4. Subjects, participants and methods
4.5 Statistical analysis
Subjects were divided into quartiles according to the mean serum omega 3 PUFA (0-0.64, 0.65-1.26, 1.27-2.50, 2.51-15.67 % of all serum fatty acids) and the mean mercury content in hair (1.70-3.63, 3.63-4.34, 4.34-5.34, 5.34-15.59 µg/g of hair). The univariate relationships between serum EPA + DPA + DHA and hair mercury and baseline characteristics were assessed by means and linear regression (for continuous variables) or χ2 tests (for categorical variables). Three different models were used. First model was adjusted by age and examination year. In the second model, body mass index; smoking; physical activity; alcohol
intake were also adjusted for. Further adjusted on systolic blood pressure; diabetes; HDL cholesterol; LDL cholesterol; serum triglyceride; C - reactive protein was done in third model.
Three different models were conducted to find out about the effect of different variables which may have the role as a confounders or modifier on the association between exposure and outcome. Associations between serum long chain PUFA, hair mercury content and stroke were analyzed using Cox regression models. Cohort mean was used to replace missing values in covariates (< 0.5%). Tests of linear trend were conducted by assigning the median values for each category of exposure variable and treating those as a single continuous variable. All P values were two-tailed (α = 0.05). Data were analyzed using SPSS 21.0 for Windows (SPSS Inc., Chicago, IL).
5. Results
5.1 Baseline characteristics
There were no significant differences between serum long chain PUFA concentrations in those who had a stroke and those who did not (Table 5). In contrast, hair MeHg content was higher in those who had a stroke in comparison to those who did not have a stroke.
141 cases of first strokes were identified, 107 cases out of 141 cases were ischemic stroke. At baseline, men with higher serum long-chain omega-3 PUFA concentration had a higher income, education, leisure-time physical activity, BMI, alcohol intake, serum LDL cholesterol, serum HDL cholesterol and hair mercury concentration and lower serum triglyceride concentration. They were also less likely to live in a rural area and smoke (Table 6).
Men with higher hair mercury concentration were older; had a lower education, physical activity, income, and serum triglyceride concentrations; and had higher BMI, alcohol intake, serum long-chain omega-3 PUFA, HDL and LDL concentrations, and higher systolic and diastolic blood pressure. They were also more likely to live in a rural area and smoke (Table 7).
5.2 Association between serum long-chain omega-3 PUFA and risk of stroke
During the average follow-up of 16.1 years, 141 men (7.7%) developed stroke. Of all strokes, 115 were ischemic strokes. After adjusted for age and year of examination (model 1 in Table 8), higher serum long chain polyunsaturated fatty acids concentration was not statistically significantly associated with ischemic stroke and total stroke. Further multivariate adjustments did not have an appreciable effect on the association (Models 2& 3 in Table 8). Further adjustment for hair mercury slightly strengthened the association (RR in the highest quartile of total serum long-chain omega-3 PUFA 0.84, 95% CI 0.51-1.34, P for trend=0.55). There were no statistically significant associations when the individual fatty acids were evaluated separately (Table 8).
The mean hair mercury concentration was 1.90 ug/g (SD 1.95). After adjusted for age and year of examination the risk of stroke in the highest vs. the lowest hair Hg quartile was increased by 59% [95% CI 0-154%, P for trend=0.01] (Model 1 in Table 9). Additional adjustments slightly attenuated the associations (Models 2&3 in Table 9). The associations were attenuated and not statistically significant, when only ischemic strokes were included in the analyses (Table 9).
Table 5. Mean baseline concentrations of serum total long-chain omega-3 polyunsaturated fatty acids and hair mercury in those who experienced stroke and those who did not during the follow-up.
