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Sleep quality linked to gut microbiome biodiversity
SAN ANTONIO – , according to results from a population sample of adults.
“These findings are preliminary and very early in the growth of this field,” lead study author Erika W. Hagen, PhD, said during an interview at the annual meeting of the Associated Professional Sleep Societies
According to Dr. Hagen, an epidemiologist at the University of Wisconsin–Madison, experimental studies in mice have shown that disturbed sleep is associated with gut microbiota composition, and a few small experimental studies in humans have found associations between curtailed sleep and measures of gut microbiota richness and diversity.
In an effort to examine associations of subjectively and objectively assessed sleep metrics with indices of gut microbiome richness and diversity, Dr. Hagen and colleagues assessed 482 individuals who participated in the Survey of the Health of Wisconsin and completed in-home study visits in 2016. They provided fecal samples, participated in a week-long wrist actigraphy protocol to measure sleep, and completed questionnaires about sleep, diet, and other health and sociodemographic factors, and an assessment of physical activity by waist-worn actigraphy.
Metrics of species richness included the Chao1 and the ACE, which estimate the number of species. Metrics of the diversity of the gut microbiome included the Inverse Simpson index and the Shannon index. All metrics were regressed on self-reported sleep duration, extreme daytime sleepiness, the Epworth Sleepiness Scale (ESS), and actigraphy-measured sleep duration and wake after sleep onset (WASO). Next, the researchers estimated associations between each of the sleep and diversity measures separately, adjusting for age and sex and then additionally adjusting for body mass index, moderate-vigorous physical activity, and dietary fat and fiber.
The mean age of the 482 subjects was 56 years, 57% were female, and the mean body mass index was 30 kg/m2. After the researchers adjusted for gender and age, they found that greater WASO was statistically significantly associated with lower richness and alpha diversity (P less than .05). These associations remained significant on the Chao1 measure and borderline significant on the ACE and Shannon measures after further adjustment for BMI, physical activity, and dietary fiber and fat. For example, 60 minutes greater WASO was associated with an approximate 26% population standard deviation reduction in microbial richness as measured by Chao1. In fully-adjusted models, greater daytime sleepiness was associated with lower richness and diversity on all indices (P = .01-.06). The ESS and sleep duration were not associated with microbiota richness or diversity.
“Our results suggest that sleep quality is associated with gut microbiome richness and diversity,” Dr. Hagen said. “Our results are in line with other research on this topic. What’s interesting is how your sleep over a period of time is affecting these measures of your microbiome. That’s something people can do something about with [eating] habits over time. What would be great is to collect longitudinal data so that you could characterize sleep over a longer period of time, but also so you could measure the microbiome at different time points to see what’s changing with changes in sleep. That would be interesting to untangle.”
She acknowledged certain limitations of the study, including the small sample size and the cross-sectional design. The study was supported by the University of Wisconsin School of Medicine and Public Health through the Wisconsin Partnership Program.
SOURCE: Hagen EW et al. SLEEP 2019, Abstract 0106.
SAN ANTONIO – , according to results from a population sample of adults.
“These findings are preliminary and very early in the growth of this field,” lead study author Erika W. Hagen, PhD, said during an interview at the annual meeting of the Associated Professional Sleep Societies
According to Dr. Hagen, an epidemiologist at the University of Wisconsin–Madison, experimental studies in mice have shown that disturbed sleep is associated with gut microbiota composition, and a few small experimental studies in humans have found associations between curtailed sleep and measures of gut microbiota richness and diversity.
In an effort to examine associations of subjectively and objectively assessed sleep metrics with indices of gut microbiome richness and diversity, Dr. Hagen and colleagues assessed 482 individuals who participated in the Survey of the Health of Wisconsin and completed in-home study visits in 2016. They provided fecal samples, participated in a week-long wrist actigraphy protocol to measure sleep, and completed questionnaires about sleep, diet, and other health and sociodemographic factors, and an assessment of physical activity by waist-worn actigraphy.
Metrics of species richness included the Chao1 and the ACE, which estimate the number of species. Metrics of the diversity of the gut microbiome included the Inverse Simpson index and the Shannon index. All metrics were regressed on self-reported sleep duration, extreme daytime sleepiness, the Epworth Sleepiness Scale (ESS), and actigraphy-measured sleep duration and wake after sleep onset (WASO). Next, the researchers estimated associations between each of the sleep and diversity measures separately, adjusting for age and sex and then additionally adjusting for body mass index, moderate-vigorous physical activity, and dietary fat and fiber.
The mean age of the 482 subjects was 56 years, 57% were female, and the mean body mass index was 30 kg/m2. After the researchers adjusted for gender and age, they found that greater WASO was statistically significantly associated with lower richness and alpha diversity (P less than .05). These associations remained significant on the Chao1 measure and borderline significant on the ACE and Shannon measures after further adjustment for BMI, physical activity, and dietary fiber and fat. For example, 60 minutes greater WASO was associated with an approximate 26% population standard deviation reduction in microbial richness as measured by Chao1. In fully-adjusted models, greater daytime sleepiness was associated with lower richness and diversity on all indices (P = .01-.06). The ESS and sleep duration were not associated with microbiota richness or diversity.
“Our results suggest that sleep quality is associated with gut microbiome richness and diversity,” Dr. Hagen said. “Our results are in line with other research on this topic. What’s interesting is how your sleep over a period of time is affecting these measures of your microbiome. That’s something people can do something about with [eating] habits over time. What would be great is to collect longitudinal data so that you could characterize sleep over a longer period of time, but also so you could measure the microbiome at different time points to see what’s changing with changes in sleep. That would be interesting to untangle.”
She acknowledged certain limitations of the study, including the small sample size and the cross-sectional design. The study was supported by the University of Wisconsin School of Medicine and Public Health through the Wisconsin Partnership Program.
SOURCE: Hagen EW et al. SLEEP 2019, Abstract 0106.
SAN ANTONIO – , according to results from a population sample of adults.
“These findings are preliminary and very early in the growth of this field,” lead study author Erika W. Hagen, PhD, said during an interview at the annual meeting of the Associated Professional Sleep Societies
According to Dr. Hagen, an epidemiologist at the University of Wisconsin–Madison, experimental studies in mice have shown that disturbed sleep is associated with gut microbiota composition, and a few small experimental studies in humans have found associations between curtailed sleep and measures of gut microbiota richness and diversity.
In an effort to examine associations of subjectively and objectively assessed sleep metrics with indices of gut microbiome richness and diversity, Dr. Hagen and colleagues assessed 482 individuals who participated in the Survey of the Health of Wisconsin and completed in-home study visits in 2016. They provided fecal samples, participated in a week-long wrist actigraphy protocol to measure sleep, and completed questionnaires about sleep, diet, and other health and sociodemographic factors, and an assessment of physical activity by waist-worn actigraphy.
Metrics of species richness included the Chao1 and the ACE, which estimate the number of species. Metrics of the diversity of the gut microbiome included the Inverse Simpson index and the Shannon index. All metrics were regressed on self-reported sleep duration, extreme daytime sleepiness, the Epworth Sleepiness Scale (ESS), and actigraphy-measured sleep duration and wake after sleep onset (WASO). Next, the researchers estimated associations between each of the sleep and diversity measures separately, adjusting for age and sex and then additionally adjusting for body mass index, moderate-vigorous physical activity, and dietary fat and fiber.
The mean age of the 482 subjects was 56 years, 57% were female, and the mean body mass index was 30 kg/m2. After the researchers adjusted for gender and age, they found that greater WASO was statistically significantly associated with lower richness and alpha diversity (P less than .05). These associations remained significant on the Chao1 measure and borderline significant on the ACE and Shannon measures after further adjustment for BMI, physical activity, and dietary fiber and fat. For example, 60 minutes greater WASO was associated with an approximate 26% population standard deviation reduction in microbial richness as measured by Chao1. In fully-adjusted models, greater daytime sleepiness was associated with lower richness and diversity on all indices (P = .01-.06). The ESS and sleep duration were not associated with microbiota richness or diversity.
“Our results suggest that sleep quality is associated with gut microbiome richness and diversity,” Dr. Hagen said. “Our results are in line with other research on this topic. What’s interesting is how your sleep over a period of time is affecting these measures of your microbiome. That’s something people can do something about with [eating] habits over time. What would be great is to collect longitudinal data so that you could characterize sleep over a longer period of time, but also so you could measure the microbiome at different time points to see what’s changing with changes in sleep. That would be interesting to untangle.”
She acknowledged certain limitations of the study, including the small sample size and the cross-sectional design. The study was supported by the University of Wisconsin School of Medicine and Public Health through the Wisconsin Partnership Program.
SOURCE: Hagen EW et al. SLEEP 2019, Abstract 0106.
REPORTING FROM SLEEP 2019
Key clinical point: Better quality of sleep, but not duration of sleep, was associated with greater species richness and diversity of the gut microbiome.
Major finding: In fully adjusted models, greater daytime sleepiness was associated with lower richness and diversity of the gut microbiome on all indices (P = .01-.06).
Study details: An assessment of 482 individuals who participated in the Survey of the Health of Wisconsin.
Disclosures: The study was supported by the University of Wisconsin School of Medicine and Public Health through the Wisconsin Partnership Program.
Source: Hagen EW et al. SLEEP 2019, Abstract 0106.
Mortality risk from mild to moderate OSA modified by age
SAN ANTONIO – , results from a large longitudinal analysis showed.
“The association between severe OSA and significant morbidity and mortality – particularly cardiovascular in nature – is well established,” the study’s first author, Alexandros N. Vgontzas, MD, said at the annual meeting of the Associated Professional Sleep Societies. “In contrast, mild to moderate OSA is highly prevalent in the general population but its association with morbidity and mortality is not well established.”
In an effort to examine the association between mild to moderate OSA and all-cause mortality, Dr. Vgontzas and colleagues drew from the Penn State Adult Cohort, a random general population sample of 1,741 men and women who were studied in the sleep lab with an 8-hour polysomnography at baseline and followed for a mean of 19.2 years for all-cause mortality.
The researchers retrieved mortality data from the Centers for Disease Control and Prevention’s National Death Index and defined mild OSA as an apnea/hypopnea index (AHI) of 5-14.9 events per hour, while moderate OSA was defined as an AHI of 15-29.9 events per hour. They used Cox proportional hazards regression to estimate all-cause mortality and adjusted for race, sex, body mass index, smoking, hypertension, diabetes, heart problems, and stroke.
Dr. Vgontzas, of the Sleep Research and Treatment Center at Penn State University, Hershey, Pa., reported that 596 individuals have died since the study began. On adjusted analysis, patients with an AHI between 5 and 29 were 1.28 times as likely to die overall (P = .019). The researchers found that the association with mortality was stronger among patients younger than age 60, compared with those aged 60 and older. The hazard ratio was 1.44 for study participants younger than age 60 (P = .027), and 1.14 for those aged 60 and older (P = .34).
“Mild to moderate sleep apnea is associated with significant all-cause mortality risk, but the strength of the association decreases markedly with age,” Dr. Vgontzas concluded. “These findings are in line with previous findings that the association of mild to moderate OSA with cardiometabolic risk is modified by age and suggests that OSA in older adults is a distinctly different phenotype than in the young and middle-aged.”
