Prevalence of Sleep Disorders by Sex and Ethnicity among Older Adolescent and Emerging Adult College Students:

Relations to Daytime Functioning, Working Memory and Mental Health

Megan E. Petrov, PhD 1 Kenneth L. Lichstein, PhD 2 Carol M. Baldwin, PhD 1

1 College of Nursing & Health Innovation, Arizona State University, Phoenix, AZ, USA

2 Department of Psychology, University of Alabama, Tuscaloosa, AL, USA

Abstract

The study determined the prevalence of sleep disorders by ethnicity and sex, and related daytime functioning, working memory, and

mental health among older adolescent to emerging adult college students. Participants were U.S.A. undergraduates (N=1,684), aged

17-25, recruited from 2010−2011. Participants completed online questionnaires for all variables. Overall, 36.0% of the sample

screened positive for sleep disorders with insomnia, restless legs syndrome, and periodic limb movement disorder being the most

prevalent. Women reported more insomnia and daytime impairment. African-Americans reported more early morning awakenings and

less daytime impairment. Students with insomnia symptoms or restless legs syndrome tended to have lower working memory

capacities. Students with nightmares or parasomnias had greater odds for mental disorders. In an older adolescent to emerging adult

college student sample, sleep disorders may be a common source of sleep disturbance and impairment. Certain sleep disorders may be

associated with lower working memory capacity and poor mental health.

Keywords

ethnicity; sleep disorders; sex; working memory capacity; mental health; daytime functioning

Abbreviations: RLS= restless legs syndrome; PLMD = periodic limb movement disorder; OSA = obstructive sleep apnea; ISI =

Insomnia Severity Index; GSAQ = Global Sleep Assessment Questionnaire; BMI = body mass index; WMC = working memory

capacity; Aopsan = Automated Operation Span task; EDS = excessive daytime sleepiness

Sleep dramatically changes both physiologically and behaviorally throughout adolescence (Colrain & Baker, 2011). The

transition to adulthood is no exception. Older adolescents to emerging adults (18-25 years; Arnett, 2000) experience greater preference

for later bedtimes and rise times, declines in electroencephalography-measured slow wave sleep activity and total sleep time, and

increasing prevalence of symptoms of insomnia and other disturbances (Buchmann et al., 2011; Ohayon, Roberts, Zulley, Smirne, &

Priest, 2000; Roberts, Roberts, & Chan, 2008; Roenneberg et al., 2004). These natural shifts combined with the transition to college,

which often herald increased demands on their time from academic, social, vocational, and other extracurricular sources, likely

increase risk for sleep problems in this segment of the older adolescent to emerging adult population.

Indeed, sleep problems are ubiquitous among older adolescent and emerging adult college students. Two-thirds to three-

quarters report at least occasional sleep difficulties (Buboltz, Brown, & Soper, 2001; Coren, 1994). Approximately 9.4−43% of

surveyed college undergraduate samples report insomnia symptoms (Fernández-Mendoza et al., 2009; Forquer, Camden, Gabriau, &

Johnson, 2008; Taylor et al., 2011) and almost 25% report insufficient sleep (Yang, Wu, Hsieh, Liu, & Lu, 2003). Data suggest these

sleep problems are worsening among older adolescent to younger adult college students globally overtime (Hicks, Fernandez, &

Pellegrini, 2001; Steptoe, Peacey, & Wardle, 2006). Furthermore, sleep disturbance during older adolescence predicts sleep

disturbance in adulthood (Dregan & Armstrong, 2010). Daytime impairment from these sleep problems such as sleepiness and fatigue

are reported in 50−75% of college students with 25% experiencing clinically significant excessive daytime sleepiness (EDS; Lund,

Reider, Whiting, & Prichard, 2010). Sleep problems and related daytime impairment are risk factors for numerous problems among

college students including poor physical and mental health (Lund et al., 2010; Pilcher, Ginter, & Sadowsky, 1997; Steptoe et al., 2006;

Taylor et al., 2011), decrements in academic performance (Gaultney, 2011), difficulty concentrating (Pilcher & Walters, 1997), and

poorer lifestyle factors, including substance use (Gaultney, 2011; Lund et al., 2010), reduced physical activity (Carney, Edinger,

Meyer, Lindman, & Istre, 2006), and less social engagement (Brown, Buboltz, & Soper, 2002).

Older adolescent and emerging adult college students commonly cite stress, nighttime worries, environmental noise, restricted

sleep duration, variable sleep schedules, and co-sleeping as reasons for their sleep problems (Brown et al., 2002; Forquer et al., 2008;

Lund et al., 2010). However, it is unknown if these sleep disturbances may also be attributable to undiagnosed sleep disorders. There

is minimal information on the prevalence of sleep disorders among college students and their impact on mental health, daytime and

neurocognitive functioning. Only one study has used a standardized screening instrument to assess the prevalence of sleep disorders

among college students (Gaultney, 2011). However, this study did not investigate the impact of disordered sleep on daytime

impairment and other daytime functioning factors such as mental health and memory. Gaultney found 25% of students were at risk for

a sleep disorder (2011). Narcolepsy was most prevalent (16.0%) followed by insomnia (12%), periodic limb movement

disorder/restless legs syndrome (PLMD/RLS, 8.0%), circadian rhythm disorders (7.0%), obstructive sleep apnea (OSA; 4%),

hypersomnia (4%), and nightmares (2%). The high prevalence of narcolepsy was likely due to poor specificity of the narcolepsy scale

because some of its items loaded onto other sleep disorder scales (Gaultney, 2010); therefore insomnia was likely the most prevalent

in that sample. This study also evaluated sleep disorder prevalence by sex and ethnicity. Women were at greater risk for PLMD/RLS,

insomnia, and nightmares. There were no significant differences in risk by ethnicity.

