Abstract
Background
The association between allergic rhinitis (AR) and behaviour problems (BPs) is still controversy. Furthermore, potential critical mediating role of sleep disturbance (SD) in their association has not been explored.
Methods
A total of 18,316 children aged 6 to 12 (mean age 7.89 years, male: 53.1%) were recruited from 34 primary schools from Shanghai, China. Demographic information, medical history, Children’s Sleep Habits Questionnaire (CSHQ), and Conners’ Parent Rating Scale (CPRS) were reported or scored by guardians via online survey. Logistic regression models with adjustment were employed to investigate the association between self-reported AR and BPs. Reproducible mediation analyses were used to explore the mediation effect of SD.
Results
The prevalence of AR, SD and any BP was 32.9%, 23.3% and 18.0%, respectively. Adjusted odds ratios (ORs) for BPs were significantly higher in children with AR compared to those without (all p < 0.001): for conduct problems the OR was 1.77 (95% CI 1.54–2.03); learning problems 1.67 (1.48–1.89); psychosomatic problems 1.82 (1.56–2.12); impulsive-hyperactive 1.68 (1.50–1.88); anxiety 1.36 (1.19–1.55); and hyperactivity 1.67 (1.49–1.88). Mediation analysis indicated that SD mediated the association between AR and BPs, with mediation proportions ranging from 32.6% to 64.1% (all p < 0.001), among which daytime sleepiness and sleep disordered breathing contributed most.
Conclusions and Relevance
Children with AR have higher odds of presenting BPs, and SD significantly mediates these associations. These results highlight the importance of proper screening and management of SD and BPs in urban children with AR.
Trial Registration
registration name (Effect of OSAHS on cognitive behavioural dysfunction in school-aged children: a large-scale prospective cohort study); registration number (ChiCTR1800014488); URL of the registry (https://www.chictr.org.cn/showproj.html?proj=24763).
Keywords: Allergic rhinitis, behaviour problems, sleep disturbance, mediation effect
Introduction
Behaviour problems (BPs) are leading causes of global disease burden in children and adolescents, which refer to a range of externalizing or internalizing behaviours that are developmentally inappropriate and interfere with learning and social interactions [1, 2]. BPs in children deserve particular attention as they portend a range of mental disorders, including attention deficit hyperactivity disorder (ADHD) and anxiety, as well as high-risk behaviours such as substance use, self-harm, and violence, the effects of which persist and have serious implications throughout life-course [2]. Childhood period is deemed as an optimal timeframe for the early intervention of BPs [2, 3]. It is therefore of great importance to identify modifiable risk factors for BPs in this period with the objective to promote timely and effective prevention and intervention strategies.
Allergic rhinitis (AR) is a highly prevalent atopic disease among children, with an estimated global self-reported prevalence of 19.93% [4]. In China, the self-reported prevalence rates vary significantly across different regions, ranging from 18.1% to 49.7% [4]. Nasal symptoms (itch and congestion) and inflammatory response evoked by AR have the potential to disrupt both physical and emotional functioning, and are likely to contribute to the emergence of BPs [5–7]. However, clinical evidence linking AR to BPs remains indirect and inconsistent [8, 9]. Supporting evidence showed that allergy nasal symptoms correlated with conduct problems (an externalizing BP) in children aged 2–6 years [10], and children or adolescents with AR are more prone to have a diagnosis of ADHD—a mental disorder characterized by significant BPs [11–14]. In contrast, others reported that once covariates such as parental smoking or asthma are accounted for, the link between AR and ADHD becomes insignificant [15–18]. Several meta-analyses and Mendelian randomization studies also failed to report a significant relationship between AR and ADHD [9, 19, 20]. These divergent findings underscore the necessity of further exploring the association between AR and BPs in large community samples, with standardized instrument designed for the assessment of BPs while accounting for essential covariates.
