
==== Front
BMC Public Health
BMC Public Health
BMC Public Health
1471-2458
BioMed Central London

39232706
19898
10.1186/s12889-024-19898-5
Research
The association between epilepsy and sleep disturbance in US adults: the mediating effect of depression
Wen Qianhui 12
Wang Qian 12
Yang Hua yanghua202203@163.com

12
1 grid.13291.38 0000 0001 0807 1581 Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan China
2 https://ror.org/011ashp19 grid.13291.38 0000 0001 0807 1581 Key Laboratory of Obstetric & Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, Sichuan University, Chengdu, Sichuan China
4 9 2024
4 9 2024
2024
24 241220 6 2024
27 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Background

People with epilepsy (PWE) frequently experience sleep disturbances that can severely affect their quality of life. Depression is also a common symptom in the PWE population and can aggravate sleep problems. However, the interplay between epilepsy, depression, and sleep disturbances is not yet fully understood. Our study was designed to investigate the association between epilepsy and sleep disturbances in US adults and to determine whether depressive symptoms play a mediating role in this relationship.

Methods

We examined data from the National Health and Nutrition Examination Survey (NHANES) spanning January 1, 2015, to March 2020, before the pandemic.A total of 10,093 participants aged ≥ 20 years with complete data on epilepsy and sleep disturbance were included. Weighted multiple logistic regression and mediation analysis were used to explore the associations among depression, epilepsy, and sleep disturbance. Interaction effects of epilepsy with various covariates were also investigated.

Results

Epilepsy was associated with depression and sleep disturbances. Weighted logistic regression analysis revealed a significant association between epilepsy and sleep disturbances (OR = 3.67, 95% CI = 1.68–8.04). Depression partially mediated this relationship, demonstrating a mediation effect of 23.0% (indirect effect = 0.037, P < 0.001). Subgroup analyses revealed variations in the relationship between epilepsy and sleep disturbances among different groups. Furthermore, interaction analyses revealed significant interactions between epilepsy and age (P = 0.049) and hypertension (P = 0.045).

Conclusions

Our study utilizing NHANES data confirmed that depression partially mediated the association between epilepsy and sleep disturbance. Additionally, we observed differences in this association across demographic groups. Addressing depressive symptoms in PWE may improve their sleep quality, but further research is needed to explore the underlying mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-024-19898-5.

Keywords

Epilepsy
Sleep disturbance
Depression
Mediation effect
NHANES
issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
==== Body
pmcIntroduction

Sleep disturbances frequently present serious challenges for individuals diagnosed with epilepsy. Earlier studies indicate that people with epilepsy (PWE) experience twice the frequency of sleep disturbances compared to their healthy counterparts [1, 2]. These disruptions primarily encompass difficulties in the onset and maintenance of sleep [2], regular nighttime awakenings, and episodes of obstructive sleep apnea [3]. Consequently, PWE often experience fatigue, cognitive impairments, and increased daytime sleepiness, compounding the difficulties they encounter in managing their health [4, 5].

Numerous studies have investigated the possible pathophysiological mechanisms contributing to sleep disturbances in this population. It is widely recognized that multiple contributors may influence the onset and development of sleep disturbances, including alterations in neurotransmitter systems, neuroendocrine dysfunction, and changes in sleep architecture [6]. Additionally, the adverse effects of antiepileptic medications [7], frequent nocturnal seizures [8], poor sleep hygiene habits, and psychological factors may worsen sleep issues in PWE.

Depression frequently coexists with epilepsy, affecting more than one-third of PWE [9]. A study conducted in China reported that 28.8% of PWE suffer from depression [10]. Fiest et al., in a meta-analysis, found that depression rates in PWE are 23.1% [11]. Hospitalized PWE exhibit an even higher depression rate, exceeding 50%, compared to approximately 8% among patients in remission [12]. The combination of social isolation, dysfunction, and inappropriate use of antiepileptic medications has the potential to trigger depressive symptoms [13]. Population-based studies suggest that individuals with prior depression have an elevated likelihood of developing epilepsy, ranging from four to seven times the risk compared to the broader population [14]. The comorbidity of epilepsy and depression is often caused or induced by a combination of pathological mechanisms, such as neurotransmitter imbalance, hippocampal dysfunction, and endocrine dysregulation [15, 16].

Notably, sleep disturbances and symptoms of depression often co-occur and exhibit patterns of interaction and influence [17]. Depressed individuals commonly suffer from a variety of sleep issues, including insomnia, excessive daytime sleepiness, and disrupted sleep-wake patterns [18]. Sleep disturbances can also serve as precipitating factors in the onset and progression of depression, exerting adverse effects on emotional regulation, cognitive function, and neuroendocrine homeostasis.

Although depression and sleep disturbances have been extensively discussed in the context of epilepsy, existing studies often isolate the relationship between epilepsy and sleep or between epilepsy and depression. However, this segmented perspective may overlook the potential complex interactions among these three factors. Understanding these interactions is crucial for enhancing management strategies and improving treatment outcomes. Thus, our study aimed to evaluate the association between epilepsy and sleep disturbances among adults in the United States, specifically investigating the potential role of depression as a mediator.

Methods

Study design and participants

Our study drew on data from the National Health and Nutrition Examination Survey (NHANES), a comprehensive database initiated in 1999, which evaluates the health and nutritional status of the U.S. population [19].To ensure national representativeness, the NHANES employs a continuous multistage probability sampling method. The NHANES study was granted ethical approval by the Research Ethics Review Board of the National Center for Health Statistics, and all participants provided informed consent prior to their involvement. Furthermore, this database is publicly accessible, and no additional ethical or administrative permissions are required. We adhered to NHANES guidelines and regulations in all analyses conducted. We included participants from the NHANES data collected between January 1, 2015, and March 2020 (prepandemic), as this period encompassed the comprehensive set of variables essential for this investigation, including the utilization of prescription medications, sleep assessment, and the Patient Health Questionnaire 9 (PHQ-9). Figure 1 illustrates the diagram of the screening procedure.

Fig. 1 Flow chart of the screening process from National Health and Nutrition Examination Survey. Abbreviations: PIR, poverty income ratio; CHD, coronary heart disease; PHQ-9, Patient Health Questionnaire-9

Antiepileptic drug use and epilepsy diagnosis

The NHANES survey assessed participants to determine if they had taken any prescription drugs in the past 30 days, querying them on the generic names of the medications, the primary reasons for their use, and any corresponding ICD-10-CM codes provided. Detailed codes and names of antiepileptic drugs are listed in Table S1. PWE were identified by their use of antiepileptic medications and the relevant ICD-10-CM codes [20, 21].

Assessment of sleep disturbance

Sleep parameter data were obtained from the “Sleep Disorders” dataset of the NHANES questionnaire [22]. Participants reported their typical nightly sleep hours on weekdays or workdays. Sleep duration was categorized as short (< 7 h), normal (7–9 h), or long (> 9 h) based on these reports [23]. Participants were also asked whether they had informed a doctor about their sleep difficulties, which was used to assess the presence of trouble sleeping. Table 1 outlines the calculation of a sleep quality score, incorporating sleep duration, trouble sleeping, snoring, snorting, or stopping breathing, and excessive daytime sleepiness as metrics. Scores ranged from 0 to 5, with lower scores indicating poorer sleep quality [24]. A sleep quality score below 2 points indicated the presence of sleep disturbances [25].