Despite known sex and ethnic differences in normal and disordered sleep in other populations (Ruiter, DeCoster, Jacobs, &

Lichstein, 2010; Ruiter, DeCoster, Jacobs, & Lichstein, 2011; Zhang & Wing, 2006;), identification of any disparities in sleep disorder

prevalence and related daytime functioning among college students is a neglected area of inquiry. Available data suggest that sex

differences in disordered sleep among college students are mixed and most studies only reported on symptoms of insomnia and

snoring (Buboltz et al., 2001; Fernandez-Mendoza et al., 2009; Forquer et al., 2008; Gaultney, 2011; Pash & Khan, 2003; Patel et al.,

2008; Tsai & Li, 2004). Furthermore, most of these studies did not have ethnically diverse samples, which precluded analytic

comparisons. Sex and ethnic identity may contribute to variations in medical and psychiatric diagnosis, perception of illness,

treatment-seeking behavior, and preferences for treatment. The accumulation of data on sex and ethnic inequities in prevalence,

severity, etiology, sequelae, comorbidity, and course of sleep disorders may prove fruitful in time with respect to developing tailored

prevention strategies, targeted treatments, and health education initiatives. Studies on prevalence estimates across ethnic groups

among college students are a first step toward addressing ethnicity and sleep in this population and may serve as a springboard for

future studies with larger ethnically diverse sample sizes.

Sleep disturbances and related negative consequences are well-documented among college students and may lead to

appreciable long-term health, social and vocational problems. Approximately 69% of 2011 USA high school graduates enrolled into

college (U.S. Census Bureau, 2009), thus college students represent a sizable portion of the older adolescent to emerging adult

population. Standardized measurement of sleep disorders prevalence in this population is important from a prevention and health

education perspective.

Within a convenience sample of older adolescents to emerging adults enrolled as undergraduates in college, the present study

aims were to a) describe the prevalence of sleep disorders, sleep-related disruptions and daytime impairments, b) identify ethnic and

sex differences in sleep disorders and daytime functioning, and c) determine if being at risk for a sleep disorder is associated with

working memory impairment, and poorer mental health outcomes. For aim a) we hypothesize that insomnia will be the most prevalent

sleep disorder in our sample. Based on previous literature in older populations, for aim b) we hypothesize that a greater proportion of

women and non-Hispanic white students will report insomnia symptoms, and African-American students will report more symptoms

of obstructive sleep apnea. Lastly, we hypothesize that screening positive for a sleep disorder will be significantly related to working

memory impairment and poorer mental health. Compared to the study conducted by Gaultney (2011) and other previous studies

(Buboltz et al., 2001; Fernandez-Mendoza et al., 2009; Forquer et al., 2008; Pash & Khan, 2003; Patel et al., 2008; Tsai & Li, 2004),

the present study used more conservative diagnostic criteria for insomnia, a standardized measure that screened for a broader range of

sleep disorders and disturbances, provided more information on sleep disorders and disturbances by ethnicity and, for the first time,

examined working memory capacity in relation to sleep disturbances.

Method

Study Design

Participants were 1,684 undergraduate college students, aged 17-25 years, attending the University of Alabama, Tuscaloosa,

Alabama, USA. Across three academic periods from 2010−2011, participants were recruited from an online research participant pool.

Within the online pool, the study was described as a 60-minute survey on ‘sleep, memory, and your health.’ Participants were able to

choose this study based on this description alongside types of numerous other ongoing studies registered with the pool. This pool

consisted of 3,192 students enrolled in introductory psychology courses. As a requirement of the course, students participated in the

pool to receive a small amount of credit toward their course grade. Students enrolled in the pool represented the vast majority of

majors offered at the university, and consisted of mostly women (~66%). There were no restrictions on participation. The response

rate from the total pool was 52.3%. Based on resources and to facilitate participation, all measures were administered online.

Participants completed the study on personal computers at times of their choosing. This study was approved by the university

institutional review board and it conformed to the principles expressed in the Declaration of Helsinki.

Measures

The Insomnia severity index (ISI) was used to quantify perceived insomnia severity (Morin, 1993). It is a seven-item

instrument with a five-point Likert-type scale ranging from 0−4 points (range: 0-28). Higher scores indicate greater severity of

insomnia. The ISI has excellent psychometric properties (Savard, Savard, Simard,& Ivers, 2005) and was validated among young

adults (mean age = 20) (Smith & Trinder, 2001). A clinical cutoff score of eight successfully discriminates between people with

insomnia and normal sleepers (Savard et al., 2005). The ISI demonstrated an acceptable Cronbach’s alpha (α = .87) in the study

sample.

The Global Sleep Assessment Questionnaire (GSAQ) is a standardized 11-item screening instrument for sleep disorders and

disruptions (Roth et al., 2002). Each item assesses the frequency of sleep-disordered symptoms over the past four weeks with response

options ‘never,’ ‘sometimes,’ ‘usually,’ and ‘always.’ The GSAQ was validated on 212 patients from sleep centers and primary care

clinics who ranged in age from 18 to 87 years old. More than half were women and about 25% were ethnic minorities. The GSAQ

demonstrated acceptable psychometric properties. Test-retest reliability values as measured by intraclass correlation coefficients were

acceptable for items screening for insomnia, OSA, RLS, and PLM. The GSAQ also demonstrated adequate known group validity such

that individuals with polysomnographic and/or clinically diagnosed sleep disorders also scored highly on GSAQ items designed to

screen for that particular disorder compared to the total sample validation group (Roth et al., 2002). The GSAQ also moderately

correlates with other standardized sleep questionnaires thus demonstrating construct validity. Lastly, area under the curve values that

summarize both sensitivity and specificity in screening for a particular sleep disorder ranged from 72-95% for GSAQ screening items.

