Sleep Disordered Breathing in Children with Autism Spectrum Disorder: An In-depth Review of Correlations and Complexities

1. Introduction

Sleep-disordered breathing (SDB) represents a significant issue affecting the pediatric population [1,2]. These conditions can have severe consequences on the health and well-being of children [1,3,4].

In the broader context, independent risk factors for Obstructive Sleep Apnea Syndrome (OSAS) encompass persistent snoring for ≥ 3 months, tonsillar and adenoid hypertrophy, and obesity (Xu et al., 2020). Moreover, the presence of frequent respiratory infections [5] may amplify the impact, particularly when coupled with factors such as tonsillar and adenoid hypertrophy or obesity. Muscle hypotonia in children with genetic comorbidities [6,7,8] may serve as concurrent catalysts exacerbating SDB. The intricate interplay of SDB can orchestrate disruptions in sleep patterns and intermittent hypoxia, exerting a discernible impact on the cognitive and behavioral faculties of children [9,10,11]. Consequently, delving into the long-term trajectories of these disorders and maintaining vigilant follow-up mechanisms becomes an imperative [1,12].

Neurodevelopmental disorders constitute a wide-ranging category of medical conditions that profoundly impact the intricate development of the nervous system, particularly during the critical phases of brain maturation. The delicate interplay of factors shaping proper nervous system development intertwines with the multifaceted complexities characterizing the manifestation of ASD during the crucial stages of childhood or infancy [13,14,15], explores the nuanced aspects of the condition. The resulting impact reverberates across a comprehensive spectrum of domains, encompassing the intricate threads of communication, the fabric of learning, the dance of social behavior, and the tapestry of motor skills. While ASD maintains its distinct identity with unique attributes, acknowledging the latent potential for multiple neurodevelopmental disorders to converge within the presentation of children remains of paramount significance [16,17,18].

Aims of the study

This study aims to explore the current understanding of the intricate relationship between ASD and SDB in children, the underlying mechanisms, and the importance of early detection and intervention for SDB in children with ASD. The study seeks to illuminate how early interventions can enhance sleep quality, address behavioral challenges, and improve the overall well-being of affected children.

2. Materials and Methods

We conducted a literature search using major search engines (PubMed, Scopus, and Web of Science; access date July 15, 2023), employing the relevant keywords listed below:

PubMed: (" autism spectrum disorders" OR " autism" OR "autistic" OR “Asperger” OR “Pervasive developmental disorder”) AND ("sleep-disordered breathing" OR "sleep apnea" OR "sleep apnoea" OR "sleep disorders breathing") AND ("Polysomnography" OR "Treatment outcomes" OR "Complications") AND ("Children" OR "Pediatric patients" OR "infant")

Scopus: (TITLE-ABS-KEY(" autism spectrum disorders") OR TITLE-ABS-KEY(" autism") OR TITLE-ABS-KEY("autistic") OR TITLE-ABS-KEY("Asperger") OR TITLE-ABS-KEY("Pervasive developmental disorder")) AND (TITLE-ABS-KEY("sleep disordered breathing") OR TITLE-ABS-KEY("sleep apnea") OR TITLE-ABS-KEY("sleep apnoea") OR TITLE-ABS-KEY("sleep disorders breathing")) AND (TITLE-ABS-KEY("polysomnography") OR TITLE-ABS-KEY("treatment outcomes") OR TITLE-ABS-KEY("complications")) AND (TITLE-ABS-KEY("children") OR TITLE-ABS-KEY("pediatric") OR TITLE-ABS-KEY("infant"))

WebOfScience: TS=(" autism spectrum disorders" OR " autism" OR "autistic" OR "Asperger" OR " Pervasive developmental disorder") AND TS=(“sleep-disordered breathing" OR "sleep apnea" OR "sleep apnoea" OR "sleep disorders breathing") AND TS=("Polysomnography" OR "Treatment outcomes" OR "Complications") AND TS=("Children" OR "Pediatric" OR “infant”).

