Migraine and the risk of stroke and heart disease: a Chinese population-based cohort study
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Abstract This study aims to investigate the relationship between migraine and the risk of stroke and heart disease among middle-aged and older adults in China. A total of 8,166 participants aged 45 years or older in the China Health and Retirement Longitudinal Study from 2011 to 2020 were included. The Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between migraine and the incidence of stroke or heart disease. Interaction analyses were performed to identify potential effect modifications. During follow-up period of 9 years, 642 (7.86%) participants experienced a stroke and 1,383 (16.94%) experienced heart disease events. Migraines were positively associated with stroke (HR: 1.70; 95% CI: 1.30–2.22) and heart disease (HR: 1.69; 95% CI: 1.41–2.03). The association between migraines and stroke was more significant in individuals without hypertension (p for interaction = 0.01) or diabetes (p for interaction = 0.02). The association between migraine and heart disease was more significant in older individuals (p for interaction = 0.02). In conclusion, migraine is associated with an increased risk of stroke, particularly among individuals without hypertension or diabetes, and a higher risk of heart disease in older adults.
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Migraine and the risk of stroke and heart disease: a Chinese population-based cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Migraine and the risk of stroke and heart disease: a Chinese population-based cohort study Panpan Zhang, Xia Xie, Yubin Wang, Guogang Luo, Yurong Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6739682/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study aims to investigate the relationship between migraine and the risk of stroke and heart disease among middle-aged and older adults in China. A total of 8,166 participants aged 45 years or older in the China Health and Retirement Longitudinal Study from 2011 to 2020 were included. The Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between migraine and the incidence of stroke or heart disease. Interaction analyses were performed to identify potential effect modifications. During follow-up period of 9 years, 642 (7.86%) participants experienced a stroke and 1,383 (16.94%) experienced heart disease events. Migraines were positively associated with stroke (HR: 1.70; 95% CI: 1.30–2.22) and heart disease (HR: 1.69; 95% CI: 1.41–2.03). The association between migraines and stroke was more significant in individuals without hypertension (p for interaction = 0.01) or diabetes (p for interaction = 0.02). The association between migraine and heart disease was more significant in older individuals (p for interaction = 0.02). In conclusion, migraine is associated with an increased risk of stroke, particularly among individuals without hypertension or diabetes, and a higher risk of heart disease in older adults. Health sciences/Neurology Health sciences/Risk factors migraine stroke heart disease Chinese population Figures Figure 1 Figure 2 Figure 3 Introduction Cardiovascular diseases (CVDs), particularly stroke and heart disease, are the leading causes of mortality and major contributors to disability worldwide [ 1 ]. Due to the control of traditional cardiovascular risk factors, the incidence of stroke and coronary heart disease has gradually declined since 2000, particularly in developed countries [ 2 ]. However, the burden of cardiovascular diseases remains substantial [ 3 , 4 ]. Cardiovascular disease-related expenditures among adults in the United States have increased by more than $ 100 billion over the past two decades [ 3 ]. Therefore, it is imperative to identify new risk factors for CVDs and implement effective prevention and control measures. Recent studies indicate a growing prevalence of comorbidity between migraine and CVDs. Migraine, a neurovascular disorder affecting over one billion people worldwide, has an estimated annual global prevalence of 15% [ 5 ]. It is typically characterized by recurrent moderate-to-severe headaches, often accompanied by nausea, vomiting, photophobia, and phonophobia. Neurological symptoms such as visual or sensory auras may also occur [ 6 , 7 ]. The vascular characteristics of migraines have led to speculation that migraines and CVDs share common pathological pathways [ 8 ]. Furthermore, the pathophysiological features observed in patients with migraines, such as cortical spreading depression, hypercoagulability, endothelial dysfunction, and vasospasm, also support the strong association between migraines and CVD events [ 9 ]. Large-scale epidemiological studies based on Danish and American populations have demonstrated a significant association between migraines and CVDs [ 10 , 11 ]. However, some studies have reported conflicting findings in different populations [ 12 , 13 ]. Recent studies indicated that the prevalence of migraines in China is significantly lower than that in other countries [ 5 ], whereas the prevalence of CVDs has reached or even exceeded that in Western countries [ 14 ]. However, there is currently a lack of large-scale cohort studies investigating the relationship between migraines and the risk of stroke and heart disease in the Chinese population. Therefore, this study aimed to investigate the relationship between migraine and the incidence of stroke and heart disease among middle-aged and older adults in China, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS). Materials and methods Data source and study population This cohort study utilized longitudinal data from five waves (2011, 2013, 2015, 2018, and 2020) of the CHARLS to evaluate the effect of migraines on the incidence of stroke and heart disease. Among 25,762 participants, we screened individuals based on the following exclusion criteria: (1) participants diagnosed with stroke or heart disease at baseline in 2011 or lost to follow-up between 2013 and 2020 (N = 14,471); (2) participants with missing data on migraine at baseline in 2011 (N = 2,846); and (3) participants younger than 45 years (N = 279). Ultimately, 8,166 participants were included in this study. The participant flowchart is shown in Fig. 1 . The CHARLS is a nationally representative survey that targets individuals aged 45 years and older, along with their spouses, and collects extensive health, economic, and household data across China. Ethical approval for the CHARLS was granted by the Biomedical Ethics Review Committee of Peking University for each survey wave, and the fieldwork protocol for the household survey was approved under approval number IRB00001052-11015 [ 15 ]. Primary Variables The exposure variable in this study was migraine, which was diagnosed based on data collected in the 2011 survey. The diagnosis followed the criteria established by the ID Migraine questionnaire [ 15 ]. The ID Migraine questionnaire consists of three items: headache-related disability, nausea, and sensitivity to light. A diagnosis of migraine was made if an individual scored positively on any two of the three items. In the CHARLS questionnaire, the items “currently experiencing stomach pain” and “currently experiencing head pain” correspond to the ID Migraine items “Do you feel nauseated or experience stomach discomfort?” and “Does your headache limit your ability to work, study, or perform necessary activities?” respectively. Therefore, migraine was defined as the presence of both head and stomach pain [ 16 ]. The outcome variables were stroke and heart disease, diagnosed based on follow-up data collected between 