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Risk Factors of Stroke in Western and Asian Countries: A Systematic Review and Meta-analysis of Prospective Cohort Studies

BMC Public Health volume 14, Article number: 776 (2014) Cite this article

Abstract

Background

There has been an increasing trend in the incidence of stroke worldwide in recent years, and the number of studies focusing on the risk factors for stroke has also increased every year. To comprehensively evaluate the risk factors of stroke identified in prospective Western and Asian cohort studies.

Methods

Population-based cohort studies on stroke were searched in databases (PubMed, EMBASE, Web of Science, Google Scholar, etc.), and the library of the Third Military Medical University was manually searched for relevant information. A meta-analysis of Western and Asian studies on risk factors was performed. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated to assess the final group of cohort studies.

Results

After screening, 22 prospective cohort studies were included in the analyses of this investigation. Two factors, smoking and alcohol consumption, showed statistically significant differences between Western and Asian populations, and the results were as follows (W/A): 2.05 (95% CI, 1.68 ~ 2.49)/1.27 (95% CI, 1.04 ~ 1.55) and 0.89 (95% CI, 0.76 ~ 1.04)/1.28 (95% CI, 1.07 ~ 1.53). The factor BMI = 18.5-21.9 kg/m2 showed statistically significant differences only in Western populations, 0.96 (95% CI, 0.93 ~ 0.99); the factor SBP = 120-139 mm Hg showed statistically significant differences only in Asian populations, 2.29 (95% CI, 1.04 ~ 5.09).

Conclusions

The prevalences of risk factors affect the stroke morbidity in Western and Asian populations, which may be biased by race. The meta-analysis of population-based studies suggests that different preventive measures should be adopted for Western and Asian population groups that are at high risk for stroke.

Peer Review reports

Background

Stroke is not only the second leading cause of death worldwide but also one of the main causes of adult-acquired disabilities [1, 2]. In certain countries, the incidence of stroke has increased over time. For example, the incidence of stroke in the city of Frederiksberg in Denmark increased from 618/100,000 during the period from 1972–1974 to 1,190 per 100,000 during the period from 1989–1990 [3], and the incidence of stroke among males in Gothenburg, Sweden increased by 35% per year from 1985 to 1990 [4]. In recent years, the incidence of stroke has gradually increased among younger populations. In a region of Western Norway, the incidence of ischemic stroke among young adults was 11.4/100,000 between 1988 and 1997, with women accounting for the majority of patients who experienced a stroke before reaching 30 years of age and males accounting for the majority of patients who experienced a stroke after 30 years of age [5]. In India, the prevalence of stroke is 1.54, with a death rate of 0.6 per 1,000 population; the age-adjusted stroke mortality is believed to be 60% higher in South-East Asia than in European populations [6]. The same situation exists in Iran; a systematic review reported that the stroke prevalence for various ages in Iran ranges from 23 to 103 per 100,000 populations [7].

There have been numerous recent research reports regarding the risk factors for stroke, which include not only unhealthy lifestyle habits such as smoking and drinking but also hypertension, diabetes, and a family history of diseases, among other traits [8–18]. However, different sets of risk factors and risk intensities have been identified by various studies, and no comprehensive systematic review has compiled and summarized the findings of these studies. In this investigation, based on a large number of prospective cohort studies from around the world, a systematic review and a meta-analysis were conducted to summarize the risk factors for stroke in Western and Asian populations.

Methods

Our investigation was conducted as suggested by the Meta-analysis of Observational Studies in Epidemiology (MOOSE) group [19]. A detailed query strategy and inclusion and exclusion criteria were developed, and the relevant literature was screened for inclusion using these standards. Two research groups were established. The first research group was responsible for searching for and reviewing relevant studies and extracting the original data from these investigations. The second group evaluated the quality of the included studies. Finally, pooled statistics describing various effects were calculated.

Systematic literature search

The following electronic literature databases were searched: PubMed, EMBASE (the Excerpta Medica Database), Web of Science, Google Scholar, the Chinese Biomedical Literature Database (CBM), the integrated Chinese Medical Citation Index/Chinese Medical Current Contents (CMCI/CMCC) database, and the Cochrane Central Register of Controlled Trials (CENTRAL) database of the Cochrane Library. The following search terms were utilized: ((((((((stroke) OR ischemic) OR hemorrhagic) OR observational study) OR cohort study) AND risk factors) OR incidence) OR mortality) AND prospective study. In addition, the library of the Third Military Medical University was manually searched for relevant information. The period specified in these searches ranged from the creation date of each database to May 2013.

Inclusion and exclusion criteria

Studies were included if they met the following criteria: ① The included studies were prospective, population-based cohort studies; ② The included studies involved research participants who were volunteers from a community or hospital, with no limitations placed on sex, age, or type of stroke, although the participants were required to be free from any complicating infectious or traumatic conditions; ③ The included studies were required to provide HRs for the risk factors; ④ The observation endpoint of the included studies was the onset of stroke; ⑤ The included studies were required to base the determination of disease on internationally adopted professional diagnostic criteria[20, 21]; ⑥ Comparability of the cohorts was required on the basis of the design or analysis; ⑦ The included studies were required to provide a full contingency table and/or adjusted HR/RR (relative risk) values.

The exclusion criteria included the following: â‘  Studies examining populations that might be affected by interactions between genes and the environment, such as the Asian-American population, were excluded; â‘¡ Case control studies and other retrospective studies were excluded from consideration; â‘¢ Duplicate publications, animal experiments, reviews, and systematic reviews were excluded from consideration.

Selection and data extraction

The retrieved literature was carefully reviewed, and various information was extracted for each examined study, including the study’s first author, publication year, sample size, study type, population characteristics, study endpoint, and HR/RR values and 95% confidence intervals (CIs) (or a contingency table). The data were independently extracted in a blinded manner by two researchers (LZ and XC) from the first research group. A third researcher (LL) from this research group was consulted to resolve discrepancies in the extracted data, and a consensus was reached through discussion.

Quality assessment and statistical analyses

The included observational studies were subjected to a comprehensive quality assessment using the Newcastle-Ottawa Scale as a guide [22]. This quality evaluation was performed in a blinded manner by two researchers (YW and YZ) from the second research team, who assigned quality scores to the included studies. The studies that were given different quality scores by the two researchers were referred to a third researcher (DY) from this research team for evaluation, and a final quality score was obtained.

