eAppendix. Questions on alcohol consumption in EIMS.
Hedström AK, Hillert J, Olsson T, Alfredsson L. Alcohol as a Modifiable Lifestyle Factor Affecting Multiple Sclerosis Risk. JAMA Neurol. 2014;71(3):300-305. doi:10.1001/jamaneurol.2013.5858
Alcohol consumption may be a modifiable lifestyle factor that affects the risk of developing multiple sclerosis (MS). Results of previous studies have been inconsistent.
To investigate the possible association of alcohol consumption with the risk of developing MS and to relate the influence of alcohol to the effect of smoking.
Design, Setting, and Participants
This report is based on 2 case-control studies: Epidemiological Investigation of Multiple Sclerosis (EIMS) included 745 cases and 1761 controls recruited from April 2005 to June 2011, and Genes and Environment in Multiple Sclerosis (GEMS) recruited 5874 cases and 5246 controls between November 2009 and November 2011. All cases fulfilled the McDonald criteria. Both EIMS and GEMS are population-based studies of the Swedish population aged 16 to 70 years. In EIMS, incident cases of MS were recruited via 40 study centers, including all university hospitals in Sweden. In GEMS, prevalent cases were identified from the Swedish national MS registry. In both studies, controls were randomly selected from the national population register, matched by age, sex, and residential area at the time of disease onset.
Main Outcome and Measure
Multiple sclerosis status.
There was a dose-dependent inverse association between alcohol consumption and risk of developing MS that was statistically significant in both sexes. In EIMS, women who reported high alcohol consumption had an odds ratio (OR) of 0.6 (95% CI, 0.4-1.0) of developing MS compared with nondrinking women, whereas men with high alcohol consumption had an OR of 0.5 (95% CI, 0.2-1.0) compared with nondrinking men. The OR for the comparison in GEMS was 0.7 (95% CI, 0.6-0.9) for women and 0.7 (95% CI, 0.2-0.9) for men. In both studies, the detrimental effect of smoking was more pronounced among nondrinkers.
Conclusions and Relevance
Alcohol consumption exhibits a dose-dependent inverse association with MS. Furthermore, alcohol consumption is associated with attenuation of the effect of smoking. Our findings may have relevance for clinical practice because they give no support for advising patients with MS to completely refrain from alcohol.
Quiz Ref IDMultiple sclerosis (MS) is a chronic neurological disease that develops as a result of the interplay between inducing and protective environmental and genetic factors. The impact of alcohol, which may directly suppress various immune responses,1 on the risk of developing MS has been investigated in 2 case-control studies2,3 and 1 prospective study.4 The results were inconsistent. However, case numbers have been small and some of the studies were subject to methodological limitations.2,3 A prospective study found no association between alcohol intake and risk of MS. Quiz Ref IDHowever, the risk of other autoimmune diseases such as autoimmune hypothyroidism,5 systemic lupus erythematosus,6 and rheumatoid arthritis7,8 has been found to be lower in alcohol drinkers as compared with nondrinkers. Extensive evidence indicates that alcohol has significant dose-dependent immunomodulatory properties.9 Using 2 large population-based case-control studies in Sweden, we investigated the possible association of alcohol consumption with the risk of MS and related the association of alcohol consumption to the effects of smoking, which is one of the most established risk factors in the etiology of the disease.
The Karolinska Institutet institutional review board approved our study. This report is based on data from 2 independent population-based case-control studies on environmental and genetic risk factors for MS. The first study is Epidemiological Investigation of Multiple Sclerosis (EIMS) with a study group comprising the population aged 16 to 70 years in Sweden. Incident cases were recruited via 40 study centers, including all university hospitals in Sweden. All cases were examined and diagnosed by a neurologist located at the unit where the case was entered. For each case, 2 controls were randomly selected from the national population register, matched by age (predetermined 5-year age groups), sex, and residential area. The study period was April 2005 to June 2011.
The second study is Genes and Environment in Multiple Sclerosis (GEMS) in which prevalent cases fulfilling the McDonald criteria were identified from the Swedish national MS registry. For each case, a control was randomly selected from the national population register matched by age, sex, and residential area at the time of the disease onset. The study participants were recruited between November 2009 and November 2011. All participants in GEMS were distinct from those in EIMS. Ethical approval for both EIMS and GEMS was obtained from the Regional Ethical Review Board in Stockholm (at Karolinska Institutet) and participants provided written informed consent.
In both studies, extensive questionnaires were used to collect information about demographic and reproductive factors, heredity, previous health, body weight and height, lifestyle factors, occupational exposures, and socioeconomic circumstances. The questionnaires were similar but not identical. All questionnaires were supposed to be answered at home.