2013 and 2020. Following established precedents [ 17 , 18 ], stroke and heart disease occurrence was determined based on self-reports, where individuals confirmed receiving a diagnosis of stroke or heart disease from a physician. The observation period for each participant ended when they were first diagnosed with either stroke or heart disease during follow-up. Covariates selection At baseline, sociodemographic and health-related factors included age, sex, educational attainment (elementary school and below, high school, and college or above), marital status (married or unmarried), and place of residence (rural or urban). Health-related factors included body mass index (BMI), smoking status (categorized as never, former, and current), drinking status (categorized as no alcohol use in the past year, less than once a month, and more than once a month), self-reported sleep duration (including nighttime sleep and napping), and self-reported physician-diagnosed hypertension, diabetes, and dyslipidemia. These data were obtained through standardized questionnaires. Laboratory assessments included measurements of glycated hemoglobin A1c (HbA1c), high-density lipoprotein cholesterol (HDL-C), C-reactive protein (CRP), uric acid (UA), and creatinine (Cr). Statistical analysis Descriptive data on participants’ characteristics are expressed as means and standard errors (SEs) for continuous variables and numbers and weighted percentages for categorical variables. One-way analysis of variance and chi-squared tests were used to compare continuous and categorical variables, respectively. The Cox proportional hazards model was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between migraine and the incidence of stroke or heart disease among middle-aged and older adults in China. Model 1 presented unadjusted results. Variables with a p-value < 0.05 in univariate analysis were included in the multivariate regression model. In Model 2, adjustments were made for baseline sex, education, smoking status, and drinking status. Model 3 was further adjusted for sleep duration at night, sleep duration at noon, HDL-C, UA, and Cr. The Kaplan–Meier method was used to estimate the cumulative incidence of stroke and heart disease. Subgroup analyses were conducted using a fully adjusted model stratified by age, sex, marital status, residence, smoking, drinking, and histories of hypertension and diabetes. All statistical analyses were conducted using the R software (version R-4.1.0; Cary, NC, USA). A two-sided p-value < 0.05 was considered statistically significant. Results Characteristics of the study population This study included 8,166 adults, with a mean age of 57.13 years. Among the participants, 3,981 (48.75%) were women. Of the 8,166 participants, 516 (6.32%) were diagnosed with migraines in 2011, 642 (7.86%) developed new-onset stroke during a mean follow-up period of 8.8 years, and 1,383 (16.94%) developed new-onset heart disease during a mean follow-up period of 8.5 years. Table 1 presents the characteristics of the participants, stratified by migraine status. Compared to non-migraine participants, those with migraines were more likely to be female, have a lower BMI, have lower educational attainment, reside in rural areas, smoke less, drink less, have shorter sleep duration, have lower levels of UA and Cr, and have higher HDL-C levels. However, no significant differences were observed in age, marital status, HbA1c and CRP levels, or the prevalence of hypertension, diabetes, and dyslipidemia. Table 1 Characteristics of study participants by migraine, CHARLS 2011–2020 Characteristic Total (n = 8,166) No Migraine (n = 7,650) Migraine (n = 516) P- value Age, years 57.13 ± 8.59 57.12 ± 8.61 57.27 ± 8.21 0.69 Sex, n (%) < 0.0001 Female 3981(48.75) 3616(47.27) 365(70.74) Male 4185(51.25) 4034(52.73) 151(29.26) Body Mass Index (kg/m 2 ) 23.48 ± 3.71 23.53 ± 3.71 22.83 ± 3.58 < 0.0001 Marital status, n (%) 0.15 Married 7252(90.85) 6810(90.98) 442(88.93) Non-Married 730(9.15) 675(9.02) 55(11.07) Education, n (%) < 0.0001 Elementary school and below 5110(62.58) 4687(61.27) 423(81.98) High school 2884(35.32) 2792(36.50) 92(17.83) College or above 172(2.11) 171(2.24) 1(0.19) Residence, n (%) < 0.0001 Rural 5126(62.77) 4711(61.58) 415(80.43) Urban 3040(37.23) 2939(38.42) 101(19.57) Smoke status, n (%) < 0.0001 Non-smoker 4855(59.45) 4490(58.69) 365(70.74) Ex-smoker 847(10.37) 808(10.56) 39(7.56) smoker 2464(30.17) 2352(30.75) 112(21.71) Drink status, n (%) < 0.0001 No alcohol use in past year 5176(63.38) 4793(62.65) 383(74.22) Less than once a month 734(8.99) 681(8.90) 53(10.27) More than once a month 2256(27.63) 2176(28.44) 80(15.50) Duration of sleep (hours) Sleep duration at night(hours) 6.58 ± 1.76 6.65 ± 1.71 5.61 ± 2.15 < 0.0001 Sleep duration at noon(minutes) 32.39 ± 42.71 32.96 ± 43.00 23.87 ± 37.28 < 0.0001 HbA1c (%) 5.24 ± 0.74 5.23 ± 0.74 5.26 ± 0.84 0.43 HDL-C (mg/dL) 1.32 ± 0.39 1.32 ± 0.39 1.36 ± 0.39 < 0.01 CRP (mg/L) 2.38 ± 6.51 2.40 ± 6.61 2.07 ± 4.77 0.13 UA (mg/dL) 4.45 ± 1.23 4.47 ± 1.24 4.16 ± 1.14 < 0.0001 Cr (mg/dL) 0.77 ± 0.18 0.78 ± 0.18 0.75 ± 0.18 < 0.01 Medical history, n (%) Hypertension 1498(18.34) 1391(18.18) 107(20.74) 0.16 Diabetes 309(3.78) 288(3.76) 21(4.07) 0.82 Dyslipidemia 528(6.47) 494(6.46) 34(6.59) 0.98 Characteristics were expressed as means and standard error (SEs) for continuous variables Associations between migraine and the incidence of stroke or heart disease Table 2 shows a significant positive association between migraine and the incidence of new-onset stroke and heart disease among middle-aged and older adults. The unadjusted HR (95% CI) of stroke with migraine was 1.70 (1.32–2.20) (p < 0.0001). In Model 2, the HR (95% CI) of stroke with migraine was similar after further adjustment for sex, education, smoking, and drinking status (1.75, 1.35–2.28; p < 0.0001). In Model 3, the HR (95% CI) of stroke with migraine was 1.70 (1.30–2.22) (p < 0.0001) after further adjusting for sleep duration at night, sleep duration at noon, HDL, UA, and Cr. Additionally, the unadjusted HR (95% CI) of heart disease with migraine was 1.71 (1.44–2.06) (p < 0.0001). In Models 2 and 3, the HRs of heart disease with migraine were 1.71 (1.43–2.05) (p < 0.0001) and 1.69 (1.41–2.03) (p < 0.0001), respectively. Migraine was associated with a 70% higher risk of stroke and a 69% higher risk of heart disease in middle-aged and older adults. Figure 2 presents the Kaplan–Meier curves for the cumulative incidence of stroke and heart disease stratified by migraine. Compared to non-migraine participants, those with migraines had a higher cumulative risk of stroke and heart disease. Table 2 Associations of migraine with the risk of stroke and heart disease, CHARLS 2011–2020 Variables Cumulative Incidence Model 1 HR (95% CI) p-Value Model 2 HR (95% CI) p-Value Model 3 HR (95% CI) p-Value Stroke Risk Migraine 642/8166(7.86%) No 577/7650(7.54%) Reference Reference Reference Yes 65/516(12.60%) 1.70(1.32,2.20) < 0.0001 1.75(1.35,2.28) < 0.0001 1.70(1.30,2.22) < 0.0001 Heart disease Risk Migraine 1383/8166(16.94%) No 1248/7650(16.31%) Reference Reference Reference Yes 135/516(26.16%) 1.72(1.44,2.06) < 0.0001 1.71(1.43,2.05) < 0.0001 1.69(1.41,2.03) < 0.0001 Model 1: No-adjust Model 2: Model 1 + sex, body mass index, education, smoking status, and drinking status. Model 3: Model 2 + sleep duration at night, sleep duration at noon, HDL-C, UA, and Cr levels. Stratification analysis Stratified analysis was performed by age, sex, marital status, residence, smoking status, drinking status, and history of hypertension and diabetes. As shown in the forest plot (Fig. 3 ) , no interaction effect was observed between