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Study links sleep and objective, subjective cognition
CHARLOTTE, N.C. – , preliminary findings from a pilot study of objective and subjective cognitive measures have shown.
The pilot study underscored the important role of objective sleep measures to better understand discrepancies when patients’ own reports of everyday cognitive function don’t align with objective cognitive profiles, Amy Costa, MA, a graduate student in psychology at the University of Missouri-Columbia, said in reporting the results at the annual meeting of the Associated Professional Sleep Societies.
“Between our previously published paper and these new pilot results, we’re reporting evidence that suggests sleep is playing a role between the objective and subjective cognition relationship,” Ms. Costa said in an interview. “It is possible that these older adults who are sleeping poorly may be worse at understanding how well they’re doing cognitively. That’s really important for doctors. For example, if we can’t diagnose someone with mild cognitive impairment or Alzheimer’s disease or other types of dementia earlier, then we can’t intervene as quickly.”
Sleep efficiency, cognition, and patient complaints
These findings are in agreement with those Ms. Costa and colleagues recently published in the Journal of Clinical Sleep Medicine, she said.
The current pilot study included 35 older adults with an average age of 69 years who had insomnia complaints. They completed one night of home-based polysomnography – specifically with the Sleep Profiler PSG2TM – and a battery of cognitive tests. Their average sleep deficiency was 57%, “indicating potentially pretty severe insomnia,” Ms. Costa said.
“We found that sleep efficiency – that is the percentage of time spent sleeping while in bed – moderated the association between self reports and objective measures of cognitive distractibility,” Ms. Costa said in reporting the results. “In other words, our findings suggest that individuals with lower sleep efficiency who are performing the worst cognitively have the least amount of complaints. Basically, this can be thought of as that they are overestimating their cognitive performance.”
Sleep stage versus working memory and distractibility
The pilot study also focused on how the percentage of lighter-stage sleep, or N1 sleep, moderated the associations between working memory, as measured by Sternberg performance, and memory, distractibility, and blunders measured with the Cognitive Failures Questionnaire.
At the highest percentage of N1 sleep, worse working memory was associated with fewer complaints about memory, distractibility, and blunders, Ms. Costa said.
“The percentage of lighter-stage N1 sleep and sleep efficiency moderated the association between cognitive flexibility and distractibility,” Ms. Costa said. At the lowest percentage of N1 sleep, worse cognitive flexibility was associated with more distractibility, while at the highest percentage of N1 sleep worse cognitive flexibility showed a reverse effect; it was linked to less distractibility. The lowest percentage of sleep efficiency showed an association between worse cognitive flexibility and less distractibility, but the highest percentage of SE showed an association between worse cognitive flexibility and more distractibility.
“So in terms of evaluating their cognitive performance, the worse working memory was associated with more blunder complaints in individuals with the lowest percentage of N1,” she said. “So whenever individuals were spending less time in N1, they were able to better recognized their cognitive ability.”
She added, “Overall, more light and more fragmented sleep moderated the association between worse objective and less cognitive complaints, suggesting that these individuals might be overestimating their cognitive abilities.”
The findings indicate that evaluation of objective sleep should consider objectively measured N1 and sleep efficiency to better understand when subjective cognitive complaints and neurophysiological/objective cognitive profiles don’t align, she said.
Important indicators of cognitive deficits
“Specifically, for an older adult who comes into the clinic with complaints of waking up during the night, low sleep efficiency and more lighter-stage sleep might be really important indicators that they are probably not going to be the best at identifying their cognitive abilities or deficits,” she said.
Future directions for this research include collecting more data and looking at other sleep measures, such as using rapid-eye movement sleep, as potential moderators for the relationship between cognitive outcomes, evaluating sleep architecture more closely, and evaluating outcomes in a longitudinal study, Ms. Costa said.
The importance of objectively measured sleep
“Studies like this one using objectively measured sleep are important because much of the prior literature relied on self-reported sleep measures,” said Brendan P. Lucey, MD, associate professor of neurology and head of the sleep medicine section at Washington University School of Medicine in St. Louis. “This study suggests how objectively measured sleep may mediate discrepancies in objective/subjective cognitive dysfunction. Future studies need to work out if we need to add objective sleep measures when evaluating cognitive complaints in older adults.”
Dr. Lucey, who was not involved in the study, voiced one concern with the pilot study methodology the future research should address: the use of the Sleep Profiler PSG2TM to measure N1 sleep, which, as he noted, records a single-channel electroencephalogram over the forehead. “Scoring N1 sleep relies on attenuation of the alpha rhythm over the occipital region and the Sleep Profiler is not as accurate as in-lab polysomnography for this sleep stage,” he said.
The pilot study received funding from the American Academy of Sleep Medicine Foundation. Ms. Costa and her coauthors have no disclosures. Dr. Lucey disclosed relationships with Merck, Eli Lilly, Eisai, and Beacon Biosignals.
CHARLOTTE, N.C. – , preliminary findings from a pilot study of objective and subjective cognitive measures have shown.
The pilot study underscored the important role of objective sleep measures to better understand discrepancies when patients’ own reports of everyday cognitive function don’t align with objective cognitive profiles, Amy Costa, MA, a graduate student in psychology at the University of Missouri-Columbia, said in reporting the results at the annual meeting of the Associated Professional Sleep Societies.
“Between our previously published paper and these new pilot results, we’re reporting evidence that suggests sleep is playing a role between the objective and subjective cognition relationship,” Ms. Costa said in an interview. “It is possible that these older adults who are sleeping poorly may be worse at understanding how well they’re doing cognitively. That’s really important for doctors. For example, if we can’t diagnose someone with mild cognitive impairment or Alzheimer’s disease or other types of dementia earlier, then we can’t intervene as quickly.”
Sleep efficiency, cognition, and patient complaints
These findings are in agreement with those Ms. Costa and colleagues recently published in the Journal of Clinical Sleep Medicine, she said.
The current pilot study included 35 older adults with an average age of 69 years who had insomnia complaints. They completed one night of home-based polysomnography – specifically with the Sleep Profiler PSG2TM – and a battery of cognitive tests. Their average sleep deficiency was 57%, “indicating potentially pretty severe insomnia,” Ms. Costa said.
“We found that sleep efficiency – that is the percentage of time spent sleeping while in bed – moderated the association between self reports and objective measures of cognitive distractibility,” Ms. Costa said in reporting the results. “In other words, our findings suggest that individuals with lower sleep efficiency who are performing the worst cognitively have the least amount of complaints. Basically, this can be thought of as that they are overestimating their cognitive performance.”
Sleep stage versus working memory and distractibility
The pilot study also focused on how the percentage of lighter-stage sleep, or N1 sleep, moderated the associations between working memory, as measured by Sternberg performance, and memory, distractibility, and blunders measured with the Cognitive Failures Questionnaire.
At the highest percentage of N1 sleep, worse working memory was associated with fewer complaints about memory, distractibility, and blunders, Ms. Costa said.
“The percentage of lighter-stage N1 sleep and sleep efficiency moderated the association between cognitive flexibility and distractibility,” Ms. Costa said. At the lowest percentage of N1 sleep, worse cognitive flexibility was associated with more distractibility, while at the highest percentage of N1 sleep worse cognitive flexibility showed a reverse effect; it was linked to less distractibility. The lowest percentage of sleep efficiency showed an association between worse cognitive flexibility and less distractibility, but the highest percentage of SE showed an association between worse cognitive flexibility and more distractibility.
“So in terms of evaluating their cognitive performance, the worse working memory was associated with more blunder complaints in individuals with the lowest percentage of N1,” she said. “So whenever individuals were spending less time in N1, they were able to better recognized their cognitive ability.”
She added, “Overall, more light and more fragmented sleep moderated the association between worse objective and less cognitive complaints, suggesting that these individuals might be overestimating their cognitive abilities.”
The findings indicate that evaluation of objective sleep should consider objectively measured N1 and sleep efficiency to better understand when subjective cognitive complaints and neurophysiological/objective cognitive profiles don’t align, she said.
Important indicators of cognitive deficits
“Specifically, for an older adult who comes into the clinic with complaints of waking up during the night, low sleep efficiency and more lighter-stage sleep might be really important indicators that they are probably not going to be the best at identifying their cognitive abilities or deficits,” she said.
Future directions for this research include collecting more data and looking at other sleep measures, such as using rapid-eye movement sleep, as potential moderators for the relationship between cognitive outcomes, evaluating sleep architecture more closely, and evaluating outcomes in a longitudinal study, Ms. Costa said.
The importance of objectively measured sleep
“Studies like this one using objectively measured sleep are important because much of the prior literature relied on self-reported sleep measures,” said Brendan P. Lucey, MD, associate professor of neurology and head of the sleep medicine section at Washington University School of Medicine in St. Louis. “This study suggests how objectively measured sleep may mediate discrepancies in objective/subjective cognitive dysfunction. Future studies need to work out if we need to add objective sleep measures when evaluating cognitive complaints in older adults.”
Dr. Lucey, who was not involved in the study, voiced one concern with the pilot study methodology the future research should address: the use of the Sleep Profiler PSG2TM to measure N1 sleep, which, as he noted, records a single-channel electroencephalogram over the forehead. “Scoring N1 sleep relies on attenuation of the alpha rhythm over the occipital region and the Sleep Profiler is not as accurate as in-lab polysomnography for this sleep stage,” he said.
The pilot study received funding from the American Academy of Sleep Medicine Foundation. Ms. Costa and her coauthors have no disclosures. Dr. Lucey disclosed relationships with Merck, Eli Lilly, Eisai, and Beacon Biosignals.
CHARLOTTE, N.C. – , preliminary findings from a pilot study of objective and subjective cognitive measures have shown.
The pilot study underscored the important role of objective sleep measures to better understand discrepancies when patients’ own reports of everyday cognitive function don’t align with objective cognitive profiles, Amy Costa, MA, a graduate student in psychology at the University of Missouri-Columbia, said in reporting the results at the annual meeting of the Associated Professional Sleep Societies.
“Between our previously published paper and these new pilot results, we’re reporting evidence that suggests sleep is playing a role between the objective and subjective cognition relationship,” Ms. Costa said in an interview. “It is possible that these older adults who are sleeping poorly may be worse at understanding how well they’re doing cognitively. That’s really important for doctors. For example, if we can’t diagnose someone with mild cognitive impairment or Alzheimer’s disease or other types of dementia earlier, then we can’t intervene as quickly.”
Sleep efficiency, cognition, and patient complaints
These findings are in agreement with those Ms. Costa and colleagues recently published in the Journal of Clinical Sleep Medicine, she said.
The current pilot study included 35 older adults with an average age of 69 years who had insomnia complaints. They completed one night of home-based polysomnography – specifically with the Sleep Profiler PSG2TM – and a battery of cognitive tests. Their average sleep deficiency was 57%, “indicating potentially pretty severe insomnia,” Ms. Costa said.
“We found that sleep efficiency – that is the percentage of time spent sleeping while in bed – moderated the association between self reports and objective measures of cognitive distractibility,” Ms. Costa said in reporting the results. “In other words, our findings suggest that individuals with lower sleep efficiency who are performing the worst cognitively have the least amount of complaints. Basically, this can be thought of as that they are overestimating their cognitive performance.”
