Risk factors for anxiety and depression in patients with atopic dermatitis and their impact on prognosis

Abstract

BACKGROUND

Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by visible lesions that can lead to anxiety and depression. These psychological impacts may severely affect the physical and mental health and the overall quality of life of the affected individuals.

AIM

To identify the risk factors for anxiety and depression among patients with AD and to assess their influence on prognosis.

METHODS

A cross-sectional study was conducted in 273 patients with AD who visited Shanghai Jinshan Tinglin Hospital between July 2021 and June 2023. Data were collected using standardized instruments, including the general information questionnaire, hospital anxiety and depression scale, scoring AD index, and dermatology life quality index.

RESULTS

Among the evaluated patients, 24.5% had symptoms of anxiety, and 19.8% had symptoms of depression. Independent risk factors for anxiety included lower education level [odds ratio (OR) = 0.338, 95% confidence interval (CI): 0.183-0.625], increased number of medical visits (OR = 2.300, 95%CI: 1.234-4.255), sleep disorders (OR = 2.013, 95%CI: 1.032-3.923), and allergic rhinitis (OR = 2.052, 95%CI: 1.097-3.839). Factors for depression included more severe pruritus (OR = 6.837, 95%CI: 1.330-35.132), higher number of medical visits (OR = 2.979, 95%CI: 1.430-6.205), sleep disorders (OR = 2.245, 95%CI: 1.033-5.024), and asthma (OR = 2.208, 95%CI: 1.003-4.859). Dermatology life quality index scores correlated positively with anxiety, depression, scoring AD index, sleep disorders, number of visits, and intensity of pruritus (P < 0.05).

CONCLUSION

In patients with AD, anxiety and depression are associated with educational level, frequency of medical visits, sleep disorders, allergic rhinitis, pruritus, and asthma, all of which exacerbate symptoms and reduce quality of life.

Key Words: Atopic dermatitis; Anxiety; Depression; Pruritus; Sleep disorder; Quality of life

Core Tip: Atopic dermatitis (AD) exhibits a substantial comorbidity with anxiety and depression, with epidemiological studies highlighting their synergistic adverse effects on psychological well-being and quality of life of patients. We identified that the risk factors for anxiety and depression in patients with AD included educational level, frequency of medical visits, severity of pruritus, sleep disorders, allergic rhinitis, and asthma. Early recognition of these factors can enable targeted mental health prevention strategies and interventions that may benefit patients with AD by addressing modifiable risk factors.

INTRODUCTION

Atopic dermatitis (AD) is a common chronic inflammatory skin disease characterized by recurrent episodes of eczematoid dermatitis, significant skin dryness, and severe pruritus[1]. Patients with AD frequently exhibit comorbid atopic conditions, including allergic rhinitis and asthma, leading to its classification as a systemic disease[2]. The pathogenesis of AD is complex and is not fully understood. It is generally believed to result from a combination of genetic factors, environmental conditions, immune abnormalities, skin barrier dysfunction, skin flora disorders, and other factors. Recent years have seen an increase in AD incidence, with nearly 25% of children worldwide and 5%-10% of adults reported to be affected[3,4]. AD typically begins in infancy and can continue into adulthood, although it may also develop in adulthood. However, 85% of patients are diagnosed before the age of 5 years.

AD significantly impacts the mental health of affected patients. According to a survey, over 30% of patients with AD have been diagnosed with depression and/or anxiety[5]. The frequent experiences of anxiety and depression in patients with AD are often due to ongoing pruritus, skin lesions, discomfort, and associated social stigma. Additionally, itch-related decreases in sleep quality can further increase the risk of mental disorders[6,7]. Proinflammatory cytokines associated with AD may drive depressive symptoms through neuroimmune dysregulation[8]. Moreover, long-term anxiety and depression can lead to endocrine dysfunction, inducing the release of neuroregulatory substances that adversely affect AD progression. This results in skin barrier dysfunction and a reduced itch threshold, further exacerbating the clinical symptoms of AD[8-10].

