Alcohol consumption and atrial fibrillation risk: An overview of systematic reviews and network meta-analysis

Hadi, M., Saha, S., Petrie, D., Woode, M.E., Gerdtham, U.F. Drug and Alcohol Review (2026) 45:e70089 doi.org/10.1111/dar.70089
Abstract
Background: Although alcohol consumption is linked to atrial fibrillation (AF), the relationship across different intake levels and between sexes remains unclear. This study presents the first network meta-analysis of prospective cohort studies bringing greater precision to these associations.
Methods: A systematic review identified five meta-analyses on alcohol and AF risk. From these, 13 cohort studies totalling over 80 million person-years were included in a random-effects network meta-analysis, including sex-stratified analyses.
Results: Compared to low-level consumption (< 12 g/day), moderate intake (12–< 24 g/day) slightly increased AF risk (hazard ratio [HR] = 1.07; 95% confidence interval [CI] 1.04–1.10), similar at 24–< 36 g/day (HR = 1.09; 95% CI 1.00–1.20). No significant risk increase was observed for 36–< 60 g/day. Heavy consumption (≥ 60 g/day) showed the highest risk (HR = 2.84; 95% CI 1.57–5.14). Non-drinkers (‘Former’, ‘Never’ or ‘Occasional’) had HRs near 1, except ‘None’, which showed a slight increase (HR = 1.08; 95% CI 1.04–1.11). In males, moderate consumption increased AF risk slightly, while heavy intake had a more pronounced effect (HR = 1.49; 95% CI 1.22–1.81). In females, moderate intake had no significant effect, but heavy intake significantly increased risk (HR = 2.53; 95% CI 1.05–6.08). Conclusions: This network meta-analysis shows a nonlinear relationship between alcohol consumption and AF risk. Low-level or occasional intake poses the lowest risk. In males, moderate consumption slightly increases AF risk, while in females, risk rises substantially only with heavy intake. These findings support limiting alcohol consumption to reduce AF risk and highlight the need for further sex-stratified studies and consideration of sex-specific recommendations. ISFAR Summary The review and meta-analysis by Hadi et al. (2026) summarise the evidence on the association between alcohol consumption and atrial fibrillation (AF). Hadi et al. (2026) report results similar to other meta-analyses, namely that moderate alcohol consumption (12-24 g alcohol/day) slightly increases the risk of AF in men but not in women. Higher drinking levels (>60 g alcohol/day) increase the risk of AF in both genders. The study includes network meta-analyses to explicitly assess associations across different drinking levels and sex subgroups.
The study reports a significantly increased risk of about 7% in moderately drinking men only. This relatively small increase is similar to that observed in non-drinking men, which may cast doubt on the biological relevance of this finding and may indicate a J-shaped relation, if any. Sex-specific physiological mechanisms remain underexplored, and the relevance of other important clinical variables, such as age, hypertension, obesity and other lifestyle factors, is not adequately considered. Also, adequate data on drinking patterns, including the regularity of consumption, binge drinking, and drinking with meals, are lacking. Therefore, a possible confounder, viz. occasions of intoxication, is missing, which may have contributed significantly to the associations reported.
The combination of a lack of drinking pattern data, small effect sizes and residual confounding limits the study’s ability to draw firm conclusions about the causality and clinical significance of alcohol consumption for AF.
ISFAR Critique
Background
Atrial fibrillation (AF) occurs when the electrical signals in the top chambers (atria) of the heart are not conducted properly. These signals should be steady and regular, but instead they quiver or twitch (fibrillation). This causes the heart to beat irregularly, so it does not pump blood as well as it should. Atrial fibrillation is not life-threatening, but it can cause blood clots in the heart that may lead to a stroke. Treatment of AF includes anticoagulants, beta-blockers and calcium channel blockers, which help slow a fast heart rate, and anti-arrhythmic drugs, which help maintain a normal sinus rhythm.
The worldwide prevalence of atrial fibrillation is estimated at 37,574 million cases and increased by 33% during the last 20 years (Lippi et al., 2021). Cases are surging due to an ageing population and higher rates of obesity, diabetes, and hypertension (Vermeer et al., 2024). While not always immediately life-threatening, it causes severe comorbidities, including hypertension, chronic kidney disease and heart failure (Shantsila et al., 2024).