Sleep stage versus working memory and distractibility
The pilot study also focused on how the percentage of lighter-stage sleep, or N1 sleep, moderated the associations between working memory, as measured by Sternberg performance, and memory, distractibility, and blunders measured with the Cognitive Failures Questionnaire.
At the highest percentage of N1 sleep, worse working memory was associated with fewer complaints about memory, distractibility, and blunders, Ms. Costa said.
“The percentage of lighter-stage N1 sleep and sleep efficiency moderated the association between cognitive flexibility and distractibility,” Ms. Costa said. At the lowest percentage of N1 sleep, worse cognitive flexibility was associated with more distractibility, while at the highest percentage of N1 sleep worse cognitive flexibility showed a reverse effect; it was linked to less distractibility. The lowest percentage of sleep efficiency showed an association between worse cognitive flexibility and less distractibility, but the highest percentage of SE showed an association between worse cognitive flexibility and more distractibility.
“So in terms of evaluating their cognitive performance, the worse working memory was associated with more blunder complaints in individuals with the lowest percentage of N1,” she said. “So whenever individuals were spending less time in N1, they were able to better recognized their cognitive ability.”
She added, “Overall, more light and more fragmented sleep moderated the association between worse objective and less cognitive complaints, suggesting that these individuals might be overestimating their cognitive abilities.”
The findings indicate that evaluation of objective sleep should consider objectively measured N1 and sleep efficiency to better understand when subjective cognitive complaints and neurophysiological/objective cognitive profiles don’t align, she said.
Important indicators of cognitive deficits
“Specifically, for an older adult who comes into the clinic with complaints of waking up during the night, low sleep efficiency and more lighter-stage sleep might be really important indicators that they are probably not going to be the best at identifying their cognitive abilities or deficits,” she said.
Future directions for this research include collecting more data and looking at other sleep measures, such as using rapid-eye movement sleep, as potential moderators for the relationship between cognitive outcomes, evaluating sleep architecture more closely, and evaluating outcomes in a longitudinal study, Ms. Costa said.
The importance of objectively measured sleep
“Studies like this one using objectively measured sleep are important because much of the prior literature relied on self-reported sleep measures,” said Brendan P. Lucey, MD, associate professor of neurology and head of the sleep medicine section at Washington University School of Medicine in St. Louis. “This study suggests how objectively measured sleep may mediate discrepancies in objective/subjective cognitive dysfunction. Future studies need to work out if we need to add objective sleep measures when evaluating cognitive complaints in older adults.”
Dr. Lucey, who was not involved in the study, voiced one concern with the pilot study methodology the future research should address: the use of the Sleep Profiler PSG2TM to measure N1 sleep, which, as he noted, records a single-channel electroencephalogram over the forehead. “Scoring N1 sleep relies on attenuation of the alpha rhythm over the occipital region and the Sleep Profiler is not as accurate as in-lab polysomnography for this sleep stage,” he said.
The pilot study received funding from the American Academy of Sleep Medicine Foundation. Ms. Costa and her coauthors have no disclosures. Dr. Lucey disclosed relationships with Merck, Eli Lilly, Eisai, and Beacon Biosignals.
AT SLEEP 2022
Snoring may lead to a sedentary lifestyle
“People who snore are also likely to have sleep apnea, but those who snore and don’t have sleep apnea are a largely understudied group,” senior author Michael Grandner, PhD, told this news organization.
“We found that even just snoring alone can impact health and well-being,” said Dr. Grandner, director of the sleep and health research program at the University of Arizona, Tucson.
The findings were presented at the annual meeting of the Associated Professional Sleep Societies.
A viscous cycle
Frequent snoring can signal sleep-disordered breathing, which is associated with a myriad of comorbidities, including increased risk for cardiovascular disease.
Prior studies have shown that sleep-disordered breathing is associated with less physical activity, but few studies have examined this at the population level or in relation to primary snoring.
Dr. Grandner and colleagues evaluated the relationship between snoring frequency and minutes of sedentary activity using 3 years’ worth of data from the National Health and Nutrition Examination Survey. Participants reported snoring frequency and sedentary activity.
After adjusting for sex, age, race, education level, and marital status, adults who were frequent snorers (5+ nights per week) spent about 36 more minutes per day sedentary, compared with peers who reported never snoring.
In addition, those individuals who were determined to be at increased risk of having sleep apnea had about 54 more minutes per day of sedentary time in the adjusted model.
“Snoring is very common, and it doesn’t just affect the nighttime,” said Dr. Grandner.
Snoring can lead to “more tiredness and less energy, which can impact everything from mood to stress to – as we saw – activity level,” he noted.
Commenting on the results for this news organization, Raman Malhotra, MD, of the Washington University Sleep Center in St. Louis, said this study clearly demonstrates how people who snore and people who are at risk for sleep apnea are more sedentary.
This could explain the “vicious cycle” that these patients suffer from, inasmuch as having obesity can lead to sleep apnea, and having sleep apnea can lead to further sedentary lifestyle and weight gain, owing to lack of energy and feeling tired, Dr. Malhotra told this news organization.
“It is important to intervene and treat the sleep disorder to hopefully make people more active,” he added.
The study had no specific funding. Dr. Grandner and Dr. Malhotra disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
“People who snore are also likely to have sleep apnea, but those who snore and don’t have sleep apnea are a largely understudied group,” senior author Michael Grandner, PhD, told this news organization.
“We found that even just snoring alone can impact health and well-being,” said Dr. Grandner, director of the sleep and health research program at the University of Arizona, Tucson.
The findings were presented at the annual meeting of the Associated Professional Sleep Societies.
A viscous cycle
Frequent snoring can signal sleep-disordered breathing, which is associated with a myriad of comorbidities, including increased risk for cardiovascular disease.
Prior studies have shown that sleep-disordered breathing is associated with less physical activity, but few studies have examined this at the population level or in relation to primary snoring.
Dr. Grandner and colleagues evaluated the relationship between snoring frequency and minutes of sedentary activity using 3 years’ worth of data from the National Health and Nutrition Examination Survey. Participants reported snoring frequency and sedentary activity.
After adjusting for sex, age, race, education level, and marital status, adults who were frequent snorers (5+ nights per week) spent about 36 more minutes per day sedentary, compared with peers who reported never snoring.
In addition, those individuals who were determined to be at increased risk of having sleep apnea had about 54 more minutes per day of sedentary time in the adjusted model.
“Snoring is very common, and it doesn’t just affect the nighttime,” said Dr. Grandner.
Snoring can lead to “more tiredness and less energy, which can impact everything from mood to stress to – as we saw – activity level,” he noted.
Commenting on the results for this news organization, Raman Malhotra, MD, of the Washington University Sleep Center in St. Louis, said this study clearly demonstrates how people who snore and people who are at risk for sleep apnea are more sedentary.
This could explain the “vicious cycle” that these patients suffer from, inasmuch as having obesity can lead to sleep apnea, and having sleep apnea can lead to further sedentary lifestyle and weight gain, owing to lack of energy and feeling tired, Dr. Malhotra told this news organization.
“It is important to intervene and treat the sleep disorder to hopefully make people more active,” he added.
The study had no specific funding. Dr. Grandner and Dr. Malhotra disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
“People who snore are also likely to have sleep apnea, but those who snore and don’t have sleep apnea are a largely understudied group,” senior author Michael Grandner, PhD, told this news organization.
“We found that even just snoring alone can impact health and well-being,” said Dr. Grandner, director of the sleep and health research program at the University of Arizona, Tucson.
The findings were presented at the annual meeting of the Associated Professional Sleep Societies.
A viscous cycle
Frequent snoring can signal sleep-disordered breathing, which is associated with a myriad of comorbidities, including increased risk for cardiovascular disease.
Prior studies have shown that sleep-disordered breathing is associated with less physical activity, but few studies have examined this at the population level or in relation to primary snoring.
Dr. Grandner and colleagues evaluated the relationship between snoring frequency and minutes of sedentary activity using 3 years’ worth of data from the National Health and Nutrition Examination Survey. Participants reported snoring frequency and sedentary activity.
After adjusting for sex, age, race, education level, and marital status, adults who were frequent snorers (5+ nights per week) spent about 36 more minutes per day sedentary, compared with peers who reported never snoring.
In addition, those individuals who were determined to be at increased risk of having sleep apnea had about 54 more minutes per day of sedentary time in the adjusted model.
“Snoring is very common, and it doesn’t just affect the nighttime,” said Dr. Grandner.
Snoring can lead to “more tiredness and less energy, which can impact everything from mood to stress to – as we saw – activity level,” he noted.
Commenting on the results for this news organization, Raman Malhotra, MD, of the Washington University Sleep Center in St. Louis, said this study clearly demonstrates how people who snore and people who are at risk for sleep apnea are more sedentary.
This could explain the “vicious cycle” that these patients suffer from, inasmuch as having obesity can lead to sleep apnea, and having sleep apnea can lead to further sedentary lifestyle and weight gain, owing to lack of energy and feeling tired, Dr. Malhotra told this news organization.
“It is important to intervene and treat the sleep disorder to hopefully make people more active,” he added.
The study had no specific funding. Dr. Grandner and Dr. Malhotra disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
FROM SLEEP 2022
Findings raise questions about migraine and sleep
CHARLOTTE, N.C. – What may be the largest case-based study of patients with migraine and sleep-disordered breathing to date has found that, counter to prevailing thought, they may not be at higher risk of having obstructive sleep apnea (OSA) than nonmigraine patients, although further prospective studies are needed to validate that finding.
“This in no way for me changes the fact that, for patients that complain of headaches, sleep apnea remains to be something that should be considered as possible cause of their headaches,” neurologist and Cleveland Clinic postdoctoral fellow Eric Gruenthal, MD, said in an interview after he presented his results at the annual meeting of the Associated Professional Sleep Societies.
The study suggested that patients with migraine may have an OSA risk that “may be a little lower” than their nonmigraine counterparts, Dr. Gruenthal said. “But we have really yet to determine whether that’s true or not.”
Large case-based study
The retrospective case study included 4,783 migraine cases from the Cleveland Clinic electronic health record database who were case matched on a 1:3 basis with 14,287 controls. Patients with migraine had an average age of 47.5 years (±13.3) and body mass index of 33.7 kg/m2 (±8.6), and 76.4% were White. All patients had polysomnography (PSG) at a Cleveland Clinic facility from 1998 to 2021.
The analysis evaluated the collected data in two domains: sleep architecture, consisting of arousal index (AI), total sleep time (TST) and percentage of sleep stage time; and sleep-disordered breathing, including apnea hypopnea index (AHI) and mean oxygen saturation. The key findings of the migraine patients versus controls include:
- Lower AI, 19.6 (95% confidence interval, 12.8-30.9) versus 22.6 (95% CI, 14.7-34.9; P < .001).
- Shorter TST, 359 (95% CI, 307-421) versus 363 (95% CI, 306-432.5) minutes (P = .01).
- With regard to sleep stage, the percentage of N2 sleep was higher, 67.8% (95% CI, 59.6%-75.6%) versus 67% (95% CI, 58.4%-74.8%; P < .001); but the percentage of REM was lower at 16.7% (95% CI, 10%-22%) versus 17% (95% CI, 11.1%-22.2%; P = .012).
