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Original Article
Diabetes, obesity and metabolism Associations of Alcohol Consumption with All-Cause and Cancer Mortalities in Patients with Type 2 Diabetes Mellitus: A Nationwide Population Cohort Study
Keypoint
- This study observed a J-shaped relationship between alcohol consumption and mortality risk in patients with type 2 diabetes mellitus.
- Compared to non-drinkers, mild alcohol consumption was associated with reduced all-cause mortality (aHR 0.81 [0.80–0.82]) and cancer mortality (aHR 0.88 [0.86–0.89]).
- Heavy drinking increased mortality risk, but effects varied across subgroups, such as chronic kidney disease and age groups.
Da Yeon Lee1*orcid, Sun-Joon Moon1*orcid, Kyung-Do Han2, Ji-Hee Ko3, Han-na Jang1, Hye-Mi Kwon1, Se-Eun Park1, Eun-Jung Rhee1orcid, Won-Young Lee1orcid
Endocrinology and Metabolism 2025;40(6):893-903.
DOI: https://doi.org/10.3803/EnM.2024.2275
Published online: July 14, 2025

1Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea

2Department of Statistics and Actuarial Science, Soongsil University, Seoul, Korea

3Division of Endocrinology and Metabolism, Department of Internal Medicine, National Health Insurance Service Ilsan Hospital, Goyang, Korea

Corresponding authors: Eun-Jung Rhee. Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul 03181, Korea Tel: +82-2-2001-2485, Fax: +82-2-2001-1588, E-mail: hongsiri@hanmail.net
Won-Young Lee. Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul 03181, Korea Tel: +82-2-2001-2579, Fax: +82-2-2001-2049, E-mail: drlwy@hanmail.net
These authors contributed equally to this work.
• Received: December 10, 2024   • Revised: March 26, 2025   • Accepted: April 15, 2025