The explanation for the association remains unclear. “Is it because the people of older age have some kind of genetic protection, or is because their sleep apnea is milder?” he asked. “We don’t have the data to tell.”
Dr. Vgontzas reported having no financial disclosures.
SOURCE: Vgontzas A et al. SLEEP 2019, abstract 0504.
SAN ANTONIO – , results from a large longitudinal analysis showed.
“The association between severe OSA and significant morbidity and mortality – particularly cardiovascular in nature – is well established,” the study’s first author, Alexandros N. Vgontzas, MD, said at the annual meeting of the Associated Professional Sleep Societies. “In contrast, mild to moderate OSA is highly prevalent in the general population but its association with morbidity and mortality is not well established.”
In an effort to examine the association between mild to moderate OSA and all-cause mortality, Dr. Vgontzas and colleagues drew from the Penn State Adult Cohort, a random general population sample of 1,741 men and women who were studied in the sleep lab with an 8-hour polysomnography at baseline and followed for a mean of 19.2 years for all-cause mortality.
The researchers retrieved mortality data from the Centers for Disease Control and Prevention’s National Death Index and defined mild OSA as an apnea/hypopnea index (AHI) of 5-14.9 events per hour, while moderate OSA was defined as an AHI of 15-29.9 events per hour. They used Cox proportional hazards regression to estimate all-cause mortality and adjusted for race, sex, body mass index, smoking, hypertension, diabetes, heart problems, and stroke.
Dr. Vgontzas, of the Sleep Research and Treatment Center at Penn State University, Hershey, Pa., reported that 596 individuals have died since the study began. On adjusted analysis, patients with an AHI between 5 and 29 were 1.28 times as likely to die overall (P = .019). The researchers found that the association with mortality was stronger among patients younger than age 60, compared with those aged 60 and older. The hazard ratio was 1.44 for study participants younger than age 60 (P = .027), and 1.14 for those aged 60 and older (P = .34).
“Mild to moderate sleep apnea is associated with significant all-cause mortality risk, but the strength of the association decreases markedly with age,” Dr. Vgontzas concluded. “These findings are in line with previous findings that the association of mild to moderate OSA with cardiometabolic risk is modified by age and suggests that OSA in older adults is a distinctly different phenotype than in the young and middle-aged.”
The explanation for the association remains unclear. “Is it because the people of older age have some kind of genetic protection, or is because their sleep apnea is milder?” he asked. “We don’t have the data to tell.”
Dr. Vgontzas reported having no financial disclosures.
SOURCE: Vgontzas A et al. SLEEP 2019, abstract 0504.
SAN ANTONIO – , results from a large longitudinal analysis showed.
“The association between severe OSA and significant morbidity and mortality – particularly cardiovascular in nature – is well established,” the study’s first author, Alexandros N. Vgontzas, MD, said at the annual meeting of the Associated Professional Sleep Societies. “In contrast, mild to moderate OSA is highly prevalent in the general population but its association with morbidity and mortality is not well established.”
In an effort to examine the association between mild to moderate OSA and all-cause mortality, Dr. Vgontzas and colleagues drew from the Penn State Adult Cohort, a random general population sample of 1,741 men and women who were studied in the sleep lab with an 8-hour polysomnography at baseline and followed for a mean of 19.2 years for all-cause mortality.
The researchers retrieved mortality data from the Centers for Disease Control and Prevention’s National Death Index and defined mild OSA as an apnea/hypopnea index (AHI) of 5-14.9 events per hour, while moderate OSA was defined as an AHI of 15-29.9 events per hour. They used Cox proportional hazards regression to estimate all-cause mortality and adjusted for race, sex, body mass index, smoking, hypertension, diabetes, heart problems, and stroke.
Dr. Vgontzas, of the Sleep Research and Treatment Center at Penn State University, Hershey, Pa., reported that 596 individuals have died since the study began. On adjusted analysis, patients with an AHI between 5 and 29 were 1.28 times as likely to die overall (P = .019). The researchers found that the association with mortality was stronger among patients younger than age 60, compared with those aged 60 and older. The hazard ratio was 1.44 for study participants younger than age 60 (P = .027), and 1.14 for those aged 60 and older (P = .34).
“Mild to moderate sleep apnea is associated with significant all-cause mortality risk, but the strength of the association decreases markedly with age,” Dr. Vgontzas concluded. “These findings are in line with previous findings that the association of mild to moderate OSA with cardiometabolic risk is modified by age and suggests that OSA in older adults is a distinctly different phenotype than in the young and middle-aged.”
The explanation for the association remains unclear. “Is it because the people of older age have some kind of genetic protection, or is because their sleep apnea is milder?” he asked. “We don’t have the data to tell.”
Dr. Vgontzas reported having no financial disclosures.
SOURCE: Vgontzas A et al. SLEEP 2019, abstract 0504.
REPORTING FROM SLEEP 2019
Key clinical point: Among adults with mild to moderate obstructive sleep apnea, the risk of mortality is highest among those younger than age 60.
Major finding: The hazard ratio for mortality was 1.44 for study participants younger than age 60 (P = .027), and 1.14 for those aged 60 and older (P = .34).
Study details: An analysis of 1,741 men and women from the Penn State Adult Cohort.
Disclosures: Dr. Vgontzas reported having no financial disclosures.
Source: Vgontzas A et al. SLEEP 2019, Abstract 0504.
Daytime eating schedule found to help with weight management
SAN ANTONIO – In adults of normal weight, a small controlled study has shown that a , independent of caloric intake.
The findings come from an 8-week controlled trial presented at the annual meeting of the Associated Professional Sleep Societies, which set out to examine the impact of a daytime versus delayed eating schedule on body mass, adiposity, and energy homeostasis in adults of normal weight.
“It is best to stop eating as early as possible in the day, and to not eat late at night,” the study’s first author, Namni Goel, PhD, said in an interview at the meeting. “There’s an open question in our field: Should you stop eating at 7:00 p.m.? 8:00 p.m.? My own feeling is, the longer it is between when you stop eating and go to bed, the better off you are metabolically.”
Dr. Goel, associate professor in the division of sleep and chronobiology in the department of psychiatry at the University of Pennsylvania, Philadelphia, and colleagues enrolled 12 healthy adults to participate in a randomized cross-over study in free-living conditions. Three meals and two snacks consisting of comparable energy and macronutrient content were provided during two 8-week counterbalanced phases: 1) daytime eating (food consumed between 8:00 a.m. and 7:00 p.m, and 2) delayed eating (food consumed between 12:00 p.m. and 11:00 p.m. A 2-week washout period occurred between the conditions. “What we wanted to do is just manipulate the timing of eating and we provided all of the meals so we could control the caloric intake,” Dr. Goel said.
The researchers asked participants to maintain a sleep-wake cycle between 11:00 p.m. and 9:00 a.m. (verified by wrist actigraphy) and to limit physical activity. They assessed weight, adiposity, energy metabolism, and hormonal markers during four inpatient visits: 1) baseline; 2) after the first eating condition; 3) after the washout period, before the second eating condition began; and 4) after the second eating condition. They used two-way analysis of variance and Cohen’s d effect sizes to examine changes in anthropometrics and metabolic measures affected by eating schedule (daytime vs. delayed) and time (before vs. after each eating schedule).
The mean age of 12 study participants was 26 years; five were females. Their mean body mass index was 21.9 kg/m2. Dr. Goel reported that participants had excellent adherence to assigned eating schedules, with no differences between the conditions. Weight was decreased on the daytime vs. delayed eating schedule. Specifically, Cohen’s d effect sizes were 0.57 overall: 1.16 for females and 0.33 for males, all in the small to large range. Resting energy expenditure, respiratory quotient, and trunk fat percentage/leg fat percentage were decreased on the daytime vs. delayed eating condition, with Cohen’s d effect sizes of 0.45-1.02, all in the medium to large range. In addition, total cholesterol and insulin were decreased on the daytime eating condition (medium effect sizes of 0.60 and 0.57, respectively), while triglycerides and glucose were increased on the delayed condition (medium effect sizes of 0.46 and 0.52, respectively).
Weight, adiposity, energy metabolism, and hormonal measures did not differ significantly between the pre-daytime and pre-delayed eating conditions, suggesting that they returned to pre-condition levels after the washout period.
“One of the things we’re advocating is that with consistent daytime eating, you can lose weight and/or remain at weight maintenance,” Dr. Goel said. “Consistency is very important. Across 8 weeks, you’re becoming metabolically healthier because you’re not eating that late-night meal or snack. We had shown in previous sleep loss studies that people were eating 500 calories late in the evening on consecutive nights and gaining a substantial amount of weight.”
She and her colleagues are currently enrolling obese individuals into a similarly designed trial, “where we expect much bigger changes metabolically,” she said. The study was funded by a grant from the National Institutes of Health. Dr. Goel reported having no financial disclosures.
SOURCE: Goel N et al. SLEEP 2019, Abstract 0036.
SAN ANTONIO – In adults of normal weight, a small controlled study has shown that a , independent of caloric intake.
The findings come from an 8-week controlled trial presented at the annual meeting of the Associated Professional Sleep Societies, which set out to examine the impact of a daytime versus delayed eating schedule on body mass, adiposity, and energy homeostasis in adults of normal weight.
“It is best to stop eating as early as possible in the day, and to not eat late at night,” the study’s first author, Namni Goel, PhD, said in an interview at the meeting. “There’s an open question in our field: Should you stop eating at 7:00 p.m.? 8:00 p.m.? My own feeling is, the longer it is between when you stop eating and go to bed, the better off you are metabolically.”
Dr. Goel, associate professor in the division of sleep and chronobiology in the department of psychiatry at the University of Pennsylvania, Philadelphia, and colleagues enrolled 12 healthy adults to participate in a randomized cross-over study in free-living conditions. Three meals and two snacks consisting of comparable energy and macronutrient content were provided during two 8-week counterbalanced phases: 1) daytime eating (food consumed between 8:00 a.m. and 7:00 p.m, and 2) delayed eating (food consumed between 12:00 p.m. and 11:00 p.m. A 2-week washout period occurred between the conditions. “What we wanted to do is just manipulate the timing of eating and we provided all of the meals so we could control the caloric intake,” Dr. Goel said.
The researchers asked participants to maintain a sleep-wake cycle between 11:00 p.m. and 9:00 a.m. (verified by wrist actigraphy) and to limit physical activity. They assessed weight, adiposity, energy metabolism, and hormonal markers during four inpatient visits: 1) baseline; 2) after the first eating condition; 3) after the washout period, before the second eating condition began; and 4) after the second eating condition. They used two-way analysis of variance and Cohen’s d effect sizes to examine changes in anthropometrics and metabolic measures affected by eating schedule (daytime vs. delayed) and time (before vs. after each eating schedule).
The mean age of 12 study participants was 26 years; five were females. Their mean body mass index was 21.9 kg/m2. Dr. Goel reported that participants had excellent adherence to assigned eating schedules, with no differences between the conditions. Weight was decreased on the daytime vs. delayed eating schedule. Specifically, Cohen’s d effect sizes were 0.57 overall: 1.16 for females and 0.33 for males, all in the small to large range. Resting energy expenditure, respiratory quotient, and trunk fat percentage/leg fat percentage were decreased on the daytime vs. delayed eating condition, with Cohen’s d effect sizes of 0.45-1.02, all in the medium to large range. In addition, total cholesterol and insulin were decreased on the daytime eating condition (medium effect sizes of 0.60 and 0.57, respectively), while triglycerides and glucose were increased on the delayed condition (medium effect sizes of 0.46 and 0.52, respectively).
