Abstract
Background:
The aim of the study was to examine the association between alcohol consumption and stroke in Nigeria and Ghana.
Methods:
The study is a multicentre, case-control study. Cases included consenting adults 18 years of age and older with acute stroke. The controls were age- and gender-matched, stroke-free adults. Alcohol consumption was self-reported. The participants were classified into three alcohol-drinking status groups, which included abstainers, former drinkers, and current drinkers. The current drinkers were further classified into different alcohol drinking levels, including infrequent drinkers, light drinkers, moderate drinkers, heavy drinkers, and binge drinkers. Conditional logistic regression was used to determine associations between the drinkers’ status and stroke, respectively, as well as the association between the different levels of current drinkers and strokes, respectively. Five models were evaluated. Model 1 was unadjusted. Model 2 had adjustments for demographic characteristics. Model 3 included Model 2, lifestyle, and psychosocial function adjustments. Model 4 includes Model 3 and dietary factor adjustments. Model 5 included Model 4 and metabolic factor adjustments.
Results:
A total of 7,368 participants took part in the study. Half were stroke participants, and half were control participants. On the associations between drinking status and strokes, respectively, former drinkers showed no significant association with strokes; however, there were significant associations between current drinkers and strokes in models 1 and 2, and the odds ratio of stroke risk was 1.19 (95% CI: 1.04–1.38; p<0.05) and 1.17 (95% CI: 1.01–1.36; p<0.05), respectively. Regarding the various levels of current drinkers and their association with stroke, no significant association was observed between light drinkers and stroke in model 5. In contrast, moderate drinkers, binge drinkers, and heavy drinkers showed a persistent and significant association with stroke, respectively.
Conclusion:
There is a significant association between strokes and current alcohol consumption, especially among heavy, binge, and moderate drinkers.
Keywords: Stroke: lifetime alcohol abstainers, former alcohol drinkers, current alcohol drinkers
INTRODUCTION
Stroke is the second-biggest cause of death in the world, with around 5.5 million deaths each year. [1] The incidence of strokes is on the rise in Nigeria and most sub-Saharan African countries. It is also a leading cause of neurological admission in most tertiary hospitals in Nigeria. [2, 3] According to data from the 2016 Global Burden of Disease Study, Nigeria had one of the highest prevalence of current alcohol use among persons 15 years of age and older in sub-Saharan Africa (SSA), with a population-level range of 40 to 59.9% for both genders. [4] Alcohol consumption is one of the behavioural risk factors for stroke. [5] It was first implicated as a possible risk factor in 1725. [6] However, some later epidemiological studies have shown that alcohol has an inconsistent association with stroke. [7, 8] Light-to-moderate consumption of alcohol has been associated with a lower risk of stroke and is protective against it, according to certain studies. [9] However, some other studies contradict these findings. [10]
There are studies from other regions of the world on the association between alcohol and strokes. [11, 12] However, there is a dearth of data emanating from the sub-Saharan African region on the association between alcohol consumption and stroke. Furthermore, a variety of research populations are required to examine the association between alcohol consumption and stroke since distinct genetic, environmental, and lifestyle differences may have varied effects on the outcome of the association between alcohol and strokes.
We present the findings of a multicentre case-control study in Nigeria and Ghana that used validated measures of alcohol consumption to examine the association between alcohol consumption and stroke in the West African region.
METHODS
Study design
The Stroke Investigative Research and Educational Network (SIREN) study is a multicentre, case-control study involving sites in Nigeria and Ghana that started from August 2014 to June 2018. We will not discuss the methods in full in this study because they have been documented in length elsewhere. [13, 14] There were 16 centres in Nigeria and Ghana. Ethical approval was obtained from the University of Ibadan/University College Hospital (UI/UCH) Ethics Committee with approval number UI/EC/13/0105. In addition, approval was obtained from all 16 sites in Nigeria and Ghana, and informed consent was obtained from all participants.
