Hormonal, metabolic, and stress-related clinical differences between episodic and chronic migraine: insights for diagnostic and therapeutic approaches

Abstract

Background

Migraine, a common neurological disorder, is categorized into episodic (EM) and chronic (CM) forms. Understanding their hormonal and metabolic differences can enhance insights into migraine pathophysiology and guide clinical approaches.

Objective

To explore hormonal and metabolic imbalances in EM and CM patients and identify key factors contributing to migraine chronicity.

Methods

This retrospective, cross-sectional study included 500 patients with migraine (318 EM and 182 CM). Data were retrospectively extracted from pre-existing clinical records, structured intake forms, physician examination notes, questionnaire-based assessments, and available laboratory results to evaluate demographic, clinical, metabolic, stress-related, mental health-related, and comorbidity variables.

Results

CM patients were older (46.28 vs. 43.13 years, p = 0.002) and had more frequent severe attacks (15 vs. 8/month) and mild attacks (12 vs. 6/month) (p < 0.001). CM patients exhibited higher rates of anaemia (34.9% vs. 25.7%, p = 0.035), asthma (12.8% vs. 7.3%, p = 0.046), and sleep apnea (4.7% vs. 1.3%, p = 0.034). Fibromyalgia-related symptoms were common in both groups (82.1% in CM vs. 78.2% in EM), while the number of fibromyalgia tender points was higher in CM than in EM patients (median 8 vs. 6). Ferritin levels were lower in CM but not significantly so (p = 0.139). Suicidal thoughts and feelings of helplessness were more common in CM (p = 0.016, p = 0.002). CM patients used Botox more often but with lower efficacy and engaged in more cognitive behavioural therapy (p = 0.002).

Conclusion

CM was associated with more severe symptoms, higher comorbidity burden, more widespread pain features, and distinct metabolic and stress-related profiles compared with EM. These findings support the early recognition of clinical and comorbid factors associated with the chronic migraine phenotype.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12883-026-05169-w.

Highlights

CM had more depressive features and fibromyalgia tender points.

CM exhibited higher rates of anaemia, asthma, and sleep apnea compared to EM.

Cranial sensitivity was higher in EM, and allodynia was more common in CM.

Early treatment of EM may prevent its progression to chronic migraine and improve overall health.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12883-026-05169-w.

Introduction

Migraines are a prevalent neurological disorder characterised by recurrent headaches that can be debilitating. The condition is commonly classified into episodic migraine (EM) and chronic migraine (CM). According to the International Classification of Headache Disorders, 3rd edition (ICHD-3), CM is defined as headache occurring on ≥ 15 days/month for > 3 months in a patient with a history of at least five attacks fulfilling criteria for migraine without aura and/or migraine with aura, with headache fulfilling migraine criteria or responding to migraine-specific acute treatment on ≥ 8 days/month, and not better accounted for by another ICHD-3 diagnosis. Understanding the differences between these two forms of migraine, particularly regarding hormonal and metabolic balance, is crucial for developing targeted diagnostic and therapeutic strategies [1].

The relationship between hormonal fluctuations and migraine is significant, with evidence suggesting that changes in sex steroid levels, weight loss, and serotonin metabolism after childbirth may contribute to migraine pathogenesis. High estrogen levels, particularly in migraine with aura, and the use of combined oral contraceptives, which can stabilize hormone levels, may also impact migraine frequency and severity. Furthermore, metabolic disorders like obesity and diabetes mellitus are associated with migraines, highlighting the role of lifestyle and hormonal factors in the disorder’s pathophysiology. Genetic variations in sex hormone receptor pathways and metabolism may also influence migraine occurrence, suggesting a complex interplay of hormonal and genetic factors in its development [2–4].

The process of migraine chronification is influenced by various factors, including aversive environmental stress, altered brain activity, and hypothalamic involvement. Aversive environmental stress has been shown to impact the chronification of migraine headaches, leading to the exploration of new therapeutic strategies [1, 3, 4]. Neuroimaging studies have revealed the involvement of brain regions such as the pons and hypothalamus, as well as disrupted intrinsic brain activity, in the chronification of migraine [5]. Additionally, altered somatosensory gating and functional connectivity of the hypothalamus have been associated with migraine chronification [6–8]. The activation of the hypothalamic-pituitary-adrenocortical axis due to factors such as irritable bowel syndrome, asthma, and childhood traumatic events has also been implicated in the process of migraine chronification [9, 10]. These findings underscore the complex interplay between environmental stress, brain activity, and the hypothalamic-pituitary-adrenal axis in the pathophysiology of migraine chronification.

In this study, we aimed to compare demographic, clinical, comorbid, hormonal, metabolic, stress-related, and mental health characteristics between patients with episodic and chronic migraine and to explore how these factors are associated with the chronic migraine phenotype.

