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Abstract

Background:

Depression and anxiety are the most common psychiatric comorbidities in patients with epilepsy (PWE). However, they are often unrecognized and consequently untreated.

Objective:

The study was conducted to evaluate the prevalence and risk factors of anxiety and depression among Chinese adult PWE.

Design:

Cross-sectional study.

Methods:

Adult PWE were recruited from 13 tertiary epilepsy centers from February to September 2022. Generalized Anxiety Disorder-7 and Neurological Disorders Depression Inventory for Epilepsy were applied to evaluate anxiety and depression, respectively. Both univariate and multivariate logistic regression analyses models were performed to explore the risk factors of anxiety and depression.

Results:

A total of 1326 PWE were enrolled in this study. The prevalence of anxiety and depression was 31.45% and 27.30%, respectively. Being female [odds ratio (OR) = 1.467, 95% CI: 1.134–1.899; p = 0.004], focal and focal to bilateral tonic-clonic seizures (TCSZ) (OR = 1.409, 95% CI: 1.021–1.939; p = 0.036), and seizure occurrence in the last 3 months (OR = 1.445, 95% CI: 1.026–2.044; p = 0.036) were the risk factors for anxiety. Focal and focal to bilateral TCSZ (OR = 1.531, 95% CI: 1.094–2.138; p = 0.013) and seizure occurrence in the last 3 months (OR = 1.644, 95% CI: 1.130–2.411; p = 0.010) were the risk factors for depression. In addition, for every 1-year increment of age, the odds of developing depression were decreased by 3.8% (p = 4.12e⁻⁵). Nevertheless, up to 70% of PWE did not receive any treatment for comorbidity.

Conclusion:

There were approximately 30% of PWE screened positive for anxiety or depression. Both focal and focal to bilateral TCSZ and seizure occurrence in the last 3 months were estimated as risk factors for anxiety and depression. However, the current status of treatment was not optimal.

Keywords

anxiety current status of treatment depression epilepsy risk factors

Introduction

Epilepsy is one of the most common neurological diseases that affect over 70 million people worldwide.¹ It rarely occurs alone and has numerous neurobiological, cognitive, psychological, and social consequences.² Depression and anxiety are the most common psychiatric comorbidities and are highly prevalent in patients with epilepsy (PWE) and higher than that in the general population.³ They are also associated with various adverse epileptic and functional outcomes, such as decreased seizure control,⁴ poor quality of life,⁵ and heavy economic burdens.⁶ However, these disorders are often underestimated and consequently untreated.

According to previous studies, the prevalence of depression was estimated to be as low as 4.5%⁷ to as high as 84.2%⁸ in PWE, whereas the prevalence of anxiety ranges from 4.3%⁹ to 52.1%.¹⁰ Such high variability in the prevalence was mainly due to differences in screening instruments, geographic areas, populations, and sample sizes.¹¹ Despite the high prevalence, the management of depression and anxiety is not adequate. It was reported that up to 72.5% of PWE with depression did not receive any antidepressant treatment in West China.¹² Furthermore, epilepsy health professionals are rarely involved in the screening for psychiatric comorbidities in PWE,¹³ a large proportion with psychiatric comorbidities remains underdiagnosed.¹⁴ This may reflect the doctors’ insufficient awareness of comorbidities and their related risk factors.¹² To promote the standardized diagnosis and treatment of epilepsy comorbidities, the Comorbidity Committee of China Association Against Epilepsy (CC-CAAE) recently published the ‘Chinese expert consensus on screening tools for epilepsy comorbidity’. Recently, several studies reported on the prevalence and risk factors of anxiety and depression in Chinese PWE.^12,15,16 However, these studies were geographically restricted to one region or hospital and included a small sample size. Currently, there is a lack of large sample multicenter studies in China on the screening and treatment of these common psychiatric disorders.

Given the current knowledge gap and variability in diagnosis, we designed this multicenter study to assess the rate of prevalence and treatment status of anxiety and depression among Chinese PWE using recommended tools of the CC-CAAE and to explore the related risk factors, to provide a theoretical basis for the preventive strategies and targeted intervention measures in China.

Materials and methods

Study design

This multicenter cross-sectional study was sponsored by the CC-CAAE. This study was conducted in 13 tertiary hospitals throughout the East, West, South, and North of China (listed in Supplemental Table 1) from February to September 2022.

Participants

Chinese PWE aged older than 18 years from the medical outpatient departments were enrolled in this study. The diagnosis of epilepsy was made by experienced epileptologists according to the International League Against Epilepsy (ILAE).² Exclusion criteria were as follows: (1) patients without epilepsy; (2) had a history of non-epileptic seizures; and (3) unable to read and respond to the questionnaire independently, such as diagnosis of severe cognitive impairment or schizophrenia. The eligible PWE were invited to participate and assessed at the outpatient epilepsy clinic through interviews. The data were collected by administering standardized and structured questionnaires.

Variables

Demographic and clinical characteristics were also collected during the interview. Demographic data included age and gender. Clinical characteristics included age of epilepsy onset, duration of epilepsy, epilepsy type [focal versus generalized versus focal and focal to bilateral tonic-clonic seizures (TCSZ)], current seizure attack in the last 3 months (yes versus no), seizure outcome [seizure-free, undetermined, drug-resistant epilepsy (DRE)], magnetic resonance imaging (MRI) (normal versus abnormal), electrocardiography (EEG) (normal versus epileptiform discharge), and current anti-seizure medications (ASMs) (monotherapy versus polypharmacy). In addition, the definitions and measurements of some of these variables were expounded as follows:

Epilepsy type

According to the 2017 ILAE classification,¹⁷ epilepsy types in this study included: (1) focal epilepsy, which may have a range of seizure types including focal aware seizures, focal impaired awareness seizures, focal motor seizures, and focal non-motor seizures; (2) generalized epilepsy, which may have a range of seizure types including absence, myoclonic, atonic, tonic, and TCSZ; (3) focal and focal to bilateral TCSZ, here refers as patients with both focal seizures and focal to bilateral TCSZ.

