Sleep was successfully monitored by actigraphy for 7 days in 18 children (15 boys, aged 9.4 ± 1.7 years, 88.9% Caucasian, 11.1% mixed ethnicity) at mid-duration of the summer camp program. Two Actiwatch recordings were corrupted, two Actiwatches were damaged, and two children discontinued wearing the watch. All children were taking one or multiple medications, ie, 50% stimulants, 28.6% stimulants combined with antihypertensive drugs, 14.3% mood stabilizers or antidepressants, and 7.1% other nonstimulant medication. Categorized on parent-reported diagnosis, the group comprised seven ADHD, eight ADHD with comorbidity, and three children with cognitive disorders not otherwise specified, nonverbal learning disability, and autism. The children had a mean BMI z score of -0.10 (standard deviation 1.49) Fifteen children were of normal weight, whereas two were overweight and one was obese.
During the study, the children slept for an average of 6 hours and 58 minutes with a variability of one hour 3 minutes relative to the mean (). On average, the children were awake for about 2 hours per night, with a variability of one hour. Sleep patterns showed 33% restlessness (ie, the sum of the percentage mobile and the percentage immobile bouts of <one minute in duration to the number of immobility bouts for the given interval), with no differences between weekdays and weekend. These were “typical” nights as reported by 66.7% of the parents. Because the cohort was a heterogeneous group, we performed secondary analyses to explore the variance in sleep schedules (). A proportion of total variance in the sleep schedule parameters was due to differences between the children (, shown in black), yet no variation could be ascribed to the diagnostic category. Alternatively, substantial variance was due to daily differences within each child (, shown in gray). In other words, bedtime did not differ greatly in the sample (or between the children, 9% variance), but daily differences within each child were apparent (90% variance, ). About 40% of the variance in wakeup time, time in bed, sleep onset latency, wake after sleep onset (WASO), and wake after sleep end was ascribable to differences between children, but could also be ascribed to daily differences within each child (, shown in grey). Part of the variance in wakeup time was solely due to the day of the week (bars, ie, 19%). In general, 50% or more of the variance in the sleep schedule was due to daily differences within the same child.
Sleep schedules, mean (hours:minutes) and variability relative to mean.
Variance in sleep schedules in children with attention deficit hyperactivity disorder and comorbid problems.
Sleep hygiene and bedtime routines
Given the substantial variability in sleep patterns, we tested if children’s sleep schedules were predicted by family sleep hygiene practices (CSHS) and bedtime routines (BRQ). The average total sleep hygiene score was 4.5 ± 0.5 (range 3.2–5.2). On the BRQ, the average subscale scores were for consistency (10 items) 40.2 ± 6.2, reactivity (5 items) 10.1 ± 5.2, and activities (16 items) 50.8 ± 6.8 (adaptive 37.8 ± 5 and maladaptive 13.1 ± 4). When compared with the values in the BRQ paper,33
our sample had significantly fewer activities [t(17) = −4.0, P
< 0.001 and t(17) = −3.6, P
< 0.01, respectively].
Better physiological hygiene (CSHS) such as drinking fewer caffeinated drinks or other liquids, feeling less hungry, reduced rough playing (β 0.8, P = 0.01), and good bedtime reactivity (BRQ, ie, the same order, place, person, and activity as bedtime routine; β 0.9, P = 0.03) significantly predicted longer mean time in bed. Additionally, the time in bed was less variable when adaptive activities (BRQ) such as bedtime hugs, being tucked in, brushing teeth, putting on pajamas, were present (β −0.8, P = 0.03). Physiological and environmental hygiene (ie, no noise, light, comfortable room, and bed CSHS) was beneficial towards mean sleep onset latency (ie, β −0.9, P = 0.04 and β 0.6, P = 0.01, respectively). Finally, performing adaptive activities decreased the variability in restlessness during sleep or sleep fragmentation (β −1.1, P = 0.01).
From parental reports, falling asleep was often a problem for 61% of the children, whereas in 39% it sometimes was a problem during the week of recording; 22% and 56% had problems often or sometimes with awakenings, respectively. Parental reports further indicated that 22% (often) and 61% (sometimes) of the children were somnolent. Snoring was highly prevalent (50% often and 44% sometimes). Enuresis was also very frequent (ie, 28% often and 28% sometimes), while restless sleep occurred often in 33% and sometimes in 56% of the children.
