SLEEP AND QUALITY OF WELL-BEING

SLEEP AND QUALITY OF WELL-BEING

Sleep and Quality of Well-Being Girardin Jean-Louis,1,2,3 Daniel F. Kripke,1 and Sonia Ancoli-Israel1 1Department

of Psychiatry, University of California San Diego, CA; 2Department of Psychology, Long Island University, NY; 3Department of Psychiatry, SUNY Downstate Medical Center, NY Background: It is commonly believed that sleep duration in the population has been declining gradually. Whereas sleep restriction in the laboratory induces sleepiness and mood disturbances, it is not certain whether a short sleep duration impairs the quality of everyday life. Methods: Using population-based data, we explored whether greater habitual sleep duration is a predictor of better health-related quality of life, measured by the Quality of Well-Being (QWB) scale. The relationships between QWB and several potential correlates were examined in a stepwise linear regression analysis. Results: Neither subjective nor actigraphic sleep duration were associated with QWB. Greater quality of well-being was associated with greater sleep satisfaction, younger age, less obesity, non-Hispanic White ethnicity, and greater experienced illumination. Conclusion: These data suggest that increasing sleep duration may not directly improve quality of life, despite evidence that curtailment of nocturnal sleep is associated with fatigue. Key words: Sleep, sleep restriction; quality of well-being; health status; actigraphy; ethnicity INTRODUCTION

health risk,5,6,9-14,17-23 Further, a recent report comparing questionnaire responses from the Minnesota Multiphasic Personality Inventory obtained in the 1930s and 1980 suggested increased fatigue among contemporary men.24 This is consistent with findings of the Omnibus Sleep in America Poll, showing that 57% of individuals surveyed reported that sleepiness interfered with their ability to drive, and of those, 23% admitted falling asleep at the wheel.5 We note on balance that negative effects of acute sleep restriction observed experimentally remain irreconcilable with findings that gradual sleep restriction may not impair physical health, personality, or performance.25,26 It has not been demonstrated that individuals can adapt to objective sleepiness, although it is argued that many become adapted to subjective sleepiness resulting from sleep restriction in the range of five to six hours.15,27 Despite the convergence of evidence, available polysomnographic, actigraphic, and survey studies all have limitations, which make the suspected decline in the population’s sleep duration somewhat uncertain. Moreover, during the decades when sleep durations may have declined, overall health has certainly improved, and the enormous preponderance of excess mortality is associated with sleep durations eight hours or longer, rather than sleep durations averaging 6.5 hours.1,28-30 This has been confirmed by more recent analyses of the American Cancer Society’s Cancer Prevention II study, in which adjusting for multiple forms of comorbidity demonstrated the risk is modest with habitual sleep as short as 4.5 hours.30 Balancing all considerations, it has not been demonstrated that the population as a whole should sleep more.

IT IS COMMONLY BELIEVED THAT SLEEP DURATION IN THE POPULATION HAS BEEN DECLINING GRADUALLY. FOUR DECADES AGO, ≥8 HOURS WAS the reported modal sleep duration.1,2 In 1974, an important nocturnal polysomnographic study showed that volunteers slept an average of seven hours at night, but time in bed may have been restricted.3 A decade later, the National Health Interview Survey found that middle-aged adults then reported sleeping seven to eight hours at night.4 According to the 1995 Gallup5 survey, the modal sleep duration had decreased to seven hours. In 1998, the “Sleep in America Poll” found that the average reported sleep duration was 6.57 hours.6 In a contemporary populationbased study of sleep patterns, actigraphic recordings have observed that adults ages 40—64 were sleeping only an average of 6.22 hours.7 A recent article in Sleep Medicine Alert argued that we may be sleeping 25% less than our forefathers 100 years ago.8 These apparent trends have alarmed observers concerned with risks of accidents and other adverse events, which might be associated with sleep loss.9-14 Experimental acute restriction of sleep times has been found to reduce daytime alertness and to disturb mood.15,16 From such evidence, increased sleepiness is decried as an important

Accepted for publication October 2000 Address correspondence to: Department of Psychology (H8A10), Long Island University, 1 University Plaza, Brooklyn, NY 11201. Tel: (718) 246-6477; Fax: (718) 246-6471; E-mail: [email protected], [email protected] Vol. 23, No. 8, 2000 DownloadedSLEEP, from https://academic.oup.com/sleep/article-abstract/23/8/1/2753251 by guest on 14 July 2018