Copyright © 2025 Korean Endocrine Society

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Background
    To investigate the impact of alcohol consumption on all-cause and cancer mortalities in patients with type 2 diabetes (T2D).
  • Methods
    This nationwide cohort study included Korean patients with T2D aged >20 years from a national health exams cohort (2009 to 2012). Participants were categorized based on alcohol consumption: non, mild (<30 g/day), and heavy drinkers (≥30 g/day). Primary outcomes were all-cause and cancer mortality rates. Cox proportional hazard regression analyses were used to calculate adjusted hazard ratios (aHRs) with a 95% confidence interval (CI) with adjustments for age, sex, body mass index, smoking, exercise, comorbidities, diabetes duration, and medications.
  • Results
    Among 2,642,359 participants (median follow-up, 7.8 years), 57.2%, 32.7%, and 10.1% were non, mild, and heavy drinkers, respectively. Compared to non-drinkers, mild alcohol consumption was associated with reduced all-cause mortality (aHR, 0.81; 95% CI, 0.80 to 0.82) and cancer mortality (aHR, 0.88; 95% CI, 0.86 to 0.89), while heavy drinking increased both all-cause (aHR, 1.06; 95% CI, 1.04 to 1.07) and cancer mortalities (aHR, 1.09; 95% CI, 1.06 to 1.11). Subgroup analyses revealed variations: in chronic kidney disease and older age groups, heavy drinkers showed lower risk of all-cause mortality compared to non-drinkers. Regarding cancer mortality, younger and middle-aged groups showed protective effects of alcohol even for heavy drinkers, while females showed linear association between alcohol consumption and cancer mortality.
  • Conclusion
    This study indicates a J-shaped relationship between alcohol consumption and all-cause and cancer mortality risk in patients with T2D, with variations across subgroups. These findings suggest the need for personalized recommendations considering individual risk factors.
  • Keywords: Alcohols; All-cause mortality; Cancer mortality; Diabetes mellitus, type 2
The production and consumption of alcohol dates back to the seventh millennium before Christ [1]. As alcohol has a long history, numerous studies on alcohol and health have been continuously published, and controversies over the impact of alcohol on health persist [2-4]. Heavy alcohol consumption leads to many health problems [5] and many studies have also shown that excessive drinking increases mortality [6].
In contrast to heavy drinking, the health effects of mild drinking remain controversial and yield inconsistent results in the general population. Some meta-analyses have reported a J-shaped curve in the relationship between alcohol consumption and mortality. These studies suggest that low to mild alcohol intake (up to 30 g/day) may decrease overall mortality by up to 15%–18% compared to non-drinkers [3,7]. However, other meta- analyses suggested that ‘sick quitters’ may contribute to the J-curve, indicating that low-volume alcohol consumption shows no overall mortality benefit compared to lifetime abstinence or occasional drinking [8]. In addition, many studies have examined the relationship between alcohol consumption and all-cause mortality in patients with type 2 diabetes (T2D). These studies have shown results similar to those observed in the general population, suggesting that mild alcohol consumption is associated with decreased mortality [9,10].
Additionally, the relationship between alcohol consumption and cancer mortality remains unclear. Worldwide, esophageal, oral cavity, pharynx, liver, and colorectal cancers have shown the strongest links to alcohol consumption, accounting for the majority of alcohol-related cancer cases [11]. However, there is a limited number of research reports investigating the correlation between alcohol consumption and cancer mortality. Moreover, while the adverse outcomes associated with heavy alcohol consumption in colorectal and esophageal cancers have been well documented [12,13], the association with light and mild alcohol drinking remains less clear [13-15]. Previous research has not thoroughly investigated the relationship between alcohol consumption and cancer mortality specifically in patients with T2D [9,10,16].
These issues are particularly important for patients with T2D, who already face higher mortality and cancer incidence rates compared to the general population; a twofold higher mortality and 10% increased risk of developing cancer [17-19]. As cancer is a leading cause of death among patients with diabetes, understanding the relationship between alcohol consumption and cancer mortality in this population is crucial [20,21]. Given the complex interplay between diabetes, alcohol consumption, and cancer mortality, there is a clear need for more comprehensive studies in this area.
Therefore, this nationwide cohort study aimed to investigate the impact of alcohol consumption on all-cause and cancer mortalities in patients with T2D.
National Health Insurance Service data
The Korean National Health Insurance Service (NHIS), a governmental agency, administers a medical insurance system for all Koreans, managing a database that includes individual medical records such as diagnoses, hospital visits, conducted tests, and prescribed medications. Additionally, the NHIS provides a health screening program every 2 years for all employees, except for those who must be screened annually. These health screening databases include personalized questionnaires, such as demographic characteristics and health behaviors; including information on drinking and smoking. The NHIS has processed and distributed all these databases for use in cohort studies [22]. Approval for this study was granted by the Institutional Review Board of Kangbuk Samsung Hospital (No. 2024-08-007) and informed consent was waived by the board.
Study population
Participants were considered eligible for the study if they were aged ≥20 years and were diagnosed with T2D. They were selected from a national health exam cohort between 2009 to 2012 (n=2,746,079), and followed up until they died to investigate the cause of death (Supplemental Fig. S1). The diagnosis of T2D was defined as individuals who met the following conditions; (1) International Classification of Diseases, 10th revision, Clinical Modification (ICD-10-CM) codes E11–E14 and prescribed with at least one of glucose-lowering agents including oral hypoglycemic agents or insulin or (2) a fasting glucose level of ≥126 mg/dL [23]. The cause of death was categorized by ICD-10-CM codes. Among the initial participants, we excluded those aged <20 years (n=441). After excluding missing data (n=103,279), 2,642,359 individuals were finally included in the analysis (Supplemental Fig. S1).
