Alcohol Intake

Life Expectancy, and All-Cause Mortality: A Comprehensive Review

1. Introduction

The relationship between alcohol intake, life expectancy, and all-cause mortality has been a subject of extensive research and ongoing debate. While some observational studies have suggested that light-to-moderate alcohol consumption may confer protective effects, particularly against cardiovascular disease, more recent genetic and methodologically robust studies challenge this notion, indicating a linear increase in mortality risk with higher alcohol intake and no clear protective threshold. The evidence is further complicated by variations in drinking patterns, beverage types, population subgroups, and confounding factors such as smoking and socioeconomic status. Notably, Mendelian randomization studies and large-scale prospective cohorts increasingly suggest that even modest alcohol consumption may elevate the risk of premature death, with heavy and binge drinking consistently associated with higher all-cause and cause-specific mortality, including cancer and cardiovascular disease [1] [2] [3] [4] [5] [6] [7] [8] [9] [10]. This review synthesizes findings from diverse study designs to clarify the dose-response relationship between alcohol intake and mortality, the impact of drinking patterns, and the implications for public health guidelines.

2. Methods

A comprehensive literature search was conducted across over 170 million research papers in Consensus, including sources such as Semantic Scholar and PubMed. The search strategy targeted studies on alcohol intake, life expectancy, and all-cause mortality, with a focus on dose-response relationships, population subgroups, and confounding factors. In total, 993 papers were identified, 413 were screened, 334 were deemed eligible, and the top 50 most relevant papers were included in this review.

Identification	Screening	Eligibility	Included
993	413	334	50

3. Results

3.1 Dose-Response Relationship and Threshold Effects

Recent Mendelian randomization and large-scale cohort studies indicate a linear or J-shaped association between alcohol intake and all-cause mortality. Genetically predicted alcohol consumption shows a strong linear increase in mortality risk, with no evidence of a protective effect at low or moderate intake levels [1] [3] [4]. Observational studies often report a J-shaped curve, with the lowest mortality risk at light-to-moderate intake (typically <10–15 g/day), but these findings are increasingly attributed to confounding and selection biases [11] [2] [12] [13] [8] [9].

3.2 Impact of Heavy and Binge Drinking

Heavy alcohol consumption (>20–30 g/day or >2 drinks/day) and binge drinking are consistently associated with increased all-cause, cancer, and cardiovascular mortality [11] [14] [2] [3] [15] [16] [17] [18]. Binge drinking, even at lower average intakes, elevates mortality risk, particularly from cancer and accidents [14] [2] [16].

3.3 Patterns, Beverage Types, and Drinking Habits

Drinking patterns (frequency, with meals, beverage type) modify risk. Wine, especially red wine, consumed with meals and spread over several days per week, is associated with lower mortality compared to spirits or beer [10] [19] [20]. However, these associations may reflect residual confounding by socioeconomic and lifestyle factors [20] [19] [21]. Stable light or moderate drinking appears less harmful than irregular or heavy episodic drinking [22] [13] [20].

3.4 Population Subgroups and Confounding Factors

Sex, age, comorbidities, and social vulnerability influence the alcohol-mortality relationship. Some studies report more pronounced protective effects in older adults and women, but these are often attenuated after adjusting for confounders [23] [24] [6] [8] [25]. Genetic studies in East Asian populations and twin studies suggest that familial and genetic factors may account for observed protective associations in some cohorts [3] [21] [4] [26].

Results Timeline

• 1995 — 1 paper: [24]
• 1997 — 1 paper: [27]
• 2009 — 1 paper: [10]
• 2017 — 2 papers: [14] [5]
• 2018 — 2 papers: [12] [6]
• 2020 — 2 papers: [23] [19]
• 2021 — 5 papers: [11] [28] [29] [20] [30]
• 2022 — 1 paper: [13]
• 2023 — 2 papers: [2] [3]
• 2024 — 2 papers: [1] [31]
• 2025 — 1 paper: [22]

Figure 2: Timeline of key studies on alcohol intake and all-cause mortality. Larger markers indicate more citations.

Top Contributors

Type	Name	Papers
Author	J. Rehm	[32] [5]
Author	R. Room	[22] [5]
Author	C. Ricci	[33] [34]
Journal	Addiction	[11] [5] [6] [17]
Journal	The BMJ	[8] [34]
Journal	Journal of Epidemiology & Community Health	[10] [18] [35]

Figure 3: Authors & journals that appeared most frequently in the included papers.