Table 1 Definition of sleep quality score

Sleep factors	Sleep condition	Sleep score	
Sleep duration (h)	< 7	0	
7–9	1	
> 9	0	
Trouble sleeping	No	1	
Yes	0	
Snoring	Never	1	
Rarely/occasionally/frequently	0	
Excessive daytime sleep	Never/rarely	1	
Rarely/sometimes/occasionally/frequently	0	
Sleep apnea symptoms	Never	1	
Rarely/sometimes/occasionally/frequently	0	
Sleep quality score	0–5	

Assessment of depression

Depression data were derived from the “Mental Health - Depression Screener” dataset within the NHANES questionnaire. Depression severity was assessed using the PHQ-9 questionnaire, a reliable and validated diagnostic tool designed to evaluate mood disorders based on diagnostic criteria for depression [26]. The questionnaire consists of nine questions, each scored on a scale of 0 to 3, resulting in a total score ranging from 0 to 27. A higher cumulative score signifies increased severity of depression [27, 28].A PHQ-9 total score ≥ 10 is considered indicative of major depressive disorder (MDD) [29].

Potential covariates

Demographic covariates were gathered through household interviews, while health-related covariates were assessed at Mobile Examination Centers (MEC). Age was stratified as < 40, 40–60, and > 60 years. Race categories were defined as Mexican American, non-Hispanic White, non-Hispanic Black, other Hispanic, and other races. Educational attainment was categorized into three groups: less than high school, high school graduate, and beyond high school. Marital status was classified as never married, married or living with a partner, and widowed, divorced, or separated. Poverty income ratio (PIR) was categorized as < 2 (low-income) and ≥ 2 (moderate to high-income).Participants reporting having smoked at least 100 cigarettes in their lifetime were classified as smokers. Hypertension was determined by clinical diagnosis, ongoing treatment with hypertension medication, or blood pressure readings above 140 mmHg for systolic or 90 mmHg for diastolic pressure measured during the physical assessment. Average blood pressure was calculated from up to three readings taken at different times. The presence of diabetes was confirmed using any of the following criteria: (1) hemoglobin A1C levels at or above 6.5%, or fasting blood glucose levels equal to or exceeding 126 mg/dL [30]; (2) physician-diagnosed diabetes, or use of anti-hyperglycemic medication or insulin. Diagnosis of coronary heart disease (CHD) and asthma was determined based on participants’ responses to whether they had ever been diagnosed with these conditions.

Statistical analysis

Given the complex multistage sampling strategy of NHANES, the data were combined and adjusted using the wtmec2 year weighting factor. Baseline characteristics were compared using t-tests for continuous variables and chi-square tests for categorical variables.Continuous data were presented as mean (standard deviation), and categorical data as weighted numbers (weighted percentages). To investigate the association between epilepsy and sleep disturbances, we utilized weighted univariate and multivariate logistic regression analyses. Three models were employed: Model 1, with no covariate adjustments; Model 2, adjusted for age, sex, race, education, marital status, and PIR; and Model 3, which included adjustments for all covariates. Mediation analyses were conducted to explore whether depression mediates the link between epilepsy and sleep disturbance. Subgroup and interaction analyses were employed to investigate associations between epilepsy and various covariates.Findings were presented as odds ratios (ORs) with 95% confidence intervals (CIs). All statistical procedures were conducted using R Studio (version 4.3.2), with a significance level set at P < 0.05.

Results

Population characteristics

Descriptive statistics of the study are detailed in Table 2. Following a sequence of screening processes, 10,093 individuals were selected from the NHANES database (January 1, 2015 - March 2020), representing a sample of 187,353,423 individuals in the general population. Among these individuals, 73 (weighted count 1,002,936) were diagnosed with epilepsy, while 10,020 (weighted count 186,350,487) were not. Compared to the control group, PWE significantly more frequently experienced MDD (18.84% vs. 7.57%, P = 0.003) and sleep disturbances (47.17% vs. 15.48%, P < 0.001). Additionally, there were statistically significant differences in terms of PIR, prevalence of hypertension, diabetes, and asthma, as well as PHQ-9 scores between individuals with and without epilepsy (P < 0.05).

