Abstract
Objectives
To investigate the sleep quality in children with allergic conjunctivitis (AC) and their parents.
Methods
Prospective, case-controlled study. Zhongshan Ophthalmic Center, a tertiary referral centre. Participants comprised 73 children aged 4–12 years with AC and their parents, and 81 healthy, age-matched children who served as controls and their parents. General information was recorded and ocular manifestations of children with AC were scored. Sleep quality of the children and parents were assessed using Children’s Sleep Habits Questionnaire (CSHQ) and Pittsburgh Sleep Quality Index (PSQI).
Results
Children with AC and their parents had reduced sleep quality (Children’s CSHQ: 48.3 ± 6.55 vs. 38.8 ± 4.63; Parental PSQI: 5.62 ± 2.12 vs. 3.40 ± 1.90, both p < 0.001) and significantly higher prevalence of poor sleep quality (CSHQ ≥ 41 in Children: 89.0% vs. 23.5%; PSQI > 7 in Parents: 18.5% vs. 1.23%, both p < 0.001). Children with AC scored worse on subcomponents of CSHQ including sleep onset delay, sleep duration, parasomnia, sleep-disordered breathing, and daytime sleepiness. Parents scored worse on subscores of PSQI including sleep duration, sleep disturbances, use of sleeping medication, and daytime sleepiness. Poor sleep quality in children with AC was associated with follicle formation (OR:3.95; 95% CI: 1.88–8.31, p < 0.001) and keratitis (OR:6.03; 95% CI: 1.29–28.3, p = 0.028). Parental poor sleep quality was associated with follicle formation (OR:7.14; 95% CI: 2.06–24.8, p = 0.002) and keratitis (OR:4.49; 95% CI: 1.27–15.9, p = 0.020) in children.
Conclusions
AC has a negative association with sleep quality in children and their parents, especially in those children with severe follicle formation and keratitis.
State the details of Clinical Trials
Chictr.org.cn, https://www.chictr.org.cn/showproj.aspx?proj=43511, ChiCTR1900027486.
Statement of significance
Allergic conjunctivitis is a frequently encountered problem diagnosed and managed by ophthalmologists, paediatricians, allergists, and primary care physicians and has become a major public health issue. Sleep is crucial for learning and effective development in children. Our study discovered a strong association between these two conditions. This is the first study to evaluate the association of allergic conjunctivitis and sleep quality in children and their parents. This case-controlled study found that allergic conjunctivitis had a negative impact on sleep quality not only for children but also for their parents. The findings of this study suggest a multifaceted impact of AC with sleep quality; detailed assessment of sleep quality for improved care of paediatric patients with allergic conjunctivitis would be useful.
Subject terms: Conjunctival diseases, Paediatrics
Introduction
Sleep is an important determinant of health and quality of life [1, 2]. In particular, sleep is crucial for learning and effective development in children [3–5]. In recent years, sleep disorders have become one of the major health concerns globally [6, 7]. A variety of diseases, including eye diseases such as dry eye and primary glaucoma, have been found to potentially correlated with sleep disorders, which can in turn exacerbate the condition, creating a vicious cycle [8–12]. However, as for children, currently the association between eye diseases and sleep quality has been reported only in myopia [13–15].
Allergic conjunctivitis (AC), one of the most common eye diseases, is affecting 40% of the American population and 15–20% of the Japanese population [16–20]. AC tends to attack children more than adults [18]. The underlying mechanisms were hypersensitivity reactions, mainly type I and type IV, of the conjunctiva to allergens [21]. There are five types of AC including perennial allergic conjunctivitis (PAC), seasonal allergic conjunctivitis (SAC), vernal keratoconjunctivitis (VKC), atopic keratoconjunctivitis (AKC), and giant papillary conjunctivitis (GPC) [18, 22]. SAC/PAC are type I allergic reactions and accounts for 74–95% total AC [21]. VKC/AKC are a combination of both type I and type IV allergic reactions and are relatively more severe as they may involve the cornea. GPC is usually induced by foreign body reaction such as contact lens, filtering tubes, etc. [18]. AC is mainly characterised by itching, redness, and tearing of the eyes, and in severe cases it can cause visual impairment [18, 23–25].
AC tends to have a long and recurrent course [16, 17]. We speculated that chronic eye discomfort of AC especially itching may affect the sleep quality of the children, and the impact of chronic childhood illness also falls on the parents [26]. Herein, we for the first time, conducted a cross-sectional observational survey to assess if and how AC potentially disturbs the sleep quality of paediatric patients and if so, whether their parents are also involved. In this study, a verified Chinese version for sleep quality assessment in children and adults respectively were used, and the association between sleep quality impairment and potential confounders such as eye conditions were further analysed and discussed.
