Abstract
Among the potential modifiable risk factors, the association between alcohol consumption and the risk of multiple myeloma remains controversial. We investigated the effects of weekly average alcohol consumption and drinking pattern on the risk of multiple myeloma using a nationwide representative database.
We identified 11,737,467 subjects who participated in the Korean National Health Screening Program in 2009 and 2010. Cox regression analyses were performed to calculate the risk of multiple myeloma according to weekly alcohol consumption, drinking frequency, and amount per session.
During a mean follow-up period of 6.8 years after a one-year time lag, 6,981 subjects (3,921 men and 3,060 women) were diagnosed with multiple myeloma. Compared with nondrinkers, all drinkers were at a significantly lower risk for multiple myeloma. The risk of multiple myeloma was reduced in a dose-dependent manner: mild drinkers [adjusted HR (aHR), 0.89; 95% confidence interval (CI), 0.84–0.95], moderate drinkers (aHR, 0.83; 95% CI, 0.76–0.91), and heavy drinkers (aHR, 0.76; 95% CI, 0.69–0.85). Furthermore, both drinking frequency and amount per drinking session showed inverse association with the risk of multiple myeloma.
Our large population-based study suggested an inverse dose-dependent association between total average alcohol consumption and the risk of multiple myeloma, and drinking frequency and amount per drinking session seemed to not differ in their relative contribution to the risk of multiple myeloma.
On the basis of the unprecedentedly large number of study population analyzed in this study, our study provides solid epidemiologic evidence of alcohol consumption on multiple myeloma risk.
Introduction
Multiple myeloma, which is characterized by the neoplastic proliferation of plasma cells producing monoclonal immunoglobulins, is associated with significant morbidity due to end-organ destruction (1). With the aging of the population, the worldwide incident cases of multiple myeloma, the second most common hematologic malignancy, increased 126% from 1990 to 2016, and the age-standardized incidence rate also increased, especially in developed countries (2).
Previously identified risk factors for multiple myeloma include older age, male sex, African ancestry, obesity, and a family history of hematologic malignancies (3, 4). Among the potential modifiable risk factors, the association between alcohol consumption and the risk of multiple myeloma remains controversial. A large pooled case–control analysis (5) and a recent cohort study (6–8) reported an inverse association between alcohol consumption and multiple myeloma, whereas one cohort study from the Netherlands reported a positive association between alcohol consumption and multiple myeloma in mild drinkers (∼10 g/day; ref. 9). On the other hand, the majority of previous cohort studies showed no associations between alcohol consumption and multiple myeloma (10–16).
In addition, the results of the available dose–response analyses of alcohol consumption and the risk of multiple myeloma remain inconclusive (6, 8, 17). In the UK Million Women Study, the risk of multiple myeloma was lower in mild drinkers (3 to < 7 drinks per week), but the risk of multiple myeloma did not decrease further as the amount of alcohol consumption increased (8). Similarly, a previous meta-analysis showed that alcohol drinking reduces the risk of multiple myeloma, but the amount of alcohol consumed did not influence the risk: mild drinkers [adjusted HR (aHR), 0.88; 95% confidence interval (CI), 0.76–1.02], moderate drinkers (aHR, 0.87; 95% CI, 0.77–0.99), and heavy drinkers (aHR, 0.86; 95% CI, 0.53–1.38; ref. 17). On the other hand, in a very recent large-scale NIH-AARP cohort study, increasing alcohol consumption was reported to be inversely associated with multiple myeloma, with a statistically significant dose–response trend (Ptrend = 0.01; ref. 6).
Previous cohort studies of the association between alcohol consumption and the risk of multiple myeloma have had several weaknesses. Notably, all previous studies focused on average alcohol consumption (e.g., number of drinks per week), and data regarding the impact of drinking pattern, such as frequency of drinking or amount per session, are lacking. Moreover, the largest number of incident multiple myeloma cases in the previous studies was about 1,500 (8), and there were several studies that included fewer than 100 incident multiple myeloma cases (12, 16). Furthermore, only a few addressed Asian populations (12, 16).
In this regard, herein we aimed to investigate the effects of drinking pattern on the risk of multiple myeloma using a nationwide population-based dataset. In particular, we evaluated the dose–response relationship, sex differences, and the relative contribution of the frequency of drinking and the amount of alcohol consumption per session, which has never been investigated, on the risk of multiple myeloma incidence.
Methods
Study setting
In South Korea, a universal insurance system provided by a single insurer, the Korean National Health Insurance Service (NHIS), covers about 97% of whole population, with the remaining 3% being Medicaid beneficiaries. The NHIS provides free biennial cardiovascular health screening for all beneficiaries over 40 years of age: the program consists of a standard questionnaire (regarding past medical history, and lifestyle habits, such as drinking, smoking, and exercise), anthropometric measurements (height, weight, and BP), and laboratory tests (fasting glucose, lipid levels, serum creatinine, etc.; ref. 18). The NHIS database provides qualification data regarding demographics, diagnosis codes from the International Classification of Diseases 10th revision (ICD-10), medical treatment information, and mortality data. The NHIS database has been used to establish cohort data for various epidemiologic studies (19).
Ethical approval
This study has been approved by the Institutional Review Board of Samsung Medical Center (IRB File No. SMC 2019–02–059). The requirement for informed consent from individual subjects was waived, as we used deidentified secondary data. This study was performed in accordance with the Declaration of Helsinki.
Study population
From the NHIS database of all Korean residents, we collected data from subjects ≥40 years old who had undergone a health examination in 2009 and 2010. Among 12,724,396 subjects, those who had any cancer (n = 303,424) before the health examination date, subjects diagnosed with any cancer (n = 124,472), or who died (n = 16,182) within 1 year after the date of examination, and those whose records were missing any information on alcohol consumption or other key variables (n = 542,851) were excluded. After these exclusions, a total of 11,737,467 individuals were included in our analyses.
Alcohol intake
In the self-administered questionnaires, participants responded to questions regarding the frequency (number of days per week) and quantity (the number of standard units per session) of their alcohol consumption in the past 12 months. In the questionnaires, a standard unit was defined as a specialized cup size for each type of alcoholic beverage, including wine, whisky, beer, and Korean traditional alcohol (soju), which was roughly equivalent to 8 g of pure alcohol (ref. 20; i.e., we uniformly converted one standard unit to 8 g of alcohol, regardless of the type of drink). Thus, the total intake of pure alcohol per week (g/week) was calculated as the total grams of pure alcohol per session multiplied by the weekly frequency of drinking. The subjects were assigned to one of four groups according to their total weekly consumption of pure alcohol (g/day): nondrinker (0 g/day), mild drinker (0–15 g/day), moderate drinker (15–30 g/day), or heavy drinker (≥ 30 g/day; ref. 20). The frequency of alcohol consumption was categorized into seven levels according to the number of days of drinking and further categorized into three groups (1–2, 3–4, or 5–7 days per week). The amount of alcohol consumed at each drinking session was categorized into five levels (1–2, 3–4, 5–7, 8–14, or >14 units per session; ref. 21).
