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For submission to: Journal of Sleep Disorders: Treatment & Care


Sleep parameters and architecture in children with attention-deficit/hyperactivity disorder: A comparison with typically developing peers and across subtypes
Tamara A. Speth1
Andre Benoit1
Penny V. Corkum1, 2, 3, 4, 5

Departments of Psychology and Neuroscience1, Pediatrics2, and Psychiatry3, Dalhousie University; Pediatrics, IWK Health Centre4; ADHD Clinic, Colchester Regional Hospital5





Correspondence should be addressed to:
Dr. Penny Corkum
Department of Psychology and Neuroscience, Dalhousie University 
1355 Oxford Street, PO BOX 15000
Halifax, Nova Scotia, Canada, B3H 4R2
E-mail:  HYPERLINK "mailto:penny.corkum@dal.ca" penny.corkum@dal.ca
Total number of pages in manuscript: 24
Abstract
Sleep problems in children with attention-deficit/hyperactivity disorder (ADHD) are common, yet poorly understood. Furthermore, little research has been done to compare sleep between subtypes of children with ADHD. The current study used polysomnography to investigate sleep architecture and sleep parameters in a rigorously diagnosed, medication-na�ve, age- and sex-matched sample of children with ADHD and their typically developing (TD) peers. Sleep was compared between 25 children with ADHD and 25 TD children between 6 and 12 years of age, and between children with different subtypes of ADHD. Results indicate that children with ADHD took longer to fall asleep and slept less than their TD peers; however, no other differences in sleep between the two groups were identified. Furthermore, no differences were found in any sleep parameters or sleep architecture variables between ADHD subtypes. Future research should continue to investigate sleep in children with ADHD by investigating additional sleep variables including nocturnal movement, stage shifts per hour, and sleep microstructure.
Keywords: ADHD, subtypes, specifiers, sleep architecture, sleep parameters 








