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Effects and differences of sleep duration on the risk of new-onset chronic disease conditions in middle-aged and elderly populations

  • Author Footnotes
    1 Yaoling Wang, Gege Jiang, and Niuniu Hou contribute equally to the article.
    Yaoling Wang
    Footnotes
    1 Yaoling Wang, Gege Jiang, and Niuniu Hou contribute equally to the article.
    Affiliations
    Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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  • Author Footnotes
    1 Yaoling Wang, Gege Jiang, and Niuniu Hou contribute equally to the article.
    Gege Jiang
    Footnotes
    1 Yaoling Wang, Gege Jiang, and Niuniu Hou contribute equally to the article.
    Affiliations
    Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
    Search for articles by this author
  • Author Footnotes
    1 Yaoling Wang, Gege Jiang, and Niuniu Hou contribute equally to the article.
    Niuniu Hou
    Footnotes
    1 Yaoling Wang, Gege Jiang, and Niuniu Hou contribute equally to the article.
    Affiliations
    Department of Thyroid, Breast and Vascular Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China

    Department of General Surgery, Eastern Theater Air Force Hospital of PLA, Nanjing, China
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  • Minfang Chen
    Affiliations
    Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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  • Kang Yang
    Affiliations
    Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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  • Kai Wen
    Affiliations
    School of Software & Microelectronics, Peking University, Beijing, China
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  • Yujie Lan
    Affiliations
    School of Accountancy, Shanghai University of Finance and Economic, China
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  • Wei Li
    Correspondence
    Corresponding author at: Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No 1277, Jiefang Avenue, Wuhan, Hubei Province, China.
    Affiliations
    Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
    Search for articles by this author
  • Author Footnotes
    1 Yaoling Wang, Gege Jiang, and Niuniu Hou contribute equally to the article.
Open AccessPublished:November 08, 2022DOI:https://doi.org/10.1016/j.ejim.2022.11.005

      Highlight

      • With aging, the sleep duration decreases, and the incidence of chronic disease increases.
      • We investigated the risk of sleep duration to the new-onset chronic disease conditions in different populations.
      • Using an age-stratified strategy and explored different thresholds of sleep duration on disease risk in specific groups.
      • Provided a pragmatic theoretical basis for establishing sleep management strategies, which vary in different conditions.

      Abstract

      Background

      Few longitude cohort studies investigated the risk of the duration of nighttime sleep and naps to the new-onset common chronic disease conditions (CDCs) in middle-aged (45-60) and the elderly (age ≥ 60) populations using an age-stratified strategy.

      Methods

      The 7025 participants from The China Health and Retirement Longitudinal Study were screened as eligible subjects. Established 13 cohorts with CDCs, acquired their’ sleep records in 2011, and obtained new-onset incidents of CDCs during follow-up in 2011-2018. Performed risk association analyses between sleep duration and 13 new-onset CDCs respectively.

      Results

      New-onset risk of four CDCs decreased with increasing nighttime sleep (p-nonlinear>0.05). The risk threshold was approximately 7 hours in middle-aged people and 6 hours in the elderly.
      For the middle-aged population, compared with 7-9hours sleep, <5hour and 5-7hours nighttime sleep were associated with 1.312∼1.675 times more risk of hypertension, kidney disease, diabetes or high blood sugar status, and multimorbidity; Compared with no nap, a 0-30 min nap was associated with 1.413(1.087∼1.837) times the heart disease risk.
      In the elderly, < 5 hours of night sleep was a significant risk factor for four CDCs including kidney disease and multimorbidity, etc. A long night's sleep (>9 hours) was connected with 61.2% reduction in risk of memory disease, a >90 min nap increased 62% risk of memory disease, and a 0-30 min nap was associated with higher risks of heart disease, hypertension, and a lower kidney disease risk.

      Conclusions

      Nighttime sleep and daytime naps may have their own implications for the new-onset CDCs' risk in the aging process.

      Graphical abstract

      Keywords

      1. Introduction

      It is expected that by 2050 the population over 65 in China will reach 400 million [
      • Zeng Y.
      Towards Deeper Research and Better Policy for Healthy Aging –Using the Unique Data of Chinese Longitudinal Healthy Longevity Survey.
      ]. A recent epidemiological study in China has demonstrated that 75.8% of residents over 60 years old suffer from at least one chronic disease [
      • Wang L.M.
      • Chen Z.H.
      • Zhang M.
      • et al.
      [Study of the prevalence and disease burden of chronic disease in the elderly in China].
      ]. According to a report from China Centers for Disease Control and Prevention in 2020, the mortality rates (1/100000) of chronic diseases aged 45-60 and over 60 were 366.88, and 3504.22 respectively [

      Chinese Center for Disease Control and Prevention Center for Chronic Noncommunicable Diseases. https://ncncd.chinacdc.cn/xzzq_1/kjsfx/. (11 August 2022, date last accessed).