Study outcomes and follow-up
The endpoint of the study was newly diagnosed multiple myeloma, defined as new claims with an ICD-10 diagnosis code of C90.0 and registration in the special copayment reduction program for critical illnesses such as cancer. The NHIS special copayment reduction program for critical illness was implemented to enhance health coverage and relieve the financial burden for patients with serious and rare diseases. Regardless of their income level, all patients with cancer that are enrolled in the copayment reduction program pay only 5% of the total medical bill in Korea. Enrollment in this program requires a registration application by the treating physician, and this information has been widely used to verify cancer diagnosis in studies using the NHIS database (22–24).
The cohort was followed for a period beginning 1 year after the health examination date (i.e., one–year lag) and continued to the date of incident multiple myeloma, death, or the end of the study period (December 31, 2017), whichever came first.
Covariates
Smoking status was categorized as never smoker, ex-smoker, or current smoker. Regular exercise was defined as performing > 30 minutes of moderate physical activity at least five times per week or > 20 minutes of strenuous physical activity at least three times per week. Body mass index (BMI) was calculated using the body weight (kg) divided by height in meters squared (m2). Systolic and diastolic blood pressure (BP) measurements were obtained after the subjects had been in a seated position for at least five minutes.
Comorbidities were defined by claims data prior to the screening (medical claim based on ICD-10 codes and relevant prescription of at least 1 claim during 1 year before screening date) and health examination results as appropriate: hypertension (I10–I13 or I15 and antihypertensive medication or BP ≥ 140/90 mmHg), diabetes mellitus (E11–E14 and antidiabetic medication or fasting glucose level ≥ 126 mg/dL), dyslipidemia (E78 and lipid-lowering medications or total cholesterol level ≥ 240 mg/dL), ischemic heart disease (I21–I22), and stroke (I63–I64). Chronic kidney disease was defined on the basis of glomerular filtration rate < 60 mL/min/1.73 m2 as estimated by the Modification of Diet in Renal Disease equation (25, 26). Rheumatoid arthritis (RA) was defined on the basis of ICD-10 codes of M05 and coadministration of copayment reduction program code (V223) for rare intractable disease (27). Income level was based on monthly insurance premium, because, in Korea, an individual's insurance premium is determined on the basis of income level.
Statistical analysis
Baseline characteristics of the study subjects according to their weekly alcohol intake are presented as the mean ± SD for continuous variables and number (%) for categorical variables. Values were compared using the independent t test for continuous variables and the χ2 test for categorical variables. The proportional hazards assumption was examined using Schoenfeld residuals and found acceptable. Cox proportional hazard regression analyses were conducted to estimate HR and 95% CIs association of weekly alcohol consumption with the development of multiple myeloma. Complete case analysis was performed in all cases, except for 4.3% of cases with missing data on variables of interest. Nondrinkers served as the referent group for all analyses. Model 1 was adjusted for age and sex. Model 2 was further adjusted for income level, smoking status (28), physical activity (29), BMI (30), and the presence of diabetes mellitus (31). We also performed sensitivity analyses to prove the robustness of our findings. First, on the basis of very recent studies reporting an association between lipid levels and the risk of multiple myeloma (22, 23), we adjusted for TG, HDL-C, and LDL-C. Second, we further analyzed the data with additional adjustment for RA as a possible confounder, given that alcohol consumption is not recommended for people with autoimmune diseases in general and that the potential presence of the positive association between autoimmune disease and the risk of multiple myeloma has been proposed by previous studies (32, 33).
In addition, among subjects with similar levels of alcohol consumption, the relative contribution of the frequency and quantity of alcohol consumption in each individual was assessed through stratified analyses according to weekly alcohol consumption status for comparison. We also performed a stratified analysis by sex to assess differences in alcohol consumption and metabolism according to sex (34).
All statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC), and a P value < 0.05 was considered statistically significant.
Data availability
The data that support the findings of this study are available from NHIS. Restrictions apply to the availability of these data, which were used under license for this study. Data are available at https://nhiss.nhis.or.kr with the permission of NIHS.
Results
Baseline characteristics
Table 1 provides the baseline information for and characteristics of the study population. Among all subjects, 40.3% (n = 4,727,135) were drinkers, with 23.7% being categorized as mild drinkers, 9.5% as moderate drinkers, and 7.1% as heavy drinkers. The average alcohol intake (g) per day was 6.2 g (SD 3.6 g), 20.6 g (SD 4.0 g), and 51.5 g (SD 26.5 g) in mild, moderate, and heavy drinkers, respectively. Subjects in the heavy drinker group tended to be younger, and were more likely to be current smokers, and to have more comorbidities (hypertension, diabetes mellitus) and higher incomes than the nondrinker group.