Sleep parameters and architecture in children with attention-deficit/hyperactivity disorder: A comparison with typically developing peers and across subtypes
Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder affecting approximately 5 percent of children in most cultures [1]. Children diagnosed with ADHD present with clinically elevated levels of inattention and/or hyperactivity-impulsivity compared to children at a similar level of development. The symptoms of ADHD cause impairments in multiple settings (e.g., home, school), and often result in academic and vocational challenges as well as social difficulties [2]. The DSM-IV-TR previously classified children with ADHD into three subtypes: predominantly inattentive, predominantly hyperactive/impulsive, or combined [3]; however, with the release of the DSM-5, these subtypes have now been replaced with the following specifiers: predominantly inattentive presentation (ADHD-I), predominantly hyperactive/impulsive presentation (ADHD-HI), and combined presentation (ADHD-C) [1]. Although there is a change in terminology from subtypes to presentations, the symptoms within each grouping have not changed. 
	In addition to the core symptoms of ADHD (i.e., inattention, impulsivity and hyperactivity), up to 70 percent of children with this diagnosis also experience sleep problems [4]. While several studies have examined the relationship between sleep and ADHD in children using a range of measurement techniques (e.g., surveys, actigraphy, polysomnography), these techniques rarely produce congruous data. Parental reports of children�s sleep have yielded the most consistent results, and suggest that children with ADHD have more difficulty falling and staying asleep and exhibit more daytime sleepiness than their typically developing (TD) peers [5]. To a lesser extent, actigraphy data have also shown differences in sleep between TD children and those with ADHD, for example, children with ADHD have been found to displaying more night-to-night variability in their sleep patterns [6]. However, recent findings suggest that differences between groups in actigraphic measures of sleep, including intra-individual variability, may be moderated by psychiatric comorbidity [7]. Although polysomnography (PSG) is the most objective method of measuring sleep, PSG studies of children with ADHD have produced highly inconsistent results.
	Several PSG studies exist that have found no differences between children with ADHD and their TD peers across a range of sleep parameters and sleep architecture variables (e.g., percent of REM/NREM sleep) [6, 8-12]; however, others have found that when compared to control children, those with ADHD show increased movement during sleep [10, 13-17], decreased SOL [14, 18] , decreased SWS [17], decreased REM [17, 19], and increased REM onset latency [19]. Still others have reported conflicting results, for example, finding that children with ADHD have increased REM [20-22], and decreased REM onset latency [21] when compared to their TD peers. 
	Several reviews and meta-analyses have been conducted to better understand the inconsistencies in research that has evaluated the sleep of children with ADHD in comparison to TD children, using both objective and subjective measures [23-30]. In 2013, Corkum and Coulombe conducted a review of reviews which included three quantitative (meta-analytic) and five qualitative reviews, which used objective and subjective measures to look at sleep problems in children with ADHD [31]. The authors first considered the findings of quantitative and qualitative reviews separately, and then evaluated the results of all eight reviews to identify consistent findings. Based on their review of reviews, Corkum and Coulombe found that across all meta-analyses and qualitative systematic reviews, parents reported more sleep problems in children with ADHD than what has been found based on objective measures, children with ADHD demonstrated more nocturnal movement than control children, and there were no significant differences in sleep architecture between children with ADHD and controls. Additionally, there were several confounding variables that were shown to moderate differences between groups. These variables included age, sex, ADHD subtype, diagnostic procedures, psychiatric comorbidity, medication use, and adaptation to the sleep lab. Findings which were less consistent across reviews (i.e., supported by at least one meta-analysis and one or more qualitative review) included an increase in sleep problems with the use of medication for ADHD, increased daytime sleepiness in children with ADHD, and a higher sleep apnea index in children with ADHD (although the elevation has not been found to be clinical). 
	Therefore, it appears that despite parental reports that children with ADHD have more difficulty falling and staying asleep and exhibit more daytime sleepiness than TD children, objective studies have failed to provide convincing evidence of either a qualitative or quantitative difference, beyond the finding of increased nocturnal movements [31]. One possible explanation for the lack of objectively measurable difference in sleep between children with ADHD and their TD peers may be related to the tendency of researchers to collapse their ADHD sample across subtypes. For example, the DSM-III listed sleep disturbance as a central feature of Attention Deficit Disorder (ADD) with Hyperactivity (ADD-H), which was a feature not listed for ADD without Hyperactivity (ADD-WO) [32]. Although versions of the DSM that have been released since this time [1, 3, 33-34] do not include sleep disturbance as a primary symptom of ADHD, this early distinction suggests the possibility that the presence and degree of sleep disturbance in children diagnosed with ADHD may vary as a function of their clinical presentation. An early study conducted by Ramos Platon and colleagues that examined sleep in children with a DSM-III diagnosis of ADD using PSG found that children with ADD, hyperactive subtype (ADD-H) experienced more fragmented and less efficient sleep than children diagnosed with ADD without hyperactivity (ADD-WO) [35].
Since this early study, researchers have used both subjective (parent report, sleep diary) and objective (actigraphy) measures to continue investigating differences in sleep between subtypes of children with ADHD (as defined by the DSM-IV or DSM-IV-TR). Such studies have generally found no differences in sleep parameters between groups [36-37]. Some studies have revealed interesting associations (e.g., daytime sleepiness was shown to be greater in children with ADHD who were predominantly inattentive) [37]; however, research has yet to establish differential sleep profiles between the ADHD subtypes. Given the early findings of Ramos Platon and colleagues it is possible that differences between groups are only apparent when examined objectively using PSG [35]. There are currently no known PSG studies that have directly compared sleep architecture between ADHD subtypes as defined by the DSM-IV-TR or DSM-5.
The current study therefore examined various sleep parameters and sleep architecture variables of children with ADHD and their TD peers. To ensure control over confounding variables, the current study (1) matched ADHD and TD groups by age and sex, (2) ensured children with ADHD were stimulant medication-na�ve, and (3) excluded children with ADHD with co-morbid psychiatric conditions (i.e., anxiety, depression), all of which are known to impact sleep in children [31]. The primary goal of the current study was to determine whether a rigorously diagnosed, medication-na�ve, age- and sex-matched sample of children with ADHD would show differences in sleep parameters and/or sleep architecture as measured by PSG. Furthermore, the current study sought to compare sleep parameters and sleep architecture variables between subtypes/presentations of children with ADHD.