Weight, adiposity, energy metabolism, and hormonal measures did not differ significantly between the pre-daytime and pre-delayed eating conditions, suggesting that they returned to pre-condition levels after the washout period.
“One of the things we’re advocating is that with consistent daytime eating, you can lose weight and/or remain at weight maintenance,” Dr. Goel said. “Consistency is very important. Across 8 weeks, you’re becoming metabolically healthier because you’re not eating that late-night meal or snack. We had shown in previous sleep loss studies that people were eating 500 calories late in the evening on consecutive nights and gaining a substantial amount of weight.”
She and her colleagues are currently enrolling obese individuals into a similarly designed trial, “where we expect much bigger changes metabolically,” she said. The study was funded by a grant from the National Institutes of Health. Dr. Goel reported having no financial disclosures.
SOURCE: Goel N et al. SLEEP 2019, Abstract 0036.
SAN ANTONIO – In adults of normal weight, a small controlled study has shown that a , independent of caloric intake.
The findings come from an 8-week controlled trial presented at the annual meeting of the Associated Professional Sleep Societies, which set out to examine the impact of a daytime versus delayed eating schedule on body mass, adiposity, and energy homeostasis in adults of normal weight.
“It is best to stop eating as early as possible in the day, and to not eat late at night,” the study’s first author, Namni Goel, PhD, said in an interview at the meeting. “There’s an open question in our field: Should you stop eating at 7:00 p.m.? 8:00 p.m.? My own feeling is, the longer it is between when you stop eating and go to bed, the better off you are metabolically.”
Dr. Goel, associate professor in the division of sleep and chronobiology in the department of psychiatry at the University of Pennsylvania, Philadelphia, and colleagues enrolled 12 healthy adults to participate in a randomized cross-over study in free-living conditions. Three meals and two snacks consisting of comparable energy and macronutrient content were provided during two 8-week counterbalanced phases: 1) daytime eating (food consumed between 8:00 a.m. and 7:00 p.m, and 2) delayed eating (food consumed between 12:00 p.m. and 11:00 p.m. A 2-week washout period occurred between the conditions. “What we wanted to do is just manipulate the timing of eating and we provided all of the meals so we could control the caloric intake,” Dr. Goel said.
The researchers asked participants to maintain a sleep-wake cycle between 11:00 p.m. and 9:00 a.m. (verified by wrist actigraphy) and to limit physical activity. They assessed weight, adiposity, energy metabolism, and hormonal markers during four inpatient visits: 1) baseline; 2) after the first eating condition; 3) after the washout period, before the second eating condition began; and 4) after the second eating condition. They used two-way analysis of variance and Cohen’s d effect sizes to examine changes in anthropometrics and metabolic measures affected by eating schedule (daytime vs. delayed) and time (before vs. after each eating schedule).
The mean age of 12 study participants was 26 years; five were females. Their mean body mass index was 21.9 kg/m2. Dr. Goel reported that participants had excellent adherence to assigned eating schedules, with no differences between the conditions. Weight was decreased on the daytime vs. delayed eating schedule. Specifically, Cohen’s d effect sizes were 0.57 overall: 1.16 for females and 0.33 for males, all in the small to large range. Resting energy expenditure, respiratory quotient, and trunk fat percentage/leg fat percentage were decreased on the daytime vs. delayed eating condition, with Cohen’s d effect sizes of 0.45-1.02, all in the medium to large range. In addition, total cholesterol and insulin were decreased on the daytime eating condition (medium effect sizes of 0.60 and 0.57, respectively), while triglycerides and glucose were increased on the delayed condition (medium effect sizes of 0.46 and 0.52, respectively).
Weight, adiposity, energy metabolism, and hormonal measures did not differ significantly between the pre-daytime and pre-delayed eating conditions, suggesting that they returned to pre-condition levels after the washout period.
“One of the things we’re advocating is that with consistent daytime eating, you can lose weight and/or remain at weight maintenance,” Dr. Goel said. “Consistency is very important. Across 8 weeks, you’re becoming metabolically healthier because you’re not eating that late-night meal or snack. We had shown in previous sleep loss studies that people were eating 500 calories late in the evening on consecutive nights and gaining a substantial amount of weight.”
She and her colleagues are currently enrolling obese individuals into a similarly designed trial, “where we expect much bigger changes metabolically,” she said. The study was funded by a grant from the National Institutes of Health. Dr. Goel reported having no financial disclosures.
SOURCE: Goel N et al. SLEEP 2019, Abstract 0036.
REPORTING FROM SLEEP 2019
Key clinical point: A daytime eating schedule is likely beneficial for weight management and metabolic health.
Major finding: Weight was decreased on the daytime vs. delayed eating schedule with Cohen’s d effect of 0.57 overall: 1.16 for females and 0.33 for males, all in the small to large range.
Study details: A randomized trial of 12 healthy adults with normal body weight.
Disclosures: The study was funded by a grant from the National Institutes of Health. Dr. Goel reported having no financial disclosures.
Source: Goel N et al. SLEEP 2019, Abstract 0036.
Children with Down syndrome may need more screening for sleep-disordered breathing
because the condition frequently persists and recurs.
“Current screening recommendations to assess for SDB at a particular age may not be adequate in this population,” the authors of the study stated, adding that “persistence/recurrence of SDB is not easily predicted.”
The study, led by Joy Nehme, BSc, of Children’s Hospital of Eastern Ontario and the University of Ottawa, was published in Pediatric Pulmonology.
According to the study, research suggests that 43%-66% of children with Down syndrome have SDB, a category that encompasses sleep apnea (both obstructive and central) and hypoventilation. Those numbers are several times higher than the prevalence of SDB in children in the general population (1%-5%).
“Because SDB is associated with cardiometabolic and neurocognitive morbidity, its prompt and accurate diagnosis is important,” the researchers wrote. However, diagnosis requires a sleep study, which is not always performed although the American Academy of Pediatrics recommends children with Down syndrome undergo one by age 4.
Treatments include adenotonsillectomy (considered first-line), positive airway pressure, and lingual tonsillectomy.
The study aims to fill in gaps in knowledge about the condition over the long term since “there is little available literature on the trajectory of SDB in children and youth with Down syndrome over time.”
The researchers launched a retrospective study of 560 children with Down syndrome who were treated from 2004 to 2015 at Children’s Hospital of Eastern Ontario. Of those, 120 showed signs of SDB and underwent sleep studies (48% male, median age 6.6 years [range 4.5-10.5], median total apnea‐hypopnea index events per hour = 3.4 [1.6-10.8]).
Of the 120 children, 67 (56%) had obstructive-mixed SDB, 9 (8%) had central sleep apnea, and 5 (4%) had hypoventilation. The others (39, 32%) had no SDB.
Fifty-four children underwent at least two sleep studies during the period of the study, with at least one undergoing seven.
Researchers found weak, nonsignificant evidence that SDB persistence/occurrence varied by age (odds ratio per year = 1.15; 95% confidence interval, 0.96-1.41; P = .13).
As for treatment, adenotonsillectomy was most common, although “previous studies have ... shown that moderate to severe OSA in children with Down syndrome is likely to persist after a tonsillectomy.”
In regard to obstructive sleep apnea (OSA) specifically, the authors wrote, “our study ... showed that OSA‐SDB persisted or recurred in the vast majority of children. Further, persistence/recurrence could not be predicted by clinical features or SDB severity in our study. This, therefore, highlights the need for serial longitudinal screening for SDB in this population and for follow‐up PSG to ensure the success of treatment interventions.”
No study funding was reported. The study authors reported no disclosures.
SOURCE: Nehme J et al. Pediatr Pulmonol. 2019 Jun 6. doi: 10.1002/ppul.24380.
because the condition frequently persists and recurs.
“Current screening recommendations to assess for SDB at a particular age may not be adequate in this population,” the authors of the study stated, adding that “persistence/recurrence of SDB is not easily predicted.”
The study, led by Joy Nehme, BSc, of Children’s Hospital of Eastern Ontario and the University of Ottawa, was published in Pediatric Pulmonology.
According to the study, research suggests that 43%-66% of children with Down syndrome have SDB, a category that encompasses sleep apnea (both obstructive and central) and hypoventilation. Those numbers are several times higher than the prevalence of SDB in children in the general population (1%-5%).
“Because SDB is associated with cardiometabolic and neurocognitive morbidity, its prompt and accurate diagnosis is important,” the researchers wrote. However, diagnosis requires a sleep study, which is not always performed although the American Academy of Pediatrics recommends children with Down syndrome undergo one by age 4.
Treatments include adenotonsillectomy (considered first-line), positive airway pressure, and lingual tonsillectomy.
The study aims to fill in gaps in knowledge about the condition over the long term since “there is little available literature on the trajectory of SDB in children and youth with Down syndrome over time.”
The researchers launched a retrospective study of 560 children with Down syndrome who were treated from 2004 to 2015 at Children’s Hospital of Eastern Ontario. Of those, 120 showed signs of SDB and underwent sleep studies (48% male, median age 6.6 years [range 4.5-10.5], median total apnea‐hypopnea index events per hour = 3.4 [1.6-10.8]).
Of the 120 children, 67 (56%) had obstructive-mixed SDB, 9 (8%) had central sleep apnea, and 5 (4%) had hypoventilation. The others (39, 32%) had no SDB.
Fifty-four children underwent at least two sleep studies during the period of the study, with at least one undergoing seven.
Researchers found weak, nonsignificant evidence that SDB persistence/occurrence varied by age (odds ratio per year = 1.15; 95% confidence interval, 0.96-1.41; P = .13).
As for treatment, adenotonsillectomy was most common, although “previous studies have ... shown that moderate to severe OSA in children with Down syndrome is likely to persist after a tonsillectomy.”
In regard to obstructive sleep apnea (OSA) specifically, the authors wrote, “our study ... showed that OSA‐SDB persisted or recurred in the vast majority of children. Further, persistence/recurrence could not be predicted by clinical features or SDB severity in our study. This, therefore, highlights the need for serial longitudinal screening for SDB in this population and for follow‐up PSG to ensure the success of treatment interventions.”
No study funding was reported. The study authors reported no disclosures.
SOURCE: Nehme J et al. Pediatr Pulmonol. 2019 Jun 6. doi: 10.1002/ppul.24380.
because the condition frequently persists and recurs.
“Current screening recommendations to assess for SDB at a particular age may not be adequate in this population,” the authors of the study stated, adding that “persistence/recurrence of SDB is not easily predicted.”
The study, led by Joy Nehme, BSc, of Children’s Hospital of Eastern Ontario and the University of Ottawa, was published in Pediatric Pulmonology.
According to the study, research suggests that 43%-66% of children with Down syndrome have SDB, a category that encompasses sleep apnea (both obstructive and central) and hypoventilation. Those numbers are several times higher than the prevalence of SDB in children in the general population (1%-5%).