The sleep disorders assessed in the study were insomnia symptoms, RLS, PLMD, OSA, and nightmares/parasomnias (assessed

jointly). Among the current sample, the GSAQ had an acceptable Cronbach’s alpha (α = .76).

Demographic, physical health, mental health and sleep information were collected. Demographic information included age,

sex, and ethnicity. Health information consisted of self-reported height, weight, and perceived health (i.e. excellent, very good, good,

fair/poor). Height and weight were used to calculate body mass index (BMI). To assess for mental health problems, participants were

asked if they had ever been diagnosed with a mental disorder, and from the GSAQ, “During the past 4 weeks, did you feel sad or

anxious?” For the latter, responses of ‘usually’ and ‘always’ were defined as poor mental health. Information on the frequency,

duration, and associated daytime impairment of insomnia symptoms were collected. Sleep-related daytime impairment was based on

the International Classification of Sleep Disorders and Coding Manual-II and American Academy of Sleep Medicine Work Group-

derived research diagnostic criteria for an insomnia disorder (American Academy of Sleep Medicine, 2005; Edinger et al., 2004).

Participants responded “yes” or “no” to experiencing the following daytime impairments in relation to any sleep difficulties in the

previous four weeks: fatigue/malaise; attention, concentration or memory problems; mood disturbances; daytime sleepiness; accidents

or errors in performance; somatic symptoms; social and vocational problems; lack of energy/motivation; and sleep-related worries.

Positive responses and the summed number of impairments were used to quantify daytime impairment.

Working memory capacity (WMC). The automated operation span task (Aospan; Schrock, Unsworth, & Heitz, 2003), a

computer-operated working memory span task, is a valid and reliable measure of WMC (Conway et al., 2005; Unsworth, Heitz,

Schrock, & Engle, 2005). Participants solved a set of simple, mathematical problems while trying to memorize letters. These

operations force working memory storage of the letters during simultaneous mathematical processing to utilize executive attention

processes. The Aospan was administered online, independent from the investigator. The task was mouse-driven and began with a

practice session. Participants were required to keep their math accuracy above 85% to ensure both tasks were performed otherwise the

results would be invalid. The Aospan creates simultaneous math problems and letters to be memorized in set sizes ranging from 3−7.

Set sizes were randomly ordered. There was a total of 75 sets. The task took approximately 20-25 minutes. The Aospan score, the total

number of letters recalled in the correction position was the continuous outcome variable. Scores ranged from 0−75. Higher scores

indicated greater WMC.

Study definition of insomnia. In order to be screened positive for insomnia in the study, participants had to satisfy the following

rigorous criteria partially derived from the Diagnostic Statistical Manual of Mental Disorders IV-TR (American Psychological

Association, 2000) and International Classification of Sleep Disorders-II (American Academy of Sleep Medicine, 2005) nosological

systems: a) responding ‘usually’ or ‘always’ to the GSAQ item, “During the past four weeks, did you have difficulty falling asleep,

staying asleep, wake up too early, or feel poorly rested in the morning?”; b) responding at least ‘sometimes’ to “During the past four

weeks, did you have trouble sleeping despite adequate opportunity and circumstances?”; c) reporting at least one sleep-related daytime

impairment; d) no other GSAQ-screened sleep disorders; e) a score of ≥ 8 on the ISI; and f) reporting sleep difficulties for at least one

month.

Study definitions of other sleep disorders. In order to be screened positive for a sleep disorder besides insomnia in this study,

participants had to report experiencing the symptoms of each sleep disorder ‘usually’ or ‘always’ on the screening items within the

GSAQ. The sleep disorders assessed were RLS, PLMD, OSA, insomnia symptoms and nightmares/parasomnias. This method of

scoring method has been used previously in community-based, ethnically-diverse samples that included young adults (Drake,

Richardson, Roehrs, Scofield, & Roth, 2004; Drake, Roehrs, Bresalu, Johnson, Jefferson, Scofield, & Roth, 2010; Drake, Scofield, &

Roth, 2008; Scofield, Roth, & Drake, 2008).

Data Analysis

For nominal variables, χ² analyses were computed. For continuous variables, ANOVA and t-tests were used to compare sex

and ethnic groups. ANCOVA and logistic regression were used, controlling for potential confounders, for the significant differences in

WMC, mental disorder diagnosis, and mental health problems according to sleep disorder status. Bonferroni adjustments corrected for

Type I error inflation. Adjustments were made to thematic clusters of tests as follows: five separate clusters compared each individual

sleep disorder to participants not at risk for a sleep disorder on WMC, mental disorder diagnosis, mental health problems, sex, and

ethnicity; and two separate clusters of tests compared daytime impairments by sex and ethnicity. The alpha level for significance

testing was p = 0.007.

