Bai J, Kong C, Luo YP, Li Y, Zhang C. Mediating role of sleep disturbance in association between nasal congestion severity and anxiety symptoms in allergic rhinitis patients. World J Psychiatry 2026; 16(10): 123481 [DOI: 10.5498/wjp.123481]
Corresponding Author of This Article
Chao Zhang, MD, Researcher, Department of Otorhinolaryngology, The First People’s Hospital of Foshan, No. 81 Lingnan Avenue North, Chancheng District, Foshan 528000, Guangdong Province, China. fsyyyent@163.com
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Bai J, Kong C, Luo YP, Li Y, Zhang C. Mediating role of sleep disturbance in association between nasal congestion severity and anxiety symptoms in allergic rhinitis patients. World J Psychiatry 2026; 16(10): 123481 [DOI: 10.5498/wjp.123481]
Author contributions: Bai J and Kong C are co-first authors; Bai J and Kong C contributed to conceptualization, methodology, and investigation; Luo YP performed formal analysis and data curation; Li Y contributed to conceptualization, formal analysis, and data curation; Zhang C contributed to data curation, methodology, and writing original draft; all authors have read and approved the final manuscript.
AI contribution statement: The authors take full responsibility and accountability for all content of this manuscript, including any portions for which AI tools were used as assistive technologies. All AI-assisted outputs were carefully reviewed, validated, and approved by the authors. AI tools were not used to generate original scientific data, perform independent scientific analyses, or draw scientific conclusions.
Institutional review board statement: This study has been approved by the Institutional Review Board and Ethics Committee of the First People’s Hospital of Foshan, and in line with the principles of the Declaration of Helsinki.
Informed consent statement: As the data is de-identified and cannot be linked to a particular individual for harm or loss of privacy, consent is not required. Therefore, it has been permitted under the rules for late-stage study retrospectively.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Data sharing statement: The datasets in this paper can be obtained from the corresponding authors upon reasonable request.
Corresponding author: Chao Zhang, MD, Researcher, Department of Otorhinolaryngology, The First People’s Hospital of Foshan, No. 81 Lingnan Avenue North, Chancheng District, Foshan 528000, Guangdong Province, China. fsyyyent@163.com
Received: May 22, 2026 Revised: June 24, 2026 Accepted: July 28, 2026 Published online: October 19, 2026 Processing time: 144 Days and 3 Hours
Abstract
BACKGROUND
Nasal congestion in allergic rhinitis (AR) is commonly associated with sleep disturbances, which may be linked to negative emotional states such as anxiety.
AIM
To investigate the statistical associations between nasal congestion severity, sleep disorders, and anxiety levels in patients with AR.
METHODS
This retrospective cross-sectional study included 235 patients diagnosed with AR between January 2020 and June 2023. Patients were stratified into a severe nasal congestion (SNC) group [Visual Analog Scale (VAS) score ≥ 7] and a moderate nasal congestion (MNC) group (VAS score 4-6). Data on demographics and clinical characteristics were collected. Assessments included the nasal congestion VAS, the Pittsburgh Sleep Quality Index (PSQI) alongside self-reported sleep symptoms, the Generalized Anxiety Disorder 7-item Scale (GAD-7), and the Cuestionario ESPañol de Calidad de Vida en RINiTis-15 quality of life questionnaire.
RESULTS
The PSQI of the SNC group were significantly higher (indicating worse sleep quality) than those in the MNC group (10.24 ± 3.19 vs 9.05 ± 2.12, P < 0.001), and more sleep symptoms were reported by the SNC group (all P < 0.05). The SNC group also exhibited higher anxiety scores (GAD-7: 8.47 ± 2.63 vs 6.82 ± 1.95, P < 0.001) and a greater proportion of patients with clinically significant anxiety symptoms (81.7% vs 65.2%, P = 0.004). Correlation analysis revealed significant positive associations between nasal congestion severity, sleep disturbance, and anxiety symptoms (all P < 0.001). Exploratory statistical mediation analysis suggested that sleep disturbances accounted for a significant proportion (67.20%, indirect effect β = 0.352, 95% confidence interval: 0.259-0.452) of the observed association between nasal congestion severity and anxiety. This analysis was exploratory and adjusted for age and gender as potential confounders.
CONCLUSION
In this retrospective cohort, sleep disturbance demonstrated a statistically significant partial mediating role in the observed cross-sectional association between nasal congestion severity and anxiety symptoms among patients with AR, highlighting these interconnected domains for comprehensive clinical management. These hypothesis-generating findings require validation in prospective longitudinal studies.