1

Sleep and Quality of Well-Being—Jean-Louis et al

description of sampling procedures.7,43-45 From the initial sample, a total of 273 volunteers were selected who had provided complete data on sociodemography, subjective sleep, and actigraphic sleep recordings. An investigator interviewed volunteers about their subjective sleep duration, difficulty falling asleep at night, difficulty waking up in the morning, sleep satisfaction rated as 1 (very satisfied) to 5 (very troubled), health status rated as 1(excellent) to 5 (poor), consumption of caffeine and alcohol, and smoking status. The investigator also recorded gender, age, ethnicity, education, and Body Mass Index (kg/m2). Volunteers were administered the Quality of WellBeing (QWB) scale. The QWB is a component of the General Health Policy Model that has been developed on a normative sample and was cross-validated, showing significant accuracy (r2 = 0.94).46-48 The quality of well-being component takes into account behavioral scales for mobility, physical activity, social activity, and symptoms; preference-weighted measures of symptoms and functioning are combined to provide a numerical point-in-time expression of well-being; higher scores indicate greater quality of well-being. The QWB correlates well with physiological measures including FEV: r = 0.55, FVC: r = 0.34, and VO2max: r = 0.58.49,50 Studies have also shown good correspondence of the QWB to psychiatric scales such as the BDI (r = -.49), the HAM-D (r = -.57), and POMS subscales (r = -.16 to r = -.35).48,51 Additionally, the QWB has been used in several clinical groups,48,52-54 and concords with medical, neurological, neuropsychological, and brain imaging evidence of impairment.48 In addition, volunteers were asked to complete the Center for Epidemiologic Studies-Depression Scale (CESD). The CES-D is a 20-item survey instrument that assesses the presence and severity of depressive symptoms occurring over the past week; higher scores indicate greater depressive symptoms.55-57 Studies have shown that the CES-D has satisfactory internal consistency (Cronbach a = 0.80-0.90),58 has good sensitivity (92%) and specificity (87%),59 and correlates with measures of health status and affect.59-61 Volunteers’ sleep was monitored at home for three days by wrist actigraphy (see below), to obtain 24-hour recordings of sleep and wakefulness and environmental illumination exposure. Illumination recordings are valuable in recognizing home bedtimes.

However, considering the effects of acute, extreme sleep loss on driving and other performance measures, individuals exhibiting symptoms of acute sleep loss should be encouraged to sleep more. Whereas acute sleep curtailment in the laboratory induces fatigue and mood disturbances,15,16 and depressed and insomniac patients complain bitterly of sleep loss, there is also excellent evidence that sleep deprivation is antidepressant.31-34 Sleep restriction is a treatment of insomnia.35 Reconciling different viewpoints on sleep duration is a fundamental challenge for investigators interested in the impact of sleep loss on public health and safety.14,21,36 The large body of evidence on acute effects of sleep restriction (negative or positive) leave uncertain the long-term effects of short sleep on overall morbidity, as reflected in health-related quality of life. There are no population-based data suggesting greater wellness or better performance among those sleeping longer than the current population median, and sleep extension studies have not shown convincing and desirable longterm benefits. A two-hour sleep extension study revealed that healthy individuals were able to sleep approximately one hour more than their habitual sleep time.37 However, this finding did not incontrovertibly expose an underlying chronic sleep loss, but might have indicated an inherent ability to forego optional sleep to fulfill social obligations without immediate ill effect.27 Conversely, the investigators observed that sleep extension impaired the ability to fall asleep at night, caused a deterioration of daytime wakefulness, and did not improve self-rated mood or alertness.37 Another experimental study suggested that sleep extension can produce a gradual reduction in nocturnal sleep efficiency.38 A case for increasing population sleep durations would be bolstered if, in addition to small increases in vigilance that accompany sleep extension,15,37 quality of life could be demonstrably improved. It would appear that the benefits of sleep extension may be observable only among individuals who are characterized by chronic sleep loss. Generally, self-perceived sleep problems have been associated with poorer health-related quality of life,39,40 but several reports have suggested that self-rated sleep quality, rather than duration, was the correlate of health status or well-being.23,41,42 To expand knowledge on the implications of short sleep, we used population-based data to examine whether greater sleep duration is associated with greater health-related quality of life.

