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Original Contribution
Daytime Napping and the Risk of All-Cause and Cause-Specific Mortality:
A 13-Year Follow-up of a British Population
Yue Leng*, Nick W. J. Wainwright, Francesco P. Cappuccio, Paul G. Surtees, Shabina Hayat,
Robert Luben, Carol Brayne, and Kay-Tee Khaw
* Correspondence to Yue Leng, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge,
Initially submitted November 22, 2013; accepted for publication February 10, 2014.
Epidemiologic studies have reported conflicting results on the relationship between daytime napping and mortal-
ity risk, and there are few data on the potential association in the British population. We investigated the associations
between daytime napping and all-cause or cause-specific mortality in the European Prospective Investigation Into
Cancer-Norfolk study, a British population-based cohort study. Among the 16,374 men and women who answered
questions on napping habits between 1998 and 2000, a total of 3,251 died during the 13-year follow-up. Daytime
napping was associated with an increased risk of all-cause mortality (for napping less than 1 hour per day on av-
erage, hazard ratio = 1.14, 95% confidence interval: 1.02, 1.27; for napping 1 hour or longer per day on average,
hazard ratio = 1.32, 95% confidence interval: 1.04, 1.68), independent of age, sex, social class, educational level,
marital status, employment status, body mass index, physical activity level, smoking status, alcohol intake, depres-
sion, self-reported general health, use of hypnotic drugs or other medications, time spent in bed at night, and pres-
ence of preexisting health conditions. This association was more pronounced for death from respiratory diseases
(for napping less than 1 hour, hazard ratio = 1.40, 95% confidence interval: 0.95, 2.05; for napping 1 hour or more,
hazard ratio = 2.56, 95% confidence interval: 1.34, 4.86) and in individuals 65 years of age or younger. Excessive
daytime napping might be a useful marker of underlying health risk, particularly of respiratory problems, especially
among those 65 years of age or younger. Further research is required to clarify the nature of the observed
association.
aging; mortality; napping; respiratory; siesta; sleep; survival analysis
Abbreviations: BMI, body mass index; CI, confidence interval; COPD, chronic obstructive pulmonary disease; CVD, cardiovascular
diseases; EPIC, European Prospective Investigation Into Cancer; HR, hazard ratio; ICD, International Classification of Diseases;
MDD, major depressive disorder; OSA, obstructive sleep apnea.
In recent years, there has been growing evidence of a rela-
tionship between habitual sleep and the risk of mortality from
all-causes and cardiovascular diseases (CVDs) (1–3). Most
of these studies focused on nighttime sleep duration (4, 5);
the implications of daytime napping are poorly understood.
A long-established practice in Mediterranean areas, daytime
napping, namely siesta, is often linked with good health
through a postulated “stress relief” mechanism (6). However,
daytime sleepiness, often characterized by daytime napping,
has been suggested as an early sign or risk indicator of a range
of health problems (7–9). To date, the association between
daytime napping and mortality risk is uncertain.
Most previous studies have come from Mediterranean
countries (10–13), in which the incidence of and rate of
death from CVD tend to be low (6). Several prospective co-
hort studies from Israel showed that an increased mortality
rate was associated with siesta among older people (10,
11), whereas 1 study from Greece suggested that the siesta
is protective against heart-related deaths, especially in work-
ing men (12). In addition, conflicting United States–based
American Journal of Epidemiology © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited
DOI: 10.1093/aje/kwu
American Journal of Epidemiology Advance Access published March 30, 2014
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research has found an increased risk of death associated with daytime napping in both men only (14) and women only (15). In both studies, only naps of long durations were found to be significant. A Japanese study suggested that daytime napping was associated with increased risks of all-cause and CVD mortality, but this association was largely explained by co- morbid conditions (16). Meanwhile, there is limited evidence from the British population. Although daytime napping has not been a tradition among British adults, the prevalence of napping is likely to increase with the rapidly aging population (17, 18), and it is therefore important to understand the health associations of daytime napping among the British. Epidemiologic evidence of` the association between day- time napping and mortality is inconsistent and dependent on cultural, environmental, and demographic factors (19). It re- mains unclear whether napping is beneficial or a risk factor for or marker of ill health. We therefore examined the associa- tion between daytime napping and all-cause and cause-specific mortality in a middle- to older-aged British population.