Categorized alcohol consumption
Alcohol consumption was ascertained by self-report. We used the Alcohol Use Disorder Identification Test-Korean revised version (AUDIT-KR) [24]. The AUDIT-KR is composed of 10 questions addressing the quantity (the number of standard drinks on each occasion), frequency (the number of days per week) of alcohol consumption, and alcohol habits in the past 12 months.
To evaluate the amount of alcohol consumed, a standard drink unit was used. A standard drink was converted by averaging the amount of alcohol in each liquor of wine, beer, soju (Korean traditional alcohol), or whisky. We assumed that one standard drink (one glass of any type of liquor) contains approximately 7.5 g of alcohol [25]. The weekly frequency and pure alcohol amount per occasion were multiplied to calculate the total amount of alcohol consumption per week, which was then converted to the daily amount of alcohol intake. Through the completed questionnaire, the participants were categorized into three groups: non (0 g/day), mild (<30 g/day), or heavy (≥30 g/day) drinkers [26,27].
Definition of outcome
The mortality data were sourced from the Korean National Statistical Office for the period and analyzed from the date of the health examination until the date of death. The data were analyzed in the NHIS database using the ICD-10-CM. The study’s outcomes were defined as cancer and all-cause mortalities. Cancer mortality was defined as deaths occurring in individuals who had a C-code in their medical records at the time of death. The analysis of death incidence covered the period from January 1, 2009, to December 31, 2012, or until the date of death, whichever occurred first.
Statistical analysis
Continuous and categorical variables were reported as mean±standard deviation and percentages, respectively. Death incidence was expressed per 1,000 person-years. Using the nondrinker group as a reference, we performed a Cox proportional hazards regression analysis to determine mortality risk based on alcohol consumption, with a 95% confidence interval (CI). Also a fully adjusted restricted cubic spline (RCS) with 4 knots of alcohol consumption level was used to visualize alcohol consumption as a continuous variable. Initially, we calculated the unadjusted hazard ratio (HR) (model 1). Subsequently, we adjusted for potential confounding factors. Model 2 incorporated age and sex. In model 3, we performed a comprehensive multivariable-adjusted analysis, which included all variables from model 2 and additionally accounted for low income, smoking status, exercise habits, hypertension, dyslipidemia, body mass index, estimated glomerular filtration rate, fasting blood glucose levels, insulin tretment, number of oral anti-diabetic medications (OAD) prescribed, duration of diabetes, history of cardiovascular disease (CVD), and cancer diagnosis. Dyslipidemia was defined as (1) a total cholesterol level of 240 mg/dL or higher at the time of the health checkup or (2) the presence of ICD-10 code E78 and a prescription for lipid-lowering medication in the year of the health checkup. To reduce potential bias related to early symptoms and detection, we conducted additional analyses using a 1-year lag period. The statistical analyses were conducted using SAS version 9.3 (SAS Institute, Cary, NC, USA), with statistical significance defined as P<0.05. A t-test or analysis of variance was also performed.
Baseline characteristics
A total of 2,642,359 participants were included in the analysis. According to the questionnaire on alcohol consumption, 1,510,195 (57.2%), 864,411 (32.7%) (<30 g/day), and 167,753 (10.1%) (≥30 g/day) were in the non, mild, and heavy drinker groups, respectively (Supplemental Fig. S1). Baseline characteristics of the study population are presented in Table 1. The mean ages were 60.8±11.9, 53.0±11.8, and 52.4±10.9 years, for the non, mild, and heavy drinker groups, respectively. The proportions of men and current smokers were significantly higher in the heavy drinker group. The prevalence of cancer, myocardial infarct, or stroke, hypertension, and dyslipidemia tended to be higher in the non-alcohol group.
Effect of alcohol consumption on all-cause and cancer mortalities in patients with T2D
In the total study population, the median rates (per 1,000 person-years) for all-cause death were 16.37, 9.33, and 11.95 for non, mild, and heavy drinkers, respectively. For cancer mortality, the corresponding rates were 4.72, 3.47, and 4.32 for non, mild, and heavy drinkers, respectively. In the fully adjusted model, heavy alcohol consumption was associated with an increased risk of all-cause mortality (adjusted hazard ratio [aHR], 1.06; 95% CI, 1.04 to 1.07) and cancer mortality (aHR, 1.09; 95% CI, 1.06 to 1.11) (Table 2, Fig. 1). Conversely, mild drinkers exhibited a decreased risk of all-cause mortality (aHR, 0.81; 95% CI, 0.80 to 0.82) and cancer mortality (aHR, 0.88; 95% CI, 0.86 to 0.89), which showed a J-shaped association. For the sensitivity analysis, the 1-year lag analysis showed a similar result (Supplemental Table S1).
Impact of the amount of alcohol consumption on all-cause and cancer mortality according to sex
Both all-cause mortality and cancer mortality showed a J-curve pattern, with a decrease in mortality among moderate drinkers and an increase among heavy drinkers. However, the proportion of heavy drinkers was overwhelmingly higher in males (97%) compared to females (3%).
When analyzed separately by sex, all-cause mortality exhibited a J-curve pattern in both males and females. Among males, 16% were heavy drinkers, whereas only 1% of females were in this category. In the fully adjusted model, aHR for moderate drinkers was 0.80 (95% CI, 0.79 to 0.81) in males and 0.88 (95% CI, 0.85 to 0.90) in females. In contrast, heavy drinkers had an aHR of 1.05 (95% CI, 1.04 to 1.07) in males and 1.19 (95% CI, 1.07 to 1.32) in females, indicating a higher mortality risk for heavy drinking females despite their lower prevalence (Fig. 2A, Supplemental Table S2). However, the alcohol consumption level at which all-cause mortality increases differed between males and females. At the same consumption level, females has a higher mortality rate than males, and the alcohol consumption level at which mortality started to increase was higher for males than for females.