In light of previous meta-analyses and the review of reviews, and given the rigorous control over potential confounds in the current study, it was expected that children with ADHD as a group would not differ significantly from their TD peers in sleep architecture variables (e.g., percent of REM) or on sleep parameters.  It was further predicted that children in the ADHD-C/HI group would have more sleep problems than children in the ADHD-I group, based on the findings of Ramos Platon and colleagues [35]. 
Method
Participants
	Data was collected from 30 children diagnosed with ADHD and 30 TD children. After age- and sex- matching participants, the final sample consisted of 25 children in each group. All children were between 6 and 12 years of age.  
	Children in the ADHD group received a comprehensive diagnostic assessment at a specialty clinic or through a private practice specializing in ADHD prior to participation. Children in this group were newly diagnosed with ADHD, stimulant medication-na�ve and free of chronic or impairing medical illness (e.g., diabetes) and/or co-morbid primary mental health disorders (e.g., depression, anxiety). As learning disabilities are highly co-morbid with ADHD [38] and are not known to impact sleep, children with ADHD and a co-morbid learning disability were not excluded from the study. 
Data from children in the ADHD group were collected as part of their participation in a larger study examining the impact of stimulant medication on sleep. Prior to completion of the medication trial, all children in the ADHD group completed an overnight PSG testing session, the data from which were used in the current study. Children in the TD group were screened using parent-report rating scales and a telephone interview. Children in this group were excluded if screening indicated that they had a chronic or impairing medical illness, a history of neurological impairments, a mental health disorder, a primary sleep disorder, or reached clinical cut-off on the questionnaire for ADHD symptoms. TD children were recruited from the community using online advertisements, word-of-mouth, newsletters, and through their participation in previous studies in our laboratory.
Procedures  
	Children in both groups completed their PSG assessment on a Friday or Saturday evening. Parents were instructed to keep their child�s sleep schedule as close as possible to their typical sleep schedule for the week preceding their PSG assessment. Children and their parents arrived at the sleep laboratory two hours prior to the child�s typical bedtime. Following a brief tour of the facility, the research assistant obtained the parent�s consent and the child�s assent to participate and then collected information from parents regarding the child�s sleep schedule for the preceding week. A PSG research assistant then applied electrodes for the PSG assessment. The child�s �lights out� and �lights on� times were set based on the child�s typical sleep schedule, which was determined using sleep diaries and actigraphy, during the week preceding the child�s PSG.
Measures
Conners� Parent Rating Scale-Revised. Each parent completed the Conners� Parent Ratings Scale � Revised (CPRS-R) [39]. The CPRS-R is an 80-item parent-report measure, most often used as a screener for various childhood behavioural problems including ADHD. The CPRS-R has been shown to demonstrate excellent validity and reliability with alpha values ranging from 0.75 to 0.94 [39]. CPRS-R scores were used to confirm that TD participants did not have clinically significant symptoms of ADHD.
Demographic Questionnaire. Parents completed a demographic questionnaire, which asked about information pertaining to child, parent, and family variables, including family socioeconomic status (SES) [40], family composition, and child�s age, sex, and medical history.
	Polysomnography. PSG assessments were conducted in a sleep laboratory equipped with a Sandman� PSG system which recorded four electroencephalogram (EEG) channels, left and right electroculogram (EOG), two electromyogram (EMG) channels, and electrocardiogram. The child�s respiratory effort and oxygen saturation were captured via oral nasal cannula, and a finger-probe pulse oximeter, respectively. A room microphone detected snoring, and an infrared camera recorded any changes in body position. Sleep stages were scored according to Rechtschaffen and Kales� guidelines [41]. 
Data Analyses 
	ADHD-C and ADHD-HI groups were combined for analysis (ADHD-C/HI) as research suggests few differences between these two subtypes/presentations. Independent samples t-tests were run to ensure that TD children and children with ADHD differed significantly on key behavioural variables (i.e., CPRS-R scores), but did not differ on the main demographic variables.
To determine whether there were differences in the sleep parameters between the children with ADHD and their TD peers, a between-subjects multivariate analysis of variance (MANOVA) was run, with (1) sleep onset latency (mins) and (2) total sleep time (mins) as dependent variables. A MANOVA was also used to determine whether the two groups differed on key sleep architecture variables, with sleep efficiency, latency to REM, number of REM periods, percent Stage 1, percent Stage 2, percent SWS, and percent REM as dependent variables. 
To determine whether there were differences in the sleep parameters of ADHD-C/HI and ADHD-I subtypes, a multivariate analysis of covariance (MANCOVA) was run, with all sleep parameters included as dependent variables. A MANCOVA was also used to determine whether ADHD-C/HI and ADHD-I subtypes differed on sleep architecture variables. 
Results 
	Demographic data for both groups are presented in Table 1. As expected, the ADHD and TD groups differed on parent-report ratings of ADHD symptomology, with ratings higher for children in the ADHD group. The two groups did not differ in mean age, or key family characteristics including SES, average household income or number of children in the household. Demographic data for ADHD-C/HI and ADHD-I subtypes are presented in Table 2. While the two subtypes did not differ in key family characteristics, the difference in age between subtypes approached significance (p = 0.06), with the ADHD-I group being older than ADHD-C/HI group.
Using Wilk�s Lambda, a MANOVA comparing sleep parameters of the ADHD and TD groups indicated that there was a significant impact of group on the dependent variables, V = 0.81, F(2, 47) = 5.58, p = 0.007 (Table 3). Children with ADHD took longer to fall asleep (Mean=47.24 min) than TD children (M=24.07 min) and slept less (M=466.01 min) than TD children (M=500.79 minutes). A MANOVA comparing sleep architecture variables did not reveal an effect for group, V = 0.86, F(7, 42) = 0.99, p = 0.45 (Table 3).
As the difference in age between ADHD-I and ADHD-C/HI subtypes approached significance, and given that there was more than a one year difference in age between these groups, MANCOVA analyses comparing sleep parameters and sleep architecture variables between the two subtypes included age as a covariate. Using Wilk�s Lambda, a MANCOVA comparing sleep parameters between the two subtypes failed to reveal a significant effect for group, V = 0.89, F(2,21) = 1.36, p = 0.28 (Table 4). Similarly, a MANCOVA comparing sleep architecture variables between ADHD-I and ADHD-C/HI subtypes also failed to reveal a significant effect for group, V = 0.90, F(7,16) = 0.26, p = 0.96 (Table 4).