- Lower AHI, 7.4 (95% CI, 2.6-17) versus 9.5 (95% CI, 3.7-22.1, P < .001).
- Higher mean oxygen saturation, 93.7 (±2.4) versus 93.3% (±2.6; P < .001).
“Also,” Dr. Gruenthal added, “we found that the percentage of sleep time with oxygen saturation below 90% was lower among patients with migraine, at 1.3% versus 2.4%” (P < .001).
A unique profile?
The goal of the study was to determine whether migraine patients would have a unique PSG profile, Dr. Gruenthal said. “We were trying to overcome some of the limitations of previous studies, most notably those that use small sample sizes, and in some cases a lack of controls.”
The findings that migraine patients would have higher AI and elevated AHI ran counter to the study’s hypotheses, but fell in line with the expectation that they would have reduced TST, Dr. Gruenthal said.
Patients with migraine “may, in fact, exhibit a lower burden of sleep-disordered breathing, and that’s based on our findings such as the lower AHI and decreased burden of hypoxemia,” he said. “We theorized that this may be related to patients with migraine having a unique CGRP [calcitonin gene-related peptide] and serotonin physiology.” He noted that previously published research has shown that sleep CGRP and serotonin have a central role in causing arousal in response to rising CO2 levels during sleep, which can occur during apneas and hypopneas.
Dr. Gruenthal noted that the researchers are still analyzing the findings. “We theorized that possible indication bias may be present in our study,” he said. “It may be the case that patients with migraine are more likely to get their PSG done because of their headache and not for things like snoring and witnessed apneas, which may be more predictive of significant sleep apnea.” They’re also evaluating the “question of medicine confounding.”
Dr. Gruenthal added that “the big unanswered question out there is, if you have a patient with migraine who also has sleep apnea, by treating the sleep apnea will that improve their migraine?”
More questions than answers
Commenting on the study, Donald Bliwise, PhD, professor of neurology at Emory Sleep Center, Atlanta, said the study findings shouldn’t change how clinicians approach migraine in relation to sleep.
“It’s a case series, it’s retrospective,” said Dr. Bliwise, who was not involved in the study. “It’s the largest study that I know of that has ever looked at the diagnosis of migraine in relation to polysomnographic measures of sleep, but it’s imprecise to the extent that migraine is a clinical diagnosis, so not everyone that carries the diagnosis of migraine has the diagnosis made by a neurologist.”
The study raises more questions than it answers, he said, “but that’s not necessarily a bad thing. I think we need more prospective studies.” Those studies should be more granular in how they analyze sleep in migraine patients “Since migraine is an intermittent event, and sleep quality and length, and percentage of REM sleep and even sleep apnea can vary from night to night, it would be fascinating to look at headaches over a month in relation to sleep over a month.”
Dr. Gruenthal and Dr. Bliwise have no disclosures. The Association of Migraine Disorders provided funding for the study.
CHARLOTTE, N.C. – What may be the largest case-based study of patients with migraine and sleep-disordered breathing to date has found that, counter to prevailing thought, they may not be at higher risk of having obstructive sleep apnea (OSA) than nonmigraine patients, although further prospective studies are needed to validate that finding.
“This in no way for me changes the fact that, for patients that complain of headaches, sleep apnea remains to be something that should be considered as possible cause of their headaches,” neurologist and Cleveland Clinic postdoctoral fellow Eric Gruenthal, MD, said in an interview after he presented his results at the annual meeting of the Associated Professional Sleep Societies.
The study suggested that patients with migraine may have an OSA risk that “may be a little lower” than their nonmigraine counterparts, Dr. Gruenthal said. “But we have really yet to determine whether that’s true or not.”
Large case-based study
The retrospective case study included 4,783 migraine cases from the Cleveland Clinic electronic health record database who were case matched on a 1:3 basis with 14,287 controls. Patients with migraine had an average age of 47.5 years (±13.3) and body mass index of 33.7 kg/m2 (±8.6), and 76.4% were White. All patients had polysomnography (PSG) at a Cleveland Clinic facility from 1998 to 2021.
The analysis evaluated the collected data in two domains: sleep architecture, consisting of arousal index (AI), total sleep time (TST) and percentage of sleep stage time; and sleep-disordered breathing, including apnea hypopnea index (AHI) and mean oxygen saturation. The key findings of the migraine patients versus controls include:
- Lower AI, 19.6 (95% confidence interval, 12.8-30.9) versus 22.6 (95% CI, 14.7-34.9; P < .001).
- Shorter TST, 359 (95% CI, 307-421) versus 363 (95% CI, 306-432.5) minutes (P = .01).
- With regard to sleep stage, the percentage of N2 sleep was higher, 67.8% (95% CI, 59.6%-75.6%) versus 67% (95% CI, 58.4%-74.8%; P < .001); but the percentage of REM was lower at 16.7% (95% CI, 10%-22%) versus 17% (95% CI, 11.1%-22.2%; P = .012).
- Lower AHI, 7.4 (95% CI, 2.6-17) versus 9.5 (95% CI, 3.7-22.1, P < .001).
- Higher mean oxygen saturation, 93.7 (±2.4) versus 93.3% (±2.6; P < .001).
“Also,” Dr. Gruenthal added, “we found that the percentage of sleep time with oxygen saturation below 90% was lower among patients with migraine, at 1.3% versus 2.4%” (P < .001).
A unique profile?
The goal of the study was to determine whether migraine patients would have a unique PSG profile, Dr. Gruenthal said. “We were trying to overcome some of the limitations of previous studies, most notably those that use small sample sizes, and in some cases a lack of controls.”
The findings that migraine patients would have higher AI and elevated AHI ran counter to the study’s hypotheses, but fell in line with the expectation that they would have reduced TST, Dr. Gruenthal said.
Patients with migraine “may, in fact, exhibit a lower burden of sleep-disordered breathing, and that’s based on our findings such as the lower AHI and decreased burden of hypoxemia,” he said. “We theorized that this may be related to patients with migraine having a unique CGRP [calcitonin gene-related peptide] and serotonin physiology.” He noted that previously published research has shown that sleep CGRP and serotonin have a central role in causing arousal in response to rising CO2 levels during sleep, which can occur during apneas and hypopneas.
Dr. Gruenthal noted that the researchers are still analyzing the findings. “We theorized that possible indication bias may be present in our study,” he said. “It may be the case that patients with migraine are more likely to get their PSG done because of their headache and not for things like snoring and witnessed apneas, which may be more predictive of significant sleep apnea.” They’re also evaluating the “question of medicine confounding.”
Dr. Gruenthal added that “the big unanswered question out there is, if you have a patient with migraine who also has sleep apnea, by treating the sleep apnea will that improve their migraine?”
More questions than answers
Commenting on the study, Donald Bliwise, PhD, professor of neurology at Emory Sleep Center, Atlanta, said the study findings shouldn’t change how clinicians approach migraine in relation to sleep.
“It’s a case series, it’s retrospective,” said Dr. Bliwise, who was not involved in the study. “It’s the largest study that I know of that has ever looked at the diagnosis of migraine in relation to polysomnographic measures of sleep, but it’s imprecise to the extent that migraine is a clinical diagnosis, so not everyone that carries the diagnosis of migraine has the diagnosis made by a neurologist.”
The study raises more questions than it answers, he said, “but that’s not necessarily a bad thing. I think we need more prospective studies.” Those studies should be more granular in how they analyze sleep in migraine patients “Since migraine is an intermittent event, and sleep quality and length, and percentage of REM sleep and even sleep apnea can vary from night to night, it would be fascinating to look at headaches over a month in relation to sleep over a month.”
Dr. Gruenthal and Dr. Bliwise have no disclosures. The Association of Migraine Disorders provided funding for the study.
CHARLOTTE, N.C. – What may be the largest case-based study of patients with migraine and sleep-disordered breathing to date has found that, counter to prevailing thought, they may not be at higher risk of having obstructive sleep apnea (OSA) than nonmigraine patients, although further prospective studies are needed to validate that finding.
“This in no way for me changes the fact that, for patients that complain of headaches, sleep apnea remains to be something that should be considered as possible cause of their headaches,” neurologist and Cleveland Clinic postdoctoral fellow Eric Gruenthal, MD, said in an interview after he presented his results at the annual meeting of the Associated Professional Sleep Societies.
The study suggested that patients with migraine may have an OSA risk that “may be a little lower” than their nonmigraine counterparts, Dr. Gruenthal said. “But we have really yet to determine whether that’s true or not.”
Large case-based study
The retrospective case study included 4,783 migraine cases from the Cleveland Clinic electronic health record database who were case matched on a 1:3 basis with 14,287 controls. Patients with migraine had an average age of 47.5 years (±13.3) and body mass index of 33.7 kg/m2 (±8.6), and 76.4% were White. All patients had polysomnography (PSG) at a Cleveland Clinic facility from 1998 to 2021.
The analysis evaluated the collected data in two domains: sleep architecture, consisting of arousal index (AI), total sleep time (TST) and percentage of sleep stage time; and sleep-disordered breathing, including apnea hypopnea index (AHI) and mean oxygen saturation. The key findings of the migraine patients versus controls include:
- Lower AI, 19.6 (95% confidence interval, 12.8-30.9) versus 22.6 (95% CI, 14.7-34.9; P < .001).
- Shorter TST, 359 (95% CI, 307-421) versus 363 (95% CI, 306-432.5) minutes (P = .01).
- With regard to sleep stage, the percentage of N2 sleep was higher, 67.8% (95% CI, 59.6%-75.6%) versus 67% (95% CI, 58.4%-74.8%; P < .001); but the percentage of REM was lower at 16.7% (95% CI, 10%-22%) versus 17% (95% CI, 11.1%-22.2%; P = .012).
- Lower AHI, 7.4 (95% CI, 2.6-17) versus 9.5 (95% CI, 3.7-22.1, P < .001).
- Higher mean oxygen saturation, 93.7 (±2.4) versus 93.3% (±2.6; P < .001).
“Also,” Dr. Gruenthal added, “we found that the percentage of sleep time with oxygen saturation below 90% was lower among patients with migraine, at 1.3% versus 2.4%” (P < .001).
A unique profile?
The goal of the study was to determine whether migraine patients would have a unique PSG profile, Dr. Gruenthal said. “We were trying to overcome some of the limitations of previous studies, most notably those that use small sample sizes, and in some cases a lack of controls.”
The findings that migraine patients would have higher AI and elevated AHI ran counter to the study’s hypotheses, but fell in line with the expectation that they would have reduced TST, Dr. Gruenthal said.
Patients with migraine “may, in fact, exhibit a lower burden of sleep-disordered breathing, and that’s based on our findings such as the lower AHI and decreased burden of hypoxemia,” he said. “We theorized that this may be related to patients with migraine having a unique CGRP [calcitonin gene-related peptide] and serotonin physiology.” He noted that previously published research has shown that sleep CGRP and serotonin have a central role in causing arousal in response to rising CO2 levels during sleep, which can occur during apneas and hypopneas.
