The Joint Effects of Sleep Duration and Exercise Habit on All-cause Mortality among Chinese Elderly: A National Community-Based Cohort Study

The Joint Effects of Sleep Duration and Exercise Habit on All-cause Mortality among Chinese Elderly: A National Community-Based Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Joint Effects of Sleep Duration and Exercise Habit on All-cause Mortality among Chinese Elderly: A National Community-Based Cohort Study Na LI, Kexin REN, Yuan TAO This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5419153/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study investigates the combined impact of sleep duration and exercise habits on all-cause mortality among the elderly population in China, utilizing data from 7,231 residents aged 60 and above from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Participants were categorized based on their exercise habits and sleep duration, which were analyzed over three follow-ups (2011, 2014, and 2018). The findings revealed that normal sleep (6-8 hours) correlated with a 20% reduction in mortality risk compared to short sleepers, while long sleep (over 8 hours) was linked to a 29% increase in mortality risk. Exercise significantly affected mortality; active individuals had a reduced risk, and those transitioning from inactivity to activity saw a 12% reduction in mortality. Notably, among short sleepers, exercise habits did not significantly impact mortality for either sex. However, for those with normal or long sleep, both men and women experienced significant mortality benefits from regular exercise. Additionally, older women moving from a sedentary lifestyle to physical activity during periods of long sleep demonstrated lower mortality rates. This research highlights the importance of both sleep and exercise in influencing health outcomes, with notable gender differences in their combined effects on mortality risk. Sleep duration Exercise habit All-cause mortality Chinese elderly CLHLS Figures Figure 1 1. Introduction Sleep duration and exercise habits are critical lifestyle factors that significantly influence health outcomes, particularly among the elderly population. As modifiable lifestyle factors, both sleep and physical activity have been associated with improved health and longevity[1][2]. With the rapid increase in the elderly population in China[3], understanding how these two factors impact health within this demographic is of utmost importance. While previous studies have thoroughly examined the individual effects of sleep and exercise on health outcomes, the combined or joint effects of these factors are less explored, particularly in the context of the Chinese elderly population. The Seniors-ENRICA cohort study in Spain demonstrated that appropriate physical activity mitigates the impact of poor sleep duration on mortality among older adults[4]. Similarly, the UK Biobank study found that physical activity and sleep duration interacted with the risk of all-cause mortality, as measured by accelerometers[5]. In contrast, a Brazilian study indicated that resting activity rhythms were not significantly associated with mortality, suggesting that physical activity might be an influencing factor[6]. Notably, there was only one relevant study involving Chinese older adults[7], which provided insights into the association between sleep scores and leisure-time physical activity with all-cause mortality. This study emphasized the potential benefits of improved sleep and increased physical activity in reducing mortality; however, it was conducted on retired employees of the Dongfeng-Tongji (DFTJ) Group and did not represent a nationwide sample. The results of these studies suggest that physical activity and sleep may interact through different mechanisms, collectively affecting the health and longevity of older adults. Therefore, further research is needed to gain a deeper understanding of the joint effects of these factors across different populations, particularly among the Chinese elderly. The imperative to study the health behaviors and outcomes among China's elderly is underscored by their rapidly growing demographic, a trend attributed to enhanced life expectancies and declining birth rates[8].This substantial demographic shift not only poses challenges to the public health and healthcare systems but also necessitates a tailored approach to health promotion and disease prevention. The unique cultural practices and health beliefs within this population may significantly influence their sleep and exercise habits, which are critical factors in determining health outcomes[9].Understanding these nuances is essential for developing effective and culturally sensitive interventions to support the health and well-being of China's elderly. The aim of this study is to investigate the joint effects of sleep duration and exercise habits on all-cause mortality in older adults in China, along with the associated mechanisms of action. This study will employ a national community-based cohort design and will be the first to examine how changes in exercise habits and sleep duration impact all-cause mortality. The findings will provide valuable insights into the most effective combinations of sleep and exercise. Additionally, these results may inform public health interventions targeting the elderly population in China and contribute significantly to our understanding of how sleep and exercise can be leveraged to improve health outcomes in this demographic. 2. Methods 2.1 Data sources The data for this study are derived from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which is the largest cohort study focusing on the elderly population in China. This study was organized by the Centre for Healthy Ageing and Development at Peking University in collaboration with the National Institute for Development Research. The CLHLS encompasses 23 provinces, municipalities, and autonomous regions, with a total of 113,000 household interviews conducted. Approximately half of the cities and counties in 22 of the research provinces (excluding Hainan Province) were randomly selected as research sites. The survey received approval from the Institutional Review Board of Peking University (IRB00001052-13074), and all participants, or their legal representatives, provided written informed consent. We utilized a sample of individuals aged 60 and older from the 2011 follow-up study, and all participants were evaluated again in 2014 and 2018, with ongoing monitoring until their death, loss to follow-up, or the end of the study. Participants with incomplete records were excluded from the analysis. The final sample size for analysis is 7,231 (refer to SFig. 1). 2.2 Variable Measurement 2.2.1 Exposure In the survey, participants were asked, “Do you exercise frequently at present?” and “Did you exercise frequently in the past?” Based on their answers to these two questions, participants were classified into four groups: 1) physically active if they exercised frequently both in the past and now, 2) physically inactive if they did not exercise frequently either in the past or the present, 3) inactive-to-active if they did not exercise frequently in the past but do so now, and 4) active-to-inactive if they exercised frequently in the past but are not currently active[10]. Sleep duration (in hours) was defined as the amount of sleep reported by the participant in the self-reported questionnaire. The exact amount of time was based on the following question: “How many hours of sleep do you currently get on a typical day?”Using restricted cubic spline curves and threshold effect analyses[11], we determined that the threshold of sleep time associated with all-cause mortality was 8 hours (SFig. 2).Based on the threshold effects and classifications from previous studies[12][13], we categorized sleep duration into three groups: short sleep ( 8 hours). 2.2.2 Outcome The outcome of this study was all-cause mortality. Data on participant survival and date of death were collected during three rounds of follow-up in 2011, 2014, and 2018. Participants who remained alive or were lost to follow-up were assessed based on the most recent point of contact (30 December 2018). 2.2.3 Covariates Based on previous studies of physical activity and mortality, as well as sleep duration and mortality, we included a variety of covariates that might influence the results: age(60~70,70~80,>80),gender(male,female),marital(married,others),education years(continuous), smoke(yes,no)[14],drink(yes,no)[15],Self-assessed health (very bad,bad,fair,good,very good )[16], BMI(continuous)[17]. 2.3 Statistical analysis The baseline characteristics of 7,231 participants were described based on sleep duration, with categorical variables expressed as frequencies and percentages, and quantitative variables expressed as means with standard deviations (SD).Comparison of baseline characteristics among sleep duration categories was performed using the χ2 test and 1-way analysis of variance for categorical and continuous variables, respectively.We first analyzed the effect of sleep duration and exercise habits on all-cause mortality using multi-model cox regression: Model 1 without covariates, Model 2 with covariates including age, gender, education, and marital status, and Model 3 with covariates including age, gender, education, marital status, smoking, drinking, health status, and BMI. We then further analysed the joint effect of sleep duration and exercise habits on all-cause mortality using stratified analyses by sex and interaction analyses. Data processing and analysis were performed using R version 4.3.0, along with the Storm Statistical Platform (www.medsta.cn/software). A 2-tailed P<0.05 was considered to be statistically significant. 