Discussion
	The goal of the current study was to compare sleep parameters and sleep architecture variables between children with ADHD and their TD peers, as well as between children with different subtypes of ADHD. As hypothesized, results indicate that there were no differences in the sleep architecture of TD children and those with ADHD. Differences in sleep parameters between the two groups indicate that children in the ADHD group took longer to fall asleep and slept significantly less than TD children. Contrary to our hypothesis, the current study did not reveal any differences in sleep parameters or sleep architecture variables between ADHD subtypes. 
The results of the current study are in-line with previous research which suggests there are no differences in sleep architecture between children with ADHD and TD children [31]. Despite subjective evidence that children with ADHD have more difficulty with sleep than their TD peers [5], there does not appear to be a specific sleep architecture profile for these children. An avenue for future research in this area that may prove to be more fruitful is the examination of sleep microstructure (for example, the cyclic alternating pattern, which is a measure of arousal fluctuation and therefore, of unstable sleep) [42]. Prihodova and colleagues argue that the macrostructure of children�s sleep (e.g., REM, SWS) does not adequately measure the quality and function of sleep [43], as it often remains unchanged despite evidence of daytime sleepiness [44-45]. The authors also point out that an analysis of sleep microstructure is of particular importance when measuring the sleep of children, as children have a higher arousal threshold and therefore, arousals in children are less frequently associated with changes in sleep macrostructure when compared to adults [46-48]. While existing research of sleep microstructure in children with ADHD has produced null results [43], more research is needed before conclusions can be drawn. 
With regard to sleep parameters, it was found that children in the ADHD group took longer to fall asleep and slept significantly less than TD children. While this is not a finding that has been consistent across systematic reviews of sleep in children with ADHD, these results were reported by Cortese and colleagues when sleep was measured using actigraphy [27] and by Bullock and Schall in their review of 10 studies which measured sleep using PSG, actigraphy, and/or video recording [23]. Given the rigorous control exercised in the current study, it is likely that the results are accurate. Based on the cognitive-energetic model of ADHD [49] it seems plausible that children in the ADHD group took longer to fall asleep and slept less than their TD peers because of difficulty with psychophysiological arousal regulation. Specifically, children with ADHD likely have underlying issues with regulation of activity or arousal, which could also explain why these children woke earlier than their TD peers. It is possible that children with ADHD were unable to moderate their arousal levels, leading to them having difficulty falling asleep. Based on this interpretation, children with ADHD could experience an exacerbation of ADHD symptoms as sleep loss in children has been linked to difficulty with attention and attention regulation [50-51]. Therefore, the relationship between reduced sleep and attentional problems in children with ADHD is likely a vicious cycle.
The current study is the first known study to have objectively investigated differences in sleep between subtypes of children with ADHD (as defined by the DSM-IV-TR, but also consistent with DSM-5 presentations) using PSG, and it was hypothesized based on the work of Ramos Platon and colleagues [35] that children in the ADHD-C/HI group would have more sleep problems than those in the ADHD-I group. Contrary to expectations, the current study failed to find any differences in sleep parameters or architecture between ADHD subtypes. This finding suggests that while children with different presentations of ADHD vary with regard to their ADHD symptom presentation, their underlying sleep physiology may be comparable. While this finding was not expected, it is consistent with the findings of Wiggs and colleagues [36] and LeBourgeous and colleagues [37] who found no differences in sleep patterns between subtypes of ADHD using parental reports and/or actigraphy. Furthermore, LeBourgeous and colleagues also found no differences in sleep quality between subtypes [37]. 
	The current study had several limitations which must be noted. First, and most relevant to an interpretation of results, the analysis of PSG data was focused on sleep architecture variables and sleep parameters and variables such as nocturnal movement were not addressed. Other variables (e.g., stage shifts per hour, sleep microstructure) might also provide further information about how these groups might differ [27, 43]. Such variables will be addressed in future analyses. Second, PSG measures of sleep were taken from children�s first night in the sleep lab. Sleep is often affected during a participant�s first night in the sleep lab (known as the �first-night-effect�) therefore potentially making it unrepresentative of a given participant�s normal sleep [52]. However, for both groups it was their first night in the sleep lab. As well, research conducted using the current sample found that, based on actigraphy data, there were no differences in sleep between the TD and ADHD groups while at the sleep lab; rather, both groups slept less and had reduced wake after sleep onset while in the sleep lab compared to home [53]. Third, given that the children in the ADHD group in the current study were newly diagnosed with ADHD, stimulant medication-na�ve and free of chronic or impairing medical illness (e.g., diabetes) and/or co-morbid primary mental disorders (e.g., depression, anxiety), the generalizability of our results to the population of children with ADHD is likely limited given the high rate of comorbidity and treatment with stimulant medication [2]. 
The results of the current study suggest that there are no differences in sleep architecture between children with ADHD and their TD peers, as well as between ADHD subtypes. With regard to sleep parameters, the results of the current study indicate that children with ADHD, regardless of subtype, take longer to fall asleep and sleep less that TD children. This finding is important as it may help to explain some of the attentional problems experienced by children with ADHD, given that shorter sleep in children has been associated with difficulties with attention [50-51]. It is important that future studies of sleep in children with ADHD at least account for factors such as medication status and comorbid psychiatric problems, as such factors likely have a significant impact on sleep and could lead researchers to draw invalid conclusions regarding differences in sleep between children with ADHD and their TD peers. Future studies of sleep in children with different presentations of ADHD should investigate variables such as nocturnal movement and daytime sleepiness. Findings related to differences in sleep between TD children and those with ADHD, as well as between children with different subtypes of ADHD, would have significant clinical implications with regard to how sleep is assessed in children with ADHD and how problems with sleep are addressed.