For cancer mortality, the patterns differed. Males exhibited the typical J-curve relationship between alcohol consumption and cancer mortality (Fig. 2B, Supplemental Table S2). Females, however, showed linear correlation between alcohol consumption and cancer mortality rates; mild drinkers (aHR, 1.01; 95% CI, 0.96 to 1.06) and heavy drinkers (aHR, 1.01; 95% CI, 0.82 to 1.24).
Impact of the amount of alcohol consumption on all-cause mortality according to chronic kidney disease and age
The results of subgroup analyses according to participants’ age, sex, diabetes duration, OAD count, insulin treatment, and comorbidities including chronic kidney disease (CKD) are presented in Supplemental Table S3. Our subgroup analyses revealed variations in the association between alcohol consumption and all-cause mortality across various demographic and clinical characteristics. Notably, the observed differences across subgroups were statistically significant (P for interaction <0.05) for all examined characteristics except for insulin tretment. While the association patterns for most subgroups were similar to those in the total population, we found older age (≥65 years) and CKD status demonstrated distinct patterns in all-cause mortality. The J-shaped relationship, which showed decreased HR in the mild amount and increased HR in the heavy amount, observed in the total population was inverted in individuals with CKD and older age groups. Mild drinkers showed the lowest mortality risk (older adults: aHR, 0.79 [95% CI, 0.78 to 0.79]; CKD: aHR, 0.73 [95% CI, 0.72–0.75]), followed by heavy drinkers (older adults: aHR, 0.95 [95% CI, 0.93 to 0.97]; CKD: aHR, 0.85 [95% CI, 0.81 to 0.88]). However when visualized as a continuous variable, in the heavy alcohol group, mortality increased again when alcohol consumption exceeded a certain level and the alcohol threshold for this increase was higher compared to the total population. Notably, the mortality protective effect of alcohol was more pronounced compared to the total population (Fig. 3, Supplemental Table S4).
Impact of the amount of alcohol consumption on cancer mortality according to age
We also conducted subgroup analyses to further investigate the relationship between alcohol consumption and cancer mortality (Supplemental Table S3). This cancer mortality relationship varied significantly when stratified by age. Younger age group (<40 years) showed a U-curve relationship, indicating that heavy drinkers had lower mortality than non-drinkers. Notably, in the younger age group, non-drinkers exhibited a higher HR compared to other age groups. And as age increased, mortality related to alcohol consumption tended to increase proportionally (Fig. 4, Supplemental Table S5). In the <40 years group, mild drinkers had the lowest cancer mortality rates (aHR, 0.55; 95% CI, 0.43 to 0.69), while heavy drinkers showed a reduced risk compared to non-drinkers (aHR, 0.71; 95% CI, 0.54 to 0.95). In the 40 to 65 years group, mild drinkers exhibited the lowest risk (aHR, 0.79; 95% CI, 0.77 to 0.81), while heavy drinkers showed a similar risk to non-drinkers (aHR, 0.97; 95% CI, 0.935 to 1.00).
In this nationwide cohort study of patients with T2D (n=2,642,359) with a median follow-up of 7.8 years, we observed a J-shaped relationship between alcohol consumption and both all-cause and cancer mortality risks. Mild alcohol consumption (<30 g/day) was associated with decreased risk of all-cause and cancer mortalities, while heavy alcohol consumption (≥30 g/day) was associated with an elevated risk compared to nondrinkers. The same trend was observed even when comparing males, who had a relatively higher proportion of heavy drinkers, and females, who had fewer in all-cause mortality. However, the point at which alcohol’s protective effect appeared differed between them. And the protective effect was stronger in mild consumers within the CKD group and in older age groups for all-cause mortality. In cancer mortality there was no protective effect in females and old age group. In these fragile groups, alcohol consumption and mortality risk increased in a linear pattern. And younger and middle-aged groups showed protective effects of alcohol.
Our results are consistent with previous prospective studies that have shown a protective effect of mild alcohol consumption on all-cause and cancer mortalities [3,7,9,10,28,29]. In the general population, a meta-analysis by Di Castelnuovo et al. [3] reported that 16% to 18% reduction in all-cause mortality risk for men consuming up to four drinks per day (one drink equal to 10 g) and women consuming up to two drinks per day, while high-level consumption (42 g/day) was associated with increased mortality. In T2D studies, mild alcohol consumption has been associated with a 14% to 36% risk reduction in all-cause mortality risk [7,9,10]. These are consistent with our observed 19% risk reduction of all-cause mortality for 15 to 30 g daily consumption and increased mortality for >30 g/day. For cancer mortality, a meta-analysis among the general population by Jin et al. [29] found that the relative risks were 0.91 to 1.02 for light to mild drinking (≤12.5 g/day, 12.5–50 g/day) and 1.31 for heavy drinking (>50 g/day). These results are comparable to our HRs of 0.88 and 1.09, respectively. These consistencies suggest that the relationship between alcohol consumption and mortality risk in patients with T2D may follow similar patterns to those observed in the general population, despite the unique health considerations associated with diabetes.
