Photophobia is associated with lower sleep quality in individuals with migraine: Results from the American Registry for Migraine Research (ARMR)

Photophobia is associated with lower sleep quality in individuals with migraine: Results from the American Registry for Migraine Research (ARMR) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Photophobia is associated with lower sleep quality in individuals with migraine: Results from the American Registry for Migraine Research (ARMR) Nina Sharp, Mark J Burish, Kathleen B Digre, Jessica Ailani, Mahya Fani, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3864442/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Apr, 2024 Read the published version in The Journal of Headache and Pain → Version 1 posted 7 You are reading this latest preprint version Abstract Background. Patients with migraine often have poor sleep quality between and during migraine attacks. Furthermore, extensive research has identified photophobia as the most common and most bothersome symptom in individuals with migraine, second only to headache. Seeking the comfort of darkness is a common strategy for managing pain during an attack and preventing its recurrence between episodes. Given the well-established effects of daily light exposure on circadian activity rhythms and sleep quality, this study aims to investigate the relationship between photophobia symptoms and sleep quality in a cohort of patients with migraine. Methods. A cross-sectional observational study was conducted using existing data extracted from the American Registry for Migraine Research (ARMR). Participants with a migraine diagnosis who had completed the baseline questionnaires (Photosensitivity Assessment Questionnaire (PAQ), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-2 (PHQ-2)), and selected questions of the ARMR Sleep questionnaire were included. Models were created to describe the relationship of photophobia and photophilia with various sleep facets, including sleep quality (SQ), sleep disturbance (SDis), sleep onset latency (SOL), and sleep-related impairments (SRI). Each model was controlled for age, sex, anxiety, and depression. Results. A total of 852 patients meeting the inclusion criteria were included in the analysis (mean age (SD) = 49.8 (13.9), 86.6% (n = 738) female). Those with photophobia exhibited significantly poorer sleep quality compared to patients without photophobia (p < 0.001). Photophobia scores were associated with SQ (p < 0.001), SDis (p < 0.001), SOL (p = 0.011), and SRI (p = 0.014), after controlling for age, sex, depression, and anxiety, signifying that higher levels of photophobia were associated with worse sleep-related outcomes. Conversely, photophilia scores were associated with better sleep-related outcomes for SQ (p < 0.001), SDis (p < 0.001), and SOL (p = 0.016). Conclusion. Results suggest that photophobia is a risk factor for sleep disorders in those with migraine. These results underscore the necessity for comprehensive and systematic investigations into the intricate interplay between photophobia and sleep to enhance our understanding and develop tailored solutions for individuals with migraine. Migraine Headache Photophobia Sleep Photophilia Light Circadian 1. Background A migraine attack consists of moderate-to-severe intensity throbbing headache accompanied by a combination of sensory hypersensitivities (e.g., photosensitivity, phonosensitivity, olfactory hypersensitivity, cutaneous allodynia), nausea, and vomiting [ 1 , 2 ]. Photophobia, defined here as discomfort caused by light and exacerbation of headache by light, is exceedingly prevalent during migraine attacks and can persist, typically to a lesser extent, between attacks [ 3 , 4 ]. Moreover, numerous migraine studies reported photophobia as the most common, most bothersome symptom other than headache [ 5 – 8 ]. Generalized photophobia (i.e., both ictally and interictally) has been linked to several aspects of migraine: higher generalized photophobia is more common in migraine with aura (MwA) compared to those without aura (MwoA) [ 9 ] and higher photophobia scores are associated with greater work-related disability and activity impairment [ 10 ]. Individuals with migraine also often report poor sleep quality and sleep disturbances, both as triggers of migraine attacks and as a consequence of the attacks [ 11 ]. These disturbances manifest as difficulty falling asleep, staying asleep, self-reported decreased sleep duration, extreme daytime sleepiness, and lack of feeling refreshed after sleep [ 12 – 16 ]. Despite substantial growth in the literature over the past two decades, the precise nature and direction of the relationship between sleep and migraine remains elusive. It is conceivable that sleep disturbances are caused by an ongoing migraine attack or sleep disruption may trigger migraine attacks. There are multiple lines of evidence to suggest that photophobia and sleep might be related in migraine. Clinically, in two open-label studies green light improves not only headaches but also photophobia and sleep [ 17 , 18 ], though these data are confounded by the fact that the headaches also improved. Mechanistically, photophobia and light may be related through the circadian system. Light, especially bright light, is the strongest zeitgeber (an environmental cue which resynchronizes our internal biological clock to the external world), and the circadian system regulates the sleep-wake cycle [ 19 ]. Specifically, light received through signals from the intrinsically photosensitive retinal ganglion cells (ipRGCs) synchronizes the rhythmic activity of the central clock in the hypothalamus, the suprachiasmatic nuclei (SCN). There are several lines of evidence that migraine has circadian properties, including lower melatonin levels amongst those with migraine and a circadian pattern of attacks; moreover, a variation in a core circadian gene – CK1δ –causes both migraine and a circadian rhythm disorder (advanced sleep phase) [ 20 , 21 ]. Epidemiologically, the Korean Sleep-Headache Study performed latent class analysis and ultimately subtyped patients into 3 groups, one of which was an ictal photophobia/phonophobia group [ 22 ]. This photophobia/phonophobia group had the highest proportion of patients with excessive daytime sleepiness on the Epworth Sleepiness Scale, though the findings were not significant (p = 0.13) possibly due to the relatively modest enrollment (n = 125 across 3 groups). However, an even smaller study (n = 48) comparing migraine patients with interictal photophobia, did find a statistically significant change in sleeping patterns compared to healthy controls and migraine patients without interictal photophobia [ 23 ]. Researchers attributed these findings to the concurrent symptoms of depression and anxiety, commonly associated with migraine [ 23 ], suggesting that generalized photophobia might have a stronger relationship with sleep than interictal photophobia, but that mood disorders could be confounders that need to be taken into account. Light, or rather the lack of light, may be important in migraine patients with photophobia. During a migraine attack, a common behavioral intervention is to seek the comfort of darkness. In one large survey, more than 92% of 2735 participants reported using a dark room during a migraine attack and more than 83% reported it as a consistent strategy to treat their pain [ 24 ]. Therefore, it is likely that individuals with migraine with photophobia may experience lower levels of daily light exposure. Given the non-image forming effects of light on circadian rhythms and sleep, we hypothesize that lack of exposure to proper lighting could be contributing to or exacerbating the sleep disturbance experienced by individuals with migraine who have photophobia. However, current literature lacks research that fully investigates the relationship between photophobia in migraine and prevalence of sleep disturbance and poor sleep quality. In this study, we investigated the relationship between photophobia and sleep (poor sleep quality and sleep disturbance) in individuals with migraine. We hypothesized that generalized photophobia would be associated with poor sleep quality and sleep disturbances in people with migraine even after accounting for the effects of depression and anxiety. 2. Methods We conducted a cross-sectional observational analysis using existing data extracted from the American Registry for Migraine Research (ARMR)—a multicenter, prospective, longitudinal patient registry, biorepository, and neuroimaging repository [ 7 , 9 ]. ARMR systematically collected data from individuals experiencing primary and secondary headaches as classified by the ICHD 3 [ 7 ]. ARMR includes information related to patients' demographics and types of headaches diagnosed by headache specialists at the medical facilities where they enrolled. Participants completed a set of baseline questionnaires on headache features, personal medical history, sleep quality, anxiety, depression, and photosensitivity, among others. A detailed description of ARMR methods and baseline data have been previously published [ 7 ]. 2.1. Research Participants Patients included within this analysis of ARMR data were recruited from specialty headache clinics at Mayo Clinic Arizona, University of Utah, University of Texas Health Science Center at Houston, University of Colorado, Georgetown University Medical Center, DENT Neurologic Institute, Dartmouth-Hitchcock Medical Center, Thomas Jefferson University Headache Center, and Yale University. Inclusion criteria for the analysis presented in this study were a clinician diagnosis of migraine according to ICHD-3 diagnostic criteria and completion of the baseline questionnaires by the time of data extraction in July 2023. The research was performed in accordance with the Declaration of Helsinki and was approved by the Mayo Clinic Institutional Review Board as well as the Institutional Review Boards of each enrolling site mentioned above. All research participants completed and signed an informed consent document. 2.2. Study Questionnaires Photosensitivity. Photosensitivity was evaluated using the Photosensitivity Assessment Questionnaire (PAQ) [ 25 , 26 ]. The PAQ is a self-reported, validated questionnaire that examines behavioral sensitivity to light and psychopathological traits. The questionnaire includes 16 items specifically designed to assess two distinct aspects: “light-avoiding” behaviors associated with photophobia (8 questions) and “light-seeking” behaviors related to photophilia (8 questions). The PAQ utilizes a dichotomous response format, where participants are presented with “Yes” or “No” options to answer each question. Negative answers are rated “0” and affirmative answers are rated “1” for a total score between 0 and 8 for each of the photophobia and photophilia scales. A third score, the global photosensitivity score is obtained through taking the difference between the photophilia and photophobia scores and dividing it by 8. This global score ranges between − 1 (extreme photophobia) and 1 (extreme photophilia) [ 27 ]. In this study, we included all 3 scores (photophobia, photophilia, and global photosensitivity scores) in our analysis. Sleep. A self-rated questionnaire was employed in ARMR to assess sleep quality of participants. The questionnaire consists of 50 questions asking participants to provide information on their typical sleep issues as well as their sleep duration, sleep onset latency, and sleep time at night, among others. To calculate the sleep quality (SQ) in this study, we selected 16 questions that covered sleep disturbance (10 questions), sleep duration (one question), sleep onset latency (one question), use of sleep medication (one question), daytime dysfunctioning (two questions), and subjective sleep quality (one question). The one question for sleep duration asked patients to report their average number of sleep hours during the prior three months while the question on sleep onset latency (SOL) inquired about the number of minutes typically taken to fall asleep during the same period. The questions related to sleep disturbance (SDis) explored the frequency of nighttime or early morning awakenings due to need to use the bathroom, bad dreams, teeth grinding, involuntary limb or body movements, headache or migraine symptoms, stomach pain, non-headache pain, anxiety, depression, and other reasons. Furthermore, the daytime dysfunctioning questions aimed to collect data on participants' level of enthusiasm and ability to carry out scheduled activities and daily tasks. The one question on sleep medication