Furthermore, a pivotal question that previous research has not addressed is the role of sleep in the association between AR and BPs. Previous studies suggested a complex interplay among AR, sleep disturbance (SD), and BPs. SD is a well-recognized risk factor for BPs [21–23], and AR has emerged as an important risk factor for SD in children, especially sleep disordered breathing [24, 25]. Therefore, evidence implies a possible critical mediating role of SD in linking AR to BPs. However, the mediating effect has not been examined. The findings are expected to deepen the understanding of the relationships among AR, SD, and BPs, and provide valuable insights for the prevention and management of BPs in children with AR.
Employing large community samples, this cross-sectional study addresses these issues with the primary objectives of (1) examining the association between AR with BPs in children aged 6 to 12 years; and (2) elucidating the mediation effect of SD on the association between AR and BPs.
Methods
Study population
This study recruited urban participants from Xuhui District, Shanghai, China. All primary school students aged 6 to 12 from Xuhui District were selected using the cluster sampling method. Invitation letters were sent to the administrative offices of all 47 primary schools in this district, of which 13 schools declined to participate. Consequently, the initial sample comprised 26,827 registered primary school students from 34 schools. From September to December 2019, informed consent and an online questionnaire with a login code was distributed by class head teachers to the guardians of each student. A total of 19,033 guardians consented to participate and completed the online survey (a consent rate of 71.0%). Demographic information, medical history, Children’s Sleep Habits Questionnaire (CSHQ), and Conners’ Parent Rating Scale (CPRS) were reported or scored by guardians via online survey. Anthropometry information, including height and weight measured within three months, was obtained from the physical examination database of Shanghai Education Committee. Exclusion criteria included missing data on AR history, CSHQ, or CPRS. A total of 717 participants met the exclusion criteria, leaving data from 18,316 participants valid for inclusion in the study.
This study was conducted in accordance with the Declaration of Helsinki. The protocol was reviewed and approved by the Institutional Review Board of Shanghai Sixth People’s Hospital (Ethical Approval No. 2018-008), and the study was reported in accordance with the Strengthening the Reporting of Observational studies in Epidemiology reporting guideline (Registration No. ChiCTR1800014488). All guardians of children who participated gave written informed consent at the beginning of the online survey.
Allergy rhinitis and sleep disturbance
The medical history of AR was gathered through the online questionnaire. Guardians were asked, ‘Has your child ever been diagnosed with allergic rhinitis by a physician?’ If the response was affirmative, additional information regarding treatment was collected by asking, ‘Has the allergic rhinitis ever been treated?’ and ‘What treatment methods were used for allergic rhinitis?’
SDs were evaluated using the Chinese version of CSHQ (35 items), an extensively utilized instrument for identifying SDs in children aged 4 to 10 [26]. The CSHQ comprises 35 items, and a total score exceeding 48 was indicative of overall SD in Chinese population [23]. Eight subscales of the CSHQ, encompassing bedtime resistance, sleep onset delay, sleep duration, sleep anxiety, night waking, parasomnias, sleep disordered breathing and daytime sleepiness, were also analyzed. Owing to the lack of normative subscale values for the targeted age range for Chinese, scores surpassing two standard deviations above the population mean were indicative of clinically pertinent SDs, as described [23]. Furthermore, given the CSHQ’s limitations for children over 10 years, a sensitivity analysis excluding this age group (n = 176) was executed to ascertain the robustness of the findings.
Behaviour problems
BPs were assessed using the CPRS (48 items), a comprehensive and standardized instrument designed for the assessment of BPs in children aged 3 to 17. The scale includes 48 items distributed across six subscales: conduct problems, learning problems, psychosomatic problems, impulsive-hyperactive, anxiety, and hyperactivity index. Each item is scored from 0 to 3, with higher scores reflecting more pronounced behavioural issues. Raw scores were normalized to z-scores based on age- and sex-specific norms derived from published community control data for China [27], with a z-score exceeding 2 denoting a BP of clinical significance, as described [28].