Instrumentation

METHODS

The Actillume (Ambulatory Monitoring, Inc., Ardsley, NY) is a monitoring device worn on the wrist, housing a photometer and a linear accelerometer. Actillumes were initialized to record activity every minute. Wrist-activity data were analyzed with ACTION3 (Ambulatory Monitoring, Inc., Ardsley, NY), applying a sleep-scoring

Participants and Procedures Using random telephone dialing, a representative sample of San Diego residents (age range: 40—64 years) were recruited for home sleep assessment. Portions of the data have been reported elsewhere, together with a detailed Vol. 23, No. 8, 2000 DownloadedSLEEP, from https://academic.oup.com/sleep/article-abstract/23/8/1/2753251 by guest on 14 July 2018

2


Table 1 Demographics of San Diego Adults (Ages: 40-64) by Race/Ethnicity Variable

White (n=203)

Minority (n=70)

Total

Age (Mean±SD)

51 ± 7

51 ± 6

51 ± 7

Education (Mean±SD)

15 ± 2

12 ± 4

14 ± 3

Body Mass Index (Mean±SD)

26 ± 5

29 ± 6

27 ± 5

34

13

29

Very Good (%)

45

33

43

Good (%)

15

25

17

Fair (%)

4

22

8

Poor (%)

2

7

3

Reported Health Status: Excellent (%)

algorithm that has been systematically tested in our laboratory on women ages 50—77 years old. That study indicated an 89% agreement between actigraphic and polysomnographic sleep estimates and a corresponding correlation coefficient of 0.90 (p<0.0001), using 24-hour recordings.62 Using ACTION3, other reports have revealed agreement rates of 0.82% and of 81%63,64 and a correlation coefficient of 0.91,65 comparing actigraphic and polysomnographic estimates. Actigraphic measures considered were nocturnal sleep duration, sleep onset latency, and sleep efficiency. The daily mean (mesor) and phase timing of sleep, environmental illumination exposure, and wrist activity were estimated with 24-hour cosine fitting.7

RESULTS Actillume recordings were seasonally balanced (25% in spring, 25% in summer, 23% in autumn, and 27% in winter). Volunteers included 144 women and 129 men, of whom 203 were non-Hispanic White and 70 were members of minority groups. Detailed information on these volunteers has been presented previously.44 Table 1 summarizes the demographics of the population studied. Of all volunteers with complete data, 18% reported using hormones (e.g., estrogens and birth control pills), 9% used hypnotics, stimulants, or tranquilizers, and 4% used antidepressants to aid sleep. Eighty percent of the volunteers were satisfied with their sleep, whereas 20% reported some trouble sleeping. Reported sleep satisfaction was correlated with reported habitual sleep time (r = -0.28, p<0.001), but was not associated with actigraphic sleep duration or efficiency. Self-reported and actigraphic sleep durations showed a moderate correlation (r = 0.35, p<0.001). Table 2 shows the five variables retained in the multiple regression model, which together accounted for 18% of the variance in QWB (F(5, 222) = 9.09, p<0.0001). Greater quality of well-being was associated with greater sleep satisfaction, younger age, less obesity, non-Hispanic White ethnicity, and greater experienced illumination. Although sleep satisfaction was the most significant correlate of QWB, neither subjective nor actigraphic sleep duration were associated with QWB. We also observed that QWB did not have a U-shaped relationship with sleep duration (subjective or objective). Descriptive statistics for the Actillume variables entered in the regression model are presented in Table 3. Given the disparity in self-perceived health status for individuals of different ethnicity (see Table 1), we further assessed the relationship between sleep satisfaction and QWB by controlling for ethnicity, finding a significant partial correlation (r = -0.30, p<0.001). This relationship remained significant even after further control for age, gender, and Body Mass Index (r = -0.23, p<0.001).

Statistical Analysis The relationships between QWB and several potential correlates were examined in a stepwise linear regression analysis using 21 independent variables from three domains. First, self-reported nocturnal sleep duration, sleep satisfaction, difficulty falling asleep at night, difficulty waking up in the morning, caffeine consumption, alcohol consumption, and smoking status were entered in the model. These were followed by objectively derived measures: Body Mass Index, nocturnal sleep duration, sleep onset latency, sleep efficiency, 24-hour sleep mean and timing, mean and timing of daily illumination, and mean and timing of daily wrist activity. Also entered in the model were demographic variables including age, gender, ethnicity, and education. Previous research has examined the association between QWB and demographic factors and between quality of life measures and self-reported sleep quality or quantity. In the present regression model, we explored the contribution of those variables as well as that of objective sleep parameters to verify previous observations. Furthermore, we assessed the relative importance of timing of sleep, of illumination, and of wrist activity, as they may be important factors in circadian synchronization. Vol. 23, No. 8, 2000 DownloadedSLEEP, from https://academic.oup.com/sleep/article-abstract/23/8/1/2753251 by guest on 14 July 2018

3


Table 2

Stepwise Regression of Factors on Quality of Well-Being Factor

Stand. Beta

Sleep Satisfaction

-.206

Std. Error 9.40

t

p

-3.23

.001

Age

-.185

.92

-3.00

.003

Body Mass Index

-.172

1.25

-2.67

.008

Non-Hispanic White Ethnicity

-.184

16.76

-2.92

.004

.134

20.66

2.17

.031

Mean Daily Illumination

Table 3 Variables Entered in Regression Model Variable

Mean

Std. Dev.

