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Study Objectives Shift work is a risk factor for cardiometabolic disease, possibly through effects on sleep–wake rhythms. We hypothesized that evening (afternoon and night combined) and irregular (irregular/on-call or rotating combined) shift work during pregnancy is associated with increased odds of preeclampsia, preterm birth, and gestational diabetes mellitus (GDM), mediated by irregular sleep timing. Methods The Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be (nuMoM2b) is a prospective cohort study (n = 10 038) designed to investigate risk factors for adverse pregnancy outcomes. Medical outcomes were determined with medical record abstraction and/or questionnaires; sleep midpoint was measured in a subset of participants with ≥5-day wrist actigraphy (ActiWatch). We estimated the association of evening and irregular shift work during pregnancy with preeclampsia, preterm birth, and GDM using logistic regression, adjusted for adversity (cumulative variable for poverty, education, health insurance, and partner status), smoking, self-reported race/ethnicity, and age. Finally, we explored whether the association between shiftwork and GDM was mediated by variability in sleep timing. Results Evening shift work is associated with approximately 75% increased odds of developing GDM (adjusted OR = 1.75, 95% CI: 1.12–2.66); we did not observe associations with irregular shifts, preterm birth, or preeclampsia after adjustment. Pregnant evening shift workers were found to have approximately 45 minutes greater variability in sleep timing compared to day workers (p Conclusions Evening shift work was associated with GDM, and this relationship may be mediated by variability in sleep timing.

STUDY OBJECTIVES The goal of this study was to examine different paradigms for determining critical closing pressures (Pcrit). Methods of determining Pcrit were compared, including direct observation of occluded (no flow) breaths versus inferring Pcrit from extrapolated data, and Pcrit generated by aggregating pressure-flow data from multiple runs versus Pcrit averaged across individual pressure-flow runs. The relationship between Pcrit and obstructive sleep apnea (OSA) was examined. METHODS A total of 351 participants with and without OSA underwent overnight polysomnography with pressure-flow measurements to determine Pcrit. A series of filters were applied to raw data to provide consistent, objective criteria for determining which data to include in Pcrit calculations. Observed Pcrit values were computed as the mean nasal pressure level at which a subject had at least two breaths with peak inspiratory flow < 50 mL/sec. Extrapolated Pcrit was calculated in two ways: (1) separately for each individual run and then averaged; and (2) using all valid data from individual runs combined into one plot. RESULTS Observed Pcrit was calculated in 67% to 69% of participants, a similar or higher proportion of study subjects compared to extrapolated Pcrit values using a ± 3 cm H2O filter. Although raw (unfiltered) extrapolated Pcrit measures were able to be calculated among a greater proportion of participants than filtered, extrapolated Pcrit values, and thus had fewer missing values, they had larger variability. Both extrapolated and observed Pcrit were higher among individuals with OSA compared to those without OSA. CONCLUSIONS Observed Pcrit provides a reliable descriptor of hypotonic upper airway collapsibility. Different methods for determining Pcrit were able to distinguish subjects with and without OSA.

Introduction While studies have established that SDB during pregnancy increases the risk of adverse maternal outcomes, fetal effects are less well studied. Evidence suggests that fetal heart rate decelerations, an indicator of fetal distress, may be elicited by SDB. We examined the relationship between maternal SDB events and fetal heart rate (FHR) and fetal heart rate variability (FHRV). Methods Obese (BMI≥30kg/m2) non-smoking women carrying singleton fetuses underwent overnight polysomnography (34-37 weeks gestational age), with simultaneous fetal heart rate monitoring. Standard methods were used to score sleep, SDB events (apneas/hypopneas) and to analyze fetal heart rate parameters. Using linear mixed effect models, we examined changes in mean FHR and FHR variability (expressed by FHR SD) between the 10-second period immediately before individual SDB events, during events to the end of the associated oxygen desaturation period, and the 10-second period immediately following the SDB event. Results Valid PSG and FHR data were obtained from 85 third trimester maternal-fetal dyads. Across all participants, there were 2779 maternal SDB events (apneas or hypopneas). Mean AHI for individual subjects was 9.04 (SD 13.75). 39 women had OSA (AHI≥5), which was mostly mild. Mean FHR did not change significantly during and after episodes of SDB episodes compared to pre-event FHR, and did not change afterwards compared to during events, in unadjusted or adjusted (sleep stage, apnea type, degree of desaturation, age) analyses. In unadjusted analyses, FHRV significantly increased during SDB episodes compared to pre-SDB FHRV. After SDB events, FHRV was significantly lower than during SDB events. In fully adjusted models, these findings remained highly significant. FHRV was not significantly different after SDB events compared to pre-SDB event FHRV in unadjusted or adjusted models. Conclusion We observed consistent changes in FHR variability during and after maternal SDB events. Mean FHRV significantly increased during maternal SDB episodes compared to baseline FHRV, and decreased after SDB episodes. In contrast, mean FHR did not change significantly before, during and after SDB episodes. These data demonstrate that the fetus reacts to maternal SDB events, and raise questions about persistent effects of maternal SDB on the developing fetus. Support NIH HD079411