In EIMS, participants were asked to provide information regarding current alcohol consumption and whether their current alcohol consumption differed from their alcohol consumption 5 years ago (eAppendix in Supplement). Incompletely answered questionnaires were completed by mail or telephone. In total, completed questionnaires were obtained from 1301 potential cases and 2826 controls, the response proportion being 91% for the case group and 69% for the controls. However, only participants with an estimated disease onset within the previous 5 years who reported no change in alcohol habits were included in the analysis (745 cases, 1761 controls). In GEMS, detailed information was obtained regarding alcohol consumption during different age periods up to the participants' current age (eAppendix in Supplement). With a response rate of 82% for the cases and 66% for the controls, the study comprised 5874 cases with MS and 5246 matched controls.
For each case, the time of the initial appearance of MS symptoms was used as an estimate of the disease onset, and the year in which this occurred was defined as the index year. The corresponding controls were given the same index year. In both studies, alcohol habits during the period comprising the index year (10-year period in GEMS and 5-year period in EIMS) were considered among cases and controls. Participants who had drunk alcohol during this period were defined as drinkers and participants who had not drunk alcohol were defined as nondrinkers. To analyze a possible dose-response association between alcohol intake and the risk of developing MS, we further categorized the drinkers into the following subgroups based on the amount of alcohol intake per week: low consumption (<50 g/wk for women and <100 g/wk for men), moderate consumption (50-112 g/wk for women and 100-168 g/wk for men), and high consumption (>112 g/wk for women and >168 g/wk for men). The cutoffs were the same as those used by Statistics Sweden.
Using logistic regression, the incidence of MS in participants with different alcohol habits was compared with that in nondrinkers by calculating odds ratios (ORs) with 95% CIs. The analyses were performed separately for men and women. Interaction, defined by departure from additivity of effects, was evaluated between alcohol and smoking by means of calculating the attributable proportion due to interaction together with its P value and 95% CI. The attributable proportion between 2 interacting factors reflects the joint effect beyond the sum of the independent effects.10
All analyses were adjusted for age, sex, and residential area (according to study design), ancestry, smoking, and body mass index at age 20 years. Age was categorized into the following 8 strata: 16 to 19, 20 to 24, 25 to 29, 30 to 34, 35 to 39, 40 to 44, 45 to 49, and 50 to 70 years of age. Assessment of ancestry was based on whether the participant was born in Sweden and whether either of the participant’s parents had immigrated to Sweden. A participant who was born in Sweden, whose parents had not immigrated, was classified as Swedish. Adjustments were also made for educational level (university degree or not), socioeconomic status (white collar, blue collar, other), parity (yes/no), sun exposure habits (low/high), and a history of infectious mononucleosis (yes/no). However, these factors had minor influence on the results and were not retained in the final analyses. All analyses were conducted using SAS version 9 (SAS Institute Inc).
Quiz Ref IDThe analyses of alcohol consumption and risk for MS based on EIMS included 745 cases and 1761 controls. The mean age at onset was 36.9 years and the median for the duration from the disease onset to the diagnosis was 2.0 years. Almost all cases were recruited within 1 year after the diagnosis and the questionnaires were completed after a median of 3.0 years following the onset of the disease. The corresponding analyses based on GEMS included 5874 cases and 5246 controls. The mean age at onset was 33.6 years, and the mean duration from the disease onset to inclusion in the study was 17.0 years. Characteristics of cases and controls in EIMS and GEMS are presented in Table 1.
In both studies, there was a dose-dependent inverse association between alcohol consumption and MS risk that was statistically significant in both sexes. In EIMS, women who reported high alcohol consumption had an OR of 0.6 (95% CI, 0.4-1.0) of developing MS compared with nondrinking women, whereas men with high alcohol consumption had an OR of 0.5 (95% CI, 0.2-1.0) compared with nondrinking men (Table 2). The OR for the corresponding comparison in GEMS was 0.7 (95% CI, 0.6-0.9) for women and 0.7 (95% CI, 0.5-0.9) for men (Table 3).
Based on GEMS data, a subanalysis was performed where participants whose alcohol consumption comprised exclusively wine or spirits were compared with nondrinkers. Participants who drank more than 3 glasses of wine per week had an OR of 0.7 (95% CI, 0.5-0.8), which was also the case for participants who drank more than 5 glasses of sprits per week (OR, 0.7; 95% CI, 0.5-0.9) (Table 4).
The risk reduction associated with alcohol consumption was more pronounced among smokers than among never smokers. A statistically significant interaction between smoking and nondrinking was observed in GEMS (attributable proportion, 0.2; P = .01 in GEMS), but not in EIMS (attributable proportion, 0.2; P = .28) (Table 5).
