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. 2025 Dec 29;66(3):712–724. doi: 10.1111/head.70035

Migraine prevalence and phenotype in autism: A retrospective cohort study using a US National Health Survey and large academic health system electronic health record

Maria Pia Grant Tejada 1, Alexandra M Klomhaus 2, Rebecca Ortiz 3, Tristan D Tibbe 2, Sinifunanya E Nwaobi 3,✉
PMCID: PMC12951701  PMID: 41459835

Abstract

Objective

We analyzed data from both a national survey and a single hospital system to determine the prevalence of migraine in individuals with autism as well as identify sociodemographic and clinical characteristics associated with migraine in individuals with autism.

Background

Few studies have examined the prevalence of migraine in autism and there are no studies examining the migraine phenotype and clinical features associated with migraine in autism.

Methods

This retrospective cohort study used two databases—the National Survey of Children's Health (NSCH) and the University of California Los Angeles hospital system electronic health record (UCLA EHR). NSCH survey data from 2018, 2019, 2020, and 2021 (data collection period for each year is June to January; e.g., NSCH 2021 period is June 2021 to January 2022; N = 50,892) were queried to identify cohorts based on responses to two survey questions identifying the presence of frequent/severe headache and autism. For UCLA cohorts, patients (12/01/1979–4/16/2023, N = 4,334,162) were queried for migraine and autism based on the International Classification of Diseases diagnosis codes. We tested the hypothesis: Headache/migraine occurs more frequently in individuals with autism versus without autism. Variables including social determinants of health (SDoH) and co‐occurring illnesses were compared between autism with versus without headache/migraine.

Results

Headache and migraine prevalence was higher in individuals with autism versus those without (2021 NSCH—headache % [95% confidence interval {CI}], 7.1% [4.62–9.56] vs. 3.0% [2.62–3.19], p < 0.001 and UCLA—migraine: 3.1% [2.86–3.43] vs. 2.0% [1.97–1.99], p < 0.001). Among those with autism, the presence of headache/migraine was associated with increased odds of adverse childhood experiences such as bullying (NSCH—‘Weekly/Almost daily’ bullying aOR = 5.93 [2.01–17.50], p = 0.001, ‘Never’ reference) and being a victim of violence (NSCH—‘Yes’ aOR = 2.82, [1.19–6.66], p = 0.018), poor general health (NSCH—‘Fair/Poor’ health aOR = 9.68, [3.01–31.19], p < 0.001, ‘Excellent’ reference), mood disturbances, including anxiety (NSCH—‘Yes’ aOR = 4.50, [1.63–12.41], p = 0.004; UCLA aOR = 3.40, [2.78–4.17], p < 0.001), and depression (NSCH—‘Yes’ aOR = 5.70, [2.50–12.97], p < 0.001; UCLA aOR = 3.76, [3.08–4.60], p < 0.001), as well as increased rates of concussion (NSCH—‘Yes’ aOR = 9.05, [3.19–25.66], p < 0.001; UCLA aOR = 10.28, [6.91–15.30], p < 0.001).

Conclusions

Headache/migraine occurs at higher rates in individuals with autism and is associated with increased odds of negative SDoH and clinically relevant co‐occurring illnesses. This study highlights the importance of migraine screening in individuals with autism. Future work is needed to understand the burden and impact of migraine in autism.

Keywords: adverse childhood events, autism spectrum disorder, concussion, migraine, social determinants of health

Plain Language Summary

Autism is associated with altered sensory processing, including pain perception, but few studies have evaluated headache and/or migraine in autism. In this study, we observed increased rates of migraine in individuals with autism compared to those without. Among those with autism, the presence of headache/migraine was associated with increased odds of adverse childhood experiences, poor health, and concussion, suggesting that these may be important directions for future research on the interaction between migraine and autism.