Study objectives Manual scoring of polysomnograms is a time-consuming and tedious process. To expedite the scoring of polysomnograms, several computerized algorithms for automated scoring have been developed. The overarching goal of this study was to determine the validity of the Somnolyzer system, an automated system for scoring polysomnograms. Design The analysis sample comprised of 97 sleep studies. Each polysomnogram was manually scored by certified technologists from four sleep laboratories and concurrently subjected to automated scoring by the Somnolyzer system. Agreement between manual and automated scoring was examined. Sleep staging and scoring of disordered breathing events was conducted using the 2007 American Academy of Sleep Medicine criteria. Setting Clinical sleep laboratories. Measurements and results A high degree of agreement was noted between manual and automated scoring of the apnea-hypopnea index (AHI). The average correlation between the manually scored AHI across the four clinical sites was 0.92 (95% confidence interval: 0.90-0.93). Similarly, the average correlation between the manual and Somnolyzer-scored AHI values was 0.93 (95% confidence interval: 0.91-0.96). Thus, interscorer correlation between the manually scored results was no different than that derived from manual and automated scoring. Substantial concordance in the arousal index, total sleep time, and sleep efficiency between manual and automated scoring was also observed. In contrast, differences were noted between manually and automated scored percentages of sleep stages N1, N2, and N3. Conclusion Automated analysis of polysomnograms using the Somnolyzer system provides results that are comparable to manual scoring for commonly used metrics in sleep medicine. Although differences exist between manual versus automated scoring for specific sleep stages, the level of agreement between manual and automated scoring is not significantly different than that between any two human scorers. In light of the burden associated with manual scoring, automated scoring platforms provide a viable complement of tools in the diagnostic armamentarium of sleep medicine.

Study objectives Distinct clinical phenotypes of obstructive sleep apnea (OSA) have been identified: Disturbed Sleep, Minimally Symptomatic, and Sleepy. Determining whether these phenotypes respond differently to standard treatment helps us to create a foundation for personalized therapies. We compared responses to positive airway pressure (PAP) therapy in these clinical OSA phenotypes. Methods The study sample included 706 patients from the Icelandic Sleep Apnea Cohort with moderate-to-severe OSA who were prescribed PAP. Linear and logistic mixed models were used to compare 2-year changes in demographics, comorbid diseases, and sleep-related health issues within and across OSA clinical phenotypes. Relationships between changes in symptoms and PAP adherence were also examined. Results Overall, effect sizes were moderate to large when comparing sleepiness, insomnia-related, and apneic symptom changes in the Sleepy group with changes in other two groups, especially those in the Minimally Symptomatic group. Within the Disturbed Sleep group, PAP users and nonusers demonstrated similar changes in insomnia-related symptoms. The Minimally Symptomatic group remained relatively asymptomatic, but reported significant decreases in daytime sleepiness and physical fatigue; PAP users generally had larger improvements. The Sleepy group had reductions in nearly all measured symptoms, including large reductions in drowsy driving; almost all of these improvements were greater among PAP users than nonusers. Conclusions OSA treatment response patterns differed by initial clinical phenotype and PAP adherence. Individuals with insomnia-related symptoms may require additional targeted therapy for these complaints. These findings underscore the need for a personalized approach to management that recognizes patients with a range of OSA presentations.