Bilingual research assistants assisted in the index evaluation of cases and controls, which was done using a comprehensive, standardized process that was based on the WHO-STEPS Stroke Surveillance, INTERSTROKE, and REGARD protocols with the necessary modifications. 13] The study included consenting adults 18 years of age and older who had their first clinical stroke within 8 days of the current symptom onset or who were last seen “without deficit’ with a cranial CT or MRI scan performed within 10 days of the current symptom onset. A close relative gave consent when the stroke participant was unconscious. Consenting adults free of stroke served as the control group;. The control participants were recruited from the SIREN hospitals’ outpatient departments and from neighbouring community hospitals. Postal questionnaire was not used in recruiting the control participants.
The eight-item questionnaire for verifying stroke-free status (QVSFS) was used to determine that a person had not had a stroke. Stroke was defined as rapidly developing clinical signs of focal or global disturbance of brain function, lasting for more than 24 hours or resulting in death, with no apparent cause other than vascular. [13] Those with subarachnoid haemorrhage, subdural hematoma, or epidural haemorrhage were not eligible for the study. Cases of recurrent or repeated strokes were also excluded.
Data collection
Data collection and description of covariates had been elaborated on earlier publication. [13, 14]. The questionnaire section on lifestyle assessment was used to obtain information regarding current and previous alcohol consumption. Each alcoholic drink type provided on the questionnaire was converted to the equivalent number of grams of alcohol to harmonize the various forms of alcohol consumed in this study. These were then standardized by converting the grams of alcohol into the equivalent number of alcoholic drinks. The quantity of pure alcohol in a typical drink is not universally agreed upon; estimates vary from 8 to 20 grams, depending on the country. [15] Ten grams is the unit of measurement used in the sample questionnaire form for the Alcohol Use Disorders Identification Test (AUDIT), developed by the World Health Organization. [16] More countries than any other have accepted this standard [17] with 10g serving as this study’s standard drink equivalent.
Alcohol consumption: Binge drinking is defined as a pattern of drinking alcohol that brings the blood alcohol concentration (BAC) to 0.08 percent, or 0.08 grams of alcohol per deciliter, or higher. For a typical adult, this pattern corresponds to consuming 5 or more drinks (male) or 4 or more drinks (female) in about 2 hours. [18] Lifetime abstinence from alcohol is defined as consuming fewer than 12 drinks in a lifetime. [19] A former regular alcohol drinker is defined as consuming at least 12 drinks in any one year of a lifetime, but no drinks in the past year. [19] A current infrequent (occasional) drinker is defined as a person who has consumed 1–11 drinks in the past year. 19 A current light drinker is defined as a person who has consumed at least 12 drinks in the past year but 3 drinks or less per week, on average, over the past year. [19] A current moderate drinker is defined as more than 3 drinks but no more than 7 drinks per week for women and more than 3 drinks but no more than 14 drinks per week for men, on average over the past year. [19] A current heavy alcohol drinker among men is defined as consuming more than 4 drinks on any day or more than 14 drinks per week and, for women, consuming more than 3 drinks on any day or more than 7 drinks per week. [19]
Statistical Analysis
The demographic, behavioural, psychological, and vascular characteristics of lifetime abstainers, former drinkers, and current drinkers were compared. Chi-square testing was conducted to determine if any of the categorical factors produced substantially different findings. Continuous variables’ mean and standard deviation were calculated, and statistical differences were examined using the ANOVA test. Conditional logistic regression at a 95% confidence interval (CI) was used to determine the associations between the different status of alcohol intake and stroke incidence, and the different current alcohol consumption levels and stroke incidence. (Table 2 and Table 3). Five models were evaluated: Model 1 was unadjusted, and Model 2 had adjustments for demographic characteristics (age, domicile, marital status, income, and education). Model 3 includes Model 2, lifestyle and psychosocial function (tobacco use, depression, stress) adjustments. Model 4 includes Model 3 and dietary factors (low vegetable consumption, regular meat intake) adjustments. Model 5 includes Model 4 and metabolic factors (waist-to-hip ratio, diabetes, hypertension, dyslipidemia, family history of CVD) adjustments. The missingness in the data was imputed using the multivariate imputation by chained equation package in R. Statistical analyses were carried out using SPSS (version 25) and the R statistical package (version 4.1.1), with a two-sided P<0.05.