Q tests were conducted to determine the heterogeneity of the included studies. If I2 ≥ 50% and P < 0.1, a random-effects model was used to combine the studies; by contrast, if I2 ≤ 50% and P > 0.1, a fixed-effects model was used to combine the studies. The adjusted HR was used to measure the effect sizes for the pooled prospective cohort studies, and 95% CIs were determined for the pooled studies. Egger’s regression test was used to verify the absence of publication bias, and by model transformation between the fixed effects model and random effects model for the sensitivity analysis. The fundamental approach utilized in this non-parametric method involves first trimming (removing) small sample studies that cause funnel plot asymmetries. The trimmed symmetric remainder is then used to estimate the center value of the funnel plot, and the removed studies and their corresponding estimated missing values are then entered into the plot on both sides of this center value [23], enabling an assessment of the stability of the entire systematic review. All of the statistical analyses were conducted using the Stata 11.0 software package.

Results

Included studies

The database search resulted in the identification of 1,288 articles; in addition, 2 conference-related publications were identified from other sources. In total, 224 of these articles were duplicates that had been identified in multiple electronic databases, and 941 articles did not address the desired research topic; thus, 125 studies were included in the initial screening (including 123 articles and two conference-related publications). The initial screening of the abstracts of these studies resulted in the exclusion of 51 non-prospective cohort studies, 15 reviews or systematic reviews, and 2 animal studies. The full-text versions of the remaining 56 articles were then assessed, and 34 articles that did not meet the inclusion criteria were excluded from consideration. Ultimately, 22 prospective cohort studies were included in this systematic review and meta-analysis (Figure 1 and Table 1).

Figure 1
figure 1

Flow diagram.

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Table 1 Characteristics of the prospective studies on stroke
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Study characteristics

This study examined data reported by researchers from Western (North America, Europe, and Oceania) and Asian (East Asia, South Asia, and Southeast Asia) countries. In the 22 prospective cohort studies that were included in this investigation, the sample sizes ranged from a minimum of 39 cases to a maximum of 7,444 cases; 30,406 cases were examined in these studies. Eleven of the included studies involved Western populations, and the remaining 11 studies involved Asian populations. In 20 of the included studies, the outcomes included both ischemic stroke and hemorrhagic stroke, whereas the remaining 2 studies only examined ischemic stroke (Table 1).

Synthesis of results

This study examined 7 risk factors for stroke in human populations, including biochemical indices, lifestyle choices, and medical history. A meta-analysis produced pooled HRs with 95% CI values for each of these factors.

The combined results indicated that 6 factors affected the incidence of stroke in Western populations. These factors included BMI, SBP, hypertension, diabetes, cardiac causes, and smoking. The following pooled HR values with 95% CIs were obtained for these factors: 0.96 (0.93 ~ 0.99) for a BMI of 18.5-21.9 kg/m2; 2.39 (1.44 ~ 3.97) for an SBP ≥140 mm Hg; 1.79 (1.39-2.30) for hypertension; 1.85 (1.43 ~ 2.38) for diabetes; 1.74 (1.47 ~ 2.04) for cardiac causes; and 2.05 (1.68 ~ 2.49) for smoking; However, 0.89 (0.76 ~ 1.04) for alcohol consumption (Table 2 and Additional files 1, 2, 3, 4, 5, 6, 7, 8).

Table 2 Meta-analysis outcomes
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In addition, in a subgroup analysis of smoking and cardiac causes, there was statistical significance in the 4 subgroups, including atrial fibrillation, current smoking, smoking ≤20 cigarettes/d and smoking >20 cigarettes/d. The pooled HRs with 95% CI values were as follows: 1.59 (1.33 ~ 1.90), 2.27 (1.76 ~ 2.93), 2.31 (1.80 ~ 2.96) and 2.99 (2.31 ~ 3.86) (Table 2 and Additional files 5, 7).

The included studies of Asian populations indicated that 7 factors affected the incidence of stroke. These factors included BMI, SBP, hypertension, diabetes, cardiac causes, smoking and alcohol. The following pooled HR values with 95% CIs were obtained for these factors: 1.28 (1.15 ~ 1.46) for a BMI of ≥25.0 kg/m2; 2.29 (1.04 ~ 5.09) for an SBP of 120–139 mm Hg; 6.22 (2.27 ~ 17.08) for an SBP ≥140 mm Hg; 2.84 (2.10-3.82) for hypertension; 1.95 (1.42 ~ 2.67) for diabetes; 1.87 (1.45 ~ 2.42) for cardiac causes; 1.27 (1.04 ~ 1.55) for smoking; and 1.28 (1.07 ~ 1.53) for alcohol consumption (Table 2 and Additional files 9, 10, 11, 12, 13, 14, 15, 16).

In the subgroup analysis of cardiac causes, there was statistical significance for atrial fibrillation. The pooled HR with the 95% CI was 2.30 (1.50 ~ 3.53) (Table 2 and Additional file 12).

Quality of the included studies

The Newcastle-Ottawa scale results revealed that 95.45% of the included studies earned above 2 stars for the NOS selection item, 77.27% of the included studies earned above 1 star for the NOS comparability item, and 36.36% of the included studies earned above 2 stars for the NOS exposure item (Table 3).

Table 3 The results of the Newcastle-Ottawa scale (NOS)
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Egger's test was performed to assess the influential factors for each of the two populations that were examined (Table 4). Publication bias affected 2 factors in studies of Western populations: cardiac causes (t = 6.32, P = 0.000) and smoking (t = 6.21, P = 0.000). This analysis revealed that publication bias affected 4 factors in the studies of Asian populations: BMI = 22.0-24.9 kg/m2 (t = -9.52, P = 0.000), BMI ≥25.0 kg/m2 (t = 3.36, P = 0.012), diabetes (t = 4.50, P = 0.003), smoking (t = 11.39, P = 0.000) and alcohol (t = 1.06, P = 0.008).

Table 4 Egger's test & Sensitivity analysis
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By model transformation between the fixed effects model and random effects model for the sensitivity analyses of the included factors (Table 4). The sensitivity analysis results were consistent (Additional files 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16).

Discussion

This systematic review of prospective cohort studies on the incidence of stroke summarized 7 risk factors for stroke that have been reported with relatively high frequency in prior studies. The prospective cohort studies incorporated into this review examined 867,782 Western or Asian participants and included investigations of large cohorts and studies of small community groups. To avoid biases attributable to differences in ethnicity and geography, the statistical analyses of the final combined results were stratified by Western or Asian population types.

Six factors affected the incidence of stroke in both Western and Asian populations. These factors included hypertension and diabetes, which are well-known risk factors for the incidence of stroke; thus, these findings are consistent with the results of earlier reports [66].