Methods

Objectives

Primary objective

The primary objective of this study was to compare demographic, clinical, comorbid, hormonal, metabolic, stress-related, and mental health characteristics between patients with episodic migraine and chronic migraine.

Secondary objectives

The secondary objectives were to identify clinical and biological factors associated with the chronic migraine phenotype; to evaluate differences in headache characteristics, comorbid conditions, laboratory markers, and stress-related symptoms between groups; and to explore treatment-related differences, including the use of botulinum toxin, cognitive behavioural therapy, and physiotherapy, in patients with episodic and chronic migraine.

Patients and methods

Study design and data sources

This retrospective, cross-sectional study was conducted using pre-existing clinical records from two databases: the Mersin University Headache Database and the Brain360 Integrative Center Database. Records of patients evaluated between 2021 and 2023 were screened for eligibility. Patients with episodic migraine and chronic migraine were identified according to the International Classification of Headache Disorders, 3rd edition (ICHD-3) criteria [11]. The study did not involve prospective recruitment; instead, eligible patients were included after retrospective review of routinely collected clinical, questionnaire-based, and laboratory data.

Study population

A total of 500 patients who met the predefined eligibility criteria were included in the final analysis, comprising 318 with episodic migraine and 182 with chronic migraine. Patients had been evaluated in neurology clinics and headache centers, including a specialized headache clinic that received referral patients from different regions of the country. As part of routine clinical assessment, all patients completed a comprehensive clinical data form at their initial evaluation. This form included information on demographic characteristics, migraine history, headache features, comorbidities, medication use, sleep patterns, stress-related symptoms, mental health-related symptoms, dietary factors, and general health-related domains. Available laboratory parameters, including metabolic and hormonal markers, were extracted from the clinical records when present. The study design and patient selection process are summarized in Supplementary Fig. 1.

Inclusion criteria included:

• Age between 18 and 80 years

• Diagnosed with episodic or chronic migraine based on ICHD-3 criteria

• Ability to provide informed consent

Exclusion criteria included:

• Presence of other significant neurological disorders that could independently influence headache phenotype, pain sensitivity, disability, cognitive or emotional symptoms, or laboratory interpretation. These included cerebrovascular disease, epilepsy, intracranial mass lesions, multiple sclerosis or other demyelinating/inflammatory central nervous system disorders, neurodegenerative diseases, active central nervous system infection, moderate-to-severe traumatic brain injury, and secondary headache disorders.

• Use of hormonal therapies that could influence hormonal or metabolic balance.

• Pregnancy or breastfeeding.

Data collection

Because this was a retrospective, cross-sectional study, no additional patient interviews, physical examinations, questionnaires, imaging procedures, or blood tests were performed after study inclusion. All variables were extracted retrospectively from pre-existing clinical records generated during routine clinical care.

Demographic variables, including age, sex, body mass index, age at migraine onset, age at diagnosis, and migraine duration, were obtained from structured patient intake forms and medical records. Migraine-related variables, including migraine subtype, attack frequency, attack duration, pain severity assessed by the visual analogue scale, headache localization, lateralization, pain quality, aura, nausea, vomiting, photophobia, phonophobia, osmophobia, and allodynia, were extracted from headache-specific clinical questionnaires and physician assessment records. The diagnosis of episodic migraine or chronic migraine was based on ICHD-3 criteria documented in the clinical records [11].

Comorbid conditions, including anaemia, asthma/bronchitis, sleep apnea, depression, fibromyalgia-related symptoms, gastrointestinal complaints, allergic conditions, and medication use, were obtained from medical history forms and physician records. Stress-related symptoms, mental health-related symptoms, sleep-related symptoms, dietary factors, toxin-related symptoms, and general health-related domains were extracted from structured self-report questionnaires completed as part of routine clinical assessment. Physical examination findings, including cranial and cervical sensitivity findings and fibromyalgia tender point assessments, were obtained from physician examination records when available.

Laboratory variables were not newly measured for this study. Available blood test results, including ferritin, vitamin D, fasting glucose, fasting insulin, and other routine metabolic parameters, were extracted from the existing medical records when present. HOMA-IR was calculated using the following formula: HOMA-IR = fasting insulin (µU/mL) × fasting glucose (mg/dL) / 405. Missing or unavailable laboratory values were coded as missing in the statistical analysis and were displayed as “unknown” in the Sankey diagrams when included in visual flow analyses.

Statistical analysis

The descriptive statistics for numerical variables were reported as mean and standard deviation, or median, interquartile range, and minimum-maximum values, as appropriate, while categorical variables were reported as frequency and percentage. The normality of numerical variables was examined using the Kolmogorov-Smirnov test, and the parametric or non-parametric methods were used accordingly. Comparisons between groups were conducted using a chi-square test for nominal variables and an independent-samples t-test or Mann-Whitney U test for numerical variables. Logistic regression analysis was utilized to identify risk factors associated with chronic migraine. The relationships between demographic, clinical, hormonal, and metabolic conditions and treatment responses in episodic and chronic migraine were analyzed using a Sankey diagram.