Abbreviations

ACEs

adverse childhood experiences

ADD/ADHD

attention deficit disorder/attention deficit hyperactivity disorder

aOR

adjusted odds ratio

ASD

autism spectrum disorder

BMI

body mass index

CI

confidence interval

EHR

electronic health record

GI

gastrointestinal

ICD‐9/10

International Classification of Diseases, Ninth and Tenth Edition

IRB

institutional review board

M:F

male:female

NSCH

National Survey of Children's Health

SD

standard deviation

SDoH

social determinants of health

UCLA

University of California Los Angeles

US

United States

WIC

Women/Infants/Children

INTRODUCTION

Migraine is the third most disabling neurological condition worldwide and is characterized by recurrent episodes of headache with associated symptoms of nausea, vomiting, and light and sound sensitivity. 1 Migraine represents a disorder of abnormal sensory processing as evidenced by sensory sensitivity to a variety of modalities during and in between migraine episodes. 2 , 3 , 4 , 5 Autism spectrum disorder (ASD or autism) is a heterogeneous neurodevelopmental disorder with an estimated prevalence of 1 in 44 children in the United States. 6 Like migraine, autism is associated with altered sensory processing, including pain perception. 7 , 8 , 9 , 10 Autism and migraine are both comorbid with epilepsy, attention deficit hyperactivity disorder (ADHD), as well as mood and sleep disorders, highlighting the potential for overlapping pathophysiology between the two conditions. 2 , 4 , 11 , 12 , 13 , 14 , 15 , 16 Several studies have identified increased rates of migraine in autism. 17 , 18 , 19 , 20 Among children with autism, one study observed increased sensory hyperreactivity in children with migraine compared to those without migraine. 17 Overall, these data suggest there exists a clinically meaningful interaction between migraine and autism.

Currently, there are limited data regarding the prevalence and phenotype of migraine in ASD and the clinical features associated with migraine in autism. We analyzed data from both a national survey and a single hospital system to investigate the prevalence of migraine in individuals with autism as well as identify sociodemographic and clinical characteristics associated with migraine in individuals with autism. We tested the primary hypothesis that headache (specifically frequent/severe headache in the National Survey of Children's Health [NSCH] dataset) or migraine (based on International Classification of Diseases [ICD] codes in the University of California Los Angeles hospital system electronic health record [UCLA EHR] dataset) occur more frequently in individuals with autism compared to individuals without autism.

METHODS

Standard protocol approvals, ethical considerations, and patients consents

Participation in the NSCH is entirely voluntary and all participants provide informed consent to participate. NSCH data is de‐identified. The UCLA Institutional Review Board (IRB) deemed this project to be exempt from IRB review (IRB ID # 25‐1302) given the retrospective study design and de‐identified data collection. All data were accessed on a secure platform to maintain patient confidentiality. This study adhered to ethical principles outlined by the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research (Belmont Report), specifically respect for persons, beneficence, and justice.

Data sources

This study used (1) the NSCH and (2) the UCLA health system EHR. The NSCH is a national (US) survey focused on physical and emotional health, access to care, and social determinants of health (SDoH) for children (aged 0–17 years). The NSCH oversamples children with special health care needs and children 0–5 years of age. 21 , 22 Households are randomly selected, and all responses are parent‐reported. The present study utilized NSCH data from years 2018 (N = 30,530), 2019 (N = 29,433), 2020 (N = 42,777), and 2021 (N = 50,892). All NSCH data are de‐identified and publicly available. 23 The UCLA EHR contains clinical data on ~4.4 million patients seen in a variety of inpatient and outpatient clinical settings. UCLA data were extracted from all available years (Decemer 1, 1979, to April 16,2023), de‐identified, and accessed using a Health Insurance Portability and Accountability Act (HIPAA) compliant platform.

Study cohort and design

This is a retrospective cohort study. For NSCH data, cohort inclusion/exclusion criteria were based on parental reporting of frequent/severe headache and autism (ASD). For UCLA EHR data, cohort inclusion/exclusion criteria were defined based on the ICD‐9 and ICD‐10 diagnosis codes for migraine (G43, 346) and autism (F84.0, F84.3, F84.5, F84.8, F84.9, 299.0, and 299.1).

To determine if headache (NSCH data) or migraine (UCLA data) prevalence was higher in individuals with autism, the presence of headache/migraine in individuals with and without autism was extracted and compared. To identify demographic and clinical factors associated with headache/migraine in autism, statistical analyses were performed comparing ASD with headache/migraine versus ASD without headache/migraine.

Variables

For NSCH data, topical variables of interest included those for cohort inclusion/exclusion criteria (‘HEADACHE’/Headaches and ‘K2Q35A’/Autism ASD), sociodemographic data, and variables categorized in one of the following overarching themes: (1) headache severity and ASD characteristics, (2) SDoH, (3) general health and comorbidities, (4) neuropsychiatric conditions, and (5) burden of and access to care (Table S1). Extracted UCLA EHR variables included sociodemographic data and select co‐occurring illnesses as defined by ICD‐9/10 diagnosis codes (Table S2). Severe and/or intractable migraine was defined by ICD‐9/10 codes of migraine with “status,” “intractable,” or “chronic” (Table S2). Race/ethnicity and gender were defined based on parent‐reporting (NSCH data) and by EHR categories (UCLA data).

Data extraction procedures

All NSCH data were extracted, processed, and statistically analyzed using SAS 9.4 (SAS Institute, Cary NC, UCA). All UCLA data were extracted, cleaned, and processed using Jupyter Notebook 6.5.4, Python (www.python.org, Python Software Foundation, version 3.12, Wilmington, DE, USA), and Python libraries, pandas 24 (The pandas development team. Pandas‐dev/pandas: Pandas, 2023, Version 1.5.3), and NumPy 25 (numpy.org. NumPy developers, Version 1.2.4) and analyzed using SAS 9.4.