Table 2 Characteristics of the participants in the NHANES

Variables	Overall	Control Group	Epilepsy Group	P-valued	
	n = 10,093a	n = 187,353,423b	n = 10,020a	n = 186,350,487 b	n = 73a	n = 1,002,936 b		
Sex	0.6	
Female	5,118 (50.71%)	95,652,900 (51.05%)	5,079 (50.69%)	95,087,093 (51.03%)	39 (53.42%)	565,807 (56.42%)		
Male	4,975 (49.29%)	91,700,523 (48.95%)	4,941 (49.31%)	91,263,393 (48.97%)	34 (46.58%)	437,129 (43.58%)		
Age (years)	0.2	
<40	3,352 (33.21%)	68,753,487 (36.70%)	3,336 (33.29%)	68,528,511 (36.77%)	16 (21.92%)	224,975 (22.43%)		
40–60	3,648 (36.14%)	70,648,211 (37.71%)	3,621 (36.14%)	70,214,351 (37.68%)	27 (36.99%)	433,860 (43.26%)		
>60	3,093 (30.65%)	47,951,726 (25.59%)	3,063 (30.57%)	47,607,625 (25.55%)	30 (41.10%)	344,101 (34.31%)		
Race	0.4	
Mexican American	1,362 (13.49%)	14,955,094 (7.98%)	1,352 (13.49%)	14,883,498 (7.99%)	10 (13.70%)	71,596 (7.14%)		
Other Hispanic	1,111 (11.01%)	12,226,964 (6.53%)	1,101 (10.99%)	12,131,335 (6.51%)	10 (13.70%)	95,629 (9.53%)		
Non-Hispanic white	3,653 (36.19%)	123,612,971 (65.98%)	3,624 (36.17%)	122,988,539 (66.00%)	29 (39.73%)	624,432 (62.26%)		
Non-Hispanic black	2,395 (23.73%)	19,781,239 (10.56%)	2,378 (23.73%)	19,623,729 (10.53%)	17 (23.29%)	157,510 (15.70%)		
Other race	1,572 (15.58%)	16,777,155 (8.95%)	1,565 (15.62%)	16,723,386 (8.97%)	7 (9.59%)	53,769 (5.36%)		
Education	0.3	
Less than high school	1,843 (18.26%)	19,838,777 (10.59%)	1,829 (18.25%)	19,718,999 (10.58%)	14 (19.18%)	119,778 (11.94%)		
High school	2,307 (22.86%)	45,250,047 (24.15%)	2,285 (22.80%)	44,907,803 (24.10%)	22 (30.14%)	342,244 (34.12%)		
High school or above	5,943 (58.88%)	122,264,599 (65.26%)	5,906 (58.94%)	121,723,685 (65.32%)	37 (50.68%)	540,914 (53.93%)		
Marital status	0.2	
Never married	1,869 (18.52%)	33,231,505 (17.74%)	1,849 (18.45%)	32,948,958 (17.68%)	20 (27.40%)	282,547 (28.17%)		
Widowed、Divorced、Separated	1,987 (19.69%)	30,231,818 (16.14%)	1,970 (19.66%)	30,034,550 (16.12%)	17 (23.29%)	197,268 (19.67%)		
Married、Living with partner	6,237 (61.80%)	123,890,100 (66.13%)	6,201 (61.89%)	123,366,979 (66.20%)	36 (49.32%)	523,121 (52.16%)		
PIR	< 0.001	
<2	4,610 (45.68%)	58,506,857 (31.23%)	4,563 (45.54%)	57,871,642 (31.06%)	47 (64.38%)	635,216 (63.34%)		
≥ 2	5,483 (54.32%)	128,846,566 (68.77%)	5,457 (54.46%)	128,478,845 (68.94%)	26 (35.62%)	367,721 (36.66%)		
Smoking	0.6	
No	5,844 (57.90%)	107,435,355 (57.34%)	5,809 (57.97%)	106,895,472 (57.36%)	35 (47.95%)	539,882 (53.83%)		
Yes	4,249 (42.10%)	79,918,069 (42.66%)	4,211 (42.03%)	79,455,015 (42.64%)	38 (52.05%)	463,054 (46.17%)		
Hypertention	0.009	
No	5,783 (57.30%)	117,566,199 (62.75%)	5,754 (57.43%)	117,168,625 (62.88%)	29 (39.73%)	397,574 (39.64%)		
Yes	4,310 (42.70%)	69,787,224 (37.25%)	4,266 (42.57%)	69,181,862 (37.12%)	44 (60.27%)	605,362 (60.36%)		
Diabetes	< 0.001	
No	8,160 (80.85%)	159,968,221 (85.38%)	8,111 (80.95%)	159,352,069 (85.51%)	49 (67.12%)	616,152 (61.43%)		
Yes	1,933 (19.15%)	27,385,202 (14.62%)	1,909 (19.05%)	26,998,418 (14.49%)	24 (32.88%)	386,784 (38.57%)		
CHD	0.4	
No	9,662 (95.73%)	180,160,819 (96.16%)	9,595 (95.76%)	179,225,292 (96.18%)	67 (91.78%)	935,527 (93.28%)		
Yes	431 (4.27%)	7,192,604 (3.84%)	425 (4.24%)	7,125,194 (3.82%)	6 (8.22%)	67,409 (6.72%)		
Asthma	0.006	
No	8,532 (84.53%)	158,714,524 (84.71%)	8,480 (84.63%)	158,020,820 (84.80%)	52 (71.23%)	693,704 (69.17%)		
Yes	1,561(15.47%)	28,638,899 (15.29%)	1,540 (15.37%)	28,329,667 (15.20%)	21 (28.77%)	309,233 (30.83%)		
PHQ-9 score c	3.07 (4.00)	3.05 (3.98)	5.49 (5.33)	0.039	
MDD	0.003	
No	9,266 (91.81%)	173,052,287 (92.37%)	9,209 (91.91%)	172,238,327 (92.43%)	57 (78.08%)	813,961 (81.16%)		
Yes	827 (8.19%)	14,301,136 (7.63%)	811 (8.09%)	14,112,160 (7.57%)	16 (21.92%)	188,976 (18.84%)		
Sleep disturbance	< 0.001	
No	8,505 (84.27%)	158,025,084 (84.35%)	8,458 (84.41%)	157,495,217 (84.52%)	47 (64.38%)	529,867 (52.83%)		
Yes	1,588 (15.73%)	29,328,340 (15.65%)	1,562 (15.59%)	28,855,270 (15.48%)	26 (35.62%)	473,070 (47.17%)		
Abbreviations: PIR, poverty income ratio; CHD, coronary heart disease; PHQ-9, Patient Health Questionnaire-9; MDD, major depressive disorder

an (percentages); bweighted n (weighted percentages); cMean (SD)

d chi-squared test with Rao & Scott’s second-order correction; Wilcoxon rank-sum test for complex survey sample

Weighted logistic regression

We performed weighted univariate and multivariate logistic regression analyses to examine the relationship between epilepsy and sleep disturbance. As shown in Table 3; Fig. 2, the fully adjusted model (Model 3) revealed a robust and statistically significant association between epilepsy and sleep disturbance (OR = 3.67, 95% CI = 1.68–8.04). Model 3 also indicated a significant relationship between MDD and the occurrence of sleep disturbances (OR = 3.32, 95% CI = 2.68–4.11).

Table 3 Associations of sleep disturbance with epilepsy and depression

	Model 1	Model 2	Model 3	
	OR(95% CI)	P	OR(95% CI)	P	OR(95% CI)	P	
Epilepsy	
No	Ref.		Ref.		Ref.		
Yes	4.87 (2.50, 9.50)	<0.001	4.43 (2.19, 8.93 )	<0.001	3.67 (1.68, 8.04)	0.002	
PHQ-9	1.15 (1.13, 1.17)	<0.001	1.16 (1.14, 1.18)	<0.001	1.14 (1.12, 1.16)	<0.001	
MDD	
No	Ref.		Ref.		Ref.		
Yes	3.93 (3.14, 4.92)	<0.001	4.04 (3.21, 5.08 )	<0.001	3.32 (2.68, 4.11)	<0.001	
Model 1: No covariate were adjusted. Model 2: Adjusted for age, sex, race, education, marital status and PIR. Model 3: Adjusted for age, sex, race, education, marital status, PIR, smoking status, diabetes, hypertension, CHD, asthma.Abbreviations: PHQ-9, Patient Health Questionnaire-9; MDD, major depressive disorder

Fig. 2 Mediational models. Abbreviations: ACME, average causal mediation effects; ADE, average direct effects; PM, proportion mediated.*indicates P < 0.01

Mediation analyses

The study evaluated the intermediary role of depression in the relationship between epilepsy and sleep disturbance through a mediation analysis. As depicted in Table 4, mediation effects were observed across all models. Specifically, in Model 1, the mediating impact represented 26.5% of the overall relationship between epilepsy and sleep disturbances (indirect effect = 0.053, 95% CI = 0.007–0.020, P < 0.001). In Model 2, with additional adjustments for age, sex, race, education level, marital status, and PIR, the mediation effect constituted 25.4% of the relationship (indirect effect = 0.049, 95% CI = 0.006–0.020, P < 0.001). With all covariates adjusted, the mediation effect comprised 23.0% of the total relationship (indirect effect = 0.037, 95% CI = 0.004–0.015, P < 0.001).