Table 2:
The associations between alcohol drinkers status and stroke respectively
| Variables | Model 1 Unadjusted OR (95% CI) | Model 2 Adjusted OR (95% CI) | Model 3 Adjusted OR (95% CI) | Model 4 Adjusted OR (95% CI) | Full model Adjusted OR (95% CI) |
|---|---|---|---|---|---|
|
| |||||
| Drinking Status | |||||
| Lifetime abstainer (Ref) | 1 | 1 | 1 | 1 | 1 |
| Former drinkers | 1.12 (0.98–1.30) | 1.03 (0.89– 1.20) | 0.97 (0.83– 1.13) | 1.01 (0.86–1.18) | 0.78 (0.64–0.96) |
| Current drinkers | 1.19 (1.04–1.38) * | 1.17 (1.01–1.36) * | 1.11 (0.95–1.29) | 1.10 (0.94– 1.29) | 0.98 (0.79–1.21) |
- P<0.05; significant variable, Model 1- Unadjusted: Model 2- Model 1 with demographic characteristics (age; “<50 vs ≥50”, domicile; “rural vs urban”, marital status; “never married vs currently married/cohabiting andformally married”, income; “≤100 vs >$100”, and education; “no education vs some education”): Model 3- Model 2 with lifestyle and psychosocial function (Tobacco use; “never vs ever”, depression; “not depressed vs depressed”, stress; “stressed vs not stressed”): Model 4-model 3 with dietary factors (low vegetable consumption; “no vs yes”, regular meat intake; “no vs yes ”): Model 5- model 4 with metabolic factors(waist to hip ration; “not raised vs raised”, diabetes; “no vs yes”, hypertension;” normotensive vs hypertensive”, dyslipidaemia; “no vs yes”, family history of CVD; “no vs yes”)
Table 3:
The associations between current alcohol drinkers’ levels and stroke respectively
| Variables | Model 1 Unadjusted OR (95% CI) | Model 2 Adjusted OR (95% CI) | Model 3 Adjusted OR (95% CI) | Model 4 Adjusted OR (95% CI) | Full model Adjusted OR (95% CI) |
|---|---|---|---|---|---|
|
| |||||
| Current drinkers’ only (alcohol | |||||
| Consumption categories) | |||||
| Infrequent (occasional) drinkers | 1 | 1 | 1 | 1 | 1 |
| Light drinkers | 4.03 (1.46–11.10) * | 4.24 (1.50–11.99) * | 3.85 (1.30–11.41) * | 3.45 (1.12–10.61) * | 2.85 (0.56–14.59) |
| Moderate drinkers | 7.34 (1.52– 35.33) * | 6.49 (1.23–34.09) * | 5.57 (1.03–30.26) * | 5.40 (0.95–30.84) * | 11.17 (1.25–99.5) * |
| binge | 6.82 (3.01–15.47) * | 7.30 (3.17–16.90) * | 6.81 (2.91–15.94) * | 5.80 (2.45–13.70) * | 3.37 (1.06–10.66) * |
| Heavy drinker | 6.59 (2.43–17.85) * | 6.21 (2.28–16.91) * | 5.62 (2.06–15.34) * | 5.42 (1.95–15.08) * | 7.28 (1.72–30.83) * |
- P<0.05
RESULTS
Characteristics of the study population based on alcohol consumption status
Among the participants, there were 5,197 (70.54%) lifetime alcohol abstainers, 1,067 (14.48%) former alcohol drinkers, and 1,104 (14.98%) current alcohol drinkers. The incidence of lifetime abstainers, former drinkers, and current drinkers was 50.8%, 48.6%, and 47.4%, respectively, among the stroke cases. Among the control group, the prevalence of lifetime abstainers, former drinkers, and current drinkers was 49.2%, 51.4%, and 52.6%, respectively.