The underlying mechanisms behind this J-shaped curve remain unclear. Most of the previous studies suggested that the J-shaped curve of all-cause mortality is owing to a decrease in deaths from CVD [9,10,30]. Moderate alcohol consumption may reduce CVD risk by improving lipid metabolism, enhancing endothelial function, reducing inflammation, and increasing insulin sensitivity. These effects contribute to higher high-density lipoprotein cholesterol, reduced arterial stiffness, and better vascular function, lowering the risk of atherosclerosis [9,31]. Because patients with T2D have more CVD risk, their improvement from alcohol consumption may explain the larger CVD risk reduction compared to that in the general population [9]. For cancer mortality, there is limited evidence on the link between alcohol consumption and cancer mortality risk. Ethanol from alcoholic drinks is converted into acetaldehyde, a substance classified as a human carcinogen [32]. Acetaldehyde can cause DNA damage, interfere with DNA replication and repair, and disrupt DNA methylation, potentially altering the expression of oncogenes and tumor-suppressor genes. Moreover, inflammation is a key factor in cancer development across various tissues, and ethanol can influence this process by promoting inflammation and oxidative stress. This leads to lipid peroxidation and additional DNA damage, creating a more favorable environment for tumor progression [33]. This may suggest a possible mechanism by which alcohol consumption increases the risk of cancer mortality. However, our data showed that mild alcohol consumption is associated with decreased cancer mortality. A series of meta-analyses have revealed inconsistent correlations between different types of cancer and alcohol consumption aligning with our findings [29]. This inconsistency highlights the complex nature of the alcohol-cancer relationship and suggests that the effects may vary by cancer type and other factors.
When comparing male and females, all-cause mortality was higher in females than in males at the same level of alcohol consumption. Additionally, the results for cancer mortality did not align in the females. These inconsistencies indicate that the effects of alcohol may differ depending on the type of cancer and sex. This probably reflects that women do not have the same benefit from mild alcohol consumption, which was also shown in other studies [29,34]. The risk difference between the sex might be owing to the difference in the cancer spectrum that affects males and females. Additionally, both the lower body water content in females and their lower gastric alcohol dehydrogenase activity, which is crucial for the initial metabolism of alcohol in the stomach, lead to higher blood ethanol levels compared to men who consume the same amount of alcohol. These factors could contribute to the attenuation or absence of the protective effect of mild alcohol consumption on mortality in females, which is more pronounced in males [34,35].
In all-cause mortality, patients with CKD and older age have more protective effect in mild consumers, different from the relationship observed in the total study population. One possible explanation for this finding lies in the reduced risk of CVD by increasing alcohol consumption, which is the leading cause of death among patients with CKD and old age with T2D [16,36]. Previous studies have found that alcohol consumption may lower the risk of developing CKD, with this protective effect persisting even with heavy drinking [37,38]. These factors may interact to produce protective effect in these subgroups.
In cancer mortality, young aged participants showed that nondrinkers had a higher HR compared to heavy drinkers. The protective effect of mild alcohol consumption and even heavy alcohol consumption for some subgroups observed in our study should be interpreted with caution. There is a potential for misclassification of former drinkers as non-drinkers, and non-drinkers could already be sick or experiencing early symptoms of disease which could affect the result, known as sick quitter bias [39]. In addition, a population survey of adults in England found that in young to middle-aged individuals, mild drinkers are more likely to occupy favorable socioeconomic positions [40], which could indirectly influence their cancer outcomes through better access to healthcare and a healthier lifestyle. Additionally, because it takes time for alcohol to accumulate as a carcinogen, these delayed effects of alcohol on cancer development might not yet be apparent in younger age groups [41], potentially masking the direct impact of alcohol consumption on cancer mortality in this subgroup.
To the best of our knowledge, this is the study with the largest sample size (n=2,642,359) that has evaluated the associations between alcohol and all-cause and cancer mortalities in T2D. Previously published reports have often been limited by factors such as small sample sizes [9], short follow-up periods [10], limited adjustment for confounding factors, and insufficient focus on cancer mortality specifically in patients with T2D [3,28,29]. We employed extensive multivariable adjustment to minimize bias, including diabetes-specific factors like OAD count, diabetes mellitus duration, and insulin use. Moreover, the long follow-up period in our study allowed for a more accurate assessment of the long-term effects of alcohol consumption on mortality risks in patients with T2D.
The current study also had limitations. First, the reliance on self-reported alcohol consumption data from surveys introduced the possibility of recall bias and changes in participants’ habits over time, which may affect the accuracy of the findings. Second, the phenomenon known as sick quitter bias [39], which could potentially lead to worse outcomes for the non-drinking group could have affected the results. Third, the cohort data lacked details on the histological type, tumor, node and metastasis stage, or specific location of the cancers, potentially obscuring specific associations between alcohol consumption and different cancer outcomes. Fourth, it is difficult to analyze the effects of different types of alcohol and A1C levels since classification based on alcohol type and data on A1C were not available. Fifth, while alcohol can influence mortality for various reasons, establishing a precise causal relationship is challenging. Sixth, since the study did not include different racial or ethnic groups, its generalizability is limited. Finally, our analysis showed different trends between aHR and RCS models in cancer mortality, possibly due to the non-linearity of the relationship and the proportional hazards assumption of the Cox model which should be interpreted with caution. Future studies need to address this limitation.
In conclusion, this large-scale nationwide cohort study of patients with T2D revealed a J-shaped relationship between alcohol consumption and both all-cause and cancer mortalities, with variations observed in specific subgroups. These complexities may underscore the importance of personalized recommendations for alcohol consumption in patients with T2D.

