Changes in nocturnal sleep and daytime nap durations predict all-cause mortality

Transcription

1 Changes in nocturnal sleep and daytime nap durations predict all-cause mortality among older adults: the Panel on Health and Ageing of Singaporean Elderly Grand H.-L. Cheng, PhD 1, *; Rahul Malhotra, MD 1 ; Truls Østbye, PhD 1 ; Angelique Chan, PhD 1 ; Stefan Ma, PhD 2 ; June C. Lo, PhD 3, * 1 Centre for Ageing Research and Education, Duke-NUS Medical School, Singapore 2 Epidemiology and Disease Control Division, Ministry of Health, Singapore 3 Centre for Cognitive Neuroscience, Duke-NUS Medical School, Singapore *Corresponding authors: Dr. Grand H.-L. Cheng Centre for Ageing Research and Education Duke-NUS Medical School, 8 College Road, Level 4, Singapore Phone: (+65) grand.cheng@duke-nus.edu.sg ABSTRACT Dr. June C. Lo Centre for Cognitive Neuroscience Duke-NUS Medical School, 8 College Road, Level 2, Singapore Phone: (+65) june.lo@duke-nus.edu.sg Study Objectives: To determine the effects of changes in nocturnal sleep and daytime nap durations on all-cause mortality among older adults. Methods: 2448 community-dwelling older Singaporeans ( 60 years) reported their nocturnal sleep and daytime nap durations at baseline (2009) and the 2-year follow-up. At each phase, they were grouped into the recommended (7-8h), short ( 6h), and long ( 9h) sleep duration categories, and the none (0h), short ( 1h), and long (>1h) nap duration categories. Cox Sleep Research Society Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please journals.permissions@oup.com.

2 regression analysis was conducted to quantify the associations of changes in sleep and nap durations over 2 years with all-cause mortality risk in the subsequent 4 years (till end of 2015). Multivariable fractional polynomial regression which treated sleep and nap durations as continuous variables was conducted as a supplementary analysis. Results: Relative to individuals who had the recommended sleep durations at both baseline and follow-up, the risks of all-cause mortality were higher among older adults who reported considerable changes in sleep duration (from short to long sleep and vice versa, HR= ). Furthermore, compared to those who did not nap at both time points, significantly higher mortality risks were found in individuals who showed any increase in nap duration (HR= ), or reduced their nap from long to short duration (HR=1.86). Supplementary analysis revealed similar findings. Conclusions: In addition to change in nocturnal sleep duration, change in daytime nap duration can also predict risks of all-cause mortality among older adults. It is crucial to track older adults sleep and nap durations longitudinally. Keywords: nocturnal sleep duration, daytime nap duration, all-cause mortality, older adults Statement of Significance Dramatic increases as well as decreases in nocturnal sleep duration are associated with elevated risks of all-cause mortality in older adults. However, the potential influence of change in daytime nap duration remains unexplored. In addition to confirming the adverse effects of substantial changes in self-reported nocturnal sleep duration, the current longitudinal study also demonstrated that older adults who reported any increase in nap duration, a decrease from long to short nap, and consistently short or long nap faced higher all-cause mortality risks compared to non-nappers. These findings indicate the importance of tracking older adults sleep and nap durations over time.

3 INTRODUCTION Multiple studies have shown that sleep duration plays an important role in mortality risks among older adults. While long sleep duration at night has consistently been linked with an elevated risk of all-cause mortality, associations of short sleep have also been documented. 1-5 However, in most existing studies, sleep duration was assessed at a single time point only. Given that sleep duration may vary across time, 6 the role of change in sleep duration warrants investigation. Indeed, dramatic changes (both increases and decreases) in sleep duration have been found to elevate the risk of all-cause mortality. 7, 8 Notably, in some of these studies, participants were required to report their sleep duration over a 24-hour period and thus, daytime napping was also included, 9-11 suggesting the possibility that changes in nap behavior over time may also influence mortality risk. Daytime napping is prevalent among older adults worldwide particularly in China, Latin America, and Mediterranean countries Previous studies have shown that compared with non-nappers, nappers face a higher mortality risk, and this relationship appears to be dose-dependent with increasing mortality risk for those who nap longer. 12, 15, 16 However, the impact of change in nap duration on mortality remains to be investigated. Here, utilizing longitudinal data from a nationally representative sample of community-dwelling older adults in Singapore, we investigated the contribution of change in self-reported nocturnal sleep duration and change in self-reported daytime nap duration to allcause mortality. Based on existing findings, 7 we hypothesized that progression to long sleep and reduction to short sleep at night would both increase mortality risks relative to consistently sleeping for the recommended durations of 7 to 8h. 17 In line with the adverse impact of long naps previously reported, 15 we also postulated that compared with those who had never napped, elderly who reported an increase in nap duration, or consistently napped for either short or long durations would face higher mortality risks.