Seizure outcome

Based on the ILAE consensus definitions,¹⁸ the categories of seizure outcome include ‘seizure-free’, ‘undetermined’, and ‘DRE’. Seizure-free is defined as freedom from all types of seizures for 12 months or a minimum of three times the pre-intervention interseizure interval (determined from seizures occurring within the past 12 months), whichever is longer.¹⁸ DRE is defined as failure of adequate trials of two tolerated and appropriately chosen and used ASMs schedules (whether as monotherapies or in combination) to achieve sustained seizure freedom.¹⁸ Undetermined is defined as any of the following: (1) not meeting criteria for seizure-free; (2) ⩾1 seizure in the preceding year, not meeting criteria for DRE (due to inadequate trials, intolerance, inappropriately chosen, or unused medications); (3) inadequate or inappropriately chosen or used drug schedules, including discontinuation for reasons other than unsatisfactory seizure control; and (4) insufficient data to confirm seizure outcome.^18–20

Magnetic resonance imaging

In this study, MRI abnormalities mainly included the following two categories: (1) image findings are considered epileptiform, such as stroke, trauma, hippocampus sclerosis, malformations of cortical development (focal cortical dysplasia, etc.), brain tumor, vascular malformations, infection and encephalitis, etc.¹⁷; (2) image findings are not considered epileptiform such as leukoencephalopathy, etc. The MRIs are typically read and interpreted by radiologists who are medical doctors specialized in diagnostic imaging. Radiologists undergo extensive training specifically in the interpretation of MRIs and other imaging studies and have intermediate or above professional and technical titles.

Electrocardiography

In this study, the EEGs are typically read by neurophysiologists or neurologists. Both of them complete specialized training in EEG organized by CAAE and obtain intermediate or above EEGs professional-level examination certificates.

Questionnaires

According to the ‘Chinese expert consensus on screening tools for epilepsy comorbidity’, and the recommendations of the ILAE Commission on Neuropsychiatry,²¹ the following self-rating questionnaires were adopted:

Generalized Anxiety Disorder-7 (GAD-7) is a seven-item instrument originally developed in 2006 to identify anxiety symptoms.²² It yields an overall score ranging from 0 to 21, with higher scores representing the severity of anxiety. The scale had been demonstrated as a reliable and valid measurement to assess anxiety in PWE, with the optimal cutoff points ranging between 6 and 8.^21,23,24 To avoid cultural and linguistic differences, a score >6 was taken as the cutoff point in this study, as reported in the study by Tong et al.²⁴

Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) is a six-item questionnaire developed in 2006 to screen for major depression in PWE.²⁵ The sum score ranges from 6 to 24, with higher scores representing the severity of symptoms. The scale had been demonstrated valid and translated to different languages, with the optimal cutoff points ranging from 11 to 16.^26,27 In this study, the Chinese version of the NDDI-E (C-NDDI-E) was used and a score >12 was taken as the cutoff point, as reported in the study by Tong et al.²⁸

In addition to depression, NDDI-E has also shown its effectiveness and good psychometric properties in screening suicidality, referring here to the NDDI-E item 4 (‘I’d be better off dead’). A recent cohort study from Southwestern China demonstrated the high specificity and sensitivity of C-NDDI-E item 4 with a score >2 for screening suicidality.²⁹ Consequently, we also evaluated the prevalence and risk factors of suicidality in this study using the C-NDDI-E item 4 with a score >2 as the optimal cutoff point.

Drug treatments

In addition to demographic and clinical characteristics, treatments for comorbidities were also collected during the interview. Here, information on drug treatments was further elucidated.

Based on the World Federation of Societies of Biological Psychiatry guidelines for the treatment of anxiety disorders,³⁰ the antianxiety drugs included: (1) selective serotonin reuptake inhibitors (SSRIs) such as escitalopram, citalopram, and fluoxetine; (2) serotonin norepinephrine reuptake inhibitors (SNRIs) such as duloxetine; (3) benzodiazepines such as alprazolam, clonazepam, and diazepam; (4) serotonin antagonist and reuptake inhibitor (SARI) such as trazodone; etc.

Based on the ILAE clinical practice recommendations³¹ and international guidelines^32,33 for the management of depression, the antidepressant drugs included: (1) SSRIs; (2) SNRIs; (3) noradrenergic and specific serotonergic antidepressant (NaSSA): mirtazapine; (4) SARI; etc.

Data collection procedure

Patients scanned the quick-response code, completed a set of self-rating questionnaires as well as demographic information, then submitted them. According to cutoff points, patients would be given positive/negative anxiety or depression conclusion. Physicians then collected the clinical information of every participant. In addition, they needed to collect previous and current treatment status for patients who were positive in screening. Every clinician was assigned a unique quick-response code to facilitate the collection of the information and avoid repetitions to the maximum extent. Finally, all the information would be automatically summarized on the data platform and sent to the leader unit after desensitization. After being reviewed, the qualified questionnaires were included in the final statistical analysis.