Table 4 Depression mediating the association between epilepsy and sleep disturbance

	ACME				ADE				Total effect				Proportion mediated				
	Estimate	95%CI lower	95%CI upper	P-value	Estimate	95%CI lower	95%CI upper	P-value	Estimate	95%CI lower	95%CI upper	P-value	Estimate	95%CI lower	95%CI upper	P-value	
Model 1	0.053	0.007	0.020	<0.001	0.147	0.066	0.228	<0.001	0.200	0.117	0.284	<0.001	0.265	0.117	0.648	<0.001	
Model 2	0.049	0.006	0.020	<0.001	0.144	0.063	0.224	<0.001	0.193	0.109	0.277	<0.001	0.254	0.112	0.395	<0.001	
Model 3	0.037	0.004	0.015	<0.001	0.124	0.044	0.204	0.002	0.161	0.078	0.243	<0.001	0.230	0.071	0.379	<0.001	
Model 1: No covariate were adjusted. Model 2: Adjusted for age, sex, race, education, marital status and PIR. Model 3: Adjusted for age, sex, race, education, marital status, PIR, smoking status, diabetes, hypertension, CHD, asthma. Abbreviations: ACME, average causal mediation effect; ADE, average direct effect

Stratified analyses and interaction analyses

Subgroup analysis elucidated the heterogeneity in the association between epilepsy and sleep disturbances across various demographic strata (Fig. 3). Notably, substantial disparities were identified among subgroups delineated by sex, age, race, educational level, marital status, PIR, smoking status, and the presence of hypertension, diabetes, CHD, and asthma (all P < 0.05). Specifically, significant differences were detected among males, females, those younger than 40 years, individuals aged 40–60 years, Mexican Americans, non-Hispanic whites, non-Hispanic blacks, individuals with education beyond high school and those with education lower than high school, those who were married or living with a partner, those with a PIR lower than 2, smokers, and those not suffering from hypertension, diabetes, CHD, or asthma. In the analysis of the interaction effects on subgroups, age (P = 0.049) and hypertension (P = 0.045) were found to interact with epilepsy. Participants under 40 years of age (OR = 3.50, 95% CI = 1.17–10.47, P = 0.025) and those aged 40–60 years (OR = 4.22, 95% CI = 1.90–9.34, P < 0.001) had a higher risk of sleep disturbance compared to those over 60 years old. Participants without hypertension (OR = 4.45, 95% CI = 2.05–9.68, P < 0.001) showed a higher risk of sleep disturbance compared to those with hypertension.

Fig. 3 Subgroup analysis of the association between epilepsy and sleep disturbance. Eachstratification was adjusted for sex, age, race, education level, marital status, PIR, smoking status, hypertension, diabetes, CHD and asthmaexcept the stratification factor itself. Abbreviations: PIR, poverty income ratio; CHD, coronary heart disease

Discussion

Our research investigated the connection between epilepsy and sleep disturbances using NHANES data. After adjusting for all confounders, we revealed a higher prevalence of sleep disturbance in PWE, which was consistent with prior research [31, 32]. Furthermore, mediation models highlighted that depression was significantly correlated with sleep disturbances in the adult American population.

A multitude of studies have documented a significant link between depressive states and disruptions in sleep [33]. Lin et al. identified several shared genetic variations, including MEIS1, OLFM4, and HEXIM1, that link MDD with insomnia [34]. Zhao et al. conducted research on 3,275 MDD patients at 32 different sub-centers, uncovering that more than 70% suffered from sleep disturbances [35]. Our data reaffirmed this association. In a retrospective and prospective collaborative study, it was found that higher depression scores could predict sleep disturbances in PWE [36]. Some researchers believe that depression, rather than epilepsy itself, is the main cause of sleep disturbances [37], which contradicts our findings. We identified epilepsy as an important contributing factor to sleep disturbances, with depression mediating approximately 23.0–26.5% of the relationship between epilepsy and sleep disturbances across various mediation models.

Epilepsy patients are at an elevated risk of experiencing sleep disturbances. Due to the considerable risks posed by comorbid conditions, extensive research has been conducted into the causes of the concurrent presence of epilepsy and sleep disorders, as well as the exploration of preventive measures [38]. Our study revealed that the prevalence of sleep disturbances among epilepsy patients was strikingly high at 47.17%, significantly exceeding that observed in the control group. A cross-sectional study indicated that 50.4% of epilepsy patients reported suffering from insomnia [39]. In a meta-analysis encompassing 25 original studies, Bergmann et al. revealed that epilepsy patients had notably higher Pittsburgh Sleep Quality Index scores than their counterparts [40]. Epileptic seizures often manifest during sleep, and recurrent episodes can disrupt sleep microstructure, hindering the progression from light to deep sleep stages, thus impacting both the quality and duration of sleep [41]. Certain antiepileptic drugs such as barbiturates and phenytoin may directly alter sleep patterns, induce drowsiness, reduce sleep quality, or trigger other related issues [42, 43].

Through subgroup analysis and interaction tests, we identified significant interactions between age, hypertension, and epilepsy regarding sleep disturbances. Our study findings indicate that epilepsy significantly increases the risk of sleep disturbance in individuals aged ≤ 60 years, whereas the association is not evident in individuals aged > 60 years. Possible explanations include age-related alterations in sleep architecture, coupled with the influence of physiological changes and comorbid chronic conditions [44, 45].It is important to recognize that although our findings reveal that the likelihood of sleep disturbances in epilepsy patients without hypertension is 4.45 times higher than in patients without epilepsy, this association is weakened among patients with hypertension. One must be cautious in interpreting these observations. Certain antihypertensive medications, including Alpha-2 agonists, can regulate the sleep structure of patients [46]. Additionally, hypertension often coexists with cardiovascular and cerebrovascular diseases [47, 48], obesity [49], and multiple comorbidities [50], potentially contributing to an elevated prevalence of sleep disturbances among hypertensive individuals, irrespective of epilepsy diagnosis. Moreover, elevated blood pressure can result in compromised regulation of cerebral blood flow [51] and perturb the equilibrium of neurotransmitters in the brain, thereby disrupting typical sleep patterns. Hence, the link between epilepsy, hypertension, and sleep disturbances may be attributed to a shared pathophysiological mechanism rather than a direct causal link.

Our study utilized a large dataset representing a national population sample to confirm that depression is a significant factor contributing to sleep disturbances in PWE. Additionally, we investigated the effects of multiple factors such as age, racial background, and the presence of hypertension. Disturbances in sleep can profoundly affect the well-being of individuals with epilepsy and have been associated with a wide range of health concerns, as indicated by prior research [52, 53]. Addressing depressive symptoms may lead to improvements in sleep quality and, consequently, promote the overall health and well-being of individuals in this patient population.