migraine and age (p for interaction = 0.52), sex (p for interaction = 0.16), marital status (p for interaction = 0.36), residence (p for interaction = 0.90), smoking status (p for interaction = 0.22), or drinking status (p for interaction = 0.56) on the risk of stroke. Therefore, none of these variables significantly modified the association between migraine and stroke in middle-aged and older adults in China. However, Migraine significantly increased stroke risk in adults without hypertension or diabetes. Significant interaction effects were found between hypertension (p for interaction = 0.01), diabetes (p for interaction = 0.02), and migraines. Additionally, Fig. 3 shows the interaction effect between age and migraine on the risk of heart disease (p for interaction = 0.02), with migraines significantly increasing the risk of heart disease in older adults. Other variables did not significantly alter the association between migraines and heart disease (p for interaction > 0.05). Discussion This cohort study of middle-aged and older adults in China revealed a significant positive association between migraines and stroke risk, particularly among individuals without hypertension or diabetes. Additionally, migraine was significantly associated with an increased risk of heart disease in older adults. This study highlights the importance of migraine prevention in preventing stroke or heart disease, particularly in nontraditional high-risk populations. Our study found that migraine was associated with a 70% increased stroke risk and a 69% increased heart disease risk in middle-aged and older Chinese adults. The association between migraine and CVD is well-established. A previous study suggested that migraine is associated with stroke but not with myocardial infarction [ 12 ]. More recent large-scale cohort studies conducted in Denmark, the United States, and South Korea have consistently demonstrated a strong association between migraine and an increased risk of CVDs, including stroke and heart disease [ 10 , 11 , 19 ]. Two meta-analyses reported a significant association between migraines and ischemic stroke [ 20 , 21 ], while a more recent meta-analysis of 16 cohort studies involving more than one million participants revealed that a history of migraine was significantly associated with a higher risk of both stroke and myocardial infarction [ 22 ]. Most of the aforementioned population studies were conducted in developed countries or regions [ 10 , 11 , 19 ], and the prevalence of migraines varies significantly across regions worldwide [ 5 ]. This variation may be associated with differences in healthcare access, environmental factors, lifestyle, and stress levels. However, large-scale cohort studies from developing countries investigating the relationship between migraines and CVD are lacking. Our study addresses this gap and provides valuable insights into this area. Furthermore, our study revealed notable findings. In middle-aged and older adults in China, migraine significantly increased the risk of stroke, particularly in individuals without traditional vascular risk factors such as hypertension or diabetes. Additionally, we observed no significant differences in the prevalence of hypertension, diabetes, or dyslipidemia between migraine and non-migraine groups, and the frequency of smoking and alcohol consumption was lower among individuals with migraines. These findings appear to contradict those of previous studies that suggested a higher prevalence of cardiovascular risk factors in patients with migraine [ 23 – 25 ], which have been suggested as a nonspecific mechanism of migraine-induced stroke [ 26 ]. Based on these earlier studies, it was hypothesized that the increased cardiovascular risk associated with migraine is primarily attributable to traditional vascular risk factors rather than the migraine itself [ 27 ]. However, our findings align with other studies [ 28 , 29 ], indicating a heightened stroke risk related to migraine in individuals without cardiovascular risk factors. At present, the underlying mechanisms linking migraine and CVDs remain incompletely understood. Some studies have suggested that migraine-specific mechanisms, including reduced cerebral perfusion, vascular spasm, shared genetic mutations, ischemic vulnerability, inflammation, endothelial dysfunction, hypercoagulable states, and poor vascular reactivity, have been proposed to contribute to stroke in patients with migraine [ 26 , 30 ]. Overall, these findings suggest that the association between migraines and stroke is largely independent of traditional cardiovascular risk factors and may be driven by migraine-specific stroke mechanisms. In the present study, no sex differences were observed in the association between migraines and cardiovascular disease, although the prevalence of migraines was higher in women than in men. Since migraines are more prevalent among young and middle-aged women, prior studies have focused on the relationship between migraines and CVD in women [ 27 , 29 , 31 ], with positive results observed. For instance, a large Danish cohort study found a higher CVD risk in women with migraines compared to men [ 11 ], a conclusion supported by other meta-analyses [ 12 , 20 ]. Overall, most studies have consistently demonstrated a stronger association between migraines and the risk of cardiovascular events in women than in men. However, these studies often focused on young women, particularly those under the age of 45. Young women are more likely to use oral contraceptives, which increases the risk of stroke [ 12 , 32 ]. In contrast, the participants in our study were aged 45 years and older, had reached menopause, and were less likely to use contraceptives. These factors may partially explain why we did not observe a stronger association between migraine and stroke or heart disease in women. Further research is required to confirm this hypothesis. This study has several strengths. First, based on the CHARLS survey, the study was a nationally representative cohort study investigating the association between migraine and the incidence of stroke and heart disease among middle-aged and older adults in China, and causality could be determined. Furthermore, the study identified high-risk individuals in whom migraine significantly increased the risk of stroke and heart disease. However, certain limitations must be acknowledged. First, the study included only individuals aged 45 years and older. Future cohort studies focusing on younger Chinese populations are warranted to validate these findings. Second, the migraine questionnaire used in the study may introduce bias, as it did not include questions on light sensitivity. The diagnosis of migraines relied solely on headache-related disability and nausea, potentially underestimating the incidence of migraines. However, the light sensitivity entry exhibited a higher misclassification error (0.22, 95% CI: 0.18–0.27) compared to headache-related disability and nausea [ 33 ]. Third, owing to the limitations of the CHARLS database, subtype analyses for stroke and heart disease were not performed. For instance, stroke was not categorized into hemorrhagic or ischemic subtypes. Therefore, future cohort studies focusing on subtypes of cardiovascular diseases are needed to confirm these findings. Conclusions Migraine increases the risk of stroke in middle-aged and older adults in China, particularly in those without hypertension or diabetes. Additionally, Migraines increase the risk of heart disease in older adults. Further research is required to elucidate the mechanisms underlying these associations. Declarations Acknowledgements We would like to acknowledge Editage (www.editage.cn) for English language editing. Authorship contributions Y.R.Z. and G.G.L. designed the research; P.P.Z. conducted research and wrote the manuscript; P.P.Z. analyzed data; Y.B.W., and X.X.revised the tables and images; Y.R.Z. and G.G.L. provided important revisions for the final content. All authors reviewed and approved the final version of the manuscript. Competing interests The authors declare no competing interests. Funding sources This study was funded by the Key Science and Technology Programme of Shaanxi Province, China (Grant No. 2025SF-YBXM-329), and the Clinical Research Award of the First Affiliated Hospital of Xi’an Jiaotong University (Grant No. XJTU1AF2021CRF-022). Data availability The datasets upholding the outcomes of this study can be accessed through a judicious solicitation to the corresponding author. References Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. 