Covariates
The covariates included sex, age, body mass index (BMI), educational levels of both parents, current parental ages, siblings, nonparental primary caregiver, household smoking exposure, and a self-reported history of low birth weight, tonsillar or adenoidal hypertrophy, and asthma. All these variables were incorporated into the minimally sufficient adjustment set, as shown in Figure S1.
Statistical analysis
Data analysis was performed using R (Version 4.0.4). Continuous variables were presented as means with standard deviations, while categorical variables were summarized using frequencies and percentages. Group differences were evaluated using Student’s t-test or Wilcoxon rank-sum test for continuous variables, and the Chi-square test for categorical variables. Unadjusted and adjusted logistic regression models were employed to investigate the associations between AR, SD and BP, with the estimation of odds ratios (ORs) and 95% confidence intervals (CIs). Interaction effect was assessed by incorporating interaction terms into the regression models. For mediation analysis, imputation with median values was performed for samples with complete CPRS data. Mediator roles were explored using a causal counterfactual framework, with the application of the g-formula method with adjustment for covariates [29]. Nonparametric bootstrapping with 1,000 replications facilitated the estimation of 95% CIs and p-values. Sensitivity analysis was applied to testify the robustness of the results. Statistical significance was set at a two-tailed p-value of less than 0.05 and Bonferroni correction was applied for multiple testing.
Results
Demographics of participants
The study comprised 18,316 children with a mean age of 7.89 ± 1.42 years and a mean body mass index (BMI) of 17.21 ± 3.03 kg/m2; of these, 9,724 (53.1%) were boys. As detailed in Table 1, the observed prevalence of self-reported AR and overall SD were 32.9% (n = 6,026) and 23.3% (n = 4,266), respectively; and 18.0% of the participants (n = 3,305) exhibited any type of BP. Children with self-reported AR had a higher prevalence of overall SD (29.3% vs. 20.3%) and any BP (22.5% vs. 15.9%) compared to their non-AR counterparts (both p < 0.001). Similar trend was observed for each type of SD and BP, as detailed in Table 1. Moreover, boys and children with a history of asthma were more frequently associated with AR, whereas children with AR had a lower likelihood of having siblings (Table 1).
Table 1.
Characteristics of the participants.
| All (n = 18316) | Without AR (n = 12290) | With AR (n = 6026) | p | |
|---|---|---|---|---|
| Age, year | 7.89 ± 1.42 | 7.85 ± 1.42 | 7.95 ± 1.41 | 0.025 |
| Boy, % | 9724 (53.1%) | 6072 (49.4%) | 3652 (60.6%) | <0.001 |
| BMI, kg/m2 | 17.2 ± 3.03 | 17.2 ± 3.03 | 17.3 ± 3.04 | 0.052 |
| BMI z-score | 0.56 ± 1.40 | 0.54 ± 1.33 | 0.58 ± 1.39 | 0.083 |
| Siblings, % | 5854 (32.0%) | 4151 (33.8%) | 1703 (28.3%) | <0.001 |
| Nonparental primary caregiver, % | 1325 (7.2%) | 896 (7.3%) | 427 (7.1%) | 0.605 |
| Household Smoker, % | 5449 (29.7%) | 3643 (29.6%) | 1806 (30.0%) | 0.655 |
| Mother current age, year | 37.6 ± 3.84 | 37.5 ± 3.96 | 37.7 ± 3.59 | <0.001 |
| Father current age, year | 39.9 ± 4.90 | 39.8 ± 5.00 | 40.0 ± 4.69 | 0.038 |
| Maternal educational level | <0.001 | |||
| High school or below, % | 2909 (15.9%) | 1890 (15.4%) | 1019 (17.0%) | |