Statistical analysis

Statistical analyses were performed on R version 3.5.1 [R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.] and GraphPad Prism 7.00 (Windows, GraphPad Software, San Diego, California USA, www.graphpad.com), and a two-tailed p < 0.05 was considered significant. The distributions of continuous variables were tested using the Shapiro–Wilk test. Continuous variables with normal distributions were described as the mean and standard deviation and compared using an independent test. Non-normal distributions were expressed as medians and interquartile ranges (IQRs) and compared using the Kruskal–Wallis test. Categorical variables were expressed as frequencies and compared using the chi-squared test. Univariate logistic regression analyses were performed using anxiety/depression/suicidality as a dependent variable and demographic and clinical characteristics as independent variables. To determine which factor demonstrated a significant effect on psychiatric comorbidities among PWE, factors showing a p value of <0.10 identified in the univariate analysis were then entered into the multivariate model. Both univariate and multivariate models were described by odds ratio (OR) and its 95% confidence interval (CI).

Results

Demographic and clinical characteristics

A total of 1326 PWE were enrolled in this study, and 52.1% of them were male patients. The median age of participants and epilepsy onset was 32 (IQR: 25–40) and 19 (IQR: 13–29) years, respectively. The median duration of epilepsy was 10 (IQR: 5–17) years. Most of the PWE (94%) were currently under ASMs and 672 (50.7%) PWE were currently under polypharmacy. The details are shown in Table 1. In addition, the demographic and clinical characteristics of the four subgroups based on the geographic distribution (East, West, South, and North) of the 13 hospitals are provided in Supplemental Table 1.

Table 1.

Demographic and clinical characteristics of adults with epilepsy.

Characteristic	N ^*	All participants (N = 1326)
Age, median (IQR), (year)	1320	32 (25–40)
Age, range, year		18–87
Gender (M/F)	1326	691/635
Epilepsy type (focal/generalized/focal and focal to bilateral TCSZ )	1235	834/167/234
Age at the onset of epilepsy median (IQR), (year)	1255	19 (13–29)
Duration of epilepsy, median (IQR), (year)	1254	10 (5–17)
Current seizure attack in the last 3 months (yes/no)	1326	831/495
MRI (normal/abnormal)	1083	497/568
EEG (normal/epileptiform discharge)	1130	168/962
Outcome (SF/undetermined/DRE)	1326	346/669/311
Current ASMs (monotherapy/polypharmacy)	1246	574/672

ASMs, anti-seizure medications; DRE, drug-resistant epilepsy; EEG, electrocardiography; IQR, interquartile range; MRI, magnetic resonance imaging; N^*, number of participants with data available; SF, seizure-free; TCSZ, tonic-clonic seizures.

Prevalence of anxiety, depression, and suicidality

Based on the GAD-7 scores, the prevalence of anxiety among PWE was 31.45% (417/1326) with a 95% CI (0.290–0.340), and the median score was 4 (IQR: 1–7). The prevalence of depression was 27.30% (362/1326) with a 95% CI (0.250–0.298), according to C-NDDI-E screening, and the median score was 9 (IQR: 6–13). The suicidality was prevalent in 12% (159/1326) of PWE with a 95% CI (0.104–0.139), according to the C-NDDI-E item 4, and the frequencies of each score were 984 (74.21%), 183 (13.80%), 123 (9.28%), and 36 (2.71%) corresponding to ‘never’, ‘rarely’, ‘sometimes’, and ‘always or often’, respectively. Moreover, the co-prevalence of more than two comorbidities was also high among PWE. For instance, the co-prevalence rate of both anxiety and depression was 20.59%, whereas depression and suicidality were 11.16%. The data relating to the prevalence are presented in Table 2, and the overlap of these three symptoms is represented in Figure 1.

Table 2.

Proportion of adults with epilepsy who screened positive for depression, anxiety, suicidality, or their combinations.

Variable	All participants (N = 1326)
Variable	N	%	95% CI
Anxiety^a	417	31.45	0.290–0.340
Depression^b	362	27.30	0.250–0.298
Suicidality^c	159	12.00	0.104–0.139
Anxiety and depression	273	20.59	0.185–0.228
Anxiety and suicidality	119	8.97	0.076–0.106
Depression and suicidality	148	11.16	0.096–0.130
Anxiety and depression and suicidality	117	8.82	0.074–0.105

Anxiety: GAD-7 > 6.

Depression: C-NDDI-E > 12.

Suicidality: C-NDDI-E item 4 > 2.

C-NDDI-E, Chinese version of the Depression Inventory for Epilepsy; GAD-7, Generalized Anxiety Disorder-7.

Figure 1.

Venn diagram showed a high overlap of anxiety, depression, and suicidality in patients with epilepsy.

Factors associated with comorbidities among PWE

Both univariate and multivariate logistic regression analyses models were performed separately for the exploration of demographic and clinical characteristics associated with anxiety and depression, and the results are as follows:

Anxiety

The univariate model revealed that gender, epilepsy type, age of onset, current seizure attack in the last 3 months, seizure outcome, and current ASMs were associated with the symptoms of anxiety (all p < 0.05). In the multivariate analysis, the odds of developing anxiety among the female patients were found to increase by 1.467 when compared with the male patients (OR = 1.467, 95% CI: 1.134–1.899; p = 0.004). Focal and focal to bilateral TCSZ (OR = 1.409, 95% CI: 1.021–1.939; p = 0.036) and current seizure attack in the last 3 months (OR = 1.445, 95% CI: 1.026–2.044; p = 0.036) increase the odds of developing anxiety by 1.409 and 1.445, respectively, when compared with their counterparts (Figure 2 and Supplemental Table 2).