3. Results 3.1. Basic characteristics Table 1 shows the basic characteristics of participants based on sleep duration.Of the total sample of 7,231 participants, there were 1,120 short sleepers (i.e., those sleeping less than 6 hours), 3,743 normal sleepers (6 to 8 hours), and 2,368 long sleepers (more than 8 hours). Further analyses revealed that the proportion of both short and long sleepers increased among individuals aged over 80 compared to those with normal sleep duration. Additionally, the ratio of long sleepers to short sleepers was relatively higher in the male group.Regarding marital status, the proportion of long sleepers versus short sleepers was notably higher among individuals who were unmarried or in other non-married categories. Non-smokers also exhibited a higher-than-average ratio of long to short sleepers. In terms of drinking habits, drinkers showed a significantly higher proportion of long sleepers.Moreover, it is worth noting that individuals who reported a Self-assessed health of "good" or above had a significantly higher proportion of long sleepers as well. All of the observed differences are statistically significant (p < 0.05). Table 1 Baseline characteristics of older adults stratified by sleep duration in CLHLS 2011–2018 Variables Total (n = 7231) Short sleep (n = 1120) Normal sleep (n = 3743) Long sleep (n = 2368) Statistic* P Age, n(%) χ²=221.62 80 4529 (62.63) 721 (64.38) 2076 (55.46) 1732 (73.14) Gender, n(%) χ²=42.28 < .001 Female 3371 (46.62) 426 (38.04) 1837 (49.08) 1108 (46.79) Male 3860 (53.38) 694 (61.96) 1906 (50.92) 1260 (53.21) Marital status, n(%) χ²=101.28 < .001 Others 4378 (60.54) 701 (62.59) 2067 (55.22) 1610 (67.99) Married 2853 (39.46) 419 (37.41) 1676 (44.78) 758 (32.01) Education(y), Mean ± SD 2.49 ± 3.63 1.99 ± 3.17 2.86 ± 3.83 2.14 ± 3.42 F = 41.63 < .001 Smoke, n(%) χ²=9.60 0.008 No 5806 (80.29) 929 (82.95) 2958 (79.03) 1919 (81.04) Yes 1425 (19.71) 191 (17.05) 785 (20.97) 449 (18.96) Drink, n(%) χ²=7.70 0.021 No 5884 (81.37) 943 (84.20) 3039 (81.19) 1902 (80.32) Yes 1347 (18.63) 177 (15.80) 704 (18.81) 466 (19.68) Health, n(%) χ²=190.29 < .001 Very bad 86 (1.19) 28 (2.50) 37 (0.99) 21 (0.89) Bad 1121 (15.50) 297 (26.52) 509 (13.60) 315 (13.30) Fair 2646 (36.59) 428 (38.21) 1406 (37.56) 812 (34.29) Good 2560 (35.40) 292 (26.07) 1343 (35.88) 925 (39.06) Very good 818 (11.31) 75 (6.70) 448 (11.97) 295 (12.46) BMI, Mean ± SD 22.08 ± 23.10 21.77 ± 9.71 22.51 ± 30.55 21.56 ± 10.44 F = 1.33 0.264 Exercise, n(%) χ²=60.68 < .001 Inactive 3525 (48.75) 561 (50.09) 1803 (48.17) 1161 (49.03) Active 1189 (16.44) 137 (12.23) 730 (19.50) 322 (13.60) Inactive-to-Active 1649 (22.80) 284 (25.36) 795 (21.24) 570 (24.07) Active-to-Inactive 868 (12.00) 138 (12.32) 415 (11.09) 315 (13.30) # Percentage of categorical variables *The χ2 test was used for categorical variables and analysis of variance for continuous variables. 3.2 Multi-model cox regression analysis In this study, we delved into the impacts of sleep duration and diverse exercise habits on all-cause mortality by employing multi-model COX regression analysis. Table 2 presents the findings from three distinct models (Model 1, Model 2, and Model 3), each incorporating various combinations of variables. Initially, we discerned a notable influence of sleep duration on all-cause mortality. Specifically, normal sleep duration (ranging from 6 to 8 hours) exhibited a 20% reduction in mortality compared to short sleep (< 6 hours) in Model 1, with statistical significance (p 8 hours) consistently correlated with an elevated risk of all-cause mortality across all models, with Model 3 indicating a 29% increase in mortality. Notably, the P-values for this association were universally below 0.001, affirming its statistical significance. Furthermore, our analysis unveiled a significant impact of exercise habits on all-cause mortality. Across all models, maintaining an exercise routine was associated with a decreased risk of all-cause mortality, as evidenced by HR below 1.00 and P-values less than 0.001, compared to those who did not exercise. Additionally, we scrutinized the effects of transitions in exercise habits. The transition from inactivity to activity was uniformly linked to a lower risk of all-cause mortality, highlighting its positive influence on mortality reduction (Model 3 demonstrated a 12% reduction). In stark contrast, shifting from an active to an inactive lifestyle was consistently associated with an increased risk of all-cause mortality across all models. While Model 3's P-value for this association hovered near the significance threshold of 0.05 (HR = 1.14, 95% CI: 0.99–1.32, P = 0.076), suggesting a potential negative impact on mortality, this correlation did not attain statistical significance. Table 2 Effect of sleep duration and different exercise habits on all-cause mortality in CLHLS 2011–2018 Variables Model1 Model2 Model3 HR (95%CI) P HR (95%CI) P HR (95%CI) P Sleep Duration Short sleep < 6h 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) Normal sleep 6-8h 0.80 (0.72 ~ 0.89) 8h 1.32 (1.19 ~ 1.47) < .001 1.28 (1.15 ~ 1.43) < .001 1.29 (1.16 ~ 1.43) < .001 Exercise Inactive 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) Active 0.62 (0.56 ~ 0.70) < .001 0.73 (0.65 ~ 0.82) < .001 0.73 (0.65 ~ 0.82) < .001 Inactive to Active 0.81 (0.74 ~ 0.88) < .001 0.88 (0.80 ~ 0.96) 0.005 0.88 (0.80 ~ 0.96) 0.006 Active to Inactive 1.20 (1.08 ~ 1.33) < .001 1.09 (0.98 ~ 1.21) 0.110 1.10 (0.99 ~ 1.22) 0.076 HR: Hazard Ratio, CI:Confidence Interval Model1: Crude Model2: Adjust: age, gender, education, marital Model3: Adjust: age, gender,education, marital status, smoke, drink, health, BMI 3.3 Joint effects of sleep duration and exercise habits on all-cause mortality To further investigate the combined influence of sleep duration and exercise habits on all-cause mortality, we conducted sex-stratified analyses and interaction analyses. Table 3 provides a detailed breakdown of how these factors jointly affect all-cause mortality among older men.Among those with short sleep duration, transitioning from an inactive to an active lifestyle was found to significantly elevate all-cause mortality (HR = 1.571, P = 0.032). Notably, after adjusting the model, a significant interaction between sleep duration and exercise habits emerged (P = 0.039).In contrast, during normal sleep duration, individuals who remained active showed a marked reduction in mortality compared to those who were inactive, both before and after model adjustment. Specifically, after model adjustment, the active group experienced a 26.2% decrease in mortality (HR = 0.738, P = 0.007). Furthermore, a significant interaction between normal sleep duration and exercise habits was observed both before and after model adjustment (P < 0.001).For those with long sleep duration, although the active group demonstrated a lower mortality rate compared to the inactive group both before and after model adjustment, no significant interaction effect was observed between sleep duration and exercise habits. This finding remained consistent across both unadjusted and adjusted models. Table 3 The joint effects of exercise habits and sleep durationon all-cause mortality in elderly Chinese men Variables Unadjusted model Adjusted model* HR (95% CI) P HR (95% CI) P Short sleep < 6h (N = 426) Inactive 1.00(Reference) 1.00(Reference) Active 1.151(0.759 ~ 1.747) 0.508 1.560(1.003 ~ 2.427) 0.051 Inactive to Active 1.024(0.725 ~ 1.447) 0.893 1.157(0.807 ~ 1.658) 0.427 Active to Inactive 1.538(1.024 ~ 2.312) 0.038 1.571(1.039 ~ 2.377) 0.032 P for interaction 0.412 0.039 Normal sleep 6-8h (N = 1837) Inactive 1.00(Reference) 1.00(Reference) Active 0.695(0.564 ~ 0.857) 0.001 0.738(0.593 ~ 0.919) 0.007 Inactive to Active 0.900(0.737 ~ 1.098) 0.299 0.898(0.734 ~ 1.098) 0.295 Active to Inactive 1.327(1.058 ~ 1.664) 0.014 0.970(0.770 ~ 1.221) 0.794 P for interaction 8h (N = 1108) Inactive 1.00(Reference) 1.00(Reference) Active 0.755(0.597 ~ 0.956) 0.020 0.740(0.579 ~ 0.946) 0.016 Inactive to Active 0.929(0.758 ~ 1.138) 0.477 0.919(0.749 ~ 1.128) 0.419 Active to Inactive 1.065(0.832 ~ 1.363) 0.616 0.989(0.769 ~ 1.271) 0.930 P for interaction 0.265 0.905 *Adjusted model to add covariates age, gender,education, marital, smoke, drink, health, BMI In contrast, Chinese elderly women exhibited a distinct pattern regarding the joint effects of sleep duration and exercise habits on all-cause mortality compared to their male counterparts, as illustrated in Table 4 . For those with short sleep duration, although elderly women who maintained exercise habits experienced a significant decrease in mortality in the unadjusted model, this relationship vanished entirely after model adjustment. Additionally, it is noteworthy that no significant interaction between sleep duration and exercise habits was observed in this short sleep duration group. When sleep duration falls within the normal range, the active elderly women demonstrated a significant reduction in mortality rates both before and after model adjustment. Specifically, after adjusting for covariates, the mortality rate in the activity group declined by 43.1% (HR = 0.569, P = 0.001). Furthermore, elderly women who transitioned from exercise to inactivity experienced a 32.1% increase in mortality rate (HR = 1.321, P = 0.014) after adjustment. Importantly, there was a significant interaction between sleep duration and exercise habits both before and after model adjustment in this normal sleep duration group (P < 0.001). For elderly women with long sleep duration, the active group also exhibited a significant reduction in mortality rates, a finding that remained consistent across both unadjusted and adjusted models, indicating high stability. Moreover, those who transitioned from inactivity to active habits showed a downward trend in mortality rates, which persisted before and after model adjustment. However, no significant interaction was observed between sleep duration and exercise habits within the long sleep duration group. Table 4 The joint effects of physical activity and sleep durationon all-cause mortality in elderly Chinese women Variables Unadjusted model Adjusted model* HR (95% CI) P HR (95% CI) P Short sleep < 6h (N = 694) Inactive 1.00(Reference) 1.00(Reference) Active 0.654(0.430 ~ 0.996) 0.048 0.837(0.542 ~ 1.291) 0.420 Inactive to Active 0.748(0.561 ~ 0.997) 0.048 0.892(0.665 ~ 1.197) 0.447 Active to Inactive 1.096(0.774 ~ 1.553) 0.606 1.127(0.789 ~ 1.608) 0.512 P for interaction 0.972 0.763 Normal sleep 6-8h (N = 1906) Inactive 1.00(Reference) 1.00(Reference) Active 0.695(0.564 ~ 0.857) 0.001 0.697(0.538 ~ 0.902) 0.006 Inactive to Active 0.900(0.737 ~ 1.098) 0.299 0.874(0.711 ~ 1.075) 0.202 Active to Inactive 1.327(1.058 ~ 1.664) 0.014 1.321(1.058 ~ 1.650) 0.014 P for interaction < .001 8h (N = 1260) Inactive 1.00(Reference) 1.00(Reference) Active 0.525(0.381 ~ 0.725) < .001 0.569(0.412 ~ 0.787) 0.001 Inactive to Active 0.721(0.595 ~ 0.875) 0.001 0.788(0.649 ~ 0.958) 0.017 Active to Inactive 1.088(0.873 ~ 1.356) 0.454 1.084(0.867 ~ 1.354) 0.479 P for interaction 0.096 0.266 *Adjusted model to add covariates age, gender,education, marital, smoke, drink, health, BMI The results presented above are illustrated more clearly in Fig. 1 . For those with short sleep duration, the impact of exercise habits on mortality was not significant for either men or women. However, for individuals with normal and prolonged sleep, both males and females experienced a significant reduction in mortality by maintaining exercise habits. Additionally, older women who transitioned from a sedentary lifestyle to regular exercise during long sleep duration also exhibited lower mortality rates. 