Quiz Ref IDAccording to our observations in 2 large population-based case-control studies, alcohol consumption exhibits a dose-dependent inverse association with MS. Furthermore, alcohol consumption is associated with attenuation of the effect of smoking. Although the effect of alcohol on already established MS has not been studied herein, the data may have relevance for clinical practice since they give no support for advising persons with MS to completely refrain from alcohol.
Our findings differ from those based on the Nurses' Health Study, which is the only prospective cohort study that we know of that has investigated the association between alcohol consumption and MS risk. For consumption more than 15 g/d (which is the amount associated with a decreased risk in our study), the number of cases in the Nurses' Health Study is estimated to be fairly small, according to the information given in the article.4 This means that the power to identify an OR on the order of 0.8 (as observed by us) is low. It is thus possible that a protective effect of alcohol on MS risk went unnoticed in the Nurses' Health Study because of limited case numbers.
Both studies were population-based case-control studies where controls were randomly selected from the national population register and were frequency matched for age, sex, and residential area at the time of the disease onset for the cases. Information regarding lifestyle factors and personal information were gathered retrospectively. In EIMS, we predominantly included cases who had received their diagnosis within the past year to minimize recall bias whereas GEMS is based on prevalent cases of MS with a mean duration of 17.0 years from onset of disease to inclusion in the study. Recall bias may thus be a concern. However, in both studies, the questionnaires contained a wide range of questions regarding many potential environmental risk factors and no sections in the questionnaires were given preeminent focus. Most often recall bias relates to the tendency to overreport previous exposure among cases relative to the controls. If our results should be explained by recall bias, cases should have systematically understated their previous alcohol consumption in relation to the statements among controls.
Another potential concern is that the recruitment of cases and controls may have introduced selection bias. Some cases may have been unidentified in our studies. However, the Swedish health care system provides equal free-of-charge access to medical services for all Swedish citizens, and we believe almost all cases of MS are referred to neurological units. It seems unlikely that the few unidentified cases would cause a substantial bias in our calculations.
The proportion of responders with regard to participation in the study was 91% for cases and 69% for controls in EIMS and 82% for cases and 66% for controls in GEMS. A potential selection bias may result from the relatively high proportion of nonresponders among the controls. However, this bias is probably modest since both the prevalence of drinkers among the controls and their drinking patterns were in line with that of the general population.11 Moreover, the prevalence of smoking among the controls, seen as an indicator of lifestyle, was in line with that of the general population at equivalent ages.11 If selection bias had occurred among controls, it would probably be positively correlated with alcohol consumption, ie, the response rate would probably be lower among those who drink large amounts of alcohol, and consequently, our observed ORs would be biased toward the null value (OR = 1).
An alternative bias is the possibility of reverse causation, ie, that the disease has influenced the alcohol consumption among MS cases, also before the diagnosis. Potentially, less drinking among patients with MS could be a consequence of a decreased alcohol tolerance among patients with MS due to preexisting negative influences on the central nervous system by the MS process. Cases and controls were classified according to the alcohol habits as prevailing at the index year (ie, for cases, the year in which the first symptom of MS occurred; controls were assigned the same index year as the case they were matched to). In EIMS, we asked about the alcohol consumption during the week before answering the questionnaire and whether the consumption had increased, decreased, or was the same compared with the consumption 5 years ago. To mirror the alcohol consumption before the index year, we restricted the analysis to participants with an estimated disease onset within the previous 5 years in relation to study inclusion and who reported no change in alcohol habits during the last 5 years. The results from EIMS may thus not be affected by reverse causation, at least not during the studied time window. It may be argued that decreased alcohol tolerance among patients with MS due to preexisting negative influences on the central nervous system may take place even before the studied time span. To shed light on this, we used information from GEMS where information was obtained regarding alcohol consumption during different age periods up to the participants' current age. We analyzed the association between alcohol consumption at ages 15 to 19 years and the risk of MS with different time lags. With a 5-year time lag, the OR was 0.9 (95% CI, 0.82-0.98); with a 10-year lag, the OR was 0.9 (95% CI, 0.80-0.98); and with a 15-year time lag, the OR was 0.9 (95% CI, 0.79-1.00) (the number of cases now becomes lower). Thus, there were no signs of reverse causality.