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Circulation 125 , 335-345 (2012). https://doi.org:10.1161/circulationaha.111.045096 Kurth, T. et al. Migraine and risk of cardiovascular disease in women. Jama 296 , 283-291 (2006). https://doi.org:10.1001/jama.296.3.283 Etminan, M., Takkouche, B., Isorna, F. C. & Samii, A. Risk of ischaemic stroke in people with migraine: systematic review and meta-analysis of observational studies. Bmj 330 , 63 (2005). https://doi.org:10.1136/bmj.38302.504063.8F Csépány, É. et al. The validation of the Hungarian version of the ID-migraine questionnaire. J Headache Pain 19 , 106 (2018). https://doi.org:10.1186/s10194-018-0938-z Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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University","correspondingAuthor":false,"prefix":"","firstName":"Xia","middleName":"","lastName":"Xie","suffix":""},{"id":528004497,"identity":"69a34f6f-b977-448e-8e70-4a0d4db4b879","order_by":2,"name":"Yubin Wang","email":"","orcid":"","institution":"The First Affiliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"prefix":"","firstName":"Yubin","middleName":"","lastName":"Wang","suffix":""},{"id":528004498,"identity":"0a02c0dc-35e1-4f1f-8a5a-8e3a2d47a7b7","order_by":3,"name":"Guogang Luo","email":"","orcid":"","institution":"The First Affiliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"prefix":"","firstName":"Guogang","middleName":"","lastName":"Luo","suffix":""},{"id":528004500,"identity":"506595a7-9857-4de2-a643-e5ac69ce580f","order_by":4,"name":"Yurong 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02:43:40","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":107142,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-6739682/v1/fbfddf9430bb00ae2808bc0c.html"},{"id":93543612,"identity":"e4ff079b-cbeb-43a4-b7f2-ea7edda33dfa","added_by":"auto","created_at":"2025-10-15 02:43:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3121846,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of the study\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6739682/v1/e3a12edb8500086903b5b3d4.png"},{"id":93543611,"identity":"d97b1f21-ec42-47c3-bb9b-ba29c04d2e50","added_by":"auto","created_at":"2025-10-15 02:43:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":6012,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative incidence curves of stroke and heart disease in the Chinese population, CHARLS 2011–2020\u003c/p\u003e\n\u003cp\u003e(a) The Kaplan–Meier curves for the cumulative incidence of stroke stratified by migraine from 2011 to2020. (b) The Kaplan–Meier curves for the cumulative incidence of heart disease stratified by migraine from 2011 to2020.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6739682/v1/3a705281214a1f117d3a2b34.png"},{"id":93543617,"identity":"677c5275-3ede-4469-a1fc-f05b71a91d66","added_by":"auto","created_at":"2025-10-15 02:43:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":21765,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis of the association of migraine with incidence of stroke and heart disease, CHARLS 2011–2020\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6739682/v1/7e303c883fcffc3a45a51bad.png"},{"id":96076528,"identity":"a53536ef-fcc4-478a-9f61-f5540b6006db","added_by":"auto","created_at":"2025-11-17 10:39:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3655774,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6739682/v1/1192421b-8535-4349-af5b-a0181877f5a3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Migraine and the risk of stroke and heart disease: a Chinese population-based cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCardiovascular diseases (CVDs), particularly stroke and heart disease, are the leading causes of mortality and major contributors to disability worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Due to the control of traditional cardiovascular risk factors, the incidence of stroke and coronary heart disease has gradually declined since 2000, particularly in developed countries [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, the burden of cardiovascular diseases remains substantial [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Cardiovascular disease-related expenditures among adults in the United States have increased by more than \u003cspan\u003e$\u003c/span\u003e100\u0026nbsp;billion over the past two decades [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Therefore, it is imperative to identify new risk factors for CVDs and implement effective prevention and control measures.\u003c/p\u003e\u003cp\u003eRecent studies indicate a growing prevalence of comorbidity between migraine and CVDs. Migraine, a neurovascular disorder affecting over one billion people worldwide, has an estimated annual global prevalence of 15% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. It is typically characterized by recurrent moderate-to-severe headaches, often accompanied by nausea, vomiting, photophobia, and phonophobia. Neurological symptoms such as visual or sensory auras may also occur [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe vascular characteristics of migraines have led to speculation that migraines and CVDs share common pathological pathways [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Furthermore, the pathophysiological features observed in patients with migraines, such as cortical spreading depression, hypercoagulability, endothelial dysfunction, and vasospasm, also support the strong association between migraines and CVD events [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Large-scale epidemiological studies based on Danish and American populations have demonstrated a significant association between migraines and CVDs [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, some studies have reported conflicting findings in different populations [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Recent studies indicated that the prevalence of migraines in China is significantly lower than that in other countries [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], whereas the prevalence of CVDs has reached or even exceeded that in Western countries [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, there is currently a lack of large-scale cohort studies investigating the relationship between migraines and the risk of stroke and heart disease in the Chinese population.\u003c/p\u003e\u003cp\u003eTherefore, this study aimed to investigate the relationship between migraine and the incidence of stroke and heart disease among middle-aged and older adults in China, utilizing data from the China Health and Retirement Longitudinal Study (CHARLS).