Results

Sample Characteristics

Participant characteristics are provided in Table 1. More than three-quarters of the sample was comprised of women (n =

1,293, 76.8%) and non-Hispanic whites (n = 1,294, 76.8%). The remainder of the sample comprised of 258 African-Americans

(15.3%) 64 individuals of mixed race/ethnicity (3.8%), 27 Hispanic/Latino(a)-Americans (1.6%), 21 Asian-Americans (1.2%), two

American Indian/Native Americans (0.1%), three Hawaiian or Pacific Islanders (0.2%), and 15 individuals who reported their

ethnic/racial background as ‘unknown.’ The sample had a mean BMI of 23.5 ± 4.7; however, the BMI of men was significantly

greater than that of women (p < 0.001). A majority of participants considered their health to be good or better. Although nearly 20% of

participants reported frequent symptoms of sadness and anxiety, less than 10% reported receiving a mental disorder diagnosis. In the

sample, women were more likely to be at risk for sleep disorders, have higher ISI scores, and report psychological symptoms. African-

Americans in the sample had poorer perceived health, higher BMIs and fewer mental disorder diagnoses. Participants at risk for sleep

disorders were more likely to have poor health, lower WMC, and more psychological symptoms than normal sleepers (i.e., no risk for

sleep disorders, EDS, or mental disorder diagnosis).

Of the 1,684 students, 1,361 (81%) completed the Aospan test, 270 students (16%) were not able to complete the Aospan test

largely due to technical incompatibility between the Aospan software and the participant’s choice of internet platform, and 53 students

(3%) provided invalid responses (i.e., math accuracy was below 85%). The WMC was higher in this sample compared to the college

student sample on which the Aospan was originally tested (Unsworth et al., 2005), but results were still within the average range.

Sleep Disorders and Daytime Impairment Prevalence

Overall, 36.0% (n = 607) of the respondents were at risk for at least one sleep disorder, and 6.3% (n = 106) were at risk for two

or more sleep disorders. Table 2 displays the prevalence of sleep disorders and sleep-related disruption and daytime impairments.

Insomnia, RLS, and PLMD were most prevalent, whereas nightmares/parasomnias and OSA were less common. More than a quarter

of the participants stated daytime activities interfered with their sleep, and nearly one of five reported nighttime worries disrupted their

sleep. About three of ten students reported frequent GSAQ-screened insomnia symptoms, whereas 14.3% met the study’s definition

of insomnia. Daytime sleepiness was endorsed by three-quarters of the full sample although only 10.7% reported EDS. Nearly half the

sample reported fatigue, motivation problems, and concentration or memory difficulties.

Sleep Disorders and WMC

Table 3 displays the results for the association between each sleep disorder and WMC. Participants screened positive for sleep

disorders (M = 61.3, SD = 12.2) had less WMC than students who were normal sleepers (M = 62.9, SD = 1.1, ηp2 = 0.005, n = 416),

but the difference did not reach the study-defined statistical significance of p = 0.007 (p = 0.03). Univariate analyses on individual

sleep disorders revealed that participants who screened positive for GSAQ-defined insomnia (p = 0.01), study-defined insomnia (p =

0.04) and RLS (p = 0.03) had lower WMC than normal sleepers but these were not statistically significant differences and the effect

sizes were small (Range of ηp2 = 0.007-0.009). In multivariate analyses controlling for sex, perceived health, and psychological

symptoms of sadness and anxiety, these differences remained non-significant according to the study definition. In Supplementary

Table 1, results are shown for the association between WMC and each sleep disorder when WMC was calculated as the sum of

perfectly recalled sets, a scoring method indicating a greater level of difficulty within the test. The results indicate more robust and

statistically significant univariate differences between normal sleepers and students screened positive for RLS or GSAQ-defined

insomnia. However, after adjustment these differences become non-significant.

Sleep Disorders and Mental Health

Students at risk for sleep disorders were more likely to report previous mental disorder diagnoses (12.0% vs. 5.5%, χ²(1, n =

1,679) = 22.8, p < 0.001, φ = .12) and frequent psychological symptoms (33.6% vs. 10.5%, χ²(1, n = 1,674) = 134.7, p < 0.001, φ =

.28) compared to students not at risk for any sleep disorder. Analyses on individual sleep disorders revealed each one was associated

with a greater prevalence of frequent psychological symptoms (all p < 0.007), but only nightmares/parasomnias (20.4% vs. 6.9%,

χ²(1, n = 1,684) = 26.2, p < 0.001, φ = .13) was associated with mental disorder diagnoses compared to participants not at risk for any

sleep disorder. After adjusting for sex and perceived health in logistic regression analyses, the relation between

nightmares/parasomnias and mental disorders remained significant (OR: 3.23, 95%CI = 1.95–5.35, p < 0.001).

Sex Differences in Sleep Disorders and Daytime Impairment

The prevalence of screened sleep disorders, sleep-related disruptions, and daytime impairment by sex are displayed in Table 4.

Women were more likely to report GSAQ and study-defined insomnia than men. After adjusting for frequency of psychological

symptoms and perceived health, women still had significantly greater odds for GSAQ insomnia (OR: 1.59, 95%CI = 1.19–2.12, p =

.002), and study-defined insomnia (OR: 1.66, 95%CI = 1.14–2.43, p = .008). Women reported more sleep-related daytime

impairments, specifically daytime sleepiness, mood disturbances, somatic symptoms, and lack of energy/motivation. Women were

also more likely to report EDS, work and other activities interfering with sleep, and more worry-disrupted sleep.

Ethnic Differences in Sleep Disorders and Daytime Impairment

The prevalence of screened sleep disorders, sleep-related disruptions, and daytime impairment by ethnicity are described in

Table 5. There were no ethnic differences in sleep disorder prevalence in the sample. An item analysis of the ISI produced a

significant difference in early morning awakenings across ethnic groups after controlling for sex, perceived health, BMI, activities

preventing sleep, snoring, sleep-disordered breathing, and psychological symptoms, F(1, 1,454) = 8.2, p = .004, ηp2 = .006. African-

American students reported more frequent early morning awakenings (M = 1.0, SD = 1.0) than non-Hispanic white students (M = 0.8,

SD = 1.0). Non-Hispanic white students endorsed fatigue/malaise, lack of energy/motivation/initiative, and a greater number of

daytime impairments significantly more than African-American students.