Methods
This prospective, case-controlled study was conducted at the cornea outpatient department of Zhongshan Ophthalmic Center from November 2019 through January 2020 in accordance with the tenets of the Helsinki Declaration of Human Studies and was approved by the Ethics Committee of Zhongshan Ophthalmic Center, Sun Yat-sen University (ChiCTR1900027486). We screened the notes of all children attending our clinic in advance to identify those who met the inclusion criteria. These children then were approached consecutively for inclusion in the study. For those who did not wish to take part, we denoted the reasons given, we addressed any questions before obtaining written consent and assent.
Inclusion and exclusion criteria
Children with AC aged younger than 12 years old and their parents were enroled. The diagnosis of AC was based on the AAO’s diagnostic criteria for allergic conjunctivitis [17, 25]. Exclusion criteria were: inability to communicate, allergic to fluorescein, any other ocular disorders except mild ametropia, any history of ocular surgery or trauma, history of other active allergic diseases in the past one year, any history of mental or sleep disorders or other systemic diseases, history of oral antiallergy pills such as glycocorticosteroids and antihistamines within 6 months. Healthy control children younger than 12 years and their parents were recruited from those receiving routine ophthalmic examination or refraction correction. Exclusion criteria of control were the same as those of AC group. As for parents, the questionnaire was intended for the primary caregiver (i.e., the caregiver that spends more time with the child). In case of equal parenting, either parent could be enroled. The exclusion criteria for parents of AC and normal control were a history of mental or sleep disorders or ocular and systemic diseases, and the recent experience of any major life-altering events. Participants in AC group were subdivided into VKC/AKC and SAC/ PAC subgroups due to the different underlying mechanisms. We enroled 80 children with AC and their parents and 85 healthy children and their parents who met the inclusion criteria, 7 children and their parents in the AC group and 4 children and their parents in the normal control refused to participate for time reason. The statistical analysis was performed for the remaining 73 children with AC and 81 healthy children and their parents (Fig. 1).
Fig. 1.
Flowchart showing enrolment, intervention, and analysis.
Ophthalmic Examination
A complete medical and ophthalmic history was collected from all participants. Children received slit-lamp examination, refraction and best-corrected visual acuity (BCVA) examination in both eyes. Conjunctival hyperaemia, papillary and follicle formation [17], corneal fluorescein staining (CFS) [27] and corneal pathologies [28] were graded as reported.
Sleep quality assessment
Chinese version of Children’s Sleep Habits Questionnaire (CSHQ) and Pittsburgh Sleep Quality Index (PSQI) of which the reliability and validity have been proven in Chinese population [10, 14, 29–32] were used to assess the sleep quality for children and their parents respectively in the present study. (Supplementary Files 1 and 2).
The CSHQ scale is originally designed for children aged between 4 and 12, which includes 33-item parent-reported questionnaire in 8 components: bedtime resistance, sleep onset delay, sleep duration, sleep anxiety, night waking, parasomnia, sleep-disordered breathing, and daytime sleepiness. The total score is the sum of the scores of the 33 items [33]. The PSQI has 18 items in 7 components, including subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction [34]. The higher score of CSHQ and PSQI indicates worse sleep quality. A total score of CSHQ ≥ 41 [33, 35, 36] and PSQI > 7 [34, 37] was considered as poor sleep quality in children and adults, respectively.
Statistical analysis
In view of retrospective data from Zhongshan Ophthalmic Center, the sample size was calculated based on the primary outcome, the Children’s CSHQ total score. Assuming the mean CSHQ scores of 45 in AC group, and 40 in healthy group with a common SD (standard deviation) of 10, a sample size of 73 children for each group was needed which will achieve 85% power, at a two-sided significance level of α = 0.05, using two-sample independent t test. The sample size was calculated using PASS, version 16.0 (NCSS Statistical Software).