In addition, 75.4% of the participants were over 50 years of age, 75.1% were married, and 55.5% lived in urban areas. The prevalence of tobacco use was 5.9%. The prevalence of physical inactivity was 3.5%, depression was 7.0%, general obesity was 21.1%, hypertension was 77.5%, diabetes was 24.4%, and dyslipidaemia was 62.3%. Low vegetable consumption was reported at 22.8%, and the meat consumption rate was 72.1% among all the participants. (Table 1).
Table 1:
Characteristics of the study population based on alcohol consumption status
| Characteristics | All N=7368 n(%) |
Lifetime abstainer N=5197 n(%) |
Former drinker N=1067 n(%) |
Current drinker N=1104 n(%) |
P-value |
|---|---|---|---|---|---|
|
| |||||
| Stroke | |||||
| Control | 3684 (50.0) | 2642 (50.8) | 519 (48.6) | 523 (47.4) | 0.071 |
| Cases | 3684 (50.0) | 2555 (49.2) | 548 (51.4) | 581 (52.6) | |
| Gender | |||||
| Female | 3376 (45.8) | 2881 (55.4) | 299 (28.0) | 196 (17.8) | |
| Male | 3992 (54.2) | 2316 (44.6) | 768 (72.0) | 908 (82.2) | |
| Age (Mean ± Sd) | 59.0 ±13.9 | 59.1 ±13.3 | 60.5 ±13.0 | 56.8 ±12.5 | <0.0001 |
| <50 | 1809 (24.6) | 1280 (24.6) | 206 (19.3) | 323 (29.3) | <0.0001 |
| ≥50 | 5559 (75.4) | 3917 (75.4) | 861 (80.7) | 781 (70.7) | |
| Domicile | |||||
| Rural | 1018 (13.8) | 799 (15.4) | 98 (9.2) | 121 (11.0) | <0.0001 |
| Semi-Urban | 2080 (28.2) | 1541 (29.6) | 286 (26.8) | 253 (22.9) | |
| Urban | 4270 (58.0) | 2857 (55.0) | 683 (64.0) | 730 (66.1) | |
| Marital Status | |||||
| Never married | 300 (4.1) | 205 (4.0) | 34 (3.2) | 61 (5.5) | <0.0001 |
| Currently married /Cohabiting | 5533 (75.1) | 3843 (73.9) | 812 (76.1) | 878 (79.5) | |
| Formally married | 1535 (20.8) | 1149 (22.1) | 221 (20.7) | 165 (15.0) | |
| Income | |||||
| ≤ $100 | 3953 (53.7) | 3021 (58.1) | 472 (44.2) | 460 (41.7) | <0.0001 |
| >$100 | 3415 (46.3) | 2176 (41.9) | 595 (55.8) | 644 (58.3) | |
| Education | |||||
| No education | 1537 (20.9) | 1330 (25.6) | 123 (11.5) | 84 (7.6) | <0.0001 |
| Some education | 5831 (79.1) | 3867 (74.4) | 944 (88.5) | 1020 (92.4) | |
| Lifestyle and psychosocial function | |||||
| Tobacco use | |||||
| Never used | 6769 (91.9) | 5071 (97.6) | 842 (78.9) | 856 (77.5) | <0.0001 |
| Former user | 166 (2.2) | 43 (0.8) | 25 (2.4) | 98 (8.9) | |
| Current user | 433 (5.9) | 83 (1.6) | 200 (18.7) | 150 (13.6) | |
| Physical inactivity (yes) | 258 (3.5) | 176 (3.4) | 47 (4.4) | 35 (3.2) | 0.208 |
| Depression (Yes) | 515 (7.0) | 292 (5.6) | 111 (10.4) | 112 (10.1) | <0.0001 |