Self-report Sleep Duration (min)

415

66

Actigraphic Sleep Duration (min)

373

64

Actigraphic Sleep Onset Latency (min)

10

5

Actigraphic Sleep Efficiency (%)

82

10

24-Hour Sleep (%)

29

6

24-Hour Light Exposure (log[lux])

.99

.32

24-Hour Wrist Activity

17

9

2:44

1.32

Acrophase of Light Exposure

12:57

1.58

Acrophase of Wrist Activity

13:43

1.79

Acrophase of Sleep

tional studies have found significant associations between greater sleep duration and poorer self-perceived health status and sleep-related complaints.40 A similar observation was made in a study of independently living 50—65 yearold individuals.66 According to that study, greater rather than shorter sleep durations were associated with greater reported snoring, and higher levels of reported snoring and daytime sleepiness, rather than habitual sleep durations, were associated with measures of disease and lower psychosocial function. Be that as it may, avoiding acute sleep loss is a prudent practice for individuals at high risks for adverse events, as apparent among truck drivers, nightshift workers, and students.10,12,14,21,67-69 We note that there is no evidence suggesing that increasing sleep time of sleepdeprived individuals will necessarily engender negative health consequences, nor are there data indicating it will lower their quality of life; we observed that sleep duration was not a predictor of QWB. Our study shows that self-rated sleep satisfaction was correlated with healthy life, although sleep satisfaction accounted for a small percentage of the variance in QWB. Despite the finding that actigraphic sleep duration (6.22 hours) in our sample is considerably less than self-reported sleep durations four decades ago, in accordance with representative data from a Canadian research group,70 80% of volunteers reported they were satisfied with their sleep, and 89% indicated good to excellent self-perceived health sta-

Since the scores obtained from the CES-D were expected to correlate with QWB scores, the CES-D variable was not entered in the regression model. A separate analysis revealed that the CES-D was correlated with QWB (rs = 0.25, p<0.001), self-rated sleep satisfaction (rs = 0.39, p<0.001), and habitual sleep time (rs = -0.14, p<0.05). DISCUSSION The optimal sleep duration needed to meet the challenges of everyday life or to foster greater quality of life has not been established. Investigating relationships between habitual sleep duration and quality of well-being in the natural setting is an important step in determining whether increasing contemporary sleep durations would likely confer significant personal and social benefits. The population-based data we analyzed yielded no evidence that greater sleep duration is associated with greater healthrelated quality of life. Neither self-reported nor actigraphic sleep duration were associated with Quality of WellBeing. This might explain why the gains of extended sleep are not coveted to the detriment of other life pursuits. That the population as a whole should sleep more is not supported by our data. Moreover, evidence from the Cancer Prevention studies cautions against broad recommendations for increasing sleep, as more excess mortality was associated with sleeping eight hours or more than with sleeping less than seven hours.1,30 In addition, observaVol. 23, No. 8, 2000 DownloadedSLEEP, from https://academic.oup.com/sleep/article-abstract/23/8/1/2753251 by guest on 14 July 2018