Further, we studied the pattern of changed alcohol consumption between different age periods based on the GEMS study. No differences between cases and controls were observed. Based on these observations, we conclude that reverse causality is less likely to explain our findings, even though we cannot completely rule out this possibility. In addition, a similar negative association has been observed for other autoimmune disorders not directly affecting the central nervous system.5- 7
While the exact mechanisms by which alcohol affects the risk of autoimmunity remain to be discovered, experimental and clinical data suggest that alcohol has significant dose-dependent immunomodulatory properties.9 Alcohol rapidly crosses the blood-brain barrier and is capable of exerting effects on the immune and nervous systems. Moderate alcohol consumption exerts anti-inflammatory effects by increasing interleukin 10 levels and decreasing monocyte inflammatory responses.12 Furthermore, alcohol stimulates the hypothalamus-pituitary-adrenal and hypothalamus-pituitary-gonadal axes, which increases glucocorticoid hormone levels and decreases estrogen levels in females. These hormonal changes may also mediate immune suppressive effects of alcohol.13 In mice, persistent ethanol consumption delays the onset and halts the progression of collagen-induced arthritis by downregulation of leukocyte migration and upregulation of testosterone secretion.14
Animal studies have shown that the consumption of alcohol itself, even in moderate amounts, leads to lower levels of leucocytes, and it has been suggested that ethanol itself might be largely responsible for the anti-inflammatory effects of moderate alcohol consumption. In the MONICA study, moderate alcohol consumption of either wine or beer appeared to be associated with lower levels of systemic inflammatory markers in 3 different European areas.15
Animal experiments have shown that acute alcohol exposure increases noradrenaline synthesis and release, leading to increased noradrenaline concentrations in the brain.16,17 Furthermore, noradrenaline concentrations were significantly higher in alcohol-dependent participants who were active drinkers compared with those in alcohol-dependent participants in remission and controls.18 The neurotransmitter is known to provide neuroprotection against various inflammatory stimuli, and increasing levels of noradrenaline in the central nervous system reduce experimental autoimmune encephalomyelitis severity.19
An inverse association between alcohol and risk of developing cardiovascular disease has long been known.20 The risk of other autoimmune diseases such as autoimmune hypothyroidism,5 systemic lupus erythematosus,6 and rheumatoid arthritis7,8 has been found to be lower in alcohol drinkers as compared with nondrinkers. A dose-dependent reduction in risk of developing rheumatoid arthritis with moderate alcohol consumption has been reported, as well as an interaction between smoking and nondrinking.7 Alcohol thus seems to have a similar impact on MS and rheumatoid arthritis, which are both complex, helper T cell subtype 1–driven inflammatory diseases.
In conclusion, alcohol consumption exhibits a dose-dependent inverse association with MS. Furthermore, alcohol consumption is associated with attenuation of the effect of smoking. Quiz Ref IDAlcohol may thus be another modifiable lifestyle factor that may affect the risk of developing MS.
Corresponding Author: Anna Karin Hedström, MD, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden (email@example.com).
Accepted for Publication: November 18, 2013.
Published Online: January 6, 2014. doi:10.1001/jamaneurol.2013.5858.
Author Contributions: Drs Olsson and Alfredsson contributed equally. Dr Hedström had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Olsson, Alfredsson.
Acquisition of data: All authors.
Analysis and interpretation of data: All authors.
Drafting of the manuscript: Hedström, Olsson.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Hedström, Alfredsson.
Obtained funding: Hillert, Olsson, Alfredsson.
Administrative, technical, and material support: Olsson.
Study supervision: Hillert, Olsson, Alfredsson.
Conflict of Interest Disclosures: Dr Hillert received honoraria for serving on advisory boards for Biogen Idec, Merck Serono, and Novartis and for speaker’s fees from Biogen Idec, Merck Serono, Bayer-Schering, Teva, and sanofi-aventis. He has served as principal investigator for and received projects supported by Biogen Idec, Merck Serono, and Bayer-Schering. His MS research is funded by the Swedish Research Council, the Bibbi and Nils Jensens Foundation, and the European Commission. Dr Olsson served on scientific advisory boards for Merck Serono, Biogen Idec, and sanofi-aventis; served as co-editor of Current Opinion in Immunology; received speaker honoraria from Novartis and Biogen; and receives research support from Bayer-Schering, sanofi-aventis, Biogen Idec, the Swedish Research Council (grant 07488), EU fp6 Neuropromise (grant LSHM-CT-2005-018637), EURATools (grant LSHG-CT-2005- 019015), the Söderberg Foundation, the Bibbi and Nils Jensens Foundation, the Montel Williams Foundation, and the Swedish Brain Foundation. Dr Alfredsson receives research support from the Swedish Medical Research Council (grant K2007-69X-14973-04-3) and Swedish Council for Working Life and Social Research (grant Dnr 2006-0655). No other disclosures were reported.
Funding/Support: The study was supported by grants from the Swedish Medical Research Council, the Swedish Council for Working Life and Social Research, the Knut and Alice Wallenberg Foundation, the AFA Foundation, the Swedish Brain Foundation, and the Swedish Association for Persons With Neurological Disabilities.
Role of the Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.