Earlier meta-analyses have generally shown a dose-response increase in AF risk with increasing alcohol consumption, though effects at light to moderate levels have been mixed in prior work (Samokhvalov et al. 2010). Some dose-response studies have also suggested differential patterns by sex and region, but the magnitude and shape vary by methodology (Jiang et al. 2022). Apart from alcohol moderation, however, other lifestyle factors contribute to the management of AF. These include maintaining a healthy body weight (Li et al., 2025), regular moderate exercise (Buckley et al., 2025) and cessation of smoking (Zhu et al., 2016).
This paper by Hadi et al (Hadi et al., 2026) summarises the available data on the association between the lifestyle factor alcohol consumption and AF, providing an overview of previously published meta-analyses and a network analysis based on prospective cohort studies. The latter was intended to provide greater statistical precision for the alcohol consumption—AF association. For example, data were pooled from 13 prospective cohort studies nested within five prior meta-analyses, totalling >80 million person-years of follow-up, thereby increasing statistical precision compared with most prior meta-analyses.
Their results show that moderate alcohol consumption (12-24 g alcohol/day) slightly increased AF risk compared with light drinking (0-12 g alcohol/day) in males only. Higher drinking levels did not increase the risk of AF up to more than 60 g of alcohol per day. When drinking 60+ g of alcohol per day, the risk of AF increased in both men and women.
Critique
This study by Hadi et al. (2026) is another review/meta-analysis summarising results on the association between alcohol consumption and AF. ISFAR discussed previous studies on the alcohol-AF association by Tolstrup et al. (2016) and Ariansen et al. (2020) , . Hadi et al. (2026) used five other recent meta-analyses, namely those of Jiang et al. (2022), Zhang et al. (2022), Yang et al. (2022), Giannopoulos et al. (2022) and (Gallagher et al. (2017). These five meta-analyses were used to substantiate and further analyse previously reported findings by performing general and sex-specific network meta-analyses (NMA), along with heterogeneity and inconsistency tests and comparative rankings. NMA allows simultaneous comparison across multiple drinking categories, including both direct and indirect evidence, which is a methodological advance over traditional pairwise meta-analysis, which typically compares only two groups at a time. This NMA formally integrates evidence across categories and estimates hazard ratios for segmented intake levels.
Hadi et al. (2026) show results similar to other meta-analyses, namely, that moderate alcohol consumption slightly increases the risk for AF in men, but not in women, and higher drinking levels increase the risk for AF in both genders. Indeed, it is one of the first network meta-analyses to explicitly assess associations across different drinking levels and sex subgroups. How alcohol-related AF risk differs between males and females is an important clinical and public health question.
Their NMA shows that the comparisons most often made are those between various control groups (former drinkers, never drinkers, teetotallers, occasional drinkers), light drinkers (0-12 g/day), moderate drinkers (12-24 g/day) and heavy drinkers up to and more than 60 g/day for men and up to 36 g/day for women. This may indicate that all relevant comparisons between drinking groups used for their conclusions were adequately represented in their analysis, except for the higher drinking group comparisons for women.
The meta-analyses show a significantly increased hazard ratio (HR) of 1.076 in the 12-24 g/day consumption group for men. This relatively small increase is similar to the increase observed in non-drinking men (HR 1.050) and occasional drinking women (HR 1.061). Occasional drinking men have a similarly small decrease in HR (HR 0.930), whereas non-drinking women have a somewhat higher increased risk, namely at an HR of 1.135. These small increases and decreases do not have a consistent pattern; men and women are affected differentially, and occasional drinking has an opposite effect in men than in women. Since the HRs are significant but quite small, this may cast doubt on the biological relevance of these findings. Although the authors mention biological mechanisms, including both acute and longer-term effects, no clear, consistent explanation for the observed pattern is provided, nor are the gender differences explained in their discussion of mechanisms.