Figure 2.

Forest plots showed the association between possible contributing factors and anxiety. The univariate model revealed that gender, epilepsy type, age of onset, current seizure attack in the last 3 months, seizure outcome, and current ASMs were associated with anxiety symptoms. In the multivariate analysis, being female, focal and focal to bilateral TCSZ, and current seizure attack in the last 3 months were identified as risk factors for epilepsy people with anxiety.

Depression

The univariate model revealed that age, epilepsy type, age of onset, current seizure attack in the last 3 months, seizure outcome, and current ASMs were associated with depression (all p < 0.05). In the multivariate model, for every 1-year increment of age, the odds of developing depression were decreased by 3.8% (OR = 0.962, 95% CI: 0.944–0.980; p = 4.12e⁻⁵). Focal and focal to bilateral TCSZ (OR = 1.531, 95% CI: 1.094–2.138; p = 0.013) and current seizure attack in the last 3 months (OR = 1.644, 95% CI: 1.130–2.411; p = 0.010) increase the odds of developing depression by 1.531 and 1.644, respectively, when compared with their counterparts (Figure 3 and Supplemental Table 3).

Figure 3.

Forest plots showed the association between possible contributing factors and depression. The univariate model revealed that age, epilepsy type, age of onset, current seizure attack in the last 3 months, seizure outcome, and current ASMs were associated with depression. In the multivariate analysis, for every 1-year increment of age, the odds of developing depression were decreased by 3.8%. Focal and focal to bilateral TCSZ and current seizure attacks in the last 3 months were identified as risk factors for epilepsy people with depression.

Suicidality

The univariate model revealed that age, age of onset, gender, current seizure attack in the last 3 months, seizure outcome, and current ASMs were associated with suicidality (all p < 0.05). In the multivariate model, the odds of developing suicidality among the female patients were found to increase by 1.750 when compared with the male patients (OR = 1.750, 95% CI: 1.174–2.630; p = 0.006). In addition, patients with abnormal EEG had higher odds of suicidality, while the association slightly missed the margin of significance (OR = 1.975, 95% CI: 1.040–4.161; p = 0.052) (Figure 4 and Supplemental Table 4).

Figure 4.

Forest plot showed the association between possible contributing factors and suicidality. The univariate model revealed that age, age of onset, gender, current seizure attack in the last 3 months, seizure outcome, and current ASMs were associated with suicidality. In the multivariate analysis, being female was identified as a risk factor for epilepsy people with suicidality. In addition, having abnormal EEG might be another potential risk factor as the association slightly missed the margin of significance.

Current status of anxiety and depression treatment in China

In our study, only 9% of patients who screened positive for anxiety were treated with antianxiety agents, 7% of patients were treated with nonpharmacological management, such as cognitive behavioral therapy or psychotherapy, 19% of patients were referred to psychiatrists, and up to 70% of patients did not receive any antianxiety treatment. Among the patients with depression, 7% of patients were treated with antidepressant drugs, 7% of patients were treated with nonpharmacological management, 20% of patients were referred to psychiatrists, and up to 71% of patients did not receive any antidepressant treatment (Table 3).

Table 3.

Proportion of patients with epilepsy who received treatment for different comorbidities.

Treatment status	Patients with anxiety (N = 417)			Patients with depression (N = 362)
	N	%	95% CI	N	%	95% CI
Patients received treatment
ASMs	397	95.20	0.927–0.969	345	95.30	0.926–0.970
Antianxiety agents^a	36	8.63	0.063–0.117	–	–	–
Antidepressant drugs^b	–	–	–	27	7.46	0.052–0.106
Nonpharmacological treatments^c	28	6.71	0.047–0.095	26	7.18	0.049–0.103
Refer patients to psychiatrists	81	19.42	0.159–0.235	74	20.44	0.166–0.249
Without treatment for comorbidity	293	70.26	0.657–0.744	258	71.27	0.664–0.757

Antianxiety agents included past use, current use, and recommended use at the visit.

Antidepressant drugs included past use, current use, and recommended use at visit.

Nonpharmacological treatments included past use and recommended use at the visit.

ASMs, anti-seizure medications.

In addition, we also collected information on antianxiety and antidepressant drug treatments in PWE who scored below the threshold on the GAD-7 and C-NDDI-E. However, the sample sizes were very small (23 and 22, respectively). We also compared the demographic and clinical characteristics between those treated with anti-comorbidities drugs without symptoms and those treated with ongoing symptoms. We found that patients treated with antidepressant drugs with ongoing symptoms of depression were younger than those without symptoms (Supplemental Table 5).

Discussion

In this multicenter study, we estimated the prevalence and identified the risk factors of anxiety, depression, and suicidality among PWE. In addition, we also investigated the status of treatment for anxiety and depression among PWE, such as whether they received drug treatment or not.

In the past few decades, there have been several studies focusing on the prevalence of depression among PWE in China. The prevalence of this disease entity in Sichuan, China, was reported to be 26.7% using the Mini International Neuropsychiatric Interview (MINI)²⁸ and 29.9% with the screening of C-NDDI-E.¹² Similarly, the prevalence of depression among PWE was 25.7% in Shanghai³⁴ and 33.59% in Zhengzhou³⁵ based on the Hamilton Depression Rating Scale. In our present multicenter study, the proportion of PWE with depression was 27.3%, similar to the previous studies. Although the population and screening instruments varied considerably across the studies, there was no significant difference in the reported prevalence of depression in PWE.