4 METHODS Participants Data came from a nationally representative longitudinal survey (Panel on Health and Ageing of Singaporean Elderly [PHASE]), which documents the psychological, social, behavioral, and health conditions of community-dwelling older adults in Singapore. Information on the mortality status, including date of death of the deceased, until end- December 2015 was obtained from the national Registry of Births and Deaths databases. PHASE Waves 2 and 3, analysis of de-identified data from PHASE Wave 1, and linkage with the deaths databases were approved by the institutional review board at the National University of Singapore. Details of data collection at baseline (2009) are available elsewhere. 18 Briefly, a single-stage stratified (by age, sex, and ethnicity, based on the 2007 population distribution) random sampling method was adopted to recruit participants aged 60 years or above. After informed consent, 4990 face-to-face interviews were conducted in the participants residence, and, of these, 4473 participants reported their nocturnal sleep and daytime nap durations. 357 individuals had died between baseline and the 2-year follow up. At the 2-year follow-up, 3103 interviews were conducted, and, of these, 2715 participants reported their sleep and nap durations. There were 2448 older adults who reported their sleep and nap durations at both time points. They did not have any missing data on the covariate variables (Table 1). None of these individuals had been diagnosed with dementia (selfreported and/or confirmed with household members). Sample characteristics by sleep and nap duration categories at baseline are shown in Tables S1 and S2 respectively. For attrition analysis, we evaluated whether the analytical sample (n=2448) and those who reported nocturnal sleep and daytime nap at baseline (n=4473) were similar in terms of baseline sleep and nap durations as well as covariates. 19 Results showed that attrition was not a serious

5 concern (η 2 s 0.01), suggesting that the analytical sample mirrored the population of this age group in Self-reported nocturnal sleep and daytime nap durations Participants indicated their nocturnal sleep duration in hours and minutes by answering the question On average, approximately how much do you sleep per night? Fractional hours were coded as rounded integers (e.g., 7h represented 6.5h to 7.4h). 20 Participants were classified into 3 categories at each phase based on the sleep duration recommendation for older adults by the National Sleep Foundation: 17 recommended (7-8h), short ( 6h), and long ( 9h) durations. Operationally, the three groups consisted of individuals reporting nocturnal sleep durations of h, 6.4h, and 8.5h, respectively. Following previous work, 7, 10, 11 we created 9 categories of change (including no change) in nocturnal sleep duration from baseline to the 2-year follow-up to represent all possible combinations of change. Similarly, participants indicated their daytime nap duration in hours and minutes, and they were classified into 3 categories at each phase: 15 none, short ( 1h), and long (>1h) durations. Using all possible combinations, 9 categories of change (including no change) in daytime nap duration were constructed. All-cause mortality All-cause mortality, until end-december 2015, was assessed primarily from the national Registry of Births and Deaths databases, supplemented by our survey data. 274 individuals (11.2%) in our sample had passed away in the approximately 4-year period from their interview date in the 2-year follow-up to end-december Covariates Covariates included 9 sociodemographic and 10 health variables. All covariates were self-reported, except height and weight. The sociodemographic covariates were age, sex, ethnicity, education level, housing type, employment status, marital status, living alone, and