Dr. Gruenthal noted that the researchers are still analyzing the findings. “We theorized that possible indication bias may be present in our study,” he said. “It may be the case that patients with migraine are more likely to get their PSG done because of their headache and not for things like snoring and witnessed apneas, which may be more predictive of significant sleep apnea.” They’re also evaluating the “question of medicine confounding.”
Dr. Gruenthal added that “the big unanswered question out there is, if you have a patient with migraine who also has sleep apnea, by treating the sleep apnea will that improve their migraine?”
More questions than answers
Commenting on the study, Donald Bliwise, PhD, professor of neurology at Emory Sleep Center, Atlanta, said the study findings shouldn’t change how clinicians approach migraine in relation to sleep.
“It’s a case series, it’s retrospective,” said Dr. Bliwise, who was not involved in the study. “It’s the largest study that I know of that has ever looked at the diagnosis of migraine in relation to polysomnographic measures of sleep, but it’s imprecise to the extent that migraine is a clinical diagnosis, so not everyone that carries the diagnosis of migraine has the diagnosis made by a neurologist.”
The study raises more questions than it answers, he said, “but that’s not necessarily a bad thing. I think we need more prospective studies.” Those studies should be more granular in how they analyze sleep in migraine patients “Since migraine is an intermittent event, and sleep quality and length, and percentage of REM sleep and even sleep apnea can vary from night to night, it would be fascinating to look at headaches over a month in relation to sleep over a month.”
Dr. Gruenthal and Dr. Bliwise have no disclosures. The Association of Migraine Disorders provided funding for the study.
AT SLEEP 2022
Long-term erratic sleep may foretell cognitive problems
CHARLOTTE, N.C. – Erratic sleep patterns over years or even decades, along with a patient’s age and history of depression, may be harbingers of cognitive impairment later in life, an analysis of decades of data from a large sleep study has found.
“What we were a little surprised to find in this model was that sleep duration, whether short, long or average, was not significant, but the sleep variability – the change in sleep across those time measurements—was significantly impacting the incidence of cognitive impairment,” Samantha Keil, PhD, a postdoctoral fellow at the University of Washington, Seattle, reported at the at the annual meeting of the Associated Professional Sleep Societies.
The researchers analyzed sleep and cognition data collected over decades on 1,104 adults who participated in the Seattle Longitudinal Study. Study participants ranged from age 55 to over 100, with almost 80% of the study cohort aged 65 and older.
The Seattle Longitudinal Study first started gathering data in the 1950s. Participants in the study cohort underwent an extensive cognitive battery, which was added to the study in 1984 and gathered every 5-7 years, and completed a health behavioral questionnaire (HBQ), which was added in 1993 and administered every 3-5 years, Dr. Keil said. The HBQ included a question on average nightly sleep duration.
The study used a multivariable Cox proportional hazard regression model to evaluate the overall effect of average sleep duration and changes in sleep duration over time on cognitive impairment. Covariates used in the model included apolipoprotein E4 (APOE4) genotype, gender, years of education, ethnicity, and depression.
Dr. Keil said the model found, as expected, that the demographic variables of education, APOE status, and depression were significantly associated with cognitive impairment (hazard ratios of 1.11; 95% confidence interval [CI], 1.02-1.21; P = .01; and 2.08; 95% CI, 1.31-3.31; P < .005; and 1.08; 95% CI, 1.04-1.13; P < .005, respectively). Importantly, when evaluating the duration, change and variability of sleep, the researchers found that increased sleep variability was significantly associated with cognitive impairment (HR, 3.15; 95% CI, 1.69-5.87; P < .005).
Under this analysis, “sleep variability over time and not median sleep duration was associated with cognitive impairment,” she said. When sleep variability was added into the model, it improved the concordance score – a value that reflects the ability of a model to predict an outcome better than random chance – from .63 to .73 (a value of .5 indicates the model is no better at predicting an outcome than a random chance model; a value of .7 or greater indicates a good model).
Identification of sleep variability as a sleep pattern of interest in longitudinal studies is important, Dr. Keil said, because simply evaluating mean or median sleep duration across time might not account for a subject’s variable sleep phenotype. Most importantly, further evaluation of sleep variability with a linear regression prediction analysis (F statistic 8.796, P < .0001, adjusted R-squared .235) found that increased age, depression, and sleep variability significantly predicted cognitive impairment 10 years downstream. “Longitudinal sleep variability is perhaps for the first time being reported as significantly associated with the development of downstream cognitive impairment,” Dr. Keil said.
What makes this study unique, Dr. Keil said in an interview, is that it used self-reported longitudinal data gathered at 3- to 5-year intervals for up to 25 years, allowing for the assessment of variation of sleep duration across this entire time frame. “If you could use that shift in sleep duration as a point of therapeutic intervention, that would be really exciting,” she said.
Future research will evaluate how sleep variability and cognitive function are impacted by other variables gathered in the Seattle Longitudinal Study over the years, including factors such as diabetes and hypertension status, diet, alcohol and tobacco use, and marital and family status. Follow-up studies will be investigating the impact of sleep variability on neuropathologic disease progression and lymphatic system impairment, Dr. Keil said.
A newer approach
By linking sleep variability and daytime functioning, the study employs a “newer approach,” said Joseph M. Dzierzewski, PhD, director of behavioral medicine concentration in the department of psychology at Virginia Commonwealth University in Richmond. “While some previous work has examined night-to-night fluctuation in various sleep characteristics and cognitive functioning, what differentiates the present study from these previous works is the duration of the investigation,” he said. The “richness of data” in the Seattle Longitudinal Study and how it tracks sleep and cognition over years make it “quite unique and novel.”
Future studies, he said, should be deliberate in how they evaluate sleep and neurocognitive function across years. “Disentangling short-term moment-to-moment and day-to-day fluctuation, which may be more reversible in nature, from long-term, enduring month-to-month or year-to-year fluctuation, which may be more permanent, will be important for continuing to advance our understanding of these complex phenomena,” Dr. Dzierzewski said. “An additional important area of future investigation would be to continue the hunt for a common biological factor underpinning both sleep variability and Alzheimer’s disease.” That, he said, may help identify potential intervention targets.
Dr. Keil and Dr. Dzierzewski have no relevant disclosures.
CHARLOTTE, N.C. – Erratic sleep patterns over years or even decades, along with a patient’s age and history of depression, may be harbingers of cognitive impairment later in life, an analysis of decades of data from a large sleep study has found.
“What we were a little surprised to find in this model was that sleep duration, whether short, long or average, was not significant, but the sleep variability – the change in sleep across those time measurements—was significantly impacting the incidence of cognitive impairment,” Samantha Keil, PhD, a postdoctoral fellow at the University of Washington, Seattle, reported at the at the annual meeting of the Associated Professional Sleep Societies.
The researchers analyzed sleep and cognition data collected over decades on 1,104 adults who participated in the Seattle Longitudinal Study. Study participants ranged from age 55 to over 100, with almost 80% of the study cohort aged 65 and older.
The Seattle Longitudinal Study first started gathering data in the 1950s. Participants in the study cohort underwent an extensive cognitive battery, which was added to the study in 1984 and gathered every 5-7 years, and completed a health behavioral questionnaire (HBQ), which was added in 1993 and administered every 3-5 years, Dr. Keil said. The HBQ included a question on average nightly sleep duration.
The study used a multivariable Cox proportional hazard regression model to evaluate the overall effect of average sleep duration and changes in sleep duration over time on cognitive impairment. Covariates used in the model included apolipoprotein E4 (APOE4) genotype, gender, years of education, ethnicity, and depression.
Dr. Keil said the model found, as expected, that the demographic variables of education, APOE status, and depression were significantly associated with cognitive impairment (hazard ratios of 1.11; 95% confidence interval [CI], 1.02-1.21; P = .01; and 2.08; 95% CI, 1.31-3.31; P < .005; and 1.08; 95% CI, 1.04-1.13; P < .005, respectively). Importantly, when evaluating the duration, change and variability of sleep, the researchers found that increased sleep variability was significantly associated with cognitive impairment (HR, 3.15; 95% CI, 1.69-5.87; P < .005).
Under this analysis, “sleep variability over time and not median sleep duration was associated with cognitive impairment,” she said. When sleep variability was added into the model, it improved the concordance score – a value that reflects the ability of a model to predict an outcome better than random chance – from .63 to .73 (a value of .5 indicates the model is no better at predicting an outcome than a random chance model; a value of .7 or greater indicates a good model).
Identification of sleep variability as a sleep pattern of interest in longitudinal studies is important, Dr. Keil said, because simply evaluating mean or median sleep duration across time might not account for a subject’s variable sleep phenotype. Most importantly, further evaluation of sleep variability with a linear regression prediction analysis (F statistic 8.796, P < .0001, adjusted R-squared .235) found that increased age, depression, and sleep variability significantly predicted cognitive impairment 10 years downstream. “Longitudinal sleep variability is perhaps for the first time being reported as significantly associated with the development of downstream cognitive impairment,” Dr. Keil said.
What makes this study unique, Dr. Keil said in an interview, is that it used self-reported longitudinal data gathered at 3- to 5-year intervals for up to 25 years, allowing for the assessment of variation of sleep duration across this entire time frame. “If you could use that shift in sleep duration as a point of therapeutic intervention, that would be really exciting,” she said.
Future research will evaluate how sleep variability and cognitive function are impacted by other variables gathered in the Seattle Longitudinal Study over the years, including factors such as diabetes and hypertension status, diet, alcohol and tobacco use, and marital and family status. Follow-up studies will be investigating the impact of sleep variability on neuropathologic disease progression and lymphatic system impairment, Dr. Keil said.
A newer approach
By linking sleep variability and daytime functioning, the study employs a “newer approach,” said Joseph M. Dzierzewski, PhD, director of behavioral medicine concentration in the department of psychology at Virginia Commonwealth University in Richmond. “While some previous work has examined night-to-night fluctuation in various sleep characteristics and cognitive functioning, what differentiates the present study from these previous works is the duration of the investigation,” he said. The “richness of data” in the Seattle Longitudinal Study and how it tracks sleep and cognition over years make it “quite unique and novel.”
Future studies, he said, should be deliberate in how they evaluate sleep and neurocognitive function across years. “Disentangling short-term moment-to-moment and day-to-day fluctuation, which may be more reversible in nature, from long-term, enduring month-to-month or year-to-year fluctuation, which may be more permanent, will be important for continuing to advance our understanding of these complex phenomena,” Dr. Dzierzewski said. “An additional important area of future investigation would be to continue the hunt for a common biological factor underpinning both sleep variability and Alzheimer’s disease.” That, he said, may help identify potential intervention targets.
Dr. Keil and Dr. Dzierzewski have no relevant disclosures.
CHARLOTTE, N.C. – Erratic sleep patterns over years or even decades, along with a patient’s age and history of depression, may be harbingers of cognitive impairment later in life, an analysis of decades of data from a large sleep study has found.
“What we were a little surprised to find in this model was that sleep duration, whether short, long or average, was not significant, but the sleep variability – the change in sleep across those time measurements—was significantly impacting the incidence of cognitive impairment,” Samantha Keil, PhD, a postdoctoral fellow at the University of Washington, Seattle, reported at the at the annual meeting of the Associated Professional Sleep Societies.