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Table 1
Demographic Characteristics of ADHD and TD Children
ADHD group
(n=25, 22 male, 3 female)TD group 
(n=25, 22 male, 
3 female)MeasureM (SD)M (SD)tpAge (months)105.72 (22.57)103.92 (21.07)0.290.77Children in Household2.24 (0.83)2.50 (1.00)1.070.29Socioeconomic Status (SES)a62.46 (21.84)63.94 (15.41)0.280.78Family Incomeb5.60 (3.10)6.60 (2.96)1.170.25CPRS score73.32 (8.11)47.17 (7.06) 11.860.01
Note. CPRS = Conners� Parent Ratings Scale.
aIndicates average parental value for Hollingshead Socioeconomic (SES)
bFamily Income was reported by parents according to nominal scale where a value of 1 = <$20,000, 2 = 21,000-$30,000, 3 = $31,000-$40,000, 4 = $41,000-$50,000, 5 = $51,000-$60,000, 6 = $61,000-$70,000, 7 = $71,000-$80,000, 8 = $81,000-$90,000, 9 = $91,000-$100,000, 10 = $100,000+








Table 2
Demographic Characteristics of ADHD-I and ADHD-C/HI Groups
ADHD-I group
(n=12, 11 male, 1 female)ADHD-C/HI group
(n=13, 11 male, 
2 female)MeasureM (SD)M (SD)F-valuepAge (months)114.33 (24.22)97.77 (18.38)3.750.06Children in Household2.25 (0.86)2.23 (0.83)0.030.96Socioeconomic Status (SES)a66.50 (20.72)58.73 (23.01)0.780.39Family Incomeb6.33 (2.64)4.92 (3.42)1.310.26
aIndicates average parental value for Hollingshead Socioeconomic (SES)
bFamily Income was reported by parents according to nominal scale where a value of 1 = <$20,000, 2 = 21,000-$30,000, 3 = $31,000-$40,000, 4 = $41,000-$50,000, 5 = $51,000-$60,000, 6 = $61,000-$70,000, 7 = $71,000-$80,000, 8 = $81,000-$90,000, 9 = $91,000-$100,000, 10 = $100,000+