Therefore, it is crucial to address not only the dermatological manifestations of AD but also the psychological well-being of patients. While the link between AD and mental disorders is well-established, the specific factors influencing these mental disorders associated with AD need further study. Research into the risk factors for anxiety and depression among AD patients is limited, yet a high incidence of these conditions is reported. Investigating the underlying causes of these psychological issues and identifying their influencing factors is essential to enable targeted mental health prevention strategies or modifiable factors for patients with AD.

In this context, this study aimed to identify the risk factors for anxiety and depression in patients with AD and their relationship with patient prognosis. The findings of this study could significantly improve the mental health and quality of life of those affected by AD.

MATERIALS AND METHODS

Study participants

In this cross-sectional study, 273 patients with AD were enrolled as study subjects using stratified random sampling (stratification variables: Sex; age; and disease severity). The sampling process was conducted at the Department of Dermatology, Shanghai Jinshan Tinglin Hospital from July 2021 to June 2023.

The inclusion criteria for participation in the study were: (1) Fulfilling the Hanifin-Rajka AD diagnostic criteria[11] and confirmation through a laboratory examination; (2) Treatment and disease management at our hospital; (3) Certain cognition and understanding ability; (4) No psychological treatment or psychological intervention received in the 6 months prior to recruitment; and (5) Good compliance and cooperation during the investigation. The exclusion criteria were as follows: (1) AD with other chronic skin diseases; (2) Pregnant or lactating females; and (3) Patients with damaged heart, liver, kidney, and other important organs.

Informed consent was obtained from all patients and their families included in the present study.

Survey tools

A structured questionnaire specifically designed for this study was used. It was distributed to participants by the researcher in the outpatient department. The survey method and precautions were explained to the patients according to unified instructions, and the principle of confidentiality was also discussed. After obtaining consent from all patients, they were asked to complete the questionnaire independently. If a participant encountered difficulty in understanding any items, the researcher provided an explanation and then assisted in completing the questionnaire according to the patient’s responses. After collecting all completed questionnaires, the researcher verified their completeness, and any missing information was supplemented, and errors corrected.

Individual characteristics

The demographic information (sex, age, marital status, education, residence, etc) and clinical data (course of disease, severity of skin lesions, degree of pruritus, number of visits, self-care ability, sleep disorders, etc) of the patients was collected.

Hospital anxiety and depression scale score

The hospital anxiety and depression scale (HADS)[12], a widely validated screening instrument, assesses anxiety (HADS-A) and depression (HADS-D) in somatic disease populations. The scale includes 14 items, divided into two subscales: Seven items for HADS-A; and seven items for HADS-D. Generally, a HADS-A ≥ 8 indicates a tendency toward anxiety, and a HADS-D ≥ 8 suggests a tendency toward depression.

Scoring AD

The scoring AD (SCORAD) index[13] is extensively used in clinical research on AD. The index is divided into three parts: (1) Skin lesion area, where 1% of the area equals 1 point, with a maximum of 100 points; (2) Severity of skin lesions, which includes six signs: Erythema; papules/edema; exudation/crusting; exfoliation; lichenification; and dry skin (unaffected skin only). Each sign is graded on a 4-point scale from 0 (none) to 3 (severe), with a maximum score of 18; and (3) Degree of pruritus and sleep disturbance, scored from 0 to 10, with a maximum of 20 points. The SCORAD score is calculated as follows: A/5 + 7B/2 + C, with the highest attainable score being 103. Scores ranging from 0-24 indicate a mild condition, a range of 25-50 indicates a moderate condition, and a range of 51-103 indicates a severe condition. The index has a Cronbach’s α coefficient of 0.841 and a content validity of 0.808.

Dermatology life quality index score

The dermatology life quality index (DLQI)[14] is an internationally recognized tool for assessing dermatology-specific quality of life. It includes 6 dimensions across 10 items, each scored from 0 to 3 points, with the maximum possible score being 30. A higher score indicates a greater impact of the disease on the patient’s quality of life. Scores of 0-1 indicate "no impact", 2-5 indicate "mild impact", 6-10 indicate "moderate impact", 11-20 indicate "severe impact", and 21-30 indicate "extremely severe impact".