Participants with stroke during follow-up (n = 141), mean (SD)
Participants without stroke during follow-up (n = 1673), mean (SD)
P value
DHA, % 2.4 (0.7) 2.5 (0.7) 0.8
EPA, % 1.7 (0.8) 1.7 (0.9) 0.9
DPA, % 0.5 (0.1) 0.5 (0.1) 0.3
Total omega 3 PUFA, %
4.7 (1.6) 4.7 (1.6) 0.9
Hairhg, ug/g 2.2 (1.9) 1.9 (1.9) 0.05
Table 6. Baseline characteristics according to serum long-chain omega-3 PUFA concentration
Serum Omega 3 PUFA, % P value Q1
(0-0.64)
Q2 (0.65-1.26)
Q3
(1.27-2.50)
Q4 (2.51-15.67)
Number of subjects 453 454 454 453 -
Age (y) 52.2 (5.6) 52.1 (5.4) 52.6 (5.0) 52.7 (5.2) 0.05
Education (y) 8.9 (3.3) 8.7 (3.4) 8.8 (3.5) 9.6 (4.0) < 0.001
Marital status, married (%) 85 87 85 91 0.06
Living in rural area (%) 30 28 28 25 0.40
Leisure-time physical activity (kcal/d) 134 (171) 132 (155) 132 (146) 153 (196) 0.07 Body mass index (kg/m2) 26.6 (3.5) 26.5 (3.3) 27 (3.5) 27 (3.5) 0.03
Current smoker (%) 31 28 28 25 0.27
Diabetes (%) 5 3 5 5 0.26
Family history of stroke (%) 21 20 22 18 0.32
Hypertension medication before stroke (%) 70 70 67 68 0.76
Alcohol intake (g/wk) 55 (90) 62 (93) 85 (136) 85 (127) < 0.001
Serum LDL, mmol/l 3.8 (0.3) 4.0 (0.9) 4.1 (1.0) 4.1 (1.0) < 0.001
Serum HDL, mmol/l 1.2 (0.3) 1.3 (0.3) 1.3 (0.3) 1.4 (0.3) < 0.001
Serum TG, mmol/l 1.5 (0.9) 1.3 (0.8) 1.1 (0.6) 1.0 (0.5) < 0.001
Systolic blood pressure (mmHg) 135 (17) 134 (16) 134 (16) 134 (17) 0.98 Diastolic blood pressure (mmHg) 90 (11) 89 (10) 89 (10) 89 (11) 0.97
Hairhg, ug/g 1.2 (1.3) 1.6 (1.7) 2.2 (2) 2.7 (2.3) < 0.001
Income, Euros 13344
(7869)
13833(9083 )
14162 (10070)
15784 (10360)
< 0.001
Table 7. Baseline characteristics according to hair mercury concentration
Hair Hg, ug/g P value
Q1 (1.70-3.63)
Q2 (3.63-4.34)
Q3 (4.34-5.34)
Q4 (5.34-15.59)
Number of subjects 452 454 456 452 -
Age (y) 51.0 (5.7) 51.8 (5.8) 52.8 (4.9) 54.0 (4.4) < 0.001
Education (y) 9.7 (3.6) 9.6 (3.9) 8.8 (3.5) 7.8 (3) < 0.001
Marital status, married (%) 86 91 87 84 0.12
Living in rural area (%) 24 22 28 38 < 0.001
Leisure-time physical activity (kcal/d) 154 (186) 143 (190) 134 (149) 120 (141) < 0.001
Body mass index (kg/m2) 26.3 (3.2) 26.6 (3.3) 27.0 (3.6) 27.0 (3.7) < 0.001
Current smoker (%) 25 25 26 36 < 0.001
Diabetes (%) 4 4 5 5 0.58
Family history of stroke (%) 21 19 21 21 0.85
Hypertension medication before stroke (%)
74 66 66 70 0.05
Alcohol intake (g/wk) 60 (112) 73 (106) 76 (129) 78 (106) 0.05
Serum LDL, mmol/l 3.8 (0.9) 3.9 (0.9) 4.0 (1) 4.3 (1) < 0.001
Serum HDL, mmol/l 1.2 (0.9) 1.3 (0.3) 1.3 (0.3) 1.3 (0.3) < 0.001
Serum TG, mmol/l 1.3 (0.8) 1.2 (0.7) 1.3 (0.9) 1.2 (0.6) 0.01
EPA, % 1.3 (0.6) 1.6 (0.8) 1.7 (0.8) 2.1 (1.1) < 0.001
DHA, % 2.2 (0.6) 2.4 (0.6) 2.5 (0.7) 2.7 (0.8) < 0.001