METHODS
Participants and measures
Data were drawn from the European Prospective Investiga- tion Into Cancer (EPIC)-Norfolk prospective cohort study. The design and study methods of EPIC-Norfolk have been described previously (20, 21). Briefly, 25,639 men and women aged 40–79 years were recruited using general prac- tice age-sex registers from Norfolk, United Kingdom, and at- tended a baseline health check during 1993–1997. These participants were then followed up for 2 further health checks from 1996 to 2000 and from 2006 to 2011. In between these health examinations, participants were sent questionnaires for completion and return by post. The Norwich District Eth- ics Committee approved the study, and all participants gave signed informed consent. During 1998–2000, a total of 16,374 participants com- pleted the following question in the health questionnaire: “Do you normally take a nap during the day?” If they an- swered in the affirmative, they were asked to categorize the duration of their nap (<1 hour or ≥1 hour). Napping habits were thereby summarized as: no napping, napping less than 1 hour, and napping 1 hour or more per day. Covariates measured closer in time to the measurement of napping were chosen and included those measured at base- line or at the time of the second health check (1998–2000). Covariates measured at baseline were social class ( profes- sionals, managerial and technical occupations, skilled work- ers subdivided into nonmanual and manual, partly skilled workers, or unskilled manual workers), educational level (highest qualification attained: no qualifications, educated to age 16 years, educated to age 18 years, or educated to de- gree level), and physical activity level (inactive, moderately inactive, moderately active, or active) (22). Body mass index (BMI; weight in kilograms divided by height in meters squared) was measured at the baseline health check. Other covariates were reported in questionnaires during the time of the second health check: age, marital status (single, mar- ried, widowed, separated, or divorced), employment status
(working or not working), smoking status (current, former, or nonsmokers), alcohol intake (units of alcohol drunk per week), self-reported general health (excellent, good, moderate, or poor), use of hypnotic drugs (yes or no), antide- pressant use (yes or no), use of drugs to treat chronic obstruc- tive pulmonary disease (COPD) (yes or no), major depressive disorder (MDD) in the previous year (yes or no) (23), and time spent in bed at night (in hours, derived from the differ- ences between reported rise times and bedtimes). Hypnotic drug use was defined according to the British National For- mulary (section 4.1) (24) and included benzodiazepines, zaleplon, zolpidem, and zopiclone, chloral and its deriva- tives, clomethiazole, and antihistamines. Preexisting health conditions included self-reported stroke, myocardial infarc- tion, diabetes, cancer, asthma, bronchitis, and emphysema, as well as a proxy measure of obstructive sleep apnea (OSA), with persons who were in the highest BMI quartile and who reported taking antihypertension drugs being de- fined as likely to have underlying OSA. Participants were flagged for death certification at the United Kingdom Office of National Statistics so that we were notified of their deaths, with vital status established for the whole cohort. The current analysis presents deaths that occurred during followed up from January 2000 and until December 2012. Deaths were coded initially according to the International Classification of Diseases (ICD), Ninth Revision, and later the Tenth Revision. The underlying cause of death was categorized as due to CVD (ICD- codes 401–448 or ICD-10 codes I10–I79), cancer (ICD- codes 140–208 or ICD-10 codes C00–C97), or respiratory diseases (ICD–9 codes 460–496 or ICD-10 codes J00–J99).
