Continuous positive airway pressure (CPAP) is a highly efficacious treatment for obstructive sleep apnea (OSA) but adherence to the treatment limits its overall effectiveness across all age groups of patients. Factors that influence adherence to CPAP include disease and patient characteristics, treatment titration procedures, technological device factors and side effects, and psychological and social factors. These influential factors have guided the development of interventions to promote CPAP adherence. Various intervention strategies have been described and include educational, technological, psychosocial, pharmacological, and multi-dimensional approaches. Though evidence to date has led to innovative strategies that address adherence in CPAP-treated children, adults, and older adults, significant opportunities exist to develop and test interventions that are clinically applicable, specific to subgroups of patients likely to demonstrate poor adherence, and address the multifactorial nature of CPAP adherence. The translation of CPAP adherence promotion interventions to clinical practice is imperative to improve health and functional outcomes in all persons with CPAP-treated OSA.

Objectives-Lower socioeconomic status is associated with short or long sleep duration and sleep disturbance (e.g., sleep apnea), which are all related to increased mortality risk. General sleep complaints, however, which may better approximate symptoms as they are experienced, have not been examined in a large population sample.Methods-Sample consisted of n=159,856 participants from the Behavioral Risk Factor Surveillance System, representing 36 states/regions across the US. Sleep complaints were measured with a telephone survey item that assessed "trouble falling asleep," "staying asleep" or "sleeping too much." Data analysis utilized hierarchical logistic regression and Rao-Schott chi-square.Results-Asian respondents reported the least complaints, and Hispanic/Latino and Black/AfricanAmerican individuals reported fewer complaints than Whites. Lower income and educational attainment was associated with more sleep complaints. Employment was associated with less sleep complaints and unemployment with more. Married individuals reported the least sleep complaints. Significant interactions with race/ethnicity indicate that the relationship between sleep complaints and marital status, income and employment differs among groups for men, and the relationship with education differs among groups for women.Conclusions-Rates of sleep complaints in African-American, Hispanic/Latino and Asian/Other groups were similar to Whites. Lower socioeconomic status was associated with higher rates of sleep complaint.

Sleep patterns change with aging, independent of other factors, and include advanced sleep timing, shortened nocturnal sleep duration, increased frequency of daytime naps, increased number of nocturnal awakenings and time spent awake during the night, and decreased slow wave sleep. Most of these changes seem to occur between young and middle adulthood; sleep parameters remain largely unchanged among healthy older adults. The circadian system and sleep homeostatic mechanisms become less robust with normal aging. The amount and pattern of sleep-related hormone secretion change as well. The causes of sleep disturbances in older adults are multifactorial.

BackgroundLittle is known about the social determinants of sleep attainment. This study examines the relationship of race/ethnicity, socio-economic status (SES) and other factors upon sleep quality.MethodsA cross-sectional survey of 9,714 randomly selected subjects was used to explore sleep quality obtained by self-report, in relation to socioeconomic factors including poverty, employment status, and education level. The primary outcome was poor sleep quality. Data were collected by the Philadelphia Health Management Corporation.ResultsSignificant differences were observed in the outcome for race/ethnicity (African-American and Latino versus White: unadjusted OR = 1.59, 95% CI 1.24-2.05 and OR = 1.65, 95% CI 1.37-1.98, respectively) and income (below poverty threshold, unadjusted OR = 2.84, 95%CI 2.41-3.35). In multivariable modeling, health indicators significantly influenced sleep quality most prominently in poor individuals. After adjusting for socioeconomic factors (education, employment) and health indicators, the association of income and poor sleep quality diminished, but still persisted in poor Whites while it was no longer significant in poor African-Americans (adjusted OR = 1.95, 95% CI 1.47-2.58 versus OR = 1.16, 95% CI 0.87-1.54, respectively). Post-college education (adjusted OR = 0.47, 95% CI 0.31-0.71) protected against poor sleep.ConclusionsA "sleep disparity" exists in the study population: poor sleep quality is strongly associated with poverty and race. Factors such as employment, education and health status, amongst others, significantly mediated this effect only in poor subjects, suggesting a differential vulnerability to these factors in poor relative to non-poor individuals in the context of sleep quality. Consideration of this could help optimize targeted interventions in certain groups and subsequently reduce the adverse societal effects of poor sleep.