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Daytime sleepiness: An epidemiological study of young adults
Abstract and Figures
Although excessive daytime sleepiness is associated with increased risks for accidents, decreased productivity, and interpersonal difficulties, information on its epidemiology is scarce. This paper examines correlates of and suspected risk factors for daytime sleepiness from a longitudinal epidemiological study of young adults.
The sample consisted of 1007 randomly selected young adults from a large health maintenance organization in southeast Michigan. Data were gathered in personal interviews conducted with 97% of the sample 5.5 years after baseline. Information on sleep characteristics in the last 2 weeks, including daytime sleepiness, nocturnal sleep onset, snoring, and hours of sleep, was collected on a self-administered instrument. Psychiatric disorders were measured by the National Institute of Mental Health's Diagnostic Interview Schedule.
The average length of nocturnal sleep on weekdays was 6.7 hours. Daytime sleepiness was inversely related to hours of sleep and positively related to the ease of falling asleep at night; it varied significantly by employment and marital status. Snoring was associated with increased daytime sleepiness, as was recent major depression.
Factors that might increase daytime sleepiness among young adults include social factors (being single and being employed full time) and pathological conditions (frequent snoring and major depression).
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... Res. Public Health 2022, 19, 16334 2 of 10 among adults [6]. Therefore, the problem of college student suicide needs extra attention, especially the study of SI among college students. ...
... Excessive daytime sleepiness (EDS) is a type of sleep disturbance [18]. Excessive daytime sleepiness may lead to a decrease in college students' ability to study and work, an increase in the risk of accidents, and difficulties in interpersonal relationships, which will undoubtedly have a huge negative impact on college students' physical and mental health [19]. Currently, multiple studies have demonstrated that EDS is associated with psychiatric disorders in college students [20][21][22]. ...
... Excessive daytime sleepiness (EDS) sleep disturbance [18]. Excessive daytime sleepiness may lead to a decrease students' ability to study and work, an increase in the risk of accidents, and dif interpersonal relationships, which will undoubtedly have a huge negative college students' physical and mental health [19]. Currently, multiple stu demonstrated that EDS is associated with psychiatric disorders in college stu 22]. ...
The purpose of this study was to verify the mediating role of depressive symptoms between excessive daytime sleepiness and suicidal ideation in college students. Of the 6944 participants, 2609 (37.6%) were male and 4335 (62.4%) were female. College students with excessive daytime sleepiness (p < 0.001) and those with depressive symptoms (p < 0.001) were more likely to have suicidal ideation. Moreover, both excessive daytime sleepiness (β = 0.14, 95% CI: 1.01–1.32) and depressive symptoms (β = 1.47, 95% CI: 3.80–5.00) were associated with suicidal ideation. The effect size of the mediating role of depressive symptoms in excessive daytime sleepiness to suicidal ideation was 50.41% for the entire sample, 58.33% for males, and 42.98% for females. Depressive symptoms partially mediated the relationship between excessive daytime sleepiness and suicidal ideation. The timely assessment of depressive symptoms in college students with excessive daytime sleepiness, and intervention, may reduce their risk of suicidal ideation.
... There is ample evidence for an association between daytime sleepiness and moderate to severe depression [31]. Given that insomnia, particularly when associated with impaired daytime function, plays a key role in the onset of depression [32], it is of significant clinical importance to unravel the link between EDS and depression. ...
... Given that insomnia, particularly when associated with impaired daytime function, plays a key role in the onset of depression [32], it is of significant clinical importance to unravel the link between EDS and depression. Furthermore, knowledge of the interrelation between EDS and mood disorders may have ramifications for the treatment of depression [31]. ...
Fatigue and excessive daytime sleepiness (EDS) are frequently conflated in everyday life, but they are separate concepts with distinct symptoms. Despite their potential to coexist or occur
independently, their interplay with depression remains largely unexplored. This study investigates the complex relationship between fatigue, excessive daytime sleepiness (EDS), and depression among students, aiming to unravel their relative associations. A cross-sectional survey of Indian school students (N=450) aged 11 to 20 (15.2±1.46) was analysed. The study used self-reported measures such as the Fatigue Severity Scale (FSS), Epworth Sleepiness Scale (ESS), and the Center for Epidemiologic Studies Depression Scale (CES-D). The findings revealed significant associations between depression and various combinations of sleepiness and fatigue, with the E+F+ group showing the strongest correlation. Depression was significantly higher in excessive daytime sleepers (N= 165, 69.9%) (P < 0.001) and fatigue (N= 167, 70.8%) (p < 0.001). Depression was found positively correlated with fatigue (r =0.332, p < 0.001 and daytime sleepiness (r=0.213, p<0.001). Chronotype was found negatively correlated with fatigue (r=-0.124, p<0.001), daytime sleepiness (r=-0.105, p<0.05), and depression (r=-0.198, p<0.001). These findings underscore a significant association (p<0.001) between depression and the presence of both excessive daytime sleepiness and fatigue. This revelation demands a nuanced approach to mental health interventions, recognizing the shared underlying mechanisms and advocating for comprehensive
strategies that address these intertwined facets of student well-being.