Although consistency across the outcomes of the various meta-analyses was assessed, with low heterogeneity and non-significant inconsistency, this does not preclude bias arising from shared limitations in the underlying studies. The most important risk factors for AF include ageing, hypertension, obesity and diabetes; however, none of the analyses focused on rigorous and consistent adjustment for these key confounders. Given that important confounding may remain uncorrected and that unknown confounding (for example, drinking pattern) may exist, the findings are most conservatively interpreted as suggesting a positive association between alcohol consumption and AF risk, primarily at high or very high levels of intake. This interpretation is further complicated by differences across cohort studies in how alcohol consumption was measured and categorised, potentially leading to exposure misclassification. Most studies relied on self-reported alcohol intake, which is prone to recall bias and under-reporting. In addition, variation in reference groups (for example, never, former, or occasional drinkers) across cohorts complicates comparisons and the interpretation of risk estimates.
The authors, however, concluded that there is a non-linear relationship between alcohol consumption and AF risk, a conclusion that differs from some of the meta-analyses included in their systematic review and network meta-analysis. Also, their advice to limit alcohol consumption to reduce AF is only supported by the data for moderately drinking men and for men and women drinking more than 60 g of alcohol per day. Their advice could have been phrased as being most relevant for heavily drinking men and women.
While this paper is a valuable contribution that clarifies how different levels of alcohol consumption relate to AF risk and highlights important sex differences, interpretation should remain cautious. This is due to methodological constraints in the underlying observational data, residual confounding, and potentially heterogeneous primary studies. Future research with standardised exposure measurement and rigorous dose-response analyses would further strengthen causal inference.
Specific comments
Forum member Ellison noted that “this paper presents newer statistical approaches for analysing large datasets. I am not qualified to judge the appropriateness of these techniques for assessing the relationship between alcohol consumption and atrial fibrillation (AF), but more knowledgeable members of our Forum consider them appropriate. Personally, however, I am always reluctant to make public recommendations that may be based only on: (1) the amount of alcohol consumed without data on the pattern of drinking; and (2) results from analyses that include data from markedly diverse groups or populations who differ in socioeconomic, educational, and many cultural factors that affect risk, as outlined below:
The present study, as do many other large studies, estimates the effects of alcohol only on the amount reported, without adequate data on the type of alcoholic beverage consumed, the regularity of consumption, how often binge drinking occurs, whether alcohol was consumed with food, and other factors that describe the pattern of drinking. All these details are necessary to determine how safe or unsafe a given amount of alcohol may be regarding its health effects.
Further, by combining data from many different countries and cultures into a single analysis, it is difficult to determine for which group of people (if any) certain recommendations on alcohol consumption based on the results of the study should apply. Unfortunately, the effects of alcohol tend to vary markedly across different cultures. For example, effects often differ between developing and highly developed countries, between cultures in which wine is or is not consumed with meals, between countries where spirits are the most commonly consumed alcoholic beverages, and between countries with markedly different religious restrictions or socioeconomic levels. In any case, recommendations for a specific segment of the population should be based on data from that segment, not on recommendations derived from data collected from widely varying populations.
For me, an elderly, educated white male living in a highly developed country who primarily drinks wine with meals each day, needs to know what the expected net health effects of drinking or not drinking are for people with similar characteristics and a similar drinking pattern.
Forum member Skovenborg suggests that “if you are a moderate drinking male you might choose to lower your intake to one glass of wine per day or raise your intake to between half a bottle to almost a whole bottle per day to eliminate your increased risk of atrial fibrillation. In my book this is a strange behaviour of a risk factor and I am looking in vain for an explanation. I am also at loss for an explanation as to why females are without the male risk for moderate intake. Maybe different drinking patters is the explanation.”
Forum member Goldfinger considers that “atrial fibrillation (AF) is a common dysthymia seen in clinical practice and is often associated with hypertension, hypertensive heart disease, valvular heart disease, particularly mitral valve disease, coronary bypass surgery, congestive heart failure/cardiomyopathy, chronic lung disease/OSA/cor pulmonale, etc.” (Chyou et al., 2015, Kotlyarov and Lyubavin, 2024). Further, a prior history of atrial fibrillation is associated with an increased risk of recurrence (Kisheva and Yotov, 2021)
Although this review attempted to address differences in sex, age and smoking, it is unclear whether there was consistent monitoring for these important comorbidities. The heterogeneity of the studies included certainly makes this quite complicated. It would appear that this study demonstrates a very low risk of primary AF in low to moderate drinkers and a higher risk in heavy drinkers among all comers. Persons with comorbidities that would be associated with a high risk of AF may be outliers with respect to these findings.”