\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData source and study population\u003c/h2\u003e\u003cp\u003eThis cohort study utilized longitudinal data from five waves (2011, 2013, 2015, 2018, and 2020) of the CHARLS to evaluate the effect of migraines on the incidence of stroke and heart disease. Among 25,762 participants, we screened individuals based on the following exclusion criteria: (1) participants diagnosed with stroke or heart disease at baseline in 2011 or lost to follow-up between 2013 and 2020 (N\u0026thinsp;=\u0026thinsp;14,471); (2) participants with missing data on migraine at baseline in 2011 (N\u0026thinsp;=\u0026thinsp;2,846); and (3) participants younger than 45 years (N\u0026thinsp;=\u0026thinsp;279). Ultimately, 8,166 participants were included in this study. The participant flowchart is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The CHARLS is a nationally representative survey that targets individuals aged 45 years and older, along with their spouses, and collects extensive health, economic, and household data across China. Ethical approval for the CHARLS was granted by the Biomedical Ethics Review Committee of Peking University for each survey wave, and the fieldwork protocol for the household survey was approved under approval number IRB00001052-11015 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePrimary Variables\u003c/h3\u003e\n\u003cp\u003eThe exposure variable in this study was migraine, which was diagnosed based on data collected in the 2011 survey. The diagnosis followed the criteria established by the ID Migraine questionnaire [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The ID Migraine questionnaire consists of three items: headache-related disability, nausea, and sensitivity to light. A diagnosis of migraine was made if an individual scored positively on any two of the three items. In the CHARLS questionnaire, the items \u0026ldquo;currently experiencing stomach pain\u0026rdquo; and \u0026ldquo;currently experiencing head pain\u0026rdquo; correspond to the ID Migraine items \u0026ldquo;Do you feel nauseated or experience stomach discomfort?\u0026rdquo; and \u0026ldquo;Does your headache limit your ability to work, study, or perform necessary activities?\u0026rdquo; respectively. Therefore, migraine was defined as the presence of both head and stomach pain [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe outcome variables were stroke and heart disease, diagnosed based on follow-up data collected between 2013 and 2020. Following established precedents [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], stroke and heart disease occurrence was determined based on self-reports, where individuals confirmed receiving a diagnosis of stroke or heart disease from a physician. The observation period for each participant ended when they were first diagnosed with either stroke or heart disease during follow-up.\u003c/p\u003e\n\u003ch3\u003eCovariates selection\u003c/h3\u003e\n\u003cp\u003eAt baseline, sociodemographic and health-related factors included age, sex, educational attainment (elementary school and below, high school, and college or above), marital status (married or unmarried), and place of residence (rural or urban). Health-related factors included body mass index (BMI), smoking status (categorized as never, former, and current), drinking status (categorized as no alcohol use in the past year, less than once a month, and more than once a month), self-reported sleep duration (including nighttime sleep and napping), and self-reported physician-diagnosed hypertension, diabetes, and dyslipidemia. These data were obtained through standardized questionnaires. Laboratory assessments included measurements of glycated hemoglobin A1c (HbA1c), high-density lipoprotein cholesterol (HDL-C), C-reactive protein (CRP), uric acid (UA), and creatinine (Cr).\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eDescriptive data on participants\u0026rsquo; characteristics are expressed as means and standard errors (SEs) for continuous variables and numbers and weighted percentages for categorical variables. One-way analysis of variance and chi-squared tests were used to compare continuous and categorical variables, respectively. The Cox proportional hazards model was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between migraine and the incidence of stroke or heart disease among middle-aged and older adults in China. Model 1 presented unadjusted results. Variables with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in univariate analysis were included in the multivariate regression model. In Model 2, adjustments were made for baseline sex, education, smoking status, and drinking status. Model 3 was further adjusted for sleep duration at night, sleep duration at noon, HDL-C, UA, and Cr. The Kaplan\u0026ndash;Meier method was used to estimate the cumulative incidence of stroke and heart disease. Subgroup analyses were conducted using a fully adjusted model stratified by age, sex, marital status, residence, smoking, drinking, and histories of hypertension and diabetes. All statistical analyses were conducted using the R software (version R-4.1.0; Cary, NC, USA). A two-sided p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eCharacteristics of the study population\u003c/h2\u003e\u003cp\u003eThis study included 8,166 adults, with a mean age of 57.13 years. Among the participants, 3,981 (48.75%) were women. Of the 8,166 participants, 516 (6.32%) were diagnosed with migraines in 2011, 642 (7.86%) developed new-onset stroke during a mean follow-up period of 8.8 years, and 1,383 (16.94%) developed new-onset heart disease during a mean follow-up period of 8.5 years.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the characteristics of the participants, stratified by migraine status. Compared to non-migraine participants, those with migraines were more likely to be female, have a lower BMI, have lower educational attainment, reside in rural areas, smoke less, drink less, have shorter sleep duration, have lower levels of UA and Cr, and have higher HDL-C levels. However, no significant differences were observed in age, marital status, HbA1c and CRP levels, or the prevalence of hypertension, diabetes, and dyslipidemia.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of study participants by migraine, CHARLS 2011\u0026ndash;2020\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8,166)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo Migraine (n\u0026thinsp;=\u0026thinsp;7,650)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMigraine\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;516)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57.13\u0026thinsp;\u0026plusmn;\u0026thinsp;8.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57.12\u0026thinsp;\u0026plusmn;\u0026thinsp;8.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57.27\u0026thinsp;\u0026plusmn;\u0026thinsp;8.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3981(48.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3616(47.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e365(70.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4185(51.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4034(52.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e151(29.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody Mass Index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.48\u0026thinsp;\u0026plusmn;\u0026thinsp;3.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.53\u0026thinsp;\u0026plusmn;\u0026thinsp;3.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.83\u0026thinsp;\u0026plusmn;\u0026thinsp;3.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7252(90.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6810(90.