Discussion

Our findings indicate that sleep disorders may be fairly prevalent among older adolescent to emerging adult college students,

with insomnia, RLS, and PLMD reported as the most prevalent in the present study sample. The sample found daytime functioning

impairments due to sleep disturbances to be a common experience, particularly daytime sleepiness. Women and non-Hispanic white

students were more likely to report daytime impairments than men and African-American students, respectively. Participants with

insomnia symptoms, or RLS were more likely to have lower WMC; however, these findings were explained by sex, perceived health,

and frequency of psychological symptoms. Participants at risk for sleep disorders also reported more frequent psychological

symptoms. After adjustment, participants with nightmares/parasomnias had greater odds of having a mental disorder diagnosis.

The sample prevalence rates for insomnia (14.3%), RLS (8.4%), PLMD (7.8%) and daytime sleepiness (75.5%) were

consistent with previous literature in the college population (Fernandez-Mendoza et al., 2009; Forquer et al., 2008; Gaultney, 2011;

Lund et al., 2010; Taylor et al., 2011) and the general population of adults (Ohayon, 2011; Insomnia: 6-15%, RLS ~10%). Our

sample, however, was less likely to report OSA and EDS, and more likely to report nightmares/parasomnias. These inconsistencies are

likely due to differences in the measurement across studies with college students. Previous studies used screening instruments that

defined OSA and EDS with greater specificity and examined nightmares alone without parasomnias (Fernandez-Mendoza et al., 2009;

Fernandez-Mendoza et al., 2010; Gaultney, 2011; Lund et al., 2010). Despite these discrepancies, it can be deduced that many college

students may suffer from sleep disruption and impairment due to sleep disorders. Students with symptoms of insomnia may be in

greater jeopardy for poorer academic and health outcomes as they were more likely to report mental health symptoms and have less

WMC in the study. It may be prudent for student health providers and college counselors to routinely inquire about sleep status so

appropriate treatment and referrals can be made.

Several sex and ethnic differences emerged in the data. Women students in the sample were more likely to report insomnia,

EDS, and more daytime impairments than men. These results are consistent with a meta-analysis that found excess risk for insomnia

symptoms among older adolescents and women ages 15−30 years (Zhang & Wing, 2006). Differences in mental health by sex may

contribute to this disparity in insomnia symptoms; however, evidence has produced mixed results (Hale et al., 2009; Lindberg et al.,

1997). Our analyses found psychological symptoms did not explain the sex disparity in risk for insomnia, although women were

overrepresented in this sample. Psychological symptoms may not play a role in this sample; however, it appears daily stresses such as

worries and activities that prevent sleep were more prevalent among women students. Further research is warranted to identify what

contributes to sex inequities in insomnia risk among college students. Psychosocial as well as biological differences in sex steroids and

other reproductive-related factors may be targets for investigation.

Similar to findings in a previous study with college students (Pasha & Khan, 2003), African-Americans in this study were not

significantly more likely to report loud snoring than non-Hispanic whites though there was a trend in that direction. Snoring is a

hallmark symptom of OSA. In a meta-analysis, the prevalence of OSA in the general population is greater in African-Americans

compared to non-Hispanic whites (Ruiter et al., 2010), but given the increase in OSA prevalence with age, the difference may not be

present in older adolescent to emerging adult college students. However, risk factors for OSA may be more prevalent in African-

Americans at a younger age and therefore may be worthy targets for further inquiry. Our results indicate this hypothesis may have

some basis because African American students in the sample had higher BMIs and poorer perceived health than non-Hispanic white

students.

Other ethnic differences found in our study were reduced reported daytime impairment but more early morning awakenings

among African-American students in the sample. Early morning awakenings are a symptom of insomnia and often may indicate the

presence of a physical or mental disorder (Ohayon, Zulley, Guilleminault, Smirne, & Priest, 2001). Early morning awakenings may

also reflect greater sleep deprivation among African Americans in the sample. In a meta-analysis, total sleep time was objectively and

subjectively shorter among African-Americans compared to non-Hispanic whites (Ruiter et al., 2011); however, in another meta-

analysis non-Hispanic whites reported greater early morning awakenings compared to African-Americans, particularly in studies

sampling young to middle-aged adults (Ruiter et al., 2010). Given the importance of early morning awakenings as a symptom of

insomnia, illness, and possibly sleep deprivation, future studies of college students are needed to determine factors that may account

for differences in early morning awakenings by ethnicity and compare these changes across the age spectrum.

A major strength of the current study is its examination of WMC related to sleep. Participants with insomnia symptoms or RLS

were more likely to have lower WMC scores though these differences did not reach study-defined statistical significance. The

literature has reported a discrepancy in self-reported and objective neurocognitive impairment among people with insomnia, although

the data on working memory performance is mixed (Orff, Drummond, Nowakowski, & Perlis, 2007; Varkevisser & Kerkhof, 2005).

Little data is available on the neurocognitive functioning of patients with RLS; however, one study has shown deficits in prefrontal

cortex function (Pearson et al., 2006). The trend between poorer WMC with insomnia symptoms, insomnia, or RLS in this older

adolescent to emerging adult college student sample may portend the potential for concomitant cognitive and sleep problems with age

and require further study. The mechanisms underlying these relationships may lie in delayed sleep onset and insufficient sleep, both

common to these sleep disorders. Experimental sleep deprivation studies consistently have found deficits in working memory with

prolonged sleep loss (Durmer & Dinges, 2005). Our results imply that these students may be most vulnerable to academic

performance problems. Treatment for these disorders may need to emphasize improvement in neurocognitive performance as an

outcome.