| Stress (Yes) | 1203 (16.3) | 697 (13.4) | 253 (23.7) | 253 (22.9) | <0.0001 |
| Metabolic factors | |||||
| BMI (Mean ± Sd) | 26.4 ±5.5 | 26.4 ±5.3 | 26.6 ±5.3 | 26.1 ±5.1 | 0.203 |
| <30 | 5812 (78.9) | 4088 (78.7) | 839 (78.6) | 885 (80.2) | 0.527 |
| ≥30 | 1556 (21.1) | 1109 (21.3) | 228 (21.4) | 219 (19.8) | |
| Waist-to-hip ratio (Mean ± Sd) | 0.93 ±0.08 | 0.92 ±0.08 | 0.93 ±0.09 | 0.93 ±0.08 | 0.622 |
| Waist-to-hip ratio (Raised) | 5637 (76.5) | 4038 (77.7) | 785 (73.6) | 814 (73.7) | 0.001 |
| Fasting Glucose (Mean ± Sd) | 104.2±40.4 | 103.8 ±40.6 | 105.6 ±44.4 | 104.2 ±35.0 | 0.582 |
| Diabetic (Yes) | 1800 (24.4) | 1241 (23.9) | 312 (29.2) | 247 (22.4) | <0.0001 |
| SBP (Mean ± Sd) | 148.0±28.4 | 147.9 ±30.3 | 148 .6±29.0 | 148.0 ±28.4 | 0.782 |
| DBP (Mean ± Sd) | 89.2 ±19.6 | 89.0 ±17.5 | 89.2 ±17.9 | 89.8 ±18.0 | 0.378 |
| Hypertensive (Yes) | 5712 (77.5) | 3966 (76.3) | 884 (82.8) | 862 (78.1) | <0.0001 |
| Total Cholesterol (Mean ± Sd) | 198.8±53.9 | 190.7 ±53.1 | 196.3 ±57.3 | 198.8 ±53.4 | <0.0001 |
| Triglyceride (Mean ± Sd) | 116.7±70.6 | 118 .8±73.2 | 110 ±62.9 | 113.6 ±65.0 | 0.002 |
| Dyslipidaemia (Yes) | 4593 (62.3) | 3168 (61.0) | 744 (69.7) | 681 (61.7) | <0.0001 |
| Family history of CVD (Yes) | 2288 (31.1) | 1346 (25.9) | 484 (45.4) | 458 (41.5) | <0.0001 |
| Low Vegetable consumption | 1683 (22.8) | 215 (19.5) | 177 (16.6) | 1291 (24.8) | <0.0001 |
| Fruit Consumption | 6357 (86.3) | 4474 (86.1) | 924 (86.6) | 959 (86.9) | 0.751 |
| Regular meat consumption (yes) | 5311 (72.1) | 3784 (72.8) | 704 (66.0) | 823 (74.5) | <0.0001 |
Furthermore, with regards to gender, women were in the majority among lifetime abstainers (55.4%). In addition, the prevalence of diabetes, triglycerides, dyslipidemia, and raised waist/hip ratios was significantly higher among women. However, men make up the majority of current drinkers (88.2%). The current drinkers were younger, more likely to be urban residents, and had more formal education when compared to lifetime abstainers. Additionally, there was a higher prevalence of depression, stress, a history of current smoking, and a family history of CVD, respectively, among current alcohol drinkers (Table 1).
Associations between alcohol drinking status and strokes
There was no significant association between former alcohol drinkers and stroke (p > 0.05). Among current alcohol drinkers, there was a significant odds risk of stroke in models 1 and 2 (p < 0.05). In models 3–5, no association was observed in any of the three models (p > 0.05) (Table 2 and Figure 1).