The researchers analyzed sleep and cognition data collected over decades on 1,104 adults who participated in the Seattle Longitudinal Study. Study participants ranged from age 55 to over 100, with almost 80% of the study cohort aged 65 and older.
The Seattle Longitudinal Study first started gathering data in the 1950s. Participants in the study cohort underwent an extensive cognitive battery, which was added to the study in 1984 and gathered every 5-7 years, and completed a health behavioral questionnaire (HBQ), which was added in 1993 and administered every 3-5 years, Dr. Keil said. The HBQ included a question on average nightly sleep duration.
The study used a multivariable Cox proportional hazard regression model to evaluate the overall effect of average sleep duration and changes in sleep duration over time on cognitive impairment. Covariates used in the model included apolipoprotein E4 (APOE4) genotype, gender, years of education, ethnicity, and depression.
Dr. Keil said the model found, as expected, that the demographic variables of education, APOE status, and depression were significantly associated with cognitive impairment (hazard ratios of 1.11; 95% confidence interval [CI], 1.02-1.21; P = .01; and 2.08; 95% CI, 1.31-3.31; P < .005; and 1.08; 95% CI, 1.04-1.13; P < .005, respectively). Importantly, when evaluating the duration, change and variability of sleep, the researchers found that increased sleep variability was significantly associated with cognitive impairment (HR, 3.15; 95% CI, 1.69-5.87; P < .005).
Under this analysis, “sleep variability over time and not median sleep duration was associated with cognitive impairment,” she said. When sleep variability was added into the model, it improved the concordance score – a value that reflects the ability of a model to predict an outcome better than random chance – from .63 to .73 (a value of .5 indicates the model is no better at predicting an outcome than a random chance model; a value of .7 or greater indicates a good model).
Identification of sleep variability as a sleep pattern of interest in longitudinal studies is important, Dr. Keil said, because simply evaluating mean or median sleep duration across time might not account for a subject’s variable sleep phenotype. Most importantly, further evaluation of sleep variability with a linear regression prediction analysis (F statistic 8.796, P < .0001, adjusted R-squared .235) found that increased age, depression, and sleep variability significantly predicted cognitive impairment 10 years downstream. “Longitudinal sleep variability is perhaps for the first time being reported as significantly associated with the development of downstream cognitive impairment,” Dr. Keil said.
What makes this study unique, Dr. Keil said in an interview, is that it used self-reported longitudinal data gathered at 3- to 5-year intervals for up to 25 years, allowing for the assessment of variation of sleep duration across this entire time frame. “If you could use that shift in sleep duration as a point of therapeutic intervention, that would be really exciting,” she said.
Future research will evaluate how sleep variability and cognitive function are impacted by other variables gathered in the Seattle Longitudinal Study over the years, including factors such as diabetes and hypertension status, diet, alcohol and tobacco use, and marital and family status. Follow-up studies will be investigating the impact of sleep variability on neuropathologic disease progression and lymphatic system impairment, Dr. Keil said.
A newer approach
By linking sleep variability and daytime functioning, the study employs a “newer approach,” said Joseph M. Dzierzewski, PhD, director of behavioral medicine concentration in the department of psychology at Virginia Commonwealth University in Richmond. “While some previous work has examined night-to-night fluctuation in various sleep characteristics and cognitive functioning, what differentiates the present study from these previous works is the duration of the investigation,” he said. The “richness of data” in the Seattle Longitudinal Study and how it tracks sleep and cognition over years make it “quite unique and novel.”
Future studies, he said, should be deliberate in how they evaluate sleep and neurocognitive function across years. “Disentangling short-term moment-to-moment and day-to-day fluctuation, which may be more reversible in nature, from long-term, enduring month-to-month or year-to-year fluctuation, which may be more permanent, will be important for continuing to advance our understanding of these complex phenomena,” Dr. Dzierzewski said. “An additional important area of future investigation would be to continue the hunt for a common biological factor underpinning both sleep variability and Alzheimer’s disease.” That, he said, may help identify potential intervention targets.
Dr. Keil and Dr. Dzierzewski have no relevant disclosures.
AT SLEEP 2022
Analysis shows predictive capabilities of sleep EEG
CHARLOTTE, N.C. – , a researcher reported at the annual meeting of the Associated Professional Sleep Societies. “Sleep EEGs contain decodable information about the risk of unfavorable outcomes,” said Haoqi Sun, PhD, an instructor of neurology at Massachusetts General Hospital, Boston, and lead study author. “The results suggest that it’s feasible to use sleep to identify people with high risk of unfavorable outcomes and it strengthens the concept of sleep as a window into brain and general health.”
The researchers performed a quantitative analysis of sleep data collected on 8,673 adults who had diagnostic sleep studies that included polysomnography (PSG). The analysis used ICD codes to consider these 11 health outcomes: dementia, mild cognitive impairment (MCI) or dementia, ischemic stroke, intracranial hemorrhage, atrial fibrillation, myocardial infarction, type 2 diabetes, hypertension, bipolar disorder, depression, and mortality.
Then, Dr. Sun explained, they extracted 86 spectral and time-domain features of REM and non-REM sleep from sleep EEG recordings, and analyzed that data by adjusting for eight covariates including age, sex, body mass index, and use of benzodiazepines, antidepressants, sedatives, antiseizure drugs, and stimulants.
Participants were partitioned into three sleep-quality groups: poor, average, and good. The outcome-wise mean prediction difference in 10-year cumulative incidence was 2.3% for the poor sleep group, 0.5% for the average sleep group, and 1.3% for the good sleep group.
The outcomes with the three greatest poor to average risk ratios were dementia (6.2; 95% confidence interval, 4.5-9.3), mortality (5.7; 95% CI, 5-7.5) and MCI or dementia (4; 95% CI, 3.2-4.9).
Ready for the clinic?
In an interview, Dr. Sun said the results demonstrated the potential of using EEG brain wave data to predict health outcomes on an individual basis, although he acknowledged that most of the 86 sleep features the researchers used are not readily available in the clinic.
He noted the spectral features used in the study can be captured through software compatible with PSG. “From there you can identify the various bands, the different frequency ranges, and then you can easily see within this range whether a person has a higher power or lower power,” he said. However, the spindle and slow-oscillation features that researchers used in the study are beyond the reach of most clinics.
Next steps
This research is in its early stage, Dr. Sun said, but at some point the data collected from sleep studies could be paired with machine learning to make the model workable for evaluating individual patients. “Our goal is to first make this individualized,” he said. “We want to minimize the noise in the recording and minimize the night-to-night variability in the findings. There is some clinical-informed approach and there is also some algorithm-informed approach where you can minimize the variation over time.”
The model also has the potential to predict outcomes, particularly with chronic diseases such as diabetes and dementia, well before a diagnosis is made, he said.
‘Fascinating’ and ‘provocative’
Donald Bliwise, PhD, professor of neurology at Emory Sleep Center in Atlanta, said the study was “fascinating; it’s provocative; it’s exciting and interesting,” but added, “Sleep is vital for health. That’s abundantly clear in a study like that, but trying to push it a little bit further with all of these 86 measurements of the EEG, I think it becomes complicated.”
The study methodology, particularly the use of cumulative incidence of various diseases, was laudable, he said, and the use of simpler EEG-measured sleep features, such as alpha band power, “make intuitive sense.”
But it’s less clear on how the more sophisticated features the study model used – for example, kurtosis of theta frequency or coupling between spindle and slow oscillation – rank on sleep quality, he said, adding that the researchers have most likely done that but couldn’t add that into the format of the presentation.
“Kurtosis of the theta frequency band we don’t get on everyone in the sleep lab,” Dr. Bliwise said. “We might be able to, but I don’t know how to quite plug that into a turnkey model.”
The clinical components of the study were conducted by M. Brandon Westover, MD, PhD, at Massachusetts General Hospital, and Robert J. Thomas, MD, at Beth Israel Deaconess Medical Center, both in Boston. The study received support from the American Academy of Sleep Medicine Foundation. Dr. Sun has no relevant disclosures. Dr. Bliwise has no disclosures.
CHARLOTTE, N.C. – , a researcher reported at the annual meeting of the Associated Professional Sleep Societies. “Sleep EEGs contain decodable information about the risk of unfavorable outcomes,” said Haoqi Sun, PhD, an instructor of neurology at Massachusetts General Hospital, Boston, and lead study author. “The results suggest that it’s feasible to use sleep to identify people with high risk of unfavorable outcomes and it strengthens the concept of sleep as a window into brain and general health.”
The researchers performed a quantitative analysis of sleep data collected on 8,673 adults who had diagnostic sleep studies that included polysomnography (PSG). The analysis used ICD codes to consider these 11 health outcomes: dementia, mild cognitive impairment (MCI) or dementia, ischemic stroke, intracranial hemorrhage, atrial fibrillation, myocardial infarction, type 2 diabetes, hypertension, bipolar disorder, depression, and mortality.
Then, Dr. Sun explained, they extracted 86 spectral and time-domain features of REM and non-REM sleep from sleep EEG recordings, and analyzed that data by adjusting for eight covariates including age, sex, body mass index, and use of benzodiazepines, antidepressants, sedatives, antiseizure drugs, and stimulants.
Participants were partitioned into three sleep-quality groups: poor, average, and good. The outcome-wise mean prediction difference in 10-year cumulative incidence was 2.3% for the poor sleep group, 0.5% for the average sleep group, and 1.3% for the good sleep group.
The outcomes with the three greatest poor to average risk ratios were dementia (6.2; 95% confidence interval, 4.5-9.3), mortality (5.7; 95% CI, 5-7.5) and MCI or dementia (4; 95% CI, 3.2-4.9).
Ready for the clinic?
In an interview, Dr. Sun said the results demonstrated the potential of using EEG brain wave data to predict health outcomes on an individual basis, although he acknowledged that most of the 86 sleep features the researchers used are not readily available in the clinic.
He noted the spectral features used in the study can be captured through software compatible with PSG. “From there you can identify the various bands, the different frequency ranges, and then you can easily see within this range whether a person has a higher power or lower power,” he said. However, the spindle and slow-oscillation features that researchers used in the study are beyond the reach of most clinics.
Next steps
This research is in its early stage, Dr. Sun said, but at some point the data collected from sleep studies could be paired with machine learning to make the model workable for evaluating individual patients. “Our goal is to first make this individualized,” he said. “We want to minimize the noise in the recording and minimize the night-to-night variability in the findings. There is some clinical-informed approach and there is also some algorithm-informed approach where you can minimize the variation over time.”
The model also has the potential to predict outcomes, particularly with chronic diseases such as diabetes and dementia, well before a diagnosis is made, he said.
‘Fascinating’ and ‘provocative’
Donald Bliwise, PhD, professor of neurology at Emory Sleep Center in Atlanta, said the study was “fascinating; it’s provocative; it’s exciting and interesting,” but added, “Sleep is vital for health. That’s abundantly clear in a study like that, but trying to push it a little bit further with all of these 86 measurements of the EEG, I think it becomes complicated.”
The study methodology, particularly the use of cumulative incidence of various diseases, was laudable, he said, and the use of simpler EEG-measured sleep features, such as alpha band power, “make intuitive sense.”
