Abstract
Objective:
To further examine a potential link between migraine and vasomotor symptoms as well as hypertension as a cardiovascular disease risk factor, potentially explaining the association in midlife women.
Patients and Methods:
This was a cross-sectional analysis from the Data Registry on the Experiences of Aging, Menopause and Sexuality (DREAMS) using questionnaire data from women aged 45-60 years seen in women’s clinics at a tertiary care center from May 15, 2015 through January 31, 2022. History of migraine was self-reported; menopause symptoms were assessed with the Menopause Rating Scale. Associations between migraine and vasomotor symptoms were evaluated utilizing multivariable logistic regression models adjusting for multiple factors.
Results:
Of 5,708 women included in the analysis, 1354 (23.7%) reported a migraine history. Women were of mean age 52.8 years, white (90.8%), and postmenopausal (58.7%). In adjusted analysis, women with migraine were significantly more likely to have severe/very severe hot flashes versus no hot flashes, OR 1.34 (95% CI 1.08-1.66; p=0.007), compared to women without migraine. Migraine was associated with a diagnosis of hypertension in adjusted analysis, OR 1.31 (95% CI 1.11-1.55; p=0.002).
Conclusions:
This large cross-sectional study confirms an association between migraine and vasomotor symptoms. Migraine also was associated with hypertension, potentially providing a link with cardiovascular disease risk. Given the high prevalence of migraine in women, this association may help identify those at risk for more severe menopause symptoms.
Keywords: Migraine, vasomotor symptoms, hot flash, menopause, cardiovascular disease risk
Introduction
Migraine is a common disorder with a 2-3 fold female preponderance, affecting approximately 20% of women.1 In addition to the sex-associated differences in migraine prevalence rates, there are also differences in disease characteristics, with women experiencing more migraine-related symptoms and disability compared to men.2 Migraine has been linked with hypertensive disorders of pregnancy3 and with incident hypertension in menopausal women,4 suggesting a propensity for vascular dysregulation in migraineurs. In addition, migraine has also been associated with angina, a greater risk of cardiovascular events and mortality in women.5-8
Vasomotor symptoms (VMS) are a hallmark symptom of menopause and are experienced by a majority of women during the menopause transition. The mean duration of VMS is 7-9 years, and these symptoms can be frequent and severe for many women.9,10 Like migraine, VMS also appear to be a predictor of cardiovascular disease (CVD) risk and are associated with CVD risk factors including hypertension.11 Women with more severe VMS have been noted to be at a greater risk for hypertension and CVD. While the mechanisms mediating hypertension and CVD risk are incompletely understood in women with VMS, vascular and autonomic dysregulation may play potential roles.12,13
To date, the exact physiologic mechanisms linking migraine and VMS individually to CVD remain unclear. It is also uncertain whether these female specific (VMS) and female predominant (migraine) CVD risk factors are themselves related. One prior study utilizing the Study of Women’s Health Across the Nation cohort investigated the association between migraine and longitudinally assessed VMS during the menopause transition. Investigators found that a self-reported history of migraine predicted an increased frequency of VMS in women during the menopause transition.14 Given the paucity of data, the primary objective of the current study was to further examine a potential link between a history of migraine and VMS. Given that vascular dysregulation has been linked with both migraine and VMS, our secondary objective was to assess whether the association between migraine and VMS altered the risk of hypertension in midlife women. The study of these associations has the potential to help clarify the complex relationships between migraine, VMS, hypertension, and ultimately, CVD in postmenopausal women.
Methods
Study design and participants
This was a cross-sectional analysis from the Data Registry on the Experiences of Aging, Menopause and Sexuality (DREAMS). Midlife women presenting for menopause and sexual health consultations to women’s clinics at Mayo Clinic in Rochester, Minnesota; Scottsdale, Arizona; and Jacksonville, Florida completed questionnaires that assessed various aspects of their health, including medical history and menopause symptoms. For the current study, data from women aged 45-60 years who were evaluated between May 15, 2015 and January 31, 2022, were included. The study was approved by the Mayo Clinic Institutional Review Board.
Measures
Migraine
History of migraine was obtained by self-report (single question; yes/no response) at the time of the visit.