4


tus. Findings of our study are consistent with data of reports discussing the relationships between sleep and general health status.23,42 A cross-sectional study (25—65 years-old) suggested that reported sleep quality was a correlate of measures of health status and well-being.23 And, among college students subjective sleep quality, but not quantity, was a correlate of health status and well being.42 Whereas sleep satisfaction was associated with self-perceived sleep time, it did not correlate with actigraphic sleep duration. This finding might reflect a tendency to view one’s sleep as satisfactory if perceived of a desired quantity, even if not verified objectively. It is fairly well documented that subjective reports of sleep time are often inaccurate71-73 and may be biased by depressed mood.74 Interestingly, sleep satisfaction was neither related to actigraphic sleep efficiency. This offers a plausible explanation for the apparent discrepancy. Sleep satisfaction, as measured in our study, does not connote sleep efficiency construed as an index of sleep quality; actigraphic sleep efficiency was not predictive of QWB. Rather, sleep satisfaction might be a proxy for depression, as we observed it correlated both with QWB and CES-D, which inherently measure depressive symptoms. This is consistent with the observation that self-perceived sleep quality was associated not only with health status and well being but also with mood measures.42 It is known that individuals who exhibit depressive symptoms often experience difficulty sleeping.40,75-77 The noted relations of Quality of Well-Being to age, Body Mass Index, and ethnicity support previous correlational findings.52,78 The finding that greater Quality of Well-Being was associated with greater illumination exposure is consistent with experimental data that bright light improves function,79-81 although causal inferences cannot be drawn. This finding, along with observed associations between experienced illumination and mood symptoms,43,45 suggests the importance of adequate environmental illumination. Also important is the finding that Quality of Well-Being was not correlated with the acrophase timings of sleep, of illumination exposure, and of wrist activity. This suggests that variability in these timings may not impair the quality of life, although extreme changes in circadian rhythm timings, as experienced by shift-workers and air travelers, are often accompanied by disturbances in sleep, mood, and performance.82-86 Definitive understanding of the consequences of a possible population decline in sleep duration awaits the determination of the sleep amount producing optimal daytime functioning, the most satisfying quality of life, and the best survival. The findings of this study support a sensible approach to improving quality of life. Rather than recommending that the population sleep more, public health educators might advocate healthy living, recommending the use of proven methods to improve sleep quality (e.g., sleep Vol. 23, No. 8, 2000 DownloadedSLEEP, from https://academic.oup.com/sleep/article-abstract/23/8/1/2753251 by guest on 14 July 2018

hygiene techniques and greater illumination). It is not likely that increasing sleep duration per se will enhance quality of life. ACKNOWLEDGMENTS This research was supported by HL55983, AG123G4, AG02711, and AG15763. We thank Mary Anne Mowen, William Mason, Daniel Mullaney, Joseph Assmus, Melville Klauber, Katherine Rex, Raul Sepulveda, and Deborah Wingard for their assistance in this study. REFERENCES 1. Kripke DF, Simons RN, Garfinkel L, Hammond EC. Short and long sleep and sleeping pills. Is increased mortality associated? Arch Gen Psychiatry 1979;361:103-116. 2. Gallup. The Gallup Study of Sleeping Habits. The Gallup Organization 1979;1-60. 3. Williams RL, Karacan I, Hursch CJ. Electroencephalography (EEG) of human sleep: clinical applications. New York: John Wiley and Sons; 1974; 26-68p. 4. Schoenborn CA. Health habits of U.S. adults, 1985: the “Alameda 7” revisited. Public Health Rep 1986;1016:571-580. 5. Gallup. Sleep In america. The Gallup Organization 1995;1-78. 6. Gallup. Omnibus Sleep in america poll. The Gallup Organization 1998;1-70. 7. Jean-Louis G, Kripke DF, Ancoli-Israel S, Klauber M, Sepulveda RS. Sleep duration, illumination, and activity profiles in a representative sample: effects of gender and ethnicity. Biol Psychiatry 2000;4710:921-927. 8. Mahowald M. Assessing excessive daytimne sleepiness: a complaint to be taken seriously. Sleep Medecine Alert 1999;43:1-4. 9. Mitler MM, Carskadon MA, Czeisler CA, Dement WC, Dinges DF, Graeber RC. Catastrophes, sleep, and public policy: consensus report. Sleep 1988;100-109. 10. Mitler MM, Miller JC, Lipsitz JJ, Walsh JK, Wylie CD. The sleep of long-haul truck drivers. N Engl J Med 1997;33711:755-761. 11. Mullaney DJ, Kripke DF, Fleck PA, Johnson LC. Sleep loss and nap effects on sustained continuous performance. Psychophysiology 1983 Nov 1983;20:643-651. 12. Pack AI, Pack AM, Rodgman E, Cucchiara A, Dinges DF, Schwab CW. Characteristics of crashes attributed to the driver having fallen asleep. Accid Anal Prev 1995;276:769-775. 13. McCartt AT, Ribner SA, Pack AI, Hammer MC. The scope and nature of the drowsy driving problem in New York state. Accid Anal Prev 1996;284:511-517. 14. Summala H, Mikkola T. Fatal accidents among car and truck drivers: effects of fatigue, age, and alcohol consumption. Hum Factors 1994;362:315-326. 15. Dinges DF, Pack F, Williams K, Gillen KA, Powell JW, Ott GE, Aptowicz C, Pack AI. Cumulative sleepiness, mood disturbance, and psychomotor vigilance performance decrements during a week of sleep restricted to 4-5 hours per night. Sleep 1997;204:267-267. 16. Bonnet MH, Arand DL. We are chronically sleep deprived. Sleep 1995;1810:908-911. 17. Horne JA, Reyner LA. Sleep related vehicle accidents. BMJ 1995;3106979:565-567. 18. Reyner LA, Horne JA. Falling asleep whilst driving: are drivers aware of prior sleepiness? Int J Legal Med 1998;1113:120-123. 19. Marcus CL, Loughlin GM. Effect of sleep deprivation on driving safety in housestaff. Sleep 1996;1910:763-766. 20. Carskadon MA. Patterns of sleep and sleepiness in adolescents. Pediatrician 1990;171:5-12. 5