“Because SDB is associated with cardiometabolic and neurocognitive morbidity, its prompt and accurate diagnosis is important,” the researchers wrote. However, diagnosis requires a sleep study, which is not always performed although the American Academy of Pediatrics recommends children with Down syndrome undergo one by age 4.
Treatments include adenotonsillectomy (considered first-line), positive airway pressure, and lingual tonsillectomy.
The study aims to fill in gaps in knowledge about the condition over the long term since “there is little available literature on the trajectory of SDB in children and youth with Down syndrome over time.”
The researchers launched a retrospective study of 560 children with Down syndrome who were treated from 2004 to 2015 at Children’s Hospital of Eastern Ontario. Of those, 120 showed signs of SDB and underwent sleep studies (48% male, median age 6.6 years [range 4.5-10.5], median total apnea‐hypopnea index events per hour = 3.4 [1.6-10.8]).
Of the 120 children, 67 (56%) had obstructive-mixed SDB, 9 (8%) had central sleep apnea, and 5 (4%) had hypoventilation. The others (39, 32%) had no SDB.
Fifty-four children underwent at least two sleep studies during the period of the study, with at least one undergoing seven.
Researchers found weak, nonsignificant evidence that SDB persistence/occurrence varied by age (odds ratio per year = 1.15; 95% confidence interval, 0.96-1.41; P = .13).
As for treatment, adenotonsillectomy was most common, although “previous studies have ... shown that moderate to severe OSA in children with Down syndrome is likely to persist after a tonsillectomy.”
In regard to obstructive sleep apnea (OSA) specifically, the authors wrote, “our study ... showed that OSA‐SDB persisted or recurred in the vast majority of children. Further, persistence/recurrence could not be predicted by clinical features or SDB severity in our study. This, therefore, highlights the need for serial longitudinal screening for SDB in this population and for follow‐up PSG to ensure the success of treatment interventions.”
No study funding was reported. The study authors reported no disclosures.
SOURCE: Nehme J et al. Pediatr Pulmonol. 2019 Jun 6. doi: 10.1002/ppul.24380.
FROM PEDIATRIC PULMONOLOGY
Key clinical point: Sleep-disordered breathing (SDB) can be persistent and recurrent in children with Down syndrome, and long-term monitoring is warranted.
Major finding: SDB persistence/recurrence did not vary by age (odds ratio per year = 1.15; 95% confidence interval, 0.96-1.41; P = .13).
Study details: Retrospective cohort analysis of 120 children with Down syndrome tested via sleep study at least once for SDB (48% male, median age 6.6 years).
Disclosures: No study funding or author disclosures were reported.
Source: Nehme J et al. Pediatr Pulmonol. 2019 Jun 6. doi: 10.1002/ppul.24380.
Treat insomnia as a full-fledged disorder
CRYSTAL CITY, VA. – Insomnia is a neuropsychiatric disorder of hyperarousal that should be evaluated as a disorder and treated with any associated comorbid conditions, Karl Doghramji, MD, said at Focus on Neuropsychiatry presented by Current Psychiatry and the American Academy of Clinical Psychiatrists.
“When I was a resident, I used to say insomnia is never a disorder. It’s always a symptom; you’ve got to find the primary disorder to know what the insomnia is caused by,” said Dr. Doghramji, medical director of the Jefferson Sleep Disorders Center at Jefferson Medical College, Philadelphia. “We no longer believe that. Throw that out the window.”
According to the new definition under the DSM-5, insomnia is characterized by dissatisfaction with sleep quality or quantity in the presence of adequate opportunity for sleep that causes significant distress or impairment for more than 3 nights per week over a period of 3 months. A survey of almost 7,500 U.S. health plan subscribers conducted a few years ago found that the prevalence of insomnia was estimated at 23.2% (Sleep. 2011 Sep 1;34[9]:1161-71).
Insomnia is also not well identified in clinical practice: In results published from his own group, Dr. Doghramji and colleagues evaluated 97 patients who were administered the Insomnia Severity Index; of those patients, 79.4% met the criteria for insomnia, but there was no mention of insomnia in the discharge notes for those patients (J Nerv Ment Dis. 2018 Oct;206[10]:765-9).
Many cognitive impairments can occur as a result of insomnia, which affects performance at work; decreases enjoyment of social activities; can lead to motor vehicle accidents or falls; and can affect health in the form of diabetes, hypertension, and increased mortality. Insomnia also can predict the risk of future depression and is a risk factor for suicide, Dr. Doghramji said at the meeting presented by Global Academy for Medical Education.
Adults can have insomnia for many reasons, including genetics, stress, negative conditioning, intrapsychic conflict, and bad habits, as well as medical and psychiatric conditions. While knowledge surrounding insomnia has advanced under a hyperarousal model, “It is really a hyperarousal disturbance which defies psychological understanding,” said Dr. Doghramji, who is also professor of psychiatry, neurology, and medicine at the university.
Evaluating the type of insomnia a patient is experiencing should be the first step in managing the disorder, followed by determining whether the insomnia is contributing to daytime impairment or decreased quality of life for the patient. From there, the insomnia can be treated with behavioral or pharmacotherapy. However, if insomnia is associated with another comorbid condition, the condition should be treated alongside the insomnia.
Sleep is highly comorbid with psychiatric and medical conditions (Sleep Med Clin. 2019 Jun;14[2]:167-75). Initial insomnia is more likely to be associated with delayed sleep phase disorder and restless legs syndrome, while middle insomnia is associated with sleep apnea and depression. Patients who wake early and are unable to go back to sleep (terminal insomnia) are likely to have depression, shift work disorder, or advanced sleep phase disorder.
said Dr. Doghramji. The comorbid condition also should be considered when deciding how to treat insomnia. For example, a patient with gastroesophageal reflux disease and insomnia would be more suited to cognitive-behavioral therapy than pharmacologic agents to help with sleep, because being able to wake up during the night from acid building in the esophagus is the body’s defense mechanism for the disease, Dr. Doghramji said.
Dr. Doghramji reported serving as a consultant for Eisai, Merck, and Pfizer. He also receives research funding from and owns stock in Merck.
Global Academy for Medical Education, Current Psychiatry, and this news organization are owned by the same company.
CRYSTAL CITY, VA. – Insomnia is a neuropsychiatric disorder of hyperarousal that should be evaluated as a disorder and treated with any associated comorbid conditions, Karl Doghramji, MD, said at Focus on Neuropsychiatry presented by Current Psychiatry and the American Academy of Clinical Psychiatrists.
“When I was a resident, I used to say insomnia is never a disorder. It’s always a symptom; you’ve got to find the primary disorder to know what the insomnia is caused by,” said Dr. Doghramji, medical director of the Jefferson Sleep Disorders Center at Jefferson Medical College, Philadelphia. “We no longer believe that. Throw that out the window.”
According to the new definition under the DSM-5, insomnia is characterized by dissatisfaction with sleep quality or quantity in the presence of adequate opportunity for sleep that causes significant distress or impairment for more than 3 nights per week over a period of 3 months. A survey of almost 7,500 U.S. health plan subscribers conducted a few years ago found that the prevalence of insomnia was estimated at 23.2% (Sleep. 2011 Sep 1;34[9]:1161-71).
Insomnia is also not well identified in clinical practice: In results published from his own group, Dr. Doghramji and colleagues evaluated 97 patients who were administered the Insomnia Severity Index; of those patients, 79.4% met the criteria for insomnia, but there was no mention of insomnia in the discharge notes for those patients (J Nerv Ment Dis. 2018 Oct;206[10]:765-9).
Many cognitive impairments can occur as a result of insomnia, which affects performance at work; decreases enjoyment of social activities; can lead to motor vehicle accidents or falls; and can affect health in the form of diabetes, hypertension, and increased mortality. Insomnia also can predict the risk of future depression and is a risk factor for suicide, Dr. Doghramji said at the meeting presented by Global Academy for Medical Education.
Adults can have insomnia for many reasons, including genetics, stress, negative conditioning, intrapsychic conflict, and bad habits, as well as medical and psychiatric conditions. While knowledge surrounding insomnia has advanced under a hyperarousal model, “It is really a hyperarousal disturbance which defies psychological understanding,” said Dr. Doghramji, who is also professor of psychiatry, neurology, and medicine at the university.
Evaluating the type of insomnia a patient is experiencing should be the first step in managing the disorder, followed by determining whether the insomnia is contributing to daytime impairment or decreased quality of life for the patient. From there, the insomnia can be treated with behavioral or pharmacotherapy. However, if insomnia is associated with another comorbid condition, the condition should be treated alongside the insomnia.
Sleep is highly comorbid with psychiatric and medical conditions (Sleep Med Clin. 2019 Jun;14[2]:167-75). Initial insomnia is more likely to be associated with delayed sleep phase disorder and restless legs syndrome, while middle insomnia is associated with sleep apnea and depression. Patients who wake early and are unable to go back to sleep (terminal insomnia) are likely to have depression, shift work disorder, or advanced sleep phase disorder.
said Dr. Doghramji. The comorbid condition also should be considered when deciding how to treat insomnia. For example, a patient with gastroesophageal reflux disease and insomnia would be more suited to cognitive-behavioral therapy than pharmacologic agents to help with sleep, because being able to wake up during the night from acid building in the esophagus is the body’s defense mechanism for the disease, Dr. Doghramji said.
Dr. Doghramji reported serving as a consultant for Eisai, Merck, and Pfizer. He also receives research funding from and owns stock in Merck.
Global Academy for Medical Education, Current Psychiatry, and this news organization are owned by the same company.
CRYSTAL CITY, VA. – Insomnia is a neuropsychiatric disorder of hyperarousal that should be evaluated as a disorder and treated with any associated comorbid conditions, Karl Doghramji, MD, said at Focus on Neuropsychiatry presented by Current Psychiatry and the American Academy of Clinical Psychiatrists.
“When I was a resident, I used to say insomnia is never a disorder. It’s always a symptom; you’ve got to find the primary disorder to know what the insomnia is caused by,” said Dr. Doghramji, medical director of the Jefferson Sleep Disorders Center at Jefferson Medical College, Philadelphia. “We no longer believe that. Throw that out the window.”
According to the new definition under the DSM-5, insomnia is characterized by dissatisfaction with sleep quality or quantity in the presence of adequate opportunity for sleep that causes significant distress or impairment for more than 3 nights per week over a period of 3 months. A survey of almost 7,500 U.S. health plan subscribers conducted a few years ago found that the prevalence of insomnia was estimated at 23.2% (Sleep. 2011 Sep 1;34[9]:1161-71).
Insomnia is also not well identified in clinical practice: In results published from his own group, Dr. Doghramji and colleagues evaluated 97 patients who were administered the Insomnia Severity Index; of those patients, 79.4% met the criteria for insomnia, but there was no mention of insomnia in the discharge notes for those patients (J Nerv Ment Dis. 2018 Oct;206[10]:765-9).
Many cognitive impairments can occur as a result of insomnia, which affects performance at work; decreases enjoyment of social activities; can lead to motor vehicle accidents or falls; and can affect health in the form of diabetes, hypertension, and increased mortality. Insomnia also can predict the risk of future depression and is a risk factor for suicide, Dr. Doghramji said at the meeting presented by Global Academy for Medical Education.