Supplemental Table S1.

Effect of Alcohol Consumption on All-Cause and Cancer Mortalities in Patients with T2D 1 Year Lag
enm-2024-2275-Supplemental-Table-S1.pdf

Supplemental Table S2.

Subgroup Analysis according to Sex
enm-2024-2275-Supplemental-Table-S2.pdf

Supplemental Table S3.

Subgroup Analysis of the Risk of Mortality with Amount of Alcohol Consumption
enm-2024-2275-Supplemental-Table-S3.pdf

Supplemental Table S4.

Subgroup Analyses according to Age and CKD: All-Cause Death
enm-2024-2275-Supplemental-Table-S4.pdf

Supplemental Table S5.

Subgroup Analyses according to Age: Cancer Death
enm-2024-2275-Supplemental-Table-S5.pdf

Supplemental Fig. S1.

Flow diagram of study participant selection.
enm-2024-2275-Supplemental-Fig-S1.pdf

CONFLICTS OF INTEREST

Eun-Jung Rhee is a deputy editor of the journal. But she was not involved in the peer reviewer selection, evaluation, or decision process of this article. No other potential conflicts of interest relevant to this article were reported.

AUTHOR CONTRIBUTIONS

Conception or design : S.J.M., K.D.H., E.J.R., W.Y.L. Acquisition, analysis, or interpretation of data: D.Y.L., S.J.M., K.D.H. Drafting the work or revising: D.Y.L., S.J.M., K.D.H., J.H.K., H.J., H.M.K., S.E.P., E.J.R., W.Y.L. Final approval of the manuscript: D.Y.L., S.J.M., K.D.H., J.H.K., H.J., H.M.K., S.E.P., E.J.R., W.Y.L.

Fig. 1.
Total population outcome: (A) all-cause death and (B) cancer death. Values are expressed as adjusted hazard ratio with 95% confidence interval (CI).
enm-2024-2275f1.jpg
Fig. 2.
All-cause and cancer mortablity by sex. (A) All-cause death with sex group and (B) cancer death with sex group. CI, confidence interval.
enm-2024-2275f2.jpg
Fig. 3.
Subgroup outcome. (A) All-cause death with age group and (B) all-cause mortality with chronic kidney disease (CKD) group. Values are expressed as adjusted hazard ratio with 95% confidence interval (CI).
enm-2024-2275f3.jpg
Fig. 4.
Subgroup outcome: cancer death with age group. (A) Cancer death with <40 years group. (B) Cancer death with 40 to 64 years group. (C) Cancer death with ≥65 years group. Values are expressed as adjusted hazard ratio with 95% confidence interval (CI).
enm-2024-2275f4.jpg
enm-2024-2275f5.jpg
Table 1.
Baseline Characteristics of the Study Population
Characteristic Non (n=1,510,195) Mild (n=864,411) Heavy (n=267,753) P value
Age, yr 60.8±11.9 53.0±11.8 52.4±10.9 <0.001
Male sex 597,173 (39.5) 737,272 (85.3) 259,602 (97.0) <0.001
Income, low 25% 333,573 (22.1) 171,111 (19.8) 51,057 (19.1) <0.001
Smoke <0.001
 Non 1,137,116 (75.3) 277,184 (32.1) 48,316 (18.0)
 Former 180,797 (12.0) 233,014 (27.0) 74,278 (27.7)
 Current 192,282 (12.7) 354,213 (41.0) 145,159 (54.2)
Underlying comorbidities
 Cancer 47,548 (3.2) 10,789 (1.6) 2,173 (0.8) <0.001
 MI or stroke 113,412 (7.5) 29,034 (3.4) 6,854 (2.6) <0.001
 Hypertension 900,634 (59.6) 448,142 (51.8) 152,115 (56.8) <0.001
 Dyslipidemia 694,937 (46.0) 317,089 (36.7) 96,700 (36.1) <0.001
DM duration ≥5 years 550,942 (36.5) 201,795 (23.3) 57,702 (21.6) <0.001
Insulin user 160,745 (10.6) 42,972 (5.0) 11,745 (4.4) <0.001
OAD ≥3 user 240,546 (15.9) 86,622 (10.0) 25,449 (9.5) <0.001
Regular exercise 284,931 (18.9) 196,448 (22.7) 57,350 (21.4) <0.001
Body mass index, kg/m2 25.02±3.9 25.1±3.3 25.2±3.4 <0.001
Waist circumference, cm 84.67±9.07 86.2±8.6 87.6±8.3 <0.001
eGFR, mL/min/1.73 m2 82.18±34.2 87.7±38.9 90.9±39.2 <0.001
Fasting glucose, mg/dL 141.39±47.4 148.7±46.5 153.99±48.8 <0.001
SBP, mm Hg 128.47±16.1 129.3±15.5 131.86±15.8 <0.001
DBP, mm Hg 77.96±10.1 80.2±10.3 82.03±10.5 <0.001
Total cholesterol, mg/dL 195.81±47.5 198.5±44.9 200.88±50.1 <0.001
Triglyceride, mg/dL 137.8 (137.7–137.9) 158.8 (158.5–159.0) 188.5 (188–188.9) <0.001