Inclusion and exclusion criteria

The inclusion criteria comprised the pediatric age group, autism, autistic, pervasive, sleep apnea, SDB, OSA, and PSG. Exclusion criteria encompassed non-English articles, reviews, case reports, case series, or letters, studies focusing on adults (>18 years), studies lacking specific outcome reporting, and duplicate studies (i.e., those published multiple times or identified from different data sources).

3. Results

Ninety-six records were initially identified, accounting for duplicates. Through a meticulous screening of titles and abstracts, we narrowed our selection to 19 studies that aligned with our research objectives. Subsequently, we comprehensively evaluated these studies to ascertain their relevance and quality. Following this procedure, we ultimately incorporated 7 articles (Figure 1).

Four studies have examined SDB within the broader context of sleep disorders in children with ASD (Table 1). Youssef et al. investigated the relationship between ferritin levels, fragmented sleep, and joint movements in children [19]. Tudor et al. explored the correlation between pain and sleep problems [20]. Elrod et al. delved into the risk of sleep disorders associated with diagnostic/surgical procedures in children [21]. Johnson et al. explored the psychometric properties of the Sleep Subscale of the CSHQ [22]. Three studies (Table 1) specifically focused on OSA. Murata et al. examined behavioural changes following tonsillectomy and adenoidectomy interventions [23]. Tomkies et al. investigated predictors of OSA and severe OSA, along with demographic and clinical characteristics [24]. Additionally, a study compared OSA symptoms and the age of diagnosis [25].

Studies investigating the relationship between SDB and children with ASD have employed various methodologies and involved diverse subject groups. The survey conducted by Youssef et al. included a large population of children with ASD, analyzing participant data for ferritin levels and PSG data [19]. Tudor et al. evaluated parent-reported sleep habits using the CSHQ questionnaire. They examined correlations between pain and sleep disorders, including SDB, to understand the impact of pain on sleep quality [20]. Elrod et al. analyzed ASD data from a broad sample of children, comparing it to a control group. They assessed the risk rates of sleep disorders and SDB. Johnson et al. evaluated sleep habits and SDB using the CSHQ, and studied psychometric properties [21]. Murata et al. investigated OSA in children with and without ASD using PSG, assessing behavioural changes before and after treatment [23]. Tomkies et al. performed PSG on children, examining predictors of OSA and considering demographic and clinical variables [24]. Santapuram et al. reviewed clinical records, looking at diagnoses and treatments for SDB [25]. In summary, through diverse methodologies such as PSG analysis, the CSHQ questionnaire, ICD-9-CM data, and clinical assessments, these studies have delved into the intricate relationship between SDB and ASD, revealing crucial aspects of this dynamic.

SDB represents a complex study area for children with ASD and has brought forth several significant findings. In the first study by Youssef et al. ferritin levels and BMI were not significantly correlated with OSA. This lack of association suggested that different factors might contribute to the onset of SDB in this population [19]. On the other hand, the investigation by Tudor et al. revealed that sleep behaviours and vocalizations could influence scores on the SDB subscale of the CSHQ. This finding suggests that SDB might be associated with specific vocal behaviours and overall sleep quality [20]. Elrod et al. uncovered a higher risk of developing sleep disorders, including OSA, in children with ASD [21]. These results underscore the need for timely assessment and intervention to address such respiratory disorders. However, despite the association between ASD and SDB, loud snoring and other abnormal breathing behaviours were only rarely found in the children examined in Johnson et al.'s study [22]. This suggests that while sleep disorders are essential to consider, they might vary significantly in frequency and presentation. The findings from Murata et al. highlighted the effect of OSA on behaviours and overall well-being of children with ASD. OSA treatment emerged as a crucial element for improving behavioural issues [23]. Irrespective of obesity and age, the extent of the scope of OSA was further explored in the study by Tomkies et al., which revealed that OSA is common in children with ASD and can vary significantly in severity. Obesity emerged as a significant predictive factor, particularly for severe OSA [24]. Lastly, Santapuram et al. examined the association between autism severity, age at diagnosis, and factors like BMI in the context of OSA [25]. While the initial association between autism severity and age at OSA diagnosis did not prove statistically significant when accounting for other factors, both BMI and age at autism diagnosis appear to contribute to the age at OSA diagnosis independently.