4. Disscusion The aim of this study was to investigate the joint effects of sleep duration and exercise habits on all-cause mortality in Chinese older adults. We analysed the effects of sleep duration and exercise habits on mortality separately, and further explored the joint effect of the two in order to gain a deeper understanding. First, regarding the impact of sleep duration on mortality, we found that long sleep duration in older adults from China is significantly associated with an increased risk of mortality, aligning with existing literature that highlights the negative health implications of extreme sleep variations. Although adequate sleep is beneficial, prolonged sleep may indicate underlying health issues such as chronic diseases[ 18 ] and depression[ 19 ]. Even after adjusting for covariates, the relationship between long sleep and increased mortality remained significant. Mechanisms may include reduced physical activity[ 20 ], raising the risk of cardiovascular diseases[ 21 ][ 22 ] and metabolic syndrome[ 23 ]. Prolonged sleep correlates with chronic inflammation[ 24 ], endocrine disruption[ 25 ], and metabolic dysregulation[ 26 ], potentially leading to insulin resistance and increased cardiovascular and diabetes risks. Moreover, long sleep duration may relate to socioeconomic factors, mental health conditions, and lifestyle habits in older adults[ 27 ]. Additionally, extended sleep can reduce social engagement, increasing feelings of loneliness and isolation[ 28 ]. Ultimately, understanding these complex interactions between sleep patterns and lifestyle factors is crucial for developing interventions to improve the health and well-being of older adults. Secondly, studies of the impact of exercise habits on mortality in the elderly have found that maintaining exercise habits or switching from inactivity to exercise significantly reduced mortality among Chinese older adults. The reason for this is that regular participation in physical activity improves physical function and mental health in older adults[ 29 ]. For example, a study of older adults found that older adults who participated in a community-based exercise programme showed significant improvements in physical functioning, ability to perform activities of daily living, and exercise self-efficacy[ 30 ]. In addition, exercise has been strongly associated with mental health, with higher levels of moderate to vigorous physical activity associated with lower depressive symptoms[ 31 ]. Among older adults, maintenance of exercise habits not only contributes to improved physical fitness, but also enhances social support and self-efficacy, all of which are important factors in promoting healthy aging[ 32 ].Therefore, encouraging older adults to maintain an exercise habit or participate in exercise activities is an effective strategy to promote their health and longevity. Finally, the joint effect of sleep duration and exercise habits on mortality in Chinese older adults was analysed stratified for gender. The results indicated that for older Chinese men, maintaining a regular exercise routine seemed to eliminate the negative health effects associated with prolonged sleep. Specifically, the risk of death did not significantly increase even with extended sleep, provided that a consistent exercise regimen was followed. Notably, we also observed a significant interaction between normal sleep duration and exercise habits in older men. This suggests that older men who maintain both normal sleep duration and regular exercise habits may experience the lowest risk of mortality. This is consistent with Duarte Junior's findings that meeting moderate-to-vigorous physical activity recommendations reduces the risk associated with short or long sleep periods[ 33 ].This finding underscores the importance of adopting a healthy lifestyle among older men, emphasizing the need for both adequate sleep and regular physical activity.In contrast, while the overall trends for older women were similar to those of men, some unique observations emerged. Specifically, we found that women who experienced prolonged sleep had a significantly lower risk of death when they transitioned from inactivity to beginning an exercise routine. This indicates that, for this group of women, even with poor sleep patterns (such as long sleep duration), the risk of mortality can still be effectively mitigated by adopting new exercise habits. This finding suggests that health intervention strategies for older women should place special emphasis on fostering and maintaining exercise habits, particularly in the context of suboptimal sleep behaviors. The findings of this study further support the critical roles of both exercise and sleep in promoting health among older adults[ 34 ][ 35 ]. Additionally, the noted gender differences may reflect varying physiological and psychological responses to exercise and sleep. Therefore, gender-specific considerations should be taken into account when developing health coaching strategies for older adults to ensure that these strategies effectively address the unique health needs of different genders. 5. Limitation The present study demonstrated only that exercise habits can offset the negative health effects associated with prolonged sleep, without providing insights into how exercise specifically affects sleep quality or the underlying mechanisms involved. Future research should aim to investigate the physiological mechanisms connecting exercise and sleep, as well as the moderating role of gender in this relationship. Additionally, this study primarily relied on data gathered from questionnaires and objective data monitoring, which may introduce some bias. Therefore, future studies should validate these findings with larger sample sizes and more comprehensive data collection. It is also important to explore in greater depth the differences in the effects of exercise habits and sleep duration across various groups of older adults. 6. Conclision In conclusion, for older adults in China, both sleep duration and exercise habits are associated with all-cause mortality, and they also have combined effects on mortality risk. Significantly, the joint effects varies between males and females. Therefore, targeted health policies are essential to encourage this demographic to enhance their sleep and exercise habits. These policies should consider gender differences and provide individualized support and resources tailored to various groups. By implementing such measures, we can more effectively reduce mortality risk and improve the overall quality of life for older individuals. Declarations Data availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Acknowledgements We express our gratitude to the CLHLS team for providing us with the data, and we extend our appreciation to every respondent in the study for their valuable contributions. Funding This study was funded and organized by the Humanities and Social Science Fund of Ministry of Education of China(24A10203020) and the Jilin Province Higher Education Teaching Reform Research Project (2024L5L2852003G). 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Sleep duration and metabolic syndrome: An updated systematic review and meta-analysis. Sleep Med Rev. 2021 Oct;59:101451. doi: 10.1016/j.smrv.2021.101451 Dai X, Gil GF, Reitsma MB, Ahmad NS, Anderson JA, Bisignano C, Carr S, Feldman R, Hay SI, He J, Iannucci V, Lawlor HR, Malloy MJ, Marczak LB, McLaughlin SA, Morikawa L, Mullany EC, Nicholson SI, O'Connell EM, Okereke C, Sorensen RJD, Whisnant J, Aravkin AY, Zheng P, Murray CJL, Gakidou E. Health effects associated with smoking: a Burden of Proof study. Nat Med. 2022 Oct;28(10):2045-2055. doi: 10.1038/s41591-022-01978-x Im PK, Wright N, Yang L, Chan KH, Chen Y, Guo Y, Du H, Yang X, Avery D, Wang S, Yu C, Lv J, Clarke R, Chen J, Collins R, Walters RG, Peto R, Li L, Chen Z, Millwood IY; China Kadoorie Biobank Collaborative Group. Alcohol consumption and risks of more than 200 diseases in Chinese men. Nat Med. 2023 Jun;29(6):1476-1486. doi: 10.1038/s41591-023-02383-8 Hu C, Jiang K, Sun X, He Y, Li R, Chen Y, Zhang Y, Tao Y, Jin L. Change in Healthy Lifestyle and Subsequent Risk of Cognitive Impairment Among Chinese Older Adults: A National Community-Based Cohort Study. J Gerontol A Biol Sci Med Sci. 2024 Aug 1;79(8):glae148. doi: 10.1093/gerona/glae148 Xiao Q, Keadle SK, Hollenbeck AR, Matthews CE. Sleep duration and total and cause-specific mortality in a large US cohort: interrelationships with physical activity, sedentary behavior, and body mass index. Am J Epidemiol. 2014 Nov 15;180(10):997-1006. doi: 10.1093/aje/kwu222 Jike M, Itani O, Watanabe N, Buysse DJ, Kaneita Y. Long sleep duration and health outcomes: A systematic review, meta-analysis and meta-regression. Sleep Med Rev. 2018 Jun;39:25-36. doi: 10.1016/j.smrv.2017.06.011 Li XL, Wei J, Zhang X, Meng Z, Zhu W. Relationship between night-sleep duration and risk for depression among middle-aged and older people: A dose-response meta-analysis. Front Physiol. 2023 Mar 2;14:1085091. doi: 10.3389/fphys.2023.1085091 Vu TH, Reid KJ, Daviglus ML, Garside DB, Liu K, Carnethon MR, Lloyd-Jones DM, Zee PC. Associations of sleep duration and sleep quality with physical performance in older adults: The Chicago Healthy Aging Study (CHAS). Circulation. 