... Sleep disorders are an important public health issue because they have a significant negative impact on individuals' physical and social performance, their ability to work and their quality of life (Billiard and Bentley, 2004). Individuals who regularly sleep an average of 7-8 h/day (intermediate sleep pattern) often have better physical health and lower risk of early mortality or the development of diabetes, cardiopathy or cognitive and psychological abnormalities, as compared with those who sleep less (short sleep pattern) or more (long sleep pattern) (Breslau et al., 1997;Chang et al., 1997;Pilcher et al., 1997;Pilcher and Ott, 1998;Kojma et al., 2000;Howard et al., 2002;Kripke et al., 2002;Parshuram et al., 2004). Insomnia is the most prevalent sleep disorder in both the general population and among psychiatric patients (Szelenberger and Soldatos, 2005). ...
... As observed in the present study, earlier studies also found that poor sleep quality and the presence of sleep disorders were associated with an impaired quality of life in patients with anxiety or depressive disorders. We are also inconsistent with recent studies that have examined the relationship between sleep disorders and the quality of life in patients with anxiety or depressive disorders (Mellinger et al., 1985;Breslau et al., 1997;Chang et al., 1997;Pilcher et al., 1997;Pilcher and Ott, 1998;Benz et al., 2000;Kojma et al., 2000;Howard et al., 2002;Kapur et al., 2002;Kripke et al., 2002;Sabbatini et al., 2002;Billiard and Bentley, 2004;Parshuram et al., 2004;Patel et al., 2004;Unruh et al., 2004;Wasserfallen et al., 2004;Abad and Guilleminault, 2005;Taylor et al., 2005;Ramsawh et al., 2009;Loria-Castellanos et al., 2010) because sleep disorders can be treated successfully, and improving sleep may, in turn, improve patients' quality of life. There was a strong association between the quality of sleep and the mental and physical quality of life. ...
... Studies show that healthy, normal young adults, particularly college students, are sleepier than healthy, normal older adults. 1,2 The cause of the increased sleepiness among younger adults has not been definitively demonstrated. Although, not sleeping enough could be one of the major factors. ...
... Although, not sleeping enough could be one of the major factors. 1,2,3 Three major hormones which influence the metabolism of the human body namely ghrelin, leptin and insulin are known to be affected by inadequate sleep. 4 Excessive Daytime Sleepiness (EDS) when present, especially in young adults hampers with the daily life of an individual and have been known to be associated with serious consequences. ...
Background: Current patterns of lifestyle, especially in young adults, linked to technological and socialdevelopment, have led to an increased prevalence of sleep disorders. Excessive daytime sleepiness (EDS) whenpresent hampers the quality of life of the individual and the overall productivity of the community as a whole.Three major hormones which influence the metabolism of the human body namely ghrelin, leptin and insulin areknown to be affected by Inadequate sleep. The purpose of this study was to find if there is any correlation betweenExcessive daytime sleepiness and body composition in order that useful interventions may be found, to reduce theburden of these conditions.Methods: The research involved 30 subjects between 18 to 25 years of age. Body mass index, waist-hip ratio andneck circumference was calculated and the daytime sleepiness was measured using the Stanford Sleepiness Scale(SSS). The Spearman rank correlation test was used for analysis.Conclusion: Stanford Sleepiness Scale score was correlated with Body mass index, waist-hip ratio and neckcircumference individually and the p value came to be 0.5876, 0.8145 and 0.9076 respectively which is notconsidered significant. Hence, no correlation was found between daytime sleepiness and Body mass index, Waisthipratio and Neck circumference.
... The association between retirement and EDS found in our study may be attributed to various factors, such as changes in daily routines, reduced social engagement, poor sleep hygiene or irregular sleep schedules, but these questions were not included in the survey. Breslau et al. showed that those who were employed had higher levels of sleepiness than those who were unemployed (16). Sleep disturbances, particularly insomnia, can contribute to mental disorders by impairing brain neuroplasticity and stress immune pathways. ...