Core Tip: This cross-sectional study of 235 allergic rhinitis patients found that sleep disturbance statistically mediated 67.2% of the observed association between nasal congestion severity and anxiety symptoms. The findings highlight that allergic rhinitis is not merely a local nasal disease but has systemic associations affecting sleep and mental health. Managing sleep disturbance may be as important as treating nasal congestion to reduce anxiety in allergic rhinitis patients. These hypothesis-generating results require prospective validation.
Citation: Bai J, Kong C, Luo YP, Li Y, Zhang C. Mediating role of sleep disturbance in association between nasal congestion severity and anxiety symptoms in allergic rhinitis patients. World J Psychiatry 2026; 16(10): 123481
Allergic rhinitis (AR) is a prevalent immunoglobulin E-mediated inflammatory disease of the nasal mucosa, characterized by symptoms such as sneezing, rhinorrhea, nasal itching, and nasal congestion[1,2]. It imposes a significant global health burden, affecting quality of life, work productivity, and socioeconomic resources[3,4]. Among these symptoms, nasal congestion is frequently the most bothersome. It persists into the night, interfering with sleep initiation and maintenance. Nasal airway obstruction can lead to increased respiratory effort, mouth breathing, and nocturnal awakening, disrupting normal sleep architecture[5]. The persistence of nasal congestion in AR is not merely a sensory experience but is underpinned by a complex pathophysiology involving inflammatory cell infiltration, mucosal edema, and potentially long-term tissue remodeling[6].
Sleep disturbance is a well-documented comorbidity in AR. Poor sleep quality, manifested as difficulty falling asleep, frequent awakenings, non-restorative sleep, and consequent daytime fatigue, is strongly correlated with the severity of nasal obstruction[7]. This creates a vicious cycle where AR symptoms impair sleep, and sleep deprivation may, in turn, lower the threshold for symptom perception and negatively impact immune function. The detrimental effects of chronically disrupted sleep extend far beyond physical tiredness, encroaching significantly on psychological and emotional well-being[8].
Anxiety is a common psychological condition frequently observed in patients with chronic inflammatory diseases like AR. The persistent nature of symptoms, their unpredictability, and their impact on daily activities and social interactions can contribute to heightened stress and anxiety levels[9]. Crucially, sleep disorders are recognized as a potent risk factor for the development and exacerbation of anxiety symptoms[10]. The neurobiological consequences of sleep loss, including dysregulation of the hypothalamic-pituitary-adrenal axis and heightened amygdala reactivity, are pathways through which poor sleep may foster an anxious state. Thus, in the context of AR, nasal congestion, sleep disturbance, and anxiety may be interlinked in a complex triad[11].
Although pairwise associations among these three factors have been explored separately, the integrated pathway remains insufficiently studied. We hypothesized a statistical pathway where nasal congestion is associated with anxiety partially through sleep disruption. We acknowledge alternative explanations including reverse causation and shared inflammatory mechanisms. Nasal congestion was chosen as the primary predictor because it is the most bothersome nocturnal symptom with a direct mechanical impact on sleep. Therefore, this retrospective cross-sectional study aims to investigate statistical associations between nasal congestion severity, sleep disorders, and anxiety in AR patients, and to exploratorily assess whether sleep disturbance statistically mediates the observed association. While causation cannot be established, mediation analysis is appropriate as a hypothesis-generating tool.
MATERIALS AND METHODS
Study subjects
This study is a single-center retrospective study. Data were sourced from the electronic medical record system of our hospital, covering patients diagnosed with AR who visited between January 2020 and June 2023. The study protocol was reviewed and approved by the Institutional Review Board (IRB) of our hospital. Given the retrospective nature of the study and the anonymization of all analyzed data, which posed no risk to individual patients, the IRB approved a waiver of informed consent.