Adults can have insomnia for many reasons, including genetics, stress, negative conditioning, intrapsychic conflict, and bad habits, as well as medical and psychiatric conditions. While knowledge surrounding insomnia has advanced under a hyperarousal model, “It is really a hyperarousal disturbance which defies psychological understanding,” said Dr. Doghramji, who is also professor of psychiatry, neurology, and medicine at the university.
Evaluating the type of insomnia a patient is experiencing should be the first step in managing the disorder, followed by determining whether the insomnia is contributing to daytime impairment or decreased quality of life for the patient. From there, the insomnia can be treated with behavioral or pharmacotherapy. However, if insomnia is associated with another comorbid condition, the condition should be treated alongside the insomnia.
Sleep is highly comorbid with psychiatric and medical conditions (Sleep Med Clin. 2019 Jun;14[2]:167-75). Initial insomnia is more likely to be associated with delayed sleep phase disorder and restless legs syndrome, while middle insomnia is associated with sleep apnea and depression. Patients who wake early and are unable to go back to sleep (terminal insomnia) are likely to have depression, shift work disorder, or advanced sleep phase disorder.
said Dr. Doghramji. The comorbid condition also should be considered when deciding how to treat insomnia. For example, a patient with gastroesophageal reflux disease and insomnia would be more suited to cognitive-behavioral therapy than pharmacologic agents to help with sleep, because being able to wake up during the night from acid building in the esophagus is the body’s defense mechanism for the disease, Dr. Doghramji said.
Dr. Doghramji reported serving as a consultant for Eisai, Merck, and Pfizer. He also receives research funding from and owns stock in Merck.
Global Academy for Medical Education, Current Psychiatry, and this news organization are owned by the same company.
EXPERT ANALYSIS FROM FOCUS ON NEUROPSYCHIATRY 2019
COPD exacerbations associated with poor sleep quality
in an 18-month prospective study of 480 patients.
“Poor sleep quality in COPD has previously been associated with reduced health-related quality of life and reduced physical activity during the day,” wrote Matthew Shorofsky, MD, of McGill University, Montreal, and associates. Their report is in CHEST. “However, to our knowledge, this is the first population-based longitudinal study evaluating exacerbation risk in relation to subjective sleep disturbances and assessing previously diagnosed and undiagnosed COPD.”
The study included participants enrolled in the Canadian Respiratory Research Network and the Canadian Cohort Obstructive Lung Disease (CanCOLD) study who had COPD, available baseline PSQI scores, and 18 months of follow-up data. The PSQI includes 19 questions on sleep quality, latency, duration, efficiency, disturbances, use of sleep medications, and daytime dysfunction. Total score ranges between 0 and 21, and a score above 5 is considered poor sleep. Online patient surveys and quarterly phone interviews were used to track symptom-based exacerbations (at least 48 hours of increased dyspnea, sputum volume, or sputum purulence) and event-based exacerbations (a symptom-based exacerbation plus the use antibiotics or corticosteroids or health services).
At baseline, 203 patients met the PSQI threshold for poor sleep quality. During follow-up, 185 patients had at least one COPD exacerbation. Poor sleep at baseline was significantly more prevalent among patients with symptoms-based COPD exacerbations (50.3%) than among patients without symptoms-based exacerbations (37.3%; P = .01). Poor baseline sleep quality remained a significant risk factor for symptom-based exacerbations of COPD even after the researchers accounted for the effect of age, gender, body mass index, smoking, depression, angina, baseline inhaled respiratory medications, forced expiratory volume in 1 second %predicted, and modified Medical Research Council (mMRC) dyspnea scale (adjusted risk ratio, 1.09; 95% confidence interval, 1.01-1.18; P =.02).
Patients with at least one symptomatic exacerbation of COPD were significantly more likely to meet the threshold for poor sleep quality on the Pittsburgh Sleep Quality Index and have significantly higher median PSQI scores compared with patients without exacerbations (6.0 [interquartile range, 3.0 to 8.0] vs. 5.0 [2.0 to 7.0]; P = .01). Poor baseline sleep quality also was associated with event-based exacerbations and with a shorter time to symptoms-based exacerbations. Sleep disturbances, such as rising to void or experiencing respiratory issues or pain during sleep, correlated most strongly with symptoms-based exacerbations.
Several factors could explain the link between poor sleep quality and COPD exacerbations, the investigators wrote. Patients with inadequately controlled COPD have more frequent and unstable respiratory symptoms, which could disrupt sleep either directly or indirectly (secondary to medication use or anxiety, for example). Conversely, sleep disruption can impede immune function and increase systemic inflammation, which might worsen COPD control and increase exacerbation risk. Poor sleep can impair memory and cognition, “potentially fostering medication nonadherence and symptom flare-up, especially in the older COPD population.” Although the link is poorly understood, patients with COPD often have comorbid obstructive sleep apnea (OSA), which is associated with COPD exacerbations, the researchers wrote. Treating OSA is associated with improved COPD morbidity and fewer exacerbations and hospitalizations.
The researchers acknowledged limitations to their study design. “Individuals with asthma or other obstructive lung diseases could not be definitively excluded; methacholine challenges were not performed. However, analyses excluding self-reported asthma were consistent with our main results. Second, because definitions of COPD exacerbation vary among studies, comparison may be limited, but CanCOLD used a standard definition, as recommended by GOLD.”
The CanCOLD study has received funding from the Canadian Respiratory Research Network, Astra Zeneca Canada, Boehringer Ingelheim Canada, GlaxoSmithKline Canada, Novartis, Merck Nycomed, Pfizer Canada, and Theratechnologies. Dr. Shorofsky had no disclosures. Several coinvestigators reported ties to GlaxoSmithKline, Novartis, Boehringer Ingelheim, Merck, Almirall, and Theratechnologies.
SOURCE: Shorofsky M et al. CHEST. 2019 May 28. doi: 10.1016/j.chest.2019.04.132.
in an 18-month prospective study of 480 patients.
“Poor sleep quality in COPD has previously been associated with reduced health-related quality of life and reduced physical activity during the day,” wrote Matthew Shorofsky, MD, of McGill University, Montreal, and associates. Their report is in CHEST. “However, to our knowledge, this is the first population-based longitudinal study evaluating exacerbation risk in relation to subjective sleep disturbances and assessing previously diagnosed and undiagnosed COPD.”
The study included participants enrolled in the Canadian Respiratory Research Network and the Canadian Cohort Obstructive Lung Disease (CanCOLD) study who had COPD, available baseline PSQI scores, and 18 months of follow-up data. The PSQI includes 19 questions on sleep quality, latency, duration, efficiency, disturbances, use of sleep medications, and daytime dysfunction. Total score ranges between 0 and 21, and a score above 5 is considered poor sleep. Online patient surveys and quarterly phone interviews were used to track symptom-based exacerbations (at least 48 hours of increased dyspnea, sputum volume, or sputum purulence) and event-based exacerbations (a symptom-based exacerbation plus the use antibiotics or corticosteroids or health services).
At baseline, 203 patients met the PSQI threshold for poor sleep quality. During follow-up, 185 patients had at least one COPD exacerbation. Poor sleep at baseline was significantly more prevalent among patients with symptoms-based COPD exacerbations (50.3%) than among patients without symptoms-based exacerbations (37.3%; P = .01). Poor baseline sleep quality remained a significant risk factor for symptom-based exacerbations of COPD even after the researchers accounted for the effect of age, gender, body mass index, smoking, depression, angina, baseline inhaled respiratory medications, forced expiratory volume in 1 second %predicted, and modified Medical Research Council (mMRC) dyspnea scale (adjusted risk ratio, 1.09; 95% confidence interval, 1.01-1.18; P =.02).
Patients with at least one symptomatic exacerbation of COPD were significantly more likely to meet the threshold for poor sleep quality on the Pittsburgh Sleep Quality Index and have significantly higher median PSQI scores compared with patients without exacerbations (6.0 [interquartile range, 3.0 to 8.0] vs. 5.0 [2.0 to 7.0]; P = .01). Poor baseline sleep quality also was associated with event-based exacerbations and with a shorter time to symptoms-based exacerbations. Sleep disturbances, such as rising to void or experiencing respiratory issues or pain during sleep, correlated most strongly with symptoms-based exacerbations.
Several factors could explain the link between poor sleep quality and COPD exacerbations, the investigators wrote. Patients with inadequately controlled COPD have more frequent and unstable respiratory symptoms, which could disrupt sleep either directly or indirectly (secondary to medication use or anxiety, for example). Conversely, sleep disruption can impede immune function and increase systemic inflammation, which might worsen COPD control and increase exacerbation risk. Poor sleep can impair memory and cognition, “potentially fostering medication nonadherence and symptom flare-up, especially in the older COPD population.” Although the link is poorly understood, patients with COPD often have comorbid obstructive sleep apnea (OSA), which is associated with COPD exacerbations, the researchers wrote. Treating OSA is associated with improved COPD morbidity and fewer exacerbations and hospitalizations.
The researchers acknowledged limitations to their study design. “Individuals with asthma or other obstructive lung diseases could not be definitively excluded; methacholine challenges were not performed. However, analyses excluding self-reported asthma were consistent with our main results. Second, because definitions of COPD exacerbation vary among studies, comparison may be limited, but CanCOLD used a standard definition, as recommended by GOLD.”
The CanCOLD study has received funding from the Canadian Respiratory Research Network, Astra Zeneca Canada, Boehringer Ingelheim Canada, GlaxoSmithKline Canada, Novartis, Merck Nycomed, Pfizer Canada, and Theratechnologies. Dr. Shorofsky had no disclosures. Several coinvestigators reported ties to GlaxoSmithKline, Novartis, Boehringer Ingelheim, Merck, Almirall, and Theratechnologies.
SOURCE: Shorofsky M et al. CHEST. 2019 May 28. doi: 10.1016/j.chest.2019.04.132.
in an 18-month prospective study of 480 patients.
“Poor sleep quality in COPD has previously been associated with reduced health-related quality of life and reduced physical activity during the day,” wrote Matthew Shorofsky, MD, of McGill University, Montreal, and associates. Their report is in CHEST. “However, to our knowledge, this is the first population-based longitudinal study evaluating exacerbation risk in relation to subjective sleep disturbances and assessing previously diagnosed and undiagnosed COPD.”
The study included participants enrolled in the Canadian Respiratory Research Network and the Canadian Cohort Obstructive Lung Disease (CanCOLD) study who had COPD, available baseline PSQI scores, and 18 months of follow-up data. The PSQI includes 19 questions on sleep quality, latency, duration, efficiency, disturbances, use of sleep medications, and daytime dysfunction. Total score ranges between 0 and 21, and a score above 5 is considered poor sleep. Online patient surveys and quarterly phone interviews were used to track symptom-based exacerbations (at least 48 hours of increased dyspnea, sputum volume, or sputum purulence) and event-based exacerbations (a symptom-based exacerbation plus the use antibiotics or corticosteroids or health services).