In the univariate analysis, factors indirectly suggesting a more severe course of epilepsy were associated with depression in PWE. Here it is referred to as seizure occurrence in the last 3 months, non-seizure-free (undetermined or DRE), and polypharmacy, and these findings are consistent with the previous studies.^12,36,37 A possible explanation could be that patients with uncontrolled epilepsy might be vulnerable to unemployment and other psychosocial stressors,³⁸ which may have increased the psychological burden. In addition, the side effects of ASMs might be another reason.³⁹ Moreover, seizures often occur suddenly in public, with urinary incontinence and abnormal postures, which often result in shame, stigmatization, and perceived discrimination.⁴⁰ Focal and focal to bilateral TCSZ was also observed as a risk factor for depression. The possible explanation is that patients could be more concerned about their disease, as they may think multiple types of seizures reflect the severity of epilepsy. Another possible explanation is that focal to bilateral TCSZ is associated with DRE,⁴¹ which also indirectly reflects the severity of epilepsy increasing the risk of depression. In contrast to a previous study on epilepsy,³⁷ increased age and the age at the onset of epilepsy were observed to reduce the odds of depression in PWE. This finding is consistent with community-based studies⁴² as well as hospital-based studies⁴³ that have demonstrated a significant association between younger age and depression. The possible explanation for the age-related decline in susceptibility to depression may be that older people are better at using psychological strategies to cope with stressful experiences than younger. For instance, older usually accept and adapt adverse situations rather than try to change them.⁴⁴ In addition, they could disengage from stressful situations by decreasing adverse emotional effects,⁴⁵ strengthening emotional control and psychological immunization.⁴⁶ However, only age, focal and focal to bilateral TCSZ, and seizure occurrence in the last 3 months remained significant in the multivariate model.

Although depression is well acknowledged to be the more common psychiatric comorbidity, recent studies have found that the prevalence of anxiety is comparable with or even exceeds that of depression,⁴⁷ as also observed in our study. We found anxiety to be prevalent in 31.45% of PWE, which is higher than the prevalence of depression (27.3%) in this cohort. However, the prevalence of anxiety varied depending on screening tools and populations, with up to 52.1% reported in previous literature.¹⁰ For instance, studies in Sichuan, China, showed a prevalence of anxiety to be 23.5%²⁴ and 33.4%¹⁵ according to the MINI and GAD-7, respectively. Similarly, based on GAD-7 in Jilin, China, the prevalence of anxiety was 28.2%.¹⁶ Nevertheless, compared with domestic or international values, 31.45% of PWE with anxiety in this study is very close to 31.6% reported in Chinese⁴⁸ and 31.37% reported in the Nigerian⁴⁹ population.

When analyzing the risk factors, we found in our present study that the occurrence of seizures in the last 3 months was a risk factor for anxiety in PWE. This is consistent with the previous studies that seizure frequency was associated with anxiety.⁵⁰ In addition, we also found focal and focal to bilateral TCSZ was associated with anxiety in the multivariate model, the possible explanation might be similar to that in depression. Moreover, being female was also identified as an independent risk factor for anxiety. A previous study found that women usually had a higher level of anxiety than men,⁵¹ which may be attributed to multiple factors. First, the biological differences between men and women may partially explain their differences in behavior and emotions. For instance, the heritability of anxiety-related vulnerability factors is greater in females than in males.⁵² Hormonal fluctuations related to menstruation and reproductive stages, particularly estradiol and progesterone, have been associated with increased anxiety.⁵³ Besides, personality differences between females and males may be another explanation.⁵⁴ Women may be more likely to experience negative affectivity, which can contribute to anxiety symptoms.⁵⁵ On the contrary, men are less likely to express their anxiety and fear due to gender stereotypes.⁵⁶ In addition, women are more likely to experience trauma and discrimination, including sexual abuse and social network crises, which may cause long-term anxiety symptoms.⁵⁶ Furthermore, female individuals usually have a heavier psychological burden when facing epilepsy or the side effects of ASMs, such as weight gain.⁵¹ This may cause low body esteem,⁵⁷ possibly increasing anxiety among female PWE. Nevertheless, the effect of gender on anxiety remains controversial, with several types of research demonstrating there was no gender difference in anxiety in PWE.⁵⁸ In addition to the abovementioned risk factors, variates reflecting the severity of epilepsy such as non-seizure-free (undetermined and DRE) and polypharmacy were also associated with anxiety. This is consistent in patients with uncontrolled epilepsy who exhibited a higher rate of anxiety.⁵⁹ In addition, the age at the onset of epilepsy was also associated with anxiety in the univariate model, with later seizure onset decreasing the odds of developing anxiety, which was in line with the literature.⁶⁰

Suicide accounted for approximately 1.5% of total deaths in the world⁶¹ and was attributed as one of the top 10 causes of death in areas where the risk of epilepsy was high.⁶² Moreover, it is considered to be an important contributor to the increased mortality among PWE.⁶³ The average rate of suicide risk was approximately 12% among PWE, up to 10 times higher than the general population.⁶⁴ Nevertheless, there is limited epidemiological data on suicide risk in PWE in China. In this study, we found the prevalence of suicidality in PWE to be 12%, which is in the same range reported in the previous study.⁶⁴ Moreover, in our present study, the prevalence was higher (40.88%) in PWE with depression, and 93.08% of the patients with suicidality risk had depression. Such a high prevalence reflected the bidirectional relationship between depression and suicidality, and possibly because suicidality and depression were assessed on the same scale. This study also evaluated the risk factors of suicidality, such as seizure-related variables and demographic variables, which tended to be negative in the previous studies.⁶⁵ In the multivariate analysis, being female was identified as an independent risk factor for suicidality, which is consistent with the earlier findings that the rate of suicidality among female patients was higher than that of male patients.⁶⁶ In addition, patients with abnormal EEG might be another potential risk factor as the association slightly missed the margin of significance. Compared with normal EEG, epileptic discharges may reflect the severity of epilepsy, which suggest the role of epilepsy in suicidality. However, these findings need further investigation.

