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Growing evidence indicates sleep is a major public health issue. Race/ethnicity and socioeconomics may contribute to sleep problems. This study assessed whether sleep symptoms were more prevalent among minorities and/or the socioeconomically disadvantaged.Cross-sectional.Epidemiologic survey.2007-2008 National Health and Nutrition Examination Survey (N = 4,081).None.Sociodemographics included age, sex, race/ethnicity, marital status, and immigration. Socioeconomics included poverty, education, private insurance, and food insecurity. Sleep symptoms assessed were sleep latency30 min, difficulty falling asleep, sleep maintenance difficulties, early morning awakenings, non-restorative sleep, daytime sleepiness, snorting/gasping, and snoring. Decreased reported problems for most symptoms were found among minorities, immigrants, and lower education levels. In general, in fully adjusted models, long sleep latency was associated with female gender, being black/African American, lower education attainment, no private insurance, and food insecurity. Difficulty falling asleep, sleep maintenance difficulties, early morning awakenings, and non-restorative sleep were also associated with female gender and food insecurity. Daytime sleepiness was seen in female and divorced respondents. Snorting/gasping was more prevalent among male, other-Hispanic/Latino, and 9(th)- to 11(th)-grade-level respondents. Snoring was prevalent among male, other-Hispanic/Latino, less-educated, and food-insecure respondents.Sleep symptoms were associated with multiple sociodemographic and economic factors, though these relationships differed by predictor and sleep outcome. Also, reports depended on question wording.

OBJECTIVE To evaluate joint task force criteria-based screening for severe obstructive sleep apnea (s-OSA) in commercial drivers. METHODS Among a community-based cohort of licensed commercial vehicle drivers, we assessed utility of the joint task force criteria. We conducted full, 14-channel overnight polysomnography in all drivers, defining s-OSA as an apnea-hypopnea index of 30 or more per hour. RESULTS One hundred of 104 drivers with successful polysomnography studies were predominantly obese (median body mass index = 32.8 kg/m; interquartile range = 26.8 to 37.4) and had a median apnea-hypopnea index of 20.6 per hour (interquartile range = 10.0 to 34.2). Examination-based criteria were more effective (sensitivity = 80%; negative posttest probability [nPTP] = 17%) than symptom-based criteria (sensitivity = 63%; nPTP = 23%). Examination and symptom-based criteria combined had high sensitivity (97%) and low nPTP (7%), but poor specificity (19%). CONCLUSIONS Examination-based criteria missed 20% of s-OSA cases. Combining examination with confidentially reported symptoms improved sensitivity but required confirmatory polysomnography in 86%, supporting universal screening of all drivers.

Background Warfarin is the primary therapy to prevent stroke and venous thromboembolism. Significant periods of nonadherence frequently go unreported by patients and undetected by providers. Currently, no comprehensive screening tool exists to help providers assess the risk of nonadherence at the time of initiation of warfarin therapy. Methods This article reports on a prospective cohort study of adults initiating warfarin therapy at two anticoagulation clinics (university- and Veterans Affairs-affiliated). Nonadherence, defined by failure to record a correct daily pill bottle opening, was measured daily by electronic pill cap monitoring. A multivariable logistic regression model was used to develop a point system to predict daily nonadherence to warfarin. Results We followed 114 subjects for a median of 141 days. Median nonadherence of the participants was 14.4% (interquartile range [IQR], 5.8-33.8). A point system, based on nine demographic, clinical, and psychosocial factors, distinguished those demonstrating low vs high levels of nonadherence: four points or fewer, median nonadherence 5.8% (IQR, 2.3-14.1); five points, 9.1% (IQR, 5.9-28.6); six points, 14.5% (IQR, 7.1-24.1); seven points, 14.7% (IQR, 7.0-34.7); and eight points or more, 29.3% (IQR, 15.5-41.9). The model produces a c-statistic of 0.66 (95% CI, 0.61-0.71), suggesting modest discriminating ability to predict day-level warfarin nonadherence. Conclusions Poor adherence to warfarin is common. A screening tool based on nine demographic, clinical, and psychosocial factors, if further validated in other patient populations, may help to identify groups of patients at lower risk for nonadherence so that intensified efforts at increased monitoring and intervention can be focused on higher-risk patients.