asked patients on the frequency of taking medications to aid with sleep in the past three months. Lastly, the subjective sleep quality question asked patients to rate the average quality of their sleep in the prior three months. Each question, except for the subjective sleep quality question, was scored on a scale from 0 to 6, where 0 indicated no difficulty or disturbance, and 6 indicated severe difficulty or disturbance. The subjective sleep quality question was scored between 0 and 4, where 0 indicated good quality of sleep, and 4 indicated very poor sleep. The component scores were then summed to generate the total SQ score, which ranged from 0 to 94. Higher scores indicated lower levels of sleep quality and more significant sleep disturbance. While the SDis was included in the overall SQ score, we extracted the score separately for further analysis. A distinct analysis was performed on the reported minutes of SOL by patients. We also incorporated an assessment of sleep-related impairment (SRI) in our analysis by including four selected questions that measured daytime sleepiness due to poor sleep quality at night. These questions asked patients to report any challenges related to waking up in the morning, feeling drowsy upon waking, experiencing daytime sleepiness, and facing daytime issues due to poor sleep at night. Each question was scored on a scale from 0 to 4, with 0 indicating the absence of daytime sleep-related impairment and 4 indicating significant sleep-related impairment. These individual scores were subsequently summed to generate the total score for sleep-related impairment that ranged from 0 to 16. The selected questions could be found in the supplemental materials of this manuscript. Anxiety. An evaluation of anxiety symptoms was carried out using the Generalized Anxiety Disorder-7 (GAD-7) assessment tool. The GAD-7 is a short and easy-to-use 7-item scale that has been found to have reliable psychometric properties [ 28 ]. The scale examines the frequency of anxiety symptoms experienced by an individual during the preceding two weeks. Response options include “not at all,” “several days,” “more than half the days,” and “nearly daily,” corresponding to scores of 0, 1, 2, and 3, respectively. The scores of 5, 10, and 15 are considered as thresholds for indicating mild, moderate, and severe anxiety, respectively [ 29 ]. Depression. The Patient Health Questionnaire-2 (PHQ-2) was employed to screen symptoms of depression. The PHQ-2 is a short self-assessment tool consisting of two simple questions that assess the occurrence of depressed mood and anhedonia over the past two weeks. Similar to GAD-7, there are four response options, “not at all,” “several days,” “more than half the days,” and “nearly daily,” which are respectively assigned scores of 0 to 3. The accumulated scores of the two questions yield a total score, ranging from 0 to 6. A score of 3 is established as a cut point for major depressive disorders, whereas a score of 2 suggests potential depressive disorders [ 30 ]. The PHQ-2 has been recognized as a valid and reliable screening instrument for identifying depressive disorders in patients with migraine [ 31 ]. 2.3. Statistics Data were managed and analyzed using IBM SPSS 28.1 statistical software. In this analysis, the scores from PAQ, the sleep questionnaire, PHQ-2, and GAD-7 were treated as continuous variables due to their extensive distribution covering the full range of possible scores. Descriptive statistics (mean and standard deviation (SD), median (interquartile range), or number (percentage)) were employed to describe the characteristics of sample such as age, sex and race, as well as the prevalence of photophobia, migraine with/without aura, years with migraine, depression, and anxiety. We conducted independent sample t-tests to compare SQ, SDis, SOL, and SRI in patients with and without photophobia. Cohen's d test was used to find the effect size of photosensitivity on various metrics of sleep. Separate multiple linear regression models were developed to examine the relationship between the severity of photophobia and SQ, SDis, SOL, and SRI. Similarly, regression models were established to probe the link between photophilia and SQ, SDis, SOL, and SRI. Each regression model generated an R 2 value as well as a corresponding P Value for the entire model, alongside individual P values for each predictor variable. Diagnostic plots were employed to confirm that all the assumptions for linear regression modeling were met. The SOL data underwent a logarithmic transformation to ensure that the assumption of normality for the linear regression was satisfied. Regression models were adjusted by accounting for age and sex as covariates. Previous research has highlighted a bidirectional causal relationship between psychiatric symptoms, notably anxiety/depression, and sleep disorders [ 32 – 36 ]. Additionally, a significant correlation has been shown to exist between anxiety/depression and photophobia [ 23 , 37 ]. In light of these insights, our analysis integrated the scores of anxiety (GAD-7) and depression (PHQ-2) as covariates in the regression models, aiming to isolate the specific influence of photophobia or photophilia on sleep. We also utilized Cohen’s f 2 to find individual effect sizes of photophobia and photophilia on the sleep-related variables measured in this study. For all analysis, two-tailed hypothesis testing was employed, and statistical significance was set at 95% ( P < 0.05). We did not conduct an a priori power analysis since the sample size was based on available data. 3. Results 3.1. Demographics In total, 852 patients met the inclusion criteria, provided the covariate information, and answered all selected questions related to sleep (Table 1 ). Patients were 86.6% female (n = 738) and 13.4% male (n = 114). The mean (SD) age was 49.79 (13.91) years (range = 22–90, n = 852). All patients were diagnosed with migraine and 27.1% of them had a migraine with aura diagnosis (n = 231). The mean headache days per month were 19.1 (9.1) and the mean duration of living with headaches was 24.1 (16.6) years. 3.2. Baseline photophobia and sleep characteristics The mean score of the PHQ-2 was 1.47 (1.64), and 22.7% of patients (n = 193) surpassed the screening cutoff of 2 for potential depressive disorders while 19.8% (n = 169) exceeded the cutoff of 3 for major depressive disorder. As for the GAD-7, mean score was 5.87 (5.07), with 8.9% (n = 76) of participants meeting the screening threshold for severe anxiety, 10.9% (n = 93) for moderate anxiety, and 31.9% (n = 272) for at least mild anxiety. The mean global score of the photosensitivity questionnaire, which does not differentiate between photosensitivity during and between migraine attacks, was 0.11 (0.55) suggesting a photophilic inclination. Totally, 35.6% of patients (n = 303) recorded scores below 0, indicating some degree of photophobia. Conversely, about 64.4% (n = 549) achieved scores of 0 or above, reporting either no photophobia (6.8%, n = 58) or a manifestation of biophilic (light-seeking) behavior (57.6%, n = 491). Table 1 Descriptive statistics summarizing the characteristics of patients and the scores from each questionnaire. Characteristics Quantity N 852 Sex, n (%) Female, 738 (86.6%); Male, 114 (13.4%) Age in years; mean (SD), range, median 49.79 (13.91), 22–90, 50 Race, n (%) Asian, 12 (1.4%); Black, 20 (2.3%); White, 802 (94.1%); Native American/Alaskan, 10 (1.2%); Hawaiian/Pacific Islander, 1 (0.1%); not reported, 7 (0.9%) Years lived with headache, mean (SD) 24.1 (16.6) Days with headaches per month, mean (SD) 19.1 (9.1) Migraine with Aura Diagnosis, n (%) 231 (27.1%) GAD-7, mean (SD) 5.87 (5.07) PHQ-2, mean (SD) 1.47 (1.64) Photosensitivity, mean (SD) 0.11 (0.55) Light as a headache trigger, n (%) 657 (77%) Roughly 46.5% of patients disagreed with the statement “My overall sleep quality was good,” signifying a subjective perception of poor sleep quality. Insomnia (21.2%, n = 181) was the most prevalent sleep disorder reported by patients, followed by obstructive sleep apnea (13.8%, n = 118). 3.3. Relationship between photophobia and sleep. The mean SQ scores for patients with and without photophobia, determined according to scores on the PAQ, were 31.33 (SD = 14.88, n = 303) and 24.33 (SD = 12.80, n = 549), respectively. The t-test revealed a statistically significant difference in sleep quality scores between the two groups (t (850) = -7.17, p < 0.001). The effect size (Cohen’s d) was calculated to be 0.513 indicating a medium effect. This suggests that patients with photophobia experience significantly worse sleep quality compared to those without photophobia. Furthermore, the t-test showed a significant difference between patients with and without photophobia in terms of SOL (t (850) = -4.89, p < 0.001), SDis (t (850) = -4.70, p < 0.001), and SRI (t (810) = -4.28, p < 0.001). Table 2 illustrates the means (SD) and results of t-test analysis. Table 2 Comparison of SQ, SDis, SOL, and SRI between migraine patients with and without photophobia. Variables Migraine without photophobia 1 (n = 549) Migraine with photophobia 2 (n = 303) Mean (SD) Mean (SD) t (df) Cohen’s d p -value Sleep Quality Score (SQ) 3 24.33 (12.80) 31.30 (14.88) -7.17 (850) 0.51 b < 0.001* Sleep Disturbance Score (SDis) 3 13.89 (8.77) 17.04 (10.39) -4.702 (850) 0.34 a < 0.001* Sleep Onset Latency (SOL) in minutes 32.65 (30.96) 46.00 (48.46) -4.89 (850) 0.35 a < 0.001* Sleep-Related Impairment score (SRI) 10.15 (3.81) 11.33 (3.74) -4.28 (810) 0.31 a < 0.001* * Two-tailed, Significant at α = 0.05 a Cohen’s d calculation: Small to medium effect size. b Cohen’s d calculation: medium effect size. 1 Photosensitivity global score ≧ 0 2 Photosensitivity global score < 0 3 Higher scores indicate worsen sleep quality and sleep disturbance The overall regression model including the primary predictor of photophobia and the covariates reached statistical significance (Adjusted R 2 = 0.330, F (5, 846) = 84.895, p < 0.001). After controlling for age, sex, depression, and anxiety, the regression coefficient for photophobia was statistically significant (β = 0.176, t = 5.799, p < 0.001). This means that for every point increase in photophobia, the sleep quality worsens by 0.176 points. Additionally, there was a statistically significant association between photophobia with SDis (β = 0.135, t = 4.104, p < 0.001), SOL (β = 0.092, t = 2.559, p = 0.011), and SRI (β = 0.081, t = 2.457, p = 0.014) when considering age, sex, depression, and anxiety as covariates in the models. Table 3 shows results for the photophobia regression analyses. Similarly, we conducted a linear regression to investigate the relationship between photophilia and sleep quality in patients with migraine. The overall regression model for the primary predictor of photophilia and the covariates reached statistical significance (Adjusted R 2 = 0.314, F (5, 846) = 79.061, p < 0.001). After controlling for age, sex, depression, and anxiety, the regression coefficient for photophilia was β = -0.107, was statistically significant (t = -3.665, p < 0.001). This indicates that for every point increase in photophilia, the sleep quality improves by 0.107 points. Furthermore, there was a statistically significant association between photophilia with SDis (β = -0.009, t = -8.564, p < 0.001) and SOL (β = -0.083, t = -2.423, p = 0.016). We also conducted a separate linear regression to investigate the relationship between photophilia and SRI with the same covariates. While the overall model was statically significant (Adjusted R 2 = 0.241, F (5, 806) = 52.558, p < 0.001), the β coefficient did not reach statistical significance (β = -0.01, t = -0.295, p = 0.768), suggesting that photophilia, when considered alongside the age, sex, depression, and anxiety, did not have a statistically significant linear relationship with SRI. Table 3 Linear regressions for investigating relationships between photophobia and photophilia with SQ, SDist, SOL, and SRI. Variable Regression a Coefficients Adj. R 2 F p -value f 2 β SE p -value Sleep Quality (SQ) Photophobia 0.33 84.90 < 0.001* 0.49 c 0.18 0.17 < 0.001* Photophilia 0.31 79.06 < 0.001* 0.46 c -0.11 0.17 < 0.001* Sleep Disturbance (SDis) Photophobia 0.22 48.22 < 0.001* 0.28 b 0.13 0.12 < 0.001* Photophilia 0.21 45.21 < 0.001* 0.27 c -0.07 0.13 0.027* Sleep Onset Latency (SOL) Photophobia 0.06 12.41 < 0.001* 0.067 b 0.09 0.01 0.011* Photophilia 0.06 12.27 < 0.001* 0.067 b -0.08 0.01 0.016* Sleep-related Impairment (SRI) Photophobia 0.25 54.136 < 0.001* 0.33 c 0.08 0.05 0.014* Photophilia 0.24 52.56 < 0.001* 0.32 c -0.01 0.05 0.77 *Significant at α = 0.05 a Overall regression model including photophobia or photophilia as the primary predictor and age, sex, anxiety, and depression as covariates. b f 2 = Cohen’s F calculation: Small effect size. c f 2 = Cohen’s F calculation: Small to medium effect size. SE = Coefficients Standard Error n = 852 4. Discussion We investigated the relationship between photosensitivity and various metrics of sleep including sleep quality, sleep disturbance, sleep onset latency, and sleep-related impairments in patients with migraine. The results were obtained using existing data extracted from ARMR from 852 patients who met the inclusion criteria. Poor sleep quality was prevalent among our participants, with over 46% reporting lack of good sleep quality. In line with several previous inquiries [ 15 , 38 ], our data exhibited insomnia as the most frequently reported sleep disorder among patients with migraine. Additionally, this study presents novel findings, demonstrating that patients with migraine with generalized photophobia tend to have poorer sleep quality compared to those without photophobia (including patients with photophilia). Both photophobia and photophilia exhibited statistically significant associations with sleep quality, sleep disturbance, and sleep onset latency. As we hypothesized, greater severity of photophobia emerged as a predictor for compromised sleep quality, increased sleep disturbance, and prolonged sleep onset latency. Conversely, a tendency for light, or photophilia, was correlated with enhanced sleep quality and lower levels of sleep disturbance and sleep onset latency. These results persisted after controlling for patient age, sex, anxiety, and depression. Our findings are aligned with a limited number of prior studies that reported photophobia as a potential risk factor for sleep disorders in migraine [ 22 , 23 ] as well as with the emerging body of literature highlighting the complex effects of light exposure on sleep quality [ 39 – 41 ]. Prior studies have demonstrated that retinal light exposure serves as a direct stimulant for the brain’s biological clock, exerting profound effects on various facets of sleep such as sleep pattern, sleep onset latency, sleep duration, and sleep efficiency [ 42 – 44 ]. The rhythmic interplay of light and darkness experienced throughout the day intricately orchestrates the timing of the circadian clock. To synchronize harmoniously with the natural light-dark cycle of Earth, a consistent exposure to high levels of morning light and a contrast between daytime and nighttime light exposure are essential. In a study by Figueiro et al. [ 45 ], it was observed that exposure to high levels of lighting in the morning was associated with reduced sleep onset latency, increased phasor magnitudes (which is a measure of circadian entrainment), and increased sleep quality in adult participants. These findings were aligned with other similar inquiries on other age groups [ 46 – 48 ]. Whereas there is growing evidence for circadian relevance in migraine and other pain disorders [ 21 , 49 ], none of the previous studies were focused on circadian effects of light on patients with migraine with photosensitivity. A prevalent coping strategy to alleviate discomfort and pain induced by migraine-associated photosensitivity involves seeking refuge in darkness, often by spending extended periods in dimly lit or dark rooms and donning dark or tinted sunglasses. These behaviors not only reduce the retinal light exposure during the daytime in patients with migraine, but also inadvertently result in constant lighting conditions, devoid of the natural contrast between the day and night. Consequently, the biological clock is deprived of a crucial time cue to stimulate the circadian clock accordingly, potentially leading to disruptions in sleep, prolonged sleep onset, and poor sleep quality. In those with migraine, insufficient sleep and sleep disturbance have consistently emerged as frequent headache triggers [ 12 , 50 – 52 ]. Conversely, adequate sleep timing, duration, and quality has been reported to be protective against headache [ 53 ]. Given the therapeutic effects of high-quality sleep in managing migraine and the potential adverse effects of pharmacological treatments, implementing non-drug interventions appears to be an effective initial approach to improve sleep quality in this population. Lighting, in particular, has been demonstrated as a potent non-pharmacological intervention capable of improving sleep and circadian activity rhythms, among other benefits [ 39 – 41 , 54 , 55 ]. In a study by Burgess et al. [ 56 ], the findings revealed that bright light therapy in the morning advanced circadian phase which was associated with an increased tolerance to pain. The positive association we found between photophilia and improved sleep outcomes further supports the potential beneficial effects of light exposure on sleep outcomes amongst those with migraine. It is reasonable to assume that patients with migraine with photophilia tend to receive more retinal light exposure during the daytime which could potentially be the reason for enhanced sleep outcomes in this population. In a recent open-label study, self-reported data revealed that two hours of exposure to narrow band green light led to an improvement in photophobia and same-night sleep for 53% and 49% of all migraine attacks, on average, respectively. [ 18 ]. However, it is not clear whether the improvement in sleep was due to the effects of light exposure on circadian activity rhythms or as a result of enhanced mood, photophobia, or headache improvement. Circadian stimulation by light is achieved through exposure to high-intensity lighting with a blue-enriched spectrum during the daytime. Nevertheless, the prevalence of photophobia in migraine poses a challenge to the implementation of circadian lighting for this population, given their severe sensitivity to high intensity light, particularly in the blue spectrum [ 57 , 58 ]. The emergence of new lighting technology holds promise for enhancing well-being among those with migraine through offering customized lighting solutions with optimized intensity and spectrum tailored to individuals’ needs, while maintaining circadian rhythms by following a natural light/dark cycle. Exposure to proper circadian lighting not only has the potential to improve sleep quality in patients with migraine but also could contribute to positive effects on anxiety and depressive symptoms – both highly associated with migraine and photophobia. The recruitment of patients from nine different sites across the United States, the large sample size, and the diverse geographical locations of enrollment enhance the potential generalizability of our findings. However, the findings of this study are limited as we only included patients from headache specialty centers who tended to have high frequency migraine and likely represent a population with severe migraine disease. To improve generalizability, future studies should include a more diverse population. Our study is also limited by its reliance on self-reported data for photosensitivity and sleep quality, collected through instruments selected by the ARMR study team. Self-reported data are inherently subjective as they rely on individuals’ subjective perceptions, introducing the possibility of recall bias. Additionally, the photosensitivity questionnaire (PAQ) utilized in ARMR, while well-validated, lacks specific assessments of headache-related light sensitivity, focusing instead on non-specific behavioral preferences. Similar limitations apply to the sleep questionnaire, which incorporates partial components from various instruments and does not include the entire set of questions from a single validated questionnaire. That makes interpretation and analysis of the sleep data challenging. Future studies should consider supplementing subjective measures with objective ones (i.e., actigraphy, wearable light trackers) to acquire precise data on sleep quality and daily light exposure behavior among patients with migraine. Furthermore, experimental trials aimed at investigating the effects of various lighting interventions on sleep quality and circadian health of those with migraine could offer valuable insights. Such research might pave the way for the development of novel lighting technologies, contributing to the improvement of well-being in this population. Lastly, it is important to acknowledge a limitation inherent in the ARMR dataset [ 7 ], which pertains to the unbalanced racial distribution of the sample. The participants in this registry are predominantly White, a characteristic that is apparent in the sample included in our analysis (94.1% White). This feature of the dataset, undeniably, limits the generalizability of our findings. It is imperative for future research to include a more diverse sample for extrapolating the results. 5. Conclusion This study demonstrated that patients with migraine with photophobia experienced worse sleep quality compared to those without generalized photophobia. Both photophobia and generalized photophilia exhibited significant associations with sleep quality, sleep disturbance, and sleep onset latency, persisting after adjusting for age, sex, anxiety, and depression. These findings suggest photophobia as a potential risk factor for sleep disorders in migraine. This relationship could be explained by the well-established influence of light on circadian activity rhythms mediated by the ipRGCs in the retina. Given the high prevalence of photophobia and sleep disorders among patients with migraine and their impacts on overall quality of life, these findings highlight the need for in-depth systematic exploration of the relationship between photophobia and sleep in this population. Such research can provide insights that will help pave the path for developing novel lighting technologies and design solutions to address the specific needs of those with migraine. Declarations Huma ethics approval and consent to participate The research was performed in accordance with the Declaration of Helsinki and was authorized by the Institutional Review Boards at each enrolling site (Mayo Clinic, University of Utah, University of Texas Health Science Center at Houston, University of Colorado, Georgetown University Medical Center, DENT Neurologic Institute, Dartmouth-Hitchcock Medical Center, Thomas Jefferson University Headache Center, and Yale University). All research participants completed and signed an informed consent document. Consent for publication The authors approved the publication of this paper. Competing Interests Nina Sharp, Kathleen B Digre , Mahya Fani, and Sophia Lamp declare no competing interests. Within the prior 24 months, Todd Schwedt has received compensation for consulting with Abbvie, Allergan, Amgen, Axsome, Biodelivery Science, Biohaven, Collegium, Eli Lilly, Linpharma, Lundbeck, Satsuma, Scilex, and Theranica, royalties from Up To Date, and research funding from American Heart Association, Amgen, National Institutes of Health, Mayo Clinic, Spark Neuro, and United States Department of Defense. He holds stock options in Aural Analytics and GBS Ventures. Mark Burish was a consultant for Beckley Psytech limited, Lundbeck, Praxis Precision Medicines, and PureTech Health. He was a site investigator for a cluster headache clinical trial funded by Lundbeck. He was a paid guest for a video podcast by the American Academy of Neurology. He is an unpaid member of the medical advisory board of Clusterbusters. Jessica Ailani has served as a consultant for Abbvie, Amgen, Aeon, Axsome, Dr. Reddy, Eli-Lilly, GlaxoSmithKline, Lundbeck, Linpharma, Ipsen, Merz, Miravio, Pfizer, Neurolief, Gore, Satsuma, Scilex, Theranica, and Toni. She has had grants to her institution for clinical trials by Parema and Ipsen and has served on the editorial board for Current Pain and Headache Reports and Medscape and served as a medical editor for SELF magazine. Funding No funding was received to support this analysis of ARMR data. Author Contribution NS and TS generated the study concept and design. NS conducted the data analysis and interpretation of results with support from SL and MF. NS wrote the first draft of the manuscript. TS and MB conducted critical revisions of the manuscript. KD and JA provided valuable comments and all authors revised and edited the manuscript. All authors read and approved the final version of the manuscript. The corresponding author confirms that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. Acknowledgments The authors gratefully acknowledge the American Migraine Foundation and the American Registry for Migraine Research (ARMR) for the use of registry data to conduct this research. In addition, we would like to thank the patients and clinicians who participated in ARMR. Kathleen Digre is supported in part by an Unrestricted Grant from Research to Prevent Blindness, New York, NY, to the Department of Ophthalmology & Visual Sciences, University of Utah. Availability of data and materials The datasets analyzed in this study are contained within the American Registry for Migraine Research (ARMR). Data access requests should be directed to the American Migraine Foundation. References Ashina M, Terwindt GM, Al-Karagholi MA-M et al (2021) Migraine: disease characterisation, biomarkers, and precision medicine. The Lancet 397:1496–1504. https://doi.org/10.1016/S0140-6736(20)32162-0 Lipton RB, Fanning KM, Buse DC et al (2018) Identifying Natural Subgroups of Migraine Based on Comorbidity and Concomitant Condition Profiles: Results of the Chronic Migraine Epidemiology and Outcomes (CaMEO) Study. Headache J Head Face Pain 58:933–947. https://doi.org/10.1111/head.13342 Silberstein SD (1995) Migraine Symptoms: Results of a Survey of Self-Reported Migraineurs. Headache J Head Face Pain 35:387–396. https://doi.org/10.1111/j.1526-4610.1995.hed3507387.x Mulleners Wm, Aurora S k., Chronicle E et al (2001) p., Self-reported Photophobic Symptoms in Migraineurs and Controls Are Reliable and Predict Diagnostic Category Accurately. Headache J Head Face Pain 41:31–39. https://doi.org/10.1046/j.1526-4610.2001.111006031.x Lipton RB, Croop R, Stock EG et al (2019) Rimegepant, an Oral Calcitonin Gene–Related Peptide Receptor Antagonist, for Migraine. 