Vasomotor symptoms
These were assessed using the Menopause Rating Scale (MRS). The MRS is a validated questionnaire consisting of 11 items including somatic, psychological, and urogenital domain scales. Somatic symptoms include hot flashes, heart discomfort, sleep problems, physical and mental exhaustion, and joint/muscular discomfort. The psychological symptom domain includes depressive mood, irritability, and anxiety. The urogenital symptom domain includes sexual problems, bladder problems, and dryness of the vagina. Each item is scored on a scale from 0 to 4 for severity (0 = none; 1 = mild; 2 = moderate; 3 = severe; 4 = very severe). The higher the composite score, the greater the menopausal symptom burden.15
Mood
The Patient Health Questionnaire-9 (PHQ-9) is a validated 9-question screen that assesses the presence and severity of depression. Results of the PHQ-9 can be used to make a depression diagnosis based on DSM-IV criteria.16 A score of ≥ 5 was considered indicative of depression in this study.
Anxiety
The Generalized Anxiety Disorder 7 (GAD-7) is a validated 7-question screen that assesses the presence and severity of anxiety.17 A score of ≥ 5 was considered indicative of anxiety in this study.
Covariates
Additional information including age, body mass index (BMI), race/ethnicity, education, employment status, partner status (married/partnered vs other), current menopausal hormone therapy (HT) use, and smoking status were gathered from the intake form completed prior to the clinic visit. Menopause status was determined by patient report or provider documentation at the time of the clinical visit (premenopause-having regular periods; perimenopause-changes in periods but have not gone 12 months in a row without a period). A diagnosis of low back pain in the preceding year was used to test the specificity of the association of migraine and VMS. This was done to rule out the possibility of a nonspecific association between other pain disorders and VMS. The high prevalence of low back pain in the population made it a suitable candidate to study this association. The International Classification of Diseases 9 and 10 codes were used to determine diagnoses of low back pain in the preceding year and diagnosis of hypertension any time prior to visit. (Supplemental Table)
Data analyses
Descriptive statistics are reported as median (interquartile range, IQR) or mean (standard deviation, SD) for continuous data, and frequencies and percentages for categorical data. Patient and clinical characteristics were compared for those with and without a history of migraine using a t-test or Wilcoxon rank sum test for continuous data, and a Chi-square or Fisher’s exact tests for categorical data. Associations between migraine history (Yes/No) and hot flash severity (severe/very severe vs none, moderate vs none, and mild vs none) were evaluated utilizing univariate and multivariable logistic regression. The multivariable model was adjusted for BMI, menopause status, depression, anxiety, smoking status, current use of menopausal HT, and if their visit was during the COVID-19 pandemic. These variables were determined a priori. Univariate and multivariable logistic regression were also used to assess associations with hypertension. For this analysis, the interaction between history of migraine and hot flash severity was assessed to determine if these factors associate independently with hypertension, or whether the risk is modified in women with both a history of migraine and VMS. We also assessed all two-way interactions between variables included in the multivariable models and found no significant interactions (data not shown). All tests were two-sided, and p-values ≤0.05 were considered statistically significant. All analyses were performed using SAS version 9.4 software (SAS Institute, Inc.; Cary, NC).
Results
A total of 5,708 women were included in the analysis, 1,354 (24%) of whom reported a history of migraine. Women were of mean age 52.8 years, white (91%), educated (86% with at least some college), employed (70%), partnered (84%) and postmenopausal (59%). Women with a migraine history were more likely have obesity (29%), anxiety (36%) and depression (44%) compared to the women without the history (23%, 30% and 32 % respectively) There were no differences in tobacco use rates between women with and without migraine history (Table 1).