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e442(88.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-Married\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e730(9.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e675(9.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55(11.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eElementary school and below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5110(62.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4687(61.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e423(81.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2884(35.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2792(36.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e92(17.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege or above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e172(2.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e171(2.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1(0.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidence, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5126(62.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4711(61.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e415(80.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3040(37.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2939(38.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e101(19.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoke status, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-smoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4855(59.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4490(58.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e365(70.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEx-smoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e847(10.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e808(10.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39(7.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003esmoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2464(30.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2352(30.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e112(21.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrink status, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo alcohol use in past year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5176(63.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4793(62.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e383(74.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than once a month\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e734(8.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e681(8.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53(10.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than once a month\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2256(27.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2176(28.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80(15.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of sleep (hours)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep duration at night(hours)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep duration at noon(minutes)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.39\u0026thinsp;\u0026plusmn;\u0026thinsp;42.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.96\u0026thinsp;\u0026plusmn;\u0026thinsp;43.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.87\u0026thinsp;\u0026plusmn;\u0026thinsp;37.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHbA1c (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDL-C (mg/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP (mg/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.38\u0026thinsp;\u0026plusmn;\u0026thinsp;6.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.40\u0026thinsp;\u0026plusmn;\u0026thinsp;6.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.07\u0026thinsp;\u0026plusmn;\u0026thinsp;4.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUA (mg/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.16\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCr (mg/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedical history, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1498(18.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1391(18.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107(20.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e309(3.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e288(3.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21(4.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDyslipidemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e528(6.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e494(6.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34(6.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eCharacteristics were expressed as means and standard error (SEs) for continuous variables\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAssociations between migraine and the incidence of stroke or heart disease\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows a significant positive association between migraine and the incidence of new-onset stroke and heart disease among middle-aged and older adults. The unadjusted HR (95% CI) of stroke with migraine was 1.70 (1.32\u0026ndash;2.20) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In Model 2, the HR (95% CI) of stroke with migraine was similar after further adjustment for sex, education, smoking, and drinking status (1.75, 1.35\u0026ndash;2.28; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In Model 3, the HR (95% CI) of stroke with migraine was 1.70 (1.30\u0026ndash;2.22) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) after further adjusting for sleep duration at night, sleep duration at noon, HDL, UA, and Cr. Additionally, the unadjusted HR (95% CI) of heart disease with migraine was 1.71 (1.44\u0026ndash;2.06) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In Models 2 and 3, the HRs of heart disease with migraine were 1.71 (1.43\u0026ndash;2.05) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and 1.69 (1.41\u0026ndash;2.03) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), respectively. Migraine was associated with a 70% higher risk of stroke and a 69% higher risk of heart disease in middle-aged and older adults. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the Kaplan\u0026ndash;Meier curves for the cumulative incidence of stroke and heart disease stratified by migraine. Compared to non-migraine participants, those with migraines had a higher cumulative risk of stroke and heart disease.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssociations of migraine with the risk of stroke and heart disease, CHARLS 2011\u0026ndash;2020\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCumulative Incidence\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eModel 3\u003c/p\u003e\u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003ep-Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eStroke Risk\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigraine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e642/8166(7.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e577/7650(7.54%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e65/516(12.60%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.70(1.32,2.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.75(1.35,2.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.70(1.30,2.