A total of 235 patients aged between 18 years and 65 years, with a disease duration of at least one year and meeting the diagnostic criteria outlined of AR were included in the study[12]. All patients had documented nasal congestion, with baseline Visual Analog Scale (VAS) scores for nasal congestion ≥ 4, indicating significant discomfort. Patients with complete clinical records were included. Patients were excluded if they met any of the following criteria: Presence of other severe chronic diseases (such as heart failure, chronic obstructive pulmonary disease, asthma requiring daily controller medication, cancer) or a history of psychiatric disorders. Presence of other known conditions that cause sleep disorders [specifically obstructive sleep apnea (OSA) confirmed by a previous sleep study or a Stop-Bang Score ≥ 3, restless legs syndrome diagnosed by a neurologist]. Use of systemic corticosteroids or any medications that may affect mood (e.g., antidepressants, anxiolytics, sedatives) within one month prior to the study. Pregnant or breastfeeding women. Patients were divided into two groups based on their recorded VAS scores for nasal congestion: The severe nasal congestion (SNC) group (VAS score ≥ 7, n = 120) and the moderate nasal congestion (MNC) group (VAS score 4-6, n = 115). The cut-off of VAS ≥ 7 for severe and 4-6 for moderate follows established clinical guidelines and previous AR research, allowing for clinically meaningful group differentiation[13]. Patients with mild nasal congestion (VAS 1-3) were not included because our primary aim was to compare clinically significant nasal congestion (moderate vs severe) that is more likely to impact sleep and anxiety; mild congestion rarely causes substantial sleep disruption based on prior literature. These groups were compared and analyzed for differences in sleep disorders and anxiety levels.
Observation indicators and data extraction
Demographic, clinical characteristic and scale evaluation data of all enrolled patients were extracted from the electronic medical record system. The observation indicators were divided into six categories: General demographic indicators, clinical disease characteristics, nasal congestion-related symptom indicators, sleep quality indicators, anxiety emotion indicators, and quality of life indicators. The evaluation tools and criteria for all indicators adopted clinically recognized scales and guideline standards, as detailed below.
General information of all patients
Demographic information was extracted for each patient, including age, gender, body mass index (BMI), educational level, occupational status, smoking history, and alcohol consumption history. BMI was calculated using the formula weight (kg)/height2 (m2). Clinical characteristics of the disease included the duration of AR, type of onset, and family history of allergies. The specific types of allergens were identified and categorized as dust mites, pollen, mold, and animal dander.
Nasal congestion-related symptom assessment
The nasal congestion VAS was used to evaluate the severity of nasal congestion[14]. Patients were asked to mark the point that best represented the worst severity of their nasal congestion during the past two weeks on a line ranging from 0 to 10. A score of 0 indicates no nasal congestion, while a score of 10 represents the most severe congestion. Higher scores indicate more SNC. Scores of 1 to 3 are categorized as mild nasal congestion. Scores of 4 to 6 are categorized as MNC. Scores of 7 or higher are categorized as SNC. All VAS assessments were completed by patients during their first ambulatory visit before any treatment was initiated.
Sleep quality assessment
Sleep quality was evaluated by a combination of the Pittsburgh Sleep Quality Index (PSQI) and self-reported clinical sleep-related symptoms[15]. For this study, the PSQI was used to assess sleep quality during the past two weeks. PSQI scale consists of 7 components, namely subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. Each component is scored on a scale from 0 to 3, with the total score ranging from 0 to 21. Higher scores indicate poorer sleep quality. Additionally, clinical records were reviewed to extract data on the presence of specific sleep-related symptoms during the past two weeks. These symptoms included nighttime awakenings due to nasal congestion (≥ 1 time per night), mouth breathing, snoring, morning dry mouth or tongue, morning fatigue, and daytime sleepiness affecting work or daily life. These symptoms were self-reported by patients or reported by family members and recorded by the physician. All PSQI and sleep symptom data were collected at the same initial visit, reflecting the patients’ status in the two weeks prior to seeking care.
Anxiety emotion assessment
The Generalized Anxiety Disorder 7-item Scale (GAD-7) was used to evaluate the severity of anxiety in patients during the past two weeks[16]. This scale is a short-form anxiety screening tool consisting of 7 items, each scored on a 0-3 point scale. The total GAD-7 score is the sum of the scores for all items, with a range from 0 to 21 points. Higher scores indicate more prominent anxiety symptoms. The clinical judgment criteria are as follows: A total score of 0-4 indicates no anxiety, 5-9 indicates mild anxiety, 10-14 indicates moderate anxiety, and 15-21 indicates severe anxiety. For analysis, patients with scores ≥ 5 were considered to have clinically significant anxiety, and those with scores ≥ 10 were considered to have at least moderate anxiety. Additionally, the number of cases and the incidence rates of mild and moderate to severe anxiety were recorded. All GAD-7 data were collected at the same initial visit, reflecting the patients’ status in the two weeks prior to seeking care.