Table 1:
Participant demographics and characteristics
| History of Migraine | ||||
|---|---|---|---|---|
| No (N=4354) |
Yes (N=1354) |
Total (N=5708) |
p value | |
| Age, Mean (SD) | 52.9 (3.9) | 52.3 (4.0) | 52.8 (4.0) | <.001 |
| Race | .039 | |||
| White | 3955 (90.8%) | 1229 (90.8%) | 5184 (90.8%) | |
| American Indian/Alaskan Native | 18 (0.4%) | 10 (0.7%) | 28 (0.5%) | |
| Asian | 105 (2.4%) | 16 (1.2%) | 121 (2.1%) | |
| Black or African American | 90 (2.1%) | 28 (2.1%) | 118 (2.1%) | |
| Native Hawaiian/Pacific Islander | 7 (0.2%) | 1 (0.1%) | 8 (0.1%) | |
| Other | 66 (1.5%) | 29 (2.1%) | 95 (1.7%) | |
| Unknown | 113 (2.6%) | 41 (3.0%) | 154 (2.7%) | |
| Menopause status | .050 | |||
| Premenopause | 220 (5.1%) | 62 (4.6%) | 282 (4.9%) | |
| Perimenopause | 816 (18.7%) | 267 (19.7%) | 1083 (19.0%) | |
| Postmenopause | 2592 (59.5%) | 756 (55.8%) | 3348 (58.7%) | |
| Unknown | 147 (3.4%) | 56 (4.1%) | 203 (3.6%) | |
| Missing | 579 (13.3%) | 213 (15.7%) | 792 (13.9%) | |
| BMI | <.001 | |||
| Missing | 128 (2.9%) | 38 (2.8%) | 166 (2.9%) | |
| Normal | 1993 (45.8%) | 526 (38.8%) | 2519 (44.1%) | |
| Overweight | 1254 (28.8%) | 412 (30.4%) | 1666 (29.2%) | |
| Obese | 979 (22.4%) | 378 (27.9%) | 1357 (23.8%) | |
| Partner Status | .33 | |||
| Married | 3625 (83.3%) | 1101 (81.3%) | 4726 (82.8%) | |
| Life Partner | 33 (0.8%) | 10 (0.7%) | 43 (0.8%) | |
| Single | 324 (7.4%) | 120 (8.9%) | 444 (7.8%) | |
| Widowed | 43 (1.0%) | 8 (0.6%) | 51 (0.9%) | |
| Separated | 23 (0.5%) | 10 (0.7%) | 33 (0.6%) | |
| Divorced | 285 (6.5%) | 96 (7.1%) | 381 (6.7%) | |
| Unknown | 21 (0.5%) | 9 (0.7%) | 30 (0.5%) | |
| Education | <.001 | |||
| High School graduate/GED or less | 283 (6.5%) | 78 (5.8%) | 361 (6.3%) | |
| Some College or 2-year degree | 994 (22.8%) | 386 (28.5%) | 1380 (24.2%) | |
| 4-year college graduate | 1511 (34.7%) | 382 (28.2%) | 1893 (33.2%) | |
| Post graduate studies | 1244 (28.6%) | 401 (29.6%) | 1645 (28.8%) | |
| Missing | 322 (7.4%) | 107 (7.9%) | 429 (7.5%) | |
| Employment Status | .060 | |||
| Missing | 1294 | 394 | 1688 | |
| Employed | 2160 (70.6%) | 647 (67.4%) | 2807 (69.8%) | |
| Other | 900 (29.4%) | 313 (32.6%) | 1213 (30.2%) | |
| Smoking Status | .048 | |||
| Current Smoker | 140 (3.2%) | 57 (4.2%) | 197 (3.5%) | |
| Former Smoker | 512 (11.8%) | 163 (12.0%) | 675 (11.8%) | |
| Never smoked | 2357 (54.1%) | 762 (56.3%) | 3119 (54.6%) | |
| Missing | 1345 (30.9%) | 372 (27.5%) | 1717 (30.1%) | |
| Systemic Hormone Therapy | 699 (16.1%) | 229 (16.9%) | 928 (16.3%) | .45 |
| GAD-7 | <.001 | |||
| <5 | 2402 (55.2%) | 705 (52.1%) | 3107 (54.4%) | |
| ≥5 | 1310 (30.1%) | 489 (36.1%) | 1799 (31.5%) | |
| Missing | 642 (14.7%) | 160 (11.8%) | 802 (14.1%) | |
| PHQ-9 | <.001 | |||
| <5 | 2128 (48.9%) | 584 (43.1%) | 2712 (47.5%) | |
| ≥5 | 1395 (32.0%) | 593 (43.8%) | 1988 (34.8%) | |
| Missing | 831 (19.1%) | 177 (13.1%) | 1008 (17.7%) | |
| Seen during COVID-19 pandemic | 1940 (44.6%) | 451 (33.3%) | 2391 (41.9%) | <.001 |
| MRS - Hot flashes | <.001 | |||
| None | 914 (21.0%) | 230 (17.0%) | 1144 (20.0%) | |
| Mild | 1342 (30.8%) | 404 (29.8%) | 1746 (30.6%) | |
| Moderate | 1222 (28.1%) | 387 (28.6%) | 1609 (28.2%) | |