Although incident snoring is common in pregnant women and has been proposed as a potential risk factor for adverse maternal-fetal outcomes, the development of sleep-disordered breathing during pregnancy has not been prospectively described.Using the Apnea Symptom Score from the Multivariable Apnea Prediction Index and the Epworth Sleepiness Scale, we prospectively assessed symptoms of sleep-disordered breathing and daytime somnolence in 155 women to determine whether symptoms increased during pregnancy and the characteristics associated with increasing symptoms.We found that sleep-disordered breathing symptoms (Apnea Symptom Score, 0.44 (SEM 0.58) vs 0.95 (0.09, P.001) and the degree of daytime somnolence (Epworth Sleepiness Scale, 8.6 (0.3) vs 10.2 (0.4), P = .0003) increased significantly during pregnancy. Women with higher baseline body mass indexes and greater increases in neck circumference during pregnancy reported higher apnea symptom scores. Of the 155 subjects, 11.4% reported an increase in Apnea Symptom Score of 2 units or more, consistent with a clinically significant increase in symptoms; these women experienced a significantly greater increase in subjective sleepiness than other subjects (P = .03). Excessive daytime somnolence (Epworth Sleepiness Scale10) was prevalent throughout pregnancy (31.0%-45.5%).Our data demonstrate that symptoms of sleep-disordered breathing increase during pregnancy and that more than 10% of our subjects may be at risk for developing sleep apnea during pregnancy. Excessive daytime somnolence was highly prevalent even early in pregnancy and became increasingly common as pregnancy progressed.

This paper reviews the topic of sleep disorders in pregnant women. We describe changes in sleep architecture and sleep pattern during pregnancy, discuss the impact of the physical and biochemical changes of pregnancy on sleep in pregnant women and examine whether maternal-fetal outcomes may be adversely affected in women with disordered sleep. The literature on common sleep disorders affecting pregnant women, including insomnia, sleep-disordered breathing and restless legs syndrome, is reviewed and recommendations are made for the management of these disorders during pregnancy.