2018;137(Suppl 1):AP335. Yin J, Jin X, Shan Z, Li S, Huang H, Li P, Peng X, Peng Z, Yu K, Bao W, Yang W, Chen X, Liu L. Relationship of Sleep Duration With All-Cause Mortality and Cardiovascular Events: A Systematic Review and Dose-Response Meta-Analysis of Prospective Cohort Studies. J Am Heart Assoc. 2017 Sep 9;6(9):e005947. doi: 10.1161/JAHA.117.005947 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 Jun;32(12):1484-92. doi: 10.1093/eurheartj/ehr007\ Che T, Yan C, Tian D, Zhang X, Liu X, Wu Z. The Association Between Sleep and Metabolic Syndrome: A Systematic Review and Meta-Analysis. Front Endocrinol (Lausanne). 2021 Nov 19;12:773646. doi: 10.3389/fendo.2021.773646 Hall MH, Smagula SF, Boudreau RM, Ayonayon HN, Goldman SE, Harris TB, Naydeck BL, Rubin SM, Samuelsson L, Satterfield S, Stone KL, Visser M, Newman AB. Association between sleep duration and mortality is mediated by markers of inflammation and health in older adults: the Health, Aging and Body Composition Study. Sleep. 2015 Feb 1;38(2):189-95. doi: 10.5665/sleep.4394 Buxton OM, Cain SW, O'Connor SP, Porter JH, Duffy JF, Wang W, Czeisler CA, Shea SA. Adverse metabolic consequences in humans of prolonged sleep restriction combined with circadian disruption. Sci Transl Med. 2012 Apr 11;4(129):129ra43. doi: 10.1126/scitranslmed.3003200 Koren D, Dumin M, Gozal D. Role of sleep quality in the metabolic syndrome. Diabetes Metab Syndr Obes. 2016 Aug 25;9:281-310. doi: 10.2147/DMSO.S95120 Nyarko SH, Luo L, Schlundt DG, Xiao Q. Individual and neighborhood socioeconomic status and long-term individual trajectories of sleep duration among Black and White adults: the Southern Community Cohort Study. Sleep. 2023 Jan 11;46(1):zsac225. doi: 10.1093/sleep/zsac225 Jiang HX, Liu Y, Jiang JJ, Wei JH, Niu CC, Yu J. The relationship of social isolation and sleep in older adults: evidence from cross-sectional and longitudinal studies. Aging Ment Health. 2023 Nov-Dec;27(11):2295-2304. doi: 10.1080/13607863.2023.2230919 Ory MG, Lee S, Han G, Towne SD, Quinn C, Neher T, Stevens A, Smith ML. Effectiveness of a Lifestyle Intervention on Social Support, Self-Efficacy, and Physical Activity among Older Adults: Evaluation of Texercise Select. Int J Environ Res Public Health. 2018 Jan 30;15(2):234. doi: 10.3390/ijerph15020234 Levy SS, Thralls KJ, Goble DJ, Krippes TB. Effects of a Community-Based Exercise Program on Older Adults' Physical Function, Activities of Daily Living, and Exercise Self-Efficacy: Feeling Fit Club. J Appl Gerontol. 2020 Jan;39(1):40-49. doi: 10.1177/0733464818760237 Carvalho J, Borges-Machado F, Pizarro AN, Bohn L, Barros D. Home Confinement in Previously Active Older Adults: A Cross-Sectional Analysis of Physical Fitness and Physical Activity Behavior and Their Relationship With Depressive Symptoms. Front Psychol. 2021 May 20;12:643832. doi: 10.3389/fpsyg.2021.643832 Nakajima C, Tomida K, Shimoda T, Kawakami A, Shimada H. Association between willingness to exercise and incident disability in older adults: a prospective longitudinal cohort study. Eur Geriatr Med. 2024 Oct 8. doi: 10.1007/s41999-024-01077-9 Duarte Junior MA, Martinez-Gomez D, Pintos-Carrillo S, Lopez-Garcia E, Rodríguez-Artalejo F, Cabanas-Sánchez V. Associations of nighttime sleep, midday napping, and physical activity with all-cause mortality in older adults: the Seniors-ENRICA cohorts. Geroscience. 2024 Sep 20. doi: 10.1007/s11357-024-01351-5 Wang W, Yang J, Wang K, Niu J, Wang J, Luo Z, Liu H, Chen X, Ge H. Assoication between self-reported sleep duration, physcial activity and the risk of all cause and cardiovascular diseases mortality from the NHANES database. BMC Cardiovasc Disord. 2023 Sep 18;23(1):467. doi: 10.1186/s12872-023-03499-y Wendt A, Bielemann RM, Wehrmeister FC, Ricardo LIC, Müller WA, Machado AKF, da Cruz MF, Bertoldi AD, Brage S, Ekelund U, Tovo-Rodrigues L, Crochemore-Silva I. Is rest-activity rhythm prospectively associated with all-cause mortality in older people regardless of sleep and physical activity level? The 'Como Vai?' Cohort study. PLoS One. 2024 Feb 16;19(2):e0298031. doi: 10.1371/journal.pone.0298031 Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5419153","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":377312768,"identity":"cd94e92c-98c5-4181-a69e-3a541995f349","order_by":0,"name":"Na LI","email":"","orcid":"","institution":"Jilin Normal University","correspondingAuthor":false,"prefix":"","firstName":"Na","middleName":"","lastName":"LI","suffix":""},{"id":377312769,"identity":"97be768a-0d80-4bed-8fa2-1887965036f5","order_by":1,"name":"Kexin REN","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtElEQVRIiWNgGAWjYBACxnYGBgmGAwxybOztB4jU0gzRYszHcyaBSGuYIVoS50k4GBCpo5n94e2KM4fT2yQYEhh+VGwjxmE8xpZnbqTltkk3HmDsOXObKC1skg0fbHLbZA4kMDO2EaWF/RlQi0Q6m0SCAbFaGMwkG27YJJCiBeiXhjNphm3AQD5IlF8M29sf3mw4dlhevr394IMfFcRoaUDiHCCsHgjkiVI1CkbBKBgFIxsAAFVwOx7rqByBAAAAAElFTkSuQmCC","orcid":"","institution":"Jilin Normal University","correspondingAuthor":true,"prefix":"","firstName":"Kexin","middleName":"","lastName":"REN","suffix":""},{"id":377312770,"identity":"69d8c065-ace2-4fd2-8dc6-516d6086ec84","order_by":2,"name":"Yuan TAO","email":"","orcid":"","institution":"Jilin Normal University","correspondingAuthor":false,"prefix":"","firstName":"Yuan","middleName":"","lastName":"TAO","suffix":""}],"badges":[],"createdAt":"2024-11-09 00:47:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5419153/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5419153/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":71676512,"identity":"277fa18f-a4c6-4caf-8355-32608c9af228","added_by":"auto","created_at":"2024-12-17 15:51:34","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":72704,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the joint effects of sleep duration and exercise habits all-cause mortality among elderly Chinese of different genders\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5419153/v1/153bf587570af13abc18c683.jpeg"},{"id":71677537,"identity":"48c93d07-b496-443c-8055-bbeddafedfe1","added_by":"auto","created_at":"2024-12-17 15:59:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":834748,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5419153/v1/a6d841be-dbb2-4e88-b415-178f28224f14.pdf"},{"id":71674331,"identity":"f8c56dac-37a9-4ef3-ae37-a2f154d3e695","added_by":"auto","created_at":"2024-12-17 15:35:34","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":210582,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-5419153/v1/5e58665c4f8b6fc5b5aeb2d7.docx"}],"financialInterests":"","formattedTitle":"The Joint Effects of Sleep Duration and Exercise Habit on All-cause Mortality among Chinese Elderly: A National Community-Based Cohort Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSleep duration and exercise habits are critical lifestyle factors that significantly influence health outcomes, particularly among the elderly population. As modifiable lifestyle factors, both sleep and physical activity have been associated with improved health and longevity[1][2]. With the rapid increase in the elderly population in China[3], understanding how these two factors impact health within this demographic is of utmost importance.\u003c/p\u003e\n\u003cp\u003eWhile previous studies have thoroughly examined the individual effects of sleep and exercise on health outcomes, the combined or joint effects of these factors are less explored, particularly in the context of the Chinese elderly population. The Seniors-ENRICA cohort study in Spain demonstrated that appropriate physical activity mitigates the impact of poor sleep duration on mortality among older adults[4]. Similarly, the UK Biobank study found that physical activity and sleep duration interacted with the risk of all-cause mortality, as measured by accelerometers[5]. In contrast, a Brazilian study indicated that resting activity rhythms were not significantly associated with mortality, suggesting that physical activity might be an influencing factor[6]. Notably, there was only one relevant study involving Chinese older adults[7], which provided insights into the association between sleep scores and leisure-time physical activity with all-cause mortality. This study emphasized the potential benefits of improved sleep and increased physical activity in reducing mortality; however, it was conducted on retired employees of the Dongfeng-Tongji (DFTJ) Group and did not represent a nationwide sample. The results of these studies suggest that physical activity and sleep may interact through different mechanisms, collectively affecting the health and longevity of older adults. Therefore, further research is needed to gain a deeper understanding of the joint effects of these factors across different populations, particularly among the Chinese elderly.\u003c/p\u003e\n\u003cp\u003eThe imperative to study the health behaviors and outcomes among China's elderly is underscored by their rapidly growing demographic, a trend attributed to enhanced life expectancies and declining birth rates[8].This substantial demographic shift not only poses challenges to the public health and healthcare systems but also necessitates a tailored approach to health promotion and disease prevention. The unique cultural practices and health beliefs within this population may significantly influence their sleep and exercise habits, which are critical factors in determining health outcomes[9].Understanding these nuances is essential for developing effective and culturally sensitive interventions to support the health and well-being of China's elderly.\u003c/p\u003e\n\u003cp\u003eThe aim of this study is to investigate the joint effects of sleep duration and exercise habits on all-cause mortality in older adults in China, along with the associated mechanisms of action. This study will employ a national community-based cohort design and will be the first to examine how changes in exercise habits and sleep duration impact all-cause mortality. The findings will provide valuable insights into the most effective combinations of sleep and exercise. Additionally, these results may inform public health interventions targeting the elderly population in China and contribute significantly to our understanding of how sleep and exercise can be leveraged to improve health outcomes in this demographic.