In the final phase of the selection process, we also reviewed studies investigating the relationship between ASD and sleep disturbances, although not directly related to SDB (Table 2). These studies were excluded because they focused on distinct strategies to enhance sleep quality and treatments for insomnia associated with ASD, rather than respiratory conditions. Additionally, these studies explored general sleep difficulties and interventions to address them without specifically highlighting SDB.

Delemere and Dounavi investigated strategies to enhance sleep quality, concentrating on the effectiveness of 'bedtime fading' to improve sleep duration and latency [32]. In contrast, McCrae et al. showcased the effectiveness of cognitive-behavioural therapy in treating insomnia linked to autism [35]. Gender discrepancies in sleep disturbances within the autistic spectrum were examined by Estes et al., uncovering distinct sleep-related challenges encountered by females with ASD and revealing associations between heightened anxiety and sleep disturbances in males with ASD [36].

Miano and Ferri demonstrated that sleep issues in children with ASD mirror those found in typically developing children, albeit with higher frequency. These problems can be tackled through medication and behavioural approaches [26]. Notably, the utilization of melatonin as a potential solution has garnered attention. Wright et al. showcased melatonin's safe and influential role in enhancing insomnia and sleep duration [28]. Giannotti et al. identified sleep alterations in non-regressive autism with implications for managing insomnia [27]. Additionally, Silveira Cruz-Machado et al. delved into the intricate connection between sleep, immunity, and autism, proposing a potential role for melatonin [34]. The use of supplements, such as carnosine, as a possible treatment approach was also discussed by Mehrazad-Saber et al. [31].

Sleep disturbances pose a significant challenge for children with ASD, impacting their behaviours and overall well-being. Addressing these issues is essential to enhance their quality of life. Research has illuminated various strategies, including 'bedtime fading' and cognitive-behavioural therapy, to improve sleep in this population. Moreover, therapeutic interventions such as melatonin and supplements like carnosine offer promising avenues to manage sleep disturbances. With an advancing understanding of the complex interaction between sleep and ASD, further studies and personalized interventions will undoubtedly pave the way for improved sleep outcomes and enhanced overall well-being for individuals on the autism spectrum.

4. Discussion

Research on the effects of SDB or OSA in children with ASD has revealed significant insights (Figure 2). One study demonstrated that 34% of children with ASD (n=53, age 7.5 [4.8, 12.8] years) were diagnosed with OSA through PSG [19]. Another study reported that children with ASD (age 4.7±1.14 years) who snore occasionally account for 25.4%, and those who snore constantly are 5.1%. Children experiencing sleep apnea occasionally are 3.5%, and those experiencing it frequently are 0.6%, according to the CSHQ [22]. An elevated susceptibility to the development of sleep disorders, encompassing OSA, has been documented. The risk of sleep disorders in autistic children is increased by 96% compared to non-autistic children. Furthermore, children with ASD are also at a higher risk of undergoing PSG (increased by 274% compared to the control group) and ENT surgery (increased by 50% compared to the control group) [21]. Among 45 children with ASD (age 6.1±2.8 years), 58% had OSA diagnosed through PSG, and 33% were obese [24].

The incidence of obesity in children with ASD is at least as high as, or even higher than, the incidence in the general population of children. Risk factors for a high BMI have been identified as advanced child age, high maternal BMI, low physical activity, and an increased likelihood of food selectivity [38]. Obesity has been identified as a predictive factor for SDB (OR 1.04, 95% CI 1.0–1.08, P = 0.02), especially for severe OSA, in children with ASD [24]. Moreover, the risk and rate of obesity in pediatric individuals with ASD are elevated [39], with causes primarily attributed to sedentary lifestyles and improper dietary habits [40]. A study found that ferritin levels and BMI in children with ASD (n=53, age 7.5 [IQR 4.8, 12.8] years) were not significantly correlated with OSA, suggesting the presence of other influential factors [19]. Another study indicated that BMI and age of autism diagnosis could independently impact the generation of OSA diagnosis [25]. The treatment of OSA (diagnosed through PSG) with A&T has been crucial in improving behavioural issues, regardless of the child's obesity and age [23].