IN THIS ISSUE OF SLEEP, THERE ARE TWO PROSPECTIVE STUDIES SHOWING THAT UNTREATED MODERATE-TO-SEVERE SLEEP APNEA IS ASSOCIATED WITH increased mortality even after controlling for relevant covariates. These studies are based on general population cohorts rather than clinical samples. The first report by Marshall and colleagues is from the Busselton study in Australia1 that was first established by Dr. Helen Bearpark, who was tragically killed in a road accident. The second report by Young and colleagues is from the highly productive Wisconsin Sleep Cohort.2 Both studies show increased all-cause mortality. The Australian study shows a hazard ratio of the order of 4.4–6.2 for moderate-to-severe sleep apnea (RDI ≥ 15 episodes/hour) after controlling for different covariates.1 The Wisconsin study shows no significant increase in all-cause mortality in individuals with an AHI between 15 and 30 episodes/hour but a hazard ratio of the order of 2.7 to 3.8 for severe OSA (AHI ≥ 30 episodes/hour), depending on which subjects and confounding variables were included in their analyses.2 While not addressed in the Busselton study, the Wisconsin study specifically looked at cardiovascular mortality. Elevated mortality from cardiovascular deaths was observed. This association was significant in the subgroup of subjects with severe sleep apnea who were untreated (i.e., excluding the small number of subjects on CPAP). This association is not surprising, since previous cohort studies3 have shown an increased incidence of coronary artery disease in untreated patients with severe OSA. Both groups argue that population studies have the advantage over studies in clinical samples since they avoid referral bias. Population studies do, however, have the disadvantage of having small numbers of individuals with moderate-to-severe disease. In the Busselton study,1 18 of the 380 subjects assessed had an RDI ≥ 15 episodes/hour while only 3 had an RDI ≥ 30 events/hour. In the larger study from Wisconsin,2 145 of the 1522 subjects had an AHI ≥ 15 episodes/hour and 63 with severe OSA (AHI ≥ 30 episodes/hour). (Since the two studies used different strategies to assess sleep disordered breathing, the metrics of sleep disordered breathing cannot be directly compared.) These relatively low numbers of individuals with disease potentially limit the power of the data analyses to detect true associations. Epidemiological studies demonstrating association always have the challenge of proving that the association is not produced by confounding. While both studies in this issue of SLEEP have addressed confounding, a particular concern is obesity which is highly associated with the presence and severity of OSA. Some have suggested that OSA modifies the effect of obesity as a cardiovascular risk factor.4 It is not simply obesity that needs to be considered but rather the degree of visceral obesity, which is more clearly associated with the metabolic syndrome.5 Visceral fat volume contributes to variation in metabolic risk factors for cardiovascular disease even after controlling for BMI and waist circumference.5 Thus, despite efforts to control for obesity as a covariate, there is the lingering concern that there could be differences in the degree of visceral obesity between those with OSA who died and those who did not. The results of these community studies are congruent with earlier studies6–8 and recent studies in large clinical cohorts.9–11 By design, studies in clinical samples have much larger numbers of untreated patients with severe disease. Studies in clinical samples also show that untreated OSA is associated with an increased rate of cardiac events and cardiovascular mortality. Indeed, the estimate of the increased risk of death of 2–4 is of similar magnitude to that reported in these new community-based studies. Thus, the new information presented in these two manuscripts in this issue of SLEEP, when combined with studies in clinical samples, leads to the highly likely conclusion that untreated severe OSA is an important risk factor for cardiovascular mortality. There are caveats that make the conclusions less than foolproof. There is the issue of residual confounding as discussed above. In the clinical cohorts, when death rates in individuals on CPAP treatment are compared to those not using CPAP,10 there is the issue of whether this is specific to OSA or whether non-use of CPAP is a marker for generally non-adherent behavior. The studies also lead to the conclusion that mild OSA (AHI from 5 to 15 episodes/hour) is not associated with increased mortality.1,2 The conclusion about the lack of mortality risk from untreated moderate OSA is less clear.1,2 An important issue is whether treatment of severe OSA with CPAP reduces mortality rates. Studies in clinical cohorts indicate it does8,10 and suggest that cardiovascular event rates and death rates in patients with severe OSA on CPAP treatment are not different than controls or snorers without OSA and with similar degrees of obesity.10 The Wisconsin study adds support to the effect of treatment by demonstrating that exclusion from the analysis of the surprisingly few individuals with OSA who were treated with CPAP (n = 126) increased the hazard ratio for all-cause and cardiovascular mortality.2 It is important to address both the implications of these findings for clinical practice and for a future research agenda. From the clinical perspective, given that we have a safe and effective therapy for OSA (i.e., nasal CPAP12), all patients with severe OSA should be treated regardless of whether they are symptomatic with excessive sleepiness. One accepts that the data are not perfect but the risk-benefit clearly favors treatment. The data indicate, however, that this is not so for mild disease in the absence of sleepiness (AHI ≥ 5 < 15 episodes/hour). For moderate disease, patients with excessive sleepiness should be treated. There is a need for further studies to determine whether patients with moderate OSA have an elevated risk for cardiovascular events and death. Ultimately, from a research perspective, we would need a large randomized trial to show that active treatment of OSA with CPAP reduces cardiovascular event rates and deaths. Our cardiology colleagues are accustomed to evaluating this type of evidence and may not be fully convinced without it. Such a trial will not require use of sham CPAP, since the endpoints are definitive and not affected by blinding. Such a trial is, however, ethically challenging since OSA patients are frequently excessively sleepy and at risk for crashes.13 Sleepy patients cannot be randomized to no treatment for many years. There are, however, patients even with severe OSA who are not excessively sleepy. While some have argued that patients without sleepiness may also be “protected” from the cardiovascular risk,14 the data from the Wisconsin study do not support this assertion. Rather, Young and colleagues2 found that the relationship of OSA to mortality is independent of self-reported sleepiness and present even in individuals without excessive sleepiness. Thus, it is conceivable that a randomized trial focusing on patients with severe OSA with minimal or absent sleepiness is feasible. In conclusion, these new prospective studies are important and add to the growing evidence base as to OSA being a risk factor for death. Given the epidemic of obesity with its cardiovascular consequences, we need to pursue identification and treatment of individuals with severe OSA and, as a field, move to more definitive randomized trials.