Statistical analyses

We present descriptive statistics for demographic characteristics, including counts and percentages for categorical variables and means and standard deviations (SDs) for continuous variables. For NSCH data, we used methods that accounted for the complex survey weights provided. Sample counts and weighted frequencies are reported to reflect the survey design. Two‐way cohort comparisons were performed: (1) ASD with headache/migraine versus ASD without headache/migraine and (2) ASD with headache/migraine versus non‐ASD with headache/migraine. For NSCH demographic characteristics, complex survey data were used in logistic regression models for categorical variables and linear regression models for continuous variables (used only for age) to determine associations between cohort and variables of interest. For UCLA demographic characteristics, t‐tests and chi‐squared tests (or Fisher's exact tests) were used to assess bivariate associations between cohort and continuous and categorical data, respectively. Chi‐squared tests (UCLA data) and Rao‐Scott chi‐squared testing (NSCH data) were performed to determine significant differences in the rates of headache/migraine in individuals with and without autism.

Binary and multinomial logistic regression for complex survey data were used to calculate the odds ratio for each NSCH variable. NSCH documentation provides limited information on the missingness of data, making imputation with complex weights challenging. Thus, we did not perform imputation; rather observations with missing data on a given variable were excluded from analyses involving that variable. Overall, the proportion of missing data was very small (<5%), with only 16 models having a higher proportion of missing data, making the assumption of missing completely at random reasonable. Moreover, those models with a higher percentage of missing data were typically associated with skip or branch logic. Table S1 provides the number of observations used for each model for NSCH dataset. For NSCH and UCLA data analyses, we adjusted for age, sex, and race/ethnicity in binary or multinomial logistic regression used to calculate the adjusted odds ratio (aOR) for each variable. All UCLA data models were performed on complete cases (N = 14,358). Table 1 lists unknown/missing frequencies for each UCLA variable, and Table S2 provides the number of observations used in each model for the UCLA dataset. When applicable, we evaluated regression model assumptions, including linearity and homoscedasticity using residual plots and Q‐Q plots. We omitted models for which we observed quasi‐complete or complete separation of data points (or for which we were concerned we did not have an adequate sample size). The majority of our regression models were univariable; thus, there was limited concern for multicollinearity. In our adjusted models, included confounders (sex, race, and age) did not demonstrate risk of multicollinearity. Of note, models for complex survey data use robust variance estimation methods which aid in addressing any potential underlying model misspecification. For all models, we assumed independence of observations at the individual‐level. For all binary and multinomial logistic regression models, we report aOR, 95% confidence intervals (CI), and associated p‐values. All hypothesis tests were two‐tailed and a p‐value of <0.05 was considered statistically significant. p‐Values were not adjusted for multiple comparisons.

TABLE 1.

NSCH and UCLA cohort demographics.

NSCH cohort demographics
ASD with headache ASD without headache Non‐ASD with headache p‐Value* p‐Value**
N = 99 N = 1434 N = 1404
N (weighted %) N (weighted %) N (weighted %)
Sex
Male 66 (65.2) 1131 (76.9) 609 (41.2) 0.143 0.009
Female 33 (34.8) 303 (23.2) 795 (58.8)
Race
White 84 (76.3) 1069 (64.4) 1140 (70.6) n/a n/a
Black/African American 4 (11.3) 119 (15.4) 105 (16.2)
American Indian/Alaska Native – 14 (4.7) 18 (1.3)
Asian 1 (0.12) 71 (2.7) 26 (1.1)
Native Hawaiian/Pacific Islander 1 (0.12) 8 (0.66) 10 (3.7)
Two or more races 9 (11.7) 153 (12.2) 105 (7.1)
Ethnicity
Hispanic/Latino origin 13 (14.1) 224 (30.5) 180 (21.7) 0.070 0.329
Not Hispanic/Latino origin 86 (86.0) 1210 (69.5) 1224 (78.3)
Age in years, weighted mean (SEM) 12.7 (0.7) 10.2 (0.3) 13.1 (0.1) <0.001 0.572
Age in years, unweighted mean (SD) 13.5 (3.4) 9.8 (4.7) 13.3 (3.3) <0.001 0.580
UCLA cohort demographics
ASD with migraine ASD without migraine Non‐ASD with migraine p‐Value*** p‐Value****
N = 450 N = 13,908 N = 85,561
N (raw %) N (raw %) N (raw %)
Sex
Male 253 (56.2) 10,481 (75.4) 20,227 (23.6) <0.001 0.011
Female 197 (43.8) 3414 (24.6) 65,302 (76.3)
Other/unknown – 13 (0.09) 32 (0.04)
Race/ethnicity
Hispanic/Latino(a) 67 (14.9) 2362 (17.0) 11,773 (13.8) <0.001 <0.001
White/Caucasian 198 (44.0) 5312 (38.2) 35,530 (41.5)
Black/African American 23 (5.1) 727 (5.2) 4053 (4.7)
Asian 29 (6.4) 975 (7.0) 5563 (6.5)
Other 91 (20.2) 1662 (12.0) 15,103 (17.7)
Unknown/refused 42 (9.3) 2870 (20.6) 13,539 (15.8)
Marital status
Married/partner 32 (7.1) 193 (1.4) 38,805 (45.4) <0.001 <0.001
Single/divorced/separated/widowed 402 (89.3) 12,569 (90.4) 41,764 (48.8)
Other/unknown 16 (3.6) 1146 (8.2) 4992 (5.8)
Age in years, mean (SD) 26.6 (13.1) 19.7 (12.0) 47.9 (17.5) <0.001 <0.001
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Note: Raw Ns and weighted percentages for NSCH data and raw Ns and unweighted percentages for UCLA data are listed for each variable, sex, race/ethnicity, marital status, and age. Significance values for two‐way comparisons are provided: autism spectrum disorder (ASD) with headache versus ASD without headache (p‐value*), ASD with headache versus non‐ASD with headache (p‐value**), ASD with migraine versus ASD without migraine (p‐value***), and ASD with migraine versus non‐ASD with migraine (p‐value****).