Data were analyzed using IBM SPSS v.22 (IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp.), and a p-value of < 0.05 was considered statistically significant. Because this was a retrospective study based on routinely collected clinical records, some variables, particularly laboratory parameters, were not available for all patients. Missing data were not imputed. Analyses were performed using available data for each variable, and unavailable values were displayed as “unknown” in the Sankey diagrams when applicable.

Ethical considerations

The study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of Toros University with approval number 26.01.2024/24. Written informed consent was obtained from all participants before inclusion in the study.

Results

The study included 500 patients, of whom 318 were diagnosed with episodic migraine (EM) and 182 with chronic migraine (CM). The main demographic, clinical, comorbid, hormonal, metabolic, stress-related, and treatment-related findings are summarized below.

Demographic and clinical characteristics

The ages at migraine onset and at diagnosis were similar between the EM and CM groups. However, patients with CM were significantly older than patients with EM (46.28 ± 11.13 vs. 43.13 ± 10.73 years, p = 0.002), (Table 1). No significant overall difference in BMI was observed between the two groups, although subgroup analyses indicated gender-specific differences. The mean age at migraine onset was also comparable between groups (22.26 ± 9.37 years in EM vs. 22.18 ± 10.62 years in CM; p = 0.931). The association of migraine subtype with age, BMI, and monthly headache attack frequency is shown in Fig. 1.

Table 1.

Demographic, clinical, and pain characteristics of patients

	Episodic (n=318)	Chronic (n=182)	p
Gender, n (%)
Male	53 (16.7)	25 (13.7)	0.385
Female	265 (83.3)	157 (86.3)
Age (years)
Overall	43.13 ± 10.73 [19-74]	46.28 ± 11.13 [23-80]	0.002
Male	43.57 ± 11.63 [19-72]	43.32 ± 9.41 [23-64]	0.926
Female	43.05 ± 10.58 [20-74]	46.7646.76 ± 11.34 [24-80]	0.001
Age at Onset
Overall	22.26 ±9.37 [6-54]	22.18 ± 10.62 [4-56]	0.931
Male	19.83 ± 9.62 [6-44]	21.60 ± 8.45 [10-41]	0.434
Female	22.75 ± 9.26 [6-54]	22.27 ± 10.95 [4-56]	0.650
Age at Diagnosis
Overall	25.04 ± 10.39 [6-70]	25.98 ± 11.57 [4-67]	0.348
Male	24.23 ± 11.94 [6-65]	25.40 ± 10.15 [10-52]	0.673
Female	25.20 ± 10.08 [9-70]	26.08 ± 11.80 [4-67]	0.419
BMI
Overall	24.41 ± 4.44 [16.14-41.36]	24.84 ± 4.84 [15.78-41.21]	0.337
Male	26.19 ± 4.21 [17.59-37.04]	26.62 ± 4.33 [19.03-35.92]	0.681
Female	24.06 ± 4.40 [16.14-41.36]	24.52 ±4.87 [15.78-41.211	0.334
Chronicity Duration (years)	-	5 (12) [1-51]	-
Attack Frequency of Severe Pain (permonth)	8 (8) [1-30]	15 (12) [2-30]	<0.001
Attack Frequency of Mild Pain (per month)	6 (7) [1-60]	12 (14) [1-30]	<0.001
Attack Duration without Medication(hours)	4 (8) [1-96]	4 (20) [1-72]	<0.001

Fig. 1.

Association of demographic and headache-frequency characteristics in patients with episodic and chronic migraine. This Sankey diagram illustrates the distribution of patients with episodic migraine (EM; n = 318) and chronic migraine (CM; n = 182) by age, body mass index (BMI), and the frequencies of severe and mild headache attacks. The values displayed in the nodes indicate patient counts. “Years” refers to patient age. “kg/m²” refers to BMI. “Attacks” refers to the number of migraine attacks per month. In the EM group, the thresholds shown are age ≤ 43 versus > 43 years, BMI ≤ 24.41 versus > 24.41 kg/m², severe headache attacks ≤ 8 versus > 8 per month, and mild headache attacks ≤ 6 versus > 6 per month. In the CM group, the thresholds shown are age ≤ 46 versus > 46 years, BMI ≤ 24.84 versus > 24.84 kg/m², severe headache attacks ≤ 15 versus > 15 per month, and mild headache attacks ≤ 12 versus > 12 per month. The width of each flow represents the number of patients passing from one category to the next