For efficacy variables collected, only the data from the “worse” eye were included in the analyses. The “worse” eye was defined as the eye with the worse keratitis grade. If both eyes were comparable, the right eye was chosen. The normality of the continuous data was checked by Shapiro–Wilk normality test and histogram. We applied descriptive statistics throughout, reporting means and standard deviations (SDs) for normally distributed data or medians and interquartile ranges (IQRs) for data not normally distributed. BCVA was converted to logarithm of the minimum angle of resolution (logMAR) for analysis. The spherical equivalent (SE) of the refractive error was calculated as the spherical value plus half of the cylindrical (astigmatic) value. We compared the differences between the two groups by using independent samples t-test or rank-sum test. The homogeneity of variance was tested for two-sample t test. Univariable and multivariable liner regression for continuous sleep quality outcomes, and logistic regression model for binary outcomes were fitted to identify risk factors that were associated with influencing sleep quality scores/ poor sleep quality at enrolment. Because the data were unevenly distributed, in the univariable and multivariable analyses, we re-coded papillae, keratitis, bulbar conjunctival hyperaemia, etc., dichotomous variables based on the occurrent. As a small number of physiological follicles may appear in normal children’s lower eyelids, 0-mild was defined as normal and recorded as 0. In contrast, moderate-severe was defined as abnormal and recorded as one during re-coding. Because bulbar conjunctival congestion had a collinear relationship with palpebral conjunctival papillae and follicles and papillae had a collinear relationship with keratitis, multivariable linear regression, and logistic regression were not performed. All statistical analyses were performed using SPSS software V.25.0, with p < 0.05 being considered significant.
Results
Participants
A total of 73 children with AC and 81 healthy children were enroled with their parents. Geographic and clinical details are shown in Table 1. The ages were matched between two groups (children: 8.45 ± 2.15 vs. 8.59 ± 2.21 years, p = 0.690, parents: 36.6 ± 4.68 vs. 36.6 ± 5.44 years, p = 0.892). Male was more prevalent in the children in AC group than that in the control (61 [83.6%] of 73 vs. 32 [39.5%] of 81, p < 0.001). Sex and education background were matched in parents in the two groups. The AC group included 47 children diagnosed as PAC/SAC and 26 children diagnosed as VKC/AKC.
Table 1.
Demographic and clinical features of children and their parents.
| AC group | Control group | P | |
|---|---|---|---|
| (N = 73) | (N = 81) | ||
| Demographics | |||
| Children | |||
| Male sex, n (%) | 61 (83.6%) | 32 (39.5%)a | <0.0001b |
| Age (years), Mean (SD) | 8.45 (2.15) | 8.59 (2.21) | 0.690c |
| Disease duration (months), Median (IQR) | 12.0 (6.00–30.0) | – | |
| Previous treatment, n (%) | 52 (71.2%) | – | |
| Parents | |||
| Gender (Male), n (%) | 24 (32.9%) | 16 (19.8%) | 0.069b |
| Age (years), Mean (SD) | 36.6(4.68) | 36.6 (5.44) | 0.892c |
| Education background, n (%) | 0.333a | ||
| ≤high school | 32 (43.8%) | 26 (32.1%) | |
| ≥Junior college | 41 (56.2%) | 55 (67.9%) | |
| Clinical features of children | |||
| BCVA, logMar, Mean (SD) | −0.07 (0.08) | −0.06 (0.07) | 0.061d |
| SE, Mean (SD) | −0.51 (1.53) | −0.70 (1.45) | 0.432c |
| Bulbar conjunctiva hyperaemia, n (%) | <0.001a | ||
| None | 78 (96.3%) | 11 (15.1%) | |
| Mild | 3 (3.7%) | 44 (60.3%) | |
| Moderate | 0 | 11 (15.0%) | |
| Severe | 0 | 7 (9.6%) | |
| Follicle | <0.001a | ||
| None | 64 (79.0%) | 11 (15.1%) | |
| Mild | 17 (21.0%) | 30 (41.1%) | |
| Moderate | 0 | 22 (30.1%) | |
| Severe | 0 | 10 (13.7%) | |
| Papillae | <0.001a | ||
| None | 81 (100%) | 11 (15.07%) | |
| Mild | 0 | 37 (50.68%) | |
| Moderate | 0 | 15 (20.55%) | |
| Severe | 0 | 10 (13.70%) | |
| Keratitis grading | <0.001a | ||
| Grade 0 | 81 (100%) | 48 (65.75%) | |
| Grade 1 | 0 | 21 (28.77%) | |
| Grade 2 | 0 | 4 (5.48%) |
AC allergic conjunctivitis, BCVA best correct visual acuity, SE mean dioptric spherical equivalent, SD standard deviation, IQR interquartile range.
aFisher’s exact test.
bPearson’s chi-squared test.
ct test.
dMann–Whitney U test.
