey. Int J Impot Res 2006; 18: 364–369.

    CAS  Article  Google Scholar 

  9. 9

    Thompson IM, Tangen CM, Goodman PJ, Probstfield JL, Moinpour CM, Coltman CA . Erectile dysfunction and subsequent cardiovascular disease. JAMA 2005; 294: 2996–3002.

    CAS  Article  Google Scholar 

  10. 10

    Le NA . Inflammation, oxidative stress, and atherosclerosis. Curr Opin Lipidol 2004; 15: 227–229.

    CAS  Article  Google Scholar 

  11. 11

    Thomas GN, Tomlinson B, Abdullah AS, Yeung VT, Chan JC, Wong KS . Association of erectile dysfunction with cardiovascular risk factors and increasing existing vascular disease in male chinese type 2 diabetic patients. Diabetes Care 2005; 28: 2051–2053.

    Article  Google Scholar 

  12. 12

    Prins J, Blanker MH, Bohnen AM, Thomas S, Bosch JL . Prevalence of erectile dysfunction: a systematic review of population-based studies. Int J Impot Res 2002; 14: 422–432.

    CAS  Article  Google Scholar 

  13. 13

    Shaeer KZ, Osegbe DN, Siddiqui SH, Razzaque A, Glasser DB, Jaguste V . Prevalence of erectile dysfunction and its correlates among men attending primary care clinics in three countries: Pakistan, Egypt, and Nigeria. Int J Impot Res 2003; 15 (Suppl 1): S8–S14.

    Article  Google Scholar 

  14. 14

    Moreira Jr ED, Lisboa Lobo CF, Villa M, Nicolosi A, Glasser DB . Prevalence and correlates of erectile dysfunction in Salvador, northeastern Brazil: a population-based study. Int J Impot Res 2002; 14 (Suppl 2): S3–S9.

    Article  Google Scholar 

  15. 15

    Akkus E, Kadioglu A, Esen A, Doran S, Ergen A, Anafarta K et al. Prevalence and correlates of erectile dysfunction in Turkey: a population-based study. Eur Urol 2002; 41: 298–304.

    Article  Google Scholar 

  16. 16

    Bai Q, Xu QQ, Jiang H, Zhang WL, Wang XH, Zhu JC . Prevalence and risk factors of erectile dysfunction in three cities of China: a community-based study. Asian J Androl 2004; 6: 343–348.

    PubMed  PubMed Central  Google Scholar 

  17. 17

    Millett C, Wen LM, Rissel C, Smith A, Richters J, Grulich A et al. Smoking and erectile dysfunction: findings from a representative sample of Australian men. Tob Control 2006; 15: 136–139.

    CAS  Article  Google Scholar 

  18. 18

    Parazzini F, Menchini Fabris F, Bortolotti A, Calabro A, Chatenoud L, Colli E et al. Frequency and determinants of erectile dysfunction in Italy. Eur Urol 2000; 37: 43–49.

    CAS  Article  Google Scholar 

  19. 19

    Mak R, De Backer G, Kornitzer M, De Meyer JM . Prevalence and correlates of erectile dysfunction in a population-based study in Belgium. Eur Urol 2002; 41: 132–138.

    Article  Google Scholar 

  20. 20

    Fedele D, Bortolotti A, Coscelli C, Santeusanio F, Chatenoud L, Colli E et al. Erectile dysfunction in type 1 and type 2 diabetics in Italy. On behalf of Gruppo Italiano Studio Deficit Erettile nei Diabetici. Int J Epidemiol 2000; 29: 524–531.

    CAS  Article  Google Scholar 

  21. 21

    Cho BL, Kim YS, Choi YS, Hong MH, Seo HG, Lee SY et al. Prevalence and risk factors for erectile dysfunction in primary care: results of a Korean study. Int J Impot Res 2003; 15: 323–328.

    CAS  Article  Google Scholar 

  22. 22

    Terai A, Ichioka K, Matsui Y, Yoshimura K . Association of lower urinary tract symptoms with erectile dysfunction in Japanese men. Urology 2004; 64: 132–136.

    Article  Google Scholar 

  23. 23

    Bacon CG, Mittleman MA, Kawachi I, Giovannucci E, Glasser DB, Rimm EB . Sexual function in men older than 50 years of age: results from the health professionals follow-up study. Ann Intern Med 2003; 139: 161–168.

    Article  Google Scholar 

  24. 24

    Bacon CG, Mittleman MA, Kawachi I, Giovannucci E, Glasser DB, Rimm EB . A prospective study of risk factors for erectile dysfunction. J Urol 2006; 176: 217–221.

    Article  Google Scholar 

  25. 25

    Feldman HA, Johannes CB, Derby CA, Kleinman KP, Mohr BA, Araujo AB et al. Erectile dysfunction and coronary risk factors: prospective results from the Massachusetts male aging study. Prev Med 2000; 30: 328–338.

    CAS  Article  Google Scholar 

  26. 26

    Schiavi RC . Chronic alcoholism and male sexual dysfunction. J Sex Marital Ther 1990; 16: 23–33.

    CAS  Article  Google Scholar 

  27. 27

    Smith DE . Alcoholism, recovery, and sexual dysfunction. Psychiatr Med 1985; 3: 163–172.

    CAS  PubMed  Google Scholar 

  28. 28

    Okulate G, Olayinka O, Dogunro AS . Erectile dysfunction: prevalence and relationship to depression, alcohol abuse and panic disorder. Gen Hosp Psychiatry 2003; 25: 209–213.

    Article  Google Scholar 

  29. 29

    Hart CL, Smith GD, Hole DJ, Hawthorne VM . Alcohol consumption and mortality from all causes, coronary heart disease, and stroke: results from a prospective cohort study of scottish men with 21 years of follow-up. BMJ 1999; 318: 1725–1729.

    CAS  Article  Google Scholar 

  30. 30

    Lieber CS . Alcoholic liver disease: new insights in pathogenesis lead to new treatments. J Hepatol 2000; 32 (1 Suppl): 113–128.

    CAS  Article  Google Scholar 

  31. 31

    Happel KI, Nelson S . Alcohol, immunosuppression, and the lung. Proc Am Thorac Soc 2005; 2: 428–432.

    CAS  Article  Google Scholar 

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Cheng, J., Ng, E., Chen, R. et al. Alcohol consumption and erectile dysfunction: meta-analysis of population-based studies. Int J Impot Res 19, 343–352 (2007).

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