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cem\u003e2.1 Data sources\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe data for this study are derived from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which is the largest cohort study focusing on the elderly population in China. This study was organized by the Centre for Healthy Ageing and Development at Peking University in collaboration with the National Institute for Development Research. The CLHLS encompasses 23 provinces, municipalities, and autonomous regions, with a total of 113,000 household interviews conducted. Approximately half of the cities and counties in 22 of the research provinces (excluding Hainan Province) were randomly selected as research sites. The survey received approval from the Institutional Review Board of Peking University (IRB00001052-13074), and all participants, or their legal representatives, provided written informed consent.\u003c/p\u003e\n\u003cp\u003eWe utilized a sample of individuals aged 60 and older from the 2011 follow-up study, and all participants were evaluated again in 2014 and 2018, with ongoing monitoring until their death, loss to follow-up, or the end of the study. Participants with incomplete records were excluded from the analysis. The final sample size for analysis is 7,231 (refer to SFig. 1).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2 Variable Measurement\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2.1 Exposure\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the survey, participants were asked, \u0026ldquo;Do you exercise frequently at present?\u0026rdquo; and \u0026ldquo;Did you exercise frequently in the past?\u0026rdquo; Based on their answers to these two questions, participants were classified into four groups: 1) physically active if they exercised frequently both in the past and now, 2) physically inactive if they did not exercise frequently either in the past or the present, 3) inactive-to-active if they did not exercise frequently in the past but do so now, and 4) active-to-inactive if they exercised frequently in the past but are not currently active[10].\u003c/p\u003e\n\u003cp\u003eSleep duration (in hours) was defined as the amount of sleep reported by the participant in the self-reported questionnaire. The exact amount of time was based on the following question: \u0026ldquo;How many hours of sleep do you currently get on a typical day?\u0026rdquo;Using restricted cubic spline curves and threshold effect analyses[11], we determined that the threshold of sleep time associated with all-cause mortality was 8 hours (SFig. 2).Based on the threshold effects and classifications from previous studies[12][13], we categorized sleep duration into three groups: short sleep (\u0026lt; 6 hours), normal sleep (6~8 hours), and long sleep (\u0026gt; 8 hours).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2.2 \u0026nbsp;Outcome\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe outcome of this study was all-cause mortality. Data on participant survival and date of death were collected during three rounds of follow-up in 2011, 2014, and 2018. Participants who remained alive or were lost to follow-up were assessed based on the most recent point of contact (30 December 2018).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2.3 \u0026nbsp; Covariates\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBased on previous studies of physical activity and mortality, as well as sleep duration and mortality, we included a variety of covariates that might influence the results: age(60~70,70~80,\u0026gt;80),gender(male,female),marital(married,others),education years(continuous), smoke(yes,no)[14],drink(yes,no)[15],Self-assessed health (very bad,bad,fair,good,very good )[16], BMI(continuous)[17].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.3 Statistical analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe baseline characteristics of 7,231 participants were described based on sleep duration, with categorical variables expressed as frequencies and percentages, and quantitative variables expressed as means with standard deviations (SD).Comparison of baseline characteristics among sleep duration categories was performed using the \u0026chi;2 test and 1-way analysis of variance for categorical and continuous variables, respectively.We first analyzed the effect of sleep duration and exercise habits on all-cause mortality using multi-model cox regression: Model 1 without covariates, Model 2 with covariates including age, gender, education, and marital status, and Model 3 with covariates including age, gender, education, marital status, smoking, drinking, health status, and BMI. We then further analysed the joint effect of sleep duration and exercise habits on all-cause mortality using stratified analyses by sex and interaction analyses. Data processing and analysis were performed using R version 4.3.0, along with the Storm Statistical Platform (www.medsta.cn/software). A 2-tailed P\u0026lt;0.05 was considered to be statistically significant.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Basic characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the basic characteristics of participants based on sleep duration.Of the total sample of 7,231 participants, there were 1,120 short sleepers (i.e., those sleeping less than 6 hours), 3,743 normal sleepers (6 to 8 hours), and 2,368 long sleepers (more than 8 hours). Further analyses revealed that the proportion of both short and long sleepers increased among individuals aged over 80 compared to those with normal sleep duration. Additionally, the ratio of long sleepers to short sleepers was relatively higher in the male group.Regarding marital status, the proportion of long sleepers versus short sleepers was notably higher among individuals who were unmarried or in other non-married categories. Non-smokers also exhibited a higher-than-average ratio of long to short sleepers. In terms of drinking habits, drinkers showed a significantly higher proportion of long sleepers.Moreover, it is worth noting that individuals who reported a Self-assessed health of \"good\" or above had a significantly higher proportion of long sleepers as well. All of the observed differences are statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of older adults stratified by sleep duration in CLHLS 2011\u0026ndash;2018\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;7231)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShort sleep\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1120)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal sleep\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;3743)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLong sleep\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2368)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStatistic*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eχ\u0026sup2;=221.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026thinsp;~\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e578 (7.99)\u003csup\u003e\u003cb\u003e#\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61 (5.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e410 (10.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e107 (4.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026thinsp;~\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2124 (29.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e338 (30.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1257 (33.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e529 (22.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4529 (62.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e721 (64.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2076 (55.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1732 (73.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eχ\u0026sup2;=42.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3371 (46.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e426 (38.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1837 (49.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1108 (46.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3860 (53.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e694 (61.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1906 (50.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1260 (53.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eχ\u0026sup2;=101.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4378 (60.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e701 (62.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2067 (55.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1610 (67.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2853 (39.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e419 (37.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1676 (44.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e758 (32.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation(y),\u003c/p\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.49\u0026thinsp;\u0026plusmn;\u0026thinsp;3.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.99\u0026thinsp;\u0026plusmn;\u0026thinsp;3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.86\u0026thinsp;\u0026plusmn;\u0026thinsp;3.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.14\u0026thinsp;\u0026plusmn;\u0026thinsp;3.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF\u0026thinsp;=\u0026thinsp;41.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eχ\u0026sup2;=9.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5806 (80.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e929 (82.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2958 (79.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1919 (81.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1425 (19.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e191 (17.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e785 (20.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e449 (18.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrink, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eχ\u0026sup2;=7.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5884 (81.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e943 (84.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3039 (81.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1902 (80.