The mean BCVA and the median SE were comparable in the two groups (Table 1). The median (IQR) disease duration was 12.00 (6.00, 30.0) months, and 52 (71.2%) of 73 AC children had been treated previously. Detailed ocular signs are shown in Table 1.
Sleep quality
As shown in Table 2, children and their parents in the AC group had significantly reduced sleep quality than those in the control (CSHQ: 48.3 ± 6.55 vs. 38.8 ± 4.63, p < 0.001; PSQI: 5.62 ± 2.12 vs. 3.40 ± 1.90, p < 0.001). We further analysed and compared sleep quality scores between different AC subtypes but did not find significant difference between those with VKC/AKC and PAC/SAC in both children and parents.
Table 2.
Sleep quality of children and their parents.
| All | AC group | |||||
|---|---|---|---|---|---|---|
| AC group | Control group | Pa | PAC/SAC | VKC/AKC | Pb | |
| (N = 73) | (N = 81) | (N = 47) | (N = 26) | |||
| Children | ||||||
| Total sleep time (hours), Mean (SD) | 8.58 (1.63) | 8.65 (7.93) | 0.704c | 8.55 (1.45) | 8.62 (1.94) | 0.861c |
| Total score of CSHQ, Mean (SD) | 48.3 (6.55) | 38.8 (4.63) | <0.001c | 47.9 (6.48) | 49.0 (1.32) | 0.501c |
| Components of CSHQ, Median (IQR) | ||||||
| Bedtime resistance | 9.00 (7.00–12.0) | 6.00 (6.00–8.00) | <0.001d | 9.00 (7.00–13.0) | 8.50 (7.00–12.0) | 0.931d |
| Sleep onset delay | 1.00 (1.00–2.00) | 1.00 (1.00–1.00) | 0.001d | 1.00 (1.00–2.00) | 1.50 (1.00–3.00) | 0.219d |
| Sleep duration | 4.00 (4.00–6.00) | 3.00 (3.00–4.00) | <0.001d | 4.00 (4.00–6.00) | 4.00 (3.00–5.25) | 0.279d |
| Sleep anxiety | 3.00 (2.00–3.00) | 2.00 (2.00–3.00) | 0.003d | 3.00 (2.00–3.00) | 3.00 (2.00–3.00) | 0.627d |
| Night wakings | 3.00 (2.00–5.00) | 3.00 (2.00–3.00) | 0.216d | 3.00 (2.00–4.00) | 3.00 (2.00–4.00) | 0.493d |
| Parasomnias | 9.00 (9.00–10.0) | 7.00 (7.00-8.00) | <0.001d | 9.00 (9.00-11.0) | 10.0 (9.00–11.0) | 0.424d |
| Sleep-disordered breathing | 3.00 (3.00–4.00) | 3.00 (3.00–3.00) | 0.025d | 3.00 (3.00–4.00) | 3.00 (3.00–4.00) | 0.579d |
| Daytime sleepiness | 13.0 (10.0–16.0) | 10.0 (8.00-12.0) | <0.001d | 13.0 (10.0–15.0) | 14.0 (12.0–17.0) | 0.129d |
| Sleep disturbances (CSHQ score≥41), n (%) | 65 (89.0%) | 19 (23.5%) | <0.001e | 42 (89.4%) | 23 (88.5%) | 0.906e |
| Parents | ||||||
| Total sleep time (hours), Mean (SD) | 7.01 (0.84) | 7.01 (0.98) | 0.553a | 7.05 (0.77) | 6.93 (0.96) | 0.567c |
| Total CPSQI score, Mean (SD) | 5.62 (2.12) | 3.40 (1.90) | <0.001a | 5.30 (1.78) | 6.20 (2.56) | 0.084c |
| Components of CPSQI, Median (IQR) | ||||||
| Subjective sleep quality | 0.00 (0.00–1.00) | 1.00 (0.00–1.00) | 0.067b | 1.00 (0.00–1.00) | 1.00 (1.00–2.00) | 0.027d |
| Sleep latency | 1.00 (1.00–2.00) | 1.00 (0.00–1.00) | 0.025b | 1.00 (0.50-2.00) | 1.00 (1.00–2.00) | 0.096d |
| Sleep duration | 1.00 (0.00–1.00) | 1.00 (0.00–1.00) | 0.819b | 1.00 (0.00–1.00) | 1.00 (0.00–1.00) | 0.764d |
| Habitual sleep efficiency | 0.00 (0.00-0.00) | 0.00 (0.00-0.00) | 0.855b | 0.00 (0.00–0.00) | 0.00 (0.00-0.00) | 0.006d |