21. Lyznicki JM, Doege TC, Davis RM, Williams MA. Sleepiness, driving, and motor vehicle crashes. Council on Scientific Affairs, American Medical Association. JAMA 1998;27923:1908-1913. 22. Webb WB. The cost of sleep-related accidents: a reanalysis. Sleep 1995;184:276-280. 23. Briones B, Adams N, Strauss M, Rosenberg C, Whalen C, Carskadon M, Roebuck T, Winters M, Redline S. Relationship between sleepiness and general health status. Sleep 1996;197:583-588. 24. Bliwise DL. Historical change in the report of daytime fatigue. Sleep 1996;196:462-464. 25. Friedmann J, Globus G, Huntley A, Naitoh P, Johnson L. Performance and mood during and after gradual sleep reduction. Psychophysiology 1977;14:245-250. 26. Binks PG, Waters WF, Hurry M. Short-term total sleep deprivation does not selectively impair higher cortical functioning. Sleep 1999;22:328-334. 27. Horne J. Why we sleep: the functions of sleep in humans and other mammals. New York: Oxford University Press; 1988. 28. Qureshi AI, Giles WH, Croft JB, Bliwise DL. Habitual sleep patterns and risk for stroke and coronary heart disease: a 10-year follow-up from NHANES I. Neurology 1997;484:904-911. 29. Wingard DL, Berkman LF. Mortality risk associated with sleeping patterns among adults. Sleep 1983;62:102-107. 30. Kripke DF, Assmus JD. A duration >= 8 hours for sleep is not safer! Sleep Research Online 1999;2:144 31. Gillin JC, Kripke DF, Janowsky DS, Risch SC. Effects of brief naps on mood and sleep in sleep-deprived depressed patients. J Psychosoc Nurs Ment Health Serv 1992;3011:15-19. 32. Parry BL, Cover H, Mostofi N, LeVeau B, Sependa PA, Resnick A, Gillin JC. Early versus late partial sleep deprivation in patients with premenstrual dysphoric disorder and normal comparison subjects. Sleep 1995;184:288-302. 33. Sack DA, Duncan W, Rosenthal NE, Mendelson WE, Wehr TA. The timing and duration of sleep in partial sleep deprivation therapy of depression. Am J Psychiatry 1985;1422:163-170. 34. Wehr TA, Sack DA, Rosenthal NE. Antidepressant effects of sleep deprivation and phototherapy. J Neurol Neurosurg Psychiatry 1995;583:379 35. Spielman AJ, Saskin P, Thorpy MJ. Treatment of chronic insomnia by restriction of time in bed. Sleep 1987;101:45-56. 36. Rechtschaffen A. Current perspectives on the function of sleep. Perspect Biol Med 1998;413:359-390. 37. Harrison Y, Horne JA. Long-term extension to sleep—are we really chronically sleep deprived? Psychophysiology 1996;331:22-30. 38. Roehrs T, Shore E, Papineau K, Rosenthal L, Roth T. A two-week sleep extension in sleepy normals. Sleep 1996;197:576-582. 39. Kuppermann M, Lubeck DP, Mazonson PD, Patrick DL, Stewart AL, Buesching DP, Fifer SK. Sleep problems and their correlates in a working population. J Gen Intern Med 1995;101:25-32. 40. Habte-Gabr E, Wallace RB, Colsher PL, Hulbert JR, White LR, Smith IM. Sleep patterns in rural elders: demographic, health, and psychobehavioral correlates. J Clin Epidemiol 1991;441:5-13. 41. Hicks RA, Mistry R, Lucero K, Lee L, Pellegrini R. The sleep duration and sleep satisfaction of college students: striking changes over the last decade (1978-1988). Percept Mot Skills 1989;683 Pt 1:806 42. Pilcher JJ, Ginter DR, Sadowsky B. Sleep quality versus sleep quantity: relationships between sleep and measures of health, well-being and sleepiness in college students. J Psychosom Res 1997;426:583596. 43. Espiritu RC, Kripke DF, Ancoli-Israel S, Mowen MA, Mason WJ, Fell RL, Klauber MR, Kaplan OJ. Low illumination experienced by San Diego adults: association with atypical depressive symptoms. Biol Psychiatry 1994;1063:780-786. 44. Kripke DF, Ancoli-Israel S, Klauber MR, Wingard DL, Mason WJ, Mullaney DJ. Prevalence of sleep disordered breathing in ages 40-64 years: a population-based survey. Sleep 1997;201:65-76. Vol. 23, No. 8, 2000 DownloadedSLEEP, from https://academic.oup.com/sleep/article-abstract/23/8/1/2753251 by guest on 14 July 2018