Abbreviations: ASD, autism spectrum disorder; NSCH, National Survey of Children's Health; UCLA, University of California Los Angeles.

RESULTS

Cohort demographics

NSCH cohort demographics

Of the 50,892 participants of the 2021 NSCH, three cohorts were identified: (1) ASD with headache (N = 99), (2) ASD without headache (N = 1434), and (3) non‐ASD with headache (N = 1404). Headache in the NSCH cohorts is defined as “frequent or severe headaches, including migraine,” and likely represents a mix of migraine and non‐migraine headache types. Two‐way comparisons of demographic data were performed between ASD with headache vs. ASD without headache (Table 1, p‐value*) and ASD with headache vs. non‐ASD with headache (Table 1, p‐value**). Unweighted mean age and SD estimates of age aligned with weighted results with significant differences in mean age between ASD with headache vs. ASD without headache (unweighted mean age [SD], 13.5 years [3.4] vs. 9.8 years [4.7], p < 0.001), but not between ASD with headache versus non‐ASD with headache (13.5 years [3.4] vs. 13.3 years [3.3], p = 0.580). There were no significant differences in sex between ASD with headache vs. ASD without headache (N = female [weighted %], 33 [34.8%] vs. 303 [23.2%], p = 0.143). Comparisons of race/ethnicity data yielded sparse cells for categorical variables, thus, “n/a” (not applicable) is listed instead of p‐values (Table 1).

UCLA cohort demographics

Of the 4,334,162 unique patients in the UCLA EHR, three cohorts were identified: (1) ASD with migraine (N = 450), (2) ASD without migraine (N = 13,908), and (3) non‐ASD with migraine (N = 85,561). Two‐way comparisons of demographic data were performed between ASD with migraine vs. ASD without migraine (Table 1, p‐value***) and ASD with migraine versus non‐ASD with migraine (Table 1, p‐value****). Mean age, sex, race/ethnicity, and marital status differed significantly between both two‐way comparisons. For ASD with migraine versus ASD without migraine, the following was observed‐ mean age (SD): 26.6 years (13.1) versus 19.7 (12.0), p < 0.001; N = female (unweighted %): 197 (43.8%) versus 3414 (24.6%), p < 0.001; and White/Caucasian race/ethnicity: 198 (44.0%) versus 5312 (38.2%), p < 0.001 (Table 1).

Headache and migraine prevalence, severity, and sex differences in individuals with autism

Using NSCH data, the prevalence of headache in children with and without autism was assessed over 4 years from 2018 to 2021. Across this period, headache prevalence was higher in children with autism compared to children without autism (Figure 1A). Using UCLA data, the prevalence of migraine was assessed in individuals with and without a diagnosis of autism for all available years. Migraine rates were higher in individuals with a diagnosis of autism compared to those without (% [95% CI]: ASD population: 3.1% [2.86–3.43], N = 450/14,358 vs. non‐ASD population: 2.0% [1.97–1.99], N = 85,561/4,319,804, p < 0.001) (Figure 1B). The aOR with 95% CI for headache/migraine prevalence for ASD with headache/migraine cohorts is provided in Figure 1C.

FIGURE 1.