| Severe | 619 (14.2%) | 208 (15.4%) | 827 (14.5%) | |
| Very Severe | 257 (5.9%) | 125 (9.2%) | 382 (6.7%) | |
| MRS - Psychological Symptoms, Median (IQR) | 3 (0, 6) | 4 (1, 7) | 3 (0, 6) | <.001 |
| MRS - Somatic Symptoms, Median (IQR) | 4 (1, 7) | 5 (2, 8) | 4 (1, 7) | <.001 |
| MRS - Urogenital Symptoms, Median (IQR) | 4 (2, 6) | 4 (2, 7) | 4 (2, 6) | <.001 |
| MRS Total, Median (IQR) | 11 (6, 17) | 14 (8, 20) | 12 (6, 18) | <.001 |
| History of Hypertension (ICD codes) | 622 (14.3%) | 258 (19.1%) | 880 (15.4%) | <.001 |
BMI-body mass index; GAD-7-Generalized Anxiety Disorder questionnaire; GED-General Educational Development; IQR-interquartile range; MRS-Menopause Rating Scale; PHQ-9-Patient Health Questionnaire; SD-standard deviation
In analyses adjusted for menopause status, BMI, smoking status, systemic hormone therapy use, anxiety, depression and timing of assessment with respect to the COVID-19 pandemic, women with a history of migraine were more likely to have severe/very severe hot flashes versus no hot flashes, OR 1.34 (95% CI 1.08-1.66; p=0.007), compared to women without migraine history (Table 2). Of note, women with low back pain were more likely to report a migraine history but were no more likely to have severe/very severe hot flashes than those without back pain (p=0.16), supporting the specificity of the link between VMS and migraine (data not shown).
Table 2:
Logistic regression models for the outcome of hot flash severity
| Univariate Analyses | ||||||
|---|---|---|---|---|---|---|
| Severe/Very Severe vs No Hot Flashes |
Moderate vs No Hot Flashes |
Mild vs No Hot Flashes |
||||
| Odds Ratio (95% CI) |
p- value |
Odds Ratio (95% CI) |
p- value |
Odds Ratio (95% CI) |
p- value |
|
| Menopause Status | <.001 | <.001 | <.001 | |||
| Premenopause | Reference | Reference | Reference | |||
| Perimenopause | 5.62 (3.47-9.11) | <.001 | 4.28 (2.95-6.20) | <.001 | 3.22 (2.31-4.48) | <.001 |
| Postmenopause | 5.50 (3.51-8.63) | <.001 | 3.07 (2.19-4.30) | <.001 | 2.08 (1.55-2.79) | <.001 |
| Unknown | 10.86 (5.73-20.57) | <.001 | 5.88 (3.37-10.26) | <.001 | 2.99 (1.74-5.16) | <.001 |
| Missing | 6.84 (4.19-11.18) | <.001 | 4.02 (2.73-5.90) | <.001 | 2.40 (1.69-3.40) | <.001 |
| BMI | <.001 | <.001 | <.001 | |||
| Normal | Reference | Reference | Reference | |||
| Overweight | 1.80 (1.47-2.20) | <.001 | 1.44 (1.20-1.73) | <.001 | 1.41 (1.18-1.69) | <.001 |
| Obese | 2.74 (2.23-3.36) | <.001 | 1.36 (1.12-1.67) | .002 | 1.28 (1.05-1.55) | .016 |
| Smoking Status | <.001 | .016 | .80 | |||
| Never Smoked | Reference | Reference | Reference | |||
| Former Smoker | 1.29 (0.99-1.67) | .056 | 1.23 (0.96-1.57) | .10 | 1.02 (0.80-1.31) | .85 |
| Current Smoker | 2.74 (1.71-4.40) | <.001 | 1.95 (1.21-3.13) | .006 | 1.08 (0.65-1.79) | .76 |
| Unknown | 1.09 (0.91-1.31) | .35 | 1.09 (0.91-1.29) | .35 | 0.93 (0.79-1.10) | .40 |
| Systemic Hormone Therapy (Y vs N) | 0.44 (0.35-0.56) | <.001 | 0.60 (0.49-0.73) | <.001 | 0.93 (0.77-1.11) | .41 |
| GAD-7 (≥ 5 vs < 5) | 2.13 (1.77-2.56) | <.001 | 1.54 (1.29-1.83) | <.001 | 1.31 (1.10-1.56) | .002 |
| PHQ-9 (≥ 5 vs < 5) | 3.08 (2.55-3.71) | <.001 | 1.66 (1.40-1.98) | <.001 | 1.30 (1.09-1.55) | .003 |