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eHeart disease Risk\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigraine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1383/8166(16.94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1248/7650(16.31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e135/516(26.16%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.72(1.44,2.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.71(1.43,2.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.69(1.41,2.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel 1: No-adjust\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel 2: Model 1\u0026thinsp;+\u0026thinsp;sex, body mass index, education, smoking status, and drinking status.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel 3: Model 2\u0026thinsp;+\u0026thinsp;sleep duration at night, sleep duration at noon, HDL-C, UA, and Cr levels.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eStratification analysis\u003c/h3\u003e\n\u003cp\u003eStratified analysis was performed by age, sex, marital status, residence, smoking status, drinking status, and history of hypertension and diabetes. As shown in the forest plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e, no interaction effect was observed between migraine and age (p for interaction\u0026thinsp;=\u0026thinsp;0.52), sex (p for interaction\u0026thinsp;=\u0026thinsp;0.16), marital status (p for interaction\u0026thinsp;=\u0026thinsp;0.36), residence (p for interaction\u0026thinsp;=\u0026thinsp;0.90), smoking status (p for interaction\u0026thinsp;=\u0026thinsp;0.22), or drinking status (p for interaction\u0026thinsp;=\u0026thinsp;0.56) on the risk of stroke. Therefore, none of these variables significantly modified the association between migraine and stroke in middle-aged and older adults in China. However, Migraine significantly increased stroke risk in adults without hypertension or diabetes. Significant interaction effects were found between hypertension (p for interaction\u0026thinsp;=\u0026thinsp;0.01), diabetes (p for interaction\u0026thinsp;=\u0026thinsp;0.02), and migraines. Additionally, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the interaction effect between age and migraine on the risk of heart disease (p for interaction\u0026thinsp;=\u0026thinsp;0.02), with migraines significantly increasing the risk of heart disease in older adults. Other variables did not significantly alter the association between migraines and heart disease (p for interaction\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cohort study of middle-aged and older adults in China revealed a significant positive association between migraines and stroke risk, particularly among individuals without hypertension or diabetes. Additionally, migraine was significantly associated with an increased risk of heart disease in older adults. This study highlights the importance of migraine prevention in preventing stroke or heart disease, particularly in nontraditional high-risk populations.\u003c/p\u003e\u003cp\u003eOur study found that migraine was associated with a 70% increased stroke risk and a 69% increased heart disease risk in middle-aged and older Chinese adults. The association between migraine and CVD is well-established. A previous study suggested that migraine is associated with stroke but not with myocardial infarction [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. More recent large-scale cohort studies conducted in Denmark, the United States, and South Korea have consistently demonstrated a strong association between migraine and an increased risk of CVDs, including stroke and heart disease [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Two meta-analyses reported a significant association between migraines and ischemic stroke [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], while a more recent meta-analysis of 16 cohort studies involving more than one million participants revealed that a history of migraine was significantly associated with a higher risk of both stroke and myocardial infarction [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Most of the aforementioned population studies were conducted in developed countries or regions [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and the prevalence of migraines varies significantly across regions worldwide [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This variation may be associated with differences in healthcare access, environmental factors, lifestyle, and stress levels. However, large-scale cohort studies from developing countries investigating the relationship between migraines and CVD are lacking. Our study addresses this gap and provides valuable insights into this area.\u003c/p\u003e\u003cp\u003eFurthermore, our study revealed notable findings. In middle-aged and older adults in China, migraine significantly increased the risk of stroke, particularly in individuals without traditional vascular risk factors such as hypertension or diabetes. Additionally, we observed no significant differences in the prevalence of hypertension, diabetes, or dyslipidemia between migraine and non-migraine groups, and the frequency of smoking and alcohol consumption was lower among individuals with migraines. These findings appear to contradict those of previous studies that suggested a higher prevalence of cardiovascular risk factors in patients with migraine [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], which have been suggested as a nonspecific mechanism of migraine-induced stroke [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Based on these earlier studies, it was hypothesized that the increased cardiovascular risk associated with migraine is primarily attributable to traditional vascular risk factors rather than the migraine itself [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, our findings align with other studies [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], indicating a heightened stroke risk related to migraine in individuals without cardiovascular risk factors. At present, the underlying mechanisms linking migraine and CVDs remain incompletely understood. Some studies have suggested that migraine-specific mechanisms, including reduced cerebral perfusion, vascular spasm, shared genetic mutations, ischemic vulnerability, inflammation, endothelial dysfunction, hypercoagulable states, and poor vascular reactivity, have been proposed to contribute to stroke in patients with migraine [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Overall, these findings suggest that the association between migraines and stroke is largely independent of traditional cardiovascular risk factors and may be driven by migraine-specific stroke mechanisms.\u003c/p\u003e\u003cp\u003eIn the present study, no sex differences were observed in the association between migraines and cardiovascular disease, although the prevalence of migraines was higher in women than in men. Since migraines are more prevalent among young and middle-aged women, prior studies have focused on the relationship between migraines and CVD in women [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], with positive results observed. For instance, a large Danish cohort study found a higher CVD risk in women with migraines compared to men [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], a conclusion supported by other meta-analyses [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Overall, most studies have consistently demonstrated a stronger association between migraines and the risk of cardiovascular events in women than in men. However, these studies often focused on young women, particularly those under the age of 45. Young women are more likely to use oral contraceptives, which increases the risk of stroke [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In contrast, the participants in our study were aged 45 years and older, had reached menopause, and were less likely to use contraceptives. These factors may partially explain why we did not observe a stronger association between migraine and stroke or heart disease in women. Further research is required to confirm this hypothesis.