Quality of life assessment
The Cuestionario ESPañol de Calidad de Vida en RINiTis-15 (ESPRINT-15) was used to evaluate disease-related quality of life in patients[17]. This scale is specifically designed for patients with AR and consists of 15 items divided into four dimensions: Symptom dimension, daily activities dimension, sleep dimension, and mental health dimension. Each item is scored on a scale from 0 to 6. The total score and the scores for each dimension are standardized, with a range from 0 to 6. Higher scores indicate more severe impairment of quality of life due to AR. All ESPRINT-15 data were collected at the same initial visit.
Statistical analysis
All analyses were performed using SPSS 29.0 software (SPSS Inc., Chicago, IL, United States). The Shapiro-Wilk test was used to assess the normality of continuous variables. Normally distributed continuous data were presented as mean ± SD, and group comparisons were conducted using independent samples t-tests. Categorical data were presented as n (%), and group comparisons were performed using the χ2 test. Correlations were analyzed using Pearson correlation analysis with the correlation coefficient r reported as an effect size. No missing data were present for the key variables used in the primary analysis, as cases with incomplete records were excluded a priori. Mediation effect analysis was conducted using Hayes’ PROCESS macro (model 4) for SPSS, with nasal congestion VAS score as the independent variable, total GAD-7 score as the dependent variable and total PSQI score as the mediating variable, so as to verify the mediating effect of sleep disorders between nasal congestion and anxiety in patients with AR. The analysis adjusted for age and gender as a priori confounders. The unstandardized indirect effect was calculated using a bias-corrected bootstrap method with 5000 resamples, generating 95% confidence intervals (CIs). The proportion mediated was calculated as (indirect effect/total effect) × 100%. The precision of this proportion is implied by the CI of the indirect effect and should be interpreted cautiously. All tests were two-tailed, with a P value < 0.05 considered statistically significant.
RESULTS
General information of all patients
The demographic and clinical characteristics of the 235 patients included in the study, stratified into the MNC group (n = 115) and the SNC group (n = 120), are presented in Tables 1 and 2. There were no statistically significant differences between the two groups in terms of age, gender, BMI, educational level, employment status, smoking history, or alcohol consumption history (all P > 0.05, Table 1). Regarding disease characteristics, no significant differences were found in the duration of AR, type of AR (perennial vs seasonal), allergen sensitization profiles (dust mites, pollen, molds, animal dander), or family history of allergies (all P > 0.05, Table 2). As per the grouping criteria, the nasal congestion VAS score was significantly higher in the SNC group (8.26 ± 0.52) compared to the MNC group (5.15 ± 0.32, P < 0.001).
Table 1 Comparison of demographic characteristics between the two groups, mean ± SD/n (%).
Comparison of sleep quality between the two groups
Sleep quality assessments are detailed in Tables 3 and 4. The PSQI score was significantly worse in the SNC group (10.24 ± 3.19) compared to the MNC group (9.05 ± 2.12, P < 0.001). Significant differences were also observed across most PSQI components, including subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, and daytime dysfunction (all P < 0.05), except for the use of sleeping medication (P = 0.234) (Table 3).
Table 3 Comparison of sleep quality between the two groups, mean ± SD.
Analysis of specific sleep-related symptoms revealed that a significantly higher proportion of patients in the SNC group reported: Waking up at night due to nasal congestion (≥ 1 time) (63.33% vs 36.52%, P < 0.001), mouth breathing during sleep (69.17% vs 43.48%, P < 0.001), snoring (64.17% vs 49.57%, P = 0.024), waking up with a dry mouth/tongue (72.50% vs 52.17%, P = 0.001), morning fatigue (76.67% vs 58.26%, P = 0.003), and daytime sleepiness affecting work/Life (60.83% vs 42.61%, P = 0.005) (Table 4).
Comparison of anxiety between the two groups
Anxiety levels, assessed using the GAD-7 scale, were significantly higher in the SNC group (Figure 1). The mean global GAD-7 score was 8.47 ± 2.63 in the SNC group compared to 6.82 ± 1.95 in the MNC group (P < 0.001). Furthermore, the proportion of patients with clinically significant mild anxiety (GAD-7 ≥ 5) was 81.7% in the SNC group vs 65.2% in the MNC group (P = 0.004). The proportion of patients with at least moderate anxiety (GAD-7 ≥ 10) was also significantly higher in the SNC group (40.0% vs 24.3%, P = 0.010).
Figure 1 Comparison of anxiety between the two groups.
A: Global Generalized Anxiety Disorder 7-item score; B: Mild anxiety; C: Moderate to severe anxiety. aP < 0.05. bP < 0.01. cP < 0.001. GAD-7: Generalized Anxiety Disorder 7-item Scale; MNC: Moderate nasal congestion; SNC: Severe nasal congestion.