      ]. With the acceleration of the aging process, aging-related chronic diseases have become the top priority of disease health management.
      Sleep is instrumental to the balance of metabolism, memory consolidation, and brain detoxification [
      • Besedovsky L.
      • Lange T.
      • Haack M.
      The Sleep-Immune Crosstalk in Health and Disease.
      ], which is crucial for the body, cognition, and mental health. However, with the increase of age, sleep problems have become increasingly prominent. About 40% of the elderly develop sleep problems [
      • Morin C.M.
      • Jarrin D.C.
      Epidemiology of Insomnia: Prevalence, Course, Risk Factors, and Public Health Burden.
      ], including insufficient and excessive sleep time [
      • Wolkove N.
      • Elkholy O.
      • Baltzan M.
      • Palayew M.
      Sleep and aging: 1. Sleep disorders commonly found in older people.
      ]. Rapid eye movement sleep and slow wave sleep decrease with age, and sleep latency and wake-up times gradually increase [
      • Ohayon M.M.
      Sleep and the elderly.
      ], which may lead to excessive nap [
      • Mander B.A.
      • Winer J.R.
      • Walker M.P.
      Sleep and Human Aging.
      ].
      Inappropriate sleep time is associated with various chronic diseases, such as cardiovascular diseases [
      • Buxton O.M.
      • Marcelli E.
      Short and long sleep are positively associated with obesity, diabetes, hypertension, and cardiovascular disease among adults in the United States.
      ], chronic kidney diseases [
      • Park S.
      • Lee S.
      • Kim Y.
      • et al.
      Short or long sleep duration and CKD: a mendelian randomization study.
      ] cognitive decline [
      • Winer J.R.
      • Deters K.D.
      • Kennedy G.
      • et al.
      Association of short and long sleep duration with amyloid-β burden and cognition in aging.
      ] and etc. A study based on people aged 50-75 in Europe shows that sleep 7-8.5 h is associated with less risk of chronic diseases [
      • Stenholm S.
      • Head J.
      • Kivimäki M.
      • et al.
      Sleep duration and sleep disturbances as predictors of healthy and chronic disease-free life expectancy between ages 50 and 75: a pooled analysis of three cohorts.
      ]. Among women aged 18-64, there is a stronger relationship between very short or very long sleep time and chronic diseases [
      • Lu C.
      • Liao B.
      • Nie J.
      • Wang W.
      • Wang Y.
      The association between sleep duration and chronic diseases: a population-based cross-sectional study.
      ]. As for daytime naps and new-onset risk of chronic diseases, some studies claim that an appropriate daytime nap will increase [
      • Zhou L.
      • Yu K.
      • Yang L.
      • et al.
      Sleep duration, midday napping, and sleep quality and incident stroke: the Dongfeng-Tongji cohort.
      ,
      • Wang C.
      • Bangdiwala S.I.
      • Rangarajan S.
      • et al.
      Association of estimated sleep duration and naps with mortality and cardiovascular events: a study of 116 632 people from 21 countries.
      ] or reduce [
      • Zhao X.
      • Cheng L.
      • Zhu C.
      • et al.
      A double-edged sword: the association of daytime napping duration and metabolism related diseases in a Chinese population.
      ,
      • Liu X.
      • Wang G.
      • Wang X.
      • et al.
      Daytime napping is associated with retinal microcirculation: a large population-based study in China.
      ] risks and some results show that there is no significant correlation between the two [
      • Lin M.
      • Su Q.
      • Wen J.
      • et al.
      Self-reported sleep duration and daytime napping are associated with renal hyperfiltration in general population.
      ]. Additionally, evidence from longitudinal investigations is lacking with regard to exploring the relationship between sleep duration, especially napping duration, to the new-onset risk of multimorbidity.
      Considering the influence of aging on sleep duration and the incidence of chronic disorders varied in different age groups, it is inappropriate to adopt the same analysis strategy to analyze the risk of sleep duration for new-onset chronic diseases in the population regardless of aging. In the current research from China Health and Retirement Longitudinal Study (CHARLS), we analyzed the risk of sleep duration (nighttime sleep and daytime nap) to 13 new-onset common chronic disease conditions (CDCs) in middle-aged (45≤age<60) and elderly (≥60) and explored different thresholds of sleep duration on disease risk in specific age groups. To our knowledge, this is the first nationwide cohort study to explore the effects and differences of sleep duration on CDCs from a different age perspective in a longitudinal cohort.

      2. Methods

      2.1 Population

      The China Health and Retirement Longitudinal Study (CHARLS) is a longitudinal survey of nationally representative people aged 45 and over. So far, a total of four waves 2011 (wave 1), 2013 (wave 2), 2015 (wave 3), and 2018 (wave 4) of data have been released (A.1).
      The study was approved by the Ethics Committee of the Peking University Health Science Center, and informed consents were obtained from each participant prior to participation.
      We selected the population data published in 2011 as the baseline. Those with qualified records to sleep questionnaires were chosen as the goal population in the study. We established a series of cohorts containing 13 CDCs by excluding those with corresponding medical histories in 2011 and tracked eligible participants until 2018 for new incidences of these diseases. The specific flow chart of the research design is shown in Fig. 1.
      Fig 1
      Fig. 1The flowchart of the study design.
      1The Health Status And Functioning questionnaire includes surveys of smoking, drinking, and sleep duration conditions.
      2The Demographic background questionnaire includes surveys of education levels.
      3The Biomarkers questionnaire includes the measurements of height, weight, and blood pressure.
      4The amounts of missing specific indicators included in this study are as follows:
      Age 171, Sex 171, SBP 252, DBP 267, Smoke 171, Drink 172, Education 173, BMI 268, Daytime nap 226, Nighttime sleep 262.
      Abbreviations could be seen in .

      2.2 Ascertainment of twelve chronic diseases and multimorbidity

      According to the participants ' answers to question DA007 (Have you been diagnosed with… by a doctor?) in the health status and function questionnaire, whether the patients had chronic diseases was determined. A respondent with no less than two chronic diseases was considered to have multimorbidity [
      • Yao S.-S.
      • Cao G.-Y.
      • Han L.
      • et al.
      Prevalence and patterns of multimorbidity in a Nationally Representative Sample of Older Chinese: results from the China Health and Retirement Longitudinal Study.
      ]. The time of onset was determined according to question DA009 (When was the condition first diagnosed or known by yourself?). The onset time of the disease (earlier than 2011) was used as the baseline history of the disease, and the disease that occurred during the follow-up period in 2011 and beyond was considered as a new-onset disease event. New-onset chronic diseases during follow-up were considered to be endpoints in this study.