But it’s less clear on how the more sophisticated features the study model used – for example, kurtosis of theta frequency or coupling between spindle and slow oscillation – rank on sleep quality, he said, adding that the researchers have most likely done that but couldn’t add that into the format of the presentation.
“Kurtosis of the theta frequency band we don’t get on everyone in the sleep lab,” Dr. Bliwise said. “We might be able to, but I don’t know how to quite plug that into a turnkey model.”
The clinical components of the study were conducted by M. Brandon Westover, MD, PhD, at Massachusetts General Hospital, and Robert J. Thomas, MD, at Beth Israel Deaconess Medical Center, both in Boston. The study received support from the American Academy of Sleep Medicine Foundation. Dr. Sun has no relevant disclosures. Dr. Bliwise has no disclosures.
CHARLOTTE, N.C. – , a researcher reported at the annual meeting of the Associated Professional Sleep Societies. “Sleep EEGs contain decodable information about the risk of unfavorable outcomes,” said Haoqi Sun, PhD, an instructor of neurology at Massachusetts General Hospital, Boston, and lead study author. “The results suggest that it’s feasible to use sleep to identify people with high risk of unfavorable outcomes and it strengthens the concept of sleep as a window into brain and general health.”
The researchers performed a quantitative analysis of sleep data collected on 8,673 adults who had diagnostic sleep studies that included polysomnography (PSG). The analysis used ICD codes to consider these 11 health outcomes: dementia, mild cognitive impairment (MCI) or dementia, ischemic stroke, intracranial hemorrhage, atrial fibrillation, myocardial infarction, type 2 diabetes, hypertension, bipolar disorder, depression, and mortality.
Then, Dr. Sun explained, they extracted 86 spectral and time-domain features of REM and non-REM sleep from sleep EEG recordings, and analyzed that data by adjusting for eight covariates including age, sex, body mass index, and use of benzodiazepines, antidepressants, sedatives, antiseizure drugs, and stimulants.
Participants were partitioned into three sleep-quality groups: poor, average, and good. The outcome-wise mean prediction difference in 10-year cumulative incidence was 2.3% for the poor sleep group, 0.5% for the average sleep group, and 1.3% for the good sleep group.
The outcomes with the three greatest poor to average risk ratios were dementia (6.2; 95% confidence interval, 4.5-9.3), mortality (5.7; 95% CI, 5-7.5) and MCI or dementia (4; 95% CI, 3.2-4.9).
Ready for the clinic?
In an interview, Dr. Sun said the results demonstrated the potential of using EEG brain wave data to predict health outcomes on an individual basis, although he acknowledged that most of the 86 sleep features the researchers used are not readily available in the clinic.
He noted the spectral features used in the study can be captured through software compatible with PSG. “From there you can identify the various bands, the different frequency ranges, and then you can easily see within this range whether a person has a higher power or lower power,” he said. However, the spindle and slow-oscillation features that researchers used in the study are beyond the reach of most clinics.
Next steps
This research is in its early stage, Dr. Sun said, but at some point the data collected from sleep studies could be paired with machine learning to make the model workable for evaluating individual patients. “Our goal is to first make this individualized,” he said. “We want to minimize the noise in the recording and minimize the night-to-night variability in the findings. There is some clinical-informed approach and there is also some algorithm-informed approach where you can minimize the variation over time.”
The model also has the potential to predict outcomes, particularly with chronic diseases such as diabetes and dementia, well before a diagnosis is made, he said.
‘Fascinating’ and ‘provocative’
Donald Bliwise, PhD, professor of neurology at Emory Sleep Center in Atlanta, said the study was “fascinating; it’s provocative; it’s exciting and interesting,” but added, “Sleep is vital for health. That’s abundantly clear in a study like that, but trying to push it a little bit further with all of these 86 measurements of the EEG, I think it becomes complicated.”
The study methodology, particularly the use of cumulative incidence of various diseases, was laudable, he said, and the use of simpler EEG-measured sleep features, such as alpha band power, “make intuitive sense.”
But it’s less clear on how the more sophisticated features the study model used – for example, kurtosis of theta frequency or coupling between spindle and slow oscillation – rank on sleep quality, he said, adding that the researchers have most likely done that but couldn’t add that into the format of the presentation.
“Kurtosis of the theta frequency band we don’t get on everyone in the sleep lab,” Dr. Bliwise said. “We might be able to, but I don’t know how to quite plug that into a turnkey model.”
The clinical components of the study were conducted by M. Brandon Westover, MD, PhD, at Massachusetts General Hospital, and Robert J. Thomas, MD, at Beth Israel Deaconess Medical Center, both in Boston. The study received support from the American Academy of Sleep Medicine Foundation. Dr. Sun has no relevant disclosures. Dr. Bliwise has no disclosures.
AT SLEEP 2022
Alcohol, degraded sleep related in young adults
CHARLOTTE, N.C. – Sleep and alcohol consumption in young adults seems to follow a “vicious cycle,” as one observer called it. and those who went to bed earlier and slept longer tended to drink less the next day, a study of drinking and sleeping habits in 21- to 29-year-olds found.
“Sleep is a potential factor that we could intervene on to really identify how to improve drinking behaviors among young adults,” David Reichenberger, a graduate student at Penn State University, University Park, said in an interview after he presented his findings at the annual meeting of the Associated Professional Sleep Societies.
This is one of the few studies of alcohol consumption and sleep patterns that used an objective measure of alcohol consumption, Mr. Reichenberger said. The study evaluated sleep and alcohol consumption patterns in 222 regularly drinking young adults over 6 consecutive days. Study participants completed morning smartphone-based questionnaires, reporting their previous night’s bedtime, sleep duration, sleep quality, and number of drinks consumed. They also wore an alcohol monitor that continuously measured their transdermal alcohol consumption (TAC).
The study analyzed the data using two sets of multilevel models: A linear model that looked at how each drinking predictor was associated with each sleep variable and a Poisson model to determine how sleep predicted next-day alcohol use.
“We found that higher average peak TAC – that is, how intoxicated they got – was associated with a 19-minute later bedtime among young adults,” Mr. Reichenberger said. “Later bedtimes were then associated with a 26% greater TAC among those adults” (P < .02).
Patterns of alcohol consumption and sleep
On days when participants recorded a higher peak TAC, bedtime was delayed, sleep duration was shorter, and subjective sleep quality was worse, he said. However, none of the sleep variables predicted next-day peak TAC.
“We found an association between the duration of the drinking episode and later bedtimes among young adults,” he added. “And on days when the drinking episodes were longer, subsequent sleep was delayed and sleep quality was worse. But we also found that after nights when they had a later bedtime, next-day drinking episodes were about 7% longer.”
Conversely, young adults who had earlier bedtimes and longer sleep durations tended to consume fewer drinks and they achieved lower intoxication levels the next day, Mr. Reichenberger said.
Between-person results showed that young adults who tended to go to bed later drank on average 24% more the next day (P < .01). Also, each extra hour of sleep was associated with a 14% decrease in drinking the next day (P < .03).
Participants who drank more went to bed on average 12-19 minutes later (P < .01) and slept 5 fewer minutes (P < .01). Within-person results showed that on nights when participants drank more than usual they went to bed 8-13 minutes later (P < .01), slept 2-4 fewer minutes (P < .03), and had worse sleep quality (P < .01).
Mr. Reichenberger acknowledged one limitation of the study: Measuring sleep and alcohol consumption patterns over 6 days might not be long enough. Future studies should address that.
A ‘vicious cycle’
Hans P.A. Van Dongen, PhD, director of the Sleep and Performance Research Center at Washington State University, Spokane, said in an interview that the findings imply a “vicious cycle” between sleep and alcohol consumption. “You create a problem and then it perpetuates itself or reinforces itself.”
In older adults, alcohol tends to act as a “sleep aid,” Dr. Van Dongen noted. “Then it disrupts their sleep later on and then the next night they need to use the sleep aid again because they had a really poor night and they’re tired and they want to fall asleep.”
He added: “I think what is new here is that’s not very likely the mechanism that they’re using alcohol as a sleep aid in younger adults that we see in older adults, so I think there is a new element to it. Now does anybody know how that works exactly? No, that’s the next thing.”
The Penn State study identifies “a signal there that needs to be followed up on,” Dr. Van Dongen said. “There’s something nature’s trying to tell us but it’s not exactly clear what it’s trying to tell us.”
The National Institute on Drug Abuse provided funding for the study. Mr. Reichenberger has no relevant disclosures. Dr. Van Dongen has no disclosures to report.
CHARLOTTE, N.C. – Sleep and alcohol consumption in young adults seems to follow a “vicious cycle,” as one observer called it. and those who went to bed earlier and slept longer tended to drink less the next day, a study of drinking and sleeping habits in 21- to 29-year-olds found.
“Sleep is a potential factor that we could intervene on to really identify how to improve drinking behaviors among young adults,” David Reichenberger, a graduate student at Penn State University, University Park, said in an interview after he presented his findings at the annual meeting of the Associated Professional Sleep Societies.
This is one of the few studies of alcohol consumption and sleep patterns that used an objective measure of alcohol consumption, Mr. Reichenberger said. The study evaluated sleep and alcohol consumption patterns in 222 regularly drinking young adults over 6 consecutive days. Study participants completed morning smartphone-based questionnaires, reporting their previous night’s bedtime, sleep duration, sleep quality, and number of drinks consumed. They also wore an alcohol monitor that continuously measured their transdermal alcohol consumption (TAC).
The study analyzed the data using two sets of multilevel models: A linear model that looked at how each drinking predictor was associated with each sleep variable and a Poisson model to determine how sleep predicted next-day alcohol use.
“We found that higher average peak TAC – that is, how intoxicated they got – was associated with a 19-minute later bedtime among young adults,” Mr. Reichenberger said. “Later bedtimes were then associated with a 26% greater TAC among those adults” (P < .02).
Patterns of alcohol consumption and sleep
On days when participants recorded a higher peak TAC, bedtime was delayed, sleep duration was shorter, and subjective sleep quality was worse, he said. However, none of the sleep variables predicted next-day peak TAC.
“We found an association between the duration of the drinking episode and later bedtimes among young adults,” he added. “And on days when the drinking episodes were longer, subsequent sleep was delayed and sleep quality was worse. But we also found that after nights when they had a later bedtime, next-day drinking episodes were about 7% longer.”
Conversely, young adults who had earlier bedtimes and longer sleep durations tended to consume fewer drinks and they achieved lower intoxication levels the next day, Mr. Reichenberger said.
Between-person results showed that young adults who tended to go to bed later drank on average 24% more the next day (P < .01). Also, each extra hour of sleep was associated with a 14% decrease in drinking the next day (P < .03).
Participants who drank more went to bed on average 12-19 minutes later (P < .01) and slept 5 fewer minutes (P < .01). Within-person results showed that on nights when participants drank more than usual they went to bed 8-13 minutes later (P < .01), slept 2-4 fewer minutes (P < .03), and had worse sleep quality (P < .01).
Mr. Reichenberger acknowledged one limitation of the study: Measuring sleep and alcohol consumption patterns over 6 days might not be long enough. Future studies should address that.
