Abstract
Objectives
Diet may change the chronic levels of systemic inflammation, which in turn influence the development of leukoaraiosis (LA). This study aimed to examine the association between dietary inflammatory index (DII) and LA in patients with ischemic stroke.
Methods
Patients with first-ever ischemic stroke were enrolled from two centers. A semi-quantitative food frequency questionnaire (FFQ) was used to evaluate diet contents. The DII score of each patient was calculated based on the reported diet contents. Presence and degree of LA were evaluated with a magnetic resonance imaging (MRI) scan. LA was graded according to Fazekas scale.
Results
Of the 497 enrolled patients, 337 (67.8%) were detected with LA. Patients with LA had a higher DII score (0.23 vs -0.88, P < 0.001). Logistic regression analysis detected that patients with highest quartile of DII score had an OR of 3.61 (95% CI: 2.05–6.36, P < 0.001) for LA compared with those with lowest quartile of DII. After adjusting for major confounders, the highest DII quartile remained as an independent predictor for LA (OR = 2.66, 95% CI: 1.41–5.00, P = 0.008).
Conclusions
A pro-inflammatory diet pattern, as indicated by higher DII values, appears to be associated with a higher risk of LA. This result suggested that dietary-mediated inflammation may involved in the pathogenesis of LA, which warrant further study.
Key words: Leukoaraiosis, dietary inflammatory index, ischemic stroke
Introduction
Leukoaraiosis (LA) also known as white matter hyperintensity (WMH), is a cardinal manifestation of cerebral small vessel disease, which can be visualized by MRI as abnormal patchy or diffuse signals in cerebral white matter (1). Patients with LA bear increased risk for dementia (2), depression (3), stroke occurance (4) and stroke recurrence (5). Determining the causes and risk factors of LA, therefore, is of vital importance for preventing and managing these disabling chronic conditions.
Inflammatory may play an important role in the initiation and development of LA (6, 7). High serum C-reactive protein (CRP) level, an established biomarker for systemic inflammation, was associated with presence and progression of LA in elderly Europeans (6). Serum CRP level, interleukin 6 (IL-6) level and IL-6 gene variation were all associated with increased risk for LA in an US study of elderly population (8). In animal study, increased astrocytes and activated microglia, both were regarded as significant neuroinflammation manifestation, were associated with white matter lesions (9).
On the other hand, diet may regulate systemic inflammation. The Mediterranean diet, which is rich in whole grains, vegetables, fruit, fish and olive oil, has been proved to reduce systemic inflammation level (10). In contrast, diet with high contents of saturated fatty acids and/or trans fatty acids has been associated with increased systemic inflammation level (11, 12).
The Dietary Inflammatory Index (DII) was developed for evaluating dietary inflammatory potential on individual level (13). Previous studies have related DII to obesity, diabetic mellitus, cardiovascular event and cancer (14, 15, 16). The relationship between DII and LA has not been assessed to date. This study aimed to probe this possible relationship in patients with ischemic stroke.
Materials and methods
Study Population
Patients with ischemic stroke were enrolled from Jinling Hospital and Huainan First People's Hospital from June 2018 to June 2019. Patients were included if they: (1) had first-ever ischemic stroke in 7 days; (2) aged ≥ 50 years; (3) completed brain magnetic resonance imaging (MRI) scan in 7 days of the index stroke. The patients were excluded if they: (1) had surgery or radiation treatment to the head; (2) had intracranial tumor; (3) had severe heart, renal or liver diseases. This study was approved by the ethic committee of the two participating centers. Informed consent was obtained from each patient.