Studies have reported that a BMI ≥25 kg/m2 is associated with increased mortality among middle-aged populations, particularly from cardiovascular and cerebrovascular diseases, which are the leading causes of death [67]. Previous studies have reported similar findings for obesity [68]; in our study, obesity was one of the risk factors for the onset of disease in Asian populations, and an elevated BMI was associated with greater risk (Figure 2). In addition, the result of the risks associated with a BMI ≥25 kg/m2 was greater among Asian populations than among Western populations.

Figure 2
figure 2

Risk factors in Western and Asian populations. (**Former, Current, ≤20 Cigarettes/d and >20 Cigarettes/d; #Cardiac causes: Coronary heart disease, Left Atrial hypertrophy, Angina, Atrial fibrillation; HR Hazard risk; CI, Confidence interval; BMI, Body mass index; SBP, Systolic blood pressure).

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Stroke-related studies in the community of Framingham in the United States and the North Karelia region of Finland, as well as investigations of interventions for stroke-related risk factors in 7 Chinese cities, have confirmed the existence of a correlation between blood pressure and stroke [69–74]. SBP, a direct indicator of hypertension, is also a factor that directly influences the incidence of stroke. However, the risk of stroke was elevated in hypertensive patients relative to patients exhibiting high blood pressure without previously diagnosed hypertension [75]. The results of this study indicate that an increasing SBP is associated with an increased risk of stroke. In fact, the risk of stroke was greater among the participants with SBP ≥140 mm Hg than among the patients with diagnosed hypertension in both Asian and Western populations (Figure 2). A possible reason for this phenomenon is that most individuals diagnosed with hypertension have received appropriate anti-hypertensive interventions. Previous studies have shown that patients diagnosed with stroke often receive antihypertensive medication [15, 16]. From the results of our investigation, the risks associated with SBP ≥140 mm Hg is greater among Asian populations than among Western populations. For example, the cohort studies of a workforce in China [42],which examined steelworkers in Beijing, China, found an age-adjusted RR of 5.6 among these individuals, which was higher than the RR of 3.5 obtained in the Framingham study [76]. In our previous retrospective study [77], the Rothman and Keller [78] model was utilized to establish a multivariate model for predicting the incidence of stroke in human populations. Consistent with previous reports, this model represented the occurrence of stroke resulting from the combined long-term effects of multiple risk factors [79]. Our prior results also explored the effects of the interactions between hypertension and other risk factors on the incidence of stroke. However, the question of whether changes in other risk factors could alter the intensity of the risk of hypertension with respect to the incidence of stroke in a particular population (Western or Asian) merits additional study and discussion.

The Busselton Study reported that atrial fibrillation is a risk factor for stroke, with an RR of 5.9 [80], and other studies have also consistently indicated that atrial fibrillation is a risk factor for stroke [81]. In our investigation, atrial fibrillation was again identified as a risk factor; the result for this factor in Western populations was 2.30 (1.50 ~ 3.53), and there was no difference in Asian populations by interval estimation (Table 2). Consistent with our results, cardiovascular-related diseases (such as angina and CHD) were identified as risk factors for stroke as early as the Framingham Study and related reports [82]. Previous studies have suggested that left ventricular hypertrophy (LVH) is not correlated with the occurrence of stroke [13]; however, our investigation indicated that LVH is a risk factor for stroke in Western populations. Therefore, effective measures for preventing stroke in Western populations include lifestyle improvements, appropriate treatments, and reductions in the morbidities associated with chronic cardiovascular and cerebrovascular diseases.

Smoking is a risk factor for stroke, and the HR values for smoking-related behaviors were relatively high in Western populations. After stratifying the results based on the periods during which smoking occurred, it was determined that former smoking had no effect on the incidence of stroke in Western populations. Certain prior studies have suggested that being a former smoker can affect the incidence of stroke [83–85], whereas other studies have found no significant effects associated with this characteristic [86]. We observed a dose–response association for the number of cigarettes smoked per day in Western populations: the HR value associated with smoking more than 20 cigarettes per day was much greater than the HR values of other risk factors by point estimation (Figure 2); this result is consistent with the findings of previous studies [86, 87]. Therefore, reducing daily cigarette consumption is an effective preventive measure for reducing the incidence of stroke.

The results from the studies of Asian populations indicated that long-term alcohol consumption was also a risk factor for stroke, although this factor had no effect on the incidence of stroke in Western populations (Table 3). Prior studies have also produced controversial results with respect to the significance of this factor: certain studies have determined that heavy long-term alcohol consumption is a risk factor for stroke [88], but other studies have reached the opposite conclusion [89]. However, heavy long-term alcohol consumption is a risk factor for many chronic diseases, and therefore, limiting alcohol consumption may play an indirect role in preventing the incidence of stroke.

Limitations

This systematic review and meta-analysis used the Newcastle-Ottawa scale to score all of the included studies. Overall, the quality of the studies on Chinese populations was significantly lower than the quality of the studies on other populations (T-Test: Z = 3.015, P = 0.007). The primary reason for this finding was that the populations examined in the former studies were mostly large, long-term, community-based cohorts. For example, the studies by the British regional heart study [24] and the PROCAM study [29, 30], among others, were based on data from large European cohorts [29, 30, 32]. By contrast, most of the included Asian studies examined small community-based cohorts or even hospital cases. For example, the research participants assessed by the cadre's sanitarium of Xi’an, China [37] were recruited from a sanatorium for retired military cadres in Xi'an, China. Result biases may be relatively low for large community cohorts but higher for smaller samples. In addition, bias may also be related to the dropout rate. For instance, the study in Shanghai, China [53] reported a dropout rate of 3.09%, whereas the CMCS study [44] reported a dropout rate of up to 22.5%. Although this investigation involved the examination of a large number of literature databases, there was less investigation of the unpublished literature and conference-related information, potentially creating publication bias.

Furthermore, only a limited number of studies were included in this investigation; thus, a large amount of data regarding risk factors was missing. In addition, few studies were pooled to obtain certain data points, particularly for Asian populations, and the number of studies finally included in the meta-analysis was very low for individual risk factors (usually in the range of 1 to 10), and this issue might have produced bias in the results. Therefore, these limitations are related to the absence of studies from South Asia and West Asia, and we believe this might be one reason for the publication bias. Consequently, to obtain more reliable data and results, additional large-sample, multi-center, randomized controlled studies and/or long-term cohort studies must be conducted.

Conclusions

This meta-analysis presents the data from large-scale prospective cohort studies to summarize and evaluate the risk factors for stroke in Western and Asian populations. The results of this investigation are credible, and the pooled results obtained in this review are more reliable than the findings from prior small-scale cohort studies and case–control studies. The analyses conducted in this investigation revealed that Western and Asian populations differ with respect to the factors that affect the incidence of stroke. Therefore, different interventional approaches should be implemented to reduce the risk of stroke among high-risk individuals from different regions and different ethnic groups.