DPA, % 0.5 (0.1) 0.5 (0.1) 0.6 (0.1) 0.6 (0.1) < 0.001
Total omega 3 PUFA, % 4.0 (1.2) 4.5 (1.4) 4.8 (1.4) 5.4 (1.9) <0.001 Systolic blood pressure (mmHg) 134 (17) 134 (16) 133 (16) 136 (16) 0.04 Diastolic blood pressure (mmHg) 89.0 (10) 89.0 (10) 88.5 (11) 90.0 (10) 0.35
Income Euros 15267
(10033)
15148 (8617)
14649 (10260)
12012 (9428)
< 0.001
Table 8. Risk of incident total stroke and ischemic stroke in quartiles of serum long-chain
Total serum long-chain omega-3 polyunsaturated fatty acids
< 3.22 3.22-3.98 3.99-4.77 > 4.77
No. of cases 36 29 38 38
Model 1 1(referent) 0.76(0.46-1.24) 1.03 (0.65-1.64)
0.99 (0.63-1.56)
0.70
Model 2 1(referent) 0.77(0.47-1.26) 1.02(0.64-1.61)
0.96(0.60-1.52)
0.86
Model 3 1(referent) 0.78(0.48-1.28) 0.99(0.61-1.60)
Model 1 1(referent) 0.93 (0.56-1.52)
Model 2 1(referent) 0.96 (0.58-1.58)
Model 3 1(referent) 0.93 (0.56-1.55)
Model 1 1(referent) 0.80 (0.49-1.31)
Model 2 1(referent) 0.78
Model 3 1(referent) 0.71 (0.43-1.17)
Model 1 1(referent) 0.92 (0.59-1.45)
Model 2 1(referent) 1.00 (0.63-1.58)
Model 3 1(referent) 1.05 (0.66-1.66)
Total serum long-chain omega-3 polyunsaturated fatty acids
< 3.22 3.22-3.98 3.99-4.77 > 4.77
No. of cases 29 21 26 31
Model 1 1(referent) 0.68(0.39-1.20) 0.87(0.51-1.47)
1.00 (0.60-1.67)
0.66
Model 2 1(referent) 0.70(0.40-1.22) 0.86(0.50-1.47)
0.99(0.59-1.65)
0.73
Model 3 1(referent) 0.70(0.39-1.23) 0.82(0.47-1.43)
Model 1 1(referent) 0.91 (0.52-1.62)
Model 2 1(referent) 0.97 (0.54-1.72)
Model 3 1(referent) 0.94
Model 1 1(referent) 0.69 (0.39-1.22)
Model 2 1(referent) 0.68 (0.38-1.21)
Model 3 1(referent) 0.62 (0.35-1.11)
Model 1 1(referent) 0.97 (0.57-1.66)
Model 2 1(referent) 1.05 (0.61-1.82)
Model 3 1(referent) 1.10 (0.64-1.91)
1 Values in the models are relative risk (RRs) and 95% CIs (in parentheses).
Model 1: adjusted for age and examination year.
Model 2: adjusted for Model 1 plus body mass index; smoking; physical activity; alcohol intake;
Model 3: adjusted for Model 2 plus systolic blood pressure; diabetes; HDL cholesterol; LDL cholesterol; serum triglyceride; C-Reactive Protein (each in quintiles).
Table 9. Risk of incident total stroke and ischemic stroke in quartiles of hair mercury
Model 2 1(referent) 0.92 (0.55-1.55)
Model 3 1(referent) 0.94 (0.56-1.57)
1 Values in the models are relative risk (RRs) and 95% CIs (in parentheses).
Model 1: adjusted for age and examination year.
Model 2: adjusted for Model 1 plus body mass index; smoking; physical activity; alcohol intake;
Model 3: adjusted for Model 2 plus systolic blood pressure; diabetes; HDL cholesterol; LDL cholesterol; serum triglyceride; C-Reactive Protein (each in quintiles).