Sleep disorders are under-diagnosed in the general population (Ohayon, 2011). The frequency of sleep disorders assessments

in college settings has not been investigated; however, it is likely sleep disorders are under-recognized in college populations akin to

the general population. Sleep disruption may be perceived as a normal part of the college experience rather than a preventable

problem. Symptoms of sleep disorders may also be misattributed to variable sleep schedules, substance use, and stress, thus the root

cause of the disturbance is missed. Emerging adulthood, and the college experience, is a formative time when many sleep disorders

can emerge and poor sleep habits can be established with negative short-term and long-term consequences (Gaultney, 2011). The

present study highlights the risk for these consequences with the associations between sleep disorders and poor mental health, daytime

functioning, and neurocognitive deficits.

Limitations

There are limitations to the study results. First, the sample was not randomly selected so generalizability is limited to college

students only with similar characteristics to the present sample. Women were overrepresented in the sample which may have inflated

the prevalence of insomnia due to excess risk for insomnia in women (Zhang & Wing, 2006). However, the prevalence was

comparable to other college populations (Fernandez-Mendoza et al., 2009; Lund et al., 2010). Second, with the exception of insomnia,

the prevalence estimates and mental health problems definition were based on categorized responses from the GSAQ. The items on

the GSAQ were validated on a mixed, multi-center clinical and community sample comprising of mostly non-Hispanic white middle-

aged adults. Therefore, validity of this scale may not transfer to a study sample recruited from a general population of college students,

though this scale has been used in population-based studies with young adults. Furthermore, the method of scoring the GSAQ used in

the present study has not been validated. However, the extant literature has considered this scoring method to be acceptable in

community-based, ethnically-diverse samples that included young adults (Drake, Richardson, Roehrs, Scofield, & Roth, 2004;

Scofield, Roth, & Drake, 2008). Therefore the results may remain an important contribution given that only one other study has used a

standardized sleep disorder screening tool in a college sample (Gaultney, 2011). Third, most of the data was self-reported and prone

to bias typical of this method. Fourth, the present study did not assess for narcolepsy or circadian rhythm disorders that typically

emerge in older adolescence and emerging adulthood. Evening circadian preference is evident in college populations and related to

poorer psychosocial functioning (Fernandez-Mendoza et al., 2009; Fernandez-Mendoza et al., 2010; Lund et al., 2010), thus the role

of delayed sleep phase may have influenced study results. Lastly, the Aospan was completed at the participants’ leisure and time-

stamped information was not available. Therefore, the study could not control for timing, environment, or learning disabilities.

However, participants were informed of the length and nature of the test, and they were encouraged to pick a time and place free of

distraction.

Conclusions

Using a standardized sleep disorder screening measure and strict diagnostic criteria for insomnia, the study found that sleep

disorders and sleep-related daytime impairment were common experiences among a sample of older adolescent to emerging adult

college students, and varied by sex and ethnicity. Swift and accurate diagnosis and treatment of sleep disorders particularly among

vulnerable subgroups of college students may improve academic performance, cognition and working memory, physical and mental

health, and reduce drop-out rates. All of these hypotheses need to be tested in future, larger studies. If identification and treatment of

sleep disorders among college students results in better health and academic performance, then college institutions may find

substantial value in widespread screening on their campuses. Future studies could test the effectiveness of such a screening and

awareness campaign on each of these outcomes.

The study results suggest several other potential research avenues. For example, to acquire accurate estimates of the prevalence

and incidence of sleep disorders among college students in general rather by institution, multi-site epidemiological cohort studies

using validated screening tools and rigorous diagnostic criteria are needed. These future studies should also assess for sleep disorder

severity and a broad range of sleep disorders across ethnically-diverse samples. Experimental studies of the day-to-day associations

between disordered sleep patterns and working memory, and its impact on academic performance are also needed. Longitudinal

relationships between sleep disorders and poor mental health should also be explored to see the temporal sequence of symptomatology

and their relationships to stress management, adjustment to college life, and mental disorder diagnosis.

The study results also indicate the need for better prevention and treatment interventions for sleep disorders in college

populations, the efficacy of which should be tested. In the present study, clinical insomnia was the sleep disorder with the highest

prevalence. Therefore, many campuses may benefit from the availability of therapists specializing in cognitive-behavioral

interventions for insomnia and other sleep disorders (Morgenthaler et al., 2006). The field of study can benefit from implementation

studies of this type in student health and counseling centers.

Acknowledgments: We thank Virginia Graydon for her assistance with data-entry.

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a Normal sleepers are defined as having a negative sleep disorder screening on the Global Sleep Assessment Questionnaire (GSAQ), no diagnosed mental

disorder, and infrequent excessive daytime sleepiness according to the GSAQ (n=416).

b Based on n = 1,594. Data were invalid or missing for 90 participants.

c Based on n = 1,361. Data were invalid or missing for 273 participants.

Table 1−Sample characteristics of 1,684 older adolescent to emerging adult undergraduate college students.