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Front Neurol 10 Afonso P, Fonseca M, Teodoro T (2022) Evaluation of anxiety, depression and sleep quality in full-time teleworkers. J Public Health 44:797–804. https://doi.org/10.1093/pubmed/fdab164 Adams SK, Kisler TS (2013) Sleep Quality as a Mediator Between Technology-Related Sleep Quality, Depression, and Anxiety. Cyberpsychology Behav Soc Netw 16:25–30. https://doi.org/10.1089/cyber.2012.0157 Mehboudi A, Modanloo M, Shariati A et al (2016) Relationship between Anxiety and Sleep Quality in Patients on Hemodialysis in Borazjan City, 2014. J Res Dev Nurs Midwifery 12:56–63 Ramsawh HJ, Stein MB, Belik S-L et al (2009) Relationship of anxiety disorders, sleep quality, and functional impairment in a community sample. J Psychiatr Res 43:926–933. https://doi.org/10.1016/j.jpsychires.2009.01.009 Seidel S, Beisteiner R, Manecke M et al (2017) Psychiatric comorbidities and photophobia in patients with migraine. J Headache Pain 18:18. https://doi.org/10.1186/s10194-017-0718-1 Garrigós-Pedrón M, Segura-Ortí E, Gracia-Naya M, La Touche R (2022) Predictive factors of sleep quality in patients with chronic migraine. Neurol Engl Ed 37:101–109. https://doi.org/10.1016/j.nrleng.2018.11.009 Figueiro M, Nagare R, Price L (2018) Non-visual effects of light: How to use light to promote circadian entrainment and elicit alertness. Light Res Technol 50:38–62. https://doi.org/10.1177/1477153517721598 Rea M, Figueiro M (2018) Light as a circadian stimulus for architectural lighting. Light Res Technol 50:497–510. https://doi.org/10.1177/1477153516682368 Shishegar N, Boubekri M, Stine-Morrow EAL, Rogers WA (2021) Tuning environmental lighting improves objective and subjective sleep quality in older adults. Build Environ 204:108096. https://doi.org/10.1016/j.buildenv.2021.108096 Mason IC, Grimaldi D, Reid KJ et al (2022) Light exposure during sleep impairs cardiometabolic function. Proc Natl Acad Sci 119:e2113290119. https://doi.org/10.1073/pnas.2113290119 Siraji MA, Spitschan M, Kalavally V, Haque S (2023) Light exposure behaviors predict mood, memory and sleep quality. Sci Rep 13:12425. https://doi.org/10.1038/s41598-023-39636-y Khanie MS, Illum T, Hosseinpour N et al (2023) Exploring the effects of spectral light exposure on University students’ sleep quality: A cross-sectional study. E3S Web Conf 396:01106. https://doi.org/10.1051/e3sconf/202339601106 Figueiro MG, Steverson B, Heerwagen J et al (2017) The impact of daytime light exposures on sleep and mood in office workers. Sleep Health 3:204–215. https://doi.org/10.1016/j.sleh.2017.03.005 Melanson EL, Ritchie HK, Dear TB et al (2018) Daytime bright light exposure, metabolism, and individual differences in wake and sleep energy expenditure during circadian entrainment and misalignment. Neurobiol Sleep Circadian Rhythms 4:49–56. https://doi.org/10.1016/j.nbscr.2017.12.002 Kawasaki A, Udry M, El Wardani M, Münch M (2021) Can Extra Daytime Light Exposure Improve Well-Being and Sleep? A Pilot Study of Patients With Glaucoma. Front Neurol 11 Dunster GP, Hua I, Grahe A et al (2023) Daytime light exposure is a strong predictor of seasonal variation in sleep and circadian timing of university students. J Pineal Res 74:e12843. https://doi.org/10.1111/jpi.12843 Ong JC, Taylor HL, Park M et al (2018) Can Circadian Dysregulation Exacerbate Migraines? Headache J Head Face Pain 58:1040–1051. https://doi.org/10.1111/head.13310 Boardman HF, Thomas E, Millson DS, Croft PR (2005) Psychological, Sleep, Lifestyle, and Comorbid Associations With Headache. Headache J Head Face Pain 45:657–669. https://doi.org/10.1111/j.1526-4610.2005.05133.x Martin PR, MacLeod C (2009) Behavioral management of headache triggers: Avoidance of triggers is an inadequate strategy. Clin Psychol Rev 29:483–495. https://doi.org/10.1016/j.cpr.2009.05.002 Kelman L (2007) The Triggers or Precipitants of the Acute Migraine Attack. Cephalalgia 27:394–402. https://doi.org/10.1111/j.1468-2982.2007.01303.x Houle TT, Butschek RA, Turner DP et al (2012) Stress and sleep duration predict headache severity in chronic headache sufferers. Pain 153:2432–2440. https://doi.org/10.1016/j.pain.2012.08.014 Figueiro MG (2013) An Overview of the Effects of Light on Human Circadian Rhythms: Implications for New Light Sources and Lighting Systems Design. J Light Vis Environ 37:51–61. https://doi.org/10.2150/jlve.IEIJ130000503 Rea MS, Nagare R, Figueiro MG (2020) Predictions of melatonin suppression during the early biological night and their implications for residential light exposures prior to sleeping. Sci Rep 10:14114. https://doi.org/10.1038/s41598-020-70619-5 Burgess HJ, Park M, Ong JC et al (2017) Morning Versus Evening Bright Light Treatment at Home to Improve Function and Pain Sensitivity for Women with Fibromyalgia: A Pilot Study. Pain Med 18:116–123. https://doi.org/10.1093/pm/pnw160 Main A, Vlachonikolis I, Dowson A (2000) The Wavelength of Light Causing Photophobia in Migraine and Tension-type Headache Between Attacks. Headache J Head Face Pain 40:194–199. https://doi.org/10.1046/j.1526-4610.2000.00028.x Noseda R, Bernstein CA, Nir R-R et al (2016) Migraine photophobia originating in cone-driven retinal pathways. Brain 139:1971–1986. https://doi.org/10.1093/brain/aww119 Additional Declarations Competing interest reported. Nina Sharp, Kathleen B Digre , Mahya Fani, and Sophia Lamp declare no competing interests. Within the prior 24 months, Todd Schwedt has received compensation for consulting with Abbvie, Allergan, Amgen, Axsome, Biodelivery Science, Biohaven, Collegium, Eli Lilly, Linpharma, Lundbeck, Satsuma, Scilex, and Theranica, royalties from Up To Date, and research funding from American Heart Association, Amgen, National Institutes of Health, Mayo Clinic, Spark Neuro, and United States Department of Defense. He holds stock options in Aural Analytics and GBS Ventures. Mark Burish was a consultant for Beckley Psytech limited, Lundbeck, Praxis Precision Medicines, and PureTech Health. He was a site investigator for a cluster headache clinical trial funded by Lundbeck. He was a paid guest for a video podcast by the American Academy of Neurology. He is an unpaid member of the medical advisory board of Clusterbusters. Jessica Ailani has served as a consultant for Abbvie, Amgen, Aeon, Axsome, Dr. Reddy, Eli-Lilly, GlaxoSmithKline, Lundbeck, Linpharma, Ipsen, Merz, Miravio, Pfizer, Neurolief, Gore, Satsuma, Scilex, Theranica, and Toni. She has had grants to her institution for clinical trials by Parema and Ipsen and has served on the editorial board for Current Pain and Headache Reports and Medscape and served as a medical editor for SELF magazine. Cite Share Download PDF Status: Published Journal Publication published 12 Apr, 2024 Read the published version in The Journal of Headache and Pain → Version 1 posted Editorial decision: Revision requested 02 Feb, 2024 Reviews received at journal 30 Jan, 2024 Reviewers agreed at journal 18 Jan, 2024 Reviewers invited by journal 18 Jan, 2024 Editor assigned by journal 18 Jan, 2024 Submission checks completed at journal 18 Jan, 2024 First submitted to journal 14 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3864442","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268386659,"identity":"21e20f94-0d90-4387-8724-ad8c86304d66","order_by":0,"name":"Nina Sharp","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYBACg8Ng6gAQMx9ggLPxAQuEFrYE4rTYHIAr4zEgUstx3oMfGP7ckTef3fPx4882Bjm+Gwn4tZgd5kuWYGx7ZjjnztnN0rxtDMaShLXwGEgwNhxmnCGRu0GasY0hcQMhLcaHeYx/MPw5bD9DIufxT6DD6glqMTzMYybBwHY4EaiFTQLosAQDYrRYJLYdTp4hc8zMmuechOHMMw/wazE4f8b4xoc/h21nSDc/vvmjzEae7zgBW8AArEaCAUESCUhSPApGwSgYBSMKAABfRUl9P7hj+wAAAABJRU5ErkJggg==","orcid":"","institution":"Arizona State University","correspondingAuthor":true,"prefix":"","firstName":"Nina","middleName":"","lastName":"Sharp","suffix":""},{"id":268386660,"identity":"3054cfc2-ecab-490a-8bf9-cc5b6be17e69","order_by":1,"name":"Mark J Burish","email":"","orcid":"","institution":"The University of Texas Health Science Center at Houston","correspondingAuthor":false,"prefix":"","firstName":"Mark","middleName":"J","lastName":"Burish","suffix":""},{"id":268386661,"identity":"3b1662b0-1528-4f73-8ca2-943a8f6993f4","order_by":2,"name":"Kathleen B Digre","email":"","orcid":"","institution":"University of Utah Health Sciences Center","correspondingAuthor":false,"prefix":"","firstName":"Kathleen","middleName":"B","lastName":"Digre","suffix":""},{"id":268386662,"identity":"9627a43f-5ee9-43d7-acc4-24bc7b14838e","order_by":3,"name":"Jessica Ailani","email":"","orcid":"","institution":"MedStar Georgetown University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jessica","middleName":"","lastName":"Ailani","suffix":""},{"id":268386663,"identity":"a4383678-43b4-47cc-b8eb-fba9eec76b80","order_by":4,"name":"Mahya Fani","email":"","orcid":"","institution":"Arizona State University","correspondingAuthor":false,"prefix":"","firstName":"Mahya","middleName":"","lastName":"Fani","suffix":""},{"id":268386664,"identity":"844201d1-ba1b-45b7-9913-9fdb99b1223e","order_by":5,"name":"Sophia Lamp","email":"","orcid":"","institution":"Arizona State University","correspondingAuthor":false,"prefix":"","firstName":"Sophia","middleName":"","lastName":"Lamp","suffix":""},{"id":268386665,"identity":"89e71c7e-91c2-46b4-8c16-5df8aa25cb4e","order_by":6,"name":"Todd J. 