Statistical analysis
The present study included 16,374 participants (7,161 men and 9,213 women) who provided information on their day- time napping habits. The characteristics of the participants were first compared by category of daytime napping. The comparisons of normally distributed variables and skewed continuous variables were based on analysis of variance and Kruskal-Wallis test, respectively. Categorical variables were compared using Pearson’s χ^2 test. The associations between daytime napping and all-cause or disease-specific mortality were examined using Cox pro- portional hazards regression models that were adjusted for covariates. The endpoints were grouped into death from all causes, CVD, cancer, respiratory diseases, and all other causes. We firstly examined the proportional hazard assump- tion using both a Kaplan-Meier plot and Schoenfeld’s test, and no sign of violation was found for any endpoint. All co- variates were chosen a priori based on the literature and their relevance to napping and health. Models were constructed with progressive adjustment of the covariates to show the as- sociations explained by the covariates: 1) Model A was ad- justed for age and sex; 2) model B was further adjusted for social class, educational level, marital status, employment status, BMI, physical activity level, smoking status, and alco- hol intake; 3) model C was adjusted for the variables in model B and MDD, self-reported general health, time spent in bed at night, hypnotic drug use, antidepressant use, and COPD drug
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Table 1. Baseline Characteristics by Categories of Napping Behaviors in 7,161 Men, European Prospective
Investigation Into Cancer-Norfolk, United Kingdom, 1998– 2000
Characteristic Total No.
Time Spent Napping None <1 hour ≥1 hour No. % No. % No. % All mena^ 7,161 4,508b^ 63.0 2,379 33.2 274 3. Age, years ≤ 65 4,125 3,072b^ 68.2 942 39.7 111 40.
65 3,027 1,431 31.8 1,433 60.3 163 59. Social class Nonmanual worker 4,319 2,741 61.6 1,425 60.9 153 56. Manual worker 2,738 1,708 38.4 913 39.1 117 43. Education category Lower 2,650 1,531b^ 34.0 989 41.6 130 47. Higher 4,509 2,976 66.0 1,389 58.4 144 52. Marital status Single 303 193 4.3 97 4.1 13 4. Married 6,244 3,936 87.6 2,075 87.6 233 85. Otherc^588 362 8.1 198 8.4 28 10. Smoking status Current smoker 608 362 b^ 8.1 203 8.6 43 15. Former smoker 3,980 2,378 53.2 1,445 61.2 157 57. Never smoker 2,517 1,730 38.7 714 30.2 73 26. Category of alcohol intake Lower 3,287 2,063 50.8 1,107 52.3 117 51. Higher 3,120 1,998 49.2 1,010 47.7 112 48. Category of body mass indexd Lower (<25.7) 3,201 2,142b^ 52.8 966 45.9 93 39. Higher (≥25.7) 3,189 1,911 47.2 1,138 54.1 140 60. Physical activity level Inactive/moderately inactive 3,834 2,295b^ 50.9 1,354 56.9 185 67. Moderately active/active 3,327 2,213 49.0 1,025 43.1 89 32. Major depressive disorder No 5,976 4,448b^ 98.7 2,341 98.4 266 97. Yes 231 60 1.3 38 1.6 8 2. Self-reported general health Excellent 1,150 805 b^ 18.0 323 13.6 22 8. Good 4,732 3,009 67.3 1,579 66.6 144 53. Poor to moderate 1,233 660 14.8 468 19.8 105 38. Hypnotic drug use No 7,055 4,448 98.7 2,341 98.4 266 97. Yes 106 60 1.3 38 1.6 8 2. Time in bed per night, hours ≤8.5 3,611 2,333e^ 60.4 1,167 57.5 111 52. 8.5 2,493 1,532 39.6 861 42.5 100 47. Preexisting health conditions f No 4,505 3,104b^ 73.1 1,285 59.7 116 47. Yes 2,142 1,144 26.9 867 40.3 131 53. a (^) Comparison was made between men and women. b (^) P < 0.001. c (^) Widowed, separated, or divorced. d (^) Weight (kg)/height (m) 2. e (^) P < 0.05. f (^) Stroke, myocardial infarction, cancer, asthma, bronchitis, and underlying sleep apnea.
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Table 2. Baseline Characteristics by Categories of Napping Behaviors in 9,213 Women, European Prospective
Investigation Into Cancer-Norfolk, United Kingdom, 1998– 2000
Characteristic Total No.