At baseline, 203 patients met the PSQI threshold for poor sleep quality. During follow-up, 185 patients had at least one COPD exacerbation. Poor sleep at baseline was significantly more prevalent among patients with symptoms-based COPD exacerbations (50.3%) than among patients without symptoms-based exacerbations (37.3%; P = .01). Poor baseline sleep quality remained a significant risk factor for symptom-based exacerbations of COPD even after the researchers accounted for the effect of age, gender, body mass index, smoking, depression, angina, baseline inhaled respiratory medications, forced expiratory volume in 1 second %predicted, and modified Medical Research Council (mMRC) dyspnea scale (adjusted risk ratio, 1.09; 95% confidence interval, 1.01-1.18; P =.02).
Patients with at least one symptomatic exacerbation of COPD were significantly more likely to meet the threshold for poor sleep quality on the Pittsburgh Sleep Quality Index and have significantly higher median PSQI scores compared with patients without exacerbations (6.0 [interquartile range, 3.0 to 8.0] vs. 5.0 [2.0 to 7.0]; P = .01). Poor baseline sleep quality also was associated with event-based exacerbations and with a shorter time to symptoms-based exacerbations. Sleep disturbances, such as rising to void or experiencing respiratory issues or pain during sleep, correlated most strongly with symptoms-based exacerbations.
Several factors could explain the link between poor sleep quality and COPD exacerbations, the investigators wrote. Patients with inadequately controlled COPD have more frequent and unstable respiratory symptoms, which could disrupt sleep either directly or indirectly (secondary to medication use or anxiety, for example). Conversely, sleep disruption can impede immune function and increase systemic inflammation, which might worsen COPD control and increase exacerbation risk. Poor sleep can impair memory and cognition, “potentially fostering medication nonadherence and symptom flare-up, especially in the older COPD population.” Although the link is poorly understood, patients with COPD often have comorbid obstructive sleep apnea (OSA), which is associated with COPD exacerbations, the researchers wrote. Treating OSA is associated with improved COPD morbidity and fewer exacerbations and hospitalizations.
The researchers acknowledged limitations to their study design. “Individuals with asthma or other obstructive lung diseases could not be definitively excluded; methacholine challenges were not performed. However, analyses excluding self-reported asthma were consistent with our main results. Second, because definitions of COPD exacerbation vary among studies, comparison may be limited, but CanCOLD used a standard definition, as recommended by GOLD.”
The CanCOLD study has received funding from the Canadian Respiratory Research Network, Astra Zeneca Canada, Boehringer Ingelheim Canada, GlaxoSmithKline Canada, Novartis, Merck Nycomed, Pfizer Canada, and Theratechnologies. Dr. Shorofsky had no disclosures. Several coinvestigators reported ties to GlaxoSmithKline, Novartis, Boehringer Ingelheim, Merck, Almirall, and Theratechnologies.
SOURCE: Shorofsky M et al. CHEST. 2019 May 28. doi: 10.1016/j.chest.2019.04.132.
FROM CHEST
New lemborexant efficacy and safety data unveiled
SAN ANTONIO – results from a pooled analysis showed.
A dual orexin receptor antagonist developed by Eisai, lemborexant is being studied as a treatment for insomnia disorder and irregular sleep-wake rhythm disorder. Early in 2019, the Food and Drug Administration accepted for review the New Drug Application for lemborexant for the treatment of insomnia. A target Prescription Drug User Fee Act date is set for Dec. 27, 2019.
“We evaluated early on whether exposure to lemborexant was going to be different between men and women,” lead study author Margaret Moline, PhD, said during an interview at the annual meeting of the Associated Professional Sleep Societies. “With some drugs, like zolpidem and other so-called Z drugs, because exposure is different, clinical studies could involve different dosing for different sexes. Because we knew the exposure to lemborexant wasn’t different between the sexes, we expected to see similar results in both sexes. That was the case.”
Dr. Moline, executive director of the Neurology Business Group and International Project Team Lead for the lemborexant clinical development program at Eisai, and colleagues presented pooled analyses of subject-reported sleep onset latency (sSOL) and subject-reported wake after sleep onset (sWASO) from lemborexant phase 3 studies, SUNRISE-1 and SUNRISE-2. SUNRISE-1 was a 1-month, double-blind, placebo- and active-controlled, parallel-group study in 1,006 subjects. Participants were females aged 55 years and older and males aged 65 years and older with a primary complaint of sleep maintenance difficulties and an Insomnia Severity Index (ISI) total score of 13 or higher. SUNRISE-2 was a placebo-controlled, 6-month, active treatment, double-blind, parallel-group study in 949 subjects with insomnia disorder. Participants were females and males aged 18 years and older with a primary complaint of sleep onset and/or sleep maintenance difficulties and an ISI total score of 15 or higher. Both analyses included subjects randomized to placebo, lemborexant 5 mg, or lemborexant 10 mg. Each study included a single-blind placebo run-in period prior to randomization.
The pooled analysis of 1,693 subjects included 402 (23.7%) men and 1,291 (76.3%) women. Results on sSOL and sWASO were consistent with the significant results on sleep diary in the individual studies. In both sexes, sSOL for lemborexant 5 mg and lemborexant 10 mg was significantly reduced versus that for placebo during the first 7 days and end of month 1 (P less than .05 for all comparisons). In women, the researchers observed significantly greater reductions in sWASO placebo for both lemborexant doses versus that with placebo (first 7 days and end of month 1; P less than .0001 for all comparisons). In males, sWASO decreased significantly, compared with placebo, for the first 7 days (lemborexant 5 mg and lemborexant 10 mg; P equal to or less than .0001) and at end of month 1 (lemborexant 10 mg only; P = .0032). For placebo, lemborexant 5 mg, and lemborexant 10 mg, the overall incidence of treatment-emergent adverse events was similar across sexes. Incidence of treatment-emergent serious adverse events was low for both sex subgroups; most events occurred in one subject each. Treatment-emergent adverse events leading to study drug withdrawal or interruption were few and similar across sexes for all treatments and was highest in males receiving lemborexant 10 mg. The most frequent treatment-emergent adverse events reported in males were somnolence, fatigue, and headache, while the most common in females were somnolence, headache, and urinary tract infection. About 3% of females (no males) reported a urinary tract infection; the incidence in females was similar across treatment groups.
“Overall, sleep diary outcomes in males and females were consistent with the significant results observed in the total populations of the individual studies,” Dr. Moline concluded. “A dose adjustment based on sex is not anticipated.”
The research was supported by Eisai. Dr. Moline is an employee of the company.
SOURCE: Moline M et al. Sleep 2019, Abstract 0368.
SAN ANTONIO – results from a pooled analysis showed.
A dual orexin receptor antagonist developed by Eisai, lemborexant is being studied as a treatment for insomnia disorder and irregular sleep-wake rhythm disorder. Early in 2019, the Food and Drug Administration accepted for review the New Drug Application for lemborexant for the treatment of insomnia. A target Prescription Drug User Fee Act date is set for Dec. 27, 2019.
“We evaluated early on whether exposure to lemborexant was going to be different between men and women,” lead study author Margaret Moline, PhD, said during an interview at the annual meeting of the Associated Professional Sleep Societies. “With some drugs, like zolpidem and other so-called Z drugs, because exposure is different, clinical studies could involve different dosing for different sexes. Because we knew the exposure to lemborexant wasn’t different between the sexes, we expected to see similar results in both sexes. That was the case.”
Dr. Moline, executive director of the Neurology Business Group and International Project Team Lead for the lemborexant clinical development program at Eisai, and colleagues presented pooled analyses of subject-reported sleep onset latency (sSOL) and subject-reported wake after sleep onset (sWASO) from lemborexant phase 3 studies, SUNRISE-1 and SUNRISE-2. SUNRISE-1 was a 1-month, double-blind, placebo- and active-controlled, parallel-group study in 1,006 subjects. Participants were females aged 55 years and older and males aged 65 years and older with a primary complaint of sleep maintenance difficulties and an Insomnia Severity Index (ISI) total score of 13 or higher. SUNRISE-2 was a placebo-controlled, 6-month, active treatment, double-blind, parallel-group study in 949 subjects with insomnia disorder. Participants were females and males aged 18 years and older with a primary complaint of sleep onset and/or sleep maintenance difficulties and an ISI total score of 15 or higher. Both analyses included subjects randomized to placebo, lemborexant 5 mg, or lemborexant 10 mg. Each study included a single-blind placebo run-in period prior to randomization.
The pooled analysis of 1,693 subjects included 402 (23.7%) men and 1,291 (76.3%) women. Results on sSOL and sWASO were consistent with the significant results on sleep diary in the individual studies. In both sexes, sSOL for lemborexant 5 mg and lemborexant 10 mg was significantly reduced versus that for placebo during the first 7 days and end of month 1 (P less than .05 for all comparisons). In women, the researchers observed significantly greater reductions in sWASO placebo for both lemborexant doses versus that with placebo (first 7 days and end of month 1; P less than .0001 for all comparisons). In males, sWASO decreased significantly, compared with placebo, for the first 7 days (lemborexant 5 mg and lemborexant 10 mg; P equal to or less than .0001) and at end of month 1 (lemborexant 10 mg only; P = .0032). For placebo, lemborexant 5 mg, and lemborexant 10 mg, the overall incidence of treatment-emergent adverse events was similar across sexes. Incidence of treatment-emergent serious adverse events was low for both sex subgroups; most events occurred in one subject each. Treatment-emergent adverse events leading to study drug withdrawal or interruption were few and similar across sexes for all treatments and was highest in males receiving lemborexant 10 mg. The most frequent treatment-emergent adverse events reported in males were somnolence, fatigue, and headache, while the most common in females were somnolence, headache, and urinary tract infection. About 3% of females (no males) reported a urinary tract infection; the incidence in females was similar across treatment groups.
“Overall, sleep diary outcomes in males and females were consistent with the significant results observed in the total populations of the individual studies,” Dr. Moline concluded. “A dose adjustment based on sex is not anticipated.”
The research was supported by Eisai. Dr. Moline is an employee of the company.
SOURCE: Moline M et al. Sleep 2019, Abstract 0368.
SAN ANTONIO – results from a pooled analysis showed.
A dual orexin receptor antagonist developed by Eisai, lemborexant is being studied as a treatment for insomnia disorder and irregular sleep-wake rhythm disorder. Early in 2019, the Food and Drug Administration accepted for review the New Drug Application for lemborexant for the treatment of insomnia. A target Prescription Drug User Fee Act date is set for Dec. 27, 2019.
“We evaluated early on whether exposure to lemborexant was going to be different between men and women,” lead study author Margaret Moline, PhD, said during an interview at the annual meeting of the Associated Professional Sleep Societies. “With some drugs, like zolpidem and other so-called Z drugs, because exposure is different, clinical studies could involve different dosing for different sexes. Because we knew the exposure to lemborexant wasn’t different between the sexes, we expected to see similar results in both sexes. That was the case.”
Dr. Moline, executive director of the Neurology Business Group and International Project Team Lead for the lemborexant clinical development program at Eisai, and colleagues presented pooled analyses of subject-reported sleep onset latency (sSOL) and subject-reported wake after sleep onset (sWASO) from lemborexant phase 3 studies, SUNRISE-1 and SUNRISE-2. SUNRISE-1 was a 1-month, double-blind, placebo- and active-controlled, parallel-group study in 1,006 subjects. Participants were females aged 55 years and older and males aged 65 years and older with a primary complaint of sleep maintenance difficulties and an Insomnia Severity Index (ISI) total score of 13 or higher. SUNRISE-2 was a placebo-controlled, 6-month, active treatment, double-blind, parallel-group study in 949 subjects with insomnia disorder. Participants were females and males aged 18 years and older with a primary complaint of sleep onset and/or sleep maintenance difficulties and an ISI total score of 15 or higher. Both analyses included subjects randomized to placebo, lemborexant 5 mg, or lemborexant 10 mg. Each study included a single-blind placebo run-in period prior to randomization.