| Junior college, % | 4897 (26.8%) | 3444 (28.1%) | 1453 (24.2%) | |
| Graduate, % | 9542 (52.3%) | 6151 (50.3%) | 3389 (56.4%) | |
| Postgraduate, % | 894 (4.9%) | 749 (6.1%) | 145 (2.4%) | |
| Unknown, % | 74 (0.40%) | 54 (0.43%) | 20 (0.33%) | |
| Father educational level | <0.001 | |||
| High school or below, % | 4041 (22.3%) | 2666 (21.9%) | 1375 (23.0%) | |
| Junior college, % | 4713 (26.0%) | 3312 (27.2%) | 1401 (23.4%) | |
| Graduate, % | 8724 (48.1%) | 5631 (46.2%) | 3093 (51.7%) | |
| Postgraduate, % | 678 (3.7%) | 567 (4.7%) | 111 (1.9%) | |
| Unknown, % | 160 (0.87%) | 114 (0.93%) | 46 (0.76%) | |
| Tonsillar or adenoidal hypertrophy, % | 2423 (13.2%) | 1070 (8.7%) | 1353 (22.5%) | <0.001 |
| AR, % | 6026 (32.9%) | -- | 6026 (100%) | -- |
| AR treatment, % | 5238 (28.6%) | -- | 5238 (86.9%) | -- |
| Asthma, % | 1367 (7.5%) | 426 (3.5%) | 941 (15.6%) | <0.001 |
| CSHQ total score | 44.03 ± 6.62 | 43.44 ± 6.50 | 45.2 ± 6.69 | <0.001 |
| Overall SD, % | 4266 (23.3%) | 2500 (20.3%) | 1766 (29.3%) | <0.001 |
| Bedtime resistance, % | 451 (2.5%) | 287 (2.3%) | 164 (2.7%) | 0.125 |
| Sleep onset delay, % | 756 (4.1%) | 485 (3.9%) | 271 (4.5%) | 0.085 |
| Sleep duration, % | 313 (1.7%) | 163 (1.3%) | 150 (2.5%) | <0.001 |
| Sleep anxiety, % | 418 (2.3%) | 241 (2.0%) | 177 (2.9%) | <0.001 |
| Night wakings, % | 575 (3.1%) | 341 (2.8%) | 234 (3.9%) | <0.001 |
| Parasomnias, % | 799 (4.4%) | 478 (3.9%) | 321 (5.3%) | <0.001 |
| Sleep-disordered breathing, % | 533 (2.9%) | 242 (2.0%) | 291 (4.8%) | <0.001 |
| Daytime sleepiness, % | 578 (3.2%) | 311 (2.5%) | 267 (4.4%) | <0.001 |
| Any behaviour problem, % | 3305 (18.0%) | 1949 (15.9%) | 1356 (22.5%) | <0.001 |
| Conduct problems, % | 968 (5.3%) | 524 (4.3%) | 444 (7.4%) | <0.001 |
| Learning problems, % | 1262 (6.9%) | 699 (5.7%) | 563 (9.3%) | <0.001 |
| Psychosomatic problems, % | 776 (4.2%) | 410 (3.3%) | 366 (6.1%) | <0.001 |
| Impulsive-hyperactive, % | 1492 (8.1%) | 824 (6.7%) | 668 (11.1%) | <0.001 |
| Anxiety, % | 1190 (6.5%) | 746 (6.1%) | 444 (7.4%) | <0.001 |
| Hyperactivity, % | 1384 (7.6%) | 767 (6.2%) | 617 (10.2%) | <0.001 |
AR = allergy rhinitis; SD = sleep disturbance; BMI = body mass index; CSHQ = Children’s Sleep Habits Questionnaire.
Missing values: A total of 60 values were missing for BMI and BMI z-score; 211 values missing for mother current age; 254 values missing for father current age; 74 missing values for maternal educational level; 160 values missing for father educational level.
Association between allergic rhinitis and behaviour problems
Table 2 reported unadjusted and adjusted ORs of the association between AR with BPs. After adjusted for covariates, children with AR showed significantly elevated odds of exhibiting BPs. As detailed in Table 2 (Model 2), the adjusted ORs and 95% CIs associated with AR (all p < 0.001) were as follows: conduct problems, OR = 1.77 (95% CI: 1.54–2.03); learning problems, OR = 1.67 (95% CI: 1.48–1.89); psychosomatic problems, OR = 1.82 (95% CI: 1.56–2.12); impulsive-hyperactive behaviour, OR = 1.68 (95% CI: 1.50–1.88); anxiety, OR = 1.36 (95% CI: 1.19–1.55); and hyperactivity, OR = 1.67 (95% CI: 1.49–1.88). After further adjustment for overall SD (Model 3 in Table 2), statistically significant but reduced ORs were also observed for BPs, expect for anxiety, suggesting that SD may partially or fully mediates the association between AR and BPs.