| Seen During COVID-19 Pandemic | 0.84 (0.72-0.99) | .043 | 0.91 (0.78-1.06) | .22 | 0.85 (0.73-0.99) | .031 |
| History of Migraine (Y vs N) | 1.51 (1.25-1.83) | <.001 | 1.26 (1.05-1.51) | .015 | 1.20 (1.00-1.44) | .054 |
| Multivariable Analyses | ||||||
| Severe/Very Severe vs No Hot Flashes |
Moderate vs No Hot Flashes |
Mild vs No Hot Flashes |
||||
| Odds Ratio (95% CI) |
p- value |
Odds Ratio (95% CI) |
p- value |
Odds Ratio (95% CI) |
p- value |
|
| Menopause Status | <.001 | <.001 | <.001 | |||
| Premenopause | Reference | Reference | Reference | |||
| Perimenopause | 5.74 (3.44-9.55) | <.001 | 4.63 (3.13-6.83) | <.001 | 3.02 (2.15-4.23) | <.001 |
| Postmenopause | 6.07 (3.77-9.76) | <.001 | 3.61 (2.52-5.15) | <.001 | 2.01 (1.48-2.73) | <.001 |
| Unknown | 10.34 (5.22-20.49) | <.001 | 6.56 (3.65-11.79) | <.001 | 2.75 (1.56-4.82) | <.001 |
| Missing | 6.20 (3.69-10.42) | <.001 | 4.26 (2.84-6.38) | <.001 | 2.27 (1.59-3.25) | <.001 |
| BMI | <.001 | .005 | .002 | |||
| Normal | Reference | Reference | Reference | |||
| Overweight | 1.65 (1.33-2.04) | <.001 | 1.35 (1.12-1.63) | .002 | 1.38 (1.15-1.66) | <.001 |
| Obese | 2.27 (1.82-2.83) | <.001 | 1.22 (0.99-1.50) | .066 | 1.22 (1.00-1.50) | .054 |
| Smoking Status | .029 | .13 | .98 | |||
| Never Smoked | Reference | Reference | Reference | |||
| Former Smoker | 1.05 (0.79-1.40) | .75 | 1.14 (0.88-1.47) | .33 | 1.00 (0.78-1.29) | .99 |
| Current Smoker | 2.14 (1.28-3.59) | .004 | 1.73 (1.06-2.84) | .029 | 1.04 (0.62-1.76) | .87 |
| Unknown | 1.14 (0.93-1.41) | .21 | 1.09 (0.91-1.32) | .35 | 0.97 (0.80-1.16) | .71 |
| Systemic Hormone Therapy (Y vs N) | 0.41 (0.31-0.53) | <.001 | 0.54 (0.43-0.67) | <.001 | 0.93 (0.76-1.14) | .50 |
| GAD-7 (≥ 5 vs < 5) | 1.39 (1.12-1.74) | .003 | 1.31 (1.07-1.60) | .010 | 1.23 (1.01-1.51) | .04 |
| PHQ-9 (≥ 5 vs < 5) | 2.43 (1.95-3.03) | <.001 | 1.39 (1.13-1.71) | .002 | 1.13 (0.93-1.39) | .23 |
| Seen During COVID-19 Pandemic | 0.92 (0.75-1.13) | .43 | 1.02 (0.85-1.22) | .84 | 0.87 (0.73-1.04) | .13 |
| History of Migraine (Y vs N) | 1.34 (1.08-1.66) | .007 | 1.17 (0.97-1.43) | .11 | 1.16 (0.96-1.40) | .13 |
BMI-body mass index; GAD-7-Generalized Anxiety Disorder questionnaire; PHQ-9-Patient Health Questionnaire
Migraine was associated with hypertension in both the univariate [OR 1.41 (95% CI 1.20-1.66); p<0.001] and multivariable models [OR 1.31 (95% CI 1.11-1.55; p=0.002)] (Table 3). In terms of a link between hot flashes and hypertension, women with severe and very severe hot flashes were more likely to have hypertension than those without hot flashes on univariate analysis [OR 1.51 (95% CI 1.18-1.92) and OR=1.69 (95% CI 1.25-2.28), respectively]. However, on multivariable analysis there was no significant association between hypertension and hot flash severity (p=0.37). Notably, similar patterns of an increased odds of hypertension with increasing hot flash severity were noted in women with and without migraine history (Figure) suggesting that there is no interaction between hot flash severity and migraine history for the outcome of a diagnosis of hypertension, and they can be viewed as being independently associated with hypertension (interaction p=0.94).