Diet Assessment
Dietary components were investigated with food frequency questionnaire (FFQ) developed for National Health and Nutrition Examination Surveys (NHNES) (17), with common Chinese food items added. As a result, this Chinese version of NHNES FFQ included 298 food items. The individual foods were classified into eight groups: staples (grains, potatoes and beans), vegetables, fruits, nuts, meats and fishes, beverages, dietary supplements and condiments. During faceto- face interviews, patients or their proxies were asked to report frequency and amount of each food consumed in the previous 12 months. Daily mean energy and nutrient intakes were calculated using the Chinese Food Composition Table 2nd edition and US Department of Agriculture (USDA) National Nutrition Databases. Male participants reported a total energy intake of < 800 or > 4200 kcal/day, and female participants reported a total energy intake of < 500 or > 3500 kcal/day were excluded. DII relies on a literature review of 1943 peer-reviewed articles that assessed the inflammatory potential of an individual’s diet based on 45 food parameters (13). DII was established based on the presumption that systemic inflammation may be reflected by six inflammatory biomarkers: serum interleukin-1β (IL-1β), IL-4, IL-6, IL-10, tumor necrosis factor-α (TNF-α) and CRP levels. A total of 31 food components were identified for changing the serum inflammatory biomarkers, and therefore were utilized for calculating DII. Pro-inflammatory components included vitamin B12, carbohydrate, cholesterol, energy, total fat, iron, protein, saturated fat and trans fat. Anti-inflammatory components included alcohol, vitamin B6, β-carotene, fiber, folate, garlic, magnesium, mono-unsaturated fat, niacin, n-3 fatty acids, onion, poly-unsaturated fat, riboflavin, selenium, thiamin, vitamin A, vitamin C, vitamin E, zinc, green/black tea, pepper and isoflavones. A lower DII score represented an anti-inflammatory diet, whereas a higher DII score a proinflammatory diet.
Assessment of LA
The cerebral MRI scan on an 1.5-T or 3.0-T system was performed within 7 days of stroke onset. The scan included T1-weighted, T2-weighted and fluid-attenuated inversion recovery sequences (FLAIR) images. LA was diagnosed as WMH on the T2-weighted images or FLAIR images. The Fazekas scale was used to rate the severity of periventricular (18). PVH was graded as: 0 =absence, 1 =caps or pencil-thin lining, 2 =smooth halo, and 3 =irregular PVH extending into the deep white matter. DWMH was scored as: 0 =absence, 1 =punctuate foci, 2 =beginning confluence of foci, and 3 =large confluent areas. The Fazekas score was a sum of PVH and DWMH scores, which ranged from 0 to 6. Finally, the severity of LA was divided into 4 grades: none (Fazekas score 0), mild (Fazekas score 1–2), moderate (Fazekas score 3–4) and severe (Fazekas score 5–6).
Statistical Analysis
Continuous variables were presented as mean ± SD or median (interquartile range). Categorical variables were presented as numbers (percentages). Independent t test or Mann-Whitney U test were applied for continuous variables. Chi-square test or Fisher exact test were employed for categorical data. Multivariate logistic regression analysis was performed for evaluating risk of LA. Model 1 was adjusted for age and sex; Model 2 was adjusted for age, sex, comorbidities (hypertension, diabetes, hyperlipemia, coronary heart disease, atrial fibrillation) and history of smoking. The pattern and magnitude of associations between DII and LA was evaluated using restricted cubic spline with 4 knots (at 5th, 35th, 65th, 95th) adjusted for covariates as in model 2. Spearman’s correlation test was applied to assess the relationship between DII and the severity of LA. Results were considered as statistically significant if two-sided P < 0.05. The R software package (version 3.0) was utilized for restricted cubic spline test, while SPSS 22.0 (IBM, New York, USA) was adopted for other statistical analyses.
Results
A total of 497 patients with first-ever ischemic stroke were enrolled. There were 277 (55.7 %) males and 220 (44.3 %) females. The median patient age was 63 (57–69) years. Based on MRI results, 337 (67.8 %) patients were defined as with LA, and their DII scores ranged between -5.31 and 3.13 (median -0.08).
Compared with subjects without LA, those with LA were older (P < 0.001), had a higher prevalence of hypertension (P < 0.001), diabetes (P = 0.020), smoking (P = 0.004), and had remarkably higher levels of DII score (P < 0.001). Patients with LA had lower intakes of energy, carbohydrate, protein, fiber, vitamin C, vitamin E, β-carotene, Fe and Mg (all P < 0.05) than those without LA (Table 1).
Table 1.