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Nina Sharp, Kathleen B Digre , Mahya Fani, and Sophia Lamp declare no competing interests. Within the prior 24 months, Todd Schwedt has received compensation for consulting with Abbvie, Allergan, Amgen, Axsome, Biodelivery Science, Biohaven, Collegium, Eli Lilly, Linpharma, Lundbeck, Satsuma, Scilex, and Theranica, royalties from Up To Date, and research funding from American Heart Association, Amgen, National Institutes of Health, Mayo Clinic, Spark Neuro, and United States Department of Defense. He holds stock options in Aural Analytics and GBS Ventures. Mark Burish was a consultant for Beckley Psytech limited, Lundbeck, Praxis Precision Medicines, and PureTech Health. He was a site investigator for a cluster headache clinical trial funded by Lundbeck. He was a paid guest for a video podcast by the American Academy of Neurology. He is an unpaid member of the medical advisory board of Clusterbusters. Jessica Ailani has served as a consultant for Abbvie, Amgen, Aeon, Axsome, Dr. Reddy, Eli-Lilly, GlaxoSmithKline, Lundbeck, Linpharma, Ipsen, Merz, Miravio, Pfizer, Neurolief, Gore, Satsuma, Scilex, Theranica, and Toni. She has had grants to her institution for clinical trials by Parema and Ipsen and has served on the editorial board for Current Pain and Headache Reports and Medscape and served as a medical editor for SELF magazine.","formattedTitle":"Photophobia is associated with lower sleep quality in individuals with migraine: Results from the American Registry for Migraine Research (ARMR)","fulltext":[{"header":"1. Background","content":"\u003cp\u003eA migraine attack consists of moderate-to-severe intensity throbbing headache accompanied by a combination of sensory hypersensitivities (e.g., photosensitivity, phonosensitivity, olfactory hypersensitivity, cutaneous allodynia), nausea, and vomiting [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Photophobia, defined here as discomfort caused by light and exacerbation of headache by light, is exceedingly prevalent during migraine attacks and can persist, typically to a lesser extent, between attacks [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, numerous migraine studies reported photophobia as the most common, most bothersome symptom other than headache [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Generalized photophobia (i.e., both ictally and interictally) has been linked to several aspects of migraine: higher generalized photophobia is more common in migraine with aura (MwA) compared to those without aura (MwoA) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and higher photophobia scores are associated with greater work-related disability and activity impairment [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIndividuals with migraine also often report poor sleep quality and sleep disturbances, both as triggers of migraine attacks and as a consequence of the attacks [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These disturbances manifest as difficulty falling asleep, staying asleep, self-reported decreased sleep duration, extreme daytime sleepiness, and lack of feeling refreshed after sleep [\u003cspan additionalcitationids=\"CR13 CR14 CR15\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Despite substantial growth in the literature over the past two decades, the precise nature and direction of the relationship between sleep and migraine remains elusive. It is conceivable that sleep disturbances are caused by an ongoing migraine attack or sleep disruption may trigger migraine attacks.\u003c/p\u003e \u003cp\u003eThere are multiple lines of evidence to suggest that photophobia and sleep might be related in migraine. Clinically, in two open-label studies green light improves not only headaches but also photophobia and sleep [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], though these data are confounded by the fact that the headaches also improved. Mechanistically, photophobia and light may be related through the circadian system. Light, especially bright light, is the strongest zeitgeber (an environmental cue which resynchronizes our internal biological clock to the external world), and the circadian system regulates the sleep-wake cycle [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Specifically, light received through signals from the intrinsically photosensitive retinal ganglion cells (ipRGCs) synchronizes the rhythmic activity of the central clock in the hypothalamus, the suprachiasmatic nuclei (SCN). There are several lines of evidence that migraine has circadian properties, including lower melatonin levels amongst those with migraine and a circadian pattern of attacks; moreover, a variation in a core circadian gene \u0026ndash; \u003cem\u003eCK1δ\u003c/em\u003e \u0026ndash;causes both migraine and a circadian rhythm disorder (advanced sleep phase) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Epidemiologically, the Korean Sleep-Headache Study performed latent class analysis and ultimately subtyped patients into 3 groups, one of which was an ictal photophobia/phonophobia group [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This photophobia/phonophobia group had the highest proportion of patients with excessive daytime sleepiness on the Epworth Sleepiness Scale, though the findings were not significant (p\u0026thinsp;=\u0026thinsp;0.13) possibly due to the relatively modest enrollment (n\u0026thinsp;=\u0026thinsp;125 across 3 groups). However, an even smaller study (n\u0026thinsp;=\u0026thinsp;48) comparing migraine patients with interictal photophobia, did find a statistically significant change in sleeping patterns compared to healthy controls and migraine patients without interictal photophobia [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Researchers attributed these findings to the concurrent symptoms of depression and anxiety, commonly associated with migraine [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], suggesting that generalized photophobia might have a stronger relationship with sleep than interictal photophobia, but that mood disorders could be confounders that need to be taken into account.\u003c/p\u003e \u003cp\u003eLight, or rather the lack of light, may be important in migraine patients with photophobia. During a migraine attack, a common behavioral intervention is to seek the comfort of darkness. In one large survey, more than 92% of 2735 participants reported using a dark room during a migraine attack and more than 83% reported it as a consistent strategy to treat their pain [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Therefore, it is likely that individuals with migraine with photophobia may experience lower levels of daily light exposure. Given the non-image forming effects of light on circadian rhythms and sleep, we hypothesize that lack of exposure to proper lighting could be contributing to or exacerbating the sleep disturbance experienced by individuals with migraine who have photophobia. However, current literature lacks research that fully investigates the relationship between photophobia in migraine and prevalence of sleep disturbance and poor sleep quality.\u003c/p\u003e \u003cp\u003eIn this study, we investigated the relationship between photophobia and sleep (poor sleep quality and sleep disturbance) in individuals with migraine. We hypothesized that generalized photophobia would be associated with poor sleep quality and sleep disturbances in people with migraine even after accounting for the effects of depression and anxiety.\u003c/p\u003e"},{"header":"2. Methods","content":" \u003cp\u003eWe conducted a cross-sectional observational analysis using existing data extracted from the American Registry for Migraine Research (ARMR)\u0026mdash;a multicenter, prospective, longitudinal patient registry, biorepository, and neuroimaging repository [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. ARMR systematically collected data from individuals experiencing primary and secondary headaches as classified by the ICHD 3 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. ARMR includes information related to patients' demographics and types of headaches diagnosed by headache specialists at the medical facilities where they enrolled. Participants completed a set of baseline questionnaires on headache features, personal medical history, sleep quality, anxiety, depression, and photosensitivity, among others. A detailed description of ARMR methods and baseline data have been previously published [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Research Participants\u003c/h2\u003e \u003cp\u003ePatients included within this analysis of ARMR data were recruited from specialty headache clinics at Mayo Clinic Arizona, University of Utah, University of Texas Health Science Center at Houston, University of Colorado, Georgetown University Medical Center, DENT Neurologic Institute, Dartmouth-Hitchcock Medical Center, Thomas Jefferson University Headache Center, and Yale University. Inclusion criteria for the analysis presented in this study were a clinician diagnosis of migraine according to ICHD-3 diagnostic criteria and completion of the baseline questionnaires by the time of data extraction in July 2023. The research was performed in accordance with the Declaration of Helsinki and was approved by the Mayo Clinic Institutional Review Board as well as the Institutional Review Boards of each enrolling site mentioned above. All research participants completed and signed an informed consent document.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Study Questionnaires\u003c/h2\u003e \u003cp\u003e \u003cb\u003ePhotosensitivity.\u003c/b\u003e Photosensitivity was evaluated using the Photosensitivity Assessment Questionnaire (PAQ) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The PAQ is a self-reported, validated questionnaire that examines behavioral sensitivity to light and psychopathological traits. The questionnaire includes 16 items specifically designed to assess two distinct aspects: \u0026ldquo;light-avoiding\u0026rdquo; behaviors associated with photophobia (8 questions) and \u0026ldquo;light-seeking\u0026rdquo; behaviors related to photophilia (8 questions). The PAQ utilizes a dichotomous response format, where participants are presented with \u0026ldquo;Yes\u0026rdquo; or \u0026ldquo;No\u0026rdquo; options to answer each question. Negative answers are rated \u0026ldquo;0\u0026rdquo; and affirmative answers are rated \u0026ldquo;1\u0026rdquo; for a total score between 0 and 8 for each of the photophobia and photophilia scales. A third score, the global photosensitivity score is obtained through taking the difference between the photophilia and photophobia scores and dividing it by 8. This global score ranges between \u0026minus;\u0026thinsp;1 (extreme photophobia) and 1 (extreme photophilia) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In this study, we included all 3 scores (photophobia, photophilia, and global photosensitivity scores) in our analysis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSleep.\u003c/b\u003e A self-rated questionnaire was employed in ARMR to assess sleep quality of participants. The questionnaire consists of 50 questions asking participants to provide information on their typical sleep issues as well as their sleep duration, sleep onset latency, and sleep time at night, among others. To calculate the sleep quality (SQ) in this study, we selected 16 questions that covered sleep disturbance (10 questions), sleep duration (one question), sleep onset latency (one question), use of sleep medication (one question), daytime dysfunctioning (two questions), and subjective sleep quality (one question). The one question for sleep duration asked patients to report their average number of sleep hours during the prior three months while the question on sleep onset latency (SOL) inquired about the number of minutes typically taken to fall asleep during the same period. The questions related to sleep disturbance (SDis) explored the frequency of nighttime or early morning awakenings due to need to use the bathroom, bad dreams, teeth grinding, involuntary limb or body movements, headache or migraine symptoms, stomach pain, non-headache pain, anxiety, depression, and other reasons. Furthermore, the daytime dysfunctioning questions aimed to collect data on participants' level of enthusiasm and ability to carry out scheduled activities and daily tasks. The one question on sleep medication asked patients on the frequency of taking medications to aid with sleep in the past three months. Lastly, the subjective sleep quality question asked patients to rate the average quality of their sleep in the prior three months. Each question, except for the subjective sleep quality question, was scored on a scale from 0 to 6, where 0 indicated no difficulty or disturbance, and 6 indicated severe difficulty or disturbance. The subjective sleep quality question was scored between 0 and 4, where 0 indicated good quality of sleep, and 4 indicated very poor sleep. The component scores were then summed to generate the total SQ score, which ranged from 0 to 94. Higher scores indicated lower levels of sleep quality and more significant sleep disturbance. While the SDis was included in the overall SQ score, we extracted the score separately for further analysis. A distinct analysis was performed on the reported minutes of SOL by patients. We also incorporated an assessment of sleep-related impairment (SRI) in our analysis by including four selected questions that measured daytime sleepiness due to poor sleep quality at night. These questions asked patients to report any challenges related to waking up in the morning, feeling drowsy upon waking, experiencing daytime sleepiness, and facing daytime issues due to poor sleep at night. Each question was scored on a scale from 0 to 4, with 0 indicating the absence of daytime sleep-related impairment and 4 indicating significant sleep-related impairment. These individual scores were subsequently summed to generate the total score for sleep-related impairment that ranged from 0 to 16. The selected questions could be found in the supplemental materials of this manuscript.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAnxiety.