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Diao T, Liu K, Zhou L, Wang Q, Lyu J, Zhu Z, Chen F, Qin W, Yang H, Wang C, Zhang X, Wu T. Sleep patterns and DNA methylation age acceleration in middle-aged and older Chinese adults. Clin Epigenetics 2025; 17:87. [PMID: 40442824 