Abbreviations

HR:

Hazard ratio

CI:

Confidence interval

BMI:

Body mass index

SBP:

Systolic blood pressure

MOOSE:

Meta-analysis of observational studies in epidemiology

CBM:

Chinese biomedical literature database

CMCI/CMCC:

Chinese medical citation index/chinese medical current contents

CENTRAL:

Cochrane central register of controlled trials

RR:

Relative risk

NOS:

Newcastle-ottawa scale

CHD:

Coronary heart disease

LVH:

Left ventricular hypertrophy.

References

  1. Feigin VL: Stroke in developing countries: can the epidemic be stopped and outcomes improved?. Lancet Neurol. 2007, 6: 94-97. 10.1016/S1474-4422(07)70007-8.

    Article  PubMed  Google Scholar 

  2. Strong K, Mathers C, Bonita R: Preventing stroke: saving lives around the world. Lancet Neurol. 2007, 6: 182-187. 10.1016/S1474-4422(07)70031-5.

    Article  PubMed  Google Scholar 

  3. Jorgensen HS: Marked increase of stroke of incidence in men between 1972 and 1990 in Frederiksberg. Denmark. Stroke. 1992, 23: 1701-1704. 10.1161/01.STR.23.12.1701.

    Article  CAS  PubMed  Google Scholar 

  4. Peltonen M, Asplund K: Aged-period-cohort effects on stroke mortality in Sweden 1969–1993, and forecast up to the year 2003. Stroke. 1996, 27: 1981-1985. 10.1161/01.STR.27.11.1981.

    Article  CAS  PubMed  Google Scholar 

  5. Naess H, Nyland HI, Thomassen L, Aarseth J, Nyland G, Myhr KM: Incidence and short-term outcome of cerebral infarction in young adults in western Norway. Stroke. 2002, 33: 2105-2108. 10.1161/01.STR.0000023888.43488.10.

    Article  CAS  PubMed  Google Scholar 

  6. Deoke A, Deoke A, Deoke S, Saoji A, Hajare S: Profile of modifiable and non-modifiable risk factors in stroke in a rural based tertiary care hospital - a case control study. Glob J Health Sci. 2012, 4: 158-163.

    PubMed  PubMed Central  Google Scholar 

  7. Hosseini AA, Sobhani-Rad D, Ghandehari K, Benamer HT: Frequency and clinical patterns of stroke in Iran - Systematic and critical review. BMC Neurol. 2010, 10: 72-10.1186/1471-2377-10-72.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Bansal BC, Prakash C, Arya RK, Gulati SK, Mittal SC: Serum lipids, platelets, and fibrinolytic activity in cerebrovascular disease. Stroke. 1978, 9: 137-139. 10.1161/01.STR.9.2.137.

    Article  CAS  PubMed  Google Scholar 

  9. Chopra JS, Prabhakar S: Clinical features and risk factors in stroke in young. Acta Neurol Scand. 1979, 60: 289-300.

    Article  CAS  PubMed  Google Scholar 

  10. Gill JS1, Shipley MJ, Tsementzis SA, Hornby RS, Gill SK, Hitchcock ER, Beevers DG: Alcohol consumption--a risk factor for hemorrhagic and non-hemorrhagic stroke. Am J Med. 1991, 90: 489-497. 10.1016/0002-9343(91)80090-9.

    Article  CAS  PubMed  Google Scholar 

  11. Shaper AG, Phillips AN, Pocock SJ, Walker M, Macfarlane PW: Risk factors for stroke in middle aged British men. BMJ. 1991, 302: 1111-1115. 10.1136/bmj.302.6785.1111.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Shinton R, Sagar G: Lifelong exercise and stroke. BMJ. 1993, 307: 231-234. 10.1136/bmj.307.6898.231.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Jamrozik K, Broadhurst RJ, Anderson CS, Stewart-Wynne EG: The role of lifestyle factors in the etiology of stroke. A population-based case–control study in Perth, Western Australia. Stroke. 1994, 25: 51-59. 10.1161/01.STR.25.1.51.

    Article  CAS  PubMed  Google Scholar 

  14. Truelsen T, Lindenstrom E, Boysen G: Comparison of probability of stroke between the copenhagen city heart study and the framingham study. Stroke. 1994, 25: 802-807. 10.1161/01.STR.25.4.802.

    Article  CAS  PubMed  Google Scholar 

  15. WHO Collaborative Study of Cardiovascular Disease and Steroid Hormone Contraception: Haemorrhagic stroke, overall stroke risk, and combined oral contraceptives: results of an international, multicentre, case–control study. Lancet. 1996, 348: 505-510.

    Article  Google Scholar 

  16. WHO Collaborative Study of Cardiovascular Disease and Steroid Hormone Contraception: Ischaemic stroke and combined oral contraceptives: results of an international, multicentre, case–control study. Lancet. 1996, 348: 498-505.

    Article  Google Scholar 

  17. Kelly DF, Robert DB: Secondary prevention strategies in ischemic stroke: identification and optimal management of modifiable risk factors. Mayo Clin Proc. 2004, 79: 1330-1340. 10.4065/79.10.1330.

    Article  Google Scholar 

  18. Wendel-Vos GC, Schuit AJ, Feskens EJ, Boshuizen HC, Verschuren WM, Saris WH, Kromhout D: Physical activity and stroke. A meta-analysis of observational data. Int J Epidemiol. 2004, 33: 787-798. 10.1093/ije/dyh168.

    Article  CAS  PubMed  Google Scholar 

  19. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, Moher D, Becker BJ, Sipe TA, Thacker SB: For the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) Group. Meta-analysis of observational studies in epidemiology: a proposal for reporting. JAMA. 2000, 283: 2008-2012. 10.1001/jama.283.15.2008.

    Article  CAS  PubMed  Google Scholar 

  20. Hatano S: Experience from a multicentre stroke register: a preliminary report. Bull World Health Organ. 1976, 54: 541-553.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Special report from the national institute of neurological disorders and stroke: classification of cerebrovascular disease III. Stroke. 1990, 21: 637-676.

  22. Stang A: The Newcastle-Ottawa Scale (NOS) for assessing the quality if nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010, 25: 603-605. 10.1007/s10654-010-9491-z.

    Article  PubMed  Google Scholar 

  23. Steichen TJ: Nonparametric trim and fill analysis of publication bias in meta-analysis. Stata Technic Bull (STB). 2001, 57: 8-14.