Time Spent Napping None <1 hour ≥1 hour No. % No. % No. % All womena^ 9,213 6,985 75.8 2,033 22.1 195 2. Age, years ≤ 65 5,820 4,888b^ 70.1 840 41.4 92 47.
65 3,378 2,084 29.9 1,191 58.6 103 52. Social class Nonmanual worker 5,755 4,404 64.3 1,230 62.2 121 64. Manual worker 3,264 2,450 35.7 747 37.8 67 35. Education category Lower 4,687 3,427b^ 49.1 1,146 56.4 114 58. Higher 4,521 3,553 50.9 887 43.6 81 41. Marital status Single 387 280 b^ 4.0 95 4.7 12 6. Married 6,750 5,236 75.4 1,389 68.5 125 64. Otherc^ 2,030 1,430 20.6 543 26.8 57 29. Smoking status Current smoker 769 596 b^ 8.6 142 7.1 31 16. Former smoker 2,997 2,205 31.9 727 36.1 65 33. Never smoker 5,352 4,110 59.5 1,144 56.8 98 50. Category of alcohol intake Lower 4,601 3,484d^ 59.9 1,027 63.0 90 66. Higher 2,984 2,336 40.1 602 37.0 46 33. Category of body mass index e Lower (<25.7) 4,096 3,250b^ 52.0 766 43.6 80 48. Higher (≥25.7) 4,071 2,995 48.0 991 56.4 85 51. Physical activity level Inactive/moderately inactive 5,551 4,092b^ 58.6 1,324 65.1 135 69. Moderately active/active 3,662 2,893 41.4 709 30.9 60 30. Major depressive disorder
No 7,458 5,656 93.6 1,650 94.3 153 90. Yes 501 385 6.4 100 5.7 16 9. Self-reported general health Excellent 1,419 1,174b^ 16.9 225 11.1 20 10. Good 5,998 4,600 66.3 1,304 64.6 94 49. Poor to moderate 1,853 1,166 16.8 490 24.3 78 40. Hypnotic drug use No 9,042 6,871 d^ 98.4 1,983 97.5 188 96. Yes 171 114 1.6 50 2.5 7 3. Time in bed per night, hours ≤8.5 3,550 2,725d^ 45.2 774 45.7 51 33.
8.5 4,321 3,299 54.8 921 54.3 101 66. Preexisting health conditions f No 5,307 4,192b^ 66.9 1,015 59.4 100 63. Yes 2,827 2,076 33.1 693 40.6 58 36. a (^) Comparison was made between men and women. b (^) P < 0.001. c (^) Widowed, separated, or divorced. d (^) P < 0.05. e (^) Weight (kg)/height (m) (^2). f (^) Stroke, myocardial infarction, cancer, asthma, bronchitis, and underlying sleep apnea.
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Table 4. Multivariablea^ Associations Between Daytime Napping and All-Cause Mortality by Subgroups, European
Prospective Investigation Into Cancer-Norfolk, United Kingdom, 2000– 2012
Variable No. of Deaths
Time Spent Napping b <1 hour ≥1 hour HR 95% CI HR 95% CI Length of follow-up, years <6.5 1,189 0.89 0.73, 1.08 1.06 0.69, 1. ≥6.5 2,062 1.10 0.97, 1.26 1.41 c^ 1.05, 1. P for interaction 0. Age, years ≤ 65 783 1.42 d^ 1.13, 1.79 1.95 c^ 1.16, 3.