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1347 (18.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e177 (15.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e704 (18.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e466 (19.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eχ\u0026sup2;=190.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery bad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e86 (1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (2.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37 (0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21 (0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1121 (15.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e297 (26.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e509 (13.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e315 (13.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2646 (36.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e428 (38.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1406 (37.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e812 (34.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2560 (35.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e292 (26.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1343 (35.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e925 (39.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e818 (11.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75 (6.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e448 (11.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e295 (12.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.08\u0026thinsp;\u0026plusmn;\u0026thinsp;23.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.77\u0026thinsp;\u0026plusmn;\u0026thinsp;9.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.51\u0026thinsp;\u0026plusmn;\u0026thinsp;30.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.56\u0026thinsp;\u0026plusmn;\u0026thinsp;10.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF\u0026thinsp;=\u0026thinsp;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eχ\u0026sup2;=60.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3525 (48.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e561 (50.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1803 (48.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1161 (49.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1189 (16.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e137 (12.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e730 (19.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e322 (13.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive-to-Active\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1649 (22.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e284 (25.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e795 (21.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e570 (24.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive-to-Inactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e868 (12.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e138 (12.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e415 (11.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e315 (13.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e\u003cb\u003e#\u003c/b\u003e\u003c/sup\u003e Percentage of categorical variables\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*The χ2 test was used for categorical variables and analysis of variance for continuous variables.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Multi-model cox regression analysis\u003c/h2\u003e \u003cp\u003eIn this study, we delved into the impacts of sleep duration and diverse exercise habits on all-cause mortality by employing multi-model COX regression analysis. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the findings from three distinct models (Model 1, Model 2, and Model 3), each incorporating various combinations of variables.\u003c/p\u003e \u003cp\u003eInitially, we discerned a notable influence of sleep duration on all-cause mortality. Specifically, normal sleep duration (ranging from 6 to 8 hours) exhibited a 20% reduction in mortality compared to short sleep (\u0026lt;\u0026thinsp;6 hours) in Model 1, with statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, while Models 2 and 3 showed hazard ratio (HR) below 1.00 for this comparison, the association failed to attain statistical significance. Conversely, prolonged sleep duration (\u0026gt;\u0026thinsp;8 hours) consistently correlated with an elevated risk of all-cause mortality across all models, with Model 3 indicating a 29% increase in mortality. Notably, the P-values for this association were universally below 0.001, affirming its statistical significance.\u003c/p\u003e \u003cp\u003eFurthermore, our analysis unveiled a significant impact of exercise habits on all-cause mortality. Across all models, maintaining an exercise routine was associated with a decreased risk of all-cause mortality, as evidenced by HR below 1.00 and P-values less than 0.001, compared to those who did not exercise. Additionally, we scrutinized the effects of transitions in exercise habits. The transition from inactivity to activity was uniformly linked to a lower risk of all-cause mortality, highlighting its positive influence on mortality reduction (Model 3 demonstrated a 12% reduction). In stark contrast, shifting from an active to an inactive lifestyle was consistently associated with an increased risk of all-cause mortality across all models. While Model 3's P-value for this association hovered near the significance threshold of 0.05 (HR\u0026thinsp;=\u0026thinsp;1.14, 95% CI: 0.99\u0026ndash;1.32, P\u0026thinsp;=\u0026thinsp;0.076), suggesting a potential negative impact on mortality, this correlation did not attain statistical significance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of sleep duration and different exercise habits on all-cause mortality in CLHLS 2011\u0026ndash;2018\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eModel3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSleep Duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShort sleep\u0026thinsp;\u0026lt;\u0026thinsp;6h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal sleep 6-8h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.80 (0.72\u0026thinsp;~\u0026thinsp;0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97 (0.87\u0026thinsp;~\u0026thinsp;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97 (0.88\u0026thinsp;~\u0026thinsp;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.601\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLong sleep\u0026thinsp;\u0026gt;\u0026thinsp;8h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.32 (1.19\u0026thinsp;~\u0026thinsp;1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.28 (1.15\u0026thinsp;~\u0026thinsp;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.29 (1.16\u0026thinsp;~\u0026thinsp;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExercise\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.62 (0.56\u0026thinsp;~\u0026thinsp;0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73 (0.65\u0026thinsp;~\u0026thinsp;0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.73 (0.65\u0026thinsp;~\u0026thinsp;0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive to Active\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81 (0.74\u0026thinsp;~\u0026thinsp;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88 (0.80\u0026thinsp;~\u0026thinsp;0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.88 (0.80\u0026thinsp;~\u0026thinsp;0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive to Inactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.20 (1.08\u0026thinsp;~\u0026thinsp;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.09 (0.98\u0026thinsp;~\u0026thinsp;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.10 (0.99\u0026thinsp;~\u0026thinsp;1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eHR: Hazard Ratio, CI:Confidence Interval\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eModel1: Crude\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eModel2: Adjust: age, gender, education, marital\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eModel3: Adjust: age, gender,education, marital status, smoke, drink, health, BMI\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Joint effects of sleep duration and exercise habits on all-cause mortality\u003c/h2\u003e \u003cp\u003eTo further investigate the combined influence of sleep duration and exercise habits on all-cause mortality, we conducted sex-stratified analyses and interaction analyses.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides a detailed breakdown of how these factors jointly affect all-cause mortality among older men.Among those with short sleep duration, transitioning from an inactive to an active lifestyle was found to significantly elevate all-cause mortality (HR\u0026thinsp;=\u0026thinsp;1.571, P\u0026thinsp;=\u0026thinsp;0.032). Notably, after adjusting the model, a significant interaction between sleep duration and exercise habits emerged (P\u0026thinsp;=\u0026thinsp;0.039).In contrast, during normal sleep duration, individuals who remained active showed a marked reduction in mortality compared to those who were inactive, both before and after model adjustment. Specifically, after model adjustment, the active group experienced a 26.2% decrease in mortality (HR\u0026thinsp;=\u0026thinsp;0.738, P\u0026thinsp;=\u0026thinsp;0.007). Furthermore, a significant interaction between normal sleep duration and exercise habits was observed both before and after model adjustment (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).For those with long sleep duration, although the active group demonstrated a lower mortality rate compared to the inactive group both before and after model adjustment, no significant interaction effect was observed between sleep duration and exercise habits. This finding remained consistent across both unadjusted and adjusted models.