Introduction
To identify predictors of excessive daytime sleepiness we analyzed data from the ‘Epidemiology of cardiovascular diseases in regions of Russia (ESSE-RF)’ study.
Methods
Data from participants of the cohort study ESSE-RF (2012–2013), aged 25–64 years, from 13 regions of Russia were analyzed (2012–2013). The participants were interviewed regarding their sleep complaints, including difficulties with initiating and maintaining sleep, sleepiness, and use of sleeping pills. Sleepiness was considered significant if it occurred at least three times a week. The examination encompassed social, demographic, and anthropometric measures, lifestyle factors, self-reported diseases, and laboratory parameters. The final analysis included 13,255 respondents.
Results
Frequent (≥3 times/week) sleepiness was reported by 5,8%, and occasional sleepiness (1–2 times/week) by 10.8% of respondents. Multivariate regression analysis identified significant predictors of frequent sleepiness. Sleep complaints (insomnia, sleep apnea, snoring) and frequent use of sleep medication were prominent factors. Additionally, age, female gender, higher education, and retirement status were associated with sleepiness. Beyond demographics and sleep, the analysis revealed predictors: abnormal anxiety levels, low high-density lipoprotein, high salt intake and following medical conditions: arrhythmia, hypertension, myocardial infarction, other heart diseases, and renal disease.
Conclusion
This study identified a significant prevalence of EDS in Russians, aligning with global trends. However, findings suggest potential regional variations. Analysis revealed a complex interplay of factors contributing to EDS, highlighting the importance of individualized treatment approaches for improved sleep health.
... Indeed, major depressive disorder is associated with a higher risk of excessive daytime sleepiness whereas excessive daytime sleepiness may promote the development of major depressive disorder [16][17][18]. Furthermore, the prevalence of major depressive disorder is estimated at 9.2% in individuals with severe daytime sleepiness whereas excessive daytime sleepiness may affect 50.8% of major depressed individuals [19,20]. Despite the existence of this special relationship between excessive daytime sleepiness and major depressive disorder, the involvement of major depressive disorder in the occurrence of excessive daytime sleepiness has not been investigated in hypertensive patients. ...
There is a special relationship between major depressive disorder and excessive daytime sleepiness. However, given the negative impact of excessive daytime sleepiness on life quality and cardiovascular outcome in hypertensive patients, the objective of this study was to investigate the potential role played by major depressive disorder in the occurrence of this complaint for this particular subpopulation. Data from 1404 hypertensive patients recruited from the Sleep Unit's polysomnographic recordings database were analyzed. A score >10 on the Epworth Sleepiness Scale was used to define excessive daytime sleepiness in this study. Logistic regression analyses were performed to investigate the risk of excessive daytime sleepiness associated with major depressive disorder in hypertensive patients. Excessive daytime sleepiness was frequent (40.0%) in our sample of hypertensive patients. After adjustments for major confounding factors, multivariate logistic regression analyses demonstrated that unlike remitted major depressive disorder, only current major depressive disorder was associated with a higher risk of excessive daytime sleepiness in hypertensive patients. Given this potential implication of current major depressive disorder in the occurrence of excessive daytime sleepiness for hypertensive patients, it is therefore essential to achieve the complete remission of this psychiatric disorder to avoid negative consequences associated with this complaint in this particular subpopulation.
... Thus, when a person gets insufficient sleep, it negatively affects that person's behavior, cognition, mood, and other aspects of daily life. An irregular sleep pattern can negatively affect physical and mental health while increasing the risk of accidents, reducing productivity, and causing social/relational issues [12]. ...
This study aimed to determine the association between symptoms of depression and sleep duration in a representative sample of the Korean population. Using national cross-sectional data from the seventh Korea National Health and Nutrition Examination Surveys (KNHANES-VII), 5461 adults aged 18–49 years were analyzed using logistic regression models. The proportions of participants with total daily sleep durations (24 h) of <6 h, 6–8 h, and ≥9 h were 26.2%, 60.6%, and 13.3%, respectively. The proportions of individuals with symptoms of depression in the <6 h, 6–8 h, and ≥9 h sleep duration groups were 37.4%, 46.3%, and 16.3%, respectively. The odds ratios (ORs) were significantly higher in the <6 h and ≥9 h sleep groups than in the 6–8 h sleep group. There was a significant association between short (<6 h/day) and long (≥9 h/day) sleep duration and symptoms of depression among the general Korean population. In particular, our findings suggest that short sleep (<6 h/day) is more associated with symptoms of depression than long sleep (≥9 h/day).