Table 2.
Odds ratios of presenting behaviour problems for children aged 6 to 12 with allergy rhinitis.
| OR (95% CI) | Conduct problems | Learning problems | Psychosomatic problems | Impulsive-hyperactive | Anxiety | Hyperactivity |
|---|---|---|---|---|---|---|
| AR | ||||||
| Model 1 | 1.78 (1.57–2.04) p < 0.001 |
1.71 (1.52–1.92) p < 0.001 |
1.87 (1.62–2.16) p < 0.001 |
1.73 (1.26–1.93) p < 0.001 |
1.23 (1.09–1.39) p < 0.001 |
1.71 (1.52–1.91) p < 0.001 |
| Model 2 | 1.77 (1.54–2.03) p < 0.001 |
1.67 (1.48–1.89) p < 0.001 |
1.82 (1.56–2.12) p < 0.001 |
1.68 (1.50–1.88) p < 0.001 |
1.36 (1.19–1.55) p < 0.001 |
1.67 (1.49–1.88) p < 0.001 |
| Model 3 | 1.46 (1.27–1.67) p < 0.001 |
1.41 (1.24–1.60) p < 0.001 |
1.51 (1.30–1.76) p < 0.001 |
1.46 (1.30–1.64) p < 0.001 |
1.15 (1.01–1.32) p = 0.037 |
1.41 (1.25–1.58) p < 0.001 |
AR = allergy rhinitis; OR = odds ratio; CI = confidence interval.
Model 1: Unadjusted.
Model 2: Adjusted for sex, age, body mass index z-score, educational levels of both parents, parental ages, siblings, nonparental primary caregiver, household smoking exposure and asthma.
Model 3: Adjusted for covariates in model 2 and overall sleep disturbance.
Mediating effect of sleep disturbance on the association between allergic rhinitis and behaviour problems
As showed in Figure 1, AR was significantly associated to increased odds of overall SD with an adjusted OR of 1.57 (95% CI 1.46–1.70), p < 0.001. Specifically, AR showed significant association with sleep duration, sleep anxiety, night wakings, parasomnias, sleep-disordered breathing and daytime sleepiness (all P < =0.001), but not with bedtime resistance and sleep onset delay (Figure 1). Table 3 showed the results of the mediation analysis. As shown, overall SD significantly mediated the association between AR and BPs. The proportions of the mediation effect by overall SD and 95% CIs were as follows (all p < 0.001): conduct problems, 42.2% (32.7%–53.6%); learning problems, 40.5% (31.7%–51.4%); psychosomatic problems, 38.9% (30.6%–49.8%); impulsive-hyperactive, 32.6% (28.1%–44.8%); anxiety, 64.1% (48.5%–100.4%); and hyperactivity, 43.6% (34.4%–52.7%). Notably, daytime sleepiness and sleep disordered breathing mediated the most among all types of SD (Figure S2). Lastly, interaction analyses revealed no significant interplay between AR with overall SD in relationships with BPs (all p for interaction > 0.05), as shown in Table S1 in Supplementary.
Figure 1.
Adjusted odds ratios of presenting sleep disturbance for children aged 6 to 12 with allergy rhinitis. This figure illustrates the significant association between allergic rhinitis with overall and various types of sleep disturbances in children aged 6 to 12 years. As depicted, AR is significantly associated to increased odds of overall sleep disturbance, sleep duration, sleep anxiety, night wakings, parasomnias, sleep disordered breathing and daytime sleepiness, but not with bedtime resistance and sleep onset delay. Adjusted covariates including sex, age, body mass index z-score, educational levels of both parents, parental ages, siblings, nonparental primary caregiver, household smoking exposure and a history of asthma. OR = odds ratio; CI = confidence interval.