FIGURE 1

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Headache & migraine prevalence, severity, and sex differences in autism spectrum disorder (ASD). (A) Headache prevalence is graphed over time for NSCH data (years 2018 through 2021) in individuals with ASD (gray line) and without ASD (black line). Weighted percentages adjusted for age, sex, race, and ethnicity as covariates are graphed. Headache in ASD cohort weighted percentages of headache are as follows: Headache % [95% CI]—2018: 7.5% [4.71–10.36]; 2019: 11.0% [4.32–17.60]; 2020: 5.0% [3.36–6.64]; 2021: 7.1% [4.62–9.56]. Asterisks denote significance based on Rao‐Scott chi‐squared testing. (B) Percentage of those with a diagnosis of migraine is graphed for individuals with versus without a diagnosis of ASD (gray vs. black bar, respectively (3.1% [2.86–3.43] vs. 2.0%, [1.97–1.99]). Asterisks denote significance based on chi‐squared testing. (C) Forest plots show adjusted odds ratio (aOR) for headache/migraine in those with ASD compared to those without. Point estimate for ASD with headache/migraine cohort is graphed with 95% confidence intervals (95% CI) listed and graphed as error bars. (D) Forest plots show aOR for each variable (female, reporting severe or moderate headache, and being diagnosed with a severe/chronic/intractable migraine). Point estimate for ASD with migraine/headache cohort is graphed with 95% CI. Cohort comparison is provided. References: Male, mild headache, and “no” diagnosis of a chronic/intractable/status migrainosus). Significance notations:* p < 0.05; **p < 0.01; ***p < 0.001; ns, not significant. Forest plots graphed with logarithmic x‐axis.

Among individuals with autism, the odds of being female (compared to male) was non‐significantly increased in those with headache versus those without headache (NSCH: ASD with headache “female” aOR = 2.28 [0.99–5.22], p = 0.052) and significantly increased in those with migraine versus those without migraine (UCLA: ASD with migraine “female” aOR = 2.22 [1.83–2.69], p < 0.001) (Figure 1D).

For NSCH data, odds of a severe headache (versus mild) were significantly increased in those with autism compared to those without (“severe” aOR = 4.33 [1.25–15.04], p = 0.021) (Figure 1D). UCLA data demonstrated a moderate, non‐significant increase in migraine severity in the ASD with migraine cohort vs. non‐ASD with migraine cohort (Figure 1D).

Socioeconomic characteristics and co‐occurring conditions in individuals with autism and headache

NSCH—Autism characteristics and neurodevelopmental conditions

NSCH data showed no difference in the odds of moderate or severe autism, the presence of a genetic condition, or other neurodevelopmental conditions (intellectual or learning disability, developmental delay, speech disorder, or cerebral palsy) between the ASD with headache and ASD without headache cohorts (Figure 2, ASD Severity and Neurodevelopmental Conditions & Characteristics). Neither were there any significant differences in the use of special services, special therapies, or special education plans. Yet, individuals with ASD and headache were more likely to require greater medical care compared to others (“yes” aOR = 5.11 [2.07–12.62], p < 0.001) and currently use/need medications than individuals with ASD without headache and currently use/need medications (Figure 2).

FIGURE 2.

FIGURE 2

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Socioeconomic factors and co‐occurring illnesses associated with the presence of headache & migraine in autism spectrum disorder (ASD). National Survey of Children's Health (NSCH) survey data and University of California Los Angeles (UCLA) International Classification of Diseases (ICD) diagnosis codes were compared among individuals with ASD and headaches/migraine versus ASD without headache/migraine. Forest plots show adjusted odds ratios with 95% confidence interval (CI) listed and graphed as error bars. Point estimates for the ASD with headache or ASD with migraine cohort are graphed for each variable. Response profile for each variable is provided. Reference is ‘No’ unless otherwise noted. Adjusted point estimates (adjusted odds ratio [aOR]) are graphed for all variables. Data are graphed on a logarithmic x‐axis.

NSCH—SDoH

Analysis of parental responses to questions focused on exposure to adverse childhood experiences (ACEs) show that children with autism and headaches were more likely to experience ACEs compared those without headache, including being a victim of violence and experiencing daily to weekly bullying (Figure 2, SDoH). Additionally, the ASD with headache cohort was more likely to be treated unfairly based on their race, health condition, and sexual orientation/gender identity. There were no statistically significant differences in parental educational attainment or the use of government assistance programs such as cash assistance, food stamps, free/reduced cost meals, or Women/Infants/Children (WIC) programs. Nor were there clear differences in community/social support or neighborhood characteristics between the two cohorts (Table S1, Social Determinants of Health). However, parents of the ASD with headache cohort were more likely to endorse difficulty covering basics such as food and housing and difficulty in caring for their child (Figure 2, SDoH).

NSCH—General health and comorbidities

Among children with autism, parents were likely to describe their child's health as fair or poor (“fair/poor” aOR = 9.68 [3.01–31.19], p < 0.001, “excellent” reference). This cohort was more likely to visit the emergency room and be admitted to the hospital over the past year and frequently missed school (11 or more days per year) secondary to injury or illness (Figure 2, General Health and Comorbidities). Children with autism and headache had increased odds of an abnormal body mass index (BMI; both high and low) compared to children with autism without headache. The ASD with headache cohort also showed increased odds of asthma, stomach difficulty, variability in bedtime, and reduced hours of sleep.