Background Evidence that continuous positive airway pressure (CPAP) reduces cardiovascular morbidity comes largely from observational studies. This association may be confounded if CPAP adherents are healthier in ways not measured by investigators. We assessed whether patients adhering to lipid-lowering medications were more adherent to CPAP. Methods This was a retrospective cohort study undertaken at the Philadelphia Veterans Affairs (VA) Medical Center (2005–2006) of consecutive patients on lipid-lowering therapy newly initiating CPAP for obstructive sleep apnea. Adherence to medications dispensed via the VA closed-pharmacy system was measured as the proportion of days covered (≥80% vs Results Complete data were available for 117 of 142 (81.5%) subjects. After adjustment for age, race, medical comorbidity, and sleep apnea-related clinical factors, subjects with low medication adherence demonstrated a 40.1% (95% CI, 30.0–51.0) probability of using CPAP ≥ 4 h/d compared with 55.2% (95% CI, 46.9–63.1) for subjects with adequate (≥80%) medication adherence (adjusted for comparison, odds ratio (OR) = 1.8 [95% CI, 1.0–3.3], P = .04). Married patients were more adherent to medications and CPAP; inclusion of this factor reduced to nonsignificance the association of medication and CPAP adherence (OR = 1.6 [95% CI, 0.9–2.8], P = .12). Conclusion Patients consistently refilling lipid-lowering medications were more adherent to CPAP, suggesting that differences in medication adherence or other health-promoting behaviors should be investigated in future nonrandomized, observational studies linking CPAP adherence and cardiovascular outcomes.

Adherence to continuous positive airway pressure (CPAP) therapy for obstructive sleep apnea is poor. Risk factors for nonadherence are not well understood but may reflect individual or neighborhood socioeconomic factors. We sought to determine the association of socioeconomic status and initial CPAP adherence.Retrospective cohort study, 2005 to 2006.Philadelphia VA Medical Center.Of 330 consecutive veterans who met study criteria for initiation of CPAP therapy for newly diagnosed sleep apnea, 266 had complete data for study inclusion.N/A.Through a multivariable logistic regression model, using an outcome of objectively measured CPAP use - 4 h daily during the first week of treatment, we tested whether patients from higher socioeconomic neighborhoods had higher CPAP adherence. We measured neighborhood socioeconomic status with an index derived from the 2000 U.S. Census at the block group-level composed of median household income, male and female employment, adult high school completion, married households, and minority composition.CPAP adherence4 h occurred on 48.9% of 1,805 patient-days observed for the 266 subjects. After adjustment for individual sociodemographic characteristics and medical comorbidity, the probability of daily CPAP use 4 h ranged from 34.1% (95% CI, 26.4-42.7) for subjects from a low socioeconomic neighborhood (5th percentile) to 62.3% (95% CI, 53.8-70.1) for subjects from a high (95th percentile) neighborhood.In a retrospective cohort of veterans, initial CPAP adherence was closely associated with higher neighborhood socioeconomic factors. Future investigation should target specific impediments to adherence in the home and neighborhood environment.

Background Warfarin is widely used to prevent stroke and venous thromboembolism despite its narrow therapeutic window. Warfarin nonadherence is a substantial problem, but risk factors have not been well elucidated. Methods A prospective cohort study of adults initiating warfarin at two anticoagulation clinics (University and VA-affiliated) was performed to determine factors affecting nonadherence to warfarin. Nonadherence, defined by failure to record a correct pill bottle opening each day, was measured daily via electronic medication event monitoring systems (MEMS) caps. A multivariable explanatory model using logistic regression for longitudinal data was used to identify risk factors for nonadherence. Results One hundred eleven subjects were followed for a median of 137 days. Warfarin nonadherence was common (4787 of 22 425 or 21% of patient-days observed). Factors independently associated with higher odds of nonadherence included education beyond high school (odds ratio (OR) 1.8 (95%CI 1.2–2.7)), lower Short Form (SF)-36 mental component score (OR 1.4 (1.1–1.6) for each 10 point decrease); and impaired cognition (≤19 points) on the Cognitive Capacity Screening Examination (CCSE) (OR 2.9 (1.7–4.8)). Compared to currently employed subjects, unemployed (OR 0.6 (0.3–1.2)) and retired (OR 0.5 (0.3–0.8)) subjects had somewhat improved adherence; disabled subjects over age 55 had worse adherence (OR 1.8 (1.1–3.1)) than younger disabled subjects (OR 0.8 (0.4–1.5)). Conclusions Poor adherence to warfarin is common and risk factors are related to education level, employment status, mental health functioning, and cognitive impairment. Within the carefully controlled anticoagulation clinic setting, such patient-specific factors may be the basis of future interventions to improve nonadherence. Copyright © 2008 John Wiley & Sons, Ltd.