65 2,464 1.05 0.93, 1.19 1.19 0.90, 1. P for interaction 0. Sex Men 1,795 1.1 0.96, 1.26 1.3 0.98, 1. Women 1,456 1.23 c^ 1.02, 1.47 1.19 0.72, 1. P for interaction 0. Employment status Working 422 1.23 0.90, 1.67 2.46 c^ 1.16, 5. Not working 2,679 1.13 c^ 1.00, 1.27 1.23 0.96, 1. P for interaction 0. Preexisting health conditions e
Yes 1,431 1.22 c^ 1.03, 1.45 1.23 0.85, 1. No 1,820 1.08 0.94, 1.24 1.44 c^ 1.04, 1. P for interaction 0. Smoking status Current or former smoker 2,042 1.19 c^ 1.04, 1.36 1.22 0.91, 1. Never smoked 1,163 1.06 0.88, 1.28 1.54 0.99, 2. P for interaction 0. Category of body mass index f Lower (<25.7) 1,393 1.32 g^ 1.12, 1.56 1.72 d^ 1.21, 2. Higher (≥25.7) 1,848 1.04 0.90, 1.20 1.08 0.77, 1. P for interaction 0. Major depressive disorder Yes 136 1.52 0.79, 2.96 2.90 c^ 1.12, 7. No 2,702 1.13 c^ 1.02, 1.27 1.25 0.97, 1. P for interaction 0. Time spent in bed at night, hours ≤8.5 1,234 1.08 0.93, 1.26 1.54 c^ 1.10, 2.
8.5 1,427 1.20 c^ 1.03, 1.40 1.13 0.80, 1. P for interaction 0. Nighttime sleep duration, hours h <6 305 1.10 0.76, 1.60 1.64 0.69, 3. 6 – 7 234 0.88 0.58, 1.32 2.02 0.78, 5. 7 362 1.13 0.84, 1.52 0.82 0.39, 1. P for interaction 0. Abbreviations: CI, confidence interval; HR, hazard ratio. a (^) Adjusted for age, sex, social class, educational level, marital status, employment status, body mass index, physical activity level, smoking status, alcohol intake, major depressive disorder, self-reported general health, hypnotic drug use, antidepressant use, chronic obstructive pulmonary disease drug use, time spent in bed at night, and preexisting health conditions. b (^) The reference group was persons who did not nap. c (^) P < 0.05. d (^) P < 0.01. e (^) Stroke, myocardial infarction, cancer, asthma, bronchitis, emphysema, and underlying sleep apnea. f (^) Weight (kg)/height (m) 2. g (^) P < 0.001. h (^) Measured in the third health check in 10,520 people; the others were all measured in the second health check.
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sleep patterns in the EPIC-Norfolk population (32). In addi- tion, a surrogate measure of OSA was included in regression models to help address the problem. This measure combines BMI and hypertension, 2 strong correlates of OSA (33–35). The surrogate measure may partly reflect the probability of having OSA; therefore, further studies with more precise measures of OSA and nighttime sleep quality are required to confirm whether the association stands independent of other sleep parameters. Our findings are consistent with most previous studies that have reported an association between self-reported daytime napping and increased all-cause mortality (10, 11, 14–16, 36, 37). These studies covered populations from the Mediter- ranean, Japan, and the United States and included primarily older populations. The largest published report to date came from the Japan Collaborative Cohort Study, in which a total of 9,643 deaths were recorded and daytime napping was found to be associated with increased mortality from specific causes, particularly CVD (16). Indeed, most previous studies have related daytime napping to increased CVD mortality risk (10, 15, 16, 37). In our study, the association between napping and CVD mortality risk was largely explained by MDD in the previous year. MDD is commonly associated with sleep disturbance, which might lead to excessive daytime napping. Previous evidence based upon our cohort (23) has shown major depression to be associated with an increased risk of ischemic heart disease mortality, though understanding of this association remains elusive. It is possible that the asso- ciation between napping and CVD mortality is mostly ex- plained by depression or MDD reported within a certain time frame. Future studies would need to carefully examine the role of depression in the napping-mortality association. At the same time, several earlier studies (6, 12) from Med- iterranean populations have suggested different findings. The Greek EPIC cohort study, which is methodologically compa- rable to our study, found napping to be protective against cor- onary mortality (12). Notably, the Greek cohort included people who were 20–86 years of age at baseline, whereas our participants were exclusively middle- to older-aged adults. Moreover, the association was particularly strong among working men in their study, which might be explained by the possible stress-releasing effect of afternoon naps (12). This effect could have been masked in our aging population, who are mostly retired and might take naps for other purposes, such as compensating for declining physical functions. Inter- estingly, in our study, the positive association between napping and mortality was seen to be stronger among persons 65 years of age or younger than among those older than 65 years of age (65 years is the age by which most people have retired from work in the United Kingdom). It is often believed that napping is protective for younger populations and problematic for older ones (12, 19, 37). Notably, the average age of our participants at baseline was 62 years, so the younger persons in the present study were not comparable to those mentioned in earlier stud- ies (12, 38). Although it is unknown why the association was stronger among those 65 years of age or younger, our finding raises the possibility that napping might be more indicative of mortality risk in this population, and this needs to be confirmed by further studies. Unlike in previous studies (14, 36), no ev- ident sex difference was observed in this study.