OSA negatively impacts behaviours and overall well-being in children with ASD [23]. A study found a correlation between the number of pain-related behaviours exhibited in the previous week. It increased overall sleep-related problems, specifically shorter sleep duration, parasomnias (sleepwalking or nightmares), and SDB [20]. Some researchers have concluded that children with ASD are more likely to receive a sleep disorder diagnosis, including SDB, and are more prone to undergo related diagnostic and surgical procedures than controls without ASD [21].

Investigations are currently in progress to delve into the potential connection between connective tissue irregularities and ASD; however, the precise nature of the relationship between these two factors remains incompletely understood. Altered connectivity can lead to phenomena of heightened sensitivity to environmental stimuli. Compared to healthy subjects, asthma and allergic rhinitis have a prevalence of 5:1 in ASD [41]. Frequent episodes of interstitial inflammation, immune-mediated forms of allergic asthma, bronchial hyperreactivity, nasal secretion, and nasal obstruction sensation have been observed following exposure to environmental allergens [42,43]. Nonetheless, a direct linear relationship between the extent of nasal obstruction and the intensity of SDB is absent. In most cases presenting moderate or severe OSA, nasal obstruction is not the primary underlying factor [44].

Hypermobility has quite a high prevalence in ASD, to the point that authors tend to include autism among hypermobility spectrum disorders (HSD) [43]. Recognizing the differences between muscle weakness (hypotonia), tendon laxity, and joint hypermobility is complex, especially when dealing with individuals with autism is an important issue [43,45]. However, hypotonia is also a recognizable marker of ASD [46]. Hypotonia is when children have very "soft" or flaccid muscle tone. The hypotonia observed was classified as mild to moderate and exhibited a widespread distribution across the entire body. Hypotonia was the most common motor symptom in a cohort of 154 children with ASD (51%), and it appears to improve over time. In the 2–6 year-old group, the prevalence of hypotonia was approximately 63% [45] at the age in which there is a high prevalence of SDB mainly due to adenotonsillar hypertrophy [47,48]. In general, the atonia of skeletal muscles present during REM sleep might be exacerbated by the underlying hypotonia in children [49], and in ASD might increase the risk of OSA. When muscles are not adequately toned, the airways can become more collapsible.

This review has analysed the relationship between ASD and SDB, particularly OSA, highlighting an intriguing landscape of complex correlations. Numerous research studies have established a notable correlation between ASD and the occurrence of OSA, with reported prevalence rates spanning from 34% to 58% [19,24]. Additionally, a higher risk of developing sleep disorders, including OSA, has been observed in children with ASD [21]. The risk and rate of obesity are increasing in pediatric individuals with ASD [24,39,40]. Obesity has been identified as a predictive factor for SDB, and BMI may be directly correlated with OSA in these children [19,25]. Surgical intervention via A&T has proven crucial in improving behavioural issues in children with ASD affected by OSA [23].

Children diagnosed with ASD might experience challenges in tolerating PSG [50,51] or discomfort sleeping in a different environment from their bed. However, some steps can help reduce anxiety during the PSG procedure, such as providing a detailed explanation of the procedure, identifying the child's strengths, using accessories that reflect the child's interests, and allowing family members to be present during the process to reduce anxiety, and paying close attention to the child's needs. It is important to note that if a child cannot undergo PSG due to their condition, there are alternative methods for assessing SDB for the development of an appropriate therapeutic plan [51,52,53].

5. Conclusions

In conclusion, this review has highlighted the complex interplay between ASD and SDB, underscoring the need for further research to understand the underlying mechanisms. The study's findings also emphasise the importance of early identification and treatment of SDB in children with ASD. SDB can significantly impact a child's physical and mental health, and early intervention can help improve sleep quality, reduce behavioural problems, and improve overall well-being.