\u003c/b\u003e An evaluation of anxiety symptoms was carried out using the Generalized Anxiety Disorder-7 (GAD-7) assessment tool. The GAD-7 is a short and easy-to-use 7-item scale that has been found to have reliable psychometric properties [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The scale examines the frequency of anxiety symptoms experienced by an individual during the preceding two weeks. Response options include \u0026ldquo;not at all,\u0026rdquo; \u0026ldquo;several days,\u0026rdquo; \u0026ldquo;more than half the days,\u0026rdquo; and \u0026ldquo;nearly daily,\u0026rdquo; corresponding to scores of 0, 1, 2, and 3, respectively. The scores of 5, 10, and 15 are considered as thresholds for indicating mild, moderate, and severe anxiety, respectively [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eDepression.\u003c/b\u003e The Patient Health Questionnaire-2 (PHQ-2) was employed to screen symptoms of depression. The PHQ-2 is a short self-assessment tool consisting of two simple questions that assess the occurrence of depressed mood and anhedonia over the past two weeks. Similar to GAD-7, there are four response options, \u0026ldquo;not at all,\u0026rdquo; \u0026ldquo;several days,\u0026rdquo; \u0026ldquo;more than half the days,\u0026rdquo; and \u0026ldquo;nearly daily,\u0026rdquo; which are respectively assigned scores of 0 to 3. The accumulated scores of the two questions yield a total score, ranging from 0 to 6. A score of 3 is established as a cut point for major depressive disorders, whereas a score of 2 suggests potential depressive disorders [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The PHQ-2 has been recognized as a valid and reliable screening instrument for identifying depressive disorders in patients with migraine [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Statistics\u003c/h2\u003e \u003cp\u003eData were managed and analyzed using IBM SPSS 28.1 statistical software. In this analysis, the scores from PAQ, the sleep questionnaire, PHQ-2, and GAD-7 were treated as continuous variables due to their extensive distribution covering the full range of possible scores. Descriptive statistics (mean and standard deviation (SD), median (interquartile range), or number (percentage)) were employed to describe the characteristics of sample such as age, sex and race, as well as the prevalence of photophobia, migraine with/without aura, years with migraine, depression, and anxiety.\u003c/p\u003e \u003cp\u003eWe conducted independent sample t-tests to compare SQ, SDis, SOL, and SRI in patients with and without photophobia. Cohen's d test was used to find the effect size of photosensitivity on various metrics of sleep.\u003c/p\u003e \u003cp\u003eSeparate multiple linear regression models were developed to examine the relationship between the severity of photophobia and SQ, SDis, SOL, and SRI. Similarly, regression models were established to probe the link between photophilia and SQ, SDis, SOL, and SRI. Each regression model generated an R\u003csup\u003e2\u003c/sup\u003e value as well as a corresponding \u003cem\u003eP\u003c/em\u003e Value for the entire model, alongside individual \u003cem\u003eP\u003c/em\u003e values for each predictor variable. Diagnostic plots were employed to confirm that all the assumptions for linear regression modeling were met. The SOL data underwent a logarithmic transformation to ensure that the assumption of normality for the linear regression was satisfied.\u003c/p\u003e \u003cp\u003eRegression models were adjusted by accounting for age and sex as covariates. Previous research has highlighted a bidirectional causal relationship between psychiatric symptoms, notably anxiety/depression, and sleep disorders [\u003cspan additionalcitationids=\"CR33 CR34 CR35\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Additionally, a significant correlation has been shown to exist between anxiety/depression and photophobia [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In light of these insights, our analysis integrated the scores of anxiety (GAD-7) and depression (PHQ-2) as covariates in the regression models, aiming to isolate the specific influence of photophobia or photophilia on sleep. We also utilized Cohen\u0026rsquo;s f\u003csup\u003e2\u003c/sup\u003e to find individual effect sizes of photophobia and photophilia on the sleep-related variables measured in this study. For all analysis, two-tailed hypothesis testing was employed, and statistical significance was set at 95% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). We did not conduct an a priori power analysis since the sample size was based on available data.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Demographics\u003c/h2\u003e \u003cp\u003eIn total, 852 patients met the inclusion criteria, provided the covariate information, and answered all selected questions related to sleep (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Patients were 86.6% female (n\u0026thinsp;=\u0026thinsp;738) and 13.4% male (n\u0026thinsp;=\u0026thinsp;114). The mean (SD) age was 49.79 (13.91) years (range\u0026thinsp;=\u0026thinsp;22\u0026ndash;90, n\u0026thinsp;=\u0026thinsp;852). All patients were diagnosed with migraine and 27.1% of them had a migraine with aura diagnosis (n\u0026thinsp;=\u0026thinsp;231). The mean headache days per month were 19.1 (9.1) and the mean duration of living with headaches was 24.1 (16.6) years.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Baseline photophobia and sleep characteristics\u003c/h2\u003e \u003cp\u003eThe mean score of the PHQ-2 was 1.47 (1.64), and 22.7% of patients (n\u0026thinsp;=\u0026thinsp;193) surpassed the screening cutoff of 2 for potential depressive disorders while 19.8% (n\u0026thinsp;=\u0026thinsp;169) exceeded the cutoff of 3 for major depressive disorder. As for the GAD-7, mean score was 5.87 (5.07), with 8.9% (n\u0026thinsp;=\u0026thinsp;76) of participants meeting the screening threshold for severe anxiety, 10.9% (n\u0026thinsp;=\u0026thinsp;93) for moderate anxiety, and 31.9% (n\u0026thinsp;=\u0026thinsp;272) for at least mild anxiety.\u003c/p\u003e \u003cp\u003eThe mean global score of the photosensitivity questionnaire, which does not differentiate between photosensitivity during and between migraine attacks, was 0.11 (0.55) suggesting a photophilic inclination. Totally, 35.6% of patients (n\u0026thinsp;=\u0026thinsp;303) recorded scores below 0, indicating some degree of photophobia. Conversely, about 64.4% (n\u0026thinsp;=\u0026thinsp;549) achieved scores of 0 or above, reporting either no photophobia (6.8%, n\u0026thinsp;=\u0026thinsp;58) or a manifestation of biophilic (light-seeking) behavior (57.6%, n\u0026thinsp;=\u0026thinsp;491).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics summarizing the characteristics of patients and the scores from each questionnaire.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuantity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e852\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale, 738 (86.6%); Male, 114 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge in years; mean (SD), range, median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.79 (13.91), 22\u0026ndash;90, 50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian, 12 (1.4%); Black, 20 (2.3%); White, 802 (94.1%); Native American/Alaskan, 10 (1.2%); Hawaiian/Pacific Islander, 1 (0.1%); not reported, 7 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears lived with headache, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.1 (16.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDays with headaches per month, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.1 (9.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMigraine with Aura Diagnosis, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e231 (27.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGAD-7, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.87 (5.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHQ-2, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.47 (1.64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhotosensitivity, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.11 (0.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLight as a headache trigger, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e657 (77%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRoughly 46.5% of patients disagreed with the statement \u0026ldquo;My overall sleep quality was good,\u0026rdquo; signifying a subjective perception of poor sleep quality. Insomnia (21.2%, n\u0026thinsp;=\u0026thinsp;181) was the most prevalent sleep disorder reported by patients, followed by obstructive sleep apnea (13.8%, n\u0026thinsp;=\u0026thinsp;118).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Relationship between photophobia and sleep.\u003c/h2\u003e \u003cp\u003eThe mean SQ scores for patients with and without photophobia, determined according to scores on the PAQ, were 31.33 (SD\u0026thinsp;=\u0026thinsp;14.88, n\u0026thinsp;=\u0026thinsp;303) and 24.33 (SD\u0026thinsp;=\u0026thinsp;12.80, n\u0026thinsp;=\u0026thinsp;549), respectively. The t-test revealed a statistically significant difference in sleep quality scores between the two groups (t (850) = -7.17, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The effect size (Cohen\u0026rsquo;s d) was calculated to be 0.513 indicating a medium effect. This suggests that patients with photophobia experience significantly worse sleep quality compared to those without photophobia. Furthermore, the t-test showed a significant difference between patients with and without photophobia in terms of SOL (t (850) = -4.89, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), SDis (t (850) = -4.70, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and SRI (t (810) = -4.28, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the means (SD) and results of t-test analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of SQ, SDis, SOL, and SRI between migraine patients with and without photophobia.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMigraine without photophobia\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;549)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMigraine with photophobia\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;303)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et (df)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep Quality Score (SQ)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.33 (12.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.30 (14.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-7.17 (850)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep Disturbance Score (SDis)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.89 (8.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.04 (10.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.702 (850)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.34\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep Onset Latency (SOL) in minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.65 (30.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.00 (48.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.89 (850)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep-Related Impairment score (SRI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.15 (3.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.33 (3.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.28 (810)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.31 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e* Two-tailed, Significant at α\u0026thinsp;=\u0026thinsp;0.05\u003c/p\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Cohen\u0026rsquo;s d calculation: Small to medium effect size.\u003c/p\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Cohen\u0026rsquo;s d calculation: medium effect size.