What Sleep Patterns Reveal About Mental Health: A Look at New Research

Sleep disorders are one of the most commonly self-reported comorbidities of adults with ADHD, affecting 50 to 70 percent of them. A team of British researchers set out to see whether this association could be further confirmed with objective sleep measures, using cognitive function tests and electroencephalography (EEG).

Measured as theta/beta ratio, EEG slowing is a widely used indicator in ADHD research. While it occurs normally in non-ADHD adults at the conclusion of a day, during the day it signals excessive sleepiness, whether from obstructive sleep apnea or from neurodegenerative and neurodevelopmental disorders. Coffee reverses EEG slowing, as do ADHD stimulant medications.

Study participants were either on stable treatment with ADHD medication (stimulant or non-stimulant medication), or on no medication. Participants had to refrain from taking any stimulant medications for at least 48 hours prior to taking the tests. Persons with IQ below 80 or with recurrent depression or undergoing a depressive episode were excluded.

The team administered a cognitive function test, The Sustained Attention to Response Task (SART). Observers rated on-task sleepiness using videos from the cognitive testing sessions. They wired participants for EEG monitoring.

Observer-rated sleepiness was found to be moderately higher in the ADHD group than in controls. Although sleep quality was slightly lower in the sleepy group than in the ADHD group, and symptom severity slightly greater in the ADHD group than the sleepy group, neither difference was statistically significant, indicating extensive overlap.

Omission errors in the SART were strongly correlated with sleepiness level, and the strength of this correlation was independent of ADHD symptom severity. EEG slowing in all regions of the brain was more than 50 percent higher in the ADHD group than in the control group and was highest in the frontal cortex.

Treating the sleepy group as a third group, EEG slowing was highest for the ADHD group, followed closely by the sleepy group, and more distantly by the neurotypical group. The gaps between the ADHD and sleepy groups on the one hand, and the neurotypical group on the other, were both large and statistically significant, whereas the gap between the ADHD and sleepy groups was not. EEG slowing was both a significant predictor of ADHD and of ADHD symptom severity.

The authors concluded, These findings indicate that the cognitive performance deficits routinely attributed to ADHD  are largely due to on-task sleepiness and not exclusively due to ADHD symptom severity. We would like to propose a simple working hypothesis that daytime sleepiness plays a major role in cognitive functioning of adults with ADHD. As adults with ADHD are more severely sleep deprived compared to neurotypical control subjects and are more vulnerable to sleep deprivation, in various neurocognitive tasks they should manifest larger sleepiness-related reductions in cognitive performance. One clear testable prediction of the working hypothesis would be that carefully controlling for sleepiness, time of day and/or individual circadian rhythms, would result in substantial reduction in the neurocognitive deficits in replications of classic ADHD studies.

A team of Spanish researchers performed a systematic search of the medical literature and found 28 studies that could be included in a series of meta-analyses of specific measures of sleep impairment. Except for a single meta-analysis with eight studies and 1,713 participants, however, all involved just three to five studies apiece, with anywhere from 121 to just over a thousand participants.

The team examined three sorts of measures:

·        Subjective measures, based on self-reporting by ADHD patients.
·        Polysomnography is an objective sleep study in which the subject is wired up and studied by technicians in a lab, usually overnight, monitoring multiple body functions, such as brain activity, eye movements, muscle activation, and heart rhythm.
·        Actigraphy, a non-invasive objective means of monitoring sleep. The subject wears an actimetry monitor, which is usually worn like a wristwatch on the non-dominant arm. Because it is minimally intrusive, the subject may wear it for a week or more while engaging in normal activities.

In the subjective measures, adults with ADHD generally reported substantially higher sleep impairments than non-ADHD controls. In the largest meta-analysis, covering eight studies and 1,713 participants, adults with ADHD reported moderately longer latency times for falling asleep than controls. In meta-analyses of five studies with between 834 and 1,130 participants, they also reported moderately poorer sleep quality, more frequent night awakenings, being moderately less rested upon awakening in the morning, and moderate-to-strongly greater daytime sleepiness. There was no significant difference in perceived sleep duration.

Polysomnography measures, on the other hand, failed to confirm these subjective impressions. No significant differences were found between adults with ADHD and controls for the initial latency period until onset of sleep, sleep efficiency, waking after the onset of sleep, total sleep time, stage one or stage two sleep, slow-wave sleep, REM (rapid eye movement) sleep, and latency period until REM sleep.