. | Nondrinker . | Mild drinker . | Moderate drinker . | Heavy drinker . |
---|---|---|---|---|
. | (n = 7,010,332) . | (n = 2,781,462) . | (n = 1,113,038) . | (n = 832,635) . |
Age (years) | 56.4 ± 11.0 | 51.8 ± 9.7 | 51.5 ± 9.1 | 52.3 ± 9.5 |
Sex (male) | 2,027,999 (28.9) | 1,805,061 (64.9) | 992,950 (89.2) | 786,681 (94.5) |
Alcohol intake (g/day) | - | 6.2 ± 3.6 | 20.6 ± 3.9 | 51.5 ± 26.5 |
Smoking status | ||||
Never | 5,810,163 (82.9) | 1,413,540 (50.8) | 283,125 (25.4) | 168,006 (20.2) |
Ex-smoker < 20 PY | 330,639 (4.7) | 426,874 (15.4) | 190,356 (17.1) | 116,989 (14.1) |
Ex-smoker ≥ 20 PY | 235,408 (3.4) | 195,990 (7.1) | 122,703 (11.0) | 118,340 (14.2) |
Current smoker < 20 PY | 281,892 (4.0) | 404,652 (14.6) | 227,469 (20.4) | 128,900 (15.5) |
Current smoker ≥ 20 PY | 352,230 (5.0) | 340,406 (12.2) | 289,385 (26.0) | 300,400 (36.1) |
Regular physical activity | 1,273,473 (18.2) | 615,562 (22.2) | 253,247 (22.8) | 186,522 (22.4) |
Anthropometrics | ||||
BMI (kg/m2) | 23.9 ± 3.1 | 23.9 ± 2.9 | 24.3 ± 2.9 | 24.4 ± 3.0 |
Waist circumference (cm) | 80.0 ± 8.7 | 81.5 ± 8.4 | 84.1 ± 7.7 | 85.1 ± 7.8 |
Systolic BP (mmHg) | 123.4 ± 15.7 | 123.5 ± 14.9 | 126.8 ± 14.8 | 128.3 ± 15.1 |
Diastolic BP (mmHg) | 76.1 ± 10.1 | 77.2 ± 10.1 | 79.6 ± 10.0 | 80.5 ± 10.1 |
Laboratory findings | ||||
Fasting glucose (mg/dL) | 98.9 ± 24.0 | 99.4 ± 23.4 | 103.0 ± 26.5 | 105.8 ± 29.2 |
Total cholesterol (mg/dL) | 199.8 ± 37.6 | 198.1 ± 35.8 | 199.0 ± 36.1 | 198.4 ± 37.0 |
Triglycerides (mg/dL) | 111.9 (111.8–111.9) | 116.0 (115.9–116.1) | 137.8 (137.6–137.9) | 147.9 (147.7–148.1) |
HDL-C (mg/dL) | 54.5 ± 17.3 | 55.0 ± 15.4 | 55.1 ± 15.5 | 56.1 ± 16.6 |
LDL-C (mg/dL) | 119.9 ± 34.3 | 116.1 ± 33.1 | 111.9 ± 34.2 | 107.7 ± 35.3 |
eGFR (mL/min/1.73 m2) | 84.6 ± 31.0 | 86.7 ± 38.1 | 88.3 ± 41.0 | 89.7 ± 40.4 |
Comorbidity | ||||
Hypertension | 2,406,414 (34.3) | 829,585 (29.8) | 404,736 (36.4) | 334,289 (40.2) |
Diabetes mellitus | 832,222 (11.9) | 274,386 (9.9) | 141,392 (12.7) | 126,937 (15.3) |
Dyslipidemia | 1,815,516 (25.9) | 564,073 (20.3) | 237,270 (21.3) | 181,905 (21.9) |
Chronic kidney disease | 615,309 (8.8) | 150,391 (5.4) | 47,429 (4.3) | 33,030 (4.0) |
Ischemic heart disease | 128,861 (1.8) | 36,448 (1.3) | 13,859 (1.3) | 10,802 (1.3) |
Stroke | 413,277 (5.9) | 85,355 (3.1) | 29,409 (2.6) | 23,340 (2.8) |
RA | 23,134 (0.3) | 3,059 (0.1) | 67 (0.1) | 416 (0.1) |
Income (lowest quartile) | 1,883,641 (26.9) | 671,687 (24.2) | 243,933 (21.9) | 186,379 (22.4) |
. | Nondrinker . | Mild drinker . | Moderate drinker . | Heavy drinker . |
---|---|---|---|---|
. | (n = 7,010,332) . | (n = 2,781,462) . | (n = 1,113,038) . | (n = 832,635) . |
Age (years) | 56.4 ± 11.0 | 51.8 ± 9.7 | 51.5 ± 9.1 | 52.3 ± 9.5 |
Sex (male) | 2,027,999 (28.9) | 1,805,061 (64.9) | 992,950 (89.2) | 786,681 (94.5) |
Alcohol intake (g/day) | - | 6.2 ± 3.6 | 20.6 ± 3.9 | 51.5 ± 26.5 |
Smoking status | ||||
Never | 5,810,163 (82.9) | 1,413,540 (50.8) | 283,125 (25.4) | 168,006 (20.2) |
Ex-smoker < 20 PY | 330,639 (4.7) | 426,874 (15.4) | 190,356 (17.1) | 116,989 (14.1) |
Ex-smoker ≥ 20 PY | 235,408 (3.4) | 195,990 (7.1) | 122,703 (11.0) | 118,340 (14.2) |
Current smoker < 20 PY | 281,892 (4.0) | 404,652 (14.6) | 227,469 (20.4) | 128,900 (15.5) |
Current smoker ≥ 20 PY | 352,230 (5.0) | 340,406 (12.2) | 289,385 (26.0) | 300,400 (36.1) |
Regular physical activity | 1,273,473 (18.2) | 615,562 (22.2) | 253,247 (22.8) | 186,522 (22.4) |
Anthropometrics | ||||
BMI (kg/m2) | 23.9 ± 3.1 | 23.9 ± 2.9 | 24.3 ± 2.9 | 24.4 ± 3.0 |
Waist circumference (cm) | 80.0 ± 8.7 | 81.5 ± 8.4 | 84.1 ± 7.7 | 85.1 ± 7.8 |
Systolic BP (mmHg) | 123.4 ± 15.7 | 123.5 ± 14.9 | 126.8 ± 14.8 | 128.3 ± 15.1 |
Diastolic BP (mmHg) | 76.1 ± 10.1 | 77.2 ± 10.1 | 79.6 ± 10.0 | 80.5 ± 10.1 |
Laboratory findings | ||||
Fasting glucose (mg/dL) | 98.9 ± 24.0 | 99.4 ± 23.4 | 103.0 ± 26.5 | 105.8 ± 29.2 |
Total cholesterol (mg/dL) | 199.8 ± 37.6 | 198.1 ± 35.8 | 199.0 ± 36.1 | 198.4 ± 37.0 |
Triglycerides (mg/dL) | 111.9 (111.8–111.9) | 116.0 (115.9–116.1) | 137.8 (137.6–137.9) | 147.9 (147.7–148.1) |
HDL-C (mg/dL) | 54.5 ± 17.3 | 55.0 ± 15.4 | 55.1 ± 15.5 | 56.1 ± 16.6 |
LDL-C (mg/dL) | 119.9 ± 34.3 | 116.1 ± 33.1 | 111.9 ± 34.2 | 107.7 ± 35.3 |
eGFR (mL/min/1.73 m2) | 84.6 ± 31.0 | 86.7 ± 38.1 | 88.3 ± 41.0 | 89.7 ± 40.4 |
Comorbidity | ||||
Hypertension | 2,406,414 (34.3) | 829,585 (29.8) | 404,736 (36.4) | 334,289 (40.2) |
Diabetes mellitus | 832,222 (11.9) | 274,386 (9.9) | 141,392 (12.7) | 126,937 (15.3) |
Dyslipidemia | 1,815,516 (25.9) | 564,073 (20.3) | 237,270 (21.3) | 181,905 (21.9) |
Chronic kidney disease | 615,309 (8.8) | 150,391 (5.4) | 47,429 (4.3) | 33,030 (4.0) |
Ischemic heart disease | 128,861 (1.8) | 36,448 (1.3) | 13,859 (1.3) | 10,802 (1.3) |
Stroke | 413,277 (5.9) | 85,355 (3.1) | 29,409 (2.6) | 23,340 (2.8) |
RA | 23,134 (0.3) | 3,059 (0.1) | 67 (0.1) | 416 (0.1) |
Income (lowest quartile) | 1,883,641 (26.9) | 671,687 (24.2) | 243,933 (21.9) | 186,379 (22.4) |
Note: Data are expressed as mean ± SD or number (%), except for triglycerides, which are presented as media (interquartile range) using the Wilcoxon rank-sum test.
Abbreviations: eGFR, estimated glomerular filtration rate; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol PY, pack-years;.