6 social networks with friends and relatives outside the household. Housing type is an indicator of socioeconomic status in Singapore ( 4 room public/ private indicates a relatively high status). Married included those not living with their spouse due to one spouse s being hospitalized, living in an institution, or living in another area for business reasons or to take care of others. Unmarried included those widowed, separated from spouse, divorced, and never married. Social networks were assessed with the 12-item modified Lubben s social network scale (scores ranging from 0 to 60). 18 Health covariates included depressive symptomatology (the 11-item Center for Epidemiological Studies Depression [CES-D] Scale with scores ranging from 0 to 22). 21 Physical exercise referred to frequency (less than one month vs. at least once a month) of physical exercise (walking for exercise purposes, playing a game of sport), and smoking was captured as current smoker vs. ex- / non-smoker. 22 In addition, participants reported whether they had ever been diagnosed by a medical professional with heart attack, other heart condition, cancer (excluding skin cancer), cerebrovascular disease, high blood pressure, and diabetes. Body mass index (BMI) was calculated using measured weight and height. Statistical analysis Using SPSS version 24, we conducted Cox proportional hazards regression analysis to estimate the associations (hazard ratio; HR) of changes in nocturnal sleep duration and daytime nap duration between baseline and the 2-year follow-up with all-cause mortality in the subsequent 4 years. Following the statistical approach used in previous studies, 7, 10, 11 we investigated change in sleep duration and mortality based on 9 categories of change, with participants reporting the recommended sleep duration at both phases as the reference group. Regarding nap duration change, consistent with our approach for analyzing sleep duration change, as well as our hypothesis about the impact of nap duration change, participants who did not nap at both phases were used as the reference group. Overall, we included all the

7 dummy variables for change in sleep duration and change in nap duration in the same statistical model to assess the unique contribution of each parameter. The proportionality assumption was evaluated with a standard procedure which concerns the interaction between time and the study variables. 23 Results indicated that this assumption was met. In the adjusted model, covariates (including the linear and the quadratic terms of BMI) assessed at baseline, together with change in health-related factors between baseline and the 2-year follow-up, were taken into account. 7 Sensitivity analysis showed that results remained similar when outliers (cases with standardized sleep and/ or nap durations exceeding at baseline and/ or 2-year follow-up) were excluded. Thus, here, we focus on the findings based on 2448 individuals (with the outliers included). The main analysis outlined above represents a planned comparison (recommendedrecommended as the reference category for change in sleep duration, and none-none as the reference category for change in nap duration), in which sleep and nap durations were treated as categorical variables. To preserve the continuous nature of these variables, we conducted a supplementary analysis multivariable fractional polynomial regression which provides a flexible parameterization for continuous variables to capture non-linear associations with the outcome of interest with Stata package MFPIgen. 24 Interaction terms are omnibus and have 25, 26 been argued to be less informative and important than the results of planned comparisons. Hence, the interaction effect between sleep duration at baseline and the 2-year follow-up, as well as that between nap duration at baseline and the 2-year follow-up revealed by the multivariable fractional polynomial regression would not be underscored here. On the other hand, the respective sliced plots 24 are provided to substantiate the main analysis.

8 RESULTS Change in nocturnal sleep duration The findings of the unadjusted and adjusted Cox regression models were similar (Table 2). In the adjusted model, relative to older adults who reported the recommended sleep durations at night at both phases, all-cause mortality risk in the subsequent 4 years increased by 114% (HR=2.14, CI 95 =1.12, 4.11; Figure S1) in those whose sleep duration increased from short to long, and by 156% (HR=2.56, CI 95 =1.22, 5.37) in those whose sleep duration decreased from long to short over 2 years. Also, older adults who reported long sleep durations at both time points had a 124% higher risk in mortality (HR=2.24, CI 95 =1.05, 4.77). A similar pattern was found when sleep durations (and nap durations) at baseline and the 2- year follow-up were used as continuous variables in a multivariable fractional polynomial regression (Figure S3). Change in daytime nap duration Compared with their counterparts who did not nap at both baseline and the 2-year follow-up, the risks for all-cause mortality were significantly increased in older adults who did not nap at baseline but reported napping at the follow-up (HR=1.86, CI 95 =1.26, 2.75 for short nap at follow-up; HR=1.91, CI 95 =1.06, 3.45 for long nap at follow-up) (Table 2; Figure S2). A significantly higher risk was also observed for older adults whose nap duration extended from short to long within the 2-year period (HR=2.16, CI 95 =1.32, 3.53). Overall, any increase in nap duration was associated with a higher mortality hazard. Out of the 3 groups that reported a decrease in nap duration from baseline to followup, only the long-short group had a significantly higher mortality risk (HR=1.86, CI 95 =1.10, 3.13). In contrast, risks were not elevated for individuals who no longer took naps at followup, regardless of their nap duration at baseline.