6. Discussion
Results from this population based cohort study suggest that a higher serum concentration of long-chain n-3 PUFA, mainly reflecting fatty fish consumption in this study population, does not have any association with total stroke and ischemic stroke. The results from this study suggest that exposure to methylmercury has a direct association with the risk of total stroke but not with the risk of ischemic stroke. Although we did not evaluate the association between methylmercury and hemorrhagic stroke separately due to the low number of participants with hemorrhagic stroke, the lower risk of ischemic stroke compared to the risk of total stroke suggests that methylmercury exposure increases especially the risk of hemorrhagic stroke.
Some studies have pointed to the long-chain omega-3 PUFA as a risk factor for hemorrhagic stroke. Long-chain omega-3 PUFA have an effect on platelet aggregation (Park et al. 2009).
Study done by Park et al. pointed to the positive association between EPA + DHA and hemorrhagic stroke in rat brains (Park et al. 2009). This effect has not been confirmed in humans. Few studies have evaluated the positive association between long-chain omega-3 PUFA and risk of hemorrhage and bleeding disorders. However, none of them have considered the effect of high intake of long-chain omega-3 PUFA on increased bleeding through oxidative stress (Park et al. 2009). Although we did not have enough cases to study the association between serum long-chain omega-3 PUFA and risk of hemorrhagic strokes separately, it seems unlikely that there is an association because the associations with total and ischemic strokes were similar. Previously in this study population higher serum concentration of total long-chain omega-3 PUFA has been associated with lower systolic blood pressure and pulse pressure (Virtanen et al. 2012), CRP (Reinders et al. 2012), SCD (Virtanen et al. 2012), CHD and CVD (Virtanen et al. 2005) and also with the risk of atrial fibrillation (Virtanen et al. 2009). Atrial fibrillation is a common cardiac arrhythmia, and it is considered as one of the most important risk factors for stroke. Atrial fibrillation reduces the cardiac output and reduces
the cerebral blood flow, which has effect on stroke incident (Wolf et al. 1991). Atrial fibrillation can also significantly increase the frequency of blood clots that are transported into the carotid arteries by alteration in cardiac hemodynamics (Choi et al. 2013). However, inspite of the inverse association with the risk of atrial fibrillation, serum long-chain omega-3 PUFA do not seem to decrease the risk of stroke in this study population.
The results of this study are consistent with the result from previous meta-analysis (Larsson and Orsini 2011, Xun et al. 2012) and with other cohort studies (Yuan et al. 2001, Folsom and Demissie 2004, Myint et al. 2006, Montonen et al. 2009), which could not find any inverse association between omega-3 PUFA and risk of stroke. However, opposite results have also been found (Iso et al. 2001, He et al. 2002, Larsson et al. 2011). The possible mechanism of the effect of fish consumption on stroke, especially ischemic stroke, could be explained by the effect of long-chain omega-3 PUFA from fatty fish. Omega-3 fatty acids from fatty fish influences blood pressure, lipid levels, inflammatory responses, red blood cell deformability, endothelial cell function, and cerebral arteriolar reactivity (Agren et al. 1990, Ellis et al. 1992, Knapp 1996, Nestel 2000). Each of these effects, separately or in combination, may plausibly reduce risk of ischemic stroke (Mozaffarian et al. 2005). Although each of these effects can have a role on reducing risk of ischemic stroke, this population cohort study could not find any beneficial effect of total serum long-chain n-3 PUFA or individual fatty acids separately with risk of stroke. Unlike with the other cardiovascular outcomes in this study cohort, high exposure to Hg does not seem to be the explanation, because adjustment for Hg only slightly strengthened the associations.
Mozafarrian et al., explained the physiological effects and molecular pathways of n-3 PUFA that might influence CVD risk (Wu and Mozaffarian 2014). Omega 3 PUFA has effect on different physiological functions in different tissues, including heart, liver, vasculature, and circulating cells. Experimental studies show that n-3 PUFA has effect on cardiac electrophysiology, which could contribute to decrease in heart rate and arrhythmic risk (Wu and Mozaffarian 2014). n-3 PUFA reduce plasma triglyceride through decreasing very low-density lipoprotein production in liver and increasing fatty acid beta-oxidation (Wu and Mozaffarian 2014). Blood pressure-lowering effect of n-3 PUFA is a result of reduced
systemic vascular resistance, which improves endothelial dysfunction, wall compliance, and vasodilatory responses. Physicochemical properties of cellular membranes are influenced by their lipid composition. n-3 PUFA have protective effect on CVD (Wu and Mozaffarian 2014) through its role on membrane fluidity, ion channels function and gene expression via nuclear receptors and transcription factors. There are no comprehensive studies in regard to the effects on risk factors, molecular pathways, of protective effect of omega-3 PUFA and stroke.