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe joint effects of exercise habits and sleep durationon all-cause mortality in elderly Chinese men\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnadjusted model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAdjusted model*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eShort sleep\u0026thinsp;\u0026lt;\u0026thinsp;6h (N\u0026thinsp;=\u0026thinsp;426)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.151(0.759\u0026thinsp;~\u0026thinsp;1.747)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.560(1.003\u0026thinsp;~\u0026thinsp;2.427)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive to Active\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.024(0.725\u0026thinsp;~\u0026thinsp;1.447)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.157(0.807\u0026thinsp;~\u0026thinsp;1.658)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive to Inactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.538(1.024\u0026thinsp;~\u0026thinsp;2.312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.571(1.039\u0026thinsp;~\u0026thinsp;2.377)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP for interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNormal sleep 6-8h (N\u0026thinsp;=\u0026thinsp;1837)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.695(0.564\u0026thinsp;~\u0026thinsp;0.857)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.738(0.593\u0026thinsp;~\u0026thinsp;0.919)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive to Active\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.900(0.737\u0026thinsp;~\u0026thinsp;1.098)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.898(0.734\u0026thinsp;~\u0026thinsp;1.098)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive to Inactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.327(1.058\u0026thinsp;~\u0026thinsp;1.664)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.970(0.770\u0026thinsp;~\u0026thinsp;1.221)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP for interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLong sleep\u0026thinsp;\u0026gt;\u0026thinsp;8h (N\u0026thinsp;=\u0026thinsp;1108)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.755(0.597\u0026thinsp;~\u0026thinsp;0.956)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.740(0.579\u0026thinsp;~\u0026thinsp;0.946)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive to Active\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.929(0.758\u0026thinsp;~\u0026thinsp;1.138)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.919(0.749\u0026thinsp;~\u0026thinsp;1.128)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive to Inactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.065(0.832\u0026thinsp;~\u0026thinsp;1.363)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.989(0.769\u0026thinsp;~\u0026thinsp;1.271)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP for interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Adjusted model to add covariates age, gender,education, marital, smoke, drink, health, BMI\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn contrast, Chinese elderly women exhibited a distinct pattern regarding the joint effects of sleep duration and exercise habits on all-cause mortality compared to their male counterparts, as illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFor those with short sleep duration, although elderly women who maintained exercise habits experienced a significant decrease in mortality in the unadjusted model, this relationship vanished entirely after model adjustment. Additionally, it is noteworthy that no significant interaction between sleep duration and exercise habits was observed in this short sleep duration group.\u003c/p\u003e \u003cp\u003eWhen sleep duration falls within the normal range, the active elderly women demonstrated a significant reduction in mortality rates both before and after model adjustment. Specifically, after adjusting for covariates, the mortality rate in the activity group declined by 43.1% (HR\u0026thinsp;=\u0026thinsp;0.569, P\u0026thinsp;=\u0026thinsp;0.001). Furthermore, elderly women who transitioned from exercise to inactivity experienced a 32.1% increase in mortality rate (HR\u0026thinsp;=\u0026thinsp;1.321, P\u0026thinsp;=\u0026thinsp;0.014) after adjustment. Importantly, there was a significant interaction between sleep duration and exercise habits both before and after model adjustment in this normal sleep duration group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eFor elderly women with long sleep duration, the active group also exhibited a significant reduction in mortality rates, a finding that remained consistent across both unadjusted and adjusted models, indicating high stability. Moreover, those who transitioned from inactivity to active habits showed a downward trend in mortality rates, which persisted before and after model adjustment. However, no significant interaction was observed between sleep duration and exercise habits within the long sleep duration group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe joint effects of physical activity and sleep durationon all-cause mortality in elderly Chinese women\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnadjusted model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAdjusted model*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eShort sleep\u0026thinsp;\u0026lt;\u0026thinsp;6h (N\u0026thinsp;=\u0026thinsp;694)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.654(0.430\u0026thinsp;~\u0026thinsp;0.996)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.837(0.542\u0026thinsp;~\u0026thinsp;1.291)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive to Active\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.748(0.561\u0026thinsp;~\u0026thinsp;0.997)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.892(0.665\u0026thinsp;~\u0026thinsp;1.197)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive to Inactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.096(0.774\u0026thinsp;~\u0026thinsp;1.553)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.127(0.789\u0026thinsp;~\u0026thinsp;1.608)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP for interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNormal sleep 6-8h (N\u0026thinsp;=\u0026thinsp;1906)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.695(0.564\u0026thinsp;~\u0026thinsp;0.857)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.697(0.538\u0026thinsp;~\u0026thinsp;0.902)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive to Active\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.900(0.737\u0026thinsp;~\u0026thinsp;1.098)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.874(0.711\u0026thinsp;~\u0026thinsp;1.075)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive to Inactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.327(1.058\u0026thinsp;~\u0026thinsp;1.664)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.321(1.058\u0026thinsp;~\u0026thinsp;1.650)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP for interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLong sleep\u0026thinsp;\u0026gt;\u0026thinsp;8h\u003c/b\u003e (N\u0026thinsp;=\u0026thinsp;1260)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.525(0.381\u0026thinsp;~\u0026thinsp;0.725)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.569(0.412\u0026thinsp;~\u0026thinsp;0.787)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive to Active\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.721(0.595\u0026thinsp;~\u0026thinsp;0.875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.788(0.649\u0026thinsp;~\u0026thinsp;0.958)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive to Inactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.088(0.873\u0026thinsp;~\u0026thinsp;1.356)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.084(0.867\u0026thinsp;~\u0026thinsp;1.354)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.479\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP for interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Adjusted model to add covariates age, gender,education, marital, smoke, drink, health, BMI\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe results presented above are illustrated more clearly in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. For those with short sleep duration, the impact of exercise habits on mortality was not significant for either men or women. However, for individuals with normal and prolonged sleep, both males and females experienced a significant reduction in mortality by maintaining exercise habits. Additionally, older women who transitioned from a sedentary lifestyle to regular exercise during long sleep duration also exhibited lower mortality rates.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Disscusion","content":"\u003cp\u003eThe aim of this study was to investigate the joint effects of sleep duration and exercise habits on all-cause mortality in Chinese older adults. We analysed the effects of sleep duration and exercise habits on mortality separately, and further explored the joint effect of the two in order to gain a deeper understanding.\u003c/p\u003e \u003cp\u003eFirst, regarding the impact of sleep duration on mortality, we found that long sleep duration in older adults from China is significantly associated with an increased risk of mortality, aligning with existing literature that highlights the negative health implications of extreme sleep variations. Although adequate sleep is beneficial, prolonged sleep may indicate underlying health issues such as chronic diseases[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and depression[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Even after adjusting for covariates, the relationship between long sleep and increased mortality remained significant. Mechanisms may include reduced physical activity[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], raising the risk of cardiovascular diseases[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e][\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and metabolic syndrome[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Prolonged sleep correlates with chronic inflammation[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], endocrine disruption[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and metabolic dysregulation[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], potentially leading to insulin resistance and increased cardiovascular and diabetes risks. Moreover, long sleep duration may relate to socioeconomic factors, mental health conditions, and lifestyle habits in older adults[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Additionally, extended sleep can reduce social engagement, increasing feelings of loneliness and isolation[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Ultimately, understanding these complex interactions between sleep patterns and lifestyle factors is crucial for developing interventions to improve the health and well-being of older adults.