Comparison of quality of life between the two groups
Disease-specific quality of life, measured by the ESPRINT-15 questionnaire, was significantly more impaired in the SNC group across all domains (Figure 2). The total ESPRINT-15 score was significantly higher in the SNC group (3.00 ± 0.85) than in the MNC group (2.35 ± 0.58, P < 0.001). Significant differences were also found in the symptom dimension (3.41 ± 0.82 vs 2.66 ± 0.70), daily activity dimension (2.59 ± 0.73 vs 2.08 ± 0.58), sleep dimension (3.22 ± 0.78 vs 2.45 ± 0.60), and psychological well-being dimension (2.74 ± 0.70 vs 2.13 ± 0.51), all with P < 0.001.
Figure 2 Comparison of quality of life between the two groups.cP < 0.001. ESPRINT-15: Cuestionario ESPañol de Calidad de Vida en RINiTis-15; MNC: Moderate nasal congestion; SNC: Severe nasal congestion.
Correlation analysis of nasal congestion, sleep, and anxiety scores
Pearson correlation analysis revealed significant positive correlations among nasal congestion severity (VAS score), sleep disturbance (global PSQI score), and anxiety severity (global GAD-7 score) (all P < 0.001, Table 5). The nasal congestion VAS score showed moderate positive correlations with both the global PSQI score (r = 0.582) and the global GAD-7 score (r = 0.423). A strong positive correlation was observed between the global PSQI score and the global GAD-7 score (r = 0.616).
Table 5 Correlation analysis of nasal congestion, sleep, and anxiety scores.
Mediating effect of sleep disorders in the relationship between nasal congestion and anxiety in patients with AR
Mediation analysis was conducted to examine whether sleep disorders (global PSQI score) mediate the relationship between nasal congestion severity (VAS score) and anxiety levels (global GAD-7 score). The analysis adjusted for age and sex as a priori confounders. The results are presented in Table 6. The total effect of nasal congestion on anxiety was significant (β = 0.524, P < 0.001). The direct effect of nasal congestion on anxiety, after accounting for the mediator (sleep disorders), remained significant but smaller (β = 0.172, P = 0.012), accounting for 32.80% of the total effect. The indirect effect through the mediator (nasal congestion, sleep disorder, anxiety) was significant (β = 0.352, P < 0.001; 95%CI: 0.259-0.452), accounting for 67.20% of the total effect. This indicates that sleep disorders play a significant partial mediating role in the observed association between nasal congestion and anxiety in patients with AR.
Table 6 Mediation effect of sleep disorders between nasal congestion and anxiety in patients with allergic rhinitis.
This retrospective study explored interrelationships among nasal congestion severity, sleep disorders, and AR patients. Findings show consistent patterns of greater impairment in sleep quality, anxiety, and quality of life with more severe nasal obstruction. Statistical mediation analysis suggests sleep disturbance accounts for a substantial portion of the observed association between nasal congestion and anxiety. Given the cross-sectional design, all mediation findings are statistical and do not imply causality. This discussion interprets findings within existing literature, explores mechanisms, acknowledges limitations, and suggests future directions.
Consistent with prior evidence, our data show that patients with more SNC experience poorer sleep quality than those with moderate congestion. This was reflected in higher global PSQI scores and across multiple domains including prolonged sleep latency, reduced sleep duration, and increased daytime dysfunction[18]. The severe congestion group also reported more nocturnal awakenings due to nasal blockage, mouth breathing, and unrefreshing sleep. These observations align with reviews establishing that sleep disorders are highly prevalent in AR, often forming a vicious cycle where nasal symptoms disrupt sleep and poor sleep exacerbates symptom perception. The pathophysiology is multifactorial. The persistence of nasal congestion in AR is underpinned by complex inflammatory and structural changes, as demonstrated in a recent rat model where benzo(a)pyrene induced mucus secretion and tissue remodeling[6]. Mechanical obstruction from mucosal edema and increased nasal resistance can force mouth breathing, leading to oropharyngeal dryness, snoring, and sleep fragmentation[19]. The systemic inflammatory response in AR, involving cytokines such as interleukin (IL)-4 and IL-13, may influence central nervous system pathways regulating sleep-wake cycles[20,21]. The bidirectional nature of this relationship is underscored by evidence suggesting that sleep deprivation itself can amplify pro-inflammatory responses, potentially worsening AR symptoms[22].
