Elsevier

Sleep Medicine

Volume 12, Issue 9, October 2011, Pages 880-886
Sleep Medicine

Original Article
Sleep disturbance in pre-school children with obstructive sleep apnoea syndrome

https://doi.org/10.1016/j.sleep.2011.07.007Get rights and content

Abstract

Study objectives

Sleep-disordered breathing in children is most prevalent in the pre-school years and has been associated with sleep fragmentation and hypoxia. We aimed to compare the sleep and spontaneous arousal characteristics of 3–5-year-old children with obstructive sleep apnoea (OSA) with that of non-snoring control children, and to further characterise the arousal responses to obstructive respiratory events.

Methods

A total of 73 children (48 male) underwent overnight polysomnography: 51 for assessment of snoring who were subsequently diagnosed with OSA (obstructive apnoea hypopnoea index (OAHI) > 1 event per h) and 22 control children recruited from the community (OAHI  1 and no history of snoring).

Results

The OSA group had poorer sleep efficiency (p < 0.05), spent a smaller proportion of their sleep period time in rapid eye movement (REM) (p < 0.05), and had significantly fewer spontaneous arousals (p < 0.001) compared with controls. One-quarter of the children with OSA had a sleep pressure score above the cut-off point for increased sleep pressure. In children with OSA, 62% of obstructive respiratory events terminated in a cortical arousal and 21% in a sub-cortical arousal. A significantly higher proportion of obstructive respiratory events terminated in a cortical arousal during non-REM (NREM) compared with REM (p < 0.001).

Conclusions

These findings suggest that in pre-school children OSA has a profound effect on sleep and arousal patterns. Given that these children are at a critical period for brain development, the impact of OSA may have more severe consequences than in older children.

Introduction

Obstructive sleep apnoea (OSA) is a condition characterised by repeated episodes of apnoea and hypopnoea. OSA is common in children of all ages, but peaks in prevalence during the pre-school years, when the size of the lymphoid tissue of the upper airway is at its largest in relation to the size of the bony skeleton. Recent population-based studies of pre-school children have reported a prevalence of habitual snoring (often or always) of up to 34.5% [1], and OSA is thought to affect 1–3% of the population [2]. OSA in school-aged children has been associated with both deficits in neurocognition and behavioural problems, which have been suggested to be the result of sleep fragmentation and intermittent hypoxia [3], [4], [5], [6], [7], [8]. Unlike adults with OSA, children with OSA do not have significant changes in sleep macroarchitecture when assessed using either conventional or spectral analysis techniques [3], [9], [10], [11], [12], [13], [14], [15]. However, using alternative methods of assessing sleep quality such as the sleep pressure score (SPS), which reflects an increased pressure for sleep in children with OSA [16] and sleep dynamics, which measures the durations of periods of the same sleep stage [17], some disturbances have been observed. Tauman et al. [16] reported that children with sleep-disordered breathing (SDB) had a significantly increased percentage of slow wave sleep (SWS) and decreased rapid eye movement (REM) sleep compared with control children and demonstrated that these children also had increased sleep pressure. Chervin et al. [17] demonstrated that analysis of the mean duration of stage 2 sleep can independently distinguish children with and without SDB [17]. Both of these studies indicate that sleep fragmentation commonly occurs in children with SDB and this raises the possibility that fundamental to the quality of sleep in children with OSA are the arousals that occur at the termination of obstructive respiratory events.

Although the prevalence of OSA peaks in the pre-school age group, at a time of crucial neurocognitive and physical development, there has only been limited research investigating respiratory-related arousals in this age group, and the studies that have been performed have included children who varied widely in age. The results have suggested that, unlike in adults, respiratory events frequently terminate without cortical arousal [10], [11], [18].

As good sleep quality is fundamentally important to pre-school children, research investigating the association between OSA and arousal in this age group is critical. Therefore, the aims of this study were twofold: first, to compare the sleep architecture and spontaneous arousal characteristics of pre-school children with OSA to that of non-snoring control children; and second, in pre-school children with OSA, to categorise the arousal responses to obstructive respiratory events as either cortical or sub-cortical arousals, or no arousal, and to determine how the different sleep stages affected the arousal response.