The pooled analysis of 1,693 subjects included 402 (23.7%) men and 1,291 (76.3%) women. Results on sSOL and sWASO were consistent with the significant results on sleep diary in the individual studies. In both sexes, sSOL for lemborexant 5 mg and lemborexant 10 mg was significantly reduced versus that for placebo during the first 7 days and end of month 1 (P less than .05 for all comparisons). In women, the researchers observed significantly greater reductions in sWASO placebo for both lemborexant doses versus that with placebo (first 7 days and end of month 1; P less than .0001 for all comparisons). In males, sWASO decreased significantly, compared with placebo, for the first 7 days (lemborexant 5 mg and lemborexant 10 mg; P equal to or less than .0001) and at end of month 1 (lemborexant 10 mg only; P = .0032). For placebo, lemborexant 5 mg, and lemborexant 10 mg, the overall incidence of treatment-emergent adverse events was similar across sexes. Incidence of treatment-emergent serious adverse events was low for both sex subgroups; most events occurred in one subject each. Treatment-emergent adverse events leading to study drug withdrawal or interruption were few and similar across sexes for all treatments and was highest in males receiving lemborexant 10 mg. The most frequent treatment-emergent adverse events reported in males were somnolence, fatigue, and headache, while the most common in females were somnolence, headache, and urinary tract infection. About 3% of females (no males) reported a urinary tract infection; the incidence in females was similar across treatment groups.
“Overall, sleep diary outcomes in males and females were consistent with the significant results observed in the total populations of the individual studies,” Dr. Moline concluded. “A dose adjustment based on sex is not anticipated.”
The research was supported by Eisai. Dr. Moline is an employee of the company.
SOURCE: Moline M et al. Sleep 2019, Abstract 0368.
REPORTING FROM SLEEP 2019
Study IDs factors contributing to sleep clinic no-show rates
SAN ANTONIO – results from a single-center study showed.
“There are lots of people with sleep problems,” one of the study’s authors, Alvan Nzewuihe, MD, said in an interview at the annual meeting of the Associated Professional Sleep Societies. “However, we have to identify these patients to be able to help them. If they don’t come to the sleep clinic [for assessment], we are going nowhere.”
In an effort to better understand determinants of no-show rates among sleep clinics, Dr. Nzewuihe and colleagues performed a 10-month, retrospective chart review of 2,532 patients scheduled at Saint Louis University’s SLUCare Sleep Disorders Center during the months of July and October 2017 and April 2018. A no-show was determined if the patient failed to show up at their scheduled appointment on time or if they canceled their appointment. The researchers used multivariable logistic regression to determine which factors were independently associated with no-show rates.
Dr. Nzewuihe, a sleep medicine physician at the university, reported that the overall no-show rate during the study period was 21.2% and did not change with age, sex, or appointment factors such as time of day, day of week, or season of the year. Significant determinants of no-show rates included being a new patient (39.1% vs. 28.8% among established patients; P less than .0001) and having no health insurance (47.5% vs. public 28.3% vs private 24.2%; P less than .0001). Multivariate logistic regression confirmed the associations. New patients were 1.96 times more likely to not show up to the sleep clinic, compared with established patients, while patients with no health insurance coverage were 1.55 times more likely to not show up, compared with those with public health insurance.
The researchers wrote in their poster abstract, “Patients who are new to the clinic or have no insurance coverage have a higher odds of not showing up to their appointment and delaying their care. Efforts to prioritize high-risk patients of nonadherence will help contribute to better care and outcomes. Further studies are needed to develop methods to decrease no-show rates once high-risk appointments have been identified.”
Dr. Nzewuihe acknowledged certain limitations of the study, including its retrospective design and the fact that other possible contributing factors were not evaluated such as literacy level, employment status, and length of time between appointment booking and appointment date. The study’s first author was Julie Sahrmann, DO. The researchers reported having no financial disclosures.
SOURCE: Sahrmann J et al. Sleep 2019, Abstract 0965.
SAN ANTONIO – results from a single-center study showed.
“There are lots of people with sleep problems,” one of the study’s authors, Alvan Nzewuihe, MD, said in an interview at the annual meeting of the Associated Professional Sleep Societies. “However, we have to identify these patients to be able to help them. If they don’t come to the sleep clinic [for assessment], we are going nowhere.”
In an effort to better understand determinants of no-show rates among sleep clinics, Dr. Nzewuihe and colleagues performed a 10-month, retrospective chart review of 2,532 patients scheduled at Saint Louis University’s SLUCare Sleep Disorders Center during the months of July and October 2017 and April 2018. A no-show was determined if the patient failed to show up at their scheduled appointment on time or if they canceled their appointment. The researchers used multivariable logistic regression to determine which factors were independently associated with no-show rates.
Dr. Nzewuihe, a sleep medicine physician at the university, reported that the overall no-show rate during the study period was 21.2% and did not change with age, sex, or appointment factors such as time of day, day of week, or season of the year. Significant determinants of no-show rates included being a new patient (39.1% vs. 28.8% among established patients; P less than .0001) and having no health insurance (47.5% vs. public 28.3% vs private 24.2%; P less than .0001). Multivariate logistic regression confirmed the associations. New patients were 1.96 times more likely to not show up to the sleep clinic, compared with established patients, while patients with no health insurance coverage were 1.55 times more likely to not show up, compared with those with public health insurance.
The researchers wrote in their poster abstract, “Patients who are new to the clinic or have no insurance coverage have a higher odds of not showing up to their appointment and delaying their care. Efforts to prioritize high-risk patients of nonadherence will help contribute to better care and outcomes. Further studies are needed to develop methods to decrease no-show rates once high-risk appointments have been identified.”
Dr. Nzewuihe acknowledged certain limitations of the study, including its retrospective design and the fact that other possible contributing factors were not evaluated such as literacy level, employment status, and length of time between appointment booking and appointment date. The study’s first author was Julie Sahrmann, DO. The researchers reported having no financial disclosures.
SOURCE: Sahrmann J et al. Sleep 2019, Abstract 0965.
SAN ANTONIO – results from a single-center study showed.
“There are lots of people with sleep problems,” one of the study’s authors, Alvan Nzewuihe, MD, said in an interview at the annual meeting of the Associated Professional Sleep Societies. “However, we have to identify these patients to be able to help them. If they don’t come to the sleep clinic [for assessment], we are going nowhere.”
In an effort to better understand determinants of no-show rates among sleep clinics, Dr. Nzewuihe and colleagues performed a 10-month, retrospective chart review of 2,532 patients scheduled at Saint Louis University’s SLUCare Sleep Disorders Center during the months of July and October 2017 and April 2018. A no-show was determined if the patient failed to show up at their scheduled appointment on time or if they canceled their appointment. The researchers used multivariable logistic regression to determine which factors were independently associated with no-show rates.
Dr. Nzewuihe, a sleep medicine physician at the university, reported that the overall no-show rate during the study period was 21.2% and did not change with age, sex, or appointment factors such as time of day, day of week, or season of the year. Significant determinants of no-show rates included being a new patient (39.1% vs. 28.8% among established patients; P less than .0001) and having no health insurance (47.5% vs. public 28.3% vs private 24.2%; P less than .0001). Multivariate logistic regression confirmed the associations. New patients were 1.96 times more likely to not show up to the sleep clinic, compared with established patients, while patients with no health insurance coverage were 1.55 times more likely to not show up, compared with those with public health insurance.
The researchers wrote in their poster abstract, “Patients who are new to the clinic or have no insurance coverage have a higher odds of not showing up to their appointment and delaying their care. Efforts to prioritize high-risk patients of nonadherence will help contribute to better care and outcomes. Further studies are needed to develop methods to decrease no-show rates once high-risk appointments have been identified.”
Dr. Nzewuihe acknowledged certain limitations of the study, including its retrospective design and the fact that other possible contributing factors were not evaluated such as literacy level, employment status, and length of time between appointment booking and appointment date. The study’s first author was Julie Sahrmann, DO. The researchers reported having no financial disclosures.
SOURCE: Sahrmann J et al. Sleep 2019, Abstract 0965.
REPORTING FROM SLEEP 2019
Insomnia common among transgender college students
SAN ANTONIO – Compared with their cisgender counterparts, , results from a large national population-based survey showed.
“That was a stronger association than we expected,” one of the study’s researchers, Lisa B. Matlen, MD, said during an interview at the annual meeting of the Associated Professional Sleep Societies.
According to Dr. Matlen, a fellow in the division of sleep medicine at the University of Michigan, Ann Arbor, the transgender population is “extremely understudied” when it comes to research on sleep disturbances. In an effort to examine the prevalence of sleep disturbances and the association between transgender identity and sleep disturbances among transgender college students in the United States, she and her colleagues drew from the 2016 and 2017 American College Health Association National College Health Assessment II, a confidential, voluntary, electronically administered survey of college and university students. In all, 224,233 students were polled, and the researchers analyzed their responses to questions about gender identity, sleep symptoms, and diagnoses.
The mean age of the respondents was 23 years, and most (82%) were undergraduate students. Of the 224,233 students, 3,471 (1.6%) self-identified as transgender. More than half of the transgender population (61.9%) was white, 10.6% were Hispanic/Latino, 10.5% were Asian or Pacific Islander, 6.3% were biracial or multiracial, 4.6% were black, and the rest were from other ethnicities. Compared with cisgender students, transgender students had increased odds of sleep disturbances (odds ratio, 1.6), not feeling well rested on 4 or more days per week (OR, 1.8), going to bed early on 3 or more days per week due to sleepiness (OR, 1.3), and having insomnia 3 or more days per week (OR, 1.7). In addition, transgender students were nearly three times more likely to have an insomnia diagnosis and treatment, compared with their cisgender counterparts (OR, 2.9).
Dr. Matlen acknowledged certain limitations of the study, including the fact that it drew from a population-based sample and that the survey was based on self-reported information. The study’s first author was Ronald R. Gavidia Romero, MD. The researchers reported having no financial disclosures.
SAN ANTONIO – Compared with their cisgender counterparts, , results from a large national population-based survey showed.
“That was a stronger association than we expected,” one of the study’s researchers, Lisa B. Matlen, MD, said during an interview at the annual meeting of the Associated Professional Sleep Societies.
According to Dr. Matlen, a fellow in the division of sleep medicine at the University of Michigan, Ann Arbor, the transgender population is “extremely understudied” when it comes to research on sleep disturbances. In an effort to examine the prevalence of sleep disturbances and the association between transgender identity and sleep disturbances among transgender college students in the United States, she and her colleagues drew from the 2016 and 2017 American College Health Association National College Health Assessment II, a confidential, voluntary, electronically administered survey of college and university students. In all, 224,233 students were polled, and the researchers analyzed their responses to questions about gender identity, sleep symptoms, and diagnoses.