Table 3
Sleep Parameters and Sleep Architecture of ADHD and TD Children
ADHD groupTD groupMeasureM (SD)M (SD)pSleep Parameters     Sleep Onset Latency (minutes)47.24 (38.61)24.07 (14.01)0.007**0.14     Sleep Duration (minutes)466.01 (69.01)500.79 (50.43)0.047*0.08Sleep Architecture      Sleep Efficiency (%)84.06 (9.13)84.46 (6.37)0.860.001     Latency to REM138.44 (59.31)131.86 (47.17)0.670.004     Number of REM Periods4.72 (1.31)4.72 (0.93)1.000.000     Percent of Stage 15.78 (2.66)4.99 (2.15)0.250.03     Percent of Stage 243.68 (9.2)45.44 (8.84)0.490.01     Percent of SWS27.79 (9.16)28.44 (8.6)0.800.001     Percent of REM22.71 (5.21)21.08 (3.92)0.220.03
* p < .05
** p < .01






Table 4
Sleep Parameters and Sleep Architecture of ADHD-I and ADHD-C/HI Groups
ADHD-I groupADHD-C/HI groupMeasureM (SD)M (SD)pSleep Parameters     Sleep Onset Latency (minutes)39.32 (28.62)54.54 (45.93)0.110.11     Sleep Duration (minutes)443.84 (81.11)486.47 (50.51)0.580.01Sleep Architecture      Sleep Efficiency (%)83.51 (8.33)84.51 (10.00)0.610.01     Latency to REM148.23 (63.56)130.75 (56.95)0.510.02     Number of REM Periods4.36 (1.36)5.00 (1.24)0.550.02     Percent of Stage 16.39 (3.31)5.31 (2.03)0.400.03     Percent of Stage 247.91 (8.53)40.36 (8.57)0.290.05     Percent of SWS24.57 (9.48)30.32 (8.36)0.490.02     Percent of REM21.11 (6.56)23.96 (3.62)0.310.05








ADHD SLEEP PARAMETERS AND ARCHITECTURE	 PAGE   \* MERGEFORMAT 21


Running head: ADHD SLEEP PARAMETERS AND ARCHITECTURE	 PAGE   \* MERGEFORMAT 1




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