Data collection and quality control

A field questionnaire survey was conducted in the outpatient department from July 6, 2021 to June 2, 2023. Before the study began, four researchers received standardized training on questionnaire design principles, collection methods, medical terminology interpretation, and communication skills. Researchers distributed questionnaires to eligible patients, explained the purpose of the survey, and the principles of anonymity and confidentiality using unified guidelines. After obtaining informed consent, patients were asked to complete the questionnaires independently in the consulting room. If any item was difficult to understand during this process, the researcher provided a colloquial explanation without leading the response. Once collected, the researchers immediately reviewed the questionnaires for completeness, asked patients to fill in any missing items, and corrected any contradictory items after double confirmation with the patients. The average time to complete the questionnaire was 9.6 min. Upon completion of the survey, data entry was conducted by two individuals using EpiData 3.1, which included checks for logical consistency and automatic flagging of conflicting data to ensure data reliability.

Statistical analysis

All data were statistically analyzed using SPSS version 23.0. Categorical data were expressed as rates or percentages and analyzed using the χ² test to compare differences between groups. Measurement data were expressed as mean and standard deviation and analyzed using analysis of variance to compare differences between groups. Bivariate normal distribution data were analyzed using Pearson linear correlation, whereas non-normal distribution data were analyzed using Spearman rank correlation. P < 0.05 was deemed statistically significant.

RESULTS

Comparison of the HADS-A and HADS-D scores among patients with different baseline data

The baseline data for the patients are presented in Table 1. A total of 273 patients with AD were enrolled in this study, of which 67 (24.5%) exhibited anxiety symptoms and 54 (19.8%) had depression symptoms. The χ² test showed statistically significant differences in the HADS-A and HADS-D scores among patients with varying education levels, disease duration, severity of skin lesions, degree of pruritus, number of visits, sleep status, and presence of asthma (P < 0.05). Significant differences were also observed in the HADS-D scores among patients with different marital statuses and food allergies and in the HADS-A scores among patients with or without allergic rhinitis.

Table 1 Comparison of hospital anxiety and depression scale assesses anxiety and depression scores among patients with different baseline data.

Characteristic	n	HADS-A	t/F value	P value	HADS-D	t/F value	P value
Gender			-2.420	0.187		-2.384	0.287
Male	127	6.66 ± 3.44			6.26 ± 3.19
Female	146	7.73 ± 3.82			7.23 ± 3.46
Age (years)			-0.101	0.222		1.067	0.699
< 35	158	7.22 ± 3.87			6.96 ± 3.38
≥ 35	115	7.26 ± 3.42			6.52 ± 3.35
Marital status			0.856	0.426		3.292	0.039
Unmarried	102	7.59 ± 3.97			7.28 ± 3.41
Married	154	6.98 ± 3.46			6.33 ± 3.19
Divorced or widowed	17	7.41 ± 3.84			7.76 ± 4.15
Educational level			1.092	0.004		-0.282	0.105
High school and below	113	7.53 ± 3.98			6.71 ± 3.54
College degree or above	160	7.03 ± 3.45			6.83 ± 3.25
Place of residence			0.060	0.393		1.331	0.135
Rural area	95	7.25 ± 3.87			6.29 ± 3.43
City	168	7.22 ± 3.59			6.58 ± 3.32
Disease duration (year)			-1.558	0.004		-1.921	0.001
< 5	87	6.77 ± 3.07			6.21 ± 2.74
≥ 5	186	7.45 ± 3.92			7.04 ± 3.60
Degree of skin lesion			7.751	0.001		19.471	0.000
No or slight	92	6.37 ± 3.00			5.40 ± 2.01
Moderate	149	7.34 ± 3.70			7.09 ± 3.50
Severe	32	9.25 ± 4.55			9.28 ± 4.10
Degree of pruritus			8.543	0.000		30.358	0.000
Slight	75	6.15 ± 2.70			5.12 ± 1.97
Moderate	88	6.86 ± 3.28			6.07 ± 2.18
Severe	110	8.27 ± 4.28			8.47 ± 4.08
Number of visits per month			-2.812	0.000		-2.480	0.000
< 3	154	6.68 ± 3.25			6.32 ± 3.01
≥ 3	119	7.96 ± 4.07			7.36 ± 3.71
Self-care ability			1.003	0.368		1.056	0.349
Low level	48	7.92 ± 4.21			7.33 ± 3.93
Intermediate level	134	7.10 ± 3.54			6.79 ± 3.35
High level	91	7.07 ± 3.59			6.46 ± 3.06
Sleep disorders			-2.477	0.000		-2.802	0.000
No	106	6.58 ± 3.23			6.10 ± 2.84
Yes	167	7.65 ± 3.89			7.20 ± 3.61
Family history			-0.542	0.398		-1.330	0.632
No	209	7.17 ± 3.64			6.63 ± 3.35
Yes	64	7.45 ± 3.82			7.27 ± 3.41
Smoking history			0.541	0.438		1.145	0.918
No	240	7.28 ± 3.75			6.88 ± 3.34
Yes	33	6.91 ± 3.16			6.00 ± 3.54
Drinking alcohol history			0.585	0.670		1.127	0.348
No	231	7.29 ± 3.73			6.87 ± 3.42
Yes	42	6.93 ± 3.44			6.24 ± 3.06
Food allergy			-0.033	0.065		-2.601	0.000
No	85	7.22 ± 3.18			6.11 ± 2.40
Yes	188	7.24 ± 3.89			7.08 ± 3.69
Allergic rhinitis			-1.448	0.041		-1.040	0.556
No	126	6.89 ± 3.51			6.55 ± 3.35
Yes	147	7.65 ± 3.81			6.97 ± 3.38
Asthma			-1.738	0.022		-1.638	0.000
No	162	7.06 ± 3.56			6.67 ± 3.09
Yes	111	7.87 ± 3.99			7.41 ± 4.01