Values are expressed as mean±standard deviation, number (%), or median (interquartile range).

MI, myocardial infarction; DM, diabetes mellitus; OAD, oral anti-diabetic medication; eGFR, estimated glomerular filtration rate; SBP, systolic blood pressure; DBP, diastolic blood pressure.

Table 2.
Effect of Alcohol Consumption on All-Cause and Cancer Mortalities in T2D
Category Amount of alcohol consumption No. of participants No. of death Duration, person-yr MR, /1,000 person-yr Adjusted model, HR (95% CI)
Model 1 Model 2 Model 3
All-cause death Non 1,510,195 191,773 11,735,889 16.34 1 (reference) 1 (reference) 1 (reference)
Mild 864,411 63,595 6,810,677.82 9.34 0.57 (0.57–0.58) 0.79 (0.78–0.80) 0.81 (0.80–0.82)
Heavy 267,753 24,957 2,088,112.19 11.95 0.73 (0.72–0.74) 1.08 (1.06–1.09) 1.06 (1.04–1.07)
Cancer death Non 1,510,195 55,417 11,735,889 4.72 1 (reference) 1 (reference) 1 (reference)
Mild 864,411 23,640 6,810,677.82 3.47 0.74 (0.73–0.75) 0.87 (0.86–0.89) 0.88 (0.86–0.89)
Heavy 267,753 9,022 2,088,112.19 4.32 0.92 (0.90–0.94) 1.12 (1.10–1.15) 1.09 (1.06–1.11)

Model 1: unadjusted; Model 2: age, sex; Model 3: age, sex, income, smoke, exercise, hypertension, dyslipidemia, body mass index, estimated glomerular filtration rate, glucose, insulin treatment, oral anti-diabetic medication number, diabetes duration, cardiovascular disease, cancer were included.

T2D, type 2 diabetes; MR, median rate; HR, hazard ratio; CI, confidence interval.

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      Associations of Alcohol Consumption with All-Cause and Cancer Mortalities in Patients with Type 2 Diabetes Mellitus: A Nationwide Population Cohort Study
      Endocrinol Metab. 2025;40(6):893-903.   Published online July 14, 2025
      DOI: https://doi.org/10.3803/EnM.2024.2275
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    Associations of Alcohol Consumption with All-Cause and Cancer Mortalities in Patients with Type 2 Diabetes Mellitus: A Nationwide Population Cohort Study
    Image Image Image Image Image
    Fig. 1. Total population outcome: (A) all-cause death and (B) cancer death. Values are expressed as adjusted hazard ratio with 95% confidence interval (CI).
    Fig. 2. All-cause and cancer mortablity by sex. (A) All-cause death with sex group and (B) cancer death with sex group. CI, confidence interval.
    Fig. 3. Subgroup outcome. (A) All-cause death with age group and (B) all-cause mortality with chronic kidney disease (CKD) group. Values are expressed as adjusted hazard ratio with 95% confidence interval (CI).
    Fig. 4. Subgroup outcome: cancer death with age group. (A) Cancer death with <40 years group. (B) Cancer death with 40 to 64 years group. (C) Cancer death with ≥65 years group. Values are expressed as adjusted hazard ratio with 95% confidence interval (CI).
    Graphical abstract

    Fig. 1.

    Fig. 2.

    Fig. 3.

    Fig. 4.