9 Finally, increased mortality hazards were observed in older adults who had napped for consistent durations across the 2 phases. Persistently napping for short durations elevated mortality risk by 49% (HR=1.49, CI 95 =1.01, 2.21), while napping for long durations at both baseline and follow-up entailed a 168% increase in all-cause mortality risk (HR=2.68, CI 95 =1.69, 4.23). The pattern revealed by the multivariable fractional polynomial regression, in which nap durations (and sleep durations) at both time points were included as continuous variables, mirrored these findings (Figure S4). DISCUSSION Using a nationally representative sample of older adults in Singapore, we have replicated earlier findings that all-cause mortality risk is elevated among older adults whose self-reported nocturnal sleep duration dramatically increases or decreases, or remains long over time. 7, 8, 11 More importantly, we report for the first time that change in daytime nap duration also impacts all-cause mortality risks. Specifically, relative to non-nappers, all-cause mortality risks in the subsequent 4 years are elevated in older individuals whose nap durations have increased in the 2-year study period either from short to long or because they have started napping, as well as older adults whose nap durations have decreased from long to short. Furthermore, older adults who have napped for similar durations at both time points (i.e. the short-short group and the long-long group) face elevated mortality risks. In other words, daytime napping is accompanied by increased mortality risks unless napping has stopped. Our observations are in line with previous studies that measured nap duration at only one time point and showed a positive relationship between nap duration and all-cause mortality risk. 15 Daytime napping and nocturnal sleep may share similar mechanisms in their associations with mortality. 27 For example, levels of inflammatory markers, such as interleukin-6 (IL-6) and C-reactive protein (CRP) have been found to increase in individuals

10 who have restricted sleep at night, 28, 29 as well as those who report long nocturnal sleep durations. 30 Also, daytime napping is associated with higher levels of CRP in older adults. 31 Hence, extreme nocturnal sleep durations and long daytime nap duration might both increase risks for all-cause mortality via chronic low-grade inflammation. Furthermore, extreme nocturnal sleep durations and daytime napping have been linked with medical conditions such as hypertension, 32, 33 diabetes, 32, 34 and coronary heart disease. 27, 35 While extreme nocturnal sleep durations and daytime napping may increase risks of these medical conditions, they can also be markers of poor physical health which elevates mortality risks The similarity in biological mechanisms suggests the possibility that daytime napping affects mortality risks because it is a consequence of poor nocturnal sleep quality, sleep disturbance at night (e.g. difficulties in initiating or maintaining sleep, the use of sleep medication), and sleep disordered breathing which have been reported to increase mortality risks Furthermore, even in healthy older adults, changes in the circadian rhythm can alter both sleep and nap patterns. Specifically, the age-related weakening in the circadian sleeppromoting signal in the early morning can lead to fragmented nocturnal sleep, 43 while the age-related weakening in the circadian arousal signal during the daytime increases levels of sleepiness and causes older adults to fall asleep more readily. 44 Thus, it may not be daytime napping per se that is associated with risks for mortality. However, critically, in this study, change in nocturnal sleep duration and change in daytime nap duration were included into the same statistical model, and various medical conditions were included as covariates. Thus, change in daytime nap duration did significantly contribute to mortality risk independent of any influence of change in nocturnal sleep duration, as well as the medical conditions we investigated. It is important to note that similar to previous findings, 45 in our sample, the associations between sleep and nap durations at baseline (r=-0.01) and the 2-year follow-up

11 (r=-0.03), as well as between changes in sleep and nap durations (r=-0.04), were negligible, further strengthening the possibility that change in nap duration uniquely influences all-cause mortality risks. A few limitations need to be acknowledged. First, we only examined the importance of self-reported nocturnal sleep and daytime nap durations. Since discrepancies exist between objective and self-reported sleep durations, 46 future studies should determine if findings are similar when sleep and nap durations are evaluated by actigraphy and polysomnography. Also, we did not address the contribution of other sleep features, such as sleep quality and architecture, as well as sleep apnea, to mortality risks which should be studied in the future. Second, in our survey, participants were not required to indicate their reasons for napping. Nevertheless, we acknowledge that implications can vary across voluntary naps and naps due to some underlying pathologies. Third, while we controlled for the potential influence of multiple pre-existing medical conditions (e.g. cancer and cerebrovascular disease), these were based on self-report and might involve broad categorizations (e.g. other heart conditions). Also, it remains possible that the associations of sleep and nap changes with all-cause mortality risk could be due to medical problems we did not investigate, as well as the use of sleep-inducing medications. Another caveat concerns the small size and low death counts of some cells which were associated with small power, and did not allow subgroup analysis for examining the potential moderating effects of age and sex. In addition, since the relevant information was not available, we could not differentiate causes of death which should be addressed in future studies. In conclusion, we have shown for the first time that in addition to change in nocturnal sleep duration, pattern of daytime nap duration over time can also predict all-cause mortality risk in older adults. These findings indicate the importance of tracking older adults sleep and nap durations longitudinally.