Children’s reporting of sleep complaints corroborated the difficulty in falling asleep (coefficient of concordance 0.40, P < 0.05; 50% often, 39% sometimes). Notwithstanding, the children also reported awakenings (39% often and 44% sometimes) and somnolence (28% often and 50% sometimes).
Food and drinking patterns
Daily food patterns () were characterized by bread, cereals, and starches (71%), red meat (57%), fruits (64%), desserts and snacks (36%), and juices (36%). Less frequent food patterns were white meat (50%), fast food meals (64%), and soft drinks.
Food patterns (%) in children with attention deficit hyperactivity disorder and comorbid problems.
Overall, during the week of recording, children at bedtime had an average score on the Sleepiness Scale of 2.87 ± 1.6 (0–5.58). Self-reported sleepiness at bedtime varied in nearly equal amounts between children (54.1% variance) as within any given child per day (variance 45.2%, variance ascribed to day 0.7%). However, more daily variation was seen within each child in the morning (64% variance) and the evening (65.6% variance), which concurs with the hypoarousal hypothesis (ie, the remaining percentage of variance can be attributed to the child). Average sleepiness at 8:30 am was 1.56 ± 1.1 and at 3:40 pm was 1.81 ± 1.35. Children became significantly more sleepy towards the end of the day [F(3,14) = 25.3, P = 0.00001].
Self-reported sleepiness at bedtime was unrelated to any of the sleep schedule parameters, except for Monday, ie, sleepiness was positively related to the sleep efficiency index (Spearman r = 0.67, P<0.01), to total sleep time (Spearman r = 0.53, P < 0.05) and inversely to restlessness (Spearman r = −0.54, P < 0.05). Children’s sleepiness at the beginning of the camp day was unrelated to their sleep schedules. However, sleepiness at the end of the day was correlated with sleep onset latency, sleep duration, immobile time, and wakeup time. More specifically, shorter mean sleep onset latency (Spearman r = −0.48, P < 0.05) and less variability (Spearman r = −0.47, P < 0.05) were associated with more sleepiness at 3:40 pm. The more variable total sleep time (Spearman r = 0.51, P < 0.05), wakeup time (Spearman r = 0.48, P < 0.05) and immobile time (Spearman r = 0.54, P < 0.05), the more sleepy the child felt at the end of the camp day.
Associations: sleepiness, sleep, and food patterns
Shared variance was assessed between the “sleepiness-BMI” set, ie, at bedtime, 8:30 am and 3:40 pm, and was also separately assessed with other sets of variables. No associations were found for the bedtime routines subscales set [Chi²(20) = 28.3, P = 0.10] and sleep hygiene subscales sets [Chi²(24) = 26.1, P = 0.35]. Nevertheless, the sleepiness-BMI set was associated with the following sleep schedules (ie, mean and variability per parameter) and food patterns sets. The sleepiness-BMI set shared 76% of variance with mean WASO and WASO variability [Chi²(8) = 17.3, P = 0.02]. More specifically, this shared variance can be attributed to the strong association between BMI and mean WASO (r = 0.53, or correlation of these variables in the sleepiness-BMI set and WASO set) and WASO variability being moderately associated with bedtime sleepiness (r = −0.35). No other associations with the sleepiness-BMI set were found regarding sleep pattern parameters: sleep onset latency set, Chi²(8) = 13.2, P = 0.11; total sleep time set, Chi²(8) = 7.3, P = 0.51; wake after sleep end set, Chi²(8) = 5.9, P = 0.66; time in bed set, Chi²(8) = 6.1, P = 0.63; sleep efficiency index set, Chi²(8) = 14.2, P = 0.08; and restlessness set, Chi²(8) = 6.6, P = 0.58. Furthermore, parental report of sleep problems as discussed above showed no association [Chi²(18) = 6.4, P = 0.99].
Regarding food patterns, the sleepiness-BMI set shared 97% of variance with the food patterns set [Chi²(28) = 41.7, P = 0.03]. Namely, desserts/snacks (r = 0.49) and fast food (r = 0.48) were associated with increased sleepiness at the start of the day (8:30 am). Sleepiness at the end of the day (3:40 pm) was inversely associated with red meat (r = −0.52), white meat (r = −0.39), and vegetables (r = −0.33) but positively associated with breads, cereals and starches (r = 0.31). Sleepiness at bedtime was inversely associated with red meat (r = −0.35). BMI was only moderately associated with desserts/snacks (r = 0.35), red meat (r = 0.33), and vegetables (r = 0.31), and the remainder were small (r < 0.3). No associations were found for drinks [Chi²(12) = 17.3, P = 0.14].