Table 3:
Logistic regression models for the outcome of hypertension
| Univariate | Multivariable | |||
|---|---|---|---|---|
| Odds Ratio (95% CI) |
p- value |
Odds Ratio (95% CI) |
p- value |
|
| Menopause Status | ||||
| Premenopause | Reference | Reference | ||
| Perimenopause | 1.43 (0.92-2.22) | .12 | 1.32 (0.84-2.07) | .24 |
| Postmenopause | 1.98 (1.31-2.99) | .001 | 1.82 (1.19-2.79) | .006 |
| Unknown | 1.78 (1.02-3.09) | .043 | 1.57 (0.88 −2.80) | .13 |
| Missing | 1.86 (1.19-2.91) | .006 | 1.55 (0.98-2.45) | .061 |
| BMI | ||||
| Normal | Reference | Reference | ||
| Overweight | 1.86 (1.55-2.24) | <.001 | 1.79 (1.48-2.16) | <.001 |
| Obese | 3.35 (2.80-4.02) | <.001 | 3.21 (2.67-3.87) | <.001 |
| Smoking Status | ||||
| Never Smoked | Reference | Reference | ||
| Former Smoker | 1.19 (0.96-1.47) | .11 | 1.10 (0.88-1.37) | .42 |
| Current Smoker | 1.34 (0.93-1.91) | .11 | 1.23 (0.85-1.78) | .27 |
| Unknown | 0.66 (0.55-0.79) | <.001 | 0.69 (0.57-0.83) | <.001 |
| Systemic Hormone Therapy (Y vs N) | 0.87 (0.71-1.06) | .16 | 0.88 (0.71-1.10) | .25 |
| GAD-7 (≥ 5 vs < 5) | 1.12 (0.95-1.32) | .17 | 1.12 (0.93-1.35) | .24 |
| PHQ-9 (≥ 5 vs < 5) | 1.15 (.98-1.35) | .088 | 0.91 (0.75-1.10) | .32 |
| Seen During COVID-19 pandemic | 0.91 (0.78-1.05) | .19 | 1.00 (0.84-1.19) | .99 |
| History of Migraine (Y vs N) | 1.41 (1.20-1.66) | <.001 | 1.31 (1.11-1.55) | .002 |
| Hot flashes | <.001a | .37a | ||
| None | Reference | Reference | ||
| Mild | 1.19 (0.96-1.47) | .12 | 1.11 (0.89-1.39) | .35 |
| Moderate | 1.10 (0.88-1.37) | .41 | 0.99 (0.78-1.25) | .92 |
| Severe | 1.51 (1.18-1.92) | .001 | 1.19 (0.91-1.54) | .20 |
| Very Severe | 1.69 (1.25-2.28) | <.001 | 1.24 (0.90-1.71) | .19 |
p-value from joint test of hot flash severity
BMI-body mass index; GAD-7-Generalized Anxiety Disorder questionnaire; PHQ-9-Patient Health Questionnaire
Figure: Adjusted association between hypertension and the combination of history of migraine and hot flash severity from multivariable logistic regression.
Odds ratios have been adjusted for menopause status, body mass index, smoking status, systemic hormone therapy, anxiety, depression, and if they were seen during the COVID-19 pandemic.