Migraine attack characteristics

Patients with CM reported a higher monthly frequency of both severe and mild headache attacks compared with patients with EM. The median number of severe attacks per month was higher in the CM group than in the EM group (15 [IQR 12] vs. 8 [IQR 8], p < 0.001), and the frequency of mild attacks was also greater in CM than in EM (12 [IQR 14] vs. 6 [IQR 7], p < 0.001). Attack duration without medication was longer in patients with CM than in those with EM (4 [IQR 20] hours vs. 4 [IQR 8] hours, p < 0.001). Headache lateralization differed significantly between groups. In EM, headache was more frequently unilateral (55.3%), whereas in CM it was more commonly bilateral (54.4%) (p = 0.002). Headache localization also differed between groups, with periorbital localization being more frequent in EM and vertex localization being more frequent in CM (p = 0.021). Among symptoms occurring before or during headache, nausea was more common in EM (p = 0.034), whereas allodynia was more common in CM (p = 0.001). Cranial and cervical sensitivity findings, including greater and lesser occipital nerve, supraorbital, supratrochlear, orbital, and shoulder sensitivity, were more pronounced in patients with EM, (Table 2).

Table 2.

Headache characteristics of episodic and chronic migraine groups

Characteristic	Episodic (n=318)	Chronic (n=182)	p-value
Headache Character, n (%)
- Throbbing	261 (82.1%)	153 (84.1%)	0.979
- Stabbing	4 (1.3%)	2 (1.1%)
- Piercing	14 (4.4%)	7 (3.8%)
- Pressing	34 (10.7%)a	18 (9.9%)
- Explosive	5 (1.6%)	2 (1.1%)
Localization 1, n (%)
- Unilateral	176 (55.3%)	77 (42.3%)	0.020
- Bilateral	134 (42.1%)	99 (54.4%)
- Both	8 (2.5%)	6 (3.3%)
Localization 2, n (%)
- Frontal	78 (24.5%)	45 (24.7%)
- Periorbital	117 (36.8%)	45 (24.7%)
- Occipital	60 (18.9%)	41 (22.5%)
- Vertex	11 (3.5%)	14 (7.7%)
- Temporal	42 (13.2%)	25 (13.7%)
- Facial	10 (3.1%)	12 (6.6%)
Pain Severity (VAS)	8 (0) [6-10]	8 (1) [5-10]	0.152
Nausea, n (%)	269 (84.6%)	166 (91.2%)	0.034
Vomiting, n (%)	83 (26.1%)	43 (23.6%)	0.540
Photophobia, n (%)	282 (88.7%)	166 (91.2%)	0.373
Phonophobia, n (%)	254 (79.9%)	148 (81.3%)	0.695
Osmophobia, n (%)	113 (35.5%)	71 (39.0%)	0.438
Allodynia, n (%)	13 (4.1%)	21 (11.5%)	0.001

Hormonal and metabolic assessment

Ferritin levels were lower in patients with CM than in those with EM; however, this difference did not reach statistical significance (16 ng/mL vs. 20 ng/mL, p = 0.139). Vitamin D levels were also similar between groups (21 ng/mL in EM vs. 23 ng/mL in CM, p = 0.285). HOMA-IR values did not differ significantly between the EM and CM groups (median: 2 vs. 2; p = 0.704). Regarding toxin-related symptoms, fatigue was reported more frequently in patients with CM than in those with EM (p = 0.002). Sleep apnea was more common in CM than in EM (4.7% vs. 1.3%, p = 0.034), whereas fatigue after sleep or rest was reported more frequently in EM than in CM (p = 0.001).

Among patients with available menopausal status data, menopause was more frequent in the CM group than in the EM group (41/139 vs. 41/241, p = 0.004). In addition, age at menopause was significantly later in the CM group than in the EM group (48.34 ± 3.47 years vs. 46.05 ± 4.82 years, p = 0.016). The distribution of available laboratory and metabolic markers, including ferritin, vitamin D, and HOMA-IR, according to migraine subtype is shown in Fig. 2.

Fig. 2.

Association of laboratory and metabolic markers in patients with episodic and chronic migraine. This Sankey diagram illustrates the distribution of available laboratory and metabolic markers among patients with episodic migraine (EM) and chronic migraine (CM). Fe indicates serum ferritin, VitD indicates serum vitamin D, and HOMA-IR indicates the Homeostatic Model Assessment for Insulin Resistance. Ferritin was categorized as unknown, ≤20 ng/mL, or >20 ng/mL. Vitamin D was categorized as unknown, ≤21 ng/mL, or >21 ng/mL. HOMA-IR was categorized as unknown, ≤2, or >2. “Unknown” indicates that the relevant laboratory value was not available in the retrospective clinical records. The numbers in the nodes represent patient counts, and the width of each flow represents the number of patients passing from one category to another

General health and comorbid conditions

General health and comorbid conditions differed between the EM and CM groups. Anaemia was more common in patients with CM than in those with EM (34.9% vs. 25.7%, p = 0.035). Asthma/bronchitis was also more frequent in CM (12.8% vs. 7.3%, p = 0.046), as was sleep apnea (4.7% vs. 1.3%, p = 0.034). Other general health conditions, including eczema, allergic reactions, and gastrointestinal complaints, were more frequent in patients with CM, but these differences did not consistently reach statistical significance.