12 ACKNOWLEDGMENTS Data utilized for this manuscript is from the Panel on Health and Ageing of Singaporean Elderly (PHASE). PHASE has been funded by the Ministry of Social and Family Development, Singapore, the Singapore Ministry of Health s National Medical Research Council under its Singapore Translational Research Investigator Award as part of the project Establishing a Practical and Theoretical Foundation for Comprehensive and Integrated Community, Policy and Academic Efforts to Improve Dementia Care in Singapore (NMRC- STAR ), and its Clinician Scientist Individual Research Grant - New Investigator Grant (NMRC-CNIG ), and the Duke-NUS Geriatric Research Fund. DISCLOSURE STATEMENT All authors declare no conflicts of interest. This work was approved by the Institutional Review Board at National University of Singapore. All participants provided informed consent. Financial support: This work was supported by Singapore Ministry of Social and Family Development, Singapore Ministry of Health s National Medical Research Council (NMRC- STAR and NMRC-CNIG ), and Duke-NUS Geriatric Research Fund. The authors declare no conflict of interest. REFERENCES 1. Cappuccio FP, D'Elia L, Strazzullo P, Miller MA. Sleep duration and all-cause mortality: A systematic review and meta-analysis of prospective studies. Sleep. 2010; 33(5):

13 2. da Silva AA, de Mello RG, Schaan CW, Fuchs FD, Redline S, Fuchs SC. Sleep duration and mortality in the elderly: A systematic review with meta-analysis. BMJ Open. 2016; 6(2): e Liu TZ, Xu C, Rota M, et al. Sleep duration and risk of all-cause mortality: A flexible, non-linear, meta-regression of 40 prospective cohort studies. Sleep Med Rev. 2017; 32: Shen X, Wu Y, Zhang D. Nighttime sleep duration, 24-hour sleep duration and risk of allcause mortality among adults: A meta-analysis of prospective cohort studies. Sci Rep. 2016; 6: Lee JSW, Auyeung TW, Leung J, et al. Long sleep duration is associated with higher mortality in older people independent of frailty: A 5-year cohort study. J Am Med Dir Assoc. 2014; 15(9): Ohayon MM, Carskadon MA, Guilleminault C, Vitiello MV. Meta-analysis of quantitative sleep parameters from childhood to old age in healthy individuals: developing normative sleep values across the human lifespan. Sleep. 2004; 27(7): Aurora RN, Kim JS, Crainiceanu C, O'Hearn D, Punjabi NM. Habitual sleep duration and all-cause mortality in a general community sample. Sleep. 2016; 39(11): Ferrie JE, Shipley MJ, Cappuccio FP, et al. A prospective study of change in sleep duration: Associations with mortality in the Whitehall II Cohort. Sleep. 2007; 30(12): Heslop P, Smith GD, Metcalfe C, Macleod J, Hart C. Sleep duration and mortality: The effect of short or long sleep duration on cardiovascular and all-cause mortality in working men and women. Sleep Med. 2002; 3(4):