A ‘vicious cycle’
Hans P.A. Van Dongen, PhD, director of the Sleep and Performance Research Center at Washington State University, Spokane, said in an interview that the findings imply a “vicious cycle” between sleep and alcohol consumption. “You create a problem and then it perpetuates itself or reinforces itself.”
In older adults, alcohol tends to act as a “sleep aid,” Dr. Van Dongen noted. “Then it disrupts their sleep later on and then the next night they need to use the sleep aid again because they had a really poor night and they’re tired and they want to fall asleep.”
He added: “I think what is new here is that’s not very likely the mechanism that they’re using alcohol as a sleep aid in younger adults that we see in older adults, so I think there is a new element to it. Now does anybody know how that works exactly? No, that’s the next thing.”
The Penn State study identifies “a signal there that needs to be followed up on,” Dr. Van Dongen said. “There’s something nature’s trying to tell us but it’s not exactly clear what it’s trying to tell us.”
The National Institute on Drug Abuse provided funding for the study. Mr. Reichenberger has no relevant disclosures. Dr. Van Dongen has no disclosures to report.
CHARLOTTE, N.C. – Sleep and alcohol consumption in young adults seems to follow a “vicious cycle,” as one observer called it. and those who went to bed earlier and slept longer tended to drink less the next day, a study of drinking and sleeping habits in 21- to 29-year-olds found.
“Sleep is a potential factor that we could intervene on to really identify how to improve drinking behaviors among young adults,” David Reichenberger, a graduate student at Penn State University, University Park, said in an interview after he presented his findings at the annual meeting of the Associated Professional Sleep Societies.
This is one of the few studies of alcohol consumption and sleep patterns that used an objective measure of alcohol consumption, Mr. Reichenberger said. The study evaluated sleep and alcohol consumption patterns in 222 regularly drinking young adults over 6 consecutive days. Study participants completed morning smartphone-based questionnaires, reporting their previous night’s bedtime, sleep duration, sleep quality, and number of drinks consumed. They also wore an alcohol monitor that continuously measured their transdermal alcohol consumption (TAC).
The study analyzed the data using two sets of multilevel models: A linear model that looked at how each drinking predictor was associated with each sleep variable and a Poisson model to determine how sleep predicted next-day alcohol use.
“We found that higher average peak TAC – that is, how intoxicated they got – was associated with a 19-minute later bedtime among young adults,” Mr. Reichenberger said. “Later bedtimes were then associated with a 26% greater TAC among those adults” (P < .02).
Patterns of alcohol consumption and sleep
On days when participants recorded a higher peak TAC, bedtime was delayed, sleep duration was shorter, and subjective sleep quality was worse, he said. However, none of the sleep variables predicted next-day peak TAC.
“We found an association between the duration of the drinking episode and later bedtimes among young adults,” he added. “And on days when the drinking episodes were longer, subsequent sleep was delayed and sleep quality was worse. But we also found that after nights when they had a later bedtime, next-day drinking episodes were about 7% longer.”
Conversely, young adults who had earlier bedtimes and longer sleep durations tended to consume fewer drinks and they achieved lower intoxication levels the next day, Mr. Reichenberger said.
Between-person results showed that young adults who tended to go to bed later drank on average 24% more the next day (P < .01). Also, each extra hour of sleep was associated with a 14% decrease in drinking the next day (P < .03).
Participants who drank more went to bed on average 12-19 minutes later (P < .01) and slept 5 fewer minutes (P < .01). Within-person results showed that on nights when participants drank more than usual they went to bed 8-13 minutes later (P < .01), slept 2-4 fewer minutes (P < .03), and had worse sleep quality (P < .01).
Mr. Reichenberger acknowledged one limitation of the study: Measuring sleep and alcohol consumption patterns over 6 days might not be long enough. Future studies should address that.
A ‘vicious cycle’
Hans P.A. Van Dongen, PhD, director of the Sleep and Performance Research Center at Washington State University, Spokane, said in an interview that the findings imply a “vicious cycle” between sleep and alcohol consumption. “You create a problem and then it perpetuates itself or reinforces itself.”
In older adults, alcohol tends to act as a “sleep aid,” Dr. Van Dongen noted. “Then it disrupts their sleep later on and then the next night they need to use the sleep aid again because they had a really poor night and they’re tired and they want to fall asleep.”
He added: “I think what is new here is that’s not very likely the mechanism that they’re using alcohol as a sleep aid in younger adults that we see in older adults, so I think there is a new element to it. Now does anybody know how that works exactly? No, that’s the next thing.”
The Penn State study identifies “a signal there that needs to be followed up on,” Dr. Van Dongen said. “There’s something nature’s trying to tell us but it’s not exactly clear what it’s trying to tell us.”
The National Institute on Drug Abuse provided funding for the study. Mr. Reichenberger has no relevant disclosures. Dr. Van Dongen has no disclosures to report.
At SLEEP 2022
COVID tied to a profound impact on children’s sleep
During the first year of the pandemic, profound changes in screen use and sleep timing occurred among U.S. adolescents as a result of spending more time using electronic devices, going to bed later, and getting up later, compared with before the pandemic, new research indicates.
The excessive screen time negatively affected sleep, said lead investigator Orsolya Kiss, PhD, with the Center for Health Sciences at SRI International, Menlo Park, Calif.
And what’s “concerning,” she told this news organization, is that there is no indication of any spontaneous decline in screen use in 2021, when there were fewer restrictions.
Dr. Kiss said she is “very much interested to see what future studies will show.”
The findings were presented at the annual meeting of the Associated Professional Sleep Societies.
Sleep takes a pandemic hit
“Adolescents and families have turned to online activities and social platforms more than ever before to maintain wellbeing, [to] connect with friends and family, and for online schooling,” Dr. Kiss said in a conference statement.
She and her colleagues examined longitudinal data from 5,027 adolescents aged 11-14 years who are participating in the ongoing Adolescent Brain Cognitive Development (ABCD) study.
As part of the study, participants reported sleep and daily screen time use prior to and at six time points during the first year of the pandemic (May 2020 to March 2021).
During the first year of the pandemic, relative to before the pandemic, recreational screen time was dramatically higher, with adolescents spending about 45 minutes more on social media and 20 minutes more playing video games, Dr. Kiss reported.
The jump in screen time was coupled with changes in sleep patterns.
Adolescents’ wake up times were delayed about 1.5 hours during May and August 2020, relative to prepandemic levels. The delay was partly due to summer break; wake-up times returned to earlier times in the fall of 2020.
During all pandemic assessments, bedtimes were delayed by about 1 hour, even when the new school year started. This was particularly the case in older adolescents and girls.
The findings highlight the need to promote “balanced and informed use of social media platforms, video games, and other digital technology to ensure adequate opportunity to sleep and maintain other healthy behaviors during this critical period of developmental change,” the authors wrote in their conference abstract.
Mental illness risk
In an interview, Ruth Benca, MD, PhD, co-chair of the Alliance for Sleep, noted that “during adolescence, the tendency to become more of a night owl naturally worsens, and when kids have no sleep schedule imposed on them, these patterns become exacerbated.”
Dr. Benca, who was not involved in the study, also noted that altered sleep patterns are risk factors for psychiatric illness.
“Adolescence, in particular, is so critical for brain development, and it really raises the question of whether sleep disturbances in adolescence or poor sleep patterns are contributing to the increase psychiatric epidemic we’re seeing in adolescents and children these days,” said Dr. Benca, with Wake Forest University School of Medicine and Atrium Health Wake Forest Baptist, Winston-Salem, N.C.
Also weighing in on the study, journalist and author Lisa Lewis, MS, based in Southern California, said, “It’s not surprising that tech use and social media – which is such an important part of their social worlds – went up during the pandemic.”
Ms. Lewis, a parent of two teenagers, played a key role in California’s new healthy school start times law, the first of its kind in the nation, and is the author of the newly released book, The Sleep-Deprived Teen (Mango Publishing).
“Far too many adolescents aren’t getting anywhere close to the 8-10 hours of nightly sleep they need,” Ms. Lewis said in an interview.
She noted that the the American Academy of Pediatrics recommends no tech use an hour before bed.
“And there are other house rules parents can implement, such as charging all devices in a central location, like the kitchen. Making sleep a priority helps teens, but it helps parents too: No one functions well when they’re sleep-deprived,” Ms. Lewis added.
Support for the study was provided by the National Institutes of Health. The authors have disclosed no relevant financial relationships. Dr. Benca is a consultant for Idorsia Pharmaceuticals. Ms. Lewis has no relevant disclosures.
A version of this article first appeared on Medscape.com.
During the first year of the pandemic, profound changes in screen use and sleep timing occurred among U.S. adolescents as a result of spending more time using electronic devices, going to bed later, and getting up later, compared with before the pandemic, new research indicates.
The excessive screen time negatively affected sleep, said lead investigator Orsolya Kiss, PhD, with the Center for Health Sciences at SRI International, Menlo Park, Calif.
And what’s “concerning,” she told this news organization, is that there is no indication of any spontaneous decline in screen use in 2021, when there were fewer restrictions.
Dr. Kiss said she is “very much interested to see what future studies will show.”
The findings were presented at the annual meeting of the Associated Professional Sleep Societies.
Sleep takes a pandemic hit
“Adolescents and families have turned to online activities and social platforms more than ever before to maintain wellbeing, [to] connect with friends and family, and for online schooling,” Dr. Kiss said in a conference statement.
She and her colleagues examined longitudinal data from 5,027 adolescents aged 11-14 years who are participating in the ongoing Adolescent Brain Cognitive Development (ABCD) study.
As part of the study, participants reported sleep and daily screen time use prior to and at six time points during the first year of the pandemic (May 2020 to March 2021).
During the first year of the pandemic, relative to before the pandemic, recreational screen time was dramatically higher, with adolescents spending about 45 minutes more on social media and 20 minutes more playing video games, Dr. Kiss reported.
The jump in screen time was coupled with changes in sleep patterns.
Adolescents’ wake up times were delayed about 1.5 hours during May and August 2020, relative to prepandemic levels. The delay was partly due to summer break; wake-up times returned to earlier times in the fall of 2020.
During all pandemic assessments, bedtimes were delayed by about 1 hour, even when the new school year started. This was particularly the case in older adolescents and girls.
The findings highlight the need to promote “balanced and informed use of social media platforms, video games, and other digital technology to ensure adequate opportunity to sleep and maintain other healthy behaviors during this critical period of developmental change,” the authors wrote in their conference abstract.
Mental illness risk
In an interview, Ruth Benca, MD, PhD, co-chair of the Alliance for Sleep, noted that “during adolescence, the tendency to become more of a night owl naturally worsens, and when kids have no sleep schedule imposed on them, these patterns become exacerbated.”
Dr. Benca, who was not involved in the study, also noted that altered sleep patterns are risk factors for psychiatric illness.
“Adolescence, in particular, is so critical for brain development, and it really raises the question of whether sleep disturbances in adolescence or poor sleep patterns are contributing to the increase psychiatric epidemic we’re seeing in adolescents and children these days,” said Dr. Benca, with Wake Forest University School of Medicine and Atrium Health Wake Forest Baptist, Winston-Salem, N.C.