Fibromyalgia-related symptoms were frequent in both groups (78.2% in EM and 82.1% in CM). However, the number of fibromyalgia tender points was higher in patients with CM than in those with EM (median 8 vs. 6), suggesting a greater widespread pain burden in the chronic migraine group. The distribution of selected comorbid conditions, including anaemia, asthma/bronchitis, depression, and sleep apnea, according to migraine subtype is shown in Fig. 3.

Fig. 3.

Association of comorbid conditions in patients with episodic and chronic migraine. This Sankey diagram shows the relationship between migraine subtype and selected comorbid conditions, including anaemia, asthma/bronchitis, depression, and sleep apnea. EM indicates episodic migraine, and CM indicates chronic migraine. “No-Anaemia,” “No-Asthma,” “No-Depression,” and “No-Sleep Apnea” indicate the absence of the respective condition in the clinical records, whereas “Anaemia,” “Asthma,” “Depression,” and “Sleep Apnea” indicate the documented presence of the condition. The numbers shown in each node represent patient counts, and the width of each flow corresponds to the number of patients moving between categories

Stress-related and mental health profile

Overall stress profile scores were similarly high in both migraine groups. Difficulty managing stress and unexplained back and neck pain were more frequently reported in patients with EM compared with patients with CM (p = 0.037 and p = 0.041, respectively). Although the prevalence of depression was numerically higher in CM than in EM, the difference was not statistically significant (22.1% vs. 20.1%, p = 0.613). However, suicidal thoughts and feelings of hopelessness and helplessness were significantly more common in the CM group than in the EM group (p = 0.016 and p = 0.002, respectively).

Treatment response

Body balances and significant therapeutic responses for all patients with migraine

Treatment-related findings were evaluated in relation to stress-related and mental health parameters, dietary factors, toxin-related symptoms, and stress profiles. Among patients who received botulinum toxin treatment (n = 174), photophobia was less frequent than among those who did not receive it (37/174 vs. 92/281, p = 0.010),(Table 3).

Table 3.

Therapeutic approaches in the management of migraine patients

Characterisic	Episodic (n=318)	Chronic (n=182)	p-value
Migraine Vaccine, n (%)	115 (36.2%)	74 (40.7%)	0.319
Botox, n (%)	99 (31.1%)	88 (48.4%)	<0.001
Interventional, n (%)	109 (34.3%)	96 (52.7%)	<0.001
Supplements, n (%)	289 (90.9%)	171 (94.0%)	0.223
CBT (Cognitive Behavioral Therapy), n (%)	211 (66.4%)	144 (79.1%)	0.002
Physiotherapy, n (%)	125 (39.3%)	101 (55.5%)	<0.001
Number of Painkillers per Month	10 (10) [1-90]	20 (18) [2-300]	<0.001
Number of Triptan Group Medications per Month	8 (8) [1-30]	15 (20) [1-300]	<0.001

Abbreviations:EM Episodic migraine, CM Chronic migraine, CBT Cognitive-behavioral therapy, HOMA-IR The Homeostatic Model Assessment for Insulin Resistance, BMI Body mass index, HIT-6 Headache impact test, VAS Visual analog scale, MIDAS Migraine Disability Assessment, BDI Beck Depression Inventory, GAD-7 Generalised Anxiety Disorder 7, ICHD3 International Classification of Headache Disorders, 3rd edition

Patients who received cognitive behavioural therapy (CBT) showed lower frequencies of menstrual period abdominal pain (p = 0.051), night sweats (p = 0.022), difficulty maintaining attention (p = 0.033), feelings of hopelessness and helplessness (p = 0.019), and crying spells (p = 0.001) compared with those who did not receive CBT. Physiotherapy was associated with lower frequencies of back and neck pain (p = 0.001), morning muscle stiffness (p = 0.022), feelings of life monotony (p = 0.015), feelings of hopelessness (p = 0.013), and constipation (p = 0.034).

Treatment-related differences between EM and CM

Treatment patterns differed between patients with EM and CM. Patients with CM were more likely to have received botulinum toxin treatment than those with EM (28.6% vs. 19.5%, p = 0.020), although reported efficacy was numerically lower in CM and did not differ significantly between groups (28.8% vs. 37.1%, p = 0.352). CBT was used more frequently among patients with CM than among those with EM (79.1% vs. 66.4%, p = 0.002). Physiotherapy was also more commonly used in the CM group than in the EM group (55.5% vs. 39.3%, p < 0.001). The distribution of treatment approaches according to migraine subtype is shown in Fig. 4.