14 10. Hublin C, Partinen M, Koskenvuo M, Kaprio J. Sleep and mortality: A population-based 22-year follow-up study. Sleep. 2007; 30(10): Soh AZ, Chee MWL, Yuan J-M, Koh W-P. Sleep lengthening in late adulthood signals increased risk of mortality. Sleep. In press. 12. Zhong G, Wang Y, Tao T, Ying J, Zhao Y. Daytime napping and mortality from all causes, cardiovascular disease, and cancer: A meta-analysis of prospective cohort studies. Sleep Med. 2015; 16(7): Martin JL, Ancoli-Israel S. Napping in older sdults. Sleep Med Clin. 2006; 1(2): Leng Y, Wainwright NWJ, Cappuccio FP, et al. Daytime napping and the risk of allcause and cause-specific mortality: A 13-year follow-up of a British population. Am J Epidemiol. 2014; 179(9): Yamada T, Hara K, Shojima N, Yamauchi T, Kadowaki T. Daytime napping and the risk of cardiovascular disease and all-cause mortality: A prospective study and dose-response meta-analysis. Sleep. 2015; 38(12): Xiao Q, Arem H, Pfeiffer R, Matthews C. Prediagnosis sleep duration, napping, and mortality among colorectal cancer survivors in a large US cohort. Sleep. In press. 17. Hirshkowitz M, Whiton K, Albert SM, et al. National Sleep Foundation's sleep time duration recommendations: Methodology and results summary. Sleep Health. 2015; 1(1): Chan A, Malhotra C, Malhotra R, Ostbye T. Living arrangements, social networks and depressive symptoms among older men and women in Singapore. Int J Geriatr Psychiatry. 2011; 26(6): Menard S. Longitudinal research. 2nd ed. Thousand Oaks, CA: Sage; 2002.

15 20. Tu X, Cai H, Gao Y-T, et al. Sleep duration and its correlates in middle-aged and elderly Chinese women: The Shanghai Women s Health Study. Sleep Med. 2012; 13(9): Kohout FJ, Berkman LF, Evans DA, Cornoni-Huntley J. Two shorter forms of the CES- D depression symptoms index. J Aging Health. 1993; 5(2): Zhong B-L, Chen S-L, Tu X, Conwell Y. Loneliness and cognitive function in older adults: Findings from the Chinese Longitudinal Healthy Longevity Survey. J Gerontol B Psychol Sci Soc Sci. 2017; 72(1): Tabachnick BG, Fidell LS. Using multivariate statistics. 6th ed. Boston, MA: Pearson; Royston P, Sauerbrei W. Multivariable model-building: A pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables. Chichester, UK: John Wiley & Sons; Gravetter FJ, Wallnau LB. Statistics for the behavioral sciences. 8th ed. Belmont, CA: Cengage; Keppel G. Design and analysis: A researcher s handbook. Englewood Cliffs, NJ: Prentice-Hall; Yang L, Yang H, He M, et al. Longer sleep duration and midday napping are associated with a higher risk of CHD incidence in middle-aged and older Chinese: The Dongfeng- Tongji Cohort Study. Sleep. 2016; 39(3): Mullington JM, Simpson NS, Meier-Ewert HK, Haack M. Sleep loss and inflammation. Best Pract Res Clin Endocrinol Metab. 2010; 24(5): van Leeuwen WMA, Lehto M, Karisola P, et al. Sleep restriction increases the risk of developing cardiovascular diseases by augmenting proinflammatory responses through IL-17 and CRP. PLOS One. 2009; 4(2): e4589.

16 30. Prather AA, Vogelzangs N, Penninx BWJH. Sleep duration, insomnia, and markers of systemic inflammation: Results from the Netherlands Study of Depression and Anxiety (NESDA). J Psychiatr Res. 2015; 60: Leng Y, Ahmadi-Abhari S, Wainwright NWJ, et al. Daytime napping, sleep duration and serum C reactive protein: a population-based cohort study. BMJ Open. 2014; 4(11): e Knutson KL. Sleep duration and cardiometabolic risk: a review of the epidemiologic evidence. Best Pract Res Clin Endocrinol Metab. 2010; 24(5): Cao Z, Shen L, Wu J, et al. The effects of midday nap duration on the risk of hypertension in a middle-aged and older Chinese population: a preliminary evidence from the Tongji-Dongfeng Cohort Study, China. J Hypertens. 2014; 32(10): Fang W, Li Z, Wu L, et al. Longer habitual afternoon napping is associated with a higher risk for impaired fasting plasma glucose and diabetes mellitus in older adults: results from the Dongfeng-Tongji cohort of retired workers. Sleep Med. 2013; 14(10): Cappuccio FP, Cooper D, D'Elia L, Strazzullo P, Miller MA. Sleep duration predicts cardiovascular outcomes: A systematic review and meta-analysis of prospective studies. Eur Heart J. 2011; 32(12): Cheng GH-L, Chan A, Lo JC. Factors of nocturnal sleep and daytime nap durations in community-dwelling elderly: A longitudinal population-based study. Int Psychogeriatr. 2017; 29(8): Ohayon MM. Interactions between sleep normative data and sociocultural characteristics in the elderly. J Psychosom Res. 2004; 56(5): Grandner MA, Drummond SPA. Who are the long sleepers? Towards an understanding of the mortality relationship. Sleep Med Rev. 2007; 11(5):