      2.3 Assessment of sleep duration

      We evaluate subjects’ sleep duration by records in the above questionnaire.
      Nighttime sleep duration(hour): Based on the answers to the question DA049 (During the past month, how many hours of actual sleep did you get at night (average hours for one night)? This may be shorter than the number of hours you spend in bed).
      Daytime nap duration(minute): Based on the answers to the question DA050 (During the past month, how long did you take a nap after lunch (minutes))?
      Groups of Nighttime sleep: (,5)hours, [5,7)hours, [7-9)hours, [9,)hours [
      • Li J.
      • Cacchione P.Z.
      • Hodgson N.
      • et al.
      Afternoon napping and cognition in Chinese older adults: findings from the China Health and Retirement Longitudinal Study Baseline Assessment.
      ]
      Groups of Daytime nap: 0 minutes, (0, 30] minutes, (30, 90] minutes, (90,) minutes [
      • Jing R.
      • Xu T.
      • Rong H.
      • Lai X.
      • Fang H.
      Longitudinal association between sleep duration and depressive symptoms in Chinese elderly.
      ]

      2.4 Covariates

      Physical examination indexes (age, sex, body mass index, systolic blood pressure, diastolic blood pressure) were included in this study. The middle-aged population was defined as 45≤age<60, and the elderly as age≥60. Habits of smoking (yes/no) and drinking (often/sometimes/never) were recorded in the study. According to the educational records of the interviewed population (BD001:" What is the highest level of education you have attained? "), we divided the population into four groups: illiterate, elementary school, middle school, and college. For each chronic disease cohort (except for multimorbidity defined by the number of diseases), the remaining 11 chronic disease histories at baseline were applied as confounding factors (A.1).

      2.5 Statistical methods

      Quantitative data of normal and non-normal distribution were expressed as mean ± SD and medians with interquartile range (IQR). Categorical data were presented as amounts with percentages, respectively. Comparisons of differences among sleep duration groups were analyzed by ANOVA and Kruskal–Wallis tests for continuous variables in line with normal and nonnormal distributions, respectively, and by chi-square tests for categorical variables. Descriptive statistics are presented for the proportion of 13 chronic diseases across age and sleep duration groups. Hazard ratios (HRs) and 95% confidence intervals (CIs) of daytime nap, daytime nap groups, nighttime sleep, and nighttime sleep groups from 2011 to 2018 for the risk of new-onset chronic diseases were estimated by Cox regression models and adjusted by covariates. We explored linear and potential nonlinear trends between sleep duration and HRs (95% CI) for new-onset chronic diseases with restricted cubic spline (RCS) regression with 3 knots and obtained the possible cutoff value of sleep duration (daytime nap and night sleep duration) for the risk of CDCs. Produce forest plots to visualize the different new-onset risks to CDCs of sleep duration groups. All calculations were performed, and graphics were created using R (version 3.6.3-Mac OS X 10.11). Two-tailed p values were used throughout the study, and p<0.05 was considered statistically significant.

      3. Results

      3.1 Basic characteristics and differences between middle-aged and elderly people at baseline

      A total of 7025 people participated in the study, including 4003 middle-aged people and 3022 elderly. Compared with the middle-aged, the elderly had less nighttime sleep duration (6.17vs.6.50 hours, p < 0.001), a greater number of diseases at baseline (1.41vs.1.07, p<0.001), a higher proportion of medical history of 8 CDCs (Table 1). In addition, there are significant differences in the proportion of sex, BMI, SBP, DBP, educational level, habits of smoking, and drinking between the two age groups (Table 1).
      Table 1Basic characteristics of the participants at baseline stratified by age groups in 2011.
      Stratified by Age (years)
      Divided the population into middle-aged (45≤ age< 60) and elderly (age ≥ 60) according to their age in 2011.
      Middle-agedThe elderlyP
      Quantitative data of normal and non-normal distribution were expressed as mean (SD) and medians with interquartile range (IQR). Categorical data were presented as amounts(percentages), respectively. Comparisons of differences among groups were respectively analyzed by ANOVA test and Kruskal-Wallis test for continuous variables in line with normal and non-normal distribution, and by Chi-square test for categorical variables. Abbreviations: BMI Body Mass Index, SBP Systolic Blood Pressure, DBP Diastolic Blood Pressure, PP Pulse Pressure, DM/Hglu diabetes or high blood sugar, Arth/Rheu Arthritis or Rheumatis.
      SMD
      N40033022
      Age52.48 (4.37)66.82 (5.79)<0.0012.797
      Sex =male (%)1729 (43.2)1463 (48.4)<0.0010.105
      BMI(Kg/m2)24.08 (3.89)23.05 (4.05)<0.0010.262
      SBP (mmHg)126.56 (20.00)133.85 (22.02)<0.0010.346
      DBP (mmHg)76.29 (12.37)74.57 (11.30)<0.0010.145
      Daytime nap(minutes)31.84 (42.70)33.84 (43.83)0.0540.046
      Nighttime sleep(hours)6.50 (1.75)6.17 (1.99)<0.0010.175
      Education=illiterate (%)877 (21.9)1082 (35.8)<0.0010.548
      =elementary (%)1520 (38.0)1426 (47.2)
      =middle (%)1560 (39.0)483 (16.0)
      =college (%)46 (1.1)31 (1.0)
      Smoke =yes (%)1467 (36.6)1240 (41.0)<0.0010.090
      Drink =often (%)1030 (25.7)741 (24.5)<0.0010.098
      =sometime (%)349 (8.7)193 (6.4)
      =never (%)2624 (65.6)2088 (69.1)
      Disease Number in 20111.07 (1.17)1.41 (1.37)<0.0010.262
      Medical History
      Heart disease (%)329 (8.2)455 (15.1)<0.0010.214
      Hypertension (%)750 (18.7)817 (27.0)<0.0010.199
      Stroke (%)96(2.4)120 (4.0)<0.0010.09
      DM/Hglu (%)212 (5.3)206 (6.8)0.0090.064
      Digestive disease (%)819 (20.5)636 (21.0)0.5680.014
      Cancer (%)49 (1.2)36 (1.2)0.9890.003
      Liver disease (%)190 (4.7)131 (4.3)0.4470.02
      Kidney disease (%)252 (6.3)226 (7.5)0.0570.047
      Lung disease (%)283 (7.1)387 (12.8)<0.0010.193
      Arth/Rheu (%)1179 (29.5)975 (32.3)0.0120.061
      Memory disease (%)33 (0.8)86 (2.8)<0.0010.151
      Asthma (%)96 (2.4)171 (5.7)<0.0010.166
      Multimorbidity (%)1148 (28.7)1195 (39.5)<0.0010.231
      a Divided the population into middle-aged (45≤ age< 60) and elderly (age ≥ 60) according to their age in 2011.
      b Quantitative data of normal and non-normal distribution were expressed as mean (SD) and medians with interquartile range (IQR). Categorical data were presented as amounts(percentages), respectively. Comparisons of differences among groups were respectively analyzed by ANOVA test and Kruskal-Wallis test for continuous variables in line with normal and non-normal distribution, and by Chi-square test for categorical variables.Abbreviations: BMI Body Mass Index, SBP Systolic Blood Pressure, DBP Diastolic Blood Pressure, PP Pulse Pressure, DM/Hglu diabetes or high blood sugar, Arth/Rheu Arthritis or Rheumatis.