Fig. 4.

Association of treatment approaches in patients with episodic and chronic migraine. This Sankey diagram shows the distribution of treatment approaches among patients with episodic migraine (EM) and chronic migraine (CM), including botulinum toxin treatment, documented response to botulinum toxin, cognitive behavioural therapy, and physiotherapy. Botox refers to botulinum toxin treatment. “No-Botox” indicates patients who did not receive botulinum toxin treatment. “Response” and “No-Response” refer to the documented clinical response among patients who received botulinum toxin treatment, whereas “None” indicates that no botulinum toxin response assessment was applicable because the patient did not receive botulinum toxin. CBT indicates cognitive behavioural therapy. “Physiotherapy” and “No-Physiotherapy” indicate whether physiotherapy was included in the treatment approach. The numbers in each node represent patient counts, and the width of each flow reflects the number of patients moving between treatment categories

Hormonal and metabolic differences in treatment response between EM and CM

Treatment responses were also evaluated in relation to hormonal and metabolic symptoms. Thyroid-related symptoms, including cold extremities, heat intolerance, dry skin, and hair dryness, did not differ significantly between treatment responders and non-responders in either migraine group. Estrogen-related symptoms, including vaginal dryness and pain during intercourse, were reported more frequently in patients with CM, although these symptoms were not significantly associated with treatment efficacy.

Overall, the Results indicate that CM is associated with older age, higher headache frequency and duration, greater allodynia, higher comorbidity burden, more widespread pain features, more severe stress-related and mental health findings, and greater use of multimodal treatment approaches compared with EM.

Discussion

This study investigated the hormonal and metabolic differences between EM and CM patients and found significant differences in several demographic, clinical, and biochemical parameters. Despite having the same age of onset, chronic migraine is associated with more severe clinical characteristics, higher comorbidity rates, and distinct metabolic profiles, as CM has more depressive features and a significantly higher number of fibromyalgia tender points than EM. While cranial sensitivity is more pronounced in EM, allodynia is higher in CM. These findings suggest that chronic migraine could be considered an advanced stage of episodic migraine and that early medical and interventional treatments during the EM phase could prevent progression to CM, with a significant impact on overall health. These conclusions are supported by real-world evidence.

Demographic and clinical characteristics

Our results indicated that patients with chronic migraine were generally older than those with episodic migraine. This finding is consistent with previous studies suggesting that migraine frequency and chronicity are influenced by cumulative clinical burden, repeated exposure to migraine triggers, and progressive central sensitization [12, 16].

Studies estimate that about 2.5% of patients with episodic migraines transition to chronic migraines annually [12]. Furthermore, research has highlighted the impact of migraine on productivity, with most migraine patients experiencing severe disability that affects their daily work and social activities [13]. The prevalence of migraine has been reported to be higher in women than in men, with peak onset typically occurring between the ages of 25 and 55 years. Additionally, familial patients with migraine have been found to exhibit specific aura patterns compared to sporadic patients with migraine, suggesting potential genetic influences on migraine presentation [14].

This age-related increase in migraine severity may be attributed to cumulative exposure to migraine triggers and progressive central sensitization. Although overall BMI did not differ significantly between groups, the observed gender-specific BMI differences are consistent with prior literature suggesting that metabolic factors, including obesity and altered metabolic status, may contribute to migraine pathophysiology and treatment response [15, 19]. The age-related differences in migraine presentation, the influence of metabolic factors such as BMI, the impact of migraine on productivity, and the potential associations with genetic and nutritional factors all contribute to a comprehensive understanding of migraine pathophysiology. Our results indicated that chronic migraine patients are generally older than those with episodic migraines. This finding is consistent with previous studies suggesting that migraine severity and frequency tend to increase with age, potentially due to cumulative exposure to migraine triggers and progressive central sensitization. The significant difference in BMI between gender subgroups also aligns with literature highlighting the role of metabolic factors in migraine pathophysiology.

Migraine attack characteristics

The study confirmed that chronic migraine patients experience more frequent and severe attacks compared to those with episodic migraines. The higher frequency of severe and mild headache attacks in the chronic migraine group is consistent with previous studies linking chronic migraine to greater disability, impaired productivity, and increased clinical burden [13, 16]. The longer attack duration observed in chronic migraine patients may reflect altered central pain processing and increased sensitization of central pain pathways, mechanisms that have previously been described in chronic migraine [5, 16]. This heightened susceptibility to migraine attacks in chronic migraine patients underscores the need for targeted interventions that address the unique pathophysiological mechanisms associated with chronic migraine to improve patient outcomes and quality of life.