Quite a large proportion of PWE had anxiety or depression. However, the current status of treatment was neither adequate nor optimum. In this study, up to 70% and 71% of PWE did not receive any antianxiety and antidepressant treatment, respectively. More significantly, only 9% and 7% of PWE received antianxiety and antidepressant drugs, respectively. Such a huge treatment gap reflected the inadequacy of epilepsy comorbidities management in China.¹³ Indeed, little attention is paid to screening for anxiety and depression in clinical practice. The possible reasons for the same are as follows: (1) A lack of time to screen during the clinic visit. Short hospital visits and large outpatient volumes limit the screening for psychiatric symptoms. (2) Patients’ stigma or inferiority on acknowledging their mental status. (3) A lack of professionals trained to recognize the psychological disorders of PWE. (4) There was no standard guideline for the management. To solve this problem, the CC-CAAE has published the Chinese expert consensus for screening epilepsy comorbidities with several self-rating scales. Internationally, the ILAE has issued clinical practice recommendations on the management of depression in PWE.³¹ Still, public education to ease the patients’ concerns as well as professional training of neurologists is necessary to fill that gap.

In this study, we also found that the rates of focal and focal to bilateral TCSZ as well as abnormal MRI seem to vary by region, which may be due to the difference in sample sizes. In addition, the various demographic genetic backgrounds and medical technologies of different regions may also contribute to the discrepancies. However, these assumptions need to be validated.

There are several limitations and strengths in our study. First, a cross-sectional study did not allow us to establish specific causal interpretations and comment on the prevalence of lifetime anxiety, depression, and suicidality in PWE. Second, all of the participants were adults. Therefore, our findings may not be adaptive for all patient groups. Third, the sample sizes of patients treated with anti-comorbidities drugs without symptoms and those treated with ongoing symptoms were very small, the comparisons of demographic and clinical characteristics between them warrant further investigation. Finally, using smartphone technology for smart code scanning may to some extent limit the inclusion of patients who are unable to use smartphones, which may lead to sample bias. The major strength of our study was that this is the first multicenter study, across geographic regions, in Chinese PWE with a large sample size to estimate the prevalence of psychiatric comorbidities at the national level.

Conclusion

Overall, this study found that approximately one-third of PWE had anxiety or depression. Being female individuals, focal and focal to bilateral TCSZ and seizure occurrence in the last 3 months were identified as risk factors for psychiatric comorbidities. However, the treatment of psychiatric comorbidities was not optimal, clinicians should pay more attention to the screening and management of the comorbidities in PWE.

Supplemental Material

sj-docx-1-tan-10.1177_17562864231187194 – Supplemental material for Prevalence and risk factors of anxiety and depression in adult patients with epilepsy: a multicenter survey-based study

Supplemental material, sj-docx-1-tan-10.1177_17562864231187194 for Prevalence and risk factors of anxiety and depression in adult patients with epilepsy: a multicenter survey-based study by Wenyan Shi, Hanlin Sun, Wei Peng, Ziyi Chen, Qun Wang, Weihong Lin, Meiping Ding, Hongbin Sun, Xiangqing Wang, Tiancheng Wang, Xuefeng Wang, Yonghong Liu, Yangmei Chen, Guoxing Zhu, Dong Zhou and Jinmei Li in Therapeutic Advances in Neurological Disorders

Footnotes

Acknowledgements

We are grateful to all the participants for their valuable information, cooperation, and participation.

Declarations

ORCID iDs

Wenyan Shi

Hanlin Sun

Wei Peng

Meiping Ding

Jinmei Li

Supplemental material

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References

Thijs

Surges

O’Brien

, et al. Epilepsy in adults. Lancet 2019; 393: 689–701.

Fisher

Acevedo

Arzimanoglou

, et al. ILAE official report: a practical clinical definition of epilepsy. Epilepsia 2014; 55: 475–482.

Tellez-Zenteno

Patten

Jette

, et al. Psychiatric comorbidity in epilepsy: a population-based analysis. Epilepsia 2007; 48: 2336–2344.

Josephson

Lowerison

Vallerand

, et al. Association of depression and treated depression with epilepsy and seizure outcomes: a multicohort analysis. JAMA Neurol 2017; 74: 533–539.

Johnson

Jones

Seidenberg

, et al. The relative impact of anxiety, depression, and clinical seizure features on health-related quality of life in epilepsy. Epilepsia 2004; 45: 544–550.

Lacey

Salzberg

Roberts

, et al. Psychiatric comorbidity and impact on health service utilization in a community sample of patients with epilepsy. Epilepsia 2009; 50: 1991–1994.

Cankurtaran

Ulug

Saygi

, et al. Psychiatric morbidity, quality of life, and disability in mesial temporal lobe epilepsy patients before and after anterior temporal lobectomy. Epilepsy Behav 2005; 7: 116–122.

Machado

Espinosa

Melendrez

, et al. Suicidal risk and suicide attempts in people treated with antiepileptic drugs for epilepsy. Seizure 2011; 20: 280–284.