    Graphical abstract

    Associations of Alcohol Consumption with All-Cause and Cancer Mortalities in Patients with Type 2 Diabetes Mellitus: A Nationwide Population Cohort Study
    Characteristic Non (n=1,510,195) Mild (n=864,411) Heavy (n=267,753) P value
    Age, yr 60.8±11.9 53.0±11.8 52.4±10.9 <0.001
    Male sex 597,173 (39.5) 737,272 (85.3) 259,602 (97.0) <0.001
    Income, low 25% 333,573 (22.1) 171,111 (19.8) 51,057 (19.1) <0.001
    Smoke <0.001
     Non 1,137,116 (75.3) 277,184 (32.1) 48,316 (18.0)
     Former 180,797 (12.0) 233,014 (27.0) 74,278 (27.7)
     Current 192,282 (12.7) 354,213 (41.0) 145,159 (54.2)
    Underlying comorbidities
     Cancer 47,548 (3.2) 10,789 (1.6) 2,173 (0.8) <0.001
     MI or stroke 113,412 (7.5) 29,034 (3.4) 6,854 (2.6) <0.001
     Hypertension 900,634 (59.6) 448,142 (51.8) 152,115 (56.8) <0.001
     Dyslipidemia 694,937 (46.0) 317,089 (36.7) 96,700 (36.1) <0.001
    DM duration ≥5 years 550,942 (36.5) 201,795 (23.3) 57,702 (21.6) <0.001
    Insulin user 160,745 (10.6) 42,972 (5.0) 11,745 (4.4) <0.001
    OAD ≥3 user 240,546 (15.9) 86,622 (10.0) 25,449 (9.5) <0.001
    Regular exercise 284,931 (18.9) 196,448 (22.7) 57,350 (21.4) <0.001
    Body mass index, kg/m2 25.02±3.9 25.1±3.3 25.2±3.4 <0.001
    Waist circumference, cm 84.67±9.07 86.2±8.6 87.6±8.3 <0.001
    eGFR, mL/min/1.73 m2 82.18±34.2 87.7±38.9 90.9±39.2 <0.001
    Fasting glucose, mg/dL 141.39±47.4 148.7±46.5 153.99±48.8 <0.001
    SBP, mm Hg 128.47±16.1 129.3±15.5 131.86±15.8 <0.001
    DBP, mm Hg 77.96±10.1 80.2±10.3 82.03±10.5 <0.001
    Total cholesterol, mg/dL 195.81±47.5 198.5±44.9 200.88±50.1 <0.001
    Triglyceride, mg/dL 137.8 (137.7–137.9) 158.8 (158.5–159.0) 188.5 (188–188.9) <0.001
    Category Amount of alcohol consumption No. of participants No. of death Duration, person-yr MR, /1,000 person-yr Adjusted model, HR (95% CI)
    Model 1 Model 2 Model 3
    All-cause death Non 1,510,195 191,773 11,735,889 16.34 1 (reference) 1 (reference) 1 (reference)
    Mild 864,411 63,595 6,810,677.82 9.34 0.57 (0.57–0.58) 0.79 (0.78–0.80) 0.81 (0.80–0.82)
    Heavy 267,753 24,957 2,088,112.19 11.95 0.73 (0.72–0.74) 1.08 (1.06–1.09) 1.06 (1.04–1.07)
    Cancer death Non 1,510,195 55,417 11,735,889 4.72 1 (reference) 1 (reference) 1 (reference)
    Mild 864,411 23,640 6,810,677.82 3.47 0.74 (0.73–0.75) 0.87 (0.86–0.89) 0.88 (0.86–0.89)
    Heavy 267,753 9,022 2,088,112.19 4.32 0.92 (0.90–0.94) 1.12 (1.10–1.15) 1.09 (1.06–1.11)
    Table 1. Baseline Characteristics of the Study Population

    Values are expressed as mean±standard deviation, number (%), or median (interquartile range).

    MI, myocardial infarction; DM, diabetes mellitus; OAD, oral anti-diabetic medication; eGFR, estimated glomerular filtration rate; SBP, systolic blood pressure; DBP, diastolic blood pressure.

    Table 2. Effect of Alcohol Consumption on All-Cause and Cancer Mortalities in T2D

    Model 1: unadjusted; Model 2: age, sex; Model 3: age, sex, income, smoke, exercise, hypertension, dyslipidemia, body mass index, estimated glomerular filtration rate, glucose, insulin treatment, oral anti-diabetic medication number, diabetes duration, cardiovascular disease, cancer were included.

    T2D, type 2 diabetes; MR, median rate; HR, hazard ratio; CI, confidence interval.

    Table 1.

    Table 2.

    Endocrinol Metab : Endocrinology and Metabolism
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