Table 3.
Mediation effect of sleep disturbance in the relationships between allergy rhinitis and behaviour problems.
| Adjusted ORs and 95% CIs | Conduct problems | Learning problems | Psychosomatic problems | Impulsive-hyperactive | Anxiety | Hyperactivity |
|---|---|---|---|---|---|---|
| Total Effect | 1.73 (1.51–1.99) | 1.62 (1.46–1.83) | 1.79 (1.51–2.05) | 1.63 (1.47–1.87) | 1.30 (1.17–1.51) | 1.66 (1.46–1.82) |
| Direct effect of AR | 1.42 (1.25–1.64) | 1.38 (1.22–1.54) | 1.48 (1.28–1.71) | 1.43 (1.26–1.58) | 1.11 (0.99–1.25) | 1.37 (1.22–1.51) |
| Indirect effect via SD | 1.22 (1.17–1.27) | 1.17 (1.14–1.23) | 1.20 (1.16–1.24) | 1.14 (1.13–1.21) | 1.17 (1.15–1.24) | 1.21 (1.15–1.24) |
| Proportion mediated | 42.2% (32.7%–53.6%) |
40.5% (31.7%–51.4%) |
38.9% (30.6%–49.8%) |
32.6% (28.1%–44.8%) |
64.1% (48.5%–100.4%) |
43.6% (34.4%–52.7%) |
| P value for mediation | p < 0.001 | p < 0.001 | p < 0.001 | p < 0.001 | p < 0.001 | p < 0.001 |
Mediator effect was explored using a causal counterfactual framework, with the application of the g-formula method with adjustment for covariates including sex, age, body mass index z-score, educational levels of both parents, parental ages, siblings, nonparental primary caregiver, household smoking exposure and asthma. Nonparametric bootstrapping with 1000 replications facilitated the estimation of 95% CIs and p-values. P-values for proportion mediated were given. OR = odds ratio; CI = confidence interval; AR = allergy rhinitis; SD = sleep disturbance.
Sensitivity analysis
After further adjusted for a history of tonsillar or adenoidal hypertrophy, the association between AR, overall SD, and BPs remained consistent (Tables S2 and S3 in Supplementary); and overall SD significantly mediated the association between AR and BPs, with mediation proportions ranging from 33.7% to 64.8% (Table S4). After exclusion of participants older than 10 years (n = 176), or those without AR treatment history (n = 788), similar results were observed (Tables S5–S7 and S8–S10, respectively).
Discussion
This cross-sectional study aimed to interpret the complex relationships between AR, SD, and BPs in children. Utilizing a large urban community sample, findings revealed that self-reported AR is associated with increased odds of exhibiting BPs in children aged 6 to 12 years. Moreover, mediation analyses indicated that overall SD significantly mediate these relationships, among which daytime sleepiness and sleep disordered breathing contributed most.
Childhood BPs are indicators for a range of mental disorders and high-risk behaviours [2]. Clinical early intervention can improve childhood BPs, but its availability is limited by multiple barriers such as high cost, time burden and the shortage of specialized physicians [3]. Therefore, identifying modifiable risk factors is of great importance for the prevention and intervention of BPs. Previous studies have found that childhood atopic diseases are closely associated with BPs, suggesting that AR, a prevalent atopic disease in children, may be a significant treatable risk factor for BPs. However, compared to other atopic diseases like asthma or dermatitis, the relationships between AR and BPs have been less studied, with inconsistent results reported. Longitudinal data from Qu et al. suggested that children with a history of AR are more likely to be diagnosed with ADHD and autism spectrum disorder, two mental disorders characterized by exhibiting BPs [13]. However, nonsignificant association between AR and ADHD symptom was also reported in kindergarten children, school-aged children or adolescents, after adjustment for other atopic diseases or parental smoking [15–18]. In consequence, there has been a lack of direct and consistent evidence linking AR to BPs. In this study, we evaluated the associations between self-reported AR and the presence of BPs as assessed by the CPRS, a well-recognized tool for multimodal assessment of children’s BPs [30]. After adjusting for essential covariates, our results provide direct evidence supporting significant associations between AR and BPs in children aged 6 to 12 years (Table 2).