This is in line with existing literature, as both groups (EM and CM) had high-stress profiles and similar ages of onset and diagnosis. However, chronic patients with migraine were more likely to have suicidal thoughts, to feel hopeless and helpless, and to have additional pain points not only in the head but also in other parts of the body, which suggests that chronic migraine is associated with increased disability and higher healthcare utilization. The longer attack duration in chronic migraine patients may reflect underlying differences in central pain processing mechanisms, as previously reported in other studies.

Comorbid conditions

The association between dietary iron intake, serum ferritin levels, and severe headaches or migraine in women aged 50 and above underscores the potential role of nutritional factors in migraine pathophysiology [17]. The association between sleep quality and migraine burden has been explored, indicating a need for further investigation into the relationship between sleep quality and migraine-related outcomes [4].

Our finding of higher comorbidity rates, particularly anaemia, asthma/bronchitis, and sleep apnea, in patients with chronic migraine is consistent with previous research showing associations between migraine and systemic comorbidities, including iron deficiency-related parameters, asthma, sleep disturbance, and psychiatric symptoms [4, 10, 17, 22].

Hormonal and metabolic assessments

The study identified significant differences in hormonal and metabolic markers between EM and CM. Lower ferritin levels in chronic migraine patients may suggest a link between iron metabolism and migraine chronicity. This finding supports previous research suggesting that iron deficiency could play a role in migraine pathogenesis through mechanisms such as hypoxia and mitochondrial dysfunction. Although vitamin D levels and HOMA-IR scores did not differ significantly between groups in our study, metabolic factors remain relevant to migraine pathophysiology, and previous studies have emphasized the potential contribution of metabolic dysregulation, obesity, diabetes-related mechanisms, and nutritional factors to migraine burden [17, 19]. Hormonal fluctuations and migraine have been a subject of extensive research. It has been suggested that the rapid fall in sex steroid levels, weight loss, and alterations in serotonin metabolism following childbirth may be relevant to the pathogenesis of migraine. Furthermore, the incidence of migraine attacks reportedly increases during periods of high circulating estrogen, particularly in migraine with aura [18]. A narrative review has highlighted the association between the aetiology and pathophysiology of migraine and metabolic disorders such as obesity and diabetes mellitus [19]. This association considers lifestyle aspects and the possible involvement of neurotransmitters, neuropeptides, and/or sex hormones. The complex interaction between sex hormones and the occurrence of migraines has also been studied, emphasizing the need for a clear identification of the relationship between migraine and hormone change in management [20]. Furthermore, genetic variants in proteins involved in sex hormone receptor pathways and metabolism have been investigated for their association with migraine, suggesting a potential role of genetic and hormonal factors in modulating migraine pathophysiology [18, 21, 22]. These findings have led to an interest in the use of hormonal treatments for migraine. Overall, the evidence suggests that hormonal and metabolic factors significantly influence the occurrence and pathophysiology of migraine, highlighting the importance of considering these factors in the management and treatment of migraine [22].

The menopausal transition has been associated with changes in migraine frequency, suggesting a potential association between hormonal changes during menopause and migraine occurrence. Menopause marks a significant hormonal shift, particularly involving a decline in estrogen levels, which has been implicated in migraine pathogenesis [23, 24]. Studies have highlighted that fluctuations in estrogen levels, such as those experienced during menarche, menstruation, pregnancy, and menopause, can influence the onset and severity of migraines in women [25]. In line with the literature, our results revealed that CM had a later age at menopause than EM. Understanding the interplay between hormonal changes during menopause and migraine pathophysiology is crucial for developing effective management strategies tailored to women experiencing migraines during this transitional phase in their lives.

Hormonal and metabolic differences in treatment response

The integration of cognitive-behavioral therapy (CBT), Botox injections, and physiotherapy in the management of migraine presents a multifaceted approach that addresses both the psychological and physical aspects of the condition. Research by Dodick [26] and Akbar [27] highlights the efficacy of Botox (onabotulinumtoxin-A) in reducing migraine frequency by blocking the release of neurochemicals associated with migraines. Additionally, studies by Mezaal et al. [28] and Mukherjee [29] emphasize the FDA-approved use of Botox for chronic migraine treatment, requiring periodic injections for sustained benefits. Physiotherapy, as discussed by Moore et al. [30] and Mouaanaki [31], plays a significant role in migraine management, with techniques such as connective tissue massage and targeted nerve-directed injections showing promise in reducing headache parameters and improving quality of life. The combination of CBT, Botox injections, and physiotherapy offers a comprehensive approach to addressing the complex nature of migraines, targeting both the psychological and physical components for enhanced therapeutic outcomes.