Whole Sample M(SD)

or n(%)

Sex

M(SD) or n(%)

Ethnicity

M(SD) or n(%)

Sleep Status

M(SD) or n(%)

Variable

n = 1,665

Males

n = 355

Females

n = 1,184

p AA

n = 255

NHW

n = 1,284

p

Normala

n = 466

Sleep Dx

n = 552

p

Age 19.3(1.4) 19.6(1.6) 19.1(1.3) <.001 19.2(1.4) 19.3(1.4) .23 19.2(1.3) 19.3(1.4) .29

Male 391(23.2) n/a n/a 52(20.2) 307(23.7) .21 153(30.2) 118(19.4) <.001

Sleep Dx 607(36.0) 118(30.3) 489(37.9) .006 93(36.2) 464(35.9) .94 n/a n/a

Health .076 <.001 <.001

Excellent 278 (16.5) 77(19.7) 201(15.6) 38(14.7) 216(16.7) 133(26.3) 64(10.5)

Very Good 837 (49.7) 195(49.9) 642(49.7) 101(39.1) 666(51.5) 267(52.8) 279(46.0)

Good 500 (29.7) 100(25.6) 400(31.0) 98(38.0) 371(28.7) 97(19.2) 217(35.7)

Fair/Poor 68 (4.0) 19(4.9) 49(3.8) 21(8.1) 40(3.1) 9(1.8) 47(7.7)

BMI b 23.5 (4.7) 25.1(5.3) 23.0(4.4) <.001 25.6(5.9) 23.1(4.3) <.001 23.5(4.3) 23.7(5.2) .51

WMC c 62.2 (11.5) 61.8(11.3) 62.3(11.6) .45 62.1(11.7) 62.1(11.5) .99 63.0(10.9) 61.2(12.2) .019

Mental Dx 132 (7.8) 24(6.1) 108(8.4) .15 8(3.1) 114(8.8) .002 n/a n/a

Sad/Anx 317(18.8) 52(13.3) 265(20.6) .001 45(17.4) 248(19.2) .50 16(3.2) 203(33.6) <.001

ISI 7.4(5.0) 6.4(4.8) 7.6(5.0) <.001 7.6(5.2) 7.3(5.0) .32 3.0(2.2) 11.3(4.9) <.001

AA = African-American; NHW = Non-Hispanic white; Dx = diagnosis; M = mean; SD = standard deviation; BMI = body mass index; WMC = working memory

capacity measured with the Automated Operation Span task; Sad/Anx = frequent sadness or anxiety according to the GSAQ; ISI = Insomnia Severity Index

score.

a Obstructive sleep apnea defined as having both loud snoring and sleep-disordered breathing

GSAQ = Global Sleep Assessment Questionnaire; EDS = excessive daytime sleepiness

Table 2−Prevalence of sleep disorders, sleep disruptions, and daytime impairment

GSAQ-Defined Sleep Disorder n (%)

Loud snoring 102 (6.1)

Sleep-disordered breathing 27 (1.6)

Obstructive sleep apneaa 27 (1.6)

Restless legs syndrome 141 (8.4)

Periodic limb movement disorder 132 (7.8)

Nightmares/ Parasomnias 113 (6.7)

GSAQ insomnia 500 (29.7)

Study definition of insomnia 240 (14.3)

Daytime Interference & Other Disruptions

EDS 181 (10.7)

Sleep difficulties/EDS interfered with daytime activities 154 (9.1)

Work and other activities prevented sleep 438 (26.0)

Pain-disrupted sleep 39 (2.3)

Physical problem-disrupted sleep 49 (2.9)

Medication-disrupted sleep 62 (3.7)

Worry-disrupted sleep 322 (19.1)

Daytime Impairment

Fatigue/Malaise 758 (45.0)

Attention/Concentration/Memory 748 (44.4)

Social/Vocational problems 261 (15.5)

Mood disturbance or irritability 688 (40.9)

Daytime sleepiness 1,271 (75.5)

Motivation/energy/initiative 794 (47.1)

Accidents/errors in performance 80 (4.8)

Somatic symptoms 415 (24.6)

Worries about sleep 356 (21.1)

M(SD)

Total no. daytime impairments 3.2(2.1)

a p<.007 – study-defined statistical significance

b Sample size was too small for meaningful analysis of sleep-disordered breathing or obstructive sleep

apnea

c Covariates included sex, perceived health and frequency of mood symptoms

d Normal sleepers are defined as having a negative screening on the GSAQ, no diagnosed mental disorder,

and infrequent excessive daytime sleepiness according to the GSAQ.

GSAQ = Global Sleep Assessment Questionnaire.

Table 3−Working memory capacity associated with each sleep disorder a,b

Sleep Disorders Univariate Multivariatec

M (SD) F p ηp2 F p ηp

2

Normal sleepers d vs. 62.9 (11.1)

Any sleep disorder 61.3 (12.2) 4.6 .03 .005 1.6 .20 .002

Loud snoring 63.1 (11.7) .01 .91 .000 1.3 .26 .003

Restless Legs Syndrome 60.3 (10.8)

(16.(16.6)

5.0 .03 .009 3.3 .07 .006

Periodic Limb Movement Disorder

Disorder

61.1 (12.1) 2.2 .14 .004 0.8 .36 .002

Nightmares/Parasomnias 61.2 (12.4) 1.5 .22 .003 1.1 .31 .002

GSAQ insomnia 60.9 (13.0)

((18.2)

5.6 .01 .007 3.3 .07 .004

Study definition of insomnia 60.8 (12.8) 4.4 .04 .007 1.6 .20 .003

ª All degrees of freedom were equal to 1.

b Obstructive sleep apnea is both loud snoring and sleep-disordered breathing.

GSAQ = Global Sleep Assessment Questionnaire; EDS = excessive daytime sleepiness.