Despite the findings, our research is subject to constraints. Primarily, the cross-sectional design prevents the determination of cause-and-effect relationships between epilepsy, depressive symptoms, and sleep disturbances. Furthermore, our selection criteria, based on pre-existing data, may not fully represent the entire epilepsy patient population. Some individuals may not have undergone standardized antiepileptic medication therapy, and some patients with a history of epilepsy did not take antiepileptic medications within the last 30 days of the survey. Additionally, the study did not consider the impact of antiepileptic drugs on sleep and depression, nor did it include key variables such as epilepsy duration, types of seizures, and seizure frequency, which were absent due to insufficient NHANES data. Another limitation arises from our reliance on self-reported assessments of sleep disturbances, lacking objective measures such as actigraphy or polysomnography, potentially introducing reporting bias. Furthermore, the use of the PHQ-9 for diagnosing depression lacks clinical confirmation. These limitations should be considered and addressed in future research.

Conclusion

This investigation reveals a strong correlation between epilepsy and the occurrence of sleep disturbances. The role of depression as a key factor in this correlation underscores the intricate links between epilepsy, psychological health, and sleep disturbances. Despite these insights, additional research is necessary to determine causal relationships and to explore the potential mechanisms. Furthermore, expanded prospective studies are required to confirm these observations and to guide the development of more precise strategies for enhancing sleep and overall health in the epileptic population.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Acknowledgements

We extend our appreciation to the team at the National Center for Health Statistics for their efforts in planning, gathering, and organizing the NHANES data, as well as for establishing the public database.

Author contributions

Qianhui Wen conceptualized the research, conducted the preliminary analysis, and drafted the initial manuscript. Qian Wang reviewed and revised the manuscript. Hua Yang was responsible for the study supervision and data collection. All authors read and approved the final manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

Additional details about the NHANES database are available on the official website at www.cdc.gov/nchs/nhanes/.

Declarations

Ethics approval and consent to participate

Ethical clearance for this study was obtained from the National Center for Health Statistics Ethics Review Committee, and all methods were conducted in line with the principles outlined in the Declaration of Helsinki. Prior to their involvement, participants gave their voluntary and informed consent in written form.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Abbreviations