The Southern Health and Monash University Human Research Ethics Committees granted ethical approval for this project. Written informed consent was obtained from parents and verbal assent from children prior to commencement of the study, and no monetary incentive was provided for participation.

All children underwent a complete medical examination prior to a routine overnight polysomnographic (PSG) study and children with conditions known to affect sleep, breathing, or blood pressure were excluded. The subjects for this study (n = 51) were those children diagnosed with OSA who were participating in a larger study of the effects of SDB on cardiovascular control, behaviour, and neurocognition in pre-school children. OSA was defined as an obstructive apnoea hypopnoea index (OAHI) > 1 event per h of sleep. All children with the diagnosis of OSA studied between July 2008 and January 2010 were included. An age-matched control group (n = 22) with no history or parental concerns of snoring was recruited from the community. The absence of SDB was confirmed by PSG with children having an OAHI  1 event per h and no observation of snoring.

Electrophysiological signals were recorded using a commercially available PSG system (E-Series, Compumedics, Melbourne, Australia). Electrodes for recording electroencephalogram (EEG; Cz, C4–A1, C3–A2, O2–A1, O1–A2 [⩾4 years]; Cz, C4–A1, C3–A2 [<4 years]), left and right electrooculogram (EOG), submental electromyogram (EMG), left and right anterior tibialis muscle EMG and electrocardiogram (ECG) were attached. The EEG and ECG signals were digitised at a sampling rate of 512 Hz. Thoracic and abdominal breathing movements using respiratory inductance plethysmography (Pro-Tech zRIP™ Effort Sensor, Pro-Tech Services Inc., Mukilteo, WA, USA), oxygen saturation (Bitmos GmbH, Dusseldorf, Germany; using 2-s averaging time), and transcutaneous carbon dioxide (TINA TCM3, Radiometer, Copenhagen, Denmark,). Nasal pressure and oronasal airflow were also recorded. Following the PSG study, data were transferred via European Data Format to specialised data analysis software (LabChart 6, ADInstruments, Sydney, Australia).

For a subject to be included in the study, he/she needed to have a minimum of 4 h of sleep. This was a clinical requirement so that the study could be evaluated for SDB severity. For this study, the entire sleep period was analysed for each child. All PSG studies were manually sleep-staged in 30-s epochs by experienced paediatric sleep technologists according to standard criteria [19].

Respiratory events ⩾2 respiratory cycles in duration were scored. Obstructive apnoea and hypopnoea scoring was based on the American Academy of Sleep Medicine (AASM) criteria [20]. Apnoeas and hypopnoeas were not scored during periods of body movement and were scored from the end of expiration to the beginning of inspiration. Obstructive apnoeas required a decrease to <10% of baseline in flow signal with continued or increased respiratory effort. There was no requirement for the event to terminate with either ⩾3% SpO2 (saturation of peripheral oxygen) desaturation or arousal. Obstructive hypopnoeas required a clear reduction from baseline in flow signal, continued respiratory effort present with paradox or phase shift, and to be associated with snoring, or noisy breathing during the event or at the termination of the event. Obstructive hypopnoeas were either associated with an awakening, arousal, or ⩾3% SpO2 desaturation. To analyse the SPS, the total arousal index (ARItotal) and the respiratory arousal index (RAI) included all obstructive hypopnoeas as defined above. To avoid the confounding effect of hypopnoeas associated with an arousal only on the quantification of arousals at event termination, only hypopnoeas that were associated with a ⩾3% SpO2 desaturation (either with or without an accompanying arousal) were included for the analysis of arousals at event termination.

The duration of each sleep stage and wake after sleep onset (WASO) were calculated as a percentage of the sleep period time (SPT), defined as the amount of time in minutes from sleep onset until lights on at the end of the study. Total sleep time (TST) was defined as SPT excluding all periods of wake fulness. Other variables calculated included sleep latency, REM latency, and sleep efficiency. Sleep latency was defined as the period from lights off to the first three consecutive epochs of stage 1 sleep or an epoch of any other stage. REM latency was defined as the period from sleep onset to the first epoch of REM sleep.