Forum member Romano states that “this article clearly outlines the clinical and epidemiological relevance of atrial fibrillation (AF). It adequately justifies the focus on alcohol as a modifiable risk factor and acknowledges inconsistencies in the existing evidence. The study’s objective is clearly defined. However, the paper implicitly assumes that AF is a homogeneous outcome and does not explore sex-specific biological mechanisms in sufficient depth. The concept of low alcohol consumption is not adequately problematised, and the relevance of other important clinical variables, such as age, hypertension, and additional cardiovascular risk factors, is not sufficiently anticipated.
Regarding methodology, the authors use a network meta-analysis approach, include prospective cohort studies, register the protocol on PROSPERO, standardise alcohol consumption measures, and assess heterogeneity. These methodological choices are clear strengths of the study.
Statistical Analysis Critique
The statistical analysis conducted by Hadi et al. (2026) has notable methodological strengths, alongside important limitations that affect the interpretation of the findings. Among the strengths is the use of a network meta-analysis with random-effects models, an advanced statistical approach that allows simultaneous comparison across multiple levels of alcohol consumption while integrating direct and indirect evidence. This approach is particularly suitable for evaluating dose–response associations when primary studies use heterogeneous exposure categories. In addition, the formal assessment of heterogeneity (I², τ²) and inconsistency enhances transparency and suggests acceptable overall coherence among the included studies.
Nevertheless, several limitations warrant consideration. First, the analysis relies on heterogeneous adjusted estimates from primary studies that did not use a uniform set of adjustment variables. This introduces the risk of residual confounding, as key factors such as age, hypertension, obesity, diabetes, and drinking patterns were not consistently adjusted for across models. By design, network meta-analysis cannot correct for these structural differences between studies.
Second, although statistically significant associations were observed at certain levels of alcohol consumption—particularly among men with moderate intake—the magnitude of the effects was small, with hazard ratios close to unity. This raises questions about the clinical relevance of these findings, especially given the large sample size, which may favour statistical significance even when absolute effects are minimal.
Another important limitation is the absence of continuous modelling of alcohol dose. Categorisation into broad intake intervals (e.g., 12–24 g/day) may mask meaningful within-category variation and limit the ability to identify true risk thresholds. Furthermore, the use of different reference groups (abstainers, former drinkers, occasional drinkers) complicates the interpretation of comparative risk estimates.
Finally, although sensitivity analyses were conducted, they did not adequately address the potential impact of systematic biases shared across studies, such as self-reported alcohol intake and exposure misclassification. The lack of analyses exploring statistical interactions with relevant clinical variables beyond sex further limits the depth of the analysis and its clinical applicability.
Overall, although the statistical analysis is technically sound and appropriate given the available data, the findings should be interpreted with caution. The combination of residual confounding, small effect sizes, and broad exposure categorisation limits the study’s ability to draw firm conclusions about causality and clinical significance.
Additional limitations
Additional limitations of the study include reliance on self-reported alcohol consumption, assumptions about standard drink definitions, lack of evaluation of drinking patterns, heterogeneous exposure categories, and the absence of analyses stratified by additional clinical variables. In summary, the study demonstrates a robust methodology, but one that remains constrained by the inherent limitations of observational data.
The results are presented clearly and indicate a non-linear association between alcohol consumption and AF risk, with analyses stratified by sex. However, confidence intervals are wide, the clinical relevance of moderate consumption remains debatable, residual confounding persists, and further stratified analyses are lacking. Although the findings are coherent, they require cautious interpretation. Sex-specific physiological mechanisms remain underexplored, and the impact of other modifying variables is not adequately addressed.
Future studies should include, or explicitly recommend, comprehensive multivariable analyses and place greater emphasis on causal inference. Overall, the discussion is prudent and conservative, and the conclusions are coherent but remain general.”
Forum member Harding admits to “having long harboured a suspicion of meta-analyses. Blind faith in the idea that the answer must be there somewhere if the collective data is tortured enough glosses over the inconvenient truth that no amount of mathematical wizardry makes the reliability of the underlying studies any more robust. And pooling data from different studies is surely fraught with unreasonable assumptions.