To determine associations between menopausal status, reproductive hormone levels, menopausal symptoms, and poor sleep quality.The present study examines subjective sleep quality over an 8-year period in participants in an ongoing longitudinal study of ovarian aging in a randomly identified cohort of African American and Caucasian women.The Penn Ovarian Aging Study, a population-based cohort of 436 women from Philadelphia County who were 35 to 47 years of age and had regular menstrual cycles at enrollment.N/A.The primary outcome measure was the Sleep Quality factor score, derived from the St. Mary's Hospital Sleep Questionnaire, which was adapted for this population and collected at each assessment period over the 8-year follow-up. Associations between menopausal status, reproductive hormone levels, menopausal symptoms, sleep quality, age, and race were examined in multivariable linear mixed regression models for repeated measures. Menopausal status was not significantly associated with sleep quality (P = 0.12). In the adjusted model, independent predictors of sleep quality were hot flashes (P0.0001), Center for Epidemiological Studies Depression Scale scores (P0.0001) and levels of the reproductive hormone inhibin B (P = 0.05).Sleep quality was predicted by hormone levels and symptoms that occur in the menopausal transition but did not worsen with advancing menopausal status alone. Lower inhibin B levels, hot flashes, and symptoms of depression were all strong and independent predictors of difficulty sleeping. Race was not a significant contributor to sleep quality. Together, the findings demonstrate that women who experience other perimenopausal symptoms are likely to experience sleep problems during the menopausal transition.

PROBLEMS WITH SLEEP ARE WIDELY REPORTED AMONG MIDDLE-AGED WOMEN AND HAVE COMMONLY BEEN ATTRIBUTED TO THE MENOPAUSAL transition or cited as a symptom of menopause.1–7 In several large, cross-sectional, community-based surveys, higher rates of self-reported difficulty sleeping have been observed among perimenopausal and postmenopausal women compared with premenopausal women.2,4,6–8 For instance, in a survey of nearly 1500 Scottish women aged 45 to 54, the prevalence of sleep problems among perimenopausal and postmenopausal women was 40% and 35% respectively, compared to 22% among premenopausal women.6 Data from the multiethnic, community-based sample comprising the Study of Women's Health Across the Nation (SWAN) have also demonstrated significantly higher rates of sleep difficulty among perimenopausal and postmenopausal women, compared with premenopausal women2; in this study, vasomotor symptoms were a strong and consistent predictor of trouble sleeping. Nevertheless, whether difficulty sleeping increases among women in the late reproductive years and occurs due to symptoms of the menopausal transition, particularly hot flashes and night sweats, or whether the aging process itself causes an increase in sleep problems that is incorrectly attributed to menopause is not well understood. In addition, given the integral relationship between reproductive hormones and menopausal status, the impact on sleep of hormones such as estradiol, which is secreted by the ovary to support developing follicles and any subsequent pregnancy, and inhibin B, which is a hormone produced by ovarian granulosa cells and falling levels of which precede the menopausal decline in estradiol levels and are a marker of the early menopausal transition,9 is also of interest. However, how reproductive hormone levels affect sleep quality has not been extensively examined. The present study examines subjective sleep quality over an 8-year period in the Penn Ovarian Aging Study, an ongoing longitudinal study of ovarian aging in a population-based cohort. The aim of our study was to determine associations among menopausal status, reproductive hormone levels, menopausal symptoms, and sleep quality. Based on our earlier study in this cohort,10 we hypothesized that women would experience worsened sleep quality during the menopausal transition, compared with the premenopausal and postmenopausal states, and that lower levels of reproductive hormones such as estradiol and inhibin B, which decrease with ovarian aging, would be associated with poorer sleep quality during the transition to menopause.