HTN- hypertension
Discussion
This large cross-sectional study demonstrated a significant association between a self-reported history of migraine and VMS severity. Migraine history also was associated with a diagnosis of hypertension, a well-established risk factor for CVD. There was no association between VMS and low back pain, another pain disorder, which supports the specificity of the relationship between VMS and migraine. These findings are consistent with the single prior study investigating the association of migraine and VMS which showed that migraine predicted an increased frequency of VMS.14
In the present study, nearly a quarter (23.7%) of the cohort of midlife women reported a migraine history. This is in line with the lifetime prevalence rates of migraine in women.1,18 Consistent with existing evidence, women with a migraine history were more likely to have obesity, anxiety and depressive symptoms than women without such history.19-21
Data linking VMS and migraine independently to CVD risk in women are robust,11,22-25 but the mechanisms responsible for these links are less certain. In the Study of Women’s Health Across the Nation (SWAN), midlife women with VMS were found to be more likely to develop hypertension compared to women without VMS.11 They were also shown to have more subclinical CVD with poorer flow-mediated dilatation and endothelial function as well as greater aortic calcification and intima media thickness than women without hot flashes.23-25 Studies have investigated whether timing of onset or frequency of VMS predict future CVD risk. In the Women’s Health Initiative Observational Study, late occurring VMS rather than early onset VMS were associated with increased coronary heart disease risk and all-cause mortality.26 In the Women’s Ischemic Syndrome Evaluation Study (WISE), women with VMS starting early in midlife had reduced endothelial function and higher CVD mortality compared with women with later onset of VMS.27 In contrast, the SWAN study, which collected VMS reports longitudinally over more than two decades rather than at a single point in time, found that frequent VMS either early in the transition or occurring persistently across the transition were associated with incident CVD.22
The current study showed that midlife women with a history of migraine were more likely to have hypertension, a well-established risk factor for CVD. The finding of an association between migraine and hypertension is consistent with two recent, large prospective studies. A report from the Women’s Health Study that involved over 29,000 middle aged and older women showed that any history of migraine conveyed a 16% increased relative risk of incident hypertension when compared to women without a history of migraine.28 The risk was higher (30% increased risk) in those women reporting a frequency of migraine attacks of at least weekly. Similarly, a large Finnish prospective cohort study involving over 13,000 working-age individuals without hypertension found that a self-reported history of migraine predicted incident hypertension with an odds ratio of 1.4.29 Similarly, it has been suggested that migraine be considered a risk factor for most cardiovascular diseases given a higher incidence of vascular disease in migraineurs.30 There is an increased risk of stroke in women who experience migraine with and without aura, with greater risk in women under age 45 years, in those who smoke and in those who use hormonal contraception.31
It remains uncertain how migraine and vascular disease, and specifically hypertension, are linked. While shared genetic markers could explain the association between migraine and hypertension given that both are associated with family histories of these conditions, no specific common genetic markers linking the two have been identified to date. This is despite the identification of multiple single-nucleotide polymorphism loci that are strongly associated with migraine and also linked with vascular mechanisms.32 Another possibility is that migraine and hypertension share some common pathophysiologic mechanism(s) such as endothelial dysfunction, autonomic dysregulation or a disturbance of the renin-angiotensin system. Babayan and colleagues sought to examine parameters of autonomic function in migraineurs with and without hypertension and found some differences in those with both conditions, including reduced arterial baroreceptor reflex and orthostatic hypertension.33 However, migraineurs had a higher frequency of family history of cardiovascular disease compared to healthy volunteers, irrespective of hypertension history. Disturbances in the renin-angiotensin system have also been implicated in the genesis of migraine, potentially through neurogenic inflammation, sensitivity to oxidative stress, and nociceptive neuromodulation.34 Finally, shared risk factors and comorbidities such as elevated BMI,19,35 insulin metabolism,36 and dyslipidemia37 may play a role.
Whether there is common pathophysiology shared by VMS and migraine is unclear. Although both VMS and migraine have been linked to sex hormones, and to estrogen specifically, absolute circulating estrogen levels are associated with neither.2,38 Rather, fluctuations or rates of change in estrogen levels may play a more important role. For example, VMS have been found to be more severe in women who experience an abrupt loss of ovarian hormones with bilateral oophorectomy before natural menopause.39 Similarly, falling levels of estrogen in the late luteal phase appears to be a trigger for menstrual related migraine.2,40
There is convincing evidence that 17β estradiol is a modulator of hypothalamic neurons via rapid membrane-initiated and intracellular signaling that regulates reproduction, temperature, energy homeostasis and stress.41 More recently, specific colocated neurons in the hypothalamus containing kisspeptin, neurokinin B (NKB) and dynorphin receptors (KNDy neurons) have been implicated in the etiology of VMS in menopause.42,43 The hypothalamus has also been attributed an important role in migraine pathophysiology.44 The orexinergic system is involved in regulating nociceptive processing, arousal, thermoregulation and autonomic function and has recently been linked with initiation and maintenance of migraine attacks.44 There is some evidence that the orexin system is tonically inhibited by estrogen and may be hyperactive in the setting of estrogen deficiency which potentially contributes to anxiety symptoms, insomnia and more severe hot flashes.41,45 A role for antagonism of the orexin system has also been suggested as a therapeutic target for management of these symptoms associated with menopause.45 Interestingly, orexin may be an intermediary in the regulation of the hypothalamic secretion of gonadotropin-releasing hormone by modulating expression of the KNDy neurons.46