† p < .05; * p < .007 – study-defined statistical significance; ** p < .001

Table 4−Sex differences in sleep disorders and disturbances ª

Variable Sex

Sleep Disorders % Males % Females χ²

Loud snoring 8.4 5.3 5.1†

Sleep-disordered breathing b 2.6 1.3 2.9

Restless Legs Syndrome 9.5 8.0 0.8

Periodic Limb Movement Disorder 6.6 8.2 1.0

Nightmares/Parasomnias 4.6 7.3 3.6

GSAQ insomnia 21.5 32.2 16.4**

Study definition of Insomnia 9.5 15.8 9.6*

Daytime Interference & Other Disruptions

EDS 5.9 12.2 12.6**

Sleep difficulties/EDS interference 7.7 9.6 1.3

Work and other activities prevented sleep 19.2 28.1 12.3**

Pain-disrupted sleep 1.8 2.5 0.6

Physical problem-disrupted sleep 1.8 3.2 2.3.

Medication-disrupted sleep 2.1 4.2 3.9†

Worry-disrupted sleep 13.0 21.0 12.2**

Daytime Impairment

Fatigue/Malaise 41.7 46.0 2.3

Attention/Concentration/Memory 39.1 46.0 5.8†

Social/Vocational problems 15.3 15.5 0.01

Mood disturbance or irritability 30.9 43.9 20.7**

Daytime sleepiness 65.0 78.7 30.4**

Motivation/energy/initiative 38.9 49.7 14.0**

Accidents/errors in performance 3.3 5.2 2.3

Somatic symptoms 11.5 28.6 47.3**

Worries about sleep 16.9 22.5 5.7†

M(SD) M(SD) t(df)

Total no. daytime impairments 2.6(2.0) 3.4(2.1) 6.1(1,676)**

Table 5 −Ethnic differences in sleep disorders and disturbances ª

Variable Ethnicity

Sleep Disorders % AA % NHW

% Other

χ²

Loud snoring 8.5 5.3

7.5

4.0†

Sleep-disordered breathing b - -

-

N/A

Obstructive sleep apnea b - -

-

N/A

Restless Legs Syndrome 9.3 8.2

8.3

0.4

Periodic Limb Movement Disorder 7.4 8.0

5.8

0.1

Nightmares/Parasomnias 3.9 7.0

9.2

3.4

GSAQ insomnia 28.3 30.0

30.0

0.3

Study definition of Insomnia 14.0 14.3

14.3

.02

Daytime Interference & Other Disruptions

EDS 13.2 10.0

14.2

2.4

Sleep difficulties/EDS interfered daytime activities 10.5 8.2

16.7

1.4

Work and other activities prevented sleep 23.3 25.5

37.5

0.6

Pain-disrupted sleep 2.3 2.3

-

0.0

Physical problem-disrupted sleep 1.9 2.9

5.0

0.8

Medication-disrupted sleep c - -

2.5

N/A

Worry-disrupted sleep 14.3 19.6

25.8

3.8†

Daytime Impairment

Fatigue/Malaise 34.9 46.7

48.3

12.1**

Attention/Concentration/Memory 37.6 45.4

50.8

5.4†

Social/Vocational problems 15.1 14.8

23.3

0.01

Mood disturbance or irritability 35.7 41.6

45.0

3.1

Daytime sleepiness 69.4 77.0

74.2

6.7†

Motivation/energy/initiative 36.8 49.5

43.3

14.0**

Accidents/errors in performance 4.3 4.9

5.0

0.2

Somatic symptoms 22.5 24.9

28.3

0.7

Worries about sleep 20.2 21.4

23.5

0.2

M(SD) M(SD)

M(SD)

t(df)

Total no. daytime impairments 2.8(2.1) 3.3(2.1)

3.4 (2.1)

3.4(1,549)**

ª All degrees of freedom were equal to 1.

b Obstructive sleep apnea is both loud snoring and sleep-disordered breathing.

c Accurate estimates could not be obtained due to a low prevalence.

GSAQ = Global Sleep Assessment Questionnaire; EDS =excessive daytime sleepiness

† p<.05, * p<.007 – study-defined statistical significance, **p<.001

SLEEP DISORDERS IN YOUNG ADULTS 38

a Working memory capacity was scored as the sum of perfectly recalled sets (Range 0-75).

b p<.007 – study-defined statistical significance

c Sample size was too small for meaningful analysis of sleep-disordered breathing or obstructive

sleep apnea

d Covariates included sex, perceived health and frequency of mood symptoms

e Normal sleepers are defined as having a negative screening on the GSAQ, no diagnosed mental

disorder, and infrequent excessive daytime sleepiness according to the GSAQ.

GSAQ = Global Sleep Assessment Questionnaire.

Supplementary Table 1− Working memory capacity associated with each sleep disorder a,b,c

Sleep Disorders Univariate Multivariate d

M (SD) F p ηp2 F p ηp

2

Normal sleepers e vs. 50.7 (17.1)

Any sleep disorder 47.6 (17.8) 7.0 .008 .008 2.8 .10 .003

Loud snoring 51.5 (16.1) .15 .70 .000 1.5 .22 .003

Restless Legs Syndrome 45.2 (16.6)

(16.(16.6)

9.0 .003 .017 5.7 .017 .011

Periodic Limb Movement

Disorder Disorder

47.7 (15.6) 2.7 .10 .005 1.2 .28 .002

Nightmares/Parasomnias 48.2 (18.4) 1.4 .23 .003 0.4 .54 .001

GSAQ insomnia 47.2 (18.2) 8.2 .004 .010 4.1 .043 .005

Study definition of insomnia 46.7 (18.4) 6.9 .009 .011 3.0 .08 .005