45. Kripke DF, Juarez S, Cole RJ, Ancoli-Israel S, Wisbey JA, Klauber MR, Mason WJ, Gruen W. Adult illumination exposures and some correlations with symptoms. In: T Hiroshige and K honma, eds. Evolution of circadian clock, Sapporo, Japan: Hokkaido University Press, 1994;349-360. 46. Kaplan RM, Anderson JP. A general health policy model: update and applications Health outcome models for policy analysis. Health Serv Res 1988;232:203-235. 47. Kaplan RM, Bush JW, Berry CJ. Health status: types of validity and the index of well-being. Health Serv Res 1976;11:478-507. 48. Kaplan RM, Anderson JP, Patterson TL, McCutchan JA, Weinrich JD, Heaton RK, Atkinson JH, Thal L, Chandler J, Grant I. Validity of the quality of well-being scale for persons with human immunodeficiency virus infection. HNRC Group. HIV Neurobehavioral Research Center. Psychosom Med 1995;572:138-147. 49. Kaplan RM, Anderson JP, Wu AW, Mathews WC, Kozin F, Orenstein D. The quality of well-being scale. Applications in AIDS, cystic fibrosis, and arthritis. Med Care 1989;273 Suppl:S27-S43. 50. Kaplan RM, Atkins CJ, Timms R. Validity of a quality of wellbeing scale as an outcome measure in chronic obstructive pulmonary disease. J Chronic Dis 1984;372:85-95. 51. Pyne JM, Patterson TL, Kaplan RM, Ho S, Gillin JC, Golshan S, Grant I. Preliminary longitudinal assessment of quality of life in patients with major depression. Psychopharmacol Bull 1997;331:23-29. 52. Orenstein DM, Nixon PA, Ross EA, Kaplan RM. The quality of well-being in cystic fibrosis. Chest 1989;952:344-347. 53. Kaplan RM. Quality of life assessment for cost/utility studies in cancer. Cancer Treat Rev 1993;19 Suppl A:85-96. 54. Kaplan RM, Coons SJ, Anderson JP. Quality of life and policy analysis in arthritis. Arthritis Care Res 1992;53:173-183. 55. Radloff.L.S. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Measure 1977;1:385401. 56. Papassotiropoulos A, Heun R. Detection of subthreshold depression and subthreshold anxiety in the elderly. Int J Geriatr Psychiatry 1999;148:643-650. 57. Myers JK, Weissman MM. Use of a self-report symptom scale to detect depression in a community sample. Am J Psychiatry 1980;1379:1081-1084. 58. Beekman AT, van Limbeek J, Deeg DJ, Wouters L, van Tilburg W. A screening tool for depression in the elderly in the general population: the usefulness of center for epidemiological studies depression scale (CES-D). Tijdschr Gerontol Geriatr 1994;253:95-103. 59. Lyness JM, Noel TK, Cox C, King DA, Conwell Y, Caine ED. Screening for depression in elderly primary care patients. A comparison of the center for epidemiologic studies-depression scale and the Geriatric Depression Scale. Arch Intern Med 1997;1574:449-454. 60. Shinar D, Gross CR, Price TR, Banko M, Bolduc PL, Robinson RG. Screening for depression in stroke patients: the reliability and validity of the center for epidemiologic studies depression scale. Stroke 1986;172:241-245. 61. Zich JM, Attkisson CC, Greenfield TK. Screening for depression in primary care clinics: the CES-D and the BDI. Int J Psychiatry Med 1990;203:259-277. 62. Jean-Louis G, Kripke DF, Cole RJ, Assmus JD, Langer RD. Sleep detection with an accelerometer actigraph: comparisons with polysomnography. [In Press] Physiol Behav 2000. 63. Blood ML, Sack RL, Percy DC, Pen JC. A comparison of sleep detection by wrist actigraphy, behavioral response, and polysomnography. Sleep 1997;206:388-395. 64. Matsumoto M, Miyagishi T, Sack RL, Hughes RJ, Blood ML, Lewy AJ. Evaluation of the actillume wrist actigraphy monitor in the detection. Psychiatry Clin Neurosci 1998;522:160-161. 65. Ancoli-Israel S, Clopton P, Klauber MR, Fell R, Mason W. Use of wrist activity for monitoring sleep/wake in demented nursing-home patients. Sleep 1997 Jan 1997;20:24-27. 6