      3.2 Baseline characteristics of participants stratified by groups of nighttime sleep and daytime nap

      A total of 1133, 2428, 2907, 557 participants were included in the nighttime sleep groups of <5, 5-7, 7-9, and>9 hours respectively, and 3329,1134,1748,814 participants were included in the daytime nap groups of 0, 0-30, 30-90 and>90 minutes respectively. Those with longer nighttime sleep duration had significantly longer daytime naps than those who slept less at night (Table A.1), and vice versa (Table A.2).
      In terms of the proportions of medical histories, among the nighttime sleep groups, except for DM/Hglu, Cancer, and liver disease, there were significant differences in the other nine CDCs. Meanwhile, among the daytime nap groups, there were significant proportion differences in heart disease, hypertension, stroke, DM/Hglu, Arth/Rheu, and multimorbidity.
      Follow up a total of 7025 participants for seven years and perform longitudinal cohort studies based on daytime sleep duration (Table A.3) and nighttime (Table A.4) to track the new onset incidents of 13 CDCs.

      3.3 Cox regression analysis of daytime nap duration for new-onset risk of thirteen CDCs

      The nap duration was an independent protective factor for new-onset kidney disease in the elderly (HR, 95%CI: 0.995, 0.91-0.999), but not in the middle-aged by covariate-adjusted Cox regression analysis (Table A.5). There was an overall negative linear relationship(p-nonlinear>0.05) between the increased length of daytime naps and the new-onset risk of kidney disease in the elderly by RCS regression (Fig. A.1). The risk of new-onset kidney disease increased slightly and then decreased as the nap's length increased, with a risk threshold of approximately 40 minutes. However, the duration of daytime naps was not significantly associated with the new-onset risk of the remaining 11 CDCs (Table A.5). Figs. A.1 and A.2 displayed the association between the length of the daytime nap and the new-onset risk of all diseases in middle-aged and elderly populations.

      3.4 Longitudinal associations between groups of daytime naps and new-onset risk of thirteen CDCs

      Compared with no nap, a 0-30-minute daytime nap was an independent risk factor for new-onset heart disease in the middle-aged (HR, 95%CI:1.413,1.087-1.837) and elderly (HR, 95%CI: 1.489, 1.125-1.972), meanwhile, it was independently associated with an increased new-onset risk of hypertension (HR, 95%CI:1.236,1.001-1.526) in the middle-aged people, but not in the elderly. In addition, 0-30 minutes (HR, 95%CI: 0.573,0.356-0.924) and >90 minutes (HR, 95%CI: 0.325,0.163-0.647) of daytime naps were both protective factors for the elderly's new-onset kidney disease risk, but they did not decrease that risk in middle-aged. A nap of >90 minutes significantly increased the new-onset risk of elderly's memory disease (HR, 95%CI: 1.620,1.015-2.586), but not in middle-aged adults (Tables A.3 and A.6; Fig. 2A).
      Fig 2
      Fig. 2Forest plots including HRs(95%CI) for the relationship between new-onset risks of 13 chronic diseases and sleep duration.
      (A) Forest plots for the HRs(95%CIs) of daytime nap groups in 2011 for new-onset risks of 13 chronic diseases.
      Take the group of no nap (0 minutes) as a reference and display facets based on age group.
      (B) Forest plots for the HRs(95%CIs) of nighttime sleep groups in 2011 for new-onset risks of 13 chronic diseases.
      Take the group of 7-9hours sleep duration as a reference and display facets based on age group.
      Models were all adjusted by age, sex, BMI, SBP, DBP, PP, smoke, and drink. In addition, considering the interrelationships between chronic diseases, we included 11 chronic diseases history as covariates (except for multimorbidity and cohort outcome event disease itself) in our subgroup analysis for each disease cohort to control for the effect of baseline medical history on outcome events when analyzing the risk of sleep duration on the new-onset chronic diseases. Specific covariate information for each model is available in Table A.5.
      Abbreviations could be seen in .