Underlying the “ideal worker” image that pervades many organizational cultures is the assumption that working longer hours equates to higher performance, despite recovery research that suggests that long work hours might actually impair future work performance. In an effort to reconcile these differences in how long work hours are thought to relate to job performance, we develop and test a conceptual model in which daily boosts in same‐day performance associated with working longer hours could be offset by lower next‐day performance. More specifically, we examine if working a longer day than usual reduces sleep, which has the potential to diminish physical (i.e., physical energy) and psychological (i.e., resilience) resources the next morning, consequently impairing next‐day work performance. In a 5‐day experience sampling study of 67 employee–coworker dyads (276 days), using sleep data from a wearable device (i.e., Fitbit) in combination with daily self‐report surveys and coworker performance ratings, results indicated that daily work hours were positively related to same‐day work performance. Our results further indicated that work hours were negatively related to next‐day work performance through reduced sleep duration and morning resilience, but not through diminished physical energy. Together, our findings indicate that although employees may experience same‐day performance gains related to working long hours, they also may pay a price the following day, as longer workdays prevent employees from recovering overnight.
Study objectives:
This review aims to assess the association between socioeconomic status (SES) and sleep health in the general population and the mediating effects of lifestyle, mental and physical health in this relationship.
Methods:
Observational studies testing the independent association between objective or subjective SES indicators and behavioral/physiological or clinical sleep health variables in the general population were included. PubMed/MEDLINE was searched for reports published from January 1990 to December 2019. The direction of effect was used as the primary effect measure, testing the hypothesis that low SES is associated with poor sleep health outcomes. Results are presented in the form of direction effect plots and synthesized as binomial proportions.
Results:
Overall, 336 studies were identified. A high proportion of effects at the expected direction was noted for measures of sleep continuity (100% for sleep latency, 50-100% for awakenings, 66.7-100% for sleep efficiency), symptoms of disturbed sleep (75-94.1% for insomnia, 66.7-100% for sleep disordered breathing, 60-100% for hypersomnia), and general sleep satisfaction (62.5-100%), while the effect on sleep duration was inconsistent and depended on the specific SES variable (92.3% for subjective SES, 31.7% for employment status). Lifestyle habits, chronic illnesses, and psychological factors were identified as key mediators of the SES-sleep relationship.
Conclusions:
Unhealthy behaviors, increased stress levels, and limited access to healthcare in low SES individuals may explain the SES-sleep health gradient. However, the cross-sectional design of most studies and the high heterogeneity in employed measures of SES and sleep limit the quality of evidence. Further research is warranted due to important implications for health issues and policy changes.
The multiple sleep latency test (MSLT) is used in the assessment and diagnosis of disorders of excessive somnolence and to evaluate daytime sleepiness in relation to various therapeutic or experimental manipulations, such as administering drugs and altering the length of timing of nocturnal sleep. The repeated measurement of sleep latency across a day provides direct access to the diurnal fraction of the sleep/wake interaction, which is of fundamental concern to the sleep specialist. Objective laboratory documentation of the clinical symptoms of slepiness well as abnormal sleep structure has greatly facilitated the diagnosis of narcolepsy, in particular, and has also been useful to determine the severity of somnolence and therapeutic response in other disorders. At the current level of clinical experience, a diagnosis of narcolepsy or other disorders of excessive somnolence usually has lifelong consequences for the patients, for example, chronic chemotherapy with psychoactive compounds, legal proscription from driving, or surgery. It therefore is incumbent upon the clinical sleep specialist to achieve as much diagnostic precision as possible. The MSLT greatly enhances the accurate diagnosis of disorders of excessive somnolence.
The relationship between social and community ties and mortality was assessed using the 1965 Human Population Laboratory survey of a random sample of 6928 adults in Alameda County, California and a subsequent nine-year mortality follow-up. The findings show that people who lacked social and community ties were more likely to die in the follow-up period than those with more extensive contacts. The age-adjusted relative risks for those most Isolated when compared to those with the most social contacts were 2.3 for men and 2.8 for women. The association between social ties and mortality was found to be independent of self-reported physical health status at the time of the 1965 survey, year of death, socioeconomic status, and health practices such as smoking, alcoholic beverage consumption, obesity, physical activity, and utilization of preventive health services as well as a cumulative index of health practices.