The independent and possibly intersectional roles of sex hormones, endothelial dysfunction, hypothalamic pathways, common risk factors and comorbidities, and genetics that may be responsible for the links between VMS and migraine need to be further explored. Given that at least one in five women experience migraine and upwards of three in four women experience VMS, and further, that both conditions associate with hypertension and future CVD, it is critically important to better understand these links. From a clinical perspective, female migraineurs should be advised that they may be at risk for a greater VMS burden in the menopause transition and provided with proactive education and potential mitigation strategies. Further, they may also be at higher risk for hypertension and potentially for CVD, and vigilant monitoring and management of CVD risk factors is essential given that heart disease remains the leading cause of death in women. From a public health perspective, additional clarity on the associations of VMS and migraine with hypertension and CVD risk in women may ultimately help to inform a more accurate CVD risk calculator for women.47,48
This study has notable strengths including the large cohort size and the use of robust, validated questionnaires to assess menopause symptom burden, mood, and anxiety. However, the findings should be interpreted in the context of several limitations. VMS were assessed subjectively rather than objectively and may be limited by recall biases. However, VMS assessed subjectively may underestimate the symptom burden when compared with objective measurement, particularly with daytime VMS and in women with anxiety.49 Thus, the burden of VMS may be even higher than what is reported in the current study. In addition, menopause symptoms were only assessed at a single point in time in the current study, and thus the overall symptom burden during the menopause transition could not be determined. Migraine history was obtained by self-report rather than by a clinical diagnosis, potentially leading to some misclassification of other types of headache as migraine. However, prior studies have shown excellent agreement between migraine self-report and International Classification of Headache Disorders criteria (>87% agreement).50 We also did not collect information on the characteristics (including presence or absence of aura) or frequency of migraine attacks which could have provided more information on the association between migraine and VMS. We assessed the presence of hypertension at the same time as the assessment of VMS. Previous studies have shown an increased risk of future development of hypertension in women with more severe VMS. Therefore, the risk of hypertension in patients with severe VMS is better assessed in a longitudinal model, and it may have been underestimated in this patient population.
The study design is cross-sectional, and therefore causality cannot be determined. While we attempted to account for covariates that could moderate the association of VMS and migraine, there may be other confounding factors not accounted for. Although three different geographic locations were represented, the study lacks racial and ethnic diversity, potentially limiting generalizability in more diverse populations of women. Furthermore, participants were mainly educated, employed, and partnered women which may limit the generalizability of these results to women of other racial/ethnic backgrounds as well as those of lower socioeconomic status.
Conclusions
This large cross-sectional study confirms an association between a history of migraine and VMS in midlife women. Further, our data showed an association between migraine and hypertension, which may partially explain the correlation of migraine and cardiovascular disease risk. Additional study is needed to better define the mechanisms through which these common conditions are linked. Whether there is a common mechanistic pathway responsible for these associations remains uncertain. Given the high prevalence of migraine in women, this finding may help identify women who are at risk for more severe VMS in midlife. Whether the combination of migraine history and VMS in midlife portend the development of hypertension and subsequently greater CVD risk than either alone, and whether these female predominant or specific factors could be used to enhance the accuracy of CVD risk calculators for women require additional study.
Supplementary Material
Acknowledgments
Dr. Ekta Kapoor receives funding from NIA grant U54 AG044170
Abbreviations:
- BMI
body mass index
- CVD
cardiovascular disease
- PHQ-9
Patient Health Questionnaire-9
- VMS
vasomotor symptoms
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Conflicts of interest:
SSF-none
TS-none
JT-none
JMK- past consulting for Proctor and Gamble and Triangle Insights group
CLS - none
KM-none
FE-none
EK-consultant for Mithra Pharmaceuticals, Scynexis, and Astellas Pharma and for Womaness
The findings in this manuscript were presented at The North American Menopause Society annual meeting 9/2021
CRediT Statement
Stephanie Faubion: Conceptualization, data curation, methodology, writing original draft
Taryn Smith: Writing – review & editing
Jacqueline Thielen: Writing – review & editing
Juliana Kling: Writing – review & editing
Chrisandra Shufelt: Writing – review & editing
Kristin Mara: Formal analysis, writing – review & editing
Felicity Enders: Methodology, formal analysis, writing – review & editing
Ekta Kapoor: Conceptualization, data curation, methodology, writing original draft
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