Race and Socioeconomic Status: Interlinked Drivers of Sleep Health Disparities.

The effect of race and socioeconomic status on sleep disorders has significant effects on the availability of healthcare and health outcomes. This paper examines how race and SES contribute to sleep health disparities, emphasizing the importance of understanding their impact on sleep disorders and treatment particularly in minority populations and veterans.

Genetic Ancestry for Sleep Research: Leveraging Health Inequalities to Identify Causal Genetic Variants.

Recent evidence has highlighted the health inequalities in sleep behaviors and sleep disorders that adversely affect outcomes in select populations, including African-American and Hispanic-American subjects. Race-related sleep health inequalities are ascribed to differences in multilevel and interlinked health determinants, such as sociodemographic factors, health behaviors, and biology. African-American and Hispanic-American subjects are admixed populations whose genetic inheritance combines two or more ancestral populations originating from different continents. Racial inequalities in admixed populations can be parsed into relevant groups of mediating factors (environmental vs genetic) with the use of measures of genetic ancestry, including the proportion of an individual's genetic makeup that comes from each of the major ancestral continental populations. This review describes sleep health inequalities in African-American and Hispanic-American subjects and considers the potential utility of ancestry studies to exploit these differences to gain insight into the genetic underpinnings of these phenotypes. The inclusion of genetic approaches in future studies of admixed populations will allow greater understanding of the potential biological basis of race-related sleep health inequalities.

Pupillometric assessment of sleepiness in narcolepsy.

PURPOSE: Excessive daytime sleepiness is highly prevalent in the general population, is the hallmark of narcolepsy, and is linked to significant morbidity. Clinical assessment of sleepiness remains challenging and the common objective multiple sleep latency test (MSLT) and subjective Epworth sleepiness scale (ESS) methods correlate poorly. We examined the relative utility of pupillary unrest index (PUI) as an objective measure of sleepiness in a group of unmedicated narcoleptics and healthy controls in a prospective, observational pilot study. METHODS: Narcolepsy (n = 20; untreated for >2 weeks) and control (n = 56) participants were tested under the same experimental conditions; overnight polysomnography was performed on all participants, followed by a daytime testing protocol including: MSLT, PUI, sleepiness visual analog scale (VAS), ESS, and the psychomotor vigilance test (PVT). RESULTS: The narcolepsy and control groups differed significantly on psychomotor performance and each measure of objective and subjective sleepiness, including PUI. Across the entire sample, PUI correlated significantly with objective (mean sleep latency, SL) and subjective (ESS and VAS) sleepiness, but none of the sleepiness measures correlated with performance (PVT). Among narcoleptics, VAS correlated with PVT measures. Within the control group, mean PUI was the only objective sleepiness measure that correlated with subjective sleepiness. Finally, in an ANCOVA model, SL and ESS were significantly predictive of PUI as measure of sleepiness. CONCLUSION: The role of PUI in quantifying and distinguishing sleepiness of narcolepsy from sleep-satiated healthy controls merits further investigation as it is a portable, brief, and objective test.