Dalmagro

Velasco

Bianchin

, et al. Psychiatric comorbidity in refractory focal epilepsy: a study of 490 patients. Epilepsy Behav 2012; 25: 593–597.

10.

Jones

Hermann

Barry

, et al. Clinical assessment of Axis I psychiatric morbidity in chronic epilepsy: a multicenter investigation. J Neuropsychiatry Clin Neurosci 2005; 17: 172–179.

11.

Scott

Sharpe

Hunt

, et al. Anxiety and depressive disorders in people with epilepsy: a meta-analysis. Epilepsia 2017; 58: 973–982.

12.

Chen

Zhu

, et al. Depression in people with epilepsy in West China: status, risk factors and treatment gap. Seizure 2019; 66: 86–92.

13.

Shen

Cai

, et al. Managing depression and anxiety in patients with epilepsy in eastern China: a survey of epilepsy health professionals in Zhejiang Province. Epilepsy Behav 2022; 127: 108516.

14.

Kanner

. Is it time to train neurologists in the management of mood and anxiety disorders? Epilepsy Behav 2014; 34: 139–143.

15.

Wang

Tan

Deng

, et al. Prevalence and risk factors of depression and anxiety among patients with convulsive epilepsy in rural West China. Acta Neurol Scand 2018; 138: 541–547.

16.

Zhong

Chen

, et al. Sex-based differences in the prevalence of and risk factors for depression in adult patients with epilepsy in Northeast China. Epilepsy Behav 2021; 122: 108201.

17.

Scheffer

Berkovic

Capovilla

, et al. ILAE classification of the epilepsies: position paper of the ILAE Commission for Classification and Terminology. Epilepsia. 2017; 58: 512–521.

18.

Kwan

Arzimanoglou

Berg

, et al. Definition of drug resistant epilepsy: consensus proposal by the ad hoc Task Force of the ILAE Commission on Therapeutic Strategies. Epilepsia 2010; 51: 1069–1077.

19.

Castano

Spotnitz

Waldman

, et al. Identification of patients with drug-resistant epilepsy in electronic medical record data using the Observational Medical Outcomes Partnership Common Data Model. Epilepsia 2022; 63: 2981–2993.

20.

Hill

Lin

Terman

, et al. Definitions of drug-resistant epilepsy for administrative claims data research. Neurology. 2021; 97: e1343–e1350.

21.

Micoulaud-Franchi

Lagarde

Barkate

, et al. Rapid detection of generalized anxiety disorder and major depression in epilepsy: validation of the GAD-7 as a complementary tool to the NDDI-E in a French sample. Epilepsy Behav 2016; 57: 211–216.

22.

Spitzer

Kroenke

Williams

, et al. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med 2006; 166: 1092–1097.

23.

Zinchuk

Kustov

Pashnin

, et al. Validation of the Generalized Anxiety Disorder-7 (GAD-7) in Russian people with epilepsy. Epilepsy Behav 2021; 123: 108269.

24.

Tong

McGonigal

, et al. Validation of the Generalized Anxiety Disorder-7 (GAD-7) among Chinese people with epilepsy. Epilepsy Res 2016; 120: 31–36.

25.

Gilliam

Barry

Hermann

, et al. Rapid detection of major depression in epilepsy: a multicentre study. Lancet Neurol. 2006; 5: 399–405.

26.

Silagadze

Kasradze

Silagadze

, et al. Validation of a Georgian version of the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E). Epilepsy Behav 2019; 101: 106587.

27.

Rashid

Katyal

Tripathi

, et al. Validation of the Indian version of Neurological Disorders Depression Inventory for Epilepsy (NDDI-E). Epilepsy Behav 2019; 95: 75–78.

28.

Tong

Lan

, et al. Validation of the Chinese version of the Neurological Disorders Depression Inventory for Epilepsy (C-NDDI-E) in West China. Epilepsy Behav 2015; 47: 6–10.

29.

Zhu

Wang

, et al. Validation of the Neurological Disorders Depression Inventory for Epilepsy (NDDIE) as a rapid suicidality screening tool in Chinese people with epilepsy. Epilepsy Behav 2019; 94: 216–221.

30.

Bandelow

Allgulander

Baldwin

, et al. World Federation of Societies of Biological Psychiatry (WFSBP) guidelines for treatment of anxiety, obsessive-compulsive and posttraumatic stress disorders – Version 3. Part I: Anxiety disorders. World J Biol Psychiatry 2023; 24: 79–117.

31.

Mula

Brodie

de Toffol

, et al. ILAE clinical practice recommendations for the medical treatment of depression in adults with epilepsy. Epilepsia 2022; 63: 316–334.

32.

Kennedy

Lam

McIntyre

, et al. Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 clinical guidelines for the management of adults with major depressive disorder: Section 3. Pharmacological treatments. Can J Psychiatry 2016; 61: 540–560.

33.

Grunze

Vieta

Goodwin

, et al. The World Federation of Societies of Biological Psychiatry (WFSBP) guidelines for the biological treatment of bipolar disorders: acute and long-term treatment of mixed states in bipolar disorder. World J Biol Psychiatry 2018; 19: 2–58.

34.

Zhao

Sun

, et al. Evaluation of clinical aspects and quality of life as risk factors for depression in patients with epilepsy. Seizure 2012; 21: 367–370.

35.

Zhu

Zhao

, et al. High risk of anxiety and depression in caregivers of adult patients with epilepsy and its negative impact on patients’ quality of life. Epilepsy Behav 2019; 90: 132–136.

36.