Alcohol intake and multiple myeloma
During a mean follow-up of 6.8 years after a one-year lag period, 6,981 subjects (3,921 men and 3,060 women) were newly diagnosed with multiple myeloma. Compared with nondrinkers, all drinkers were at a significantly reduced risk for multiple myeloma in a dose-dependent manner: mild drinkers (aHR, 0.89; 95% CI, 0.84–0.95), moderate drinkers (aHR, 0.83; 95% CI, 0.76–0.91), and heavy drinkers (aHR, 0.76; 95% CI, 0.69–0.85). With respect to the frequency of drinking per week, 1 to 6 days of drinking per week was significantly associated with a 12% to 31% lower risk of multiple myeloma compared with not drinking (aHR, 0.69–0.88), whereas drinking every day showed only a marginally inverse association (aHR, 0.89; 95% CI, 0.77–1.02). As the amount of alcohol consumption per session increased, the risk of multiple myeloma decreased linearly in a dose-dependent manner (aHR, 0.70; 95% CI, 0.55–0.89 in subjects who drank > 14 units per session; Table 2; Fig. 1).
. | Subjects . | Events . | Person-years . | Incidence rate . | Model 1 . | Model 2 . |
---|---|---|---|---|---|---|
. | (N) . | (n) . | . | (per 100,000 person-years) . | aHR (95% CI) . | aHR (95% CI) . |
Weekly alcohol intake | ||||||
Nondrinker | 7,010,332 | 4,556 | 47815671.1 | 9.5 | 1 (ref.) | 1 (ref.) |
Mild drinker | 2,781,462 | 1,434 | 19069083.3 | 7.5 | 0.89 (0.84–0.95) | 0.89 (0.84–0.95) |
Moderate drinker | 1,113,038 | 566 | 7611783.3 | 7.4 | 0.85 (0.77–0.93) | 0.83 (0.76–0.91) |
Heavy drinker | 832,635 | 425 | 5663888.8 | 7.5 | 0.79 (0.71–0.87) | 0.76 (0.69, 0.85) |
Frequency (days per week) | ||||||
0 | 7,010,332 | 4,556 | 47815671.1 | 9.5 | 1 (ref.) | 1 (ref.) |
1 | 1,897,327 | 868 | 13042318.9 | 6.7 | 0.88 (0.82–0.95) | 0.88 (0.82–0.95) |
2 | 1,224,552 | 587 | 8400144.5 | 7.0 | 0.85 (0.78–0.93) | 0.85 (0.77–0.93) |
3 | 787,753 | 433 | 5380087.7 | 8.0 | 0.90 (0.81–0.99) | 0.88 (0.79–0.98) |
4 | 272,126 | 150 | 1853588.2 | 8.1 | 0.85 (0.72–1.00) | 0.83 (0.70–0.98) |
5 | 208,885 | 104 | 1416887.6 | 7.3 | 0.71 (0.58–0.86) | 0.69 (0.56–0.84) |
6 | 117,079 | 80 | 788992.3 | 10.1 | 0.80 (0.64–1.00) | 0.79 (0.63–0.98) |
7 | 219,413 | 203 | 1462736.2 | 13.9 | 0.90 (0.78–1.04) | 0.89 (0.77–1.02) |
Amount (units per session) | ||||||
0 | 7,010,332 | 4,556 | 47815671.1 | 9.5 | 1 (ref.) | 1 (ref.) |
1–2 | 827,080 | 470 | 5642998.6 | 8.3 | 0.87 (0.79–0.96) | 0.88 (0.80–0.97) |
3–4 | 1,155,831 | 664 | 7910930.2 | 8.4 | 0.89 (0.82–0.97) | 0.89 (0.82–0.97) |
5–7 | 1,622,238 | 870 | 11091624.6 | 7.8 | 0.90 (0.83–0.98) | 0.89 (0.82–0.96) |
8–14 | 923,266 | 349 | 6334242.6 | 5.5 | 0.74 (0.66–0.83) | 0.71 (0.64–0.80) |
>14 | 198,720 | 72 | 1364959.3 | 5.3 | 0.73 (0.58–0.93) | 0.70 (0.55–0.89) |
. | Subjects . | Events . | Person-years . | Incidence rate . | Model 1 . | Model 2 . |
---|---|---|---|---|---|---|
. | (N) . | (n) . | . | (per 100,000 person-years) . | aHR (95% CI) . | aHR (95% CI) . |
Weekly alcohol intake | ||||||
Nondrinker | 7,010,332 | 4,556 | 47815671.1 | 9.5 | 1 (ref.) | 1 (ref.) |
Mild drinker | 2,781,462 | 1,434 | 19069083.3 | 7.5 | 0.89 (0.84–0.95) | 0.89 (0.84–0.95) |
Moderate drinker | 1,113,038 | 566 | 7611783.3 | 7.4 | 0.85 (0.77–0.93) | 0.83 (0.76–0.91) |
Heavy drinker | 832,635 | 425 | 5663888.8 | 7.5 | 0.79 (0.71–0.87) | 0.76 (0.69, 0.85) |
Frequency (days per week) | ||||||
0 | 7,010,332 | 4,556 | 47815671.1 | 9.5 | 1 (ref.) | 1 (ref.) |
1 | 1,897,327 | 868 | 13042318.9 | 6.7 | 0.88 (0.82–0.95) | 0.88 (0.82–0.95) |
2 | 1,224,552 | 587 | 8400144.5 | 7.0 | 0.85 (0.78–0.93) | 0.85 (0.77–0.93) |
3 | 787,753 | 433 | 5380087.7 | 8.0 | 0.90 (0.81–0.99) | 0.88 (0.79–0.98) |
4 | 272,126 | 150 | 1853588.2 | 8.1 | 0.85 (0.72–1.00) | 0.83 (0.70–0.98) |
5 | 208,885 | 104 | 1416887.6 | 7.3 | 0.71 (0.58–0.86) | 0.69 (0.56–0.84) |
6 | 117,079 | 80 | 788992.3 | 10.1 | 0.80 (0.64–1.00) | 0.79 (0.63–0.98) |
7 | 219,413 | 203 | 1462736.2 | 13.9 | 0.90 (0.78–1.04) | 0.89 (0.77–1.02) |
Amount (units per session) | ||||||
0 | 7,010,332 | 4,556 | 47815671.1 | 9.5 | 1 (ref.) | 1 (ref.) |
1–2 | 827,080 | 470 | 5642998.6 | 8.3 | 0.87 (0.79–0.96) | 0.88 (0.80–0.97) |
3–4 | 1,155,831 | 664 | 7910930.2 | 8.4 | 0.89 (0.82–0.97) | 0.89 (0.82–0.97) |
5–7 | 1,622,238 | 870 | 11091624.6 | 7.8 | 0.90 (0.83–0.98) | 0.89 (0.82–0.96) |
8–14 | 923,266 | 349 | 6334242.6 | 5.5 | 0.74 (0.66–0.83) | 0.71 (0.64–0.80) |
>14 | 198,720 | 72 | 1364959.3 | 5.3 | 0.73 (0.58–0.93) | 0.70 (0.55–0.89) |
Note: Model 1: adjusted for age and sex. Model 2: Model 1 plus additional adjustment for income, smoking, regular exercise, BMI, and diabetes mellitus. Statistically significant values are marked in bold.