| Sleep disturbance | 1.00 (1.00–1.00) | 0.00 (0.00–1.00) | <0.001b | 1.00 (1.00–1.00) | 1.00 (1.00–1.00) | 0.676d |
| Sleep medication use | 1.00 (1.00–2.00) | 1.00 (0.00–1.00) | <0.001b | 0.00 (1.00–2.00) | 1.00 (0.00–2.00) | 0.220d |
| Daytime dysfunction | 1.00 (0.00–2.00) | 0.00 (0.00-0.00) | <0.001b | 1.00 (1.00–2.00) | 2.00 (1.00–2.00) | 0.154d |
| Sleep dysfunction, n (%) (CPSQI score>7) | 15 (18.52%) | 1 (1.23%) | <0.001f | 6 (12.77%) | 9 (39.13%) | 0.027f |
AC allergic conjunctivitis, PAC perennial allergic conjunctivitis, SAC seasonal allergic conjunctivitis, VKC vernal keratoconjunctivitis, AKC atopic keratoconjunctivitis, CSHQ Children’s Sleep Habits Questionnaire, PSQI Pittsburgh Sleep Quality Index, SD standard deviation, IQR interquartile range.
aAC vs. control.
bPAC/SAC vs. VKC/AKC.
ct test.
dMann–Whitney U test.
ePearson’s chi-squared test.
fFisher’s exact test.
Children with AC and their parents had significant higher prevalence of poor sleep quality (children: 65 of 73 [89.0%] vs.19 of 81 [23.5%]; parents: 15 of 73 [18.5%] vs. 1 of 81 [1.23%], both p < 0.001) when compared to the control. Nearly 90% of children had poor sleep quality in both PAC/SAC (42 of 47 [89.4%]) and VKC/AKC (23 of 26 [88.5%]) subgroups and such difference was not significant. However, parents in VKC/AKC subgroup had significant higher prevalence of poor sleep quality than those in PAC/SAC subgroup (9 of 26 [39.1%] vs. 6 of 47 [12.8%], p = 0.027).
The components of CSHQ for children were further compared (Table 2). Children with AC had significant higher scores for bedtime resistance (9.00; IQR, 7.00–12.0 vs. 6.00; IQR, 6.00–8.00; p < 0.001), sleep onset delay (1.00; IQR, 1.00–2.00 vs. 1.00; IQR, 1.00–1.00; p = 0.001), sleep duration (4.00; IQR, 4.00–6.00 vs. 3.00; IQR, 3.00–4.00; p < 0.001), parasomnia(9.00; IQR, 9.00–10.0 vs. 7.00; IQR, 7.00–8.00; p < 0.001), sleep-disordered breathing(3.00; IQR, 3.00–4.00 vs. 3.00; IQR, 3.00–3.00; p = 0.025), sleep anxiety(3.00; IQR, 2.00–3.00 vs. 2.00; IQR, 2.00–3.00; p = 0.003) and daytime sleepiness(13.0; IQR, 10.0-16.0 vs. 10.0; IQR, 8.00–12.0; p < 0.001) than children in the control, while there was no statistically significant difference in night wakings (3.00; IQR, 2.00–5.00 vs. 3.00; IQR, 2.00–3.00; p = 0.216). The increase in daytime sleepiness was most dominant.
The components of PSQI for parents were further compared as well (Table 2). Parents in the AC group had significantly higher scores for sleep latency (1.00; IQR, 1.00–2.00 vs. 1.00; IQR, 0.00–1.00; p = 0.025), use of sleeping medication (1.00; IQR, 1.00–2.00 vs. 1.00; IQR, 0.00–1.00; p < 0.001), and daytime sleepiness (1.00; IQR, 0.00–2.00 vs. 0.00; IQR, 0.00–0.00; p < 0.001) than those in normal control, while subjective sleep quality (0.00; IQR, 0.00–1.00 vs. 1.00; IQR, 0.00–1.00; p = 0.067), sleep duration (1.00; IQR, 0.00–1.00 vs. 1.00; IQR, 0.00–1.00; p = 0.819), and sleep efficiency (0.00; IQR, 0.00–0.00 vs. 0.00; IQR, 0.00–0.00; p = 0.855) were not significantly different. The increase in daytime dysfunction was most dominant.