The mean age of the respondents was 23 years, and most (82%) were undergraduate students. Of the 224,233 students, 3,471 (1.6%) self-identified as transgender. More than half of the transgender population (61.9%) was white, 10.6% were Hispanic/Latino, 10.5% were Asian or Pacific Islander, 6.3% were biracial or multiracial, 4.6% were black, and the rest were from other ethnicities. Compared with cisgender students, transgender students had increased odds of sleep disturbances (odds ratio, 1.6), not feeling well rested on 4 or more days per week (OR, 1.8), going to bed early on 3 or more days per week due to sleepiness (OR, 1.3), and having insomnia 3 or more days per week (OR, 1.7). In addition, transgender students were nearly three times more likely to have an insomnia diagnosis and treatment, compared with their cisgender counterparts (OR, 2.9).
Dr. Matlen acknowledged certain limitations of the study, including the fact that it drew from a population-based sample and that the survey was based on self-reported information. The study’s first author was Ronald R. Gavidia Romero, MD. The researchers reported having no financial disclosures.
SAN ANTONIO – Compared with their cisgender counterparts, , results from a large national population-based survey showed.
“That was a stronger association than we expected,” one of the study’s researchers, Lisa B. Matlen, MD, said during an interview at the annual meeting of the Associated Professional Sleep Societies.
According to Dr. Matlen, a fellow in the division of sleep medicine at the University of Michigan, Ann Arbor, the transgender population is “extremely understudied” when it comes to research on sleep disturbances. In an effort to examine the prevalence of sleep disturbances and the association between transgender identity and sleep disturbances among transgender college students in the United States, she and her colleagues drew from the 2016 and 2017 American College Health Association National College Health Assessment II, a confidential, voluntary, electronically administered survey of college and university students. In all, 224,233 students were polled, and the researchers analyzed their responses to questions about gender identity, sleep symptoms, and diagnoses.
The mean age of the respondents was 23 years, and most (82%) were undergraduate students. Of the 224,233 students, 3,471 (1.6%) self-identified as transgender. More than half of the transgender population (61.9%) was white, 10.6% were Hispanic/Latino, 10.5% were Asian or Pacific Islander, 6.3% were biracial or multiracial, 4.6% were black, and the rest were from other ethnicities. Compared with cisgender students, transgender students had increased odds of sleep disturbances (odds ratio, 1.6), not feeling well rested on 4 or more days per week (OR, 1.8), going to bed early on 3 or more days per week due to sleepiness (OR, 1.3), and having insomnia 3 or more days per week (OR, 1.7). In addition, transgender students were nearly three times more likely to have an insomnia diagnosis and treatment, compared with their cisgender counterparts (OR, 2.9).
Dr. Matlen acknowledged certain limitations of the study, including the fact that it drew from a population-based sample and that the survey was based on self-reported information. The study’s first author was Ronald R. Gavidia Romero, MD. The researchers reported having no financial disclosures.
REPORTING FROM SLEEP 2019
Estimated prevalence of OSA in the Americas stands at 170 million
, results from a novel epidemiologic analysis showed.
“I would not have thought that there are 170 million people in the Americas with clinically important sleep apnea based on our conservative estimates,” the study’s first author, Atul Malhotra, MD, said in an interview in advance of the annual meeting of the Associated Professional Sleep Societies. “Even if we restrict the conversation to moderate to severe sleep apnea, we still see 81 million people afflicted in the Americas alone. We have recently estimated almost 1 billion patients afflicted with OSA worldwide.”
In an effort to estimate the Americas’ prevalence of adult OSA using existing data from epidemiologic studies, Dr. Malhotra, director of sleep medicine at the University of California, San Diego, senior author Adam V. Benjafield, PhD, and their colleagues contacted authors of important analyses on the topic following an exhaustive review of the literature. For countries where no measurement had been made, they used publicly available data to obtain estimates of age, sex, race, and body mass index. Next, they developed an algorithm to match countries without prevalence estimates with countries from which OSA epidemiologic studies exist. “The situation was complicated given the variable age of the existing studies, the differences in technology used (e.g., nasal pressure vs. thermistor), the changing scoring criteria, and other sources of variability,” the researchers wrote in their abstract.
Dr. Malhotra reported on data from 38 of 40 countries in the Americas. Drawing from American Academy of Sleep Medicine 2012 criteria and using what they characterized as a “somewhat conservative” approach, the researchers estimated the prevalence of adult OSA in the Americas to be 170 million, or 37% of the population. In addition, they estimate that 81 million adults, or 18% of the population, suffer from moderate to severe OSA based on an apnea hypopnea index of 15 or more per hour. The countries with the greatest burden of OSA are the United States (54 million), Brazil (49 million), and Colombia (11 million).
“The findings will hopefully help to raise awareness about the disease but also encourage a strategic conversation regarding how best to address this large burden,” Dr. Malhotra said. “We are unaware of prior efforts to estimate OSA prevalence on a large scale.”
He acknowledged certain limitations of the study, including that the methods, equipment, definitions, and criteria used in existing studies in the medial literature varied widely. “We did our best to harmonize these methods across studies but obviously we can’t change the equipment that was used in previous studies,” he said. “Thus, we view our findings as an estimate requiring further efforts to corroborate.”
The research stemmed from an academic/industry partnership with ResMed, which provided a donation the UCSD Sleep Medicine Center. Dr. Malhotra reported having no financial disclosures. Dr. Benjafield is an employee of ResMed, a medical equipment company that specializes in sleep-related breathing devices.
SOURCE: Malhotra A et al. SLEEP 2019, Abstract 0477.
, results from a novel epidemiologic analysis showed.
“I would not have thought that there are 170 million people in the Americas with clinically important sleep apnea based on our conservative estimates,” the study’s first author, Atul Malhotra, MD, said in an interview in advance of the annual meeting of the Associated Professional Sleep Societies. “Even if we restrict the conversation to moderate to severe sleep apnea, we still see 81 million people afflicted in the Americas alone. We have recently estimated almost 1 billion patients afflicted with OSA worldwide.”
In an effort to estimate the Americas’ prevalence of adult OSA using existing data from epidemiologic studies, Dr. Malhotra, director of sleep medicine at the University of California, San Diego, senior author Adam V. Benjafield, PhD, and their colleagues contacted authors of important analyses on the topic following an exhaustive review of the literature. For countries where no measurement had been made, they used publicly available data to obtain estimates of age, sex, race, and body mass index. Next, they developed an algorithm to match countries without prevalence estimates with countries from which OSA epidemiologic studies exist. “The situation was complicated given the variable age of the existing studies, the differences in technology used (e.g., nasal pressure vs. thermistor), the changing scoring criteria, and other sources of variability,” the researchers wrote in their abstract.
Dr. Malhotra reported on data from 38 of 40 countries in the Americas. Drawing from American Academy of Sleep Medicine 2012 criteria and using what they characterized as a “somewhat conservative” approach, the researchers estimated the prevalence of adult OSA in the Americas to be 170 million, or 37% of the population. In addition, they estimate that 81 million adults, or 18% of the population, suffer from moderate to severe OSA based on an apnea hypopnea index of 15 or more per hour. The countries with the greatest burden of OSA are the United States (54 million), Brazil (49 million), and Colombia (11 million).
“The findings will hopefully help to raise awareness about the disease but also encourage a strategic conversation regarding how best to address this large burden,” Dr. Malhotra said. “We are unaware of prior efforts to estimate OSA prevalence on a large scale.”
He acknowledged certain limitations of the study, including that the methods, equipment, definitions, and criteria used in existing studies in the medial literature varied widely. “We did our best to harmonize these methods across studies but obviously we can’t change the equipment that was used in previous studies,” he said. “Thus, we view our findings as an estimate requiring further efforts to corroborate.”
The research stemmed from an academic/industry partnership with ResMed, which provided a donation the UCSD Sleep Medicine Center. Dr. Malhotra reported having no financial disclosures. Dr. Benjafield is an employee of ResMed, a medical equipment company that specializes in sleep-related breathing devices.
SOURCE: Malhotra A et al. SLEEP 2019, Abstract 0477.
, results from a novel epidemiologic analysis showed.
“I would not have thought that there are 170 million people in the Americas with clinically important sleep apnea based on our conservative estimates,” the study’s first author, Atul Malhotra, MD, said in an interview in advance of the annual meeting of the Associated Professional Sleep Societies. “Even if we restrict the conversation to moderate to severe sleep apnea, we still see 81 million people afflicted in the Americas alone. We have recently estimated almost 1 billion patients afflicted with OSA worldwide.”
In an effort to estimate the Americas’ prevalence of adult OSA using existing data from epidemiologic studies, Dr. Malhotra, director of sleep medicine at the University of California, San Diego, senior author Adam V. Benjafield, PhD, and their colleagues contacted authors of important analyses on the topic following an exhaustive review of the literature. For countries where no measurement had been made, they used publicly available data to obtain estimates of age, sex, race, and body mass index. Next, they developed an algorithm to match countries without prevalence estimates with countries from which OSA epidemiologic studies exist. “The situation was complicated given the variable age of the existing studies, the differences in technology used (e.g., nasal pressure vs. thermistor), the changing scoring criteria, and other sources of variability,” the researchers wrote in their abstract.
Dr. Malhotra reported on data from 38 of 40 countries in the Americas. Drawing from American Academy of Sleep Medicine 2012 criteria and using what they characterized as a “somewhat conservative” approach, the researchers estimated the prevalence of adult OSA in the Americas to be 170 million, or 37% of the population. In addition, they estimate that 81 million adults, or 18% of the population, suffer from moderate to severe OSA based on an apnea hypopnea index of 15 or more per hour. The countries with the greatest burden of OSA are the United States (54 million), Brazil (49 million), and Colombia (11 million).
“The findings will hopefully help to raise awareness about the disease but also encourage a strategic conversation regarding how best to address this large burden,” Dr. Malhotra said. “We are unaware of prior efforts to estimate OSA prevalence on a large scale.”
He acknowledged certain limitations of the study, including that the methods, equipment, definitions, and criteria used in existing studies in the medial literature varied widely. “We did our best to harmonize these methods across studies but obviously we can’t change the equipment that was used in previous studies,” he said. “Thus, we view our findings as an estimate requiring further efforts to corroborate.”
The research stemmed from an academic/industry partnership with ResMed, which provided a donation the UCSD Sleep Medicine Center. Dr. Malhotra reported having no financial disclosures. Dr. Benjafield is an employee of ResMed, a medical equipment company that specializes in sleep-related breathing devices.
SOURCE: Malhotra A et al. SLEEP 2019, Abstract 0477.
REPORTING FROM SLEEP 2019
Key clinical point: The large burden of OSA in the Americas has not been widely appreciated.
Major finding: The estimated prevalence of adult OSA in the Americas is 170 million, or 37% of the population.
Study details: An analysis of epidemiologic studies that included data on 38 countries in the Americas.
Disclosures: The research stemmed from an academic/industry partnership with ResMed, a medical equipment company that specializes in sleep-related breathing devices, which provided a donation the UCSD Sleep Medicine Center. Dr. Malhotra reported having no financial disclosures. Dr. Benjafield is an employee of ResMed.
Source: Malhotra A et al. SLEEP 2019, Abstract 0477.