To ascertain the prevalence of posttraumatic stress disorder (PTSD) and risk factors associated with it, we studied a random sample of 1007 young adults from a large health maintenance organization in the Detroit, Mich, area. The lifetime prevalence of exposure to traumatic events was 39.1%. The rate of PTSD in those who were exposed was 23.6%, yielding a lifetime prevalence in the sample of 9.2%. Persons with PTSD were at increased risk for other psychiatric disorders; PTSD had stronger associations with anxiety and affective disorders than with substance abuse or dependence. Risk factors for exposure to traumatic events included low education, male sex, early conduct problems, extraversion, and family history of psychiatric disorder or substance problems. Risk factors for PTSD following exposure included early separation from parents, neuroticism, preexisting anxiety or depression, and family history of anxiety. Life-style differences associated with differential exposure to situations that have a high risk for traumatic events and personal predispositions to the PTSD effects of traumatic events might be responsible for a substantial part of PTSD in this population.
• We examined the level of agreement between diagnoses derived from data gathered by lay interviewers using the Diagnostic Interview Schedule (DIS) in a general population survey (the Epidemiologic Catchment Area project) and both DIS and clinical diagnoses made by psychiatrists. Overall percent agreement between the lay DIS and the psychiatrists clinical impression ranged from 79% to 96%. The chancecorrected concordance was .60 or better for eight of the 11 diagnoses. Specificities were all 90% or better. Sensitivities were lower, but lay results showed a bias for only two diagnoses: major depression was significantly underdiagnosed and obsessive illness was overdiagnosed. We compared the present results with those of previous studies from clinical settings. We explored possible reasons for disagreement and discussed the implications of the findings for psychiatric epidemiologic research.
• We studied DSM-III diagnoses made by the lay Diagnostic Interview Schedule (DIS) method in relation to a standardized DSM-III diagnosis by psychiatrists in the two-stage Baltimore Epidemiologic Catchment Area mental morbidity survey. Generally, prevalence estimates based on the DIS one-month diagnoses were significantly different from those based on the psychiatric diagnoses. Subjects identified as cases by each method were often different subjects. Measured in terms of K, the chance-corrected degree of agreement between the DIS and psychiatrists' one-month diagnoses was moderate for DSM-III alcohol-use disorder (abuse and dependence combined), and lower for other mental disorder categories. The unreliability of either the DIS or psychiatric diagnoses is one potential explanation for the observed disagreements. Others include the following: (1) insufficient or inadequate information (on which to base a diagnosis); (2) recency of disorder; (3) incomplete criterion coverage; (4) overinclusive DIS questions; and (5) degree of reliance on subject symptom reports. Further study of the nature and sources of these discrepancies is underway. This work should produce a more complete understanding of obstacles to mental disorder case ascertainment by lay interview and clinical examination methods in the context of a field survey.
24 healthy men (aged 21–35 yrs) with no complaints of daytime sleepiness, no habitual napping, and polysomnographically verified normal nocturnal sleep extended their time in bed (TIB) to 10 hrs for 6 consecutive nights to assess the effects of sleep extension on daytime sleepiness and performance. 12 Ss had basal average daily sleep latencies of ≤6 min on the Multiple Sleep Latency Test (M. A. Carskadon et al; 1986) and 12 had latencies of ≥16 min before TIB was extended. The sleep extension improved daytime sleepiness differentially in the 2 groups. Sleepy Ss showed an immediate and uniform increase in alertness, while alert Ss did not show improvements until late in the extension. However, sleepy Ss never achieved the baseline level of sleepiness/alertness seen in the alert Ss. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Sleep and daytime sleepiness were evaluated in 10 young adult subjects to determine whether restricting nocturnal step by a constant amount produces cumulative impairment. Subjects were studied for 12 consecutive days, including 3 baseline days with a 10-hr time in bed, 7 days with sleep restricted to 5 hrs, and 2 recovery days. In 5 subjects, recovery included a 10-hr time in bed; in the remaining subject, recovery induced a 5-hr time in bed with a 1-hr daytime nap. Sleepiness was measured using two self-rating scales and the multiple sleep latency test. During sleep restriction, nocturnal stage 2 and REM sleep were reduced and slow wave sleep was unaffected. Stanford Sleepiness Scales showed an immediate increase in daytime sleepiness that reached a plateau after 4 days. An analog sleepiness rating scale showed increased sleepiness after 2 restricted nights and leveled off after the fourth restricted night. The multiple sleep latency tests showed no effect of sleep restriction until the second day, followed by a progressive increase in sleepiness that persisted through the seventh sleep restriction day. During the recovery period, daytime sleepiness returned to basal values on all three measures following one full night of sleep; with a daytime nap, no further cumulative effects of sleep restriction were seen.