Risk factors related to sleep quality
As shown in Table 3, reduced sleep quality score in children was correlated with sex, bulbar conjunctival hyperaemia, palpebral conjunctival papillae, follicles, and keratitis (all p < 0.001) by univariable regression analysis; while was correlated with palpebral conjunctival papillae (β:5.12; 95% CI: 2.70–7.54, p < 0.001), follicles (β:3.14; 95% CI: 0.96–5.32, p = 0.005), and keratitis (β:3.09; 95% CI: 0.17–6.01, p = 0.038) by multivariable linear regression. Bivariable logistic regression analysis showed that poor sleep quality in children was associated with follicles (OR:3.95; 95% CI: 1.88–8.31, p < 0.001) and keratitis (OR:6.03; 95% CI: 1.29–28.3, p = 0.028).
Table 3.
Regression analysis of potential risk factors of sleep disturbance and sleep dysfunction caused by allergic conjunctivitis among children.
| CSHQ for children (n = 154) - linear regression | CSHQ for children (n = 154) - logistic regression | |||||||
|---|---|---|---|---|---|---|---|---|
| Univariable | Multivariable | Univariable | Multivariable | |||||
| β (95% CI) | P | β (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | |
| Children’s sex | 4.65 (2.37, 6.94) | <0.001 | 1.25 (−0.85, 3.36) | 0.241 | 4.00 (2.02, 7.93) | <0.001 | 2.49 (1.17, 5.30) | 0.017 |
| Children’s age | −0.31 (−0.85, 0.23) | 0.259 | – | – | 0.93 (0.80, 1.08) | 0.326 | – | – |
| Parents’ age | – | – | – | – | – | – | – | – |
| SE | 0.39 (−0.40, 1.18) | 0.332 | – | – | 1.04 (0.84, 1.29) | 0.693 | – | – |
| BCVA, LogMar | −5.32 (−28.8, 18.1) | 0.655 | – | – | 0.01 (0.00, 9.64) | 0.175 | ||
| Bulbar conjunctiva hyperemia | – | – | ||||||
| No | Ref | – | – | Ref | – | – | ||
| Yes | 7.65 (5.64, 9.65) | <0.001 | – | – | 14.5 (6.56, 32.1) | <0.001 | – | – |
| Papillae | ||||||||
| No | Ref | Ref | Ref | – | – | |||
| Yes | 8.16 (6.12, 10.2) | <0.001 | 5.12 (2.70, 7.54) | <0.001 | 18.2 (7.08, 47.0) | <0.001 | – | – |
| Follicle | ||||||||
| No | Ref | – | – | Ref | Ref | |||
| Yes | 6.57 (4.47, 8.68) | <0.001 | 3.14 (0.96, 5.32) | 0.005 | 5.90 (2.94, 11.9) | <0.001 | 3.95 (1.88, 8.31) | <0.001 |
| Keratitis | ||||||||
| No | Ref | Ref | Ref | Ref | ||||
| Yes | 7.98 (5.06, 10.9) | <0.001 | 3.09 (0.17, 6.01) | 0.038 | 5.67 (1.21, 25.6) | 0.001 | 6.03 (1.29, 28.3) | 0.028 |
Variables with P < 0.10 in the univariable regression analysis were included in the multivariable regression analysis. Bulbar conjunctival was not included in the multivariate regression due to collinearity with hyperaemia, papillae and follicle. The papillae was excluded in the multivariable logistic regression due to collinearity with keratitis.
SE mean dioptric spherical equivalent, BCVA best correct visual acuity, CSHQ Children’s Sleep Habits Questionnaire, OR odds ratio, CI confidence interval.
As for parents (Table 4), parental sleep quality score was correlated with the sleep quality of their children’, and with palpebral conjunctival papillae, follicles, and keratitis in children in univariable regression (all p < 0.001); while with decreased best-corrected visual acuity (β:7.13, 95% CI: 0.31–14.0, p = 0.041), follicles (β:1.16; 95% CI: 0.43–1.90, p = 0.002), and keratitis (β:1.48; 95% CI: 0.49–2.47, p = 0.004) in children in multivariable linear regression. Bivariable logistic regression analysis showed that parental poor sleep quality was associated with follicles (OR:7.14; 95% CI: 2.06 to 24.8, p = 0.002) and keratitis (OR:4.49; 95% CI: 1.27–15.9, p = 0.020) in children.
Table 4.