Data are presented as mean ± SD. Statistical methods: Two-tailed independent t-test (equal variances); One-way analysis of variance. HADS-A: Hospital anxiety and depression scale assesses anxiety score; HADS-D: Hospital anxiety and depression scale assesses depression score.

Binary logistic regression analysis of the risk factors for anxiety in patients with AD

Independent risk factors for anxiety in patients with AD included lower education level [odds ratio (OR) = 0.338, 95% confidence interval (CI): 0.183-0.625], higher number of visits (OR = 2.300, 95%CI: 1.234-4.255), sleep disorders (OR = 2.013, P < 0.05, 95%CI: 1.032-3.923), and allergic rhinitis (OR = 2.052, 95%CI: 1.097-3.839) (Table 2).

Table 2 Binary logistic regression analysis of risk factors for anxiety in patients with atopic dermatitis.

Item	B	SE	Wald	P value	OR	95%CI
						Lower	Upper
Educational level	-1.085	0.313	11.985	0.001	0.338	0.183	0.625
Disease duration	0.125	0.337	0.138	0.710	1.134	0.585	2.195
Degree of skin lesion			2.697	0.260
	0.599	0.481	1.552	0.213	1.820	0.709	4.671
	0.991	0.606	2.674	0.102	2.693	0.821	8.830
Degree of pruritus			0.087	0.958
	0.128	0.503	0.064	0.800	0.880	0.328	2.361
	0.047	0.552	0.007	0.932	0.954	0.323	2.814
Number of visits	0.833	0.314	7.036	0.008	2.300	1.234	4.255
Sleep disorders	0.699	0.341	4.216	0.004	2.013	1.032	3.923
Allergic rhinitis	0.719	0.320	5.062	0.024	2.052	1.097	3.839
Asthma	0.222	0.323	0.474	0.491	0.801	0.425	1.508

Statistical method: Binary logistic regression analysis. OR: Odds ratio; CI: Confidence interval.

Binary logistic regression analysis of the risk factors for depression in patients with AD

Independent risk factors for depression in patients with AD included severe pruritus (OR = 6.837, 95%CI: 1.330-35.132), higher number of visits (OR = 2.979, 95%CI: 1.430-6.205), sleep disorders (OR = 2.245, 95%CI: 1.033-5.024), and asthma (OR = 2.208, 95%CI: 1.003-4.859) (Table 3).