      3.5 Cox regression analysis of nighttime sleep duration for new-onset risk of thirteen chronic disease status

      By covariate-adjusted Cox regression analysis, the nighttime duration was an independent protective factor for new-onset DM/Hglu (HR, 95%CI: 0.939, 0.887-0.994) and memory disease (HR, 95%CI: 0.875, 0.772-0.992) in the middle-aged population, but not in the elderly. Meanwhile, it significantly diseased the risk of kidney disease in the elderly (HR, 95%CI: 0.895, 0.829-0.966) but not in middle-aged persons. Increased nighttime sleep duration was associated with a reduced risk of multimorbidity in both the middle-aged and elderly populations (Table A.7). As the nighttime sleep duration increased, the risk of new-onset chronic disease conditions generally decreased, with a risk threshold of approximately 7 hours in middle-aged people and 6 hours in the elderly (Figs. 3 and A.3).
      Fig 3
      Fig. 3The combined graphs of restricted cubic splines with 3 knots to flexibly model the association between the elderly's nighttime sleep in 2011 and HRs (95% CI) for their new-onset diseases and distribution density maps of their nighttime sleep in 2011 in each chronic disease subgroup cohort.

      3.6 Longitudinal associations between groups of nighttime sleep and new-onset risk of thirteen chronic disease status

      Cox regression analyses adjusted by confounders were performed to explore the association between groups of nighttime sleep and risk of chronic disease status. Compared with a group of 7-9 nightsleep duration, a short nightsleep of < 5 hours was a significant new-onset risk predictor for hypertension in the middle-aged population (HR,95%CI: 1.312,1.042-1.651), but not in the elderly. In addition, it also increased the new-onset risk of asthma only in the elderly and increased the risk for kidney disease and multimorbidity in both middle-aged and elderly populations. A 5-7hours nightsleep was associated higher risk of DM/Hglu(HR,95%CI: 1.456,1.155∼1.837) and multimorbidity(HR,95%CI: 1.306,1.098∼1.552) in the middle-aged persons. Especially, a long sleep duration at night (> 9 hours) decreased the elderly's risk of memory disease (HR,95%CI: 0.388,0.156∼0.970), but not in the middle-aged population (Tables 2 and A.4; Fig. 2B).
      Table 2Cox regression analysis of nighttime sleep groups in 2011 to the 7-year new-onset risk of thirteen chronic diseases.
      Middle-aged
      <5h5h-7h7h-9h>9h
      HR (95%CI)PHR (95%CI)PHR (95%CI) PHR (95%CI)P
      Heart disease1.052(0.768∼1.442)0.7531.179(0.949∼1.466)0.137reference0.868(0.578∼1.303)0.494
      Hypertension1.217(0.973∼1.523)0.0861.031(0.873∼1.218)0.719Reference1.014(0.763∼1.347)0.923
      Stroke1.438(0.903∼2.291)0.1261.436(1.016∼2.028)0.040Reference1.576(0.921∼2.698)0.097
      DM/Hglu1.453(1.067∼1.977)0.0181.477(1.174∼1.857)0.001Reference1.169(0.779∼1.754)0.452
      Digestive disease1.472(1.070∼2.025)0.0181.259(0.990∼1.601)0.060Reference1.067(0.697∼1.634)0.765
      Cancer1.873(0.835∼4.201)0.1281.672(0.888∼3.148)0.112reference1.360(0.458∼4.041)0.580
      Model1
      No adjusted
      Liver disease0.990(0.617∼1.590)0.9680.968(0.689∼1.360)0.853Reference0.652(0.327∼1.300)0.224
      Kidney disease1.664(1.129∼2.453)0.0101.251(0.918∼1.705)0.157reference1.274(0.765∼2.123)0.352
      Lung disease1.422(1.004∼2.014)0.0481.111(0.845∼1.460)0.451Reference1.183(0.756∼1.853)0.462
      Arth/Rheu1.118(0.805∼1.553)0.5061.091(0.870∼1.369)0.451Reference1.169(0.805∼1.697)0.411
      Memory disease1.837(0.963∼3.503)0.0651.585(0.953∼2.635)0.076Reference1.069(0.412∼2.776)0.891
      Asthma0.669(0.280∼1.600)0.3671.052(0.627∼1.765)0.848Reference0.891(0.347∼2.287)0.810
      Multimorbidity1.635(1.307∼2.047)<0.0011.329(1.119∼1.579)0.001Reference1.142(0.848∼1.537)0.381
      Heart disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      0.990(0.719∼1.363)0.9481.082(0.869∼1.346)0.483Reference0.889(0.591∼1.336)0.571
      Hypertension
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.312(1.042∼1.651)0.0210.975(0.823∼1.155)0.768Reference1.024(0.769∼1.365)0.869
      Stroke
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.418(0.880∼2.288)0.1521.346(0.950∼1.907)0.095Reference1.623(0.944∼2.791)0.080
      DM/Hglu
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.363(0.994∼1.868)0.0541.456(1.155∼1.837)0.002Reference1.182(0.785∼1.781)0.423
      Digestive disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.255(0.906∼1.738)0.1711.203(0.944∼1.533)0.135Reference1.051(0.684∼1.613)0.822
      Cancer
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.758(0.768∼4.023)0.1821.457(0.768∼2.764)0.249Reference1.486(0.496∼4.455)0.480
      Model2
      Considering the interrelationships between chronic diseases, we included 11 chronic diseases history as covariates (except for multimorbidity and cohort outcome event disease itself) in our subgroup analysis for each disease cohort to control for the effect of baseline medical history on outcome events when analyzing the risk of daytime nap duration on the new-onset chronic diseases.
      Liver disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      0.882(0.541∼1.440)0.6160.891(0.632∼1.256)0.509Reference0.682(0.341∼1.367)0.281
      Kidney disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.675(1.126∼2.491)0.0111.212(0.886∼1.657)0.229reference1.387(0.828∼2.320)0.214
      Lung disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, Arth/Rheu, memory disease, asthma)
      1.298(0.907∼1.859)0.1541.066(0.809∼1.404)0.651Reference1.203(0.766∼1.888)0.422
      Arth/Rheu
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, memory disease, asthma)
      1.046(0.750∼1.459)0.7921.062(0.845∼1.336)0.607Reference1.114(0.765∼1.622)0.574
      Memory disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, asthma)