Interestingly, 86.9% of children with AR in the current study reported a history of treatment. Those with a treatment history were also closely associated with higher odds of BPs (Table S5). One possible explanation is that children may be difficult to adhere to AR treatment in a long-term, leading to unrelieved damage. Evidence supports this notion, by showing that the natural course of AR prone to persistent, with approximately 75% of children with pollen-AR showed persistent disease for at least 20 years [31]; and a noncompliance rate between 30% and 50% was reported for AR in long-term regimes, which was associated with poor health outcomes [32, 33]. Another explanation could be a shared pathogenic basis for AR and BPs. For instance, previous studies have reported several common genetic bases between allergic diseases and mental disorders with BPs [34–36]. Furthermore, exposures during pregnancy (such as immune disturbances, drinking or psychological stress) have also been associated with the etiology of both atopic diseases and BPs in offspring [37–39]. Unfortunately, our study could not address treatment effectiveness, compliance and common pathogenic factors, which need to be considered in further study. Additionally, conflicting evidence suggested that montelukast, a commonly used anti-allergic drug for children, may have side effects that induce BPs [40, 41]. To address this, we excluded children with a history of oral allergic drug use, and no significant changes were found (Table S11 and S12). Further randomized controlled trials are needed to determine whether appropriate and long-term treatment can mitigate BPs in children with AR.
Sleep is essential for children’s health, and SD is a recognized risk factor for BPs [21]. AR is an emerging risk factor for SD in children [24, 25]. In this study, our results reinforced the significant association by demonstrating that self-reported AR was linked to increased odds of overall SD in children aged 6 to 12 years, as well as SD types specifying reduced sleep duration, sleep anxiety, night wakings, parasomnias, sleep-disordered breathing, and daytime sleepiness. Our findings align with previous studies, although there are some inconsistencies. For instance, a recent meta-analysis that included both adults and children found significant association between AR and overall sleep disturbance scores, insomnia, sleep-disordered breathing, and daytime sleepiness [23]. However, no significant difference in sleep duration between AR and the control groups were observed [23]. Additionally, a study of 167 children aged 4 to 10 years reported negative relationships between AR and sleep duration, sleep anxiety, and night wakings [42]. These discrepancies might be due to variations in the age of the study populations and different assessment methods used. Future research employing standardized diagnoses of AR and SD is necessary to further validate these associations. Furthermore, our results showed that over one-third of the associations between AR and BPs were mediated by SD (Table 3), aligning with observations in children with other mental health related conditions. For example, Sherrey et al. found that sleep plays a significant mediating role in the relationship between AR and psychological distress in 1,449 children aged 6 to 10 years [43]. In a large-scale study involving 400,382 adolescents, Noh et al. also demonstrated that poor sleep mediates the association between school accidents and allergic diseases, including AR [44]. These findings underscore the necessity for greater attention to the assessment and management of sleep in children with AR. Implementing a multidisciplinary and long-term management approach, incorporating expertise from otorhinolaryngology, sleep medicine, immunology, and psychiatry, may mitigate the long-term impact of AR [22].
Nasal symptoms, including itching and nasal obstruction, are the potential mechanisms linking AR with SD and BPs [10, 24, 25]. Additionally, neuroinflammation induced by allergy and SD could further elucidate the associations observed in this study [22]. Neuroinflammation has been recognized as a key driver of BPs [7, 45]. Recent experimental and clinical research demonstrated that both AR and SD are associated with dysregulation of inflammatory pathways in the central nervous system, contributing to behavioural disturbances [46, 47]. Furthermore, gut microbiota dysbiosis associated with AR and SD is another potential mechanism that warrants further investigation [48–50].