The collection of studies on alcohol and atrial fibrillation (AF) has already been the subject of six meta-analyses, and this study chose to focus on five of them. All five were conducted on a subset of the 23 available studies, each selecting between 9 and 16, depending on the criteria used. They found the following:
Gallagher et al. (2017)
Low intake is not associated with AF.
Moderate intake is associated with AF among men only.
High intake is associated with AF among men and women.
Giannopoulos et al. (2022)
J-shaped relationship for men and women.
Yang et al. (2022)
Low to moderate intake is associated with an increased risk of AF in males but not in females.
Moderate intake is associated with an increased risk in Europeans and Asians, but not in Americans.
Low intake increases the risk in Europeans, but not in North Americans.
Moderate beer consumption generally increases the risk.
Jiang et al. (2022)
The risk of AF increases linearly in men, but in women it follows a J-shaped relationship.
Zhang et al. (2022)
At low intakes, there was no effect on AF.
Moderate intakes increased the risk in males but not in females.
In other words, a mess of disparate conclusions. They can’t all be right. Hadi and his colleagues have had another go and selected 13 cohort studies (I counted 15) for a ‘random-effects network meta-analysis’. They concluded that:
Low-level intake carries the lowest risk of AF;
Moderate consumption slightly increases the risk of AF in males, but not in females; and
In females, the risk of AF rises only with heavy intake.
I noticed another conclusion mentioned in the Discussion (first paragraph), but not in the Abstract or Conclusions, that ‘abstaining from alcohol was linked to a subtle but significantly higher level of risk’. In other words, a J-shaped relationship. Overall, I conclude that this meta-analysis adds no more to the sum of human knowledge than the others.
Colleagues have already pointed out the woeful lack of attention paid to drinking patterns in this paper (and indeed also in the other five). And given that atrial fibrillation is known as ‘holiday heart syndrome’, i.e. caused by binge drinking, this is a major flaw. All this data could be explained by occasions of intoxication, no matter what the overall level of alcohol consumption of individuals. It could be as simple as that.
The Discussion section speculates on what mechanisms might explain the associations observed in these epidemiological studies, indicating the way forward. There is already more than enough to justify further studies to test these possible mechanisms, and that is what is needed, not more epidemiology like this. Physicist Ernest Rutherford said, ‘If your experiment needs statistics, you ought to have done a better experiment’.
Forum member Mattivi muses that “several colleagues have already highlighted the chronic lack of in-depth analyses (in the reviewed studies and in the meta-analysis) of alcohol consumption patterns, as well as the complete absence of biomarkers to verify the veracity of the collected data, which is essentially based on participants’ self-reports.
I struggle to understand how studies structured in this way can provide reliable answers to such specific questions about holiday heart syndrome (HHS). HHS refers to acute heart rhythm disturbances, most commonly atrial fibrillation (AF), induced by hangovers, often during holidays, weekends, or celebrations. I would, therefore, have expected an experimental design that takes this relevant aspect into account.”
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Comments on this critique by the International Scientific Forum on Alcohol Research were provided by the following members:
Henk Hendriks, PhD, Independent consultant and partner of the Nutrition Consultants Cooperative, Netherlands
Creina Stockley, PhD, MBA, Independent consultant and Adjunct Senior Lecturer in the School of Agriculture, Food and Wine at the University of Adelaide, Australia
R. Curtis Ellison, MD, Section of Preventive Medicine/Epidemiology, Boston University School of Medicine, Boston, MA, USA
Andrew L. Waterhouse, PhD, Professor Emeritus of Enology, Department of Viticulture and Enology, University of California, Davis, CA, USA
Tedd Goldfinger, DO, FACC, Desert Cardiology of Tucson Heart Center, University of Arizona School of Medicine, Tucson, AZ, USA
Raquel Romano, PhD, Independent consultant and Professor of Applied Technology at the University of Aconcagua, Argentina
Richard Harding, PhD, Formerly Head of Consumer Choice, Food Standards and Special Projects Division, Food Standards Agency, UK
Erik Skovenborg, MD, specialized in family medicine, member of the Scandinavian Medical Alcohol Board, Aarhus, Denmark