Table 3 Binary logistic regression analysis of risk factors for depression in patients with atopic dermatitis.

Item	B	SE	Wald	P value	OR	95%CI
						Lower	Upper
Marital status			2.816	0.245
	-0.625	0.380	2.709	0.100	0.535	0.255	1.127
	-0.142	0.683	0.043	0.835	0.868	0.228	3.307
Disease duration	0.680	0.419	2.628	0.105	1.973	0.868	4.489
Degree of skin lesion			2.509	0.285
	0.466	0.655	0.506	0.477	1.593	0.442	5.746
	1.100	0.765	2.086	0.150	3.006	0.671	13.467
Degree of pruritus			9.440	0.009
	0.725	0.802	0.817	0.366	2.065	0.428	9.953
	1.922	0.835	5.298	0.021	6.837	1.330	35.132
Number of visits	1.092	0.374	8.504	0.004	2.979	1.430	6.205
Sleep disorders	0.809	0.411	3.874	0.049	2.245	1.033	5.024
Food allergy	0.809	0.438	3.420	0.064	2.247	0.953	5.298
Asthma	0.792	0.402	3.873	0.049	2.208	1.003	4.859

Statistical method: Binary logistic regression analysis. OR: Odds ratio; CI: Confidence interval.

Comparison of the SCORAD and DLQI scores among patients with different emotional symptoms

Compared with individuals without anxiety symptoms, those with anxiety symptoms had substantially higher SCORAD and DLQI ratings (P < 0.05). Similarly, the SCORAD and DLQI scores of patients with symptoms of depression were significantly higher than those of patients without depression symptoms (P < 0.05) (Table 4).

Table 4 Comparison of the scoring atopic dermatitis and dermatology life quality index scores among patients with different emotional symptoms.

	Anxiety		t value	P value	Depression		t value	P value
	Yes	No			Yes	No
SCORAD	46.78 ± 20.27	39.44 ± 18.47	-2.630	0.010	53.81 ± 20.08	38.14 ± 17.63	-5.261	0.020
DLQI	9.58 ± 5.71	7.81 ± 5.12	-2.259	0.026	11.46 ± 6.05	7.45 ± 4.81	-4.537	0.000

Data are presented as mean ± SD. Statistical method: Two-tailed independent t-test (equal variances). SCORAD: Scoring atopic dermatitis; DLQI: Dermatology life quality index.

Bivariate correlation of each factor to the DLQI

The average SCORAD score for patients with AD was 41.24 ± 19.15, and the average DLQI score was 8.24 ± 5.31. The DLQI score was positively correlated with HADS-A, HADS-D, SCORAD, sleep disorders, number of visits, and degree of pruritus (P < 0.05). There was no significant correlation between the DLQI score and self-care ability or course of disease (P > 0.05) (Table 5).

Table 5 Bivariate correlation between each factor and quality of life score (dermatology life quality index).

	1	2	3	4	5	6	7	8	9
HADS-A	1
HADS-D	0.337b	1
SCORAD	0.249b	0.361b	1
Self-care ability	-0.049	-0.047	0.076	1
Sleep disorders	0.133a	0.142a	0.147a	0.021	1
Number of visits	0.310b	0.322b	0.512b	0.038	0.170b	1
Degree of pruritus	0.240b	0.416b	0.693b	-0.021	0.168b	0.519b	1
Disease duration	0.064	0.045	-0.012	-0.030	0.068	0.046	-0.052	1
DLQI	0.265b	0.376b	0.925b	0.059	0.224b	0.533a	0.743b	-0.002	1

^aP < 0.05.

^bP < 0.01.

Statistical method: Pearson correlation analysis. HADS-A: Hospital anxiety and depression scale assesses anxiety score; HADS-D: Hospital anxiety and depression scale assesses depression score; SCORAD: Scoring atopic dermatitis; DLQI: Dermatology life quality index.

DISCUSSION

Patients with AD exhibit a significantly higher probability of experiencing anxiety and depression compared to the general population. In this study, 24.5% of the patients displayed symptoms of anxiety, and 19.8% exhibited symptoms of depression, indicating a substantial impact of AD on mental health. Multivariate logistic regression analysis identified several factors influencing anxiety and depression among these patients, including education level, number of medical visits, sleep disorders, allergic rhinitis, degree of pruritus, and asthma, with the number of visits and sleep disorders being common to both.