    Google Scholar 

  24. Shaper AG, Pocock SJ, Walker M, Cohen NM, Wale CJ, Thomson AG: British Regional Heart Study: cardiovascular risk factors in middle-aged men in 24 towns. BMJ. 1981, 283: 179-186. 10.1136/bmj.283.6285.179.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Rexrode KM, Hennekens CH, Willett WC, Colditz GA, Stampfer MJ, Rich-Edwards JW, Speizer FE, Manson JE: A prospective study of body mass index, weight change, and risk of stroke in women. JAMA. 1997, 277: 1539-1545. 10.1001/jama.1997.03540430051032.

    Article  CAS  PubMed  Google Scholar 

  26. Manson JE, Colditz GA, Stampfer MJ, Willett WC, Rosner B, Monson RR, Speizer FE, Hennekens CH: A prospective study of obesity and risk of coronary heart disease in women. N Engl J Med. 1990, 322: 882-889. 10.1056/NEJM199003293221303.

    Article  CAS  PubMed  Google Scholar 

  27. Willett WC, Manson JE, Stampfer MJ, Colditz GA, Rosner B, Speizer FE, Hennekens CH: Weight, weight change, and coronary heart disease in women: risk within the 'normal' weight range. JAMA. 1995, 273: 461-465. 10.1001/jama.1995.03520300035033.

    Article  CAS  PubMed  Google Scholar 

  28. Berger K, Schulte H, Stögbauer F, Assmann G: Incidence and risk factors for stroke in an occupational cohort: the PROCAM Study. Prospective cardiovascular muenster study. Stroke. 1998, 29: 1562-1566. 10.1161/01.STR.29.8.1562.

    Article  CAS  PubMed  Google Scholar 

  29. Assmann G, Schulte H: PROCAM Trial. 1986, Hedingen-Zurich, Switzerland: Panscientia Publishing House

    Google Scholar 

  30. Assmann G, Schulte H, Seedorf U: The Prospective Cardiovascular Munster (PROCAM) Study: prevalence of hyperlipidemia in persons with hypertension and/or diabetes mellitus and the relationship to coronary heart disease. Am Heart J. 1988, 116: 1713-1724. 10.1016/0002-8703(88)90220-7.

    Article  CAS  PubMed  Google Scholar 

  31. Simons LA, McCallum J, Friedlander Y, Simons J: Risk factors for ischemic stroke: Dubbo Study of the elderly. Stroke. 1998, 29: 1341-1346. 10.1161/01.STR.29.7.1341.

    Article  CAS  PubMed  Google Scholar 

  32. Simons LA, McCallum J, Simons J, Powell I, Ruys J, Heller R, Lerba C: The Dubbo Study: an Australian prospective community study of the health of elderly. Aust N Z J Med. 1990, 20: 783-789. 10.1111/j.1445-5994.1990.tb00423.x.

    Article  CAS  PubMed  Google Scholar 

  33. Wong KS: Risk factors for early death in acute ischemic stroke and intracerebral hemorrhage: A prospective hospital-based study in Asia. Asian Acute Stroke Advisory Panel. Stroke. 1999, 30: 2326-2330. 10.1161/01.STR.30.11.2326.

    Article  CAS  PubMed  Google Scholar 

  34. McCarron P, Greenwood R, Elwood P, Shlomo YB, Bayer A, Baker I, Frankel S, Ebrahim S, Murray L, Smith GD: The incidence and aetiology of stroke in the Caerphilly and Speedwell Collaborative Studies II: risk factors for ischaemic stroke. Public Health. 2001, 115: 12-20.

    CAS  PubMed  Google Scholar 

  35. Caerphilly and Speedell Collaborative Group: Caerphilly and speedwell collaborative heart disease studies. J Epidemiol Community Health. 1984, 38: 259-262.

    Article  Google Scholar 

  36. Greenwood R, McCarron P, Elwood P, Shlomo YB, Bayer A, Baker I, Frankel S, Ebrahim S, Murray L, Smith GD: The incidence and aetiology of stroke in the Caerphilly and Speedwell collaborative studies I: Methods and incidence of events. Public Health. 2001, 115: 4-11.

    CAS  PubMed  Google Scholar 

  37. He Y, Chang Q, Huang JY, Jiang Y, Shi QL, Ni B, Zhang L, Zhang F, Wan ZH, Lam T, Li LS: Study on mortality, incidence and risk factors of stroke in a cohort of elderly in Xi'an, China. Zhonghua Liu Xing Bing Xue Za Zhi. 2003, 24: 476-479.

    PubMed  Google Scholar 

  38. Rodgers H, Greenaway J, Davies T, Wood R, Steen N, Thomson R: Risk factors for first-ever stroke in older people in the north East of England: a population-based study. Stroke. 2004, 35: 7-11.

    Article  PubMed  Google Scholar 

  39. Sudlow M, Thomson R, Thwaites B, Rodgers H, Kenny RA: Prevalence of atrial fibrillation and eligibility for anticoagulants in the community. Lancet. 1998, 352: 1167-1671. 10.1016/S0140-6736(98)01401-9.

    Article  CAS  PubMed  Google Scholar 

  40. Song YM, Sung J, Davey Smith G, Ebrahim S: Body mass index and ischemic and hemorrhagic stroke: a prospective study in Korean men. Stroke. 2004, 35: 831-836. 10.1161/01.STR.0000119386.22691.1C.

    Article  PubMed  Google Scholar 

  41. Song YM, Sung J, Lawlor DA, Davey Smith G, Shin Y, Ebrahim S: Blood pressure, haemorrhagic stroke, and ischaemic stroke: the Korean national prospective occupational cohort study. BMJ. 2004, 328: 324-325. 10.1136/bmj.328.7435.324.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Zhang XF1, Attia J, D'Este C, Yu XH: Prevalence and magnitude of classical risk factors for stroke in a cohort of 5092 Chinese steelworkers over 13.5 years of follow-up. Stroke. 2004, 35: 1052-1056. 10.1161/01.STR.0000125305.12859.ff.

    Article  PubMed  Google Scholar 

  43. Wang W, Zhao D, Sun JY, Wang WH, Cheng J, Liu J, Qin LP, Liu S, Wu ZS: Risk factors comparison in Chinese patients developing acute coronary syndrome, ischemic or hemorrhagic stroke: a multi-provincial cohort study. Zhonghua Xin Xue Guan Bing Za Zhi. 2006, 34: 1133-1137.

    PubMed  Google Scholar 

  44. Liu J, Hong Y, D'Agostino RB, Wu Z, Wang W, Sun J, Wilson PW, Kannel WB, Zhao D: Predictive value for the Chinese population of the Framingharn CHD risk assessment tool compared with the Chinese Muhi—Provincial Cohort Study. JAMA. 2004, 29l: 259l-2599l.