Baseline characteristics of participants with or without LA
| Variables | Total (n = 497) | Without LA (n = 160) | With LA (n = 337) | P value |
|---|---|---|---|---|
| Age, years | 63 (57.69) | 58 (54.64) | 65 (60.71) | <0.001 |
| Gender, Male, n (%) | 277 (55.7) | 83 (51.9) | 194 (57.6) | 0.233 |
| BMI, kg/m2 | 24.5 (22.9–26.8) | 24.2 (22.8–26.4) | 24.8 (22.9–27.0) | 0.191 |
| Hypertension, n (%) | 314 (63.2) | 67 (41.9) | 247 (73.3) | <0.001 |
| Diabetes, n (%) | 135 (27.2) | 33 (20.6) | 103 (30.6) | 0.020 |
| Hyperlipemia, n (%) | 24 (4.8) | 8 (5.0) | 16 (4.7) | 0.902 |
| History of coronary heart disease, n (%) | 38 (7.6) | 11 (6.9) | 27 (8.0) | 0.656 |
| Atrial fibrillation, n (%) | 53 (10.7) | 15 (9.4) | 38 (11.3) | 0.521 |
| Smoking, n (%) | 152 (30.6) | 37 (23.1) | 115 (34.1) | 0.004 |
| DII, score | -0.08 (-1.71–1.03) | -0.88 (-2.52–0.53) | 0.23 (-1.23–1.30) | <0.001 |
| Energy, kcal/d | 1303 (967–1654) | 1408 (1043–1807) | 1216 (928–1577) | <0.001 |
| Carbohydrate, g/d | 181(147–232) | 199 (154–263) | 173 (142–212) | <0.001 |
| Protein, g/d | 42.9 (34.8–54.7) | 43.6 (35.7–57.1) | 41.8 (34.0–53.0) | 0.041 |
| Total fat, g/d | 42.2 (29.8–62.0) | 44.3 (28.9–70.7) | 41.0 (30.2.59.3) | 0.245 |
| Fiber, g/d | 10.9 (8.8–13.9) | 11.3 (9.3–14.5) | 10.7 (8.6–13.5) | 0.015 |
| Vitamin C, mg/d | 76 (50–120) | 95 (56–130) | 68 (49–113) | <0.001 |
| Vitamin E, mg/d | 18.0 (13.–26.3) | 19.5 (15.2–27.9) | 17.5 (13.5–25.8) | 0.023 |
| β-carotene, mg/d | 1824 (1144–3045) | 2340 (1363–3469) | 1626 (1129–2725) | <0.001 |
| Fe, mg/d | 14.7 ± 5.4 | 16.1 ± 4.4 | 14.1 ± 5.7 | <0.001 |
| Mg, mg/d | 222 (176–293) | 250 (200–323) | 205 (167–272) | <0.001 |
LA, leukoaraiosis; BMI, body mass index; DII, dietary inflammatory index.
There were 67 (19.9%), 79 (23.4%), 91 (27.0%) and 100 (29.7%) patients with LA in DII quartile 1, quartile 2, quartile 3, and quartile 4 respectively. Patients with higher DII had higher prevalence of LA (P < 0.001 for trends).
Logistic regression analysis detected that patients with the highest quartile of DII had higher risk of LA (OR 3.61, 95% CI 2.05–6.36, P < 0.001) compared to patients with the lowest quartile of DII. After adjusting for age, sex and cardiovascular risk factors, the top DII quartile remained independently related to the prevalence of LA (OR 2.66, 95% CI 1.41–5.00, P = 0.008, Table 2). Multiple-adjusted restricted cubic spline regression showed a positive correlation between DII scores and the risk of LA (P for linear trend = 0.002, Figure 1). DII scores had a moderate correlation with the severity of LA (r = 0.477, P < 0.001).
Table 2.
Odds ratios and 95% CIs for LA according to DII quartiles
| Quartiles of DII score | Q1 (< -1.71) n = 125 | Q2 (-1.71 to -0.08) n = 123 | Q3 (-0.08 to 1.03) n = 125 | Q4 (≥ 1.03) n = 124 P value | |
|---|---|---|---|---|---|
| Unadjusted model | 1.00 | 1.55 (0.93–2.59) | 2.32 (1.37–3.93) | 3.61 (2.05–6.36) | < 0.001 |
| Model 1 | 1.00 | 1.76 (1.02–3.03) | 2.49 (1.42–4.37) | 3.64 (2.–6.62) | <0.001 |
| Model 2 | 1.00 | 1.85 (1.03–3.32) | 2.29 (1.26–4.18) | 2.66 (1.41–5.00) | 0.008 |
Model 1: adjusted for age and sex; Model 2: adjusted for age, sex, comorbidities (hypertension, diabetes, hyperlipemia, CHD, atrial fibrillation) and history of smoking; LA, leukoaraiosis; DII, dietary inflammatory index; CHD, coronary heart disease; CI, confidence interval.