17 39. Grandner MA, Hale L, Moore M, Patel NP. Mortality associated with short sleep duration: The evidence, the possible mechanisms, and the future. Sleep Med Rev. 2010; 14(3): 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): Young T, Finn L, Peppard PE, et al. Sleep disordered breathing and mortality: eighteenyear follow-up of the Wisconsin sleep cohort. Sleep. 2008; 31(8): Punjabi NM, Caffo BS, Goodwin JL, et al. Sleep-disordered breathing and mortality: A prospective cohort study. PLoS Med. 2009; 6(8): e Dijk D-J, Duffy JF, Riel E, Shanahan TL, Czeisler CA. Ageing and the circadian and homeostatic regulation of human sleep during forced desynchrony of rest, melatonin and temperature rhythms. J Physiol. 1999; 516(2): Munch M, Knoblauch V, Blatter K, et al. Age-related attenuation of the evening circadian arousal signal in humans. Neurobiol Aging. 2005; 26(9): Goldman SE, Hall M, Boudreau R, et al. Association between nighttime sleep and napping in older adults. Sleep. 2008; 31(5): Lauderdale DS, Knutson KL, Yan LL, Liu K, Rathouz PJ. Self-reported and measured sleep duration: how similar are they? Epidemiology. 2008; 19(6):

18 Table 1. Sample characteristics at baseline (N=2448). N/ Mean %/ SD Age (years) Sex (men) Chinese ethnicity Education level Below secondary Secondary or above Housing type 1-3 room public room public/ private Currently working Married Living alone Social networks Depressive symptomatology Heart attack Other heart condition Cancer Cerebrovascular disease High blood pressure Diabetes Physical exercise Less than once a month At least once a month Currently smoking Body mass index Note: N and % are shown except for age (years), social networks, depressive symptomatology (scale score ranges = 0 to 60 and 0 to 22 respectively, with higher scores indicating higher levels of the constructs), and body mass index.

19 Table 2. Associations of changes in nocturnal sleep and daytime nap durations with all-cause mortality. Group size Death Unadjusted model Adjusted model Baseline Follow-up N % Count % HR CI 95 HR CI 95 Nocturnal sleep duration Recommended Recommended Ref. Ref. Ref. Ref. Recommended Short (0.49, 1.18) 0.75 (0.47, 1.17) Recommended Long (0.54, 2.38) 0.85 (0.40, 1.79) Short Recommended (0.69, 1.55) 1.00 (0.66, 1.51) Short Short (0.74, 1.40) 0.88 (0.63, 1.24) Short Long (1.44, 5.03) 2.14 (1.12, 4.11) Long Recommended (0.52, 2.52) 1.01 (0.45, 2.24) Long Short (1.69, 6.99) 2.56 (1.22, 5.37) Long Long (1.36, 6.05) 2.24 (1.05, 4.77) Daytime nap duration None None Ref. Ref. Ref. Ref. None Short (1.52, 3.27) 1.86 (1.26, 2.75) None Long (1.37, 4.30) 1.91 (1.06, 3.45) Short None (0.52, 1.72) 0.78 (0.42, 1.46) Short Short (1.23, 2.60) 1.49 (1.01, 2.21) Short Long (1.95, 5.03) 2.16 (1.32, 3.53) Long None (0.85, 4.09) 1.32 (0.58, 2.97) Long Short (1.51, 4.22) 1.86 (1.10, 3.13) Long Long (3.12, 7.25) 2.68 (1.69, 4.23) Note: Recommended sleep duration = 7 to 8h, short sleep = 6h or less, long sleep = 9h or more. Short nap = up to 1h, long nap = more than 1h. Death percentage = death count divided by group size. HR = hazard ratio, CI 95 = 95% confidence interval. Significant findings are in bold. The unadjusted model included all the dummy variables for change in sleep duration and change in nap duration as predictors. In the adjusted model, sociodemographic and health covariates at baseline, and change in health-related factors from baseline to the 2-year followup were taken into account.

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