NSCH—Neuropsychiatric conditions

Odds of parental‐reported concussion were significantly increased in the ASD with headache cohort compared to the ASD without headache cohort (“yes” aOR = 9.05 [3.19–25.66], p < 0.001). Among children with autism, anxiety and depression occurred more frequently in those with headache versus those without headache. Anxiety was more severe in the ASD with headache cohort (“severe anxiety” aOR = 5.61 [1.94–16.28], p = 0.002, “mild” as reference). ADD/ADHD and behavioral problems were higher in the ASD with headache cohort compared to ASD without headache cohort. There were no significant differences in the odds of epilepsy between the two cohorts (Figure 2, Neuropsychiatric Conditions).

NSCH—Burden of and access to care

Compared to the ASD without headache cohort, the ASD with headache cohort was more likely to visit the doctor and need specialist care. Notably, parents of this cohort reported increased odds of not seeing a specialist despite the child needing one (aOR = 7.62 [2.09–27.83], p = 0.002). There was no significant difference in access to care and insurance coverage between the two cohorts. Yet, the ASD with headache cohort was more likely to report a lack of insurance coverage for services needed and problems paying for healthcare (Figure 2, Access to Care).

UCLA data—Co‐occurring illnesses

Twenty illnesses/conditions of interest were selected and compared between ASD with migraine and ASD without migraine cohorts in the UCLA data (Table S2). Outcomes adjusted for age, sex, and race/ethnicity are presented with 95% CIs (aOR [95% CI]) (Figure 2, UCLA Co‐occurring Illnesses). There were no differences in the odds of intellectual disability, behavioral problems, or cerebral palsy. However, the odds of learning or speech disabilities were increased in the ASD with migraine vs. ASD without migraine cohort. The ASD with migraine cohort also had higher odds of a diagnosis of underweight, overweight, and obesity. Odds of diabetes, asthma, sleep disorders, and gastrointestinal (GI) upset were increased in the ASD with migraine vs. ASD without migraine cohort. Neuropsychiatric diagnoses of ADD/ADHD, anxiety, depression, and epilepsy were elevated in the ASD with migraine cohort. Odds of concussion (aOR = 10.28 [6.91–15.30], p < 0.001) were increased in the ASD with migraine cohort (Figure 2, UCLA Co‐occurring Illnesses, Table S2).

DISCUSSION

Elevated migraine in autism and its clinical implications

In this retrospective study using NSCH data, headache prevalence in children with autism ranged from 5.0 to 11.0% from 2018 to 2021, a rate significantly higher (over two to three times higher) than in children without autism in this study. Using UCLA data, migraine prevalence was 3.1% in individuals with a diagnosis of autism, significantly higher than in individuals without a diagnosis of autism (2.0%) (Figure 1A–C). It should be noted that robust studies estimate a mean prevalence of headache at 54.4% and migraine at 9.1% in children. 26 Thus, the headache and migraine rates reported in our study are significantly lower.

In agreement with prior studies, 17 , 18 , 19 , 20 we observed higher rates of migraine in individuals with autism compared to those without. Our rates of headache (5%–11%) and migraine (3%) in individuals with autism are similar to observed rates in other studies in which participants were recruited from the general population via national survey or from non‐specialized clinical settings. 27 , 28 , 29 Studies that recruit participants from subspeciality clinics or neurodevelopment‐focused settings report higher rates of migraine in autism (20%–61%), potentially reflecting a selection bias (e.g. Berkson's bias), or perhaps, underdiagnosis of migraine in autism within the general population and general healthcare system. 17 , 18 , 19 Utilization of subspecialty services is high in autism and those with autism have a four times higher odds of seeking neurological subspecialty services compared to those without. 30 , 31 , 32 Increased rates of migraine observed in this setting suggest subspecialty neurology/neurodevelopmental care may serve as a valuable entry point to improve headache management in autism.

Despite high utilization of subspecialty services, it is important to note that the majority of autism management is conducted through the pediatrician and other primary healthcare providers. 30 Migraine is underdiagnosed and undertreated in the general population. 33 , 34 Individuals with autism may be more susceptible to delays in migraine diagnosis and treatment given known barriers in communication, competing medical concerns within a clinical visit, and reduced access to healthcare services. 35 , 36 In the face of these challenges, this study and others underscore the importance of not overlooking migraine symptoms in individuals with autism for both the general provider/pediatrician and neurologist/sub‐specialist.