4. Discussion

The evidence base for the relationship between alcohol intake and all-cause mortality has evolved significantly. While earlier observational studies suggested a J- or U-shaped curve with potential protective effects of light-to-moderate drinking, more recent genetic and methodologically rigorous studies challenge this, indicating that any increase in alcohol intake is associated with increased mortality risk [1] [3] [4] [7]. The apparent protective effects in some cohorts are likely due to confounding by socioeconomic status, health behaviors, and the "sick quitter" effect, where abstainers include former heavy drinkers or those with poor health [6] [8] [20] [21].

Heavy and binge drinking are unequivocally harmful, increasing the risk of death from cancer, cardiovascular disease, and external causes [11] [14] [2] [3] [15] [16] [17] [18]. The impact of drinking patterns, beverage types, and social context further complicates the risk profile, with some evidence suggesting that wine, consumed with meals and in moderation, may be less harmful, though this is not universally supported [10] [19] [20] [21].

Genetic studies, including Mendelian randomization and polygenic risk scores, provide strong evidence that the relationship between alcohol and mortality is likely causal and linear, with no safe threshold [1] [3] [4] [26]. These findings have important implications for public health guidelines, which may need to be revised downward to reflect the absence of a protective effect and the risks associated with even low levels of alcohol consumption [5] [33] [8].

Claims and Evidence Table

Claim	Evidence Strength	Reasoning	Papers
Any increase in alcohol intake raises all-cause mortality risk	Strong (9/10)	Mendelian randomization and large cohorts show linear risk increase	[1] [3] [4] [7] [26]
Heavy and binge drinking significantly increase mortality risk	Strong (10/10)	Consistent across designs and populations	[11] [14] [2] [3] [15] [16] [17] [18]
Light-to-moderate drinking may appear protective	Moderate (5/10)	Observational J-shaped curve likely due to confounding	[11] [2] [12] [13] [8] [9]
Wine with meals may be less harmful than spirits/beer	Moderate (4/10)	Likely residual confounding by lifestyle/SES	[10] [19] [20] [21]
No safe threshold for alcohol intake	Strong (8/10)	Genetic and meta-analytic evidence supports linear risk	[1] [3] [5] [4] [7] [26]
Protective effects may be limited to older women	Weak (3/10)	Small subgroup effects; likely bias	[24] [8] [36]

Figure 4: Key claims and support evidence identified in these papers.

5. Conclusion

The current body of evidence indicates that alcohol intake is associated with increased all-cause mortality risk in a linear fashion, with no clear protective threshold. Heavy and binge drinking are particularly harmful, while the apparent benefits of light-to-moderate drinking are likely due to confounding and selection biases. Public health guidelines should reflect the absence of a safe level of alcohol consumption, and interventions should target reductions in both average intake and harmful drinking patterns.

5.1 Research Gaps

Despite extensive research, gaps remain in understanding the effects of alcohol on specific subpopulations, the role of drinking patterns, and the impact of genetic and environmental modifiers. There is also a need for more studies using robust causal inference methods and for research on the health risks to others from alcohol consumption.

Research Gaps Matrix

Population/Outcome	All-cause Mortality (n)	CVD Mortality (n)	Cancer Mortality (n)	Genetic Studies (n)	Patterns/Type (n)
General population	30	25	20	8	10
Older adults	10	7	6	2	3
Patients with comorbidities	7	5	4	1	2
Sex-specific analyses	8	6	5	2	2
Low- and middle-income countries	3	2	1	GAP	1

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Disclaimer: This article is for informational purposes only and not a substitute for medical advice.
Scientific summaries were compiled and synthesised using the AI models and peer-reviewed research.