Alcohol intake pattern and multiple myeloma: frequency versus amount per session
When we performed analyses stratified by weekly alcohol consumption status, the analyses showed that the tendency of association between frequency of drinking and the risk of multiple myeloma in the heavy drinker group was different from that in the mild and moderate drinker groups (Table 3; Fig. 2). The risk of multiple myeloma was the greatest in those who drank 3 to 4 times per week and the lowest in those who drank 5 to 7 times per week in mild and moderate drinker groups. In the heavy drinker group, as the frequency of drinking increased, the risk of multiple myeloma increased linearly in a dose-dependent manner (aHR, 0.59; 95% CI, 0.41–0.86 for subjects who drank 1–2 times/week; aHR, 0.67; 95% CI, 0.56–0.80 for 3–4 times/week; and aHR, 0.85; 95% CI, 0.74–0.96 for 5–7 times/week). When assessed with respect to amount of alcohol consumed per session, the risk of multiple myeloma was lowest in those who drank ≥8 units per session in each strata.
. | Subjects . | Events . | Person-years . | Incidence rate . | Model 1 . | Model 2 . | |
---|---|---|---|---|---|---|---|
. | (N) . | (n) . | . | (per 100,000 person-years) . | aHR (95% CI) . | aHR (95% CI) . | |
Frequency (days per week) | |||||||
Nondrinker | 0 | 7,010,332 | 4,556 | 47815671.1 | 9.5 | 1 (ref.) | 1 (ref.) |
Mild drinker | 1–2 | 2,478,062 | 1,201 | 17015675.1 | 7.1 | 0.89 (0.83–0.95) | 0.89 (0.83–0.95) |
3–4 | 262,156 | 198 | 1779678.2 | 11.1 | 0.96 (0.83–1.11) | 0.96 (0.83–1.11) | |
5–7 | 41,244 | 35 | 273730.1 | 12.8 | 0.78 (0.56–1.09) | 0.78 (0.56–1.09) | |
Moderate drinker | 1–2 | 547,950 | 226 | 3766478.4 | 6.0 | 0.81 (0.71–0.94) | 0.80 (0.69–0.92) |
3–4 | 438,236 | 255 | 2994646.0 | 8.5 | 0.95 (0.83–1.08) | 0.93 (0.81–1.06)a | |
5–7 | 126,852 | 85 | 850658.9 | 10.0 | 0.70 (0.56–0.86) | 0.69 (0.56–0.86)a | |
Heavy drinker | 1–2 | 95,867 | 28 | 660309.9 | 4.2 | 0.62 (0.42–0.89) | 0.59 (0.41–0.86) |
3–4 | 359,487 | 130 | 2459351.7 | 5.3 | 0.69 (0.58–0.83) | 0.67 (0.56–0.80) | |
5–7 | 377,281 | 267 | 2544227.1 | 10.5 | 0.87 (0.77–0.99) | 0.85 (0.74–0.96) | |
Amount (units per session) | |||||||
Nondrinker | 0 | 7,010,332 | 4,556 | 47815671.1 | 9.5 | 1 (ref.) | 1 (ref.) |
Mild drinker | 1–2 | 807,489 | 453 | 5513671.2 | 8.2 | 0.88 (0.80–0.97) | 0.89 (0.80–0.98) |
3–4 | 1,033,278 | 565 | 7087392.0 | 8.0 | 0.91 (0.83–0.99) | 0.91 (0.83–0.99) | |
5–7 | 740,175 | 352 | 5084315.8 | 6.9 | 0.93 (0.83–1.04) | 0.92 (0.82–1.03) | |
≥ 8 | 200,520 | 64 | 1383704.2 | 4.6 | 0.71 (0.55–0.91) | 0.70 (0.54–0.90) | |
Moderate drinker | 1–2 | 19,591 | 17 | 129327.4 | 13.1 | 0.73 (0.45–1.18) | 0.73 (0.46–1.18) |
3–4 | 104,558 | 75 | 703463.1 | 10.7 | 0.75 (0.60–0.95) | 0.74 (0.59–0.94) | |
5–7 | 623,044 | 339 | 4259040.6 | 8.0 | 0.91 (0.81–1.02) | 0.89 (0.79–0.99) | |
≥ 8 | 365,845 | 135 | 2519952.2 | 5.4 | 0.78 (0.65–0.93) | 0.76 (0.63–0.90) | |
Heavy drinker | 3–4 | 17,995 | 24 | 120075.1 | 20.0 | 1.19 (0.80–1.78) | 1.18 (0.79–1.76) |
5–7 | 259,019 | 179 | 1748268.2 | 10.2 | 0.84 (0.72–0.98) | 0.82 (0.70–0.96) | |
≥ 8 | 555,621 | 222 | 3795545.5 | 5.8 | 0.72 (0.63–0.83) | 0.69 (0.60–0.80) |
. | Subjects . | Events . | Person-years . | Incidence rate . | Model 1 . | Model 2 . | |
---|---|---|---|---|---|---|---|
. | (N) . | (n) . | . | (per 100,000 person-years) . | aHR (95% CI) . | aHR (95% CI) . | |
Frequency (days per week) | |||||||
Nondrinker | 0 | 7,010,332 | 4,556 | 47815671.1 | 9.5 | 1 (ref.) | 1 (ref.) |
Mild drinker | 1–2 | 2,478,062 | 1,201 | 17015675.1 | 7.1 | 0.89 (0.83–0.95) | 0.89 (0.83–0.95) |
3–4 | 262,156 | 198 | 1779678.2 | 11.1 | 0.96 (0.83–1.11) | 0.96 (0.83–1.11) | |
5–7 | 41,244 | 35 | 273730.1 | 12.8 | 0.78 (0.56–1.09) | 0.78 (0.56–1.09) | |
Moderate drinker | 1–2 | 547,950 | 226 | 3766478.4 | 6.0 | 0.81 (0.71–0.94) | 0.80 (0.69–0.92) |
3–4 | 438,236 | 255 | 2994646.0 | 8.5 | 0.95 (0.83–1.08) | 0.93 (0.81–1.06)a | |
5–7 | 126,852 | 85 | 850658.9 | 10.0 | 0.70 (0.56–0.86) | 0.69 (0.56–0.86)a | |
Heavy drinker | 1–2 | 95,867 | 28 | 660309.9 | 4.2 | 0.62 (0.42–0.89) | 0.59 (0.41–0.86) |
3–4 | 359,487 | 130 | 2459351.7 | 5.3 | 0.69 (0.58–0.83) | 0.67 (0.56–0.80) | |
5–7 | 377,281 | 267 | 2544227.1 | 10.5 | 0.87 (0.77–0.99) | 0.85 (0.74–0.96) | |
Amount (units per session) | |||||||
Nondrinker | 0 | 7,010,332 | 4,556 | 47815671.1 | 9.5 | 1 (ref.) | 1 (ref.) |
Mild drinker | 1–2 | 807,489 | 453 | 5513671.2 | 8.2 | 0.88 (0.80–0.97) | 0.89 (0.80–0.98) |
3–4 | 1,033,278 | 565 | 7087392.0 | 8.0 | 0.91 (0.83–0.99) | 0.91 (0.83–0.99) | |
5–7 | 740,175 | 352 | 5084315.8 | 6.9 | 0.93 (0.83–1.04) | 0.92 (0.82–1.03) | |
≥ 8 | 200,520 | 64 | 1383704.2 | 4.6 | 0.71 (0.55–0.91) | 0.70 (0.54–0.90) | |
Moderate drinker | 1–2 | 19,591 | 17 | 129327.4 | 13.1 | 0.73 (0.45–1.18) | 0.73 (0.46–1.18) |
3–4 | 104,558 | 75 | 703463.1 | 10.7 | 0.75 (0.60–0.95) | 0.74 (0.59–0.94) | |
5–7 | 623,044 | 339 | 4259040.6 | 8.0 | 0.91 (0.81–1.02) | 0.89 (0.79–0.99) | |
≥ 8 | 365,845 | 135 | 2519952.2 | 5.4 | 0.78 (0.65–0.93) | 0.76 (0.63–0.90) | |
Heavy drinker | 3–4 | 17,995 | 24 | 120075.1 | 20.0 | 1.19 (0.80–1.78) | 1.18 (0.79–1.76) |
5–7 | 259,019 | 179 | 1748268.2 | 10.2 | 0.84 (0.72–0.98) | 0.82 (0.70–0.96) | |
≥ 8 | 555,621 | 222 | 3795545.5 | 5.8 | 0.72 (0.63–0.83) | 0.69 (0.60–0.80) |
Note: Model 1: adjusted for age and sex. Model 2: Model 1 plus additional adjustment for income, smoking, regular exercise, BMI, and diabetes mellitus. Statistically significant values are marked in bold.