Kobau

Gilliam

Thurman

. Prevalence of self-reported epilepsy or seizure disorder and its associations with self-reported depression and anxiety: results from the 2004 HealthStyles Survey. Epilepsia 2006; 47: 1915–1921.

37.

Yang

Shi

, et al. Risk factors for depression in patients with epilepsy: a meta-analysis. Epilepsy Behav 2020; 106: 107030.

38.

Bosak

Turaj

Dudek

, et al. Depressogenic medications and other risk factors for depression among Polish patients with epilepsy. Neuropsychiatr Dis Treat 2015; 11: 2509–2517.

39.

Perucca

Gilliam

. Adverse effects of antiepileptic drugs. Lancet Neurol 2012; 11: 792–802.

40.

Akinsulore

Adewuya

. Psychosocial aspects of epilepsy in Nigeria: a review. Afr J Psychiatry. 2010; 13: 351–356.

41.

Xue-Ping

Hai-Jiao

Li-Na

, et al. Risk factors for drug-resistant epilepsy: a systematic review and meta-analysis. Medicine (Baltimore) 2019; 98: e16402.

42.

Fujise

Abe

Fukunaga

, et al. Comparisons of prevalence and related factors of depression in middle-aged adults between urban and rural populations in Japan. J Affect Disord 2016; 190: 772–776.

43.

Luo

, et al. Prevalence and risk factors for depression in outpatient departments of three general hospitals in China: a cross-sectional study. Int J Psychiatry Clin Pract 2020; 24: 88–95.

44.

Diehl

Coyle

Labouvie-Vief

. Age and sex differences in strategies of coping and defense across the life span. Psychol Aging 1996; 11: 127–139.

45.

Charles

Carstensen

. Unpleasant situations elicit different emotional responses in younger and older adults. Psychol Aging 2008; 23: 495–504.

46.

Jorm

. Does old age reduce the risk of anxiety and depression? A review of epidemiological studies across the adult life span. Psychol Med 2000; 30: 11–22.

47.

Suda

Tatsuzawa

Mogi

, et al. Interictal dysphoric disorder in patients with localization-related epilepsy: diagnostic relationships with DSM-IV psychiatric disorders and the impact of psychosocial burden. Epilepsy Behav 2016; 54: 142–147.

48.

Liu

Yin

Fan

, et al. Gender differences in associated and predictive factors of anxiety and depression in people with epilepsy. Front Psychiatry 2020; 11: 670.

49.

Adewuya

Ola

. Prevalence of and risk factors for anxiety and depressive disorders in Nigerian adolescents with epilepsy. Epilepsy Behav 2005; 6: 342–347.

50.

Jacoby

Baker

Steen

, et al. The clinical course of epilepsy and its psychosocial correlates: findings from a U.K. Community study. Epilepsia 1996; 37: 148–161.

51.

Zhong

Chen

, et al. Sex differences in anxiety in patients with epilepsy: status and risk factors analysis. Epilepsy Behav 2021; 116: 107801.

52.

Lake

Eaves

Maes

, et al. Further evidence against the environmental transmission of individual differences in neuroticism from a collaborative study of 45,850 twins and relatives on two continents. Behav Genet 2000; 30: 223–233.

53.

Graham

. Why are women so vulnerable to anxiety, trauma-related and stress-related disorders? The potential role of sex hormones. Lancet Psychiatry 2017; 4: 73–82.

54.

Schmitt

Long

McPhearson

, et al. Personality and gender differences in global perspective. Int J Psychol 2017; 52: 45–56.

55.

Norton

Sexton

Walker

, et al. Hierarchical model of vulnerabilities for anxiety: replication and extension with a clinical sample. Cogn Behav Ther 2005; 34: 50–63.

56.

McLean

Anderson

. Brave men and timid women? A review of the gender differences in fear and anxiety. Clin Psychol Rev 2009; 29: 496–505.

57.

Mak

Pang

Lai

, et al. Body esteem in Chinese adolescents: effect of gender, age, and weight. J Health Psychol 2013; 18: 46–54.

58.

Gaus

Kiep

Holtkamp

, et al Gender differences in depression, but not in anxiety in people with epilepsy. Seizure 2015; 32: 37–42.

59.

Kwon

Park

. Depression and anxiety in people with epilepsy. J Clin Neurol 2014; 10: 175–188.

60.

Zhong

, et al. Social anxiety is associated with poor quality of life in adults with epilepsy in Northeast China: a cross-sectional study. Epilepsy Behav 2021; 117: 107866.

61.

Naghavi M and Global Burden of Disease Self-Harm Collaborators. Global, regional, and national burden of suicide mortality 1990 to 2016: systematic analysis for the Global Burden of Disease Study 2016. BMJ 2019; 364: l94.

62.

GBD 2016 Epilepsy Collaborators. Global, regional, and national burden of epilepsy, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol 2019; 18: 357–375.

63.

Nilsson

Ahlbom

Farahmand

, et al. Risk factors for suicide in epilepsy: a case control study. Epilepsia 2002; 43: 644–651.

64.

Jones

Hermann

Barry

, et al. Rates and risk factors for suicide, suicidal ideation, and suicide attempts in chronic epilepsy. Epilepsy Behav 2003; 4: S31–S38.

65.

Hecimovic

Santos

Carter

, et al. Depression but not seizure factors or quality of life predicts suicidality in epilepsy. Epilepsy Behav 2012; 24: 426–429.

66.

Phillips

Zhang

. Suicide rates in China, 1995–1999. Lancet 2002; 359: 835–840.

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