Although most of the risk factors for CVD and stroke are similar, we could not find any association between omega 3 PUFA and stroke.
We used hair mercury as a reliable marker of long-term exposure (World Health Organization 1990) . This study found a direct association between hair methylmercury content and risk of total stroke, which contradicts the null findings from the only previous study done by Mozaffarian et al (Mozaffarian et al. 2011). Several explanations may explain the conflicting results. Higher mercury level in the KIHD population could explain the different study findings. In the US cohort study the mean toenail mercury concentration was 0.44 µg/g in the male controls, corresponding to about 1.2 µg/g in hair (Mozaffarian et al. 2012). In our study the mean hair mercury concentration is 1.9 µg/g. Thus, in lower concentrations mercury may not have any adverse effects and higher levels of exposure are needed for the adverse effects.
Also the effects of other factors, like dietary antioxidants and selenium, or differences in the genetic-based defenses, may explain the conflicting study findings.
Hair methylmercury could also be a marker of other factors with possible effect on stroke risk.
As seen in the Table 7, high hair mercury concentration has associated with stroke risk factors, such as systolic blood pressure, serum TG, body mass index. Other factors or residual confounding possibly can explain at least partly the higher risk in the highest hair mercury tertile. There were no significant differences in baseline serum long-chain omega-3 PUFA in those who experienced stroke during the follow-up and in those who did not. However, hair methylmercury concentration was higher in those who had a stroke (Table 5). Higher mercury content of selected fish or genetical differences in the elimination of mercury (Schlawicke Engstrom et al. 2008) could explain this.
Few studies have focused on the association between different risk factors and hemorrhagic stroke. Study done by Wang et al., pointed to the positive association between low total cholesterol and LDL-cholesterol levels and hemorrhagic stroke, especially intracerebral hemorrhage (ICH) (Wang et al. 2013). Also, there is an association between low intake of saturated fat and animal protein and increased risk of intraparenchymal hemorrhage (Iso et al.
2001). Previous studies did not focus on the association between mercury exposure and different stroke types separately. Oxidative stress effect of methylmercury, which can decrease anti-oxidative capacity in plasma and cells and increase lipid peroxidation in cell membranes, could at least partly explain the association between mercury exposure and risk of stroke (Virtanen et al. 2005). Mercury also has high affinity to sulfhydryl groups, which results in inactivation of anti-oxidative thiolic compounds (Flora et al. 2008). In addition, mercury binds with selenium and forms an inactive form that cannot act as a catalytic center of glutathione peroxidase, a main scavenger of H2O2 and lipid peroxides (Virtanen et al. 2005). However, we do not have an explanation for why Hg would increase the risk of hemorrhagic stroke but not the risk of ischemic stroke. Further research is needed to elucidate the associations.
Strength of the present study is the use of serum long-chain n-3 PUFA measurements instead of dietary intakes. Few prior studies have used circulating long-chain n-3 PUFA concentration as an exposure, which is important to reduce bias by misclassification that attenuates the associations in studies using dietary intakes. Serum long-chain n-3 PUFA concentration is a good biomarker of n3 fatty acid exposure (Hunter 1998). The other strength is the population-based recruitment and high participation rate. Limitation of the study is the low number of stroke cases, especially hemorrhagic strokes and the participants were only men.
7. Conclusions
In summary, our findings suggest that circulating n3-PUFA levels are not associated with stroke. However, methylmercury exposure was associated with higher risk of total stroke.
Although some studies have found an inverse association between serum omega 3 PUFA and stroke, there is not enough evidence about the specific amount of long-chain omega-3 PUFAs that is needed to reduce risk of stroke. Also, the amount of long-chain omega-3 PUFAs in
supplements is higher than what is commonly obtained from diet, so recommendation to take fish oil as a supplement instead of dietary fish intake should be done cautiously (He et al.
2004).
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