As mentioned above, polysomnography is conducted in lab settings, and therefore inevitably diverges from normal patterns of behavior. Actigraphy helps bridge that gap, by monitoring normal behavior, though with more limited types and precision of data analysis.

And indeed, a meta-analysis of four studies with 222 participants confirmed self-reports that sleep efficiency was moderate to strongly lower in adults with ADHD and that the latency period until the onset of sleep was markedly longer. On the other hand, it found no significant difference in true sleep.

The researchers also looked at prevalence statistics. Whereas the prevalence of sleep-onset insomnia in the general population has been reported in the range of 13 to 15 percent, a meta-analysis of four studies with 466 participants found fully two-thirds of adults with ADHD reporting insomnia, a greater than four-to-one ratio. Similarly, a meta-analysis of three studies with 458 participants found one-third reporting daytime sleepiness, which is twice the rate reported in the general population.

There was no sign of publication bias in any of these results. The authors cautioned, however, about the small number of studies involved, stating this "compromises the generalizability of the findings." Also, some studies included patients undergoing pharmacological treatment for ADHD, "increasing the risk of confounding results."

Moreover, "Sleep onset latency and sleep efficiency were not significantly impaired in the polysomnography, which was incongruent with the actigraphy results. This may be due to a difference in the evaluation context. Whereas polysomnography is considered the gold-standard measure to objectively assess sleep architecture, actigraphy shows a more ecological approach, with the evaluation being conducted in a more naturalistic context for a longer period. However, actigraphy has more environmental influence, which can compromise the data recorded and the interpretation of the results, whereas, in polysomnography, multiple variables can be controlled in the laboratory setting to increase the internal validity of the results. On the contrary, polysomnography studies can produce artifacts due to the unusual circumstances in the setting, so results may need to be interpreted with caution."

The authors concluded, "The results found in the present study show the relevance of addressing sleep concerns in adult populations diagnosed with neurodevelopmental conditions."

We are only beginning to explore how ADHD affects sleep in adults. A team of European researchers recently published the first meta-analysis on the subject, drawing on thirteen studies with 1,439 participants. They examined both subjective evaluations from sleep questionnaires and objective measurements from actigraphy and polysomnography. However, due to differences among the studies, only two to seven could be combined for any single topic, generally with considerably fewer participants (88 to 873).

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Several patterns emerged. Looking at results from sleep questionnaires, they found that adults with ADHD were far more likely to report general sleep problems (very large SMD effect size 1.55). Getting more specific, they were also more likely to report frequent night awakenings(medium effect size 0.56), taking longer to get to sleep (medium-to-large effect size 0.67), lower sleep quality (medium-to-large effect size 0.69), lower sleep efficiency (medium effect size 0.55), and feeling sleepy during the daytime(large effect size 0.75).

There was little to no sign of publication bias, though considerable heterogeneity on all but night awakenings and sleep quality.

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Actigraphy readings confirmed some subjective reports. On average, adults with ADHD took longer to get to sleep (large effect size 0.80) and had lower sleep efficiency (medium-to-large effect size 0.68). They also spent more time awake (small-to-medium effect size 0.40). There was little to no sign of publication bias and there was little heterogeneity among studies.

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None of the polysomnography measurements, however, found any significant differences between adults with and without ADHD. All effect sizes were small (under 0.20), and none came close to being statistically significant.

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There were four instances where measurement criteria overlapped those from actigraphy and self-reporting, with varying degrees of agreement and divergence. There was no significant difference in total sleep time, matching findings from both the questionnaires and actigraphy. On percent time spent awake, polysomnography found little to no effect size with no statistical significance, whereas actigraphy found a small-to-medium effect size that did not quite reach significance, and self-reporting came up with a medium effect size that was statistically significant. Sleep onset latency and sleep efficiency, for which questionnaires and actigraphy found medium-to-large effects, the polysomnography measurements found little to none, with no statistical significance.

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Polysomnography found no significant differences in stage 1-sleep, stage 2-sleep, slow-wave sleep, and REM sleep. Except for slow-wave sleep, there was no sign of publication bias. Heterogeneity was generally minimal.

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One problem with the extant literature is that many studies did not take medication status into account.

The authors concluded, "future studies should be conducted in medicatio- naïve samples of adults with and without ADHD matched for comorbid psychiatric disorders and other relevant demographic variables."

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In summary, these findings provide robust evidence that ADHD adults report a variety of sleep problems.  In contrast, objective demonstrations of sleep abnormalities have not been consistently demonstrated.   More work in medication-naïve samples is needed to confirm these conclusions.