Educational attainment has consistently been identified as a protective factor against anxiety[15], a finding further validated in our study (β = -1.085, P = 0.001), showing a significant negative correlation between education level and anxiety scores. Notably, patients with lower education levels were at a markedly elevated risk for anxiety. This association may operate through dual pathways involving social support networks and neuroendocrine regulation. According to social support theory, highly educated patients typically have better capabilities to acquire instrumental support (e.g., using educational resources to understand AD treatment and proactively access clinical services) and mobilize emotional support networks to mitigate disease-related uncertainty. Conversely, patients with lower education levels may perceive the disease as ‘uncontrollable’ due to a lack of health knowledge and communication barriers, thus exacerbating anxiety cognitive susceptibility. Basic biological research suggests that educational level is positively correlated with the development of brain executive control networks, such as prefrontal cortex gray matter volume and amygdala-prefrontal cortex functional connectivity, indicating that a higher educational level may inhibit excessive stress responses by enhancing the neural efficacy of emotional regulation.

The educational level of individuals has long been considered a protective factor against anxiety[15], and the findings of this study confirm a significant negative correlation between education level and anxiety scores. Specifically, patients with lower education levels were more likely to suffer from anxiety. It is hypothesized that patients with higher education levels possess a more comprehensive understanding of AD and its prognosis as well as stronger cognitive abilities enabling them to actively cooperate with medical advice and manage the disease more effectively. In contrast, patients with lower education levels may have less understanding and awareness of AD, leading to difficulties in objectively and rationally approaching their condition, which may increase their likelihood of experiencing anxiety.

The frequency of medical visits for patients with AD, an illness characterized by chronicity and recurrence, plays a crucial role in patient emotions. This study found that 119 patients (43.6%) averaged three or more visits per month. While frequent visits are closely linked to treatment outcomes, they can also impact patients’ moods due to the ongoing nature of skin issues, medical appointments, and medication management, potentially leading to increased stress and anxiety. Furthermore, frustration during treatment can exacerbate psychological distress. Based on these findings, a tiered intervention strategy is recommended: (1) Establish a graded diagnosis and treatment system for mild, moderate, and severe cases, utilizing remote monitoring and multidisciplinary joint clinics to reduce unnecessary visit frequency; (2) Integrate electronic medical record systems with the patient health questionnaire-4 emotional screening tool to initiate timely cognitive-behavioral interventions for high-risk patients (scores ≥ 6); and (3) Develop regional patient support networks to alleviate sociopsychological stressors through peer experience sharing.

Pruritus is one of the primary symptoms of AD and a significant stressor for affected patients, with most reporting severe or unbearable pruritus[16,17]. This symptom causes physical discomfort and distress, significantly impacting patients’ psychological states. Long-term severe pruritus can cause extreme discomfort as the intense sensation is not effectively controlled or relieved promptly, leading to irritability or even depression in patients. Additionally, the redness, swelling, scaling, and exudation from dermatitis episodes can be embarrassing in social situations, making patients feel inferior and leading them to avoid social activities for fear of ridicule or rejection. This self-limiting behavior exacerbates negative emotions, creating a vicious cycle of isolation, anxiety, and depression. In this study, patients with severe pruritus had significantly higher anxiety and depression scores compared to those with mild or moderate pruritus. Adverse emotional states such as anxiety and depression can increase the excitability of sympathetic nerves in patients, promoting the release of catecholamines, histamine, and other vasoactive substances that ultimately aggravate facial redness, swelling, and pruritus[18-20].

Sleep disturbance is the most common complaint among patients with AD and often results from pruritus. Sleep disturbances, including prolonged sleep onset latency, nocturnal awakenings, and excessive daytime drowsiness, have been extensively documented in AD populations. Epidemiological studies estimate their prevalence at 47%-80% in pediatric cases and 33%-87% among adults[21,22]. This aligns with findings by Kaaz et al[23], who identified insomnia as a clinically significant comorbidity strongly correlated with pruritus severity in patients with AD. Research evidence demonstrates a significant association between sleep disturbances and an elevated risk of developing mood disorders, including anxiety and depression[24].