Figure 1.
Association of DII score with risk of LA. Odds ratio and 95% CI were derived from restricted cubic spline regression, with knots placed at 5th, 35th, 65th, and 95th percentiles of DII. The reference point for DII was the midpoint (-0.08) of the reference group from categorical analysis. Odds ratio was adjusted for the same variables as in model 2 (Table 2).
Discussion
This study observed a 2.66-fold higher risk of LA among individuals with the highest quartile of the DII compared to those with the lowest DII quartile after adjusting for major confounders. To the best of our knowledge, this is the first study to investigate the association between DII and LA.
The DII scores in this study ranged between -5.31 and 3.13, which is comparable to a large cohort of North American people from the Osteoarthritis Initiative database (DII range: -5.65 to 3.57) (19), while differ from a study to investigate the role of dietary inflammatory capacity and odds of psychological disorders among Iranian general adults (DII range: -4.49 to 5.39) (20) and a cohort of middle-aged French (DII range: -4.99 to 5.98) (21). This may due to the diversity of dietary habits in different nations and races.
Although the mechanisms for the association between DII score and LA remained largely undetermined, some possible explanations should be considered. First, a higher DII signifies a pro-inflammatory diet which is related to high levels of circulating inflammatory markers (13). Numerous studies have shown that inflammatory mechanisms play an important role in the development of LA. In the US Cardiovascular Health Study, both plasma IL6 and CRP levels have been associated with the presence of LA in both Whites and Blacks (8). Also, another research reported that the inflammatory markers lipoproteinassociated phospholipase A2 (Lp-PLA2) and myeloperoxidase (MPO) in the upper quartile had a greater burden of WMH after adjusting for the relevant variables of stroke-free participants (7). Second, cerebral hypoperfusion possibly play an additional role between DII and LA. Cerebral white matter is highly vulnerable to the reduction of brain blood flow and animal models have demonstrated that white matter abnormalities detecting by in vivo MRI are observed following hypoperfusion (22). Increased inflammatory response is involved as an important underlying mechanism in LA caused by cerebral hypoperfusion (23), furthermore, the administration of dimethyl fumarate (DMF), an anti-inflammatory drug, has been shown to improve white matter lesion after cerebral hypoperfusion, which indirectly proves the role of inflammation in white matter injury following cerebral hypoperfusion (24). A proinflammatory diet may exacerbate such a process. Last but not the least, individuals with higher levels of DII were more likely to be smokers, obesity and more often had a history of hypertension and diabetes, and all of which have been shown to accelerate the formation of LA (25, 26, 27, 28).
One prominent advantage of DII lies in that it can generally reflects the overall dietary inflammation, and its effectiveness has been proved in different populations. This study used the modified Chinese version of NHNES with many common food items added, which we think is more suitable for the Chinese population. Subjects in this study were from two centers in Anhui and Jiangsu provinces, where the socioeconomic development was more advanced, and diet patterns in this population were more diverse. These profiles enable us to investigate the impact of diet on LA thoroughly.
Several limitations should be addressed when interpreting the results of this study. First, this was a cross-sectional study, which, by nature, is impossible to determine a causal relationship. Further prospective study is warrant. Second, diet components were obtained using a FFQ, with which memory bias is inevitable. In elderly patients this bias may be more remarkable. Lastly, due to dietary habits of Chinese population, only 31 food parameters were available for DII calculation, and 14 food parameters were not included in this study. However, it has been validated that the predictive ability of DII remains about the same even when the amount of food parameters decreased to 28 (29).
Conclusions
A pro-inflammatory diet pattern, as indicated by higher DII values, appears to be associated with a higher risk of LA. This result suggested that dietary-mediated inflammation may involved in the pathogenesis of LA, which warrant further study.
Acknowledgments
This work was partly supported by China Nature Science Foundation (CNSF #81870947).
Contributor Information
Xiongfei Zhao, Email: zhaoxiongfei1973@sina.com.
Gelin Xu, Email: gelinxu@nju.edu.cn.
Conflict of interest
All authors declare that there were no conflict of interests.
Ethical Standards
The authors declare that this study complies with the current laws of China.
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