aSignificantly different (P < 0.05).
Sex differences
When we performed analyses stratified by sex, alcohol consumption reduced the risk of multiple myeloma in both sexes (Table 4; Fig. 1). The association between alcohol consumption and reduced risk of multiple myeloma was stronger in women [mild drinkers (aHR, 0.84; 95% CI, 0.75–0.96), moderate drinkers (aHR, 0.68; 95% CI, 0.47–0.99), and heavy drinkers (aHR, 0.66; 95% CI, 0.35–1.23)] than in men [mild drinkers (aHR, 0.92; 95% CI, 0.85–0.99), moderate drinkers (aHR, 0.86; 95% CI, 0.78–0.95), and heavy drinkers (aHR, 0.78; 95% CI, 0.70–0.87)]. However, the estimates were not statistically significant due to the low number of heavy drinkers among the female study subjects.
. | Men . | Women . | ||||||
---|---|---|---|---|---|---|---|---|
. | Subjects . | Events . | Incidence rate . | aHR (95% CI)a . | Subjects . | Events . | Incidence rate . | aHR (95% CI)† . |
. | (N) . | (n) . | (per 100,000 person-years) . | . | (N) . | (n) . | (per 100,000 person-years) . | . |
Weekly alcohol intake | ||||||||
Nondrinker | 2,027,999 | 1,827 | 13.4 | 1 (ref.) | 4,982,333 | 2,729 | 8.0 | 1 (ref.) |
Mild drinker | 1,805,061 | 1,140 | 9.2 | 0.92 (0.85–0.99) | 976,401 | 294 | 4.4 | 0.84 (0.75–0.96) |
Moderate drinker | 992,950 | 539 | 7.9 | 0.86 (0.78–0.95) | 120,088 | 27 | 3.3 | 0.68 (0.47–0.99) |
Heavy drinker | 786,681 | 415 | 7.8 | 0.78 (0.70–0.87) | 45,954 | 10 | 3.2 | 0.66 (0.35–1.23) |
Frequency (days per week) | ||||||||
0 | 2,027,999 | 1,827 | 13.4 | 1 (ref.) | 4,982,333 | 2,729 | 8.0 | 1 (ref.) |
1 | 1,199,692 | 662 | 8.0 | 0.91 (0.83–0.99) | 697,635 | 206 | 4.3 | 0.84 (0.73–0.97) |
2 | 981,169 | 523 | 7.8 | 0.88 (0.79–0.97) | 243,383 | 64 | 3.8 | 0.77 (0.60–0.99) |
3 | 674,025 | 393 | 8.5 | 0.89 (0.79–0.99) | 113,728 | 40 | 5.1 | 1.02 (0.74–1.40) |
4 | 242,293 | 145 | 8.8 | 0.87 (0.73–1.03) | 29,833 | 5 | 2.4 | 0.47 (0.20–1.14) |
5 | 187,341 | 98 | 7.7 | 0.69 (0.57–0.85) | 21,544 | 6 | 4.1 | 0.76 (0.34–1.69) |
6 | 106,745 | 77 | 10.7 | 0.79 (0.63–0.99) | 10,334 | 3 | 4.2 | 0.67 (0.21–2.06) |
7 | 193,427 | 196 | 15.3 | 0.90 (0.77–1.04) | 25,986 | 7 | 3.9 | 0.54 (0.26–1.13) |
Amount (units per session) | ||||||||
0 | 2,027,999 | 1,827 | 13.4 | 1 (ref.) | 4,982,333 | 2,729 | 8.0 | 1 (ref.) |
1–2 | 384,596 | 319 | 12.3 | 0.89 (0.79–1.00) | 442,484 | 151 | 5.0 | 0.84 (0.72–0.99) |
3–4 | 759,761 | 571 | 11.0 | 0.94 (0.85–1.03) | 396,070 | 93 | 3.4 | 0.70 (0.57–0.87) |
5–7 | 1,381,879 | 796 | 8.4 | 0.89 (0.82–0.98) | 240,359 | 74 | 4.5 | 1.02 (0.81–1.30) |
8–14 | 866,673 | 337 | 5.7 | 0.74 (0.66–0.84) | 56,593 | 12 | 3.1 | 0.73 (0.41–1.29) |
>14 | 191,783 | 71 | 5.4 | 0.74 (0.58–0.94) | 6,937 | 1 | 2.1 | 0.48 (0.07–3.38) |
. | Men . | Women . | ||||||
---|---|---|---|---|---|---|---|---|
. | Subjects . | Events . | Incidence rate . | aHR (95% CI)a . | Subjects . | Events . | Incidence rate . | aHR (95% CI)† . |
. | (N) . | (n) . | (per 100,000 person-years) . | . | (N) . | (n) . | (per 100,000 person-years) . | . |
Weekly alcohol intake | ||||||||
Nondrinker | 2,027,999 | 1,827 | 13.4 | 1 (ref.) | 4,982,333 | 2,729 | 8.0 | 1 (ref.) |
Mild drinker | 1,805,061 | 1,140 | 9.2 | 0.92 (0.85–0.99) | 976,401 | 294 | 4.4 | 0.84 (0.75–0.96) |
Moderate drinker | 992,950 | 539 | 7.9 | 0.86 (0.78–0.95) | 120,088 | 27 | 3.3 | 0.68 (0.47–0.99) |
Heavy drinker | 786,681 | 415 | 7.8 | 0.78 (0.70–0.87) | 45,954 | 10 | 3.2 | 0.66 (0.35–1.23) |
Frequency (days per week) | ||||||||
0 | 2,027,999 | 1,827 | 13.4 | 1 (ref.) | 4,982,333 | 2,729 | 8.0 | 1 (ref.) |
1 | 1,199,692 | 662 | 8.0 | 0.91 (0.83–0.99) | 697,635 | 206 | 4.3 | 0.84 (0.73–0.97) |
2 | 981,169 | 523 | 7.8 | 0.88 (0.79–0.97) | 243,383 | 64 | 3.8 | 0.77 (0.60–0.99) |
3 | 674,025 | 393 | 8.5 | 0.89 (0.79–0.99) | 113,728 | 40 | 5.1 | 1.02 (0.74–1.40) |
4 | 242,293 | 145 | 8.8 | 0.87 (0.73–1.03) | 29,833 | 5 | 2.4 | 0.47 (0.20–1.14) |
5 | 187,341 | 98 | 7.7 | 0.69 (0.57–0.85) | 21,544 | 6 | 4.1 | 0.76 (0.34–1.69) |
6 | 106,745 | 77 | 10.7 | 0.79 (0.63–0.99) | 10,334 | 3 | 4.2 | 0.67 (0.21–2.06) |
7 | 193,427 | 196 | 15.3 | 0.90 (0.77–1.04) | 25,986 | 7 | 3.9 | 0.54 (0.26–1.13) |
Amount (units per session) | ||||||||
0 | 2,027,999 | 1,827 | 13.4 | 1 (ref.) | 4,982,333 | 2,729 | 8.0 | 1 (ref.) |
1–2 | 384,596 | 319 | 12.3 | 0.89 (0.79–1.00) | 442,484 | 151 | 5.0 | 0.84 (0.72–0.99) |
3–4 | 759,761 | 571 | 11.0 | 0.94 (0.85–1.03) | 396,070 | 93 | 3.4 | 0.70 (0.57–0.87) |
5–7 | 1,381,879 | 796 | 8.4 | 0.89 (0.82–0.98) | 240,359 | 74 | 4.5 | 1.02 (0.81–1.30) |
8–14 | 866,673 | 337 | 5.7 | 0.74 (0.66–0.84) | 56,593 | 12 | 3.1 | 0.73 (0.41–1.29) |
>14 | 191,783 | 71 | 5.4 | 0.74 (0.58–0.94) | 6,937 | 1 | 2.1 | 0.48 (0.07–3.38) |
Note: Statistically significant values are marked in bold.
aAdjusted for age, income, smoking, regular exercise, BMI, and diabetes mellitus.
Sensitivity analyses
The association pattern between alcohol consumption and the risk of multiple myeloma was not changed by further adjustment for lipid levels (TG, HDL-C, and LDL-C) and RA, although the association was slightly attenuated by further adjustment (Supplementary Tables S1 and S2).
Discussion