Multiple regression analysis of potential risk factors of sleep disturbance and sleep dysfunction among parents.
| PSQI for parents (n = 154) - linear regression | PSQI for parents (n = 154) - logistic regression | |||||||
|---|---|---|---|---|---|---|---|---|
| Univariable | Multivariable | Univariable | Multivariable | |||||
| Variables | β (95% CI) | P | β (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P |
| Children’s sex | 0.70 (−0.03, 1.44) | 0.063 | 0.11 (−0.62, 0.84) | 0.763 | 3.14 (0.86, 11.5) | 0.084 | 1.38 (0.32, 6.06) | 0.668 |
| Children’s age | 0.07 (_0.10, 0.24) | 0.434 | – | – | 1.24 (0.96, 1.61) | 0.103 | – | – |
| Parents’ age | 0.06 (−0.01, 0.13) | 0.117 | – | – | 1.03 (0.92, 1.15) | 0.593 | – | – |
| SE | 0.05 (−0.19, 0.30) | 0.665 | – | – | 0.91 (0.64, 1.30) | 0.595 | – | – |
| BCVA, LogMar | 6.37 (−0.92, 13.7) | 0.086 | 7.13 (0.31, 14.0) | 0.041 | 0.43 (0.17, 13.8) | 0.822 | – | – |
| Bulbar conjunctiva hyperaemia | ||||||||
| No | Ref | – | – | Ref | – | – | ||
| Yes | 1.82 (1.15, 2.49) | <0.001 | – | – | 8.84 (1.93, 40.4) | 0.005 | – | – |
| Papillae | ||||||||
| No | Ref | – | – | Ref | – | – | ||
| Yes | 1.76 (1.07, 2.46) | <0.001 | – | – | 4.13 (1.35, 12.6) | 0.013 | – | – |
| Follicle | ||||||||
| No | Ref | Ref | – | Ref | Ref | |||
| Yes | 1.41 (0.71, 2.10) | <0.001 | 1.16 (0.43, 1.90) | 0.002 | 12.3 (3.86, 38.9) | <0.001 | 7.14 (2.06, 24.8) | 0.002 |
| Keratitis | ||||||||
| No | Ref | Ref | Ref | Ref | ||||
| Yes | 2.13 (1.20, 3.06) | <0.001 | 1.48 (0.49, 2.47) | 0.004 | 9.84 (3.21, 30.0) | <0.001 | 4.49 (1.27, 15.9) | 0.020 |
Variables with P < 0.10 in the univariable regression analysis were included in the multivariable regression analysis. Bulbar conjunctival was not included in the multivariate regression due to collinearity with hyperaemia, papillae and follicle. The papillae was excluded in the multivariable logistic regression due to collinearity with keratitis.
SE mean dioptric spherical equivalent, BCVA best correct visual acuity, PSQI Pittsburgh Sleep Quality Index, OR odds ratio, CI confidence interval.
Discussion
Poor sleep quality is an indicator that allergic disease is in poor control and has particular relevance for a patient’s daytime functioning and overall quality of life [38]. In previous studies, sleep disturbance affects up to 60% of children with allergic dermatitis, increasing to 83% during exacerbation, which might be related to nocturnal itching [39, 40]. As for paediatric allergic rhinitis, sleep problems was detected in 40%-88% of children [38, 41–44]. As one of the common allergic diseases, the potential effect of AC on children’s quality of life has been underestimated. The results of our most recent study disclose an association between AC and impaired health-related quality of life for children and their parents [45]. In present study, we excluded children with other active allergic conditions such as allergic rhinitis and allergic dermatitis to avoid the potential negative impact of these conditions on sleep quality.
The results of our study showed that sleep quality in children patient and their parents were generally significantly impaired. The prevalence of poor sleep quality in AC children was 89%, which seems to be comparable or even higher than those reported in allergic rhinitis [38, 41–44] and allergic dermatitis [39, 40]. It may be inappropriate to compare these results directly because of the different diseases severity and cultural differences. Sleep quality was reduced in all components of sleep except for the night wakings in our children patient. Children with AC had shorter sleep duration, more difficulty in falling asleep, and more other sleep disorders such as being anxiety or afraid of sleeping alone, etc. and therefore more daytime sleepiness.
It is noteworthy that impaired sleep quality was evident even in children with PAC/SAC which are considered as common but relatively mild types of the disease. Mean sleep quality score in both PAC/SAC and VKC/AKC subgroups were higher than 41 indicating the presence of poor sleep quality was common, no matter in mild or severe types of AC. Indeed, the prevalence of poor sleep quality was both high as 89.4% in PAC/SAC and 88.5% in VKC/AKC subgroups. Taken together, our study suggests that although AC is an overall none-blinding topical eye disease, its potential effect on children’s sleep quality should not be ignored.