66. Bliwise DL, King AC, Harris RB. Habitual sleep durations and health in a 50-65 year old population. J Clin Epidemiol 1994;471:3541. 67. Jean-Louis G, von Gizycki H, Zizi F, Nunes J. Mood states and sleepiness in college students: influences of age, sex, habitual sleep, and substance use. Percept Mot Skills 1998;872:507-512. 68. Wolfson AR, Carskadon MA. Sleep schedules and daytime functioning in adolescents. Child Dev 1998;694:875-887. 69. Hicks RA, Pellegrini RJ. The changing sleep habits of college students. Percept Mot Skills 1991;723Pt 2:1106. 70. Ohayon MM, Caulet M, Guilleminault C. How a general population perceives its sleep and how this relates to the complaint of insomnia. Sleep 1997;209:715-723. 71. Carskadon MA, Dement WC, Mitler MM, Guilleminault C, Zarcone VP, Spiegel R. Self-reports versus sleep laboratory findings in 122 drug-free subjects. Am J Psychiatry 1976;13312:1382-1388. 72. Hauri PJ, Olmstead EM. Reverse first night effect in insomnia. Sleep 1989;122:97-105. 73. Monroe LJ. Psychological and physiological differences between good and poor sleepers. J Abnorm Psychol 1967;723:255-264. 74. Bliwise DL, Friedman L, Yesavage JA. Depression as a confounding variable in the estimation of habitual sleep time. Psychiatry Res 1993;483:277-292. 75. Kupfer DJ, Foster FG, Detre TP. Sleep continuity changes in depression. Dis Nerv Syst 1973;344:192-195. 76. Partonen T. A mechanism of action underlying the antidepressant effect of light. Chronobiologia 1984;111:21-27. 77. Reynolds CF, Kupfer DJ. Sleep research in affective illness: state of the art circa 1987. Sleep 1987;103:199-215. 78. Kaplan RM, Alcaraz JE, Anderson JP, Weisman M. Quality-adjusted life years lost to arthritis: effects of gender, race,and social class. Arthritis Care Res 1996;96:473-482. 79. Saletu B, Dietzel M, Lesch OM, Musalek M, Walter H, Grunberger J. Effect of biologically active light and partial sleep deprivation on sleep, awakening and circadian rhythms in normals. Eur Neurol 1986;25 Suppl 2:82-92. 80. Dietzel M, Saletu B, Lesch OM, Sieghart W, Schjerve M. Light treatment in depressive illness. Polysomnographic, psychometric and neuroendocrinological findings. Eur Neurol 1986;25 (Suppl 2):93-103. 81. Partonen T, Leppamaki S, Hurme J, Lonnqvist J. Randomized trial of physical exercise alone or combined with bright light on mood and health-related quality of life. Psychol Med 1998;286:1359-1364. 82. Tepas DI, Carvalhais AB. Sleep patterns of shiftworkers. Am J Psychiatry 1995;1523:404-412. 83. Cole RJ, Loving RT, Kripke DF. Psychiatric aspects of shiftwork. Prog Clin Biol Res 1990;341B:35-43. 84. Eastman CI, Boulos Z, Terman M, Campbell SS, Dijk DJ, Lewy AJ. Light treatment for sleep disorders: consensus report. VI. Shift work. J Biol Rhythms 1995;102:167-176. 85. Arendt J, Skene DJ, Middleton B, Lockley SW, Deacon S. Efficacy of melatonin treatment in jet lag, shift work, and blindness. J Biol Rhythms 1997;126:604-617. 86. Deacon S, Arendt J. Adapting to phase shifts, I. An experimental model for jet lag and shift work. Physiol Behav 1996;594-5:665-673.

Vol. 23, No. 8, 2000 DownloadedSLEEP, from https://academic.oup.com/sleep/article-abstract/23/8/1/2753251 by guest on 14 July 2018

7


SLEEP AND QUALITY OF WELL-BEING

Recommend Documents