      1.785(0.924∼3.447)0.0851.569(0.940∼2.620)0.085Reference1.131(0.433∼2.952)0.801
      Asthma
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease)
      0.616(0.255∼1.487)0.2810.985(0.585∼1.659)0.956Reference0.890(0.346∼2.293)0.809
      Multimorbidity
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education
      1.672(1.332∼2.098)<0.0011.306(1.098∼1.552)0.003Reference1.133(0.841∼1.526)0.413
      The elderly
      <5h5h-7h7h-9h>9h
      HR (95%CI)PHR (95%CI)PHR (95%CI) PHR (95%CI)P
      Heart disease1.263(0.959∼1.663)0.0971.103(0.861∼1.412)0.438reference0.911(0.597∼1.391)0.667
      Hypertension1.107(0.891∼1.376)0.3600.914(0.754∼1.109)0.362reference1.198(0.895∼1.602)0.225
      Stroke0.943(0.637∼1.396)0.7691.129(0.820∼1.555)0.457reference0.795(0.441∼1.435)0.447
      DM/Hglu1.154(0.841∼1.583)0.3761.133(0.859∼1.494)0.377reference1.132(0.730∼1.756)0.580
      Digestive disease1.670(1.193∼2.337)0.0031.353(0.999∼1.833)0.051reference1.542(0.989∼2.406)0.056
      Cancer0.725(0.281∼1.867)0.5051.018(0.492∼2.110)0.961reference1.512(0.549∼4.159)0.424
      Model1
      No adjusted
      Liver disease1.153(0.710∼1.885)0.5701.075(0.697∼1.657)0.745reference0.761(0.341∼1.696)0.504
      Kidney disease1.604(1.081∼2.381)0.0191.430(0.999∼2.048)0.051reference0.857(0.436∼1.685)0.655
      Lung disease1.411(1.025∼1.943)0.0350.981(0.725∼1.327)0.900reference1.147(0.725∼1.814)0.559
      Arth/Rheu1.111(0.782∼1.580)0.5561.020(0.754∼1.381)0.896reference1.002(0.611∼1.646)0.992
      Memory disease1.074(0.704∼1.641)0.7400.912(0.623∼1.334)0.634reference0.393(0.158∼0.979)0.045
      Asthma1.893(1.131∼3.167)0.0151.360(0.837∼2.211)0.215reference1.417(0.671∼2.994)0.361
      Multimorbidity1.311(1.055∼1.629)0.0151.105(0.910∼1.341)0.313reference1.020(0.747∼1.393)0.902
      Heart disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.136(0.857∼1.504)0.3751.065(0.830∼1.366)0.620reference0.956(0.624∼1.463)0.835
      Hypertension
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.064(0.849∼1.332)0.5910.915(0.754∼1.112)0.372reference1.067(0.794∼1.433)0.667
      Stroke
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      0.941(0.630∼1.405)0.7651.159(0.840∼1.600)0.368reference0.742(0.409∼1.344)0.325
      DM/Hglu
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.144(0.828∼1.581)0.4131.113(0.843∼1.471)0.450reference1.174(0.753∼1.832)0.479
      Digestive disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.516(1.077∼2.135)0.0171.315(0.969∼1.785)0.079reference1.523(0.973∼2.385)0.066
      Cancer
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      0.717(0.271∼1.896)0.5030.969(0.464∼2.022)0.933reference1.582(0.570∼4.390)0.379
      Model2
      Considering the interrelationships between chronic diseases, we included 11 chronic diseases history as covariates (except for multimorbidity and cohort outcome event disease itself) in our subgroup analysis for each disease cohort to control for the effect of baseline medical history on outcome events when analyzing the risk of daytime nap duration on the new-onset chronic diseases.
      Liver disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.201(0.725∼1.988)0.4771.048(0.677∼1.624)0.833reference0.877(0.392∼1.964)0.750
      Kidney disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, lung disease, Arth/Rheu, memory disease, asthma)
      1.670(1.112∼2.508)0.0131.421(0.990∼2.040)0.057reference0.937(0.475∼1.849)0.851
      Lung disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, Arth/Rheu, memory disease, asthma)
      1.368(0.985∼1.900)0.0621.013(0.747∼1.372)0.936reference1.133(0.714∼1.800)0.600
      Arth/Rheu
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, memory disease, asthma)
      1.021(0.713∼1.464)0.1151.034(0.762∼1.405)0.216reference1.027(0.624∼1.692)0.106
      Memory disease
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, asthma)
      1.012(0.656∼1.560)0.9590.893(0.609∼1.310)0.562reference0.388(0.156∼0.970)0.043
      Asthma
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease)
      1.809(1.069∼3.059)0.0271.319(0.810∼2.148)0.266reference1.591(0.748∼3.382)0.228
      Multimorbidity
      Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education
      1.303(1.045∼1.626)0.0191.120(0.922∼1.359)0.254reference1.014(0.742∼1.387)0.929
      1 No adjusted
      2 Considering the interrelationships between chronic diseases, we included 11 chronic diseases history as covariates (except for multimorbidity and cohort outcome event disease itself) in our subgroup analysis for each disease cohort to control for the effect of baseline medical history on outcome events when analyzing the risk of daytime nap duration on the new-onset chronic diseases.
      3 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      4 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      5 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      6 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      7 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      8 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      9 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, kidney disease, lung disease, Arth/Rheu, memory disease, asthma)
      10 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, lung disease, Arth/Rheu, memory disease, asthma)
      11 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, Arth/Rheu, memory disease, asthma)
      12 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, memory disease, asthma)
      13 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, asthma)
      14 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education, and 11 medical histories (heart disease, hypertension, stroke, DM/Hglu, digestive disease, cancer, liver disease, kidney disease, lung disease, Arth/Rheu, memory disease)
      15 Adjusted by age, sex, BMI, SBP, DBP, PP, smoke, drink, Education