In this large population-based cohort study, we assessed the effects of weekly average alcohol consumption as well as the weekly frequency of drinking and the amount of alcohol consumption per session, which have not been examined in previous studies, on the risk of multiple myeloma. Our analyses provided solid evidence indicating the average weekly alcohol consumption and the risk of multiple myeloma are inversely associated in a dose-dependent manner, which appeared more evident in women than men. Moreover, we found that both the frequency and amount of alcohol drinking were associated with the risk of multiple myeloma. The strengths of our study included an unprecedentedly large and representative study population (N = 11,737,467) and number of cases (N = 6,981) and near complete follow-up.
Most of the previously published cohort studies reported null associations between alcohol consumption and the risk of multiple myeloma (10–16), but these studies may have been limited by their inclusion of only relatively small numbers of cases (69–786 multiple myeloma cases; ref. 10–16), low prevalence of heavy drinking among the study subjects (15), and/or the presence of uncontrolled confounders such as BMI (16) or regular physical activity (11, 12, 14, 16). On the other hand, three recent cohort studies (6–8) reported inverse associations between alcohol consumption and the risk of multiple myeloma. A prospective investigation in Sweden found that the risk of multiple myeloma (SIR, 0.52; 95% CI, 0.45–0.60) was significantly lower among individuals with alcohol use disorder (AUD, also termed problem drinking) compared with the general population without AUD (7). In the UK Million Women Study of about 1.3 million middle-aged women, greater alcohol intake was associated with significantly reduced risk of multiple myeloma (RR, 0.88 per 10 g alcohol/day; 95% CI, 0.80–0.98; ref. 8). In a recent large-scale NIH-AARP cohort study, increasing alcohol consumption was reported to be inversely associated with multiple myeloma (aHR, 0.96 per 10 g alcohol/day; 95% CI, 0.93–0.99; ref. 6). The latter two cohort studies included relatively large numbers of cases [1,312 (6) and 1,162 (8) multiple myeloma cases, respectively] and longer follow-up periods [11.8 (6) and 10.3 (8) years, respectively] compared with other similar studies in general. The current study is the largest (6,981 multiple myeloma cases) to date examining the association of alcohol consumption with multiple myeloma, and provides solid evidence supporting the inverse association between alcohol consumption and the risk of multiple myeloma, consistent with the results of aforementioned recent cohort studies.
The biological mechanisms underlying the influence of alcohol consumption on hematologic malignancies including multiple myeloma have not been thoroughly investigated. Nevertheless, we can infer the possible underlying biological mechanisms from clues provided by related studies. One previous study reported that mild to moderate drinking might improve immunologic function by improving cellular and humoral immune responses (35). In addition, it has been reported that exposure to ethanol-induced dose-dependent inhibition of the mTOR signaling, a key driver and regulator of cell growth, proliferation, and survival, in a lymphoid-tissue-specific manner, and in a xenograft model, chronic exposure to alcohol at physiologically relevant concentrations resulted in inhibition of lymphoma growth through disruption of mTOR signaling (36).
Our study showed an inverse association between alcohol consumption and the risk of multiple myeloma, which is different from the results reported in the majority of previous cohort studies that indicated there was no dose–response relationship despite a lower risk of multiple myeloma in drinkers (8, 10, 13–16). For example, in the UK Million Women Study, those who consumed ≥3 drinks per week had a lower risk of multiple myeloma compared with those who consumed <3 drinks per week, while the risk did not increase further with greater alcohol consumption (aHR, 0.83; 95% CI, 0.72–0.97 for 3 to <7 drinks per week; and aHR, 0.85; 95% CI, 0.74–0.98 for >7 drinks per week; ref. 8). However, in this study, the four weekly alcohol consumption categories comprised nondrinkers, and those who drank 0.5 to <3, 3 to < 7, or >7 drinks per week, thereby making analyses of what could be considered moderate-to-heavy drinkers less specific. On the other hand, a very recent large-scale NIH-AARP cohort study reported a dose–response relationship (Ptrend = 0.01; ref. 6) similar to that found in our study. In addition, an inverse association between alcohol consumption and the risk of multiple myeloma was also reported in a recent meta-analysis when the analyses included only with cohort studies [mild drinkers (aHR, 1.01; 95% CI, 0.85–1.21), moderate drinkers (aHR, 0.87; 95% CI, 0.78–0.97), and heavy drinkers (aHR, 0.66; 95% CI, 0.34–1.25; ref. 17). Thus, together with these recent studies, our study provides solid evidence supporting an inverse association between alcohol consumption and the risk of multiple myeloma.