Sex differences and headache severity in autism

Sex differences for migraine (M:F ratio of 1:3) 37 and autism (M:F ratio of 3:1) 6 are well reported within the literature and reflected in our demographic data (Table 1). In both datasets, among those with autism, the odds of being female was over two times higher in individuals with headache/migraine compared to those without, confirming a predilection for migraine in females with autism (Figure 1D). We hypothesized headache/migraine severity would be increased in those with autism compared to those without. In NSCH data, the odds of severe headache were over four times higher in those with autism, compared to those without autism. UCLA data demonstrated a significant, albeit moderate increase in the odds of severe headache (status migrainosus/chronic/intractable migraine) (Figure 1D). Challenges in communicating migraine symptoms (e.g., photophobia, nausea, visual aura), severity, and frequency may contribute to reduced caregiver/provider awareness of the full impact of migraine in this patient population. Further studies are needed to explore migraine characteristics (subtype, chronicity) and expression patterns (e.g., behavioral, mood, sleep disturbances) as well as access to migraine care in autism.

Interactions between ACEs, co‐occurring illnesses, and migraine in autism

NSCH data revealed a striking increase in the odds of several ACEs in individuals with autism and headache, including exposure to bullying, discrimination, and violence. ACEs such as childhood maltreatment, physical, sexual, and emotional abuse are associated with migraine and hypothesized to modulate migraine expression. 38 , 39 , 40 , 41 , 42 The effect of ACEs on migraine is dose‐dependent whereby an increased number of ACEs portends higher prevalence and increased headache severity. 38 , 41 , 43 This is notable as children with autism are at greater risk for ACEs compared to individuals without autism and have a two‐fold relative risk of having four or more ACEs. 44 , 45 Thus, the presence of ACEs may serve as a driving mechanism for the expression of migraine in autism. Overlapping comorbidities in migraine and autism such as depression/anxiety and obesity can modulate the relationship between ACEs and migraine. 39 , 40 Additional studies are needed to determine whether increased rates of migraine in autism are dependent or independent of these ACEs, whether the type of and/or number of ACEs are important in this association, and whether the increased odds of ACEs in those with autism and migraine are independent of overlapping comorbidities.

In this study, those with autism and concurrent headache/migraine were more likely to report poor health and a diagnosis of a weight problem. Asthma, a comorbidity of migraine, was increased in ASD with headache/migraine cohort. 46 Across both NSCH and UCLA data, the odds of neuropsychiatric conditions, sleep disturbances, and GI upset were increased in the ASD with headache/migraine vs. ASD without headache/migraine cohort. Each of these are associated with migraine and migraine chronification. 8 In autism, rates of depression, sleep disturbances, and GI upset are all elevated compared to those without and are known to drive poor clinical outcomes in autism. 47 , 48 , 49 Thus, the elevated odds of each of these co‐occurring illnesses in those with concurrent autism and migraine raises several questions: Are these illnesses driving migraine frequency/severity in autism? Does migraine modulate the expression of these conditions and/or behavioral changes in autism? Is the relationship between certain conditions and migraine and autism unilateral, bilateral, or synergistic? Higher rates of migraine have been observed in those with concurrent ASD and ADHD versus those with only ASD. 20 Thus, the presence of specific comorbidities and/or multiple neurodevelopmental diagnoses may impact migraine expression. Further investigation is needed to determine if identification of specific clinical characteristics can effectively screen and risk‐stratify individuals for migraine in autism.

Finally, in both datasets, we observed striking increases in the odds of concussion in ASD with headache/migraine cohorts vs. ASD without headache/migraine. In the general population, migraine‐like symptoms are common post‐concussion. 50 However, there are few to no data examining rates of concussion and/or post‐concussive headache in individuals with autism. 51 Repetitive head banging, impulsivity, frequent elopement, and/or reduced motor awareness might all contribute to the observed increased odds of concussion in autism and migraine. Studies are needed to clarify these mechanisms as well as determine if individuals with autism are at increased risk for the development of migraine post‐concussion.

STUDY LIMITATIONS

This study did not adjust for overlapping comorbidities such as depression, anxiety, GI upset, etc. Use of a multimorbidity index in future studies may offer a valuable method of adjusting for the complex interactions of common comorbidities in migraine and autism. Other study limitations include a lack of diversity of the NSCH population and a reliance on parent/guardian‐reported diagnosis of autism and headache for NSCH data. Prior studies show parents under‐report their child's chronic pain symptoms such as severity, frequency, and associated functional disability. 52 When comparing self‐ versus parent‐proxy report of general health and well‐being, adolescents reported significantly lower/poorer general health, mental health, and higher bodily pain compared to parent report. 53 Given our reliance on parent report of clinical symptoms for NSCH data, our results may underestimate the rates and/or severity headache as well as other clinical symptoms such as anxiety, depression, and severity of autism.