      4. Discussion

      This large prospective cohort study revealed risk associations and differences in nighttime sleep and daytime nap duration for new-onset CDCs in middle-aged and elderly:
      • a
        There is a significant negative linear relationship between daytime nap duration and the new-onset risk of chronic kidney disease in the elderly. The risk of new-onset chronic diseases roughly decreases with the increase in nighttime sleep duration, and the risk threshold is 7 hours in the middle-aged and 6 hours in the elderly, respectively.
      • b
        For middle-aged and elderly people, compared with no nap, 0-30 minutes of daytime nap is an independent risk factor for new-onset heart disease; compared with 7-9 hours of nighttime sleep, <5 hours of sleep is a predictor for new-onset kidney disease.
      • c
        For middle-aged people, not the elderly, 0-30 minutes of a nap and <5 hours of nighttime sleep were risk factors for new-onset hypertension; 5-7 hours of nighttime sleep increased the new-onset risk of DM/Hglu and multimorbidity.
      • d
        For the elderly, but not middle-aged, a 0-30 minutes nap was a protective factor for new-onset chronic kidney disease. A nap of >90 minutes significantly increased the new-onset risk of memory disease. The nighttime sleep of < 5 hours was associated with a higher risk of chronic kidney disease and asthma. Nighttime sleep >9 hours significantly reduced the risk of developing memory diseases.
      Sleep duration decreased with age [
      • Dijk D.-J.
      • Groeger J.A.
      • Stanley N.
      • Deacon S.
      Age-related reduction in daytime sleep propensity and nocturnal slow wave sleep.
      ,
      • Feinsilver S.H.
      Normal and abnormal sleep in the elderly.
      ]. Healthy elderly people are more tolerant of sleep deprivation than young elderly people [
      • Duffy J.F.
      • Willson H.J.
      • Wang W.
      • Czeisler C.A.
      Healthy older adults better tolerate sleep deprivation than young adults.
      ]. The physiological mechanism may explain that: The number of ventrolateral preoptic nuclei of the hypothalamus decreases with age, resulting in a reduction in sleep time in physiological [
      • Duffy J.F.
      • Willson H.J.
      • Wang W.
      • Czeisler C.A.
      Healthy older adults better tolerate sleep deprivation than young adults.
      ]. That suggested the need to separately investigate the effect of sleep duration on the risk of new-onset CDCs in middle-aged and the elderly, and the physiological basis for this risk difference. Consistently with this, we found that 7 hours and 6 hours were the risk thresholds for new-onset CDCs in the middle-aged and the elderly, respectively. Therefore, it may be unreasonable to analyze the relationship between sleep duration and CDCs by ignoring aging.
      A SNAC-K survey found that sleep disturbances were associated with a faster rate of developing multimorbidity in people (age>60) [
      • Sindi S.
      • Pérez L.M.
      • Vetrano D.L.
      • et al.
      Sleep disturbances and the speed of multimorbidity development in old age: results from a longitudinal population-based study.
      ]. A cross-sectional study from KORA revealed that short daily sleep duration was significantly associated with multimorbidity in the elderly (age range 65-93) [
      • Helbig A.K.
      • Stöckl D.
      • Heier M.
      • et al.
      Relationship between sleep disturbances and multimorbidity among community-dwelling men and women aged 65-93 years: results from the KORA Age Study.
      ]. Our study confirmed that shorter nighttime sleep duration was an independent new-onset risk factor for multimorbidity. However, the specific sleep length that manifested risk was not consistent across age groups: when sleep duration was less than 7 hours, the risk increased significantly in middle-aged, but in the elderly, a similar risk profile could be observed when sleep duration was less than 5 hours.
      Multiple previous studies have shown that short sleep duration appears to increase the risk of cardiovascular-related events [
      • Wang C.
      • Bangdiwala S.I.
      • Rangarajan S.
      • et al.
      Association of estimated sleep duration and naps with mortality and cardiovascular events: a study of 116 632 people from 21 countries.
      ,
      • Zhang B.
      • Wang Y.
      • Liu X.
      • et al.
      The association of sleep quality and night sleep duration with coronary heart disease in a large-scale rural population.
      ]. Another study (age from 18-98) found no significant association between night sleep duration and myocardial infarction [
      • Wang X.
      • Liu X.
      • Song Q.
      • Wu S.
      Sleep duration and risk of myocardial infarction and all-cause death in a Chinese population: the Kailuan study.
      ]. The populations in these studies spanned a wide age range, which may lead to age-mediated links between shorter sleep duration and increased risk of heart disease. No association was found between the new-onset risk of heart disease and nighttime sleep duration in this study. But there is a significant association between that risk and a 0–30-minute nap among middle-aged and the elderly, which agreed with the previous study that there were adverse effects of naps on serious cardiovascular-related events [
      • Wang C.
      • Bangdiwala S.I.
      • Rangarajan S.
      • et al.
      Association of estimated sleep duration and naps with mortality and cardiovascular events: a study of 116 632 people from 21 countries.
      ,
      • Cohen-Mansfield J.
      • Perach R.
      Sleep duration, nap habits, and mortality in older persons.
      ].
      A study of 4810 Americans(age from 48-59) found that short nighttime sleep was 60% associated with an increased hypertension risk [
      • Gangwisch J.E.
      • Heymsfield S.B.
      • Boden-Albala B.
      • et al.