Alcohol intake patterns vary between individuals: for example, some people drink small amounts of alcohol every day, while others binge drink once a week. The findings of a previous study suggested that the frequency of drinking and the amount of alcohol consumption per session has different influences on the associations between alcohol consumption and cancer risk; specifically, for alcohol-related cancers (cancers of the oral cavity, pharynx, larynx, esophagus colorectum, and liver), increased frequency of drinking was associated with increased risk of cancer in men (37). Notably, in a recent study on the association between alcohol intake and the risk of gastrointestinal cancer using the same Korean NIHS database, drinking frequency and the amount per drinking session showed noticeably a different association pattern with the risk of gastrointestinal cancer, different from our results. The authors concluded that frequent drinking was a more important risk factor for incident gastrointestinal cancers than the amount of alcohol consumed per session (24), which can serve as a good comparison to our study. To the best of our knowledge, all previous studies investigating alcohol consumption and multiple myeloma risk used total overall alcohol consumption (determined by the average number of drinks consumed in a day or a week) as a criterion. When we evaluated the relative contribution of the frequency of drinking and the amount of alcohol consumption per session on the risk of multiple myeloma incidence, drinking frequency and amount per session did not significantly differ in their contribution to the risk of multiple myeloma.
Interestingly, however, a difference was noted between the frequency of alcohol consumption and the risk of multiple myeloma in the heavy drinkers compared with that in the mild/moderate drinkers. Specifically, less frequent alcohol consumption (Fig. 2A) and binge drinking (Fig. 2B) were associated with lower risk of multiple myeloma in the heavy drinker group. Heavy drinking is defined by total amount of alcohol consumption, and this group includes different subpopulations such as binge drinkers who consume alcohol infrequently and daily drinkers who consume a lower amount of alcohol per occasion. Therefore, individuals who typically consume 3 to 4 drinks per day every day seemed to have a less preventive effect from alcohol consumption than binge drinkers. The reason for this is not clear, but we suggest several possibilities. First, chronic use of a certain amount of alcohol might induce tolerance to the preventive mechanisms, such as ethanol-induced dose-dependent inhibition of mTOR signaling, as described above. This hypothesis should be explored in further studies. Second, certain social or genetic properties related to chronic heavy alcohol use may not be fully covered by our study analysis. Finally, these results may be obtained just by chance because of the relatively small number of individuals in the study population belonging to the “heavy drinker” group. Further studies are warranted to explore whether such association found in our study will be replicated in other populations.
In this study, the inverse association between alcohol consumption and the risk of multiple myeloma was stronger in women than in men, which is consistent with previous findings (7, 17). In a recent meta-analysis, a protective effect of alcohol drinking was reported for females (pooled RR, 0.79; 95% CI, 0.69–0.89 for ever drinkers), whereas no significant effect was reported for males (pooled RR, 0.89; 95% CI, 0.72–1.10; ref. 17). In general, because women have less fluid in their bodies to distribute alcohol around, compared with men, they have higher blood alcohol levels after drinking the same amount of alcohol (38). Moreover, alcohol dehydrogenase levels in the stomach are lower in women than men, which increases the bioavailability of alcohol (39). Thus, we postulate that a greater sensitivity to alcohol among the women in our study may underlie the protective effect of alcohol consumption on the risk of multiple myeloma in this study. However, this possibility is not strongly supported by clear evidence or well-established previous findings, and therefore further studies are warranted to explore this possibility.
Notably, very recent studies proposed an association between lipid levels and the risk of multiple myeloma. These studies reported that low levels of HDL-C (22), TC, TG, and LDL-C (23) were associated with an increased risk of multiple myeloma. When we further analyzed the data with adjustment for TG, HDL-C, and LDL-C, the results were consistent with the main conclusion from our original analysis. Moreover, the potential presence of the positive association between autoimmune disease and the risk of multiple myeloma has been proposed by previous studies. In the meta-analysis by McShane and colleagues, “any autoimmune disorder” was associated with an increased risk of multiple myeloma (RR, 1.13; 95% CI, 1.04–1.22; ref. 33). However, there was some evidence of moderate heterogeneity (I2 = 43%; P ≤ 0.001). Likewise, in another meta-analysis by Shen and colleagues, the meta-estimate of the association between RA and multiple myeloma was 1.14 (95% CI, 0.97–1.33) overall, with significant heterogeneity among studies (32). However, subgroup analysis in cohort studies revealed that patients with RA are more likely to suffer from subsequent multiple myeloma (RR, 1.32; 95% CI, 1.04–1.67). When we further analyzed the data with an additional adjustment for RA, the results were almost similar to those without further adjustment. Collectively, these results provide solid evidence supporting the association between alcohol consumption and the risk of multiple myeloma.
There were several limitations to our study. First, our study subjects were limited to health screening participants and may have been healthier and more engaged in having a healthy lifestyle than the general population. Second, the study subjects may have underreported their alcohol consumption (40, 41) in their self-administered questionnaires. Third, some participants who abstained from alcohol consumption might have had underlying health issues that affected their drinking patterns. However, we have adjusted the data with potential comorbidity confounders (DM and RA) in our analysis, and the results were consistent. In addition, a dose-related association in the current study makes this a less likely explanation. Fourth, our data were obtained from an East Asian population having a high prevalence of the ALDH2*2 allele, which encodes an ALDH2 enzyme with extremely low enzymatic activity required for the metabolism of acetaldehyde, an alcohol metabolite, into acetate. Thus, caution is required when applying our results to other ethnic groups. Fifth, while "nondrinker" refers to current drinking status, there was no information available about former drinking. Sixth, the type of alcoholic beverage was not considered in our analyses. Lastly, it is possible that missing data could have impacted our study results, although the proportion of cases with any type of missing data in our study was small, at approximately 4.3%.
In summary, our analysis of data from a nationwide cohort study showed that both the frequency and amount of alcohol consumed were inversely associated with the risk of multiple myeloma. More strikingly, we found that total average alcohol consumption and the risk of multiple myeloma had an obvious inverse dose–response relationship, which appeared to be stronger in women than men.
Authors' Disclosures
T. Choi reports personal fees from Janssen Biotech outside the submitted work. No disclosures were reported by the other authors.
Disclaimer
This study was performed using the database from the National Health Insurance System, and the results do not necessarily represent the opinion of the National Health Insurance Corporation.
Authors' Contributions
K.H. Jeon: Conceptualization, writing-original draft, writing-review and editing. S.M. Jeong: Conceptualization, writing-original draft, writing-review and editing. D.W. Shin: Conceptualization, supervision, writing-review and editing. K. Han: Formal analysis. D. Kim: Formal analysis. J.E. Yoo: Writing-review and editing. T. Choi: Writing-review and editing.
Acknowledgments
The authors received no specific funding for this work.
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