PWE People with epilepsy

MDD Major depressive disorder

PHQ-9 Patient Health Questionnaire-9

PIR Poverty income ratio

CHD Coronary heart disease

NHANES National health and nutrition examination survey

MEC Mobile examination center

OR Odds ratio

CI Confidence interval

ACME Average causal mediation effects

ADE Average direct effects

PM Proportion mediated

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
References

1. van Golde EG Gutter T de Weerd AW Sleep disturbances in people with epilepsy; prevalence, impact and treatment Sleep Med Rev 2011 15 6 357 68 10.1016/j.smrv.2011.01.002 21439869
van Golde EG, Gutter T, de Weerd AW. Sleep disturbances in people with epilepsy; prevalence, impact and treatment. Sleep Med Rev. 2011;15(6):357–68.21439869 10.1016/j.smrv.2011.01.002
2. Vendrame M Yang B Jackson S Auerbach SH Insomnia and epilepsy: a questionnaire-based study J Clin Sleep Med 2013 9 2 141 6 10.5664/jcsm.2410 23372467
Vendrame M, Yang B, Jackson S, Auerbach SH. Insomnia and epilepsy: a questionnaire-based study. J Clin Sleep Med. 2013;9(2):141–6.23372467 10.5664/jcsm.2410
3. Jain SV Simakajornboon N Glauser TA Provider practices impact adequate diagnosis of sleep disorders in children with epilepsy J Child Neurol 2013 28 5 589 95 10.1177/0883073812449692 22791548
Jain SV, Simakajornboon N, Glauser TA. Provider practices impact adequate diagnosis of sleep disorders in children with epilepsy. J Child Neurol. 2013;28(5):589–95.22791548 10.1177/0883073812449692
4. Quigg M Gharai S Ruland J Schroeder C Hodges M Ingersoll KS Thorndike FP Yan G Ritterband LM Insomnia in epilepsy is associated with continuing seizures and worse quality of life Epilepsy Res 2016 122 91 6 10.1016/j.eplepsyres.2016.02.014 26994361
Quigg M, Gharai S, Ruland J, Schroeder C, Hodges M, Ingersoll KS, Thorndike FP, Yan G, Ritterband LM. Insomnia in epilepsy is associated with continuing seizures and worse quality of life. Epilepsy Res. 2016;122:91–6.26994361 10.1016/j.eplepsyres.2016.02.014
5. Giorelli AS Neves GS Venturi M Pontes IM Valois A Gomes Mda M Excessive daytime sleepiness in patients with epilepsy: a subjective evaluation Epilepsy Behav 2011 21 4 449 52 10.1016/j.yebeh.2011.05.002 21703934
Giorelli AS, Neves GS, Venturi M, Pontes IM, Valois A, Gomes Mda M. Excessive daytime sleepiness in patients with epilepsy: a subjective evaluation. Epilepsy Behav. 2011;21(4):449–52.21703934 10.1016/j.yebeh.2011.05.002
6. Bazil CW Epilepsy and sleep disturbance Epilepsy Behav 2003 4 Suppl 2 S39 45 10.1016/j.yebeh.2003.07.005 14527482
Bazil CW. Epilepsy and sleep disturbance. Epilepsy Behav. 2003;4(Suppl 2):S39–45.14527482 10.1016/j.yebeh.2003.07.005
7. Toledo M Gonzalez-Cuevas M Miró-Lladó J Molins-Albanell A Falip M Martinez AB Fernandez S Quintana M Cambrodi R Santamarina E Sleep quality and daytime sleepiness in patients treated with adjunctive perampanel for focal seizures Epilepsy Behav 2016 63 57 62 10.1016/j.yebeh.2016.08.004 27566967
Toledo M, Gonzalez-Cuevas M, Miró-Lladó J, Molins-Albanell A, Falip M, Martinez AB, Fernandez S, Quintana M, Cambrodi R, Santamarina E, et al. Sleep quality and daytime sleepiness in patients treated with adjunctive perampanel for focal seizures. Epilepsy Behav. 2016;63:57–62.27566967 10.1016/j.yebeh.2016.08.004
8. Tezer FI Rémi J Erbil N Noachtar S Saygi S A reduction of sleep spindles heralds seizures in focal epilepsy Clin Neurophysiol 2014 125 11 2207 11 10.1016/j.clinph.2014.03.001 24684944
Tezer FI, Rémi J, Erbil N, Noachtar S, Saygi S. A reduction of sleep spindles heralds seizures in focal epilepsy. Clin Neurophysiol. 2014;125(11):2207–11.24684944 10.1016/j.clinph.2014.03.001
9. Kanner AM Schachter SC Barry JJ Hesdorffer DC Mula M Trimble M Hermann B Ettinger AE Dunn D Caplan R Depression and Epilepsy: epidemiologic and neurobiologic perspectives that may explain their high comorbid occurrence Epilepsy Behav 2012 24 2 156 68 10.1016/j.yebeh.2012.01.007 22632406
Kanner AM, Schachter SC, Barry JJ, Hesdorffer DC, Mula M, Trimble M, Hermann B, Ettinger AE, Dunn D, Caplan R, et al. Depression and Epilepsy: epidemiologic and neurobiologic perspectives that may explain their high comorbid occurrence. Epilepsy Behav. 2012;24(2):156–68.22632406 10.1016/j.yebeh.2012.01.007
10. Song H Zhao Y Hu C Zhao C Wang X Xiao Z Relationships among anxiety, depression, and health-related quality of life in adult epilepsy: a network analysis Epilepsy Behav 2024 154 109748 10.1016/j.yebeh.2024.109748 38640553
Song H, Zhao Y, Hu C, Zhao C, Wang X, Xiao Z. Relationships among anxiety, depression, and health-related quality of life in adult epilepsy: a network analysis. Epilepsy Behav. 2024;154:109748.38640553 10.1016/j.yebeh.2024.109748
11. Fiest KM Dykeman J Patten SB Wiebe S Kaplan GG Maxwell CJ Bulloch AG Jette N Depression in Epilepsy: a systematic review and meta-analysis Neurology 2013 80 6 590 9 10.1212/WNL.0b013e31827b1ae0 23175727
Fiest KM, Dykeman J, Patten SB, Wiebe S, Kaplan GG, Maxwell CJ, Bulloch AG, Jette N. Depression in Epilepsy: a systematic review and meta-analysis. Neurology. 2013;80(6):590–9.23175727 10.1212/WNL.0b013e31827b1ae0
12. Piedad J Rickards H Besag FM Cavanna AE Beneficial and adverse psychotropic effects of antiepileptic drugs in patients with epilepsy: a summary of prevalence, underlying mechanisms and data limitations CNS Drugs 2012 26 4 319 35 10.2165/11599780-000000000-00000 22393904
Piedad J, Rickards H, Besag FM, Cavanna AE. Beneficial and adverse psychotropic effects of antiepileptic drugs in patients with epilepsy: a summary of prevalence, underlying mechanisms and data limitations. CNS Drugs. 2012;26(4):319–35.22393904 10.2165/11599780-000000000-00000
13. Kanner AM Management of psychiatric and neurological comorbidities in epilepsy Nat Rev Neurol 2016 12 2 106 16 10.1038/nrneurol.2015.243 26782334
Kanner AM. Management of psychiatric and neurological comorbidities in epilepsy. Nat Rev Neurol. 2016;12(2):106–16.26782334 10.1038/nrneurol.2015.243
14. Hesdorffer DC Lúdvígsson P Hauser WA Olafsson E Kjartansson O Co-occurrence of major depression or suicide attempt with migraine with aura and risk for unprovoked seizure Epilepsy Res 2007 75 2–3 220 3 10.1016/j.eplepsyres.2007.05.001 17572070
Hesdorffer DC, Lúdvígsson P, Hauser WA, Olafsson E, Kjartansson O. Co-occurrence of major depression or suicide attempt with migraine with aura and risk for unprovoked seizure. Epilepsy Res. 2007;75(2–3):220–3.17572070 10.1016/j.eplepsyres.2007.05.001
15. Singh T Goel RK Epilepsy Associated Depression: an update on current scenario, suggested mechanisms, and opportunities Neurochem Res 2021 46 6 1305 21 10.1007/s11064-021-03274-5 33665775
Singh T, Goel RK. Epilepsy Associated Depression: an update on current scenario, suggested mechanisms, and opportunities. Neurochem Res. 2021;46(6):1305–21.33665775 10.1007/s11064-021-03274-5
16. Kanner AM Psychiatric comorbidities and epilepsy: is it the old story of the chicken and the egg? Ann Neurol 2012 72 2 153 5 10.1002/ana.23679 22926848
Kanner AM. Psychiatric comorbidities and epilepsy: is it the old story of the chicken and the egg? Ann Neurol. 2012;72(2):153–5.22926848 10.1002/ana.23679
17. Wen W, Zhou J, Zhan C, Wang J. Microglia as a Game Changer in Epilepsy Comorbid Depression. Mol Neurobiol 2023.