\u003c/p\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Photosensitivity global score\u0026thinsp;≧\u0026thinsp;0\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Photosensitivity global score\u0026thinsp;\u0026lt;\u0026thinsp;0\u003c/p\u003e \u003cp\u003e\u003csup\u003e3\u003c/sup\u003e Higher scores indicate worsen sleep quality and sleep disturbance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe overall regression model including the primary predictor of photophobia and the covariates reached statistical significance (Adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.330, F (5, 846)\u0026thinsp;=\u0026thinsp;84.895, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). After controlling for age, sex, depression, and anxiety, the regression coefficient for photophobia was statistically significant (β\u0026thinsp;=\u0026thinsp;0.176, t\u0026thinsp;=\u0026thinsp;5.799, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This means that for every point increase in photophobia, the sleep quality worsens by 0.176 points. Additionally, there was a statistically significant association between photophobia with SDis (β\u0026thinsp;=\u0026thinsp;0.135, t\u0026thinsp;=\u0026thinsp;4.104, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), SOL (β\u0026thinsp;=\u0026thinsp;0.092, t\u0026thinsp;=\u0026thinsp;2.559, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011), and SRI (β\u0026thinsp;=\u0026thinsp;0.081, t\u0026thinsp;=\u0026thinsp;2.457, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014) when considering age, sex, depression, and anxiety as covariates in the models. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows results for the photophobia regression analyses.\u003c/p\u003e \u003cp\u003eSimilarly, we conducted a linear regression to investigate the relationship between photophilia and sleep quality in patients with migraine. The overall regression model for the primary predictor of photophilia and the covariates reached statistical significance (Adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.314, F (5, 846)\u0026thinsp;=\u0026thinsp;79.061, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). After controlling for age, sex, depression, and anxiety, the regression coefficient for photophilia was β = -0.107, was statistically significant (t = -3.665, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This indicates that for every point increase in photophilia, the sleep quality improves by 0.107 points. Furthermore, there was a statistically significant association between photophilia with SDis (β = -0.009, t = -8.564, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and SOL (β = -0.083, t = -2.423, p\u0026thinsp;=\u0026thinsp;0.016). We also conducted a separate linear regression to investigate the relationship between photophilia and SRI with the same covariates. While the overall model was statically significant (Adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.241, F (5, 806)\u0026thinsp;=\u0026thinsp;52.558, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the β coefficient did not reach statistical significance (β = -0.01, t = -0.295, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.768), suggesting that photophilia, when considered alongside the age, sex, depression, and anxiety, did not have a statistically significant linear relationship with SRI.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLinear regressions for investigating relationships between photophobia and photophilia with SQ, SDist, SOL, and SRI.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eRegression \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eCoefficients\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdj. R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ef\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep Quality (SQ)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhotophobia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhotophilia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.46 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSleep Disturbance (SDis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhotophobia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhotophilia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.027*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSleep Onset Latency (SOL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhotophobia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.067 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.011*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhotophilia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.067 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.016*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSleep-related Impairment (SRI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhotophobia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.014*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhotophilia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e*Significant at α\u0026thinsp;=\u0026thinsp;0.05\u003c/p\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Overall regression model including photophobia or photophilia as the primary predictor and age, sex, anxiety, and depression as covariates.\u003c/p\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003ef\u003csup\u003e2\u003c/sup\u003e = Cohen\u0026rsquo;s F calculation: Small effect size.\u003c/p\u003e \u003cp\u003e\u003csup\u003ec\u003c/sup\u003ef\u003csup\u003e2\u003c/sup\u003e = Cohen\u0026rsquo;s F calculation: Small to medium effect size.\u003c/p\u003e \u003cp\u003eSE\u0026thinsp;=\u0026thinsp;Coefficients Standard Error\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;852\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":" \u003cp\u003eWe investigated the relationship between photosensitivity and various metrics of sleep including sleep quality, sleep disturbance, sleep onset latency, and sleep-related impairments in patients with migraine. The results were obtained using existing data extracted from ARMR from 852 patients who met the inclusion criteria. Poor sleep quality was prevalent among our participants, with over 46% reporting lack of good sleep quality. In line with several previous inquiries [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], our data exhibited insomnia as the most frequently reported sleep disorder among patients with migraine. Additionally, this study presents novel findings, demonstrating that patients with migraine with generalized photophobia tend to have poorer sleep quality compared to those without photophobia (including patients with photophilia). Both photophobia and photophilia exhibited statistically significant associations with sleep quality, sleep disturbance, and sleep onset latency. As we hypothesized, greater severity of photophobia emerged as a predictor for compromised sleep quality, increased sleep disturbance, and prolonged sleep onset latency. Conversely, a tendency for light, or photophilia, was correlated with enhanced sleep quality and lower levels of sleep disturbance and sleep onset latency. These results persisted after controlling for patient age, sex, anxiety, and depression. Our findings are aligned with a limited number of prior studies that reported photophobia as a potential risk factor for sleep disorders in migraine [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] as well as with the emerging body of literature highlighting the complex effects of light exposure on sleep quality [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrior studies have demonstrated that retinal light exposure serves as a direct stimulant for the brain\u0026rsquo;s biological clock, exerting profound effects on various facets of sleep such as sleep pattern, sleep onset latency, sleep duration, and sleep efficiency [\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The rhythmic interplay of light and darkness experienced throughout the day intricately orchestrates the timing of the circadian clock. To synchronize harmoniously with the natural light-dark cycle of Earth, a consistent exposure to high levels of morning light and a contrast between daytime and nighttime light exposure are essential. In a study by Figueiro et al. [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], it was observed that exposure to high levels of lighting in the morning was associated with reduced sleep onset latency, increased phasor magnitudes (which is a measure of circadian entrainment), and increased sleep quality in adult participants. These findings were aligned with other similar inquiries on other age groups [\u003cspan additionalcitationids=\"CR47\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Whereas there is growing evidence for circadian relevance in migraine and other pain disorders [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], none of the previous studies were focused on circadian effects of light on patients with migraine with photosensitivity.\u003c/p\u003e \u003cp\u003eA prevalent coping strategy to alleviate discomfort and pain induced by migraine-associated photosensitivity involves seeking refuge in darkness, often by spending extended periods in dimly lit or dark rooms and donning dark or tinted sunglasses. These behaviors not only reduce the retinal light exposure during the daytime in patients with migraine, but also inadvertently result in constant lighting conditions, devoid of the natural contrast between the day and night. Consequently, the biological clock is deprived of a crucial time cue to stimulate the circadian clock accordingly, potentially leading to disruptions in sleep, prolonged sleep onset, and poor sleep quality.\u003c/p\u003e \u003cp\u003eIn those with migraine, insufficient sleep and sleep disturbance have consistently emerged as frequent headache triggers [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Conversely, adequate sleep timing, duration, and quality has been reported to be protective against headache [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Given the therapeutic effects of high-quality sleep in managing migraine and the potential adverse effects of pharmacological treatments, implementing non-drug interventions appears to be an effective initial approach to improve sleep quality in this population. Lighting, in particular, has been demonstrated as a potent non-pharmacological intervention capable of improving sleep and circadian activity rhythms, among other benefits [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. In a study by Burgess et al. [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], the findings revealed that bright light therapy in the morning advanced circadian phase which was associated with an increased tolerance to pain. The positive association we found between photophilia and improved sleep outcomes further supports the potential beneficial effects of light exposure on sleep outcomes amongst those with migraine. It is reasonable to assume that patients with migraine with photophilia tend to receive more retinal light exposure during the daytime which could potentially be the reason for enhanced sleep outcomes in this population. In a recent open-label study, self-reported data revealed that two hours of exposure to narrow band green light led to an improvement in photophobia and same-night sleep for 53% and 49% of all migraine attacks, on average, respectively. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, it is not clear whether the improvement in sleep was due to the effects of light exposure on circadian activity rhythms or as a result of enhanced mood, photophobia, or headache improvement.\u003c/p\u003e \u003cp\u003eCircadian stimulation by light is achieved through exposure to high-intensity lighting with a blue-enriched spectrum during the daytime. Nevertheless, the prevalence of photophobia in migraine poses a challenge to the implementation of circadian lighting for this population, given their severe sensitivity to high intensity light, particularly in the blue spectrum [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. The emergence of new lighting technology holds promise for enhancing well-being among those with migraine through offering customized lighting solutions with optimized intensity and spectrum tailored to individuals\u0026rsquo; needs, while maintaining circadian rhythms by following a natural light/dark cycle. Exposure to proper circadian lighting not only has the potential to improve sleep quality in patients with migraine but also could contribute to positive effects on anxiety and depressive symptoms \u0026ndash; both highly associated with migraine and photophobia.