    Google Scholar 

  45. Per H, Georg L, Annika R, Wilhelmsen L: Long-term risk factors for stroke: twenty-eight years of follow-up of 7457 middle-aged men in Goteborg, Sweden. Stroke. 2006, 37: 663-667.

    Google Scholar 

  46. Wilhelmsen L, Tibblin G, Werko L: A primary preventive study in Gothenburg, Sweden. Prev Med. 1972, 1: 153-160. 10.1016/0091-7435(72)90082-5.

    Article  CAS  PubMed  Google Scholar 

  47. Janghorbani M, Hu FB, Willett WC, Li TY, Manson JE, Logroscino G, Rexrode KM: Prospective study of type 1 and type 2 diabetes and risk of stroke subtypes: the Nurses' Health Study. Diabetes Care. 2007, 30: 1730-1735. 10.2337/dc06-2363.

    Article  PubMed  Google Scholar 

  48. Pham TM, Fujino Y, Tokui N, Ide R, Kubo T, Shirane K, Mizoue T, Ogimoto I, Yoshimura T: Mortality and risk factors for stroke and its subtypes in a cohort study in Japan. Prev Med. 2007, 44: 526-530. 10.1016/j.ypmed.2007.02.016.

    Article  PubMed  Google Scholar 

  49. Mizoue T, Tokui N, Nishisaka K, Nishisaka S, Ogimoto I, Ikeda M, Yoshimura T: Prospective study on the relation of cigarette smoking with cancer of the liver and stomach in an endemic region. Int J Epidemiol. 2000, 29: 232-237. 10.1093/ije/29.2.232.

    Article  CAS  PubMed  Google Scholar 

  50. Ngoan LT, Mizoue T, Fujino Y, Tokui N, Yoshimura T: Dietary factors and stomach cancer mortality. Br J Cancer. 2002, 87: 37-42. 10.1038/sj.bjc.6600415.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Weikert C, Berger K, Heidemann C, Bergmann MM, Hoffmann K, Klipstein-Grobusch K, Boeing H: Joint effects of risk factors for stroke and transient ischemic attack in a German population: the EPIC Potsdam Study. J Neurol. 2007, 254: 315-321. 10.1007/s00415-006-0358-x.

    Article  PubMed  Google Scholar 

  52. Boeing H, Korfmann A, Bergmann MM: Recruitment procedures of EPIC-Germany. European investigation into cancer and nutrition. Ann Nutr Metab. 1999, 43: 205-215. 10.1159/000012787.

    Article  CAS  PubMed  Google Scholar 

  53. Wang Y, Huang JY, Cao YF, Guo JP, Yang YJ, Yu XH, Shen FY, Wang GQ: Baseline study and analysis on a stroke risk factor-related cohort in Fengxian county of Shanghai. Zhonghua Liu Xing Bing Xue Za Zhi. 2007, 28: 1171-1174.

    PubMed  Google Scholar 

  54. Kubo M, Hata J, Doi Y, Tanizaki Y, Iida M, Kiyohara Y: Secular trends in the incidence of and risk factors for ischemic stroke and its subtypes in Japanese population. Circulation. 2008, 118: 2672-2678. 10.1161/CIRCULATIONAHA.107.743211.

    Article  PubMed  Google Scholar 

  55. Kubo M, Kiyohara Y, Kato I, Tanizaki Y, Arima H, Tanaka K, Nakamura H, Okubo K, Iida M: Trends in the incidence, mortality, and survival rateof cardiovascular disease in a Japanese community: the Hisayama Study. Stroke. 2003, 34: 2349-2354. 10.1161/01.STR.0000090348.52943.A2.

    Article  PubMed  Google Scholar 

  56. Zhang Y, Galloway JM, Welty TK, Wiebers DO, Whisnant JP, Devereux RB, Kizer JR, Howard BV, Cowan LD, Yeh J, Howard WJ, Wang W, Best L, Lee ET: Incidence and risk factors for stroke in American Indians: the Strong Heart Study. Circulation. 2008, 118: 1577-1584. 10.1161/CIRCULATIONAHA.108.772285.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Lee ET, Welty TK, Fabsitz R, Cowan LD, Le NA, Oopik AJ, Cucchiara AJ, Savage PJ, Howard BV: The Strong Heart Study: a study of cardiovasculardisease in American Indians: design and methods. Am J Epidemiol. 1990, 132: 1141-1155.

    CAS  PubMed  Google Scholar 

  58. Howard BV, Welty TK, Fabsitz RR, Cowan LD, Oopik AJ, Le NA, Yeh J, Savage PJ, Lee ET: Risk factors for coronary heart disease in diabetic and nondiabetic Native Americans: the Strong Heart Study. Diabetes. 1992, 41: 4-11. 10.2337/diab.41.2.S4.

    Article  PubMed  Google Scholar 

  59. Cowan LD, Go OT, Howard BV, Devereux RB, Pettitt DJ, Fabsitz RR, Lee ET, Welty TK: Parity, postmenopausal estrogen use, and cardiovascular disease risk factors in American Indian women: the Strong Heart Study. J Women Health. 1997, 6: 441-449. 10.1089/jwh.1997.6.441.

    Article  CAS  Google Scholar 

  60. Howard G, Cushman M, Kissela BM, Kleindorfer DO, McClure LA, Safford MM, Rhodes JD, Soliman EZ, Moy CS, Judd SE, Howard VJ, REasons for Geographic And Racial Differences in Stroke (REGARDS) Investigators: Traditional risk factors as the underlying cause of racial disparities in stroke: lessons from the half-full (empty?) glass. Stroke. 2011, 42: 3369-3375. 10.1161/STROKEAHA.111.625277.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Cushman M, Cantrell RA, McClure LA, Howard G, Prineas RJ, Moy CS, Temple EM, Howard VJ: Estimated 10-year stroke risk by region and race in the United States. Ann Neurol. 2008, 64: 507-513. 10.1002/ana.21493.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Saito I, Iso H, Kokubo Y, Inoue M, Tsugane S: Body mass index, weight change and risk of stroke and stroke subtypes: the Japan Public Health Center-based prospective (JPHC) study. Int J Obes (Lond). 2011, 35: 283-291. 10.1038/ijo.2010.131.

    Article  CAS  Google Scholar 

  63. Mogensen UB, Olsen TS, Andersen KK, Gerds TA: Cause-specific mortality after stroke: relation to age, sex, stroke severity, and risk factors in a 10-year follow-up study. J Stroke Cerebrovasc Dis. 2012, 22: e59-e65.

    Article  PubMed  Google Scholar 

  64. Nakayama H, Jørgensen HS, Raaschou HO, Olsen TS: The influence of age on stroke outcome: The Copenhagen Stroke Study. Stroke. 1994, 25: 808-813. 10.1161/01.STR.25.4.808.