      Short sleep duration as a risk factor for hypertension: analyses of the first National Health and Nutrition Examination Survey.
      ]. Meanwhile, another study (participants aged 58-98) found no association between nighttime sleep and hypertension or blood pressure changes [
      • van den Berg J.F.
      • Tulen J.H.M.
      • Neven A.K.
      • et al.
      Sleep duration and hypertension are not associated in the elderly.
      ]. A Spanish study (age >60) reported the same conclusion [
      • Lopez-Garcia E.
      • Faubel R.
      • Guallar-Castillon P.
      • Leon-Muñoz L.
      • Banegas J.R.
      • Rodriguez-Artalejo F.
      Self-reported sleep duration and hypertension in older Spanish adults.
      ]. In our study, this link was not observed in the elderly, either. And it was found that a short night's sleep duration for increased hypertension risk in the middle-aged. The biological relationship between nighttime sleep and hypertension is not clear. A link between sleep apnea and hypertension only exists in middle-aged people [
      • Haas D.C.
      • Foster G.L.
      • Nieto F.J.
      • et al.
      Age-dependent associations between sleep-disordered breathing and hypertension: importance of discriminating between systolic/diastolic hypertension and isolated systolic hypertension in the Sleep Heart Health Study.
      ] may partly explain why a significant association between short sleep duration and increased hypertension risk was found in middle-aged people only.
      Japanese cohort studies reported the lowest risk of chronic kidney disease with sleep duration <6 hours [
      • Nakajima H.
      • Hashimoto Y.
      • Okamura T.
      • et al.
      Association between sleep duration and incident chronic kidney disease: a population-based cohort analysis of the NAGALA study.
      ]. A prospective cohort (age > 20) from Taiwan found a "U"-shaped dose association: Both <6 and >8 hours of sleep increased the risk of kidney disease [
      • Bo Y.
      • Yeoh E.K.
      • Guo C.
      • et al.
      Sleep and the risk of chronic kidney disease: a cohort study.
      ]. In the present study, a shorter nighttime sleep duration (<5 hours), but not a longer sleep duration (>9 hours), was an independent risk factor for new-onset kidney disease in the middle-aged and the elderly. In addition, for the first time, we found the protective effect of the nap on new-onset nephropathy in the elderly. That means that a daytime nap may act as a compensatory measure to reduce the risk of new-onset kidney disease from sleep deprivation at night.
      Our study found that a long duration of sleep at night significantly reduced the risk of memory disease in the elderly, whereas prolonged daytime naps significantly increased this risk. This phenomenon has not been captured in the middle-aged population. That suggests a link between sleep, especially nighttime sleep, for memory consolidation, memory recovery, cognitive protection, and neuronal repair in the brain [
      • Muehlroth B.E.
      • Rasch B.
      • Werkle-Bergner M.
      Episodic memory consolidation during sleep in healthy aging.
      ]. Long daytime naps may compete for nighttime sleep duration and counteract this physiological effect on cognitive memory protection. Several studies have confirmed that sleep helps consolidate memories, while sleep deprivation increases the formation of false memories [
      • Lo J.C.
      • Chong P.L.
      • Ganesan S.
      • Leong R.L.
      • Chee M.W.
      Sleep deprivation increases formation of false memory.
      ]. However, large-scale cohort studies on the effects of daytime and nighttime sleep on the risk of long-term memory-related disorders are lacking.
      As we know, the current study is the first to investigate the age-stratified effects of daytime and nighttime sleep duration on the new-onset risk of CDCs in the middle-aged or the elderly, respectively, and how these effects differ with aging. That provided a pragmatic theoretical basis for establishing sleep management strategies, which vary in process of aging and different disease conditions. However, all sleep features are self-reported in this study, which may lead to potential misclassifications. In addition, a long daytime nap may reduce the duration of sleep at night and compensate lack of night sleep at the same time. There was an interaction between nighttime and daytime sleep duration that is difficult to completely disentangle in the analysis, which may overestimate or underestimate the risk effect of nighttime sleep or daytime nap on diseases. Exploring the overall, rational physiological effects of a 24-hour sleep pattern is the focus of our further study.

      Author contributions

      We thank all the researchers who contributed to this article: Conceptualization and Funding Acquisition: Niuniu Hou and WeiLi; Investigation, Methodology, Project Administration: Yaoling Wang, Minfang Chen, and Kang Yang; Software and Visualization: Yaoling Wang and KaiWen; Art and Drawing Instruction: Yujie Lan; Writing-Original Draft Preparation: Yaoling Wang, Niuniu Hou, and Gege Jiang; Writing-Review & editing: Yaoling Wang and Niuniu Hou.

      Availability of data and materials

      The data that support the findings of this study are available from http://charls.pku.edu.cn/index/zh-cn.html. Restrictions apply to the availability of these data, which were used under license for this study. Data are available from the authors with the permission of National Development Institute, Peking University

      Declaration of Competing Interest

      None.

      Funding

      This study was supported by the National Natural Science Foundation of China to W.L. (Grant No. 81974113 ).

      Acknowledgments

      Also, special thanks to all members of the CHARLS research team, all fieldworkers, and every interviewee.

      Appendix. Supplementary materials

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