We speculated that nocturnal itching may be responsible for such sleep impairment. However, no symptomatic questionnaire or scales for AC is available, so the association between decline in sleep quality and the symptom severity and time could not be established. Nonetheless, our results revealed that decreased sleep quality in children did being associated with the occurrence of more clinical signs including palpebral conjunctival papillae, follicles, and keratitis in patients which generally link to more discomfort. Another plausible mechanism is circadian fluctuation of inflammatory mediators such as an increase in nocturnal inflammation [46, 47]. Histamine, an inflammatory mediator released during allergic reactions, might contribute to disturbed sleep because it is involved in the regulation of the sleep-wake cycle and arousal but also can induce symptoms of conjunctivitis, directly leading to sleep disruption [48].
Antihistamines and/or glucocorticoids, which are often used in treating allergic rhinitis and allergic dermatitis, have a side-effect of affecting sleep [49, 50]. This is also a great concern of doctors in drug use of treating allergic diseases. In our study, we found that children with allergic conjunctivitis, without using systemic antihistamines or glucocorticoids, also had a decreased sleep quality, indicating that the disease itself had a negative impact on sleep quality.
Changes in children’s sleep would potentially affect the sleep of other family members. The impact of chronic illness on caregivers is a core issue when managing paediatric patients. Similar to the results in children, overall sleep quality and sleep latency, sleep disturbances, sleep medication use and daytime dysfunction were all significantly worse in parents of children with AC, although the prevalence of poor sleep quality in parents was much lower as 18.5% than 89% in their children with AC. Such prevalence significantly increased to 39.1% in patients of children with more severe AC as VKC/AKC. Again, similar to results in children, the decreased sleep quality in parents was found to be linked to a decreased vision and more clinical signs as papillae and keratitis in children. The worries or concerns of the disease especially in those cases with worse visual function and more eye pathologies, as well as taking care of the children with more sleep problem contributed to the sleep problem in parents.
Our study has some limitations. Firstly, we didn’t investigate whether the most intense itching experienced by the majority of patients occurred at night or during sleep. Secondly, our data were collected from subjective questionnaires instead of objective monitoring or assessment of sleep quality. Thirdly, all the patients were recruited from cornea department in a referral ophthalmic centre. More severe cases were rerolled and subsequently generated selection bias.
Conclusion
To the best of our knowledge, this is the first study to assess the status of sleep quality in children with AC and their parents. The results of our study indicate that AC potentially impairs sleep quality and further daytime functioning in both children and their parents. Such impact was common and evident in children especially in those with more clinal signs as severe follicle formation and keratitis. It should be noted that causal relationship between AC and reduced sleep quality can’t be established by the current observational study. Further studies to investigate whether anti-allergic therapy may improve sleep quality in AC is warranted. It would be interesting to know whether administration right before sleep can improve children’s sleep quality.
Supplementary information is available at Eye’s website.
Summary
What was known before
AC has a negative association with quality of life for children and their parents.
A variety of chronic eye diseases including dry eye disease, glaucoma, have been found to potentially correlated with sleep disorders which can in turn exacerbate the condition, creating a vicious cycle.
For children, currently the association between eye diseases and sleep quality has been reported only in myopia with reduced sleep quality.
What this study adds
AC potentially impairs sleep quality and further daytime functioning in both children and their parents. especially in those with more severe clinal signs as follicle formation and keratitis.
Although AC is an overall none-blinding topical eye disease, its potential effect on children’s and their parents’ sleep quality should not be ignored.
Supplementary information
Author contributions
LL conceived the study; JL, and SZ initially designed the study, analysed data, and prepared the manuscript; ZF, and RL collected clinical samples; LJ contributed to data visualisation. All authors read and approved the final version of the manuscript.
Funding
This study is supported by grants (82070922) from the National Natural Science Foundation of China, a grant (2019A1515012012) from the Science Foundation of Guangdong Province and a grant (303020101) from the High-level Hospital Construction Project.
Data availability
Data are available upon reasonable request from the authors.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
These authors contributed equally: Jing Li, Shi-yao Zhang.
Supplementary information
The online version contains supplementary material available at 10.1038/s41433-022-02182-4.
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Data Availability Statement
Data are available upon reasonable request from the authors.