This aligns with the findings of the present study, which demonstrated that patients with sleep disorders exhibited increased symptoms of anxiety and depression. Notably, this deterioration in sleep-mood interaction may be closely linked to the neural mechanisms mediated by pruritus. Persistent nocturnal pruritus excessively activates the thalamocortical arousal pathway, disrupting the regulatory effects of the inhibitory neurotransmitter gamma-aminobutyric acid on sleep centers and leading to frequent nighttime awakenings. Sleep deprivation further reduces serotonin and dopamine secretion in the prefrontal cortex, thereby compromising emotional stability. Concurrently, chronic pruritus-induced stress triggers hyperactivity of the hypothalamic-pituitary-adrenal axis, resulting in abnormally elevated nocturnal cortisol levels. Cortisol inhibits hippocampal neurogenesis via glucocorticoid receptors and amplifies negative emotional processing[7,25].

Consequently, clinical interventions should adopt a multitarget approach: Using antidepressants (e.g., selective serotonin reuptake inhibitors) to modulate the serotonin system for improved emotional regulation; employing biologics to block interleukin-4/interleukin-13 pathways and reduce pruritus-driven neural activation; and integrating sleep-focused cognitive training to restore healthy circadian rhythms. This comprehensive strategy aims to disrupt the self-perpetuating cycle of "pruritus-neuroendocrine dysregulation-psychological comorbidities".

Several patients diagnosed with AD also had complications such as asthma and allergic rhinitis. AD, asthma, and allergic rhinitis are all linked to immune system abnormalities triggered by allergic reactions, and therefore these conditions can mutually promote or aggravate each other[26]. Managing multiple chronic diseases is particularly challenging, imposing both physical and psychological burdens on patients. Physically, the persistent discomfort affects their ability to work, study, and participate in social activities. Psychologically, it leads to feelings of anxiety, depression, and loss of confidence.

In the present study, Spearman’s correlation analysis was used to thoroughly examine multiple clinical indicators in patients with AD. Significant positive correlations were found between the DLQI score and variables such as HADS-A, HADS-D, SCORAD, sleep disturbance, the number of visits, and the degree of pruritus. The SCORAD score, which reflects disease severity, indicated that greater severity correlated with a poorer quality of life. Additionally, a positive correlation was observed between the SCORAD score and the number of hospital visits, suggesting that more severe disease leads to more frequent hospital visits, which in turn affects patients’ quality of life. The survey also found that 61.2% of these patients experienced sleep disorders. Both pruritus and sleep disorders are common in patients with AD and are primary reasons for a decline in quality of life[27]. Furthermore, a significant positive correlation between anxiety and depression was noted, indicating that more severe anxiety symptoms are associated with more severe depressive symptoms. These findings suggest that treatment for patients with AD should consider not only the physical symptoms but also the mental health aspects, including symptoms of anxiety and depression, to improve the overall quality of life.

As with all research, the present study had certain limitations. First, the sample size was relatively small. Additionally, the psychological assessment of patients was limited to the use of the HADS scale, without conducting a detailed and structured psychological interview. These limitations could have introduced bias into the survey results. In future studies, we plan to expand the sample size, continue collecting data on patients with AD, and more comprehensively evaluate the influencing factors of anxiety and depression in these patients.

CONCLUSION

Anxiety and depression in patients with AD are associated with factors such as educational level, number of visits, sleep disorders, allergic rhinitis, degree of pruritus, and asthma. Furthermore, the quality of life for AD patients is linked to anxiety, depression, SCORAD, sleep disorders, number of visits, and degree of pruritus. Therefore, in the clinical diagnosis and treatment of AD, it is crucial to adhere to a holistic approach that treats both the body and mind. This includes assessing the psychological state of patients and implementing psychological interventions to alleviate symptoms of anxiety and depression. Additionally, it is necessary to strengthen the comprehensive management of the disease and collaborate on multiple fronts to improve the quality of life for patients with AD.