    Article  CAS  PubMed  Google Scholar 

  65. Jørgensen HS, Nakayama H, Raaschou HO, Olsen TS: Effect of blood pressure and diabetes on stroke-in-progression. Lancet. 1994, 344: 156-159. 10.1016/S0140-6736(94)92757-X.

    Article  PubMed  Google Scholar 

  66. Ezzati M, Hoorn SV, Rodgers A, Lopez AD, Mathers CD, Murray CJ, Comparative Risk Assessment Collaborating Group: Estimates of global and regional potential health gains from reducing multiple major risk factors. Lancet. 2003, 362: 271-280. 10.1016/S0140-6736(03)13968-2.

    Article  PubMed  Google Scholar 

  67. Yuan JM, Ross RK, Gao YT, Yu MC: Body weight and mortalit y: a prospective evaluation in a cohort middle-aged men in Shanghai, China. Int J Epidemiol. 1998, 27: 824-832. 10.1093/ije/27.5.824.

    Article  CAS  PubMed  Google Scholar 

  68. Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng L, INTERHEART Study Investigators: Effect of potentially modifi ablerisk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case–control study. Lancet. 2004, 364: 937-952. 10.1016/S0140-6736(04)17018-9.

    Article  PubMed  Google Scholar 

  69. Bharucha NE, Bharucha EP, Bharucha AE, Bhise AV, Schoenberg BS: Case–control study of completed ischemic stroke in the Parsis of Bombay: a population-based study. Neurology. 1988, 38: 490-492. 10.1212/WNL.38.3.490.

    Article  CAS  PubMed  Google Scholar 

  70. Sridharan R: Risk factors for ischemic stroke: a case control analysis. Neuroepidemiology. 1992, 11: 24-30. 10.1159/000110903.

    Article  CAS  PubMed  Google Scholar 

  71. Gorelick PB, Sacco RL, Smith DB, Alberts M, Mustone-Alexander L, Rader D, Ross JL, Raps E, Ozer MN, Brass LM, Malone ME, Goldberg S, Booss J, Hanley DF, Toole JF, Greengold NL, Rhew DC: Prevention of a first stroke: a review of guidelines and a multjdisciplinary consensus statement from the National Stroke Association. JAMA. 1999, 28l: 1112-1120.

    Article  Google Scholar 

  72. Stegmayr B, Asplund K, Kuulasmaa K, Rajakangas AM, Thorvaldsen P, Tuomilehto J: Stroke incidence and mortality correlated to stroke risk factors in the WHO MONICA Project. An ecological study of 18 populations. Stroke. 1997, 28: 1367-1374.

    Article  CAS  PubMed  Google Scholar 

  73. Antikainen RL, Jousilahti P, Vanhanen H, Tuomilehto J: Excess mortality assciated w ith increased pulse pressure among middleaged men and women is explained by high systolic blood pressure. J Hypertens. 2000, 18: 417-423. 10.1097/00004872-200018040-00010.

    Article  CAS  PubMed  Google Scholar 

  74. Kannel WB: Fifty years of Framingham Study contributions to understanding hypertension. J Hum Hypertens. 2000, 14: 83-90. 10.1038/sj.jhh.1000949.

    Article  CAS  PubMed  Google Scholar 

  75. Redón J, Cea-Calvo L, Lozano JV, Martí-Canales JC, Llisterri JL, Aznar J, González-Esteban J, Investigators of the PREV-ICTUS study: Blood pressure and estimated risk of stroke in the elderly population of spain: the prev-ictus study. Stroke. 2007, 38: 1167-1173. 10.1161/01.STR.0000259815.51547.31.

    Article  PubMed  Google Scholar 

  76. Kannel WB: Elevated systolic blood pressure as a cardiovascular risk factor. Am J Cardiol. 2000, 85: 251-255. 10.1016/S0002-9149(99)00635-9.

    Article  CAS  PubMed  Google Scholar 

  77. Wu Y, Zhang L, Yuan X, Wu Y, Yi D: Quantifying links between stroke and risk factors: a study on individual health risk appraisal of stroke in a community of Chongqing. Neurol Sci. 2011, 32: 211-219. 10.1007/s10072-010-0333-2.

    Article  PubMed  Google Scholar 

  78. Rothman K, Keller A: The effect of joint exposure to alcohol and tobacco on risk of cancer of the mouth and pharynx. J Chronic Dis. 1972, 25: 711-716. 10.1016/0021-9681(72)90006-9.

    Article  CAS  PubMed  Google Scholar 

  79. Carallo C, Lucca LF, Ciamei M, Tucci S, De Franceschi MS: Wall shear stress is lower in the carotid artery responsible for a unilateral ischemic stroke. Atherosclerosis. 2006, 185: 108-113. 10.1016/j.atherosclerosis.2005.05.019.

    Article  CAS  PubMed  Google Scholar 

  80. Knuiman MW, Vu HTV: Risk factors for stroke mortality in men and women: the Busselton Study. J Cardiovasc Risk. 1996, 3: 447-452.

    Article  CAS  PubMed  Google Scholar 

  81. Hart RG, Benavente O, McBride R, Pearce LA: Antithrombotic therapy to prevent stroke in patients with atrial fibrillation: a meta-analysis. Ann Intern Med. 1999, 131: 492-501.

    Article  CAS  PubMed  Google Scholar 

  82. Wolf PA, Abbott RD, Kannel WB: Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke. 1991, 22: 983-988. 10.1161/01.STR.22.8.983.

    Article  CAS  PubMed  Google Scholar 

  83. Welin L, Svärdsudd K, Wilhelmsen L, Larsson B, Tibblin G: Analysis of risk factors for stroke in a cohort of men born in 1913. N Engl J Med. 1987, 317: 521-526. 10.1056/NEJM198708273170901.

    Article  CAS  PubMed  Google Scholar 

  84. Wolf PA, D'Agostino RB, Kannel WB, Bonita R, Belanger AJ: Cigarette smoking as a risk factor for stroke. The Framingham Study. JAMA. 1988, 259: 1025-1029. 10.1001/jama.1988.03720070025028.

    Article  CAS  PubMed  Google Scholar 

  85. Shinton R, Beevers G: Meta-analysis of relation between cigarette smoking and stroke. BMJ. 1989, 298: 789-794. 10.1136/bmj.298.6676.789.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Wannamethee SG, Shaper AG, Whincup PH, Walker M: Smoking cessation and the risk of stroke in middle-aged men. JAMA. 1995, 274: 155-160. 10.1001/jama.1995.03530020073035.