Warfarin is the primary therapy to prevent stroke and venous thromboembolism. Significant periods of nonadherence frequently go unreported by patients and undetected by providers. Currently, no comprehensive screening tool exists to help providers assess the risk of nonadherence at the time of initiation of warfarin therapy.This article reports on a prospective cohort study of adults initiating warfarin therapy at two anticoagulation clinics (university- and Veterans Affairs-affiliated). Nonadherence, defined by failure to record a correct daily pill bottle opening, was measured daily by electronic pill cap monitoring. A multivariable logistic regression model was used to develop a point system to predict daily nonadherence to warfarin.We followed 114 subjects for a median of 141 days. Median nonadherence of the participants was 14.4% (interquartile range [IQR], 5.8-33.8). A point system, based on nine demographic, clinical, and psychosocial factors, distinguished those demonstrating low vs high levels of nonadherence: four points or fewer, median nonadherence 5.8% (IQR, 2.3-14.1); five points, 9.1% (IQR, 5.9-28.6); six points, 14.5% (IQR, 7.1-24.1); seven points, 14.7% (IQR, 7.0-34.7); and eight points or more, 29.3% (IQR, 15.5-41.9). The model produces a c-statistic of 0.66 (95% CI, 0.61-0.71), suggesting modest discriminating ability to predict day-level warfarin nonadherence.Poor adherence to warfarin is common. A screening tool based on nine demographic, clinical, and psychosocial factors, if further validated in other patient populations, may help to identify groups of patients at lower risk for nonadherence so that intensified efforts at increased monitoring and intervention can be focused on higher-risk patients.

Warfarin is an anticoagulant effective in preventing stroke, but it has a narrow therapeutic range requiring optimal adherence to achieve the most favorable effects.The goal of this study was to examine specific patient factors that might help explain warfarin non-adherence at outpatient anticoagulation clinics.In a prospective cohort study of 156 adults, we utilized logistic regression analyses to examine the relationship between the five Treatment Prognostics scales from the Millon Behavioral Medicine Diagnostic (MBMD), as well as three additional MBMD scales (Depression, Future Pessimism, and Social Isolation), and daily warfarin non-adherence assessed using electronic medication event monitoring systems caps over a median of 139 days.Four of the five Treatment Prognostic scales and greater social isolation were associated with warfarin non-adherence. When controlling for pertinent demographic and medical variables, the Information Discomfort scale remained significantly associated with warfarin non-adherence over time.Although several factors were related to warfarin non-adherence, patients reporting a lack of receptivity to details regarding their medical illness seemed most at risk for warfarin non-adherence. This information might aid in the development of interventions to enhance warfarin adherence and perhaps reduce adverse medical events.

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.

Warfarin is widely used to prevent stroke and venous thromboembolism despite its narrow therapeutic window. Warfarin nonadherence is a substantial problem, but risk factors have not been well elucidated.A prospective cohort study of adults initiating warfarin at two anticoagulation clinics (University and VA-affiliated) was performed to determine factors affecting nonadherence to warfarin. Nonadherence, defined by failure to record a correct pill bottle opening each day, was measured daily via electronic medication event monitoring systems (MEMS) caps. A multivariable explanatory model using logistic regression for longitudinal data was used to identify risk factors for nonadherence.One hundred eleven subjects were followed for a median of 137 days. Warfarin nonadherence was common (4787 of 22,425 or 21% of patient-days observed). Factors independently associated with higher odds of nonadherence included education beyond high school (odds ratio (OR) 1.8 (95%CI 1.2-2.7)), lower Short Form (SF)-36 mental component score (OR 1.4 (1.1-1.6) for each 10 point decrease); and impaired cognition (or =19 points) on the Cognitive Capacity Screening Examination (CCSE) (OR 2.9 (1.7-4.8)). Compared to currently employed subjects, unemployed (OR 0.6 (0.3-1.2)) and retired (OR 0.5 (0.3-0.8)) subjects had somewhat improved adherence; disabled subjects over age 55 had worse adherence (OR 1.8 (1.1-3.1)) than younger disabled subjects (OR 0.8 (0.4-1.5)).Poor adherence to warfarin is common and risk factors are related to education level, employment status, mental health functioning, and cognitive impairment. Within the carefully controlled anticoagulation clinic setting, such patient-specific factors may be the basis of future interventions to improve nonadherence.