Our analysis further demonstrates that heightened nasal congestion is associated with elevated anxiety scores and a greater proportion of patients meeting the threshold for clinically relevant anxiety. This is congruent with prior reviews indicating that a majority of studies report a positive association between allergic conditions and anxiety syndromes. For instance, large-scale claims data analyses have found odds of anxiety diagnoses to be higher in individuals with AR compared to controls[23]. The deterioration in disease-specific quality of life observed in our study, particularly within the psychological well-being dimension, underscores the holistic burden of severe AR[24]. It extends beyond physical symptoms to impair emotional state and daily functioning, a concept well-recognized in the literature[25]. The link between AR and anxiety may be partially direct, mediated by shared immunological pathways. Systemic inflammation can cross the blood-brain barrier and modulate neural circuits involved in fear and anxiety[26]. Additionally, the chronic, unpredictable, and intrusive nature of AR symptoms like persistent nasal congestion can serve as a constant stressor, contributing to a state of heightened vigilance and worry[27].
The most salient finding of this study is the statistical identification of sleep disturbance as a statistical mediator in this cross-sectional dataset in the pathway linking nasal congestion to anxiety[26]. This mediation model accounted for a considerable proportion of the total association, suggesting that a substantial part of the anxiety burden in AR patients with severe nasal obstruction may be statistically attributable to the detrimental effects of poor sleep[28]. This finding synthesizes the previously discussed pairwise relationships into a more integrated model[29]. Deeper mechanistic interpretation may involve central regulators of allergic inflammation; for example, molecules like CLC identified in bioinformatics analyses could be future targets for understanding how inflammation affects sleep and mood.
Several interconnected mechanisms may explain this statistical mediation. First, sleep fragmentation leads to impaired emotional regulation. Research in OSA has shown that poor sleep quality diminishes adaptive strategies (cognitive reappraisal) and increases maladaptive ones (expressive suppression), elevating anxiety. Similar mechanisms likely operate in AR-related sleep disruption[28]. Second, chronic sleep interruption may lead to hyperactivation of the amygdala (the brain’s fear center) and altered prefrontal cortex function, creating a neurobiological substrate prone to anxiety[29,30]. Third, both sleep deprivation and anxiety can be fueled by a common pro-inflammatory state, synergistically harming mental health[31,32]. Thus, SNC likely shows a statistical association with anxiety through a dual pathway: Direct psychophysiological stress and an indirect route via the statistically associated pathway of poor sleep.
Several limitations must be acknowledged. First, the retrospective cross-sectional design precludes causality inference; temporal sequence requires prospective validation. Secondly, the reliance on subjective, self-reported questionnaires may introduce the possibility of recall bias and same-source variance. future studies should incorporate objective measures such as rhinomanometry for nasal patency and actigraphy for sleep. Third, single-center design limits generalizability. Fourth, reverse causation is possible: Anxiety can impair sleep and heighten subjective nasal congestion perception. Fifth, our mediation model is one of many possible; shared etiologies such as a common neuroinflammatory process cannot be ruled out. Given the high prevalence of snoring and mouth breathing in our SNC group, which overlaps with OSA phenotypes, future studies should incorporate objective sleep assessments such as polysomnography to distinguish AR-related sleep disruption from undiagnosed sleep-disordered breathing. Recent studies on OSA and nasal continuous positive airway pressure therapy have shown that nasal obstruction and mouth breathing are common in patients with sleep-disordered breathing, and such overlap may confound the relationship between AR and sleep disturbance[33]. Unmeasured confounders (socioeconomic status, comorbidities, medications) could also influence results. Finally, nasal congestion may affect anxiety through other unmeasured pathways (e.g., direct systemic inflammation, psychological distress) not captured in our model. Future research should aim to address these limitations. Prospective cohort studies tracking patients over time are essential to establish temporal relationships and causal links.
CONCLUSION
In conclusion, this study provides cross-sectional clinical evidence supporting a model in which sleep disorders serve as a statistically significant intermediary factor between the severity of nasal congestion and anxiety symptoms in patients with AR. These findings underscore that AR, particularly when characterized by significant nasal obstruction, is not merely a local nasal disease but a condition with measured systemic associations affecting sleep and mental health. Our findings generate the hypothesis that a holistic management approach that actively screens for and addresses sleep disturbances, alongside standard allergy care, may be crucial for alleviating the full spectrum of AR-related burden and improving patient well-being. Prospective studies are needed to test this hypothesis.
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