In the present study, we found large effect sizes for the as- sociation between napping and death from respiratory disease even though there were much fewer respiratory deaths than CVD and cancer deaths. The association was independent of smoking status, preexisting respiratory diseases, and COPD drug use. This is surprising given the lack of evidence of the associations between napping and respiratory health. Although none of the previous studies highlighted the asso- ciation between napping and respiratory mortality, most of them did suggest the association with non-CVD/non-cancer mortality (10, 15, 16), and these categories were largely made up of respiratory mortality in our study. The reason why day- time napping may increase respiratory mortality is not known, but it is worth noting the interrelationship between the cardiovascular and respiratory systems (39). Although we failed to find an association between napping and CVD mortality, the napping-respiratory association might not be separate from the cardiovascular consequences of sleep prob- lems (e.g., OSA). It seems reasonable to suggest that persons with respiratory problems (especially hypoxic conditions) were more likely to nap and were also more likely to die of respiratory disease because of their underlying problems. The incidence of OSA was not recorded directly in this study, and a proxy measure was used to account for the ef- fects. Given the close link between OSA and mortality (40, 41), daytime napping might well be a good surrogate measure of OSA, which is potentially important for early detection of OSA in the general population. Although in this study the association between napping and all-cause mortality remained after excluding participants with known preexisting health conditions at baseline, it re- mains possible that daytime napping is simply a marker of undiagnosed health problems and of reverse causation, with those individuals who have undiagnosed ill health napping more. In this case, we would expect attenuation in the asso- ciation whereby it is stronger in the immediate period of follow-up and lessens thereafter. However, the association seemed to be even stronger among those with a follow-up length of 6.5 years or more. Interestingly, the association was stronger among persons with a lower BMI. Although the exact reason for this observation is unclear, it is worth not- ing the “obesity paradox,” which might have been brought about by existing physiological or pathological changes (42, 43). It is possible that persons with lower BMI could have been suffering from underlying illnesses that led to weight loss and that this added to the health risk conveyed by daytime napping. In the United Kingdom, daytime napping is not part of the cultural norm, and in the absence of obvious disruptions in nighttime sleep patterns, it remains plausible that napping might be an early sign of system disregulation and a marker of future health problems. Alternatively, there may be a bio- logical mechanism through which napping is associated with mortality, for example, through inflammatory pathways, espe- cially increased chronic low-grade inflammation. Increased levels of inflammation have been suggested for persons with reduced nighttime sleep durations (44), but we are unaware of any evidence to show an association between daytime nap- ping and inflammation. Our findings need confirmation from further population studies that include examination of the
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- Wareham NJ, Jakes RW, Rennie KL, et al. Validity and repeatability of a simple index derived from the short physical activity questionnaire used in the European Prospective Investigation Into Cancer and Nutrition (EPIC) study. Public Health Nutr. 2003;6(4):407–413.
- Surtees PG, Wainwright NWJ, Luben RN, et al. Depression and ischemic heart disease mortality: evidence from the EPIC-Norfolk United Kingdom prospective cohort study. Am J Psychiatry. 2008;165(4):515–523.