The differential use of treatments such as botulinum toxin and physiotherapy between EM and CM underscores the complexity of managing chronic migraine, which often requires more intensive and multimodal treatment strategies [26, 30, 31]. The higher utilization of CBT among CM patients suggests a greater need for psychological support in this group, reflecting the significant impact of chronic migraine on mental health.

Analysing treatment responses with respect to hormonal and metabolic imbalances revealed no significant differences in thyroid- or estrogen-related symptoms between treatment responders and non-responders. This suggests that while these hormonal factors may contribute to migraine pathophysiology, they do not significantly influence the efficacy of treatments like Botox or CBT straightforwardly. Further research is needed to explore how hormonal modulation might optimize treatment outcomes for migraine patients.

Clinical implications

The identification of specific hormonal and metabolic imbalances in chronic migraine patients provides a basis for developing personalized treatment strategies. Clinicians should consider evaluating hormonal and metabolic profiles in migraine patients to tailor interventions more effectively. Integrating multidisciplinary approaches that address comorbid conditions, psychological factors, and lifestyle modifications may enhance treatment outcomes for chronic migraine patients.

Limitations

Despite the comprehensive nature of this study, several limitations should be acknowledged to contextualize the findings and guide future research efforts. Firstly, the cross-sectional design inherently limits our ability to establish causality between hormonal and metabolic imbalances and migraine chronicity. Longitudinal studies are necessary to explore temporal relationships and potential causal pathways more effectively.

The reliance on self-reported data for migraine characteristics and comorbid conditions introduces the possibility of recall bias, as participants may not accurately remember or report their medical histories. This could impact the reliability of our findings. Because the records were obtained from specific neurology clinics and headache centers, the generalizability of the findings to the broader population of patients with migraine may be limited. Future studies should aim for more diverse and representative samples to enhance generalizability.

Hormonal and metabolic assessments in this study were based on single-time-point measurements, which may not capture fluctuations over time. Particularly among women, hormonal variations related to menstrual cycles were not accounted for, which could have influenced the results. Furthermore, although a broad range of comorbid conditions was included, the interactions between these conditions and migraine were not fully explored, necessitating more detailed analyses of specific comorbidities and their impact on migraine chronicity in future research.

The variability in treatment regimens among participants could also influence the results. Different treatment histories and adherence levels were not controlled for, which might affect the comparison of treatment responses between episodic and chronic migraine patients. While the study assessed several hormonal and metabolic markers, other relevant biomarkers may have been missed. Comprehensive profiling, including additional markers such as cortisol, leptin, and ghrelin, could provide a more complete understanding of the biological differences between episodic and chronic migraine.

Psychological factors were considered, but only assessments of depression and anxiety were included. Other psychological factors, such as stress and coping mechanisms, were not thoroughly examined, though they could play a significant role in migraine chronicity. Environmental and lifestyle factors, such as diet, physical activity, and stress exposure, were also not accounted for, which could influence hormonal and metabolic profiles and migraine outcomes.

Despite attempts to control for confounding variables, there may still be unmeasured confounders that could impact the results. Future studies should include a more comprehensive set of potential confounding variables to strengthen the findings. By acknowledging these limitations, we can better interpret the results of this study and guide future research efforts to address these gaps, building upon our understanding of the hormonal and metabolic differences in migraine patients.

Conclusion

This study highlights significant hormonal and metabolic differences between episodic and chronic migraine patients, with implications for improving clinical and diagnostic approaches. Further research should focus on elucidating the mechanisms by which these imbalances contribute to migraine chronicity and exploring targeted interventions to mitigate their impact. By advancing our understanding of the biological underpinnings of chronic migraine, we can move towards more personalized and effective migraine management strategies.

Abbreviations

EM

episodic migraine

CM

chronic migraine

CBT

cognitive-behavioral therapy, HOMA-IR: The Homeostatic Model Assessment for Insulin Resistance

BMI

body mass index

HIT-6

Headache impact test

VAS

visual analog scale

MIDAS

Migraine Disability Assessment, BDI: Beck Depression Inventory

GAD-7

Generalised Anxiety Disorder 7, ICHD3:International Classification of Headache Disorders, 3rd edition

Authors’ contributions

Conceptualization: Uluduz D, Ozge A, Gozubatik-Celik RG; Data acquisition: Uluduz D, Ozge A, Uluduz E, İskender; M, Eyüboğlu S. Formal analysis; Sungur MA; Funding: None, Supervision: Uluduz D, Ozge A. Writing original draft Gozubatik-Celik RG, Writingeview & editing: Uluduz D, Ozge A; All authors reviewed the manuscript.

Funding

None.

Data availability

All information analysed in this study was collected in a dataset and this is available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of Toros University (approval number: 26.01.2024/24). Written informed consent was obtained from all participants before inclusion in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.