References

1. Kassaw N, Zhou A, Mulugeta A, Lee S, Burgess S, Hyppönen E. Int J Epidemiol. 2024. https://doi.org/10.1093/ije/dyae046
2. Tian Y, Liu J, Zhao Y, et al. BMC Med. 2023. https://doi.org/10.1186/s12916-023-02907-6
3. Millwood I, Im P, Bennett D, et al. Lancet Public Health. 2023. https://doi.org/10.1016/s2468-2667(23)00217-7
4. Hu C, Huang C, Li J, et al. Am J Clin Nutr. 2022. https://doi.org/10.1093/ajcn/nqac159
5. Shield K, Gmel G, Mäkelä P, et al. Addiction. 2017. https://doi.org/10.1111/add.13827
6. Ortolá R, García-Esquinas E, López-García E, et al. Addiction. 2018. https://doi.org/10.1111/add.14402
7. Shao L, Chen Y, Zhao Z, Luo S. Medicine (Baltimore). 2024. https://doi.org/10.1097/md.0000000000038857
8. Knott C, Coombs N, Stamatakis E, Biddulph J. BMJ. 2015. https://doi.org/10.1136/bmj.h384
9. Marmot M, Rose G, Shipley M, Thomas B. Lancet. 1981. https://doi.org/10.1016/s0140-6736(81)92032-8
10. Streppel M, Ocké M, Boshuizen H, et al. J Epidemiol Community Health. 2009. https://doi.org/10.1136/jech.2008.082198
11. Di Castelnuovo A, Costanzo S, Bonaccio M, et al. Addiction. 2021. https://doi.org/10.1111/add.15593
12. Kunzmann A, Coleman H, Huang W, Berndt S. PLoS Med. 2018. https://doi.org/10.1371/journal.pmed.1002585
13. Qiu W, Cai A, Li L, Feng Y. Nutrients. 2022. https://doi.org/10.3390/nu14235073
14. Xi B, Veeranki S, Zhao M, et al. J Am Coll Cardiol. 2017. https://doi.org/10.1016/j.jacc.2017.06.054
15. Jankhotkaew J, Bundhamcharoen K, Suphanchaimat R, et al. BMJ Open. 2020. https://doi.org/10.1136/bmjopen-2020-038198
16. Galán I, Fontán J, Ortiz C, et al. Addict Behav. 2024. https://doi.org/10.1016/j.addbeh.2024.108108
17. Whitfield J, Heath A, Madden P, et al. Addiction. 2018. https://doi.org/10.1111/add.14008
18. Stewart D, Han L, Doran T, McCambridge J. J Epidemiol Community Health. 2017. https://doi.org/10.1136/jech-2017-209241
19. Jani B, McQueenie R, Nicholl B, et al. BMC Med. 2020. https://doi.org/10.1186/s12916-020-01878-2
20. Li H, Zhou T, Sun D, et al. Mayo Clin Proc. 2021. https://doi.org/10.1016/j.mayocp.2021.02.011
21. Ystrøm E, Degerud E, Tesli M, et al. Psychol Med. 2022. https://doi.org/10.1017/s0033291722000812
22. Bassett J, Peng Y, MacInnis R, et al. Int J Epidemiol. 2025. https://doi.org/10.1093/ije/dyaf022
23. Van Den Brandt P, Brandts L. Age Ageing. 2020. https://doi.org/10.1093/ageing/afaa003
24. Fuchs C, Stampfer M, Colditz G, et al. N Engl J Med. 1995. https://doi.org/10.1056/nejm199505113321901
25. Weng T, Meng L, Peng L, et al. J Am Med Dir Assoc. 2024. https://doi.org/10.1016/j.jamda.2024.03.119
26. Kiiskinen T, Mars N, Palviainen T, et al. Transl Psychiatry. 2020. https://doi.org/10.1038/s41398-019-0676-2
27. Thun M, Peto R, Lopez A, et al. N Engl J Med. 1997. https://doi.org/10.1056/nejm199712113372401
28. Zhang X, Liu Y, Li S, et al. Nutr J. 2021. https://doi.org/10.1186/s12937-021-00671-y
29. Moissl A, Delgado G, Krämer B, et al. Atherosclerosis. 2021. https://doi.org/10.1016/j.atherosclerosis.2021.08.014
30. Ye X, Miao C, Zhang W, et al. BMC Public Health. 2021. https://doi.org/10.1186/s12889-021-12140-6
31. Ortolá R, Sotos-Prieto M, García-Esquinas E, et al. JAMA Netw Open. 2024. https://doi.org/10.1001/jamanetworkopen.2024.24495
32. Rehm J, Shield K. Alcohol Res Curr Rev. 2014.
33. Ricci C, Schutte A, Schutte R, et al. Am J Clin Nutr. 2020. https://doi.org/10.1093/ajcn/nqaa008
34. Ricci C, Wood A, Muller D, et al. BMJ. 2018. https://doi.org/10.1136/bmj.k934
35. Östergren O, Martikainen P, Tarkiainen L, et al. J Epidemiol Community Health. 2019. https://doi.org/10.1136/jech-2018-211640
36. Paganini-Hill A, Kawas C, Corrada M. Age Ageing. 2007. https://doi.org/10.1093/ageing/afl184