18. Yan T Qiu Y Yu X Yang L Glymphatic dysfunction: a Bridge between Sleep Disturbance and Mood disorders Front Psychiatry 2021 12 658340 10.3389/fpsyt.2021.658340 34025481
Yan T, Qiu Y, Yu X, Yang L. Glymphatic dysfunction: a Bridge between Sleep Disturbance and Mood disorders. Front Psychiatry. 2021;12:658340.34025481 10.3389/fpsyt.2021.658340
19. The National Health and Nutrition Examination Survey. https://www.cdc.gov/nchs/nhanes/index. htm.
20. Terman SW Hill CE Burke JF Disability in people with epilepsy: a nationally representative cross-sectional study Epilepsy Behav 2020 112 107429 10.1016/j.yebeh.2020.107429 32919202
Terman SW, Hill CE, Burke JF. Disability in people with epilepsy: a nationally representative cross-sectional study. Epilepsy Behav. 2020;112:107429.32919202 10.1016/j.yebeh.2020.107429
21. Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey. 2017–2018 Prescription Medications Data. https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/RXQ_RX_J.htm
22. Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey. 2017–2018 Sleep Disorder Data.https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/SLQ_J.htm
23. Li C Shang S Relationship between Sleep and Hypertension: findings from the NHANES (2007–2014) Int J Environ Res Public Health 2021 18 15 7867 10.3390/ijerph18157867 34360157
Li C, Shang S. Relationship between Sleep and Hypertension: findings from the NHANES (2007–2014). Int J Environ Res Public Health. 2021;18(15):7867.34360157 10.3390/ijerph18157867
24. Zhu F Liu B Kuang D Zhu X Bi X Song Y Quan T Yang Y Ren Y The association between physical activity and sleep in adult ADHD patients with stimulant medication use Front Psychiatry 2023 14 1236636 10.3389/fpsyt.2023.1236636 38076701
Zhu F, Liu B, Kuang D, Zhu X, Bi X, Song Y, Quan T, Yang Y, Ren Y. The association between physical activity and sleep in adult ADHD patients with stimulant medication use. Front Psychiatry. 2023;14:1236636.38076701 10.3389/fpsyt.2023.1236636
25. Li Y Tan S Sleep factors were associated with a higher risk of MAFLD and significant fibrosis Sleep Breath 2024 28 3 1381 91 10.1007/s11325-024-03017-0 38514588
Li Y, Tan S. Sleep factors were associated with a higher risk of MAFLD and significant fibrosis. Sleep Breath. 2024;28(3):1381–91.38514588 10.1007/s11325-024-03017-0
26. Artom M Czuber-Dochan W Sturt J Norton C Cognitive behavioural therapy for the management of inflammatory bowel disease-fatigue with a nested qualitative element: study protocol for a randomised controlled trial Trials 2017 18 1 213 10.1186/s13063-017-1926-3 28490349
Artom M, Czuber-Dochan W, Sturt J, Norton C. Cognitive behavioural therapy for the management of inflammatory bowel disease-fatigue with a nested qualitative element: study protocol for a randomised controlled trial. Trials. 2017;18(1):213.28490349 10.1186/s13063-017-1926-3
27. Yuan L Zhu L Chen F Cheng Q Yang Q Zhou ZZ Zhu Y Wu Y Zhou Y Zha X A survey of psychological responses during the Coronavirus Disease 2019 (COVID-19) epidemic among Chinese police officers in Wuhu Risk Manag Healthc Policy 2020 13 2689 97 10.2147/RMHP.S269886 33244282
Yuan L, Zhu L, Chen F, Cheng Q, Yang Q, Zhou ZZ, Zhu Y, Wu Y, Zhou Y, Zha X. A survey of psychological responses during the Coronavirus Disease 2019 (COVID-19) epidemic among Chinese police officers in Wuhu. Risk Manag Healthc Policy. 2020;13:2689–97.33244282 10.2147/RMHP.S269886
28. Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey. 2017–2018 Depression Data. https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/DPQ_J.htm
29. Manea L Gilbody S McMillan D Optimal cut-off score for diagnosing depression with the Patient Health Questionnaire (PHQ-9): a meta-analysis CMAJ 2012 184 3 E191 196 10.1503/cmaj.110829 22184363
Manea L, Gilbody S, McMillan D. Optimal cut-off score for diagnosing depression with the Patient Health Questionnaire (PHQ-9): a meta-analysis. CMAJ. 2012;184(3):E191–196.22184363 10.1503/cmaj.110829
30. Menke A Casagrande S Geiss L Cowie CC Prevalence of and trends in diabetes among adults in the United States, 1988–2012 JAMA 2015 314 10 1021 9 10.1001/jama.2015.10029 26348752
Menke A, Casagrande S, Geiss L, Cowie CC. Prevalence of and trends in diabetes among adults in the United States, 1988–2012. JAMA. 2015;314(10):1021–9.26348752 10.1001/jama.2015.10029
31. Winsor AA Richards C Bissell S Seri S Liew A Bagshaw AP Sleep disruption in children and adolescents with epilepsy: a systematic review and meta-analysis Sleep Med Rev 2021 57 101416 10.1016/j.smrv.2021.101416 33561679
Winsor AA, Richards C, Bissell S, Seri S, Liew A, Bagshaw AP. Sleep disruption in children and adolescents with epilepsy: a systematic review and meta-analysis. Sleep Med Rev. 2021;57:101416.33561679 10.1016/j.smrv.2021.101416
32. Fonseca E Campos Blanco DM Castro Vilanova MD Garamendi Í Gómez-Eguilaz M Pérez Díaz H Poza JJ Querol-Pascual MR Quiroga-Subirana P Rodríguez-Osorio X Relationship between sleep quality and cognitive performance in patients with epilepsy Epilepsy Behav 2021 122 108127 10.1016/j.yebeh.2021.108127 34147020
Fonseca E, Campos Blanco DM, Castro Vilanova MD, Garamendi Í, Gómez-Eguilaz M, Pérez Díaz H, Poza JJ, Querol-Pascual MR, Quiroga-Subirana P, Rodríguez-Osorio X, et al. Relationship between sleep quality and cognitive performance in patients with epilepsy. Epilepsy Behav. 2021;122:108127.34147020 10.1016/j.yebeh.2021.108127
33. Khachatryan SG, Vardanyan LV, Stepanyan TA, Tunyan YS. [Impact of sleep disorders on quality of life in epilepsy]. Volume 120. Zh Nevrol Psikhiatr Im S S Korsakova; 2020. pp. 24–8. 5.
34. Lin YS, Wang CC, Chen CY. GWAS Meta-Analysis reveals Shared genes and Biological pathways between Major Depressive Disorder and Insomnia. Genes (Basel) 2021, 12(10).
35. Zhao J Liu H Wu Z Wang Y Cao T Lyu D Huang Q Wu Z Zhu Y Wu X Clinical features of the patients with major depressive disorder co-occurring insomnia and hypersomnia symptoms: a report of NSSD study Sleep Med 2021 81 375 81 10.1016/j.sleep.2021.03.005 33813234
Zhao J, Liu H, Wu Z, Wang Y, Cao T, Lyu D, Huang Q, Wu Z, Zhu Y, Wu X, et al. Clinical features of the patients with major depressive disorder co-occurring insomnia and hypersomnia symptoms: a report of NSSD study. Sleep Med. 2021;81:375–81.33813234 10.1016/j.sleep.2021.03.005
36. Moser D Pablik E Aull-Watschinger S Pataraia E Wöber C Seidel S Depressive symptoms predict the quality of sleep in patients with partial epilepsy–A combined retrospective and prospective study Epilepsy Behav 2015 47 104 10 10.1016/j.yebeh.2015.04.021 25982882
Moser D, Pablik E, Aull-Watschinger S, Pataraia E, Wöber C, Seidel S. Depressive symptoms predict the quality of sleep in patients with partial epilepsy–A combined retrospective and prospective study. Epilepsy Behav. 2015;47:104–10.25982882 10.1016/j.yebeh.2015.04.021
37. Karapinar E YunusoĞlu C Tekin B Dede H Bebek N Baykan B GÜrses C Depression is a major determinant of sleep abnormalities in patients with epilepsy Arq Neuropsiquiatr 2020 78 12 772 7 10.1590/0004-282x20200064 33331513
Karapinar E, YunusoĞlu C, Tekin B, Dede H, Bebek N, Baykan B, GÜrses C. Depression is a major determinant of sleep abnormalities in patients with epilepsy. Arq Neuropsiquiatr. 2020;78(12):772–7.33331513 10.1590/0004-282x20200064