THE ABILITY TO MEASURE OBJECTIVE ADHERENCE TO CONTINUOUS POSITIVE AIRWAY PRESSURE (CPAP) THERAPY OFFERS SLEEP PHYSICIANS AND BEHAVIORAL researchers a unique window into the daily activities of patients with obstructive sleep apnea (OSA). Commercially available CPAP machines monitor treatment efficacy by recording the time that the CPAP circuit is pressurized (i.e., mask-on time), as well as the amount of air leaking from the circuit and the presence or absence of snoring, apneas, and hypopneas. This information has proven invaluable in patient management. For example, the finding of a large air leak on the CPAP download may indicate the need to change the patient's mask interface. Downloads with an unacceptably high residual apnea-hypopnea index can alert the provider that the CPAP setting may need to be adjusted. Using this objective measure of CPAP adherence, Weaver and colleagues were the first to identify that, as early as the first week of therapy, patients segregate themselves into consistent daily users of CPAP or intermittent users who skip days and have low hours of use on days when they do adhere.1 The individual patterns of usage established within the first week of treatment persist for months or longer. The availability of such reliable, readily obtained data on patient behavior offers an opportunity to develop and evaluate early interventions to improve CPAP adherence before patterns of nonadherence become ingrained. These interventions may be based not only on technical problems relating to the mask interface, pressure setting, or effectiveness of treatment, but also on socioeconomic and psychological factors that may influence the patient's ability and willingness to adhere to CPAP on a daily basis.2–4 Now that physicians and researchers have a tool to track daily adherence to CPAP and identify patterns of nonadherence, an important question arises: are sleep apnea patients who adhere poorly to CPAP also nonadherent in other medical treatments? In other words, are patients who are nonadherent to CPAP also nonadherent to diet, exercise, and medications? The important article by Villar and her colleagues in this issue of the journal indicates that this may not be the case.5 Patients appear to be selective in choosing which medical interventions they will adhere to. In one of the first studies to compare patient adherence across different medical interventions, the authors compared medication adherence in patients with OSA who were CPAP adherent (> 4 hr/day) versus those who refused or discontinued CPAP therapy. Adherence to medications treating hypertension and hyperlipidemia and reducing platelet aggregation was determined based on medication refills over a two-year period that occurred some time after the patients had accepted or declined CPAP treatment. Villar and colleagues found that patients who declined or discontinued CPAP treatment had similar adherence to all three medication categories as patients who were CPAP adherent. This intriguing finding rebuts a vexing criticism raised against non-randomized longitudinal studies reporting that untreated OSA is an independent risk factor for incident cardiovascular morbidity and mortality. In 2005, the same group of Spanish investigators, taking advantage of the refusal of some patients with OSA to use CPAP, reported that patients with severe OSA who refused treatment had a greater risk of fatal and non-fatal cardiovascular events over a 10-year follow-up period compared to age- and weight-matched individuals without OSA, even after adjustment for baseline demographic and clinical factors.6 In contrast, the risks of fatal and non-fatal cardiovascular events in patients with OSA who had adequate CPAP adherence were similar to those in the control group. Other observational cohort studies have reported similar results.7–10 However, these nonrandomized studies may exaggerate the effectiveness of CPAP if the CPAP adherent patients were healthier than nonadherent patients in ways not typically measured in cohort studies. Patients who adhere to one treatment may be more likely to adhere to other interventions that are known to influence cardiovascular outcomes. Such a “healthy user” bias has been detected in studies of hormone replacement therapy11 and in landmark cardiovascular trials in which placebo-adherent subjects experienced lower mortality than placebo-nonadherent subjects.12–15 The observational studies linking OSA with increased cardiovascular risk did not assess whether participants with OSA who did not use CPAP may also have been nonadherent to other, potentially cardioprotective measures such as diet, exercise, and medications for hypertension, hyperlipidemia, and reduction of platelet aggregation. Therefore, differences in cardiovascular outcomes observed between CPAP users vs. non-users may actually have been due to a healthy user bias rather than CPAP treatment for OSA per se. The finding of Villar and her colleagues that medication adherence patterns are similar in CPAP users and non-users provides important new evidence that the results of their earlier observational study may not be attributed to a healthy user bias, at least as it relates to and can be measured by pharmacy prescription-refill records. Their current study, however, does not completely resolve the issue. One of the study's limitations is the collection of CPAP and medication adherence data over widely different time periods. A second limitation is the failure to track daily CPAP and medication adherence. It is possible that a more refined tracking of daily CPAP usage and daily pill taking for cardiovascular conditions may yet demonstrate some association between nonadherent behaviors in these separate domains of medical care. Moreover, other factors that may have influenced cardiovascular outcomes, such as diet and exercise, were not examined and may have differed between the two groups. Of note, behavior may differ across different patient populations. Therefore, it may not be possible to generalize results from one center. Additional studies addressing the above issues relative to CPAP use and healthy user bias are needed. Despite these limitations, the study of Villar and colleagues provides an excellent example of how behavioral measures controlling for potential confounding factors can be incorporated into and strengthen future observational studies. In light of the ethical challenge of conducting randomized controlled trials of CPAP therapy that would deny treatment to patients with moderate to severe OSA, well-conducted observational studies such as those from these Spanish investigators are providing mounting evidence of a causal relationship between OSA and cardiovascular outcomes.