\u003c/p\u003e\u003cp\u003eThis study has several strengths. First, based on the CHARLS survey, the study was a nationally representative cohort study investigating the association between migraine and the incidence of stroke and heart disease among middle-aged and older adults in China, and causality could be determined. Furthermore, the study identified high-risk individuals in whom migraine significantly increased the risk of stroke and heart disease. However, certain limitations must be acknowledged. First, the study included only individuals aged 45 years and older. Future cohort studies focusing on younger Chinese populations are warranted to validate these findings. Second, the migraine questionnaire used in the study may introduce bias, as it did not include questions on light sensitivity. The diagnosis of migraines relied solely on headache-related disability and nausea, potentially underestimating the incidence of migraines. However, the light sensitivity entry exhibited a higher misclassification error (0.22, 95% CI: 0.18\u0026ndash;0.27) compared to headache-related disability and nausea [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Third, owing to the limitations of the CHARLS database, subtype analyses for stroke and heart disease were not performed. For instance, stroke was not categorized into hemorrhagic or ischemic subtypes. Therefore, future cohort studies focusing on subtypes of cardiovascular diseases are needed to confirm these findings.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eMigraine increases the risk of stroke in middle-aged and older adults in China, particularly in those without hypertension or diabetes. Additionally, Migraines increase the risk of heart disease in older adults. Further research is required to elucidate the mechanisms underlying these associations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge Editage (www.editage.cn) for English language editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.R.Z. and G.G.L. designed the research; P.P.Z. conducted research and wrote the manuscript; P.P.Z. analyzed data; Y.B.W., and X.X.revised the tables and images; Y.R.Z. and G.G.L. provided important revisions for the final content. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Key Science and Technology Programme of Shaanxi Province, China (Grant No. 2025SF-YBXM-329), and the Clinical Research Award of the First Affiliated Hospital of Xi\u0026rsquo;an Jiaotong University (Grant No. XJTU1AF2021CRF-022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets upholding the outcomes of this study can be accessed through a judicious solicitation to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGlobal burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. \u003cem\u003eLancet\u003c/em\u003e \u003cstrong\u003e396\u003c/strong\u003e, 1204-1222 (2020). https://doi.org:10.1016/s0140-6736(20)30925-9\u003c/li\u003e\n\u003cli\u003eConrad, N.\u003cem\u003e et al.\u003c/em\u003e Trends in cardiovascular disease incidence among 22 million people in the UK over 20 years: population based study. \u003cem\u003eBmj\u003c/em\u003e \u003cstrong\u003e385\u003c/strong\u003e, e078523 (2024). https://doi.org:10.1136/bmj-2023-078523\u003c/li\u003e\n\u003cli\u003eBirger, M.\u003cem\u003e et al.\u003c/em\u003e Spending on Cardiovascular Disease and Cardiovascular Risk Factors in the United States: 1996 to 2016. \u003cem\u003eCirculation\u003c/em\u003e \u003cstrong\u003e144\u003c/strong\u003e, 271-282 (2021). https://doi.org:10.1161/circulationaha.120.053216\u003c/li\u003e\n\u003cli\u003eGheorghe, A.\u003cem\u003e et al.\u003c/em\u003e The economic burden of cardiovascular disease and hypertension in low- and middle-income countries: a systematic review. \u003cem\u003eBMC Public Health\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 975 (2018). https://doi.org:10.1186/s12889-018-5806-x\u003c/li\u003e\n\u003cli\u003eAshina, M.\u003cem\u003e et al.\u003c/em\u003e Migraine: epidemiology and systems of care. \u003cem\u003eLancet\u003c/em\u003e \u003cstrong\u003e397\u003c/strong\u003e, 1485-1495 (2021). https://doi.org:10.1016/s0140-6736(20)32160-7\u003c/li\u003e\n\u003cli\u003ePietrobon, D. \u0026amp; Moskowitz, M. 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Risk of ischaemic stroke in people with migraine: systematic review and meta-analysis of observational studies. \u003cem\u003eBmj\u003c/em\u003e \u003cstrong\u003e330\u003c/strong\u003e, 63 (2005). https://doi.org:10.1136/bmj.38302.504063.8F\u003c/li\u003e\n\u003cli\u003eCs\u0026eacute;p\u0026aacute;ny, \u0026Eacute;.\u003cem\u003e et al.\u003c/em\u003e The validation of the Hungarian version of the ID-migraine questionnaire. \u003cem\u003eJ Headache Pain\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 106 (2018). https://doi.org:10.1186/s10194-018-0938-z\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"migraine, stroke, heart disease, Chinese population","lastPublishedDoi":"10.21203/rs.3.rs-6739682/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6739682/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study aims to investigate the relationship between migraine and the risk of stroke and heart disease among middle-aged and older adults in China. A total of 8,166 participants aged 45 years or older in the China Health and Retirement Longitudinal Study from 2011 to 2020 were included. The Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between migraine and the incidence of stroke or heart disease. Interaction analyses were performed to identify potential effect modifications. During follow-up period of 9 years, 642 (7.86%) participants experienced a stroke and 1,383 (16.94%) experienced heart disease events. Migraines were positively associated with stroke (HR: 1.70; 95% CI: 1.30\u0026ndash;2.22) and heart disease (HR: 1.69; 95% CI: 1.41\u0026ndash;2.03). The association between migraines and stroke was more significant in individuals without hypertension (p for interaction\u0026thinsp;=\u0026thinsp;0.01) or diabetes (p for interaction\u0026thinsp;=\u0026thinsp;0.02). The association between migraine and heart disease was more significant in older individuals (p for interaction\u0026thinsp;=\u0026thinsp;0.02). In conclusion, migraine is associated with an increased risk of stroke, particularly among individuals without hypertension or diabetes, and a higher risk of heart disease in older adults.\u003c/p\u003e","manuscriptTitle":"Migraine and the risk of stroke and heart disease: a Chinese population-based cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-15 02:43:35","doi":"10.21203/rs.3.rs-6739682/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9d02bd0b-2130-4407-93da-d4babd124eed","owner":[],"postedDate":"October 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56127115,"name":"Health sciences/Neurology"},{"id":56127116,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2025-11-17T10:39:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-15 02:43:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6739682","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6739682","identity":"rs-6739682","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
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