Also weighing in on the study, journalist and author Lisa Lewis, MS, based in Southern California, said, “It’s not surprising that tech use and social media – which is such an important part of their social worlds – went up during the pandemic.”
Ms. Lewis, a parent of two teenagers, played a key role in California’s new healthy school start times law, the first of its kind in the nation, and is the author of the newly released book, The Sleep-Deprived Teen (Mango Publishing).
“Far too many adolescents aren’t getting anywhere close to the 8-10 hours of nightly sleep they need,” Ms. Lewis said in an interview.
She noted that the the American Academy of Pediatrics recommends no tech use an hour before bed.
“And there are other house rules parents can implement, such as charging all devices in a central location, like the kitchen. Making sleep a priority helps teens, but it helps parents too: No one functions well when they’re sleep-deprived,” Ms. Lewis added.
Support for the study was provided by the National Institutes of Health. The authors have disclosed no relevant financial relationships. Dr. Benca is a consultant for Idorsia Pharmaceuticals. Ms. Lewis has no relevant disclosures.
A version of this article first appeared on Medscape.com.
During the first year of the pandemic, profound changes in screen use and sleep timing occurred among U.S. adolescents as a result of spending more time using electronic devices, going to bed later, and getting up later, compared with before the pandemic, new research indicates.
The excessive screen time negatively affected sleep, said lead investigator Orsolya Kiss, PhD, with the Center for Health Sciences at SRI International, Menlo Park, Calif.
And what’s “concerning,” she told this news organization, is that there is no indication of any spontaneous decline in screen use in 2021, when there were fewer restrictions.
Dr. Kiss said she is “very much interested to see what future studies will show.”
The findings were presented at the annual meeting of the Associated Professional Sleep Societies.
Sleep takes a pandemic hit
“Adolescents and families have turned to online activities and social platforms more than ever before to maintain wellbeing, [to] connect with friends and family, and for online schooling,” Dr. Kiss said in a conference statement.
She and her colleagues examined longitudinal data from 5,027 adolescents aged 11-14 years who are participating in the ongoing Adolescent Brain Cognitive Development (ABCD) study.
As part of the study, participants reported sleep and daily screen time use prior to and at six time points during the first year of the pandemic (May 2020 to March 2021).
During the first year of the pandemic, relative to before the pandemic, recreational screen time was dramatically higher, with adolescents spending about 45 minutes more on social media and 20 minutes more playing video games, Dr. Kiss reported.
The jump in screen time was coupled with changes in sleep patterns.
Adolescents’ wake up times were delayed about 1.5 hours during May and August 2020, relative to prepandemic levels. The delay was partly due to summer break; wake-up times returned to earlier times in the fall of 2020.
During all pandemic assessments, bedtimes were delayed by about 1 hour, even when the new school year started. This was particularly the case in older adolescents and girls.
The findings highlight the need to promote “balanced and informed use of social media platforms, video games, and other digital technology to ensure adequate opportunity to sleep and maintain other healthy behaviors during this critical period of developmental change,” the authors wrote in their conference abstract.
Mental illness risk
In an interview, Ruth Benca, MD, PhD, co-chair of the Alliance for Sleep, noted that “during adolescence, the tendency to become more of a night owl naturally worsens, and when kids have no sleep schedule imposed on them, these patterns become exacerbated.”
Dr. Benca, who was not involved in the study, also noted that altered sleep patterns are risk factors for psychiatric illness.
“Adolescence, in particular, is so critical for brain development, and it really raises the question of whether sleep disturbances in adolescence or poor sleep patterns are contributing to the increase psychiatric epidemic we’re seeing in adolescents and children these days,” said Dr. Benca, with Wake Forest University School of Medicine and Atrium Health Wake Forest Baptist, Winston-Salem, N.C.
Also weighing in on the study, journalist and author Lisa Lewis, MS, based in Southern California, said, “It’s not surprising that tech use and social media – which is such an important part of their social worlds – went up during the pandemic.”
Ms. Lewis, a parent of two teenagers, played a key role in California’s new healthy school start times law, the first of its kind in the nation, and is the author of the newly released book, The Sleep-Deprived Teen (Mango Publishing).
“Far too many adolescents aren’t getting anywhere close to the 8-10 hours of nightly sleep they need,” Ms. Lewis said in an interview.
She noted that the the American Academy of Pediatrics recommends no tech use an hour before bed.
“And there are other house rules parents can implement, such as charging all devices in a central location, like the kitchen. Making sleep a priority helps teens, but it helps parents too: No one functions well when they’re sleep-deprived,” Ms. Lewis added.
Support for the study was provided by the National Institutes of Health. The authors have disclosed no relevant financial relationships. Dr. Benca is a consultant for Idorsia Pharmaceuticals. Ms. Lewis has no relevant disclosures.
A version of this article first appeared on Medscape.com.
FROM SLEEP 2022
‘Alarming’ new data on disordered sleep after COVID-19
Such disturbances are especially common among Black people, new research shows.
The “high” prevalence of moderate to severe sleep disturbances is “alarming,” study investigator Cinthya Pena Orbea, MD, sleep specialist at the Cleveland Clinic, said in an interview.
The findings were presented at the annual meeting of the Associated Professional Sleep Societies.
Dr. Pena and colleagues analyzed data on 962 patients with PASC seen at the Cleveland Clinic ReCOVer Clinic between February 2021 and April 2022.
More than two-thirds of patients (67.2%) reported at least moderate fatigue, while 21.8% reported severe fatigue, Dr. Pena reported.
In addition, 41.3% reported at least moderate sleep disturbances, while 8% of patients reported severe sleep disturbances, including insomnia, “which may impair quality of life,” Dr. Pena said.
Obesity, mood disorders, and Black race emerged as contributors to problems with sleep and fatigue after COVID.
Notably, after adjusting for demographics, Black race conferred threefold higher odds of moderate to severe sleep disturbances.
“We don’t know why this is, and one of our next steps is to better understand race-specific determinants of sleep disturbances after COVID and create targeted interventions,” Dr. Pena said.
How long after COVID the fatigue and sleep problems last “remains uncertain,” Dr. Pena acknowledged. However, in her clinical experience with therapy, patients’ sleep and fatigue may improve after 6 or 8 months.
Ruth Benca, MD, PhD, cochair of the Alliance for Sleep, is not surprised by the Cleveland Clinic findings.
“Sleep disturbances and fatigue are part of the sequelae of COVID,” Dr. Benca, who was not involved in the study, said in an interview.
“We know that people who have had COVID have more trouble sleeping afterwards. There is the COVID insomnia created in all of us just out of our worries, fears, isolation, and stress. And then there’s an actual impact of having the infection itself on worsening sleep,” said Dr. Benca, with Wake Forest University and Atrium Health Wake Forest Baptist, both in Winston-Salem, N.C.
The study had no specific funding. The authors have disclosed no relevant financial relationships. Dr. Benca is a consultant for Idorsia Pharmaceuticals.
A version of this article first appeared on Medscape.com.
Such disturbances are especially common among Black people, new research shows.
The “high” prevalence of moderate to severe sleep disturbances is “alarming,” study investigator Cinthya Pena Orbea, MD, sleep specialist at the Cleveland Clinic, said in an interview.
The findings were presented at the annual meeting of the Associated Professional Sleep Societies.
Dr. Pena and colleagues analyzed data on 962 patients with PASC seen at the Cleveland Clinic ReCOVer Clinic between February 2021 and April 2022.
More than two-thirds of patients (67.2%) reported at least moderate fatigue, while 21.8% reported severe fatigue, Dr. Pena reported.
In addition, 41.3% reported at least moderate sleep disturbances, while 8% of patients reported severe sleep disturbances, including insomnia, “which may impair quality of life,” Dr. Pena said.
Obesity, mood disorders, and Black race emerged as contributors to problems with sleep and fatigue after COVID.
Notably, after adjusting for demographics, Black race conferred threefold higher odds of moderate to severe sleep disturbances.
“We don’t know why this is, and one of our next steps is to better understand race-specific determinants of sleep disturbances after COVID and create targeted interventions,” Dr. Pena said.
How long after COVID the fatigue and sleep problems last “remains uncertain,” Dr. Pena acknowledged. However, in her clinical experience with therapy, patients’ sleep and fatigue may improve after 6 or 8 months.
Ruth Benca, MD, PhD, cochair of the Alliance for Sleep, is not surprised by the Cleveland Clinic findings.
“Sleep disturbances and fatigue are part of the sequelae of COVID,” Dr. Benca, who was not involved in the study, said in an interview.
“We know that people who have had COVID have more trouble sleeping afterwards. There is the COVID insomnia created in all of us just out of our worries, fears, isolation, and stress. And then there’s an actual impact of having the infection itself on worsening sleep,” said Dr. Benca, with Wake Forest University and Atrium Health Wake Forest Baptist, both in Winston-Salem, N.C.
The study had no specific funding. The authors have disclosed no relevant financial relationships. Dr. Benca is a consultant for Idorsia Pharmaceuticals.
A version of this article first appeared on Medscape.com.
Such disturbances are especially common among Black people, new research shows.
The “high” prevalence of moderate to severe sleep disturbances is “alarming,” study investigator Cinthya Pena Orbea, MD, sleep specialist at the Cleveland Clinic, said in an interview.
The findings were presented at the annual meeting of the Associated Professional Sleep Societies.
Dr. Pena and colleagues analyzed data on 962 patients with PASC seen at the Cleveland Clinic ReCOVer Clinic between February 2021 and April 2022.
More than two-thirds of patients (67.2%) reported at least moderate fatigue, while 21.8% reported severe fatigue, Dr. Pena reported.
In addition, 41.3% reported at least moderate sleep disturbances, while 8% of patients reported severe sleep disturbances, including insomnia, “which may impair quality of life,” Dr. Pena said.
Obesity, mood disorders, and Black race emerged as contributors to problems with sleep and fatigue after COVID.
Notably, after adjusting for demographics, Black race conferred threefold higher odds of moderate to severe sleep disturbances.
“We don’t know why this is, and one of our next steps is to better understand race-specific determinants of sleep disturbances after COVID and create targeted interventions,” Dr. Pena said.
How long after COVID the fatigue and sleep problems last “remains uncertain,” Dr. Pena acknowledged. However, in her clinical experience with therapy, patients’ sleep and fatigue may improve after 6 or 8 months.
Ruth Benca, MD, PhD, cochair of the Alliance for Sleep, is not surprised by the Cleveland Clinic findings.
“Sleep disturbances and fatigue are part of the sequelae of COVID,” Dr. Benca, who was not involved in the study, said in an interview.
“We know that people who have had COVID have more trouble sleeping afterwards. There is the COVID insomnia created in all of us just out of our worries, fears, isolation, and stress. And then there’s an actual impact of having the infection itself on worsening sleep,” said Dr. Benca, with Wake Forest University and Atrium Health Wake Forest Baptist, both in Winston-Salem, N.C.
The study had no specific funding. The authors have disclosed no relevant financial relationships. Dr. Benca is a consultant for Idorsia Pharmaceuticals.
A version of this article first appeared on Medscape.com.
FROM SLEEP 2022