    Article  CAS  PubMed  Google Scholar 

  87. Robbins AS, Manson JE, Lee IM, Satterfield S, Hennekens CH: Cigarette smoking and stroke in a cohort of US male physicians. Ann Intern Med. 1994, 120: 458-462. 10.7326/0003-4819-120-6-199403150-00002.

    Article  CAS  PubMed  Google Scholar 

  88. You RX, McNeil JJ, O'Malley HM, Davis SM, Thrift AG, Donnan GA: Risk factors for stroke due to cerebral infarction in young adults. Stroke. 1997, 28: 1913-1918. 10.1161/01.STR.28.10.1913.

    Article  CAS  PubMed  Google Scholar 

  89. Spriggs DA, French JM, Murdy JM, Bates D, James OF: Historical risk factors for stroke: a case control study. Age Ageing. 1990, 19: 280-287. 10.1093/ageing/19.5.280.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

The study was supported by two grants from the Natural Science Foundation of China (No. 81172773 and No. 81202286).

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    Authors and Affiliations

    1. Department of Health Statistics, College of Preventive Medicine, Third Military Medical University, PO Box 400038, Chongqing, China

      Xuetao Chen, Liang Zhou, Yanqi Zhang, Dali Yi, Ling Liu, Yazhou Wu, Dihui Ma, Xiaoyu Liu & Dong Yi

    2. Department of Information, Xinqiao Hospital, Third Military Medical University, Xinqiao Street, Chongqing, 400037, China

      Xuetao Chen

    3. Department of Epidemiology, College of Preventive Medicine, Third Military Medical University, Chongqing, 400038, China

      Wen Rao

    4. Department of Biostatistics, School of Public Health and Community Medicine, University of Washington, Seattle, 98124-6108, USA

      Xiao-Hua Andrew Zhou

    5. Department of Epidemiology, Institute of tropical medicine, Third Military Medical University, Chongqing, 400038, China

      Hui Lin

    6. School of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

      Dixiang Cheng

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    The authors declare that they have no competing interests.

    Authors’ contributions

    XC, LZ and DY conducted the literature search and quality assessment and contributed to the drafting of the manuscript. LL, YZ and YW performed the data extraction and statistical analysis. WR and DM consulted on the statistical analysis. DC, HL and XL critically revised the manuscript drafts. XAZ and DY conceived and designed the review, assisted with the inclusion/exclusion criteria, acted as independent assessors and critically revised the manuscript drafts. All of the authors contributed to the interpretation of the data and critically revised the manuscript. All of the authors are guarantors for this study and have read and approved the final manuscript.

    Xuetao Chen, Liang Zhou contributed equally to this work.

    Electronic supplementary material

    Additional file 1: BMI of Western, Body Mass Index (1. 25.0-25.9 Kg/m 2 , 2. ≥26.0 Kg/m 2 ; Left: Fixed effects model, Right: Random effects model).(DOC 38 KB)

    12889_2014_7280_MOESM2_ESM.doc

    Additional file 2: SBP of Western, Systolic blood pressure (1. 120–129 mm Hg, 2. 130–139 mm Hg, 3. 140-149 mm Hg2. 150-159 mm Hg2. ≥160 mm Hg; Left: Fixed effects model, Right: Random effects model).(DOC 32 KB)

    Additional file 3: Hypertension of Western (Left: Fixed effects model, Right: Random effects model).(DOC 29 KB)

    Additional file 4: Diabetes of Western (Left: Fixed effects model, Right: Random effects model).(DOC 30 KB)

    12889_2014_7280_MOESM5_ESM.doc

    Additional file 5: Cardiac causes of Western (1. Angina, 2. Coronary Heart Disease, 3. Atrial fibrillation, 4. Left ventricular hypertrophy; Left: Fixed effects model, Right: Random effects model).(DOC 28 KB)

    Additional file 6: Cardiac causes -Atrial fibrillation of Western (Left: Fixed effects model, Right: Random effects model).(DOC 28 KB)

    12889_2014_7280_MOESM7_ESM.doc

    Additional file 7: Smoking of Western (1. < 20 Cigarettes/d, 2. =20 Cigarettes/d, 3. > 20 Cigarettes/d; Left: Fixed effects model, Right: Random effects model).(DOC 48 KB)

    Additional file 8: BMI of Asian, Body Mass Index (1. 25.0-25.9 Kg/m 2 , 2. ≥26.0 Kg/m 2 ; Left: Fixed effects model, Right: Random effects model).(DOC 46 KB)

    12889_2014_7280_MOESM9_ESM.doc

    Additional file 9: SBP of Asian, Systolic blood pressure (1. 120–129 mm Hg, 2. 130–139 mm Hg, 3. 140-149 mm Hg2. 150-159 mm Hg2. ≥160 mm Hg; Left: Fixed effects model, Right: Random effects model).(DOC 34 KB)

    Additional file 10: Hypertension of Asian (Left: Fixed effects model, Right: Random effects model).(DOC 32 KB)

    Additional file 11: Diabetes of Asian (Left: Fixed effects model, Right: Random effects model).(DOC 34 KB)

    12889_2014_7280_MOESM12_ESM.doc

    Additional file 12: Cardiac causes of Asian (1. Angina, 2. Coronary Heart Disease, 3. Atrial fibrillation, 4. Left ventricular hypertrophy; Left: Fixed effects model, Right: Random effects model).(DOC 31 KB)

    12889_2014_7280_MOESM13_ESM.doc

    Additional file 13: Cardiac causes -Atrial fibrillation of Asian (Left: Fixed effects model, Right: Random effects model).(DOC 30 KB)

    Additional file 14: Smoking of Asian (Fixed effects model, Right: Random effects model).(DOC 33 KB)

    12889_2014_7280_MOESM15_ESM.doc

    Additional file 15: Alcohol of Asian (*Ischemic stroke, #Hemorrhagic stroke; Left: Fixed effects model, Right: Random effects model).(DOC 32 KB)

    12889_2014_7280_MOESM16_ESM.doc

    Additional file 16: Alcohol of Western (*Ischemic stroke, #Hemorrhagic stroke; Left: Fixed effects model, Right: Random effects model).(DOC 33 KB)

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    Chen, X., Zhou, L., Zhang, Y. et al. Risk Factors of Stroke in Western and Asian Countries: A Systematic Review and Meta-analysis of Prospective Cohort Studies. BMC Public Health 14, 776 (2014). https://doi.org/10.1186/1471-2458-14-776

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    • DOI: https://doi.org/10.1186/1471-2458-14-776

    Keywords

    • Stroke
    • Risk factors
    • Prospective study
    • Epidemiology
    • Systematic review
    • Public health

    BMC Public Health

    ISSN: 1471-2458

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