Several limitations should be addressed when interpreting the results of this study. First, due to the nature of large community-based study, the diagnosis and treatment history of AR were not assessed via formal medical records, and SD and BPs were not assessed with polysomnography or face-to-face clinical interviews. This may cause misclassification bias, potentially leading to unreal associations. With the aim to mitigate this bias, detailed instructions for each questionnaire were provided and guardians could contact the researchers via phone or online when needed. Besides, strong associations remained consistent after sensitivity analysis, illustrated the robustness of the findings. Second, other potential covariates were not considered, such as genetic susceptibility, maternal exposures, family income and caregiver’s sleep and behaviour problems, and other atopic conditions including food allergy and atopic dermatitis. Third, as a cross-sectional study, causality could not be determined. Furthermore, AR was defined based on medical history, which does not allow for differentiation between current AR, specific AR episodes, and ever AR. Furthermore, the severity of allergic rhinitis was not assessed, preventing the evaluation of a dose–effect relationship. These limitations restrict this study to fully elucidate the relationships between AR with SD and BPs. Future studies employing longitudinal designs and more detailed AR assessments are necessary to address these limitations. Lastly, all participants were recruited from one district in Shanghai, which limits the generalizability of the results. Future studies using a stratified random sampling design would enhance the representativeness of the sample. Despite these limitations, our study demonstrated tight relationships among AR, SD and BPs with sufficiently large community sample and reliable data. The findings provide a basis for future longitudinal and interventional studies aiming to improve the clinical outcome of children with AR and BPs.
Conclusion
In conclusion, this community study provides evidence supporting significant associations between AR with BPs in urban children aged 6 to 12 years old. Furthermore, results showed that over one-third of these associations are mediated by SD, among which daytime sleepiness and sleep disordered breathing contributed most.
Supplementary Material
Acknowledgement
Shiyin Yang, Jiaxin Yang, and Jiawen Xu contributed equally to this work.
Funding Statement
This study was funded by the Ministry of Science and Technology of the People’s Republic of China (STI2030-Major Projects 2021ZD0201900); National Natural Science Foundation of China [82101205]; Innovation Program of Shanghai Municipal Education Commission [2017-01-07-00-02-E00047]; Shanghai Shen-Kang Hospital Management Center [SHDC2022CRS016B, SHDC2020CR2044B and SHDC2020CR3056B]; Shanghai Sixth People’s Hospital Clinical Research Project [YNTS202205 and X-4267].
Authors contributions
S.Y., J.Y., and J.X.: study execution, data collection, data analysis and manuscript preparation. Y.H., C.L. and H.Y.: data collection, data analysis and manuscript preparation. L.Z., L.S., H.X. and F.L.: data analysis, data interpretation and manuscript review. H.Y., S.Y., J.G: study design, data interpretation and manuscript review. Y.L: study design, study execution, data collection and analysis, manuscript preparation and review. All authors have approved the final manuscript as submitted and agreed to be accountable for all aspects of this work. All authors have read and agreed to the published version of the manuscript.
Conflicts of interest
No financial or non-financial benefits have been received or will be received from any party related directly or indirectly to the subject of this article.
Data availability
The data that support the findings of this study are available from Shanghai Sixth People’s Hospital affiliated to Shanghai Jiao Tong University School of Medicine. But restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Shanghai Sixth People’s Hospital affiliated to Shanghai Jiao Tong University School of Medicine.
Disclosure statement
No potential competing interest was reported by the authors.
Ethical approval
This study was conducted in accordance with the Declaration of Helsinki. The study protocol received approval from the Institutional Review Board of Shanghai Sixth People’s Hospital (Approval No. 2018-008). Written informed consent was obtained from the guardians of all participating children
References
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available from Shanghai Sixth People’s Hospital affiliated to Shanghai Jiao Tong University School of Medicine. But restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Shanghai Sixth People’s Hospital affiliated to Shanghai Jiao Tong University School of Medicine.