- British Medical Association and the Royal Pharmaceutical Society of Great Britain. British National Formulary. 47th ed. London, UK: British Medical Association; 2004.
- Yoon I-Y, Kripke DF, Youngstedt SD, et al. Actigraphy suggests age-related differences in napping and nocturnal sleep. J Sleep Res. 2003;12(2):87–93.
- Dautovich ND, McCrae CS, Rowe M. Subjective and objective napping and sleep in older adults: are evening naps “bad” for nighttime sleep? J Am Geriatr Soc. 2008;56(9):1681–1686.
- Tamaki M, Shirota A, Hayashi M, et al. Restorative effects of a short afternoon nap (<30 min) in the elderly on subjective mood, performance and EEG activity. Sleep Res Online. 2000; 3(3):131–139.
- Milner CE, Cote KA. Benefits of napping in healthy adults: impact of nap length, time of day, age, and experience with napping. J Sleep Res. 2009;18(2):272–281.
- Ruggiero JS, Redeker NS. Effects of napping on sleepiness and sleep-related performance deficits in night-shift workers: a systematic review. Biol Res Nurs. 2014;16(2):134–142.
- Tassi P, Muzet A. Sleep inertia. Sleep Med Rev. 2000;4(4): 341 – 353.
- Rod NH, Vahtera J, Westerlund H, et al. Sleep disturbances and cause-specific mortality: results from the GAZEL cohort study. Am J Epidemiol. 2011;173(3):300–309.
- Leng Y, Wainwright NW, Cappuccio FP, et al. Self-reported sleep patterns in a British population cohort. Sleep Med. 2014; 15(3):295–302.
- Lavie P, Herer P, Hoffstein V. Obstructive sleep apnoea syndrome as a risk factor for hypertension: population study. BMJ. 2000;320(7233):479–482.
- Young T, Shahar E, Nieto FJ, et al. Predictors of sleep-disordered breathing in community-dwelling adults: the Sleep Heart Health Study. Arch Intern Med. 2002;162(8): 893 – 900.
- Tishler PV, Larkin EK, Schluchter MD, et al. Incidence of sleep-disordered breathing in an urban adult population: the relative importance of risk factors in the development of sleep-disordered breathing. JAMA. 2003;289(17): 2230 – 2237.
- Bursztyn M, Ginsberg G, Stessman J. The siesta and mortality in the elderly: effect of rest without sleep and daytime sleep duration. Sleep. 2002;25(2):187–191.
- Burazeri G, Gofin J, Kark JD. Siesta and mortality in a Mediterranean population: a community study in Jerusalem. Sleep. 2003;26(5):578–584.
- Kalandidi A, Tzonou A, Toupadaki N, et al. A case-control study of coronary heart disease in Athens, Greece. Int J Epidemiol. 1992;21(6):1074–1080.
- Maclay JD, McAllister DA, Macnee W. Cardiovascular risk in chronic obstructive pulmonary disease. Respirology. 2007; 12(5):634–641.
- Young T, Finn L, Peppard PE, et al. Sleep disordered breathing and mortality: eighteen-year follow-up of the Wisconsin sleep cohort. Sleep. 2008;31(8):1071–1078.
- Yaggi HK, Concato J, Kernan WN, et al. Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med. 2005; 353(19):2034–2041.
- Adams KF, Leitzmann MF, Ballard-Barbash R, et al. Body mass and weight change in adults in relation to mortality risk. Am J Epidemiol. 2014;179(2):135–144.
- Strandberg TE, Stenholm S, Strandberg AY, et al. The “obesity paradox,” frailty, disability, and mortality in older men: a prospective, longitudinal cohort study. Am J Epidemiol. 2013; 178(9):1452–1460.
- Ferrie JE, Kivimäki M, Akbaraly TN, et al. Associations between change in sleep duration and inflammation: findings on C-reactive protein and interleukin 6 in the Whitehall II Study. Am J Epidemiol. 2013;178(6): 956 – 961.
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