Figure 1:
Forest plot of the association between drinking status and Stroke
Forest plot of odds ratio (OR) and 95% confidence intervals (CI) for the association of drinking status (including former and current alcohol users) with Stroke. Conditional logistic regression models were used to estimate OR (95%CI) using lifetime abstainers as a reference. Model 1 was unadjusted or crude odds. Model 2 was adjusted for demographic factors, including age, domicile, marital status, income, and education. Model 3 was adjusted for lifestyle and psychosocial factors, including tobacco use, depression and stress, in addition to covariates in Model 2. Model 4 was adjusted for dietary factors, including low vegetable and regular meat consumption, in addition to covariates in Model 3. Model 5 is the final model and was adjusted for metabolic factors, including waist-to-hip ratio, diabetes, hypertension, dyslipidemia, and family history of CVD, in addition to covariates in Model 4. All statistical analyses were carried out at a two-sided P<0.05.
Associations between current alcohol drinkers’ levels and stroke
The association between current alcohol drinker levels versus stroke, with “infrequent (occasional) alcohol drinker” used as a reference, showed that light alcohol drinking had significant associations with stroke in models 1–4 (p <0.05). The ORs of stroke risk were higher in models 1 and 2, with a progressive decrease from models 3–5. The association in model 5 was not significant (p > 0.05). There was a significant association between binge alcohol drinking and stroke in all 5 models (p <0.05). However, the ORs of stroke occurrence were higher in models 1–3, with a progressive decrease in models 4–5. Furthermore, all five models showed a strong correlation (p<0.05) between the level of heavy drinking and stroke, with high probabilities of stroke in each model. This trend was consistent with what was shown in people who consumed moderate amounts of alcohol. (Table 3 and Figure 2).
Figure 2:
Forest plot of the association between current drinking levels and Stroke
Forest plot of odds ratio (OR) and 95% confidence intervals (CI) for the association of current drinking levels (including light, moderate, binge and heavy alcohol users) with Stroke. Conditional logistic regression models were used to estimate OR (95%CI) using infrequent/occasional drinkers as a reference. Model 1 was unadjusted or crude odds. Model 2 was adjusted for demographic factors, including age, domicile, marital status, income, and education. Model 3 was adjusted for lifestyle and psychosocial factors, including tobacco use, depression and stress, in addition to covariates in Model 2. Model 4 was adjusted for dietary factors, including low vegetable and regular meat consumption, in addition to covariates in Model 3. Model 5 is the final model and was adjusted for metabolic factors, including waist-to-hip ratio, diabetes, hypertension, dyslipidemia, and family history of CVD, in addition to covariates in Model 4. All statistical analyses were carried out at a two-sided P<0.05.
DISCUSSION
This study examined the association between alcohol consumption and stroke in Nigeria and Ghana. The study included consenting participants, half of whom were stroke participants, including the unconscious that the relatives gave consent, and half of whom were control participants (consenting stroke-free adults), recruited mostly from the communities in the catchment areas of the SIREN hospitals. In this study, current drinkers were found to be younger, male, cigarette smokers, and in higher-paying occupations. The INTERSTROKE study and the PURE study reported similar findings. [20, 21] However, the prevalence of current drinkers in this study (14.98%) was substantially lower than the prevalence reported in the INTERSTROKE (25.0%). [20] and the PURE study (31%). [21]
There were 5,197 (70.13%) abstainers among the study participants. In the majority of African countries, including Nigeria and Ghana, alcohol plays an important role in several social events and cultural activities [22, 23] and one would have expected a lower prevalence of lifetime abstainers. However, religion could be one of the reasons for the finding. Drinking alcohol is forbidden in Islam, and in Nigeria and Ghana, Muslims constitute about 53% and 19% of the population, respectively [24, 25]. Furthermore, some Christians abstain from alcohol because it is forbidden by some factions of the pentecostal and evangelical churches in the sub-Saharan African region. There may also be some people who do not drink alcohol due to poverty, bearing in mind that the income of the abstainers was significantly lower than that of former and current alcohol drinkers (Table 1).