This study is also limited by the reliance on provider diagnosis and ICD code documentation of autism, migraine, and co‐occurring illnesses for UCLA data. Individuals with autism face numerous barriers to obtaining healthcare treatment. 35 , 54 Thus, our reliance on ICD coding for assessment of co‐occurring illnesses and migraine severity is limited by both the individual presenting to the healthcare system and the physician accurately diagnosing and coding the illness within the time constraints of a structured clinical visit. Moreover, difficulty or barriers to communicating pain severity, headache frequency, and associated symptoms may also impact rates of headache/migraine in our study. Overall, both data sources (NSCH and UCLA EHR) likely underestimate the rates of headache/migraine in autism as well as the occurrence of associated clinical characteristics. It should be noted that UCLA EHR data spanned from 1979 to 2023 to capture as many individuals as possible with a concurrent diagnosis of autism and migraine. Yet, over these decades, reported rates of autism and migraine have both increased and diagnostic coding practices have evolved, as have cultural perspectives on neurodevelopment, mental health, and neurodivergent populations. A larger cohort study over a more narrow and recent time‐period would offer better insight into the current diagnosis rates of migraine in autism.

Finally, this is a retrospective study; thus, the potential for recall bias (e.g., parental recall of NSCH data), selection bias (e.g., cases selected from an academic, tertiary care center), and misclassification bias (e.g., retrospective selection of UCLA EHR cohorts) exist. The analysis of two separate data sets—NSCH and UCLA EHR—was used to increase the validity of our findings in the face of these potential biases. Future prospective studies using validated diagnostic tools for migraine and autism as well as established patient reported outcome measures are needed to address these study limitations. Based on our results, the autism population may benefit from targeted screening to identify, diagnosis, and manage migraine.

CONCLUSIONS

In this retrospective study using two data sources, headache and migraine prevalence was increased in individuals with autism compared to individuals without autism. Headache and migraine severity were increased in those with autism compared to those without. Headache and migraine in autism was associated with increased odds of ACEs, neuropsychiatric conditions, and concussion. Based on our results, the autism population may benefit from targeted screening to identify, diagnosis, and manage migraine.

AUTHOR CONTRIBUTIONS

Maria Pia Grant Tejada: Conceptualization; data curation; methodology; validation; writing – review and editing. Alexandra M. Klomhaus: Data curation; formal analysis; methodology; validation; writing – review and editing. Rebecca Ortiz: Validation; visualization; writing – review and editing. Tristan D. Tibbe: Formal analysis; methodology; writing – review and editing. Sinifunanya E. Nwaobi: Conceptualization; data curation; formal analysis; funding acquisition; investigation; methodology; resources; software; supervision; validation; visualization; writing – original draft; writing – review and editing.

FUNDING INFORMATION

This study was supported by an Amgen Competitive Research Award (2022). Amgen had no role in the design and conduct of the study.

CONFLICT OF INTEREST STATEMENT

Sinifunanya Nwaobi received a competitive research award from Amgen and Pfizer. Maria Pia Grant Tejada, Alexandra M. Klomhaus, Rebecca Ortiz, and Tristan D. Tibbeno report no conflicts of interest.

Supporting information

Table S1. Categorization of NSCH Topical Variables and Associated ASD with Headache Odds Ratios. Topical name, description, response profile, and reference response are listed. This table indicates cohort comparison as well as point estimate for the ASD and headache cohort, 95% upper and lower confidence intervals (95% CI), and p‐value. Number of observations used in each model is listed.

HEAD-66-712-s002.docx (41KB, docx)

Table S2. ICD‐9 and ICD‐9 Codes Evaluated for Co‐occurring Illnesses. Full list of the ICD‐9 and ICD‐10 codes used to evaluate co‐occurring illnesses in the UCLA data. Assigned disease category is listed. Number of unique patients and percent (%) of total cohort in each category is listed.

HEAD-66-712-s001.docx (29.4KB, docx)

ACKNOWLEDGMENTS

This work was supported by Amgen Competitive Grant Program in Migraine Research 2022. Additional support included the UCLA CTSI Bioinformatics (NIH/NCATS Grant UL1TR001881). The authors are deeply appreciative of publicly accessible NSCH data and the families that participated.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1. Categorization of NSCH Topical Variables and Associated ASD with Headache Odds Ratios. Topical name, description, response profile, and reference response are listed. This table indicates cohort comparison as well as point estimate for the ASD and headache cohort, 95% upper and lower confidence intervals (95% CI), and p‐value. Number of observations used in each model is listed.

HEAD-66-712-s002.docx (41KB, docx)

Table S2. ICD‐9 and ICD‐9 Codes Evaluated for Co‐occurring Illnesses. Full list of the ICD‐9 and ICD‐10 codes used to evaluate co‐occurring illnesses in the UCLA data. Assigned disease category is listed. Number of unique patients and percent (%) of total cohort in each category is listed.

HEAD-66-712-s001.docx (29.4KB, docx)

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