38. Nobili L Beniczky S Eriksson SH Romigi A Ryvlin P Toledo M Rosenzweig I Expert Opinion: managing sleep disturbances in people with epilepsy Epilepsy Behav 2021 124 108341 10.1016/j.yebeh.2021.108341 34619543
Nobili L, Beniczky S, Eriksson SH, Romigi A, Ryvlin P, Toledo M, Rosenzweig I. Expert Opinion: managing sleep disturbances in people with epilepsy. Epilepsy Behav. 2021;124:108341.34619543 10.1016/j.yebeh.2021.108341
39. Planas-Ballvé A Grau-López L Jiménez M Ciurans J Fumanal A Becerra JL Insomnia and poor sleep quality are associated with poor seizure control in patients with epilepsy Neurologia (Engl Ed) 2022 37 8 639 46 10.1016/j.nrl.2019.07.006 34649817
Planas-Ballvé A, Grau-López L, Jiménez M, Ciurans J, Fumanal A, Becerra JL. Insomnia and poor sleep quality are associated with poor seizure control in patients with epilepsy. Neurologia (Engl Ed). 2022;37(8):639–46.34649817 10.1016/j.nrl.2019.07.006
40. Bergmann M Tschiderer L Stefani A Heidbreder A Willeit P Högl B Sleep quality and daytime sleepiness in epilepsy: systematic review and meta-analysis of 25 studies including 8,196 individuals Sleep Med Rev 2021 57 101466 10.1016/j.smrv.2021.101466 33838598
Bergmann M, Tschiderer L, Stefani A, Heidbreder A, Willeit P, Högl B. Sleep quality and daytime sleepiness in epilepsy: systematic review and meta-analysis of 25 studies including 8,196 individuals. Sleep Med Rev. 2021;57:101466.33838598 10.1016/j.smrv.2021.101466
41. Adiga D Gupta A Khanna M Taly AB Thennarasu K Sleep disorders in children with cerebral palsy and its correlation with sleep disturbance in primary caregivers and other associated factors Ann Indian Acad Neurol 2014 17 4 473 6 10.4103/0972-2327.144044 25506179
Adiga D, Gupta A, Khanna M, Taly AB, Thennarasu K. Sleep disorders in children with cerebral palsy and its correlation with sleep disturbance in primary caregivers and other associated factors. Ann Indian Acad Neurol. 2014;17(4):473–6.25506179 10.4103/0972-2327.144044
42. Jain SV Glauser TA Effects of Epilepsy treatments on sleep architecture and daytime sleepiness: an evidence-based review of objective sleep metrics Epilepsia 2014 55 1 26 37 10.1111/epi.12478 24299283
Jain SV, Glauser TA. Effects of Epilepsy treatments on sleep architecture and daytime sleepiness: an evidence-based review of objective sleep metrics. Epilepsia. 2014;55(1):26–37.24299283 10.1111/epi.12478
43. Sinha S Nagappa M Thennarasu K Effect of carbamazepine on the sleep microstructure of temporal lobe epilepsy patients: a cyclic alternating pattern-based study Sleep Med 2016 27–28 80 5 27938924
Nayak CS, Sinha S, Nagappa M, Thennarasu K, Taly AB. Effect of carbamazepine on the sleep microstructure of temporal lobe epilepsy patients: a cyclic alternating pattern-based study. Sleep Med. 2016;27–28:80–5.27938924
44. Ryden AM Martin JL Matsuwaka S Fung CH Dzierzewski JM Song Y Mitchell MN Fiorentino L Josephson KR Jouldjian S Insomnia disorder among older veterans: results of a Postal Survey J Clin Sleep Med 2019 15 4 543 51 10.5664/jcsm.7710 30952212
Ryden AM, Martin JL, Matsuwaka S, Fung CH, Dzierzewski JM, Song Y, Mitchell MN, Fiorentino L, Josephson KR, Jouldjian S, et al. Insomnia disorder among older veterans: results of a Postal Survey. J Clin Sleep Med. 2019;15(4):543–51.30952212 10.5664/jcsm.7710
45. Jaqua EE Hanna M Labib W Moore C Matossian V Common Sleep disorders affecting older adults Perm J 2023 27 1 122 32 10.7812/TPP/22.114 36503403
Jaqua EE, Hanna M, Labib W, Moore C, Matossian V. Common Sleep disorders affecting older adults. Perm J. 2023;27(1):122–32.36503403 10.7812/TPP/22.114
46. Hernández-Aceituno A Guallar-Castillón P García-Esquinas E Rodríguez-Artalejo F Banegas JR Association between sleep characteristics and antihypertensive treatment in older adults Geriatr Gerontol Int 2019 19 6 537 40 10.1111/ggi.13660 30912276
Hernández-Aceituno A, Guallar-Castillón P, García-Esquinas E, Rodríguez-Artalejo F, Banegas JR. Association between sleep characteristics and antihypertensive treatment in older adults. Geriatr Gerontol Int. 2019;19(6):537–40.30912276 10.1111/ggi.13660
47. He L Fan C Li G The relationship between serum C-reactive protein and senile hypertension BMC Cardiovasc Disord 2022 22 1 500 10.1186/s12872-022-02948-4 36418968
He L, Fan C, Li G. The relationship between serum C-reactive protein and senile hypertension. BMC Cardiovasc Disord. 2022;22(1):500.36418968 10.1186/s12872-022-02948-4
48. Cai N Li C Gu X Zeng W Zhong J Liu J Zeng G Zhu J Hong H CYP2C19 loss-of-function is associated with increased risk of hypertension in a Hakka population: a case-control study BMC Cardiovasc Disord 2023 23 1 185 10.1186/s12872-023-03207-w 37024851
Cai N, Li C, Gu X, Zeng W, Zhong J, Liu J, Zeng G, Zhu J, Hong H. CYP2C19 loss-of-function is associated with increased risk of hypertension in a Hakka population: a case-control study. BMC Cardiovasc Disord. 2023;23(1):185.37024851 10.1186/s12872-023-03207-w
49. Weng C Shen Z Li X Jiang W Peng L Yuan H Yang K Wang J Effects of chemerin/CMKLR1 in obesity-induced hypertension and potential mechanism Am J Transl Res 2017 9 6 3096 104 28670396
Weng C, Shen Z, Li X, Jiang W, Peng L, Yuan H, Yang K, Wang J. Effects of chemerin/CMKLR1 in obesity-induced hypertension and potential mechanism. Am J Transl Res. 2017;9(6):3096–104.28670396
50. Li N Lin M Heizhati M Wang L Luo Q Li Y Yili J Hong J Yao X Zhu Q Effect of spironolactone on cardiovascular morbidity and mortality in patients with hypertension and glucose metabolism disorders (ESCAM): a study protocol for a pragmatic randomised controlled trial BMJ Open 2020 10 11 e038694 10.1136/bmjopen-2020-038694 33444188
Li N, Lin M, Heizhati M, Wang L, Luo Q, Li Y, Yili J, Hong J, Yao X, Zhu Q. Effect of spironolactone on cardiovascular morbidity and mortality in patients with hypertension and glucose metabolism disorders (ESCAM): a study protocol for a pragmatic randomised controlled trial. BMJ Open. 2020;10(11):e038694.33444188 10.1136/bmjopen-2020-038694
51. Gewirtz AN Gao V Parauda SC Robbins MS Posterior reversible Encephalopathy Syndrome Curr Pain Headache Rep 2021 25 3 19 10.1007/s11916-020-00932-1 33630183
Gewirtz AN, Gao V, Parauda SC, Robbins MS. Posterior reversible Encephalopathy Syndrome. Curr Pain Headache Rep. 2021;25(3):19.33630183 10.1007/s11916-020-00932-1
52. Goyal M Mishra P Jaseja H Obstructive sleep apnea and epilepsy: understanding the pathophysiology of the comorbidity Int J Physiol Pathophysiol Pharmacol 2023 15 4 105 14 37736503
Goyal M, Mishra P, Jaseja H. Obstructive sleep apnea and epilepsy: understanding the pathophysiology of the comorbidity. Int J Physiol Pathophysiol Pharmacol. 2023;15(4):105–14.37736503
53. Gutter T Callenbach PMC Brouwer OF de Weerd AW Prevalence of sleep disturbances in people with epilepsy and the impact on quality of life: a survey in secondary care Seizure 2019 69 298 303 10.1016/j.seizure.2019.04.019 31152984
Gutter T, Callenbach PMC, Brouwer OF, de Weerd AW. Prevalence of sleep disturbances in people with epilepsy and the impact on quality of life: a survey in secondary care. Seizure. 2019;69:298–303.31152984 10.1016/j.seizure.2019.04.019