\u003c/p\u003e \u003cp\u003eSecondly, studies of the impact of exercise habits on mortality in the elderly have found that maintaining exercise habits or switching from inactivity to exercise significantly reduced mortality among Chinese older adults. The reason for this is that regular participation in physical activity improves physical function and mental health in older adults[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. For example, a study of older adults found that older adults who participated in a community-based exercise programme showed significant improvements in physical functioning, ability to perform activities of daily living, and exercise self-efficacy[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In addition, exercise has been strongly associated with mental health, with higher levels of moderate to vigorous physical activity associated with lower depressive symptoms[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Among older adults, maintenance of exercise habits not only contributes to improved physical fitness, but also enhances social support and self-efficacy, all of which are important factors in promoting healthy aging[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].Therefore, encouraging older adults to maintain an exercise habit or participate in exercise activities is an effective strategy to promote their health and longevity.\u003c/p\u003e \u003cp\u003eFinally, the joint effect of sleep duration and exercise habits on mortality in Chinese older adults was analysed stratified for gender. The results indicated that for older Chinese men, maintaining a regular exercise routine seemed to eliminate the negative health effects associated with prolonged sleep. Specifically, the risk of death did not significantly increase even with extended sleep, provided that a consistent exercise regimen was followed. Notably, we also observed a significant interaction between normal sleep duration and exercise habits in older men. This suggests that older men who maintain both normal sleep duration and regular exercise habits may experience the lowest risk of mortality. This is consistent with Duarte Junior's findings that meeting moderate-to-vigorous physical activity recommendations reduces the risk associated with short or long sleep periods[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].This finding underscores the importance of adopting a healthy lifestyle among older men, emphasizing the need for both adequate sleep and regular physical activity.In contrast, while the overall trends for older women were similar to those of men, some unique observations emerged. Specifically, we found that women who experienced prolonged sleep had a significantly lower risk of death when they transitioned from inactivity to beginning an exercise routine. This indicates that, for this group of women, even with poor sleep patterns (such as long sleep duration), the risk of mortality can still be effectively mitigated by adopting new exercise habits. This finding suggests that health intervention strategies for older women should place special emphasis on fostering and maintaining exercise habits, particularly in the context of suboptimal sleep behaviors.\u003c/p\u003e \u003cp\u003eThe findings of this study further support the critical roles of both exercise and sleep in promoting health among older adults[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e][\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Additionally, the noted gender differences may reflect varying physiological and psychological responses to exercise and sleep. Therefore, gender-specific considerations should be taken into account when developing health coaching strategies for older adults to ensure that these strategies effectively address the unique health needs of different genders.\u003c/p\u003e"},{"header":"5. Limitation","content":"\u003cp\u003eThe present study demonstrated only that exercise habits can offset the negative health effects associated with prolonged sleep, without providing insights into how exercise specifically affects sleep quality or the underlying mechanisms involved. Future research should aim to investigate the physiological mechanisms connecting exercise and sleep, as well as the moderating role of gender in this relationship.\u003c/p\u003e \u003cp\u003eAdditionally, this study primarily relied on data gathered from questionnaires and objective data monitoring, which may introduce some bias. Therefore, future studies should validate these findings with larger sample sizes and more comprehensive data collection. It is also important to explore in greater depth the differences in the effects of exercise habits and sleep duration across various groups of older adults.\u003c/p\u003e"},{"header":"6. Conclision","content":"\u003cp\u003eIn conclusion, for older adults in China, both sleep duration and exercise habits are associated with all-cause mortality, and they also have combined effects on mortality risk. Significantly, the joint effects varies between males and females. Therefore, targeted health policies are essential to encourage this demographic to enhance their sleep and exercise habits. These policies should consider gender differences and provide individualized support and resources tailored to various groups. By implementing such measures, we can more effectively reduce mortality risk and improve the overall quality of life for older individuals.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe express our gratitude to the CLHLS team for providing us with the data, and we extend our appreciation to every respondent in the study for their valuable contributions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded and organized by the Humanities and Social Science Fund of Ministry of Education of China(24A10203020) and the Jilin Province Higher Education Teaching Reform Research Project (2024L5L2852003G).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZheng YB, Huang YT, Gong YM, Li MZ, Zeng N, Wu SL, Zhang ZB, Tian SS, Yuan K, Liu XX, Vitiello MV, Wang YM, Wang YX, Zhang XJ, Shi J, Shi L, Yan W, Lu L, Bao YP. 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Eur Geriatr Med. 2024 Oct 8. doi: 10.1007/s41999-024-01077-9\u003c/li\u003e\n\u003cli\u003eDuarte Junior MA, Martinez-Gomez D, Pintos-Carrillo S, Lopez-Garcia E, Rodr\u0026iacute;guez-Artalejo F, Cabanas-S\u0026aacute;nchez V. Associations of nighttime sleep, midday napping, and physical activity with all-cause mortality in older adults: the Seniors-ENRICA cohorts. Geroscience. 2024 Sep 20. doi: 10.1007/s11357-024-01351-5\u003c/li\u003e\n\u003cli\u003eWang W, Yang J, Wang K, Niu J, Wang J, Luo Z, Liu H, Chen X, Ge H. Assoication between self-reported sleep duration, physcial activity and the risk of all cause and cardiovascular diseases mortality from the NHANES database. BMC Cardiovasc Disord. 2023 Sep 18;23(1):467. doi: 10.1186/s12872-023-03499-y\u003c/li\u003e\n\u003cli\u003eWendt A, Bielemann RM, Wehrmeister FC, Ricardo LIC, M\u0026uuml;ller WA, Machado AKF, da Cruz MF, Bertoldi AD, Brage S, Ekelund U, Tovo-Rodrigues L, Crochemore-Silva I. 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PLoS One. 2024 Feb 16;19(2):e0298031. doi: 10.1371/journal.pone.0298031\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sleep duration, Exercise habit, All-cause mortality, Chinese elderly, CLHLS","lastPublishedDoi":"10.21203/rs.3.rs-5419153/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5419153/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the combined impact of sleep duration and exercise habits on all-cause mortality among the elderly population in China, utilizing data from 7,231 residents aged 60 and above from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Participants were categorized based on their exercise habits and sleep duration, which were analyzed over three follow-ups (2011, 2014, and 2018). The findings revealed that normal sleep (6-8 hours) correlated with a 20% reduction in mortality risk compared to short sleepers, while long sleep (over 8 hours) was linked to a 29% increase in mortality risk. Exercise significantly affected mortality; active individuals had a reduced risk, and those transitioning from inactivity to activity saw a 12% reduction in mortality. Notably, among short sleepers, exercise habits did not significantly impact mortality for either sex. However, for those with normal or long sleep, both men and women experienced significant mortality benefits from regular exercise. Additionally, older women moving from a sedentary lifestyle to physical activity during periods of long sleep demonstrated lower mortality rates. This research highlights the importance of both sleep and exercise in influencing health outcomes, with notable gender differences in their combined effects on mortality risk.\u003c/p\u003e","manuscriptTitle":"The Joint Effects of Sleep Duration and Exercise Habit on All-cause Mortality among Chinese Elderly: A National Community-Based Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-17 15:35:29","doi":"10.21203/rs.3.rs-5419153/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d9a581ea-f08c-4aad-9cb0-5c1daf5e24c1","owner":[],"postedDate":"December 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-17T15:35:31+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-17 15:35:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5419153","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5419153","identity":"rs-5419153","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}