\u003c/p\u003e \u003cp\u003eThe recruitment of patients from nine different sites across the United States, the large sample size, and the diverse geographical locations of enrollment enhance the potential generalizability of our findings. However, the findings of this study are limited as we only included patients from headache specialty centers who tended to have high frequency migraine and likely represent a population with severe migraine disease. To improve generalizability, future studies should include a more diverse population. Our study is also limited by its reliance on self-reported data for photosensitivity and sleep quality, collected through instruments selected by the ARMR study team. Self-reported data are inherently subjective as they rely on individuals\u0026rsquo; subjective perceptions, introducing the possibility of recall bias. Additionally, the photosensitivity questionnaire (PAQ) utilized in ARMR, while well-validated, lacks specific assessments of headache-related light sensitivity, focusing instead on non-specific behavioral preferences. Similar limitations apply to the sleep questionnaire, which incorporates partial components from various instruments and does not include the entire set of questions from a single validated questionnaire. That makes interpretation and analysis of the sleep data challenging. Future studies should consider supplementing subjective measures with objective ones (i.e., actigraphy, wearable light trackers) to acquire precise data on sleep quality and daily light exposure behavior among patients with migraine. Furthermore, experimental trials aimed at investigating the effects of various lighting interventions on sleep quality and circadian health of those with migraine could offer valuable insights. Such research might pave the way for the development of novel lighting technologies, contributing to the improvement of well-being in this population.\u003c/p\u003e \u003cp\u003eLastly, it is important to acknowledge a limitation inherent in the ARMR dataset [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], which pertains to the unbalanced racial distribution of the sample. The participants in this registry are predominantly White, a characteristic that is apparent in the sample included in our analysis (94.1% White). This feature of the dataset, undeniably, limits the generalizability of our findings. It is imperative for future research to include a more diverse sample for extrapolating the results.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study demonstrated that patients with migraine with photophobia experienced worse sleep quality compared to those without generalized photophobia. Both photophobia and generalized photophilia exhibited significant associations with sleep quality, sleep disturbance, and sleep onset latency, persisting after adjusting for age, sex, anxiety, and depression. These findings suggest photophobia as a potential risk factor for sleep disorders in migraine. This relationship could be explained by the well-established influence of light on circadian activity rhythms mediated by the ipRGCs in the retina. Given the high prevalence of photophobia and sleep disorders among patients with migraine and their impacts on overall quality of life, these findings highlight the need for in-depth systematic exploration of the relationship between photophobia and sleep in this population. Such research can provide insights that will help pave the path for developing novel lighting technologies and design solutions to address the specific needs of those with migraine.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cb\u003eHuma ethics approval and consent to participate\u003c/b\u003e \u003c/p\u003e \u003cp\u003e The research was performed in accordance with the Declaration of Helsinki and was authorized by the Institutional Review Boards at each enrolling site (Mayo Clinic, University of Utah, University of Texas Health Science Center at Houston, University of Colorado, Georgetown University Medical Center, DENT Neurologic Institute, Dartmouth-Hitchcock Medical Center, Thomas Jefferson University Headache Center, and Yale University). All research participants completed and signed an informed consent document.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eThe authors approved the publication of this paper.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cp\u003eNina Sharp, Kathleen B Digre , Mahya Fani, and Sophia Lamp declare no competing interests. Within the prior 24 months, Todd Schwedt has received compensation for consulting with Abbvie, Allergan, Amgen, Axsome, Biodelivery Science, Biohaven, Collegium, Eli Lilly, Linpharma, Lundbeck, Satsuma, Scilex, and Theranica, royalties from Up To Date, and research funding from American Heart Association, Amgen, National Institutes of Health, Mayo Clinic, Spark Neuro, and United States Department of Defense. He holds stock options in Aural Analytics and GBS Ventures. Mark Burish was a consultant for Beckley Psytech limited, Lundbeck, Praxis Precision Medicines, and PureTech Health. He was a site investigator for a cluster headache clinical trial funded by Lundbeck. He was a paid guest for a video podcast by the American Academy of Neurology. He is an unpaid member of the medical advisory board of Clusterbusters. Jessica Ailani has served as a consultant for Abbvie, Amgen, Aeon, Axsome, Dr. Reddy, Eli-Lilly, GlaxoSmithKline, Lundbeck, Linpharma, Ipsen, Merz, Miravio, Pfizer, Neurolief, Gore, Satsuma, Scilex, Theranica, and Toni. She has had grants to her institution for clinical trials by Parema and Ipsen and has served on the editorial board for Current Pain and Headache Reports and Medscape and served as a medical editor for SELF magazine.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNo funding was received to support this analysis of ARMR data.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eNS and TS generated the study concept and design. NS conducted the data analysis and interpretation of results with support from SL and MF. NS wrote the first draft of the manuscript. TS and MB conducted critical revisions of the manuscript. KD and JA provided valuable comments and all authors revised and edited the manuscript. All authors read and approved the final version of the manuscript. The corresponding author confirms that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThe authors gratefully acknowledge the American Migraine Foundation and the American Registry for Migraine Research (ARMR) for the use of registry data to conduct this research. In addition, we would like to thank the patients and clinicians who participated in ARMR. Kathleen Digre is supported in part by an Unrestricted Grant from Research to Prevent Blindness, New York, NY, to the Department of Ophthalmology \u0026amp; Visual Sciences, University of Utah.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eThe datasets analyzed in this study are contained within the American Registry for Migraine Research (ARMR). Data access requests should be directed to the American Migraine Foundation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAshina M, Terwindt GM, Al-Karagholi MA-M et al (2021) Migraine: disease characterisation, biomarkers, and precision medicine. The Lancet 397:1496\u0026ndash;1504. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(20)32162-0\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(20)32162-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLipton RB, Fanning KM, Buse DC et al (2018) Identifying Natural Subgroups of Migraine Based on Comorbidity and Concomitant Condition Profiles: Results of the Chronic Migraine Epidemiology and Outcomes (CaMEO) Study. 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Brain 139:1971\u0026ndash;1986. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/brain/aww119\u003c/span\u003e\u003cspan address=\"10.1093/brain/aww119\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-journal-of-headache-and-pain","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tjhp","sideBox":"Learn more about [The Journal of Headache and Pain](https://thejournalofheadacheandpain.biomedcentral.com/)","snPcode":"10194","submissionUrl":"https://submission.nature.com/new-submission/10194/3","title":"The Journal of Headache and Pain","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Migraine, Headache, Photophobia, Sleep, Photophilia, Light, Circadian","lastPublishedDoi":"10.21203/rs.3.rs-3864442/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3864442/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground. \u003c/strong\u003ePatients with migraine often have poor sleep quality between and during migraine attacks. Furthermore, extensive research has identified photophobia as the most common and most bothersome symptom in individuals with migraine, second only to headache. Seeking the comfort of darkness is a common strategy for managing pain during an attack and preventing its recurrence between episodes. Given the well-established effects of daily light exposure on circadian activity rhythms and sleep quality, this study aims to investigate the relationship between photophobia symptoms and sleep quality in a cohort of patients with migraine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods. \u003c/strong\u003eA cross-sectional observational study was conducted using existing data extracted from the American Registry for Migraine Research (ARMR). Participants with a migraine diagnosis who had completed the baseline questionnaires (Photosensitivity Assessment Questionnaire (PAQ), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-2 (PHQ-2)), and selected questions of the ARMR Sleep questionnaire were included. Models were created to describe the relationship of photophobia and photophilia with various sleep facets, including sleep quality (SQ), sleep disturbance (SDis), sleep onset latency (SOL), and sleep-related impairments (SRI). Each model was controlled for age, sex, anxiety, and depression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults.\u003c/strong\u003e A total of 852 patients meeting the inclusion criteria were included in the analysis (mean age (SD) = 49.8 (13.9), 86.6% (n = 738) female). Those with photophobia exhibited significantly poorer sleep quality compared to patients without photophobia (p \u0026lt; 0.001). Photophobia scores were associated with SQ (p \u0026lt; 0.001), SDis (p \u0026lt; 0.001), SOL (p = 0.011), and SRI (p = 0.014), after controlling for age, sex, depression, and anxiety, signifying that higher levels of photophobia were associated with worse sleep-related outcomes. Conversely, photophilia scores were associated with better sleep-related outcomes for SQ (p \u0026lt; 0.001), SDis (p \u0026lt; 0.001), and SOL (p = 0.016).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion. \u003c/strong\u003eResults suggest that photophobia is a risk factor for sleep disorders in those with migraine. These results underscore the necessity for comprehensive and systematic investigations into the intricate interplay between photophobia and sleep to enhance our understanding and develop tailored solutions for individuals with migraine.\u003c/p\u003e","manuscriptTitle":"Photophobia is associated with lower sleep quality in individuals with migraine: Results from the American Registry for Migraine Research (ARMR)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-22 08:24:57","doi":"10.21203/rs.3.rs-3864442/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-02-03T01:07:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-01-30T22:09:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"86e9cf16-036c-4403-bfb6-2c86c5f47022","date":"2024-01-18T15:11:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-18T15:03:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-18T11:00:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-18T11:00:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"The Journal of Headache and Pain","date":"2024-01-14T21:14:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"the-journal-of-headache-and-pain","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tjhp","sideBox":"Learn more about [The Journal of Headache and Pain](https://thejournalofheadacheandpain.biomedcentral.com/)","snPcode":"10194","submissionUrl":"https://submission.nature.com/new-submission/10194/3","title":"The Journal of Headache and Pain","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65a79f0e-0cd5-455c-b46a-c18c2a16f0fb","owner":[],"postedDate":"January 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-04-15T15:09:46+00:00","versionOfRecord":{"articleIdentity":"rs-3864442","link":"https://doi.org/10.1186/s10194-024-01756-9","journal":{"identity":"the-journal-of-headache-and-pain","isVorOnly":false,"title":"The Journal of Headache and Pain"},"publishedOn":"2024-04-12 15:02:01","publishedOnDateReadable":"April 12th, 2024"},"versionCreatedAt":"2024-01-22 08:24:57","video":"","vorDoi":"10.1186/s10194-024-01756-9","vorDoiUrl":"https://doi.org/10.1186/s10194-024-01756-9","workflowStages":[]},"version":"v1","identity":"rs-3864442","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3864442","identity":"rs-3864442","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}