Episodes of periodic limb movements (PLMs) were identified according to the published standards devised by the World Association of Sleep Medicine in collaboration with a Task Force from the International Restless Legs Syndrome Study Group [21].

The SPS for the TST was calculated for the children with OSA following the method described in Tauman et al. [16]. In addition, the SPS was calculated for non-REM (NREM) and REM. The ARItotal for TST, NREM and REM was divided into an RAI (includes cortical and subcortical respiratory arousals), a spontaneous arousal index (SAI), and a periodic leg movement arousal index (PLMAI), where ARI total = RAI + PLMAI + SAI.

The SPS was calculated using the formula:SPS=(RAI/ARItotal)×(1-SAI/ARItotal)

It has been suggested that an SPS value of 0.25, at which point RAI/ARItotal and SAI/ARItotal are equal, represents the cut-off point defining increased sleep pressure [16].

The arousal sequelae of every obstructive respiratory event for each subject in the OSA group were manually categorised as cortical arousal, sub-cortical arousal, or non-arousal. Arousals were scored as either cortical [22] or sub-cortical (⩾2 of: increase in heart rate, increase in submental EMG activity and distortion of respiratory effort belts) [23]. Both cortical and sub-cortical arousals were scored if they occurred within 2 s of the termination of the respiratory event.

The proportion of respiratory events terminating in each type of arousal is presented for TST, and separately for NREM and REM.

Statistical analyses were performed using Sigmaplot 11 (Systat Software Inc, San Jose, CA, USA). Data from both control and OSA groups were first tested for normality and equal variance and were found to be normally distributed. Demographic and sleep data from control and OSA groups were compared using non-paired Student’s t-tests. A two-way analysis of variance (ANOVA) was used to compare differences in arousal type (the mean percentage of obstructive respiratory events that were followed by cortical or sub-cortical arousals for each subject) and differences in sleep state (NREM and REM) in the OSA group. Paired Student’s t-tests were used to compare the number of obstructive respiratory events that occurred during NREM compared with during REM as an index of the time spent in each sleep state. Multiple linear regressions were performed for TST, NREM, and REM to determine significant predictors for arousal, with cortical and sub-cortical arousals as the dependant variable and OAHI, age, gender, and body mass index (BMI) as the independent variables. In addition, for TST, sleep state was added as an independent variable by including the %TST spent in NREM sleep. A P value of <0.05 was considered significant. Data are presented as mean ± standard error of the mean (SEM).

Section snippets

Demographic, sleep, and arousal characteristics in control children and children with OSA

Demographic, sleep, and arousal characteristics of children with OSA compared with non-snoring controls are presented in Table 1. Children with OSA spent a significantly lower proportion of SPT in REM compared with controls (P < 0.05). The time spent in NREM1, NREM2, or SWS as a percentage of SPT did not significantly differ between the groups. There were no significant differences between the two groups for age, sleep latency, REM latency, or WASO as a percentage of SPT. TST and sleep efficiency

Discussion

Although SDB peaks in the pre-school years, the consequence on sleep in this age group has received little attention. Previous studies in older children have shown no difference in sleep architecture between children with OSA and healthy children [3], [9], [10], [12], [13], [17], [24]. We found that pre-school children with OSA spent a smaller proportion of their SPT in REM sleep compared with control children. We also determined that children with OSA had fewer spontaneous arousals compared

Conclusions

Pre-school children with OSA spent significantly less time in REM compared with controls and exhibited more cortical arousals in response to obstructive respiratory events during NREM than REM. A substantial number of obstructive respiratory events terminate with a sub-cortical arousal, a finding which has not been commonly reported in older children. However, as demonstrated in older children, OSA reduces spontaneous arousals and increases SPS in pre-school children, indicating that these

Conflict of interest

The ICMJE Uniform Disclosure Form for Potential Conflict of interest associated with this article can be viewed by clicking on the following link: 10.1016/j.sleep.2011.07.007.

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Acknowledgements

The authors would like to thank the staff of the Melbourne Children’s Sleep Centre for their help and technical advice, and the parents and children who participated in this study.

This study has been supported by a National Health and Medical Research Council project grant and the Victorian Government’s Operational Infrastructure Support Program.

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