It was also observed that a majority of the lifetime abstainers in this study were women. This is not surprising because it is a known fact that alcohol consumption among women in Africa is low. [26] However, some research is needed to determine the reasons for the high prevalence of lifetime abstainers among women in the sub-Saharan African region. Although there are a variety of contributing factors to this result, our study has shown that a very significant percentage of the population in the west African region are abstainers.
The prevalence of former drinkers in this study was 14.48%, similar to that observed in the INTERSTROKE study. [20] The reason for the former drinker’s status may be due to a decision to change their lifestyle, usually due to pressure from relatives and friends or a chronic illness that is attributed to alcohol consumption by a medical doctor.
The association between alcohol drinking status and strokes was explored, with lifetime abstainers as a reference. Among former alcohol drinkers, there was no significant risk of stroke in the five models. This was in contrast with the odd risks of stroke in the current alcohol drinkers’ category. The associations between current drinkers and stroke were significant (p<0.5) in models 1 and 2 only. These results implied that the likelihood of stroke occurring among current drinkers in the two models was about 19% and 17%, respectively, higher than it was in lifetime abstainers. In the interstroke study, current drinking was not associated with stroke in the African region. [20] A previous study reported that lifetime abstinence from alcohol is a risk factor for stroke and that the likelihood of stroke occurring in lifetime abstainers is significantly higher than in former and current drinkers. The differences observed may be due to the small sample size of the study (309 participants). In addition, the study was conducted in a different geographical region. [27] There was no significant association between former drinkers and stroke and the same observation was made in the INTERSTROKE study. [20]
The associations between light, binge, moderate and heavy drinkers and stroke, with occasional drinkers used as the reference, were to some extent influenced by confounding variables. However, the influences observed varied at the different current drinkers’ levels and were more profound at the light drinker’s level. The odds of stroke risk were significant in all models, among binge, moderate and heavy drinker levels. Like a coin, there were two sides to the observations made in the light drinkers’ category: the ORs observed in models 1–4 were significant (p<0.05), but the OR of stroke risk was not significant in model 5 (OR: 2.85; 95% CI: 0.56–14.59; p>0.05).
Our findings are similar to those made in the Interstroke study. [20] In the study, high, moderate, and binge alcohol drinking were associated with increased odds of all strokes, respectively. However, low drinking (light drinkers) levels were associated with reduced odds of stroke in the African region and some other regions.
Our study provides insight into the association between alcohol consumption and stroke in the West African region. We observed that heavy, moderate, and binge alcohol drinking levels were associated with increased odds of stroke in all five models of confounders’ adjustment. The same applies to the light drinking level, except in model 5. These findings suggest that none of the current alcohol consumption levels is safe or protective against stroke in the West African region and that light alcohol drinking (except when fully adjusted for confounders), moderate alcohol drinking, binge alcohol drinking, and heavy alcohol drinking levels are all risk factors for stroke in the region. Our findings are similar to those of larger studies, which reported that high alcohol intake was associated with harm and low alcohol intake was associated with little or no protection against stroke. [20, 28] Our findings are also in keeping with the statement by the World Health Organization that there is no safe level of alcohol use that is not harmful to one’s health and that “the potential protective effects of alcohol consumption, as suggested by some studies, are tightly connected with the comparison groups chosen and the statistical methods used and may not consider other relevant factors”. [29]
However, to be categorically certain that these current alcohol drinking levels are all risk factors for stroke, the relative risk (RR) will have to be estimated, and this is not an option in case-control studies. [30]
Funding Statement:
The SIREN and SIBS Genomics studies were funded by the National Institutes of Health grants U54 HG007479 and R01NS107900 under the H3Africa initiative
Footnotes
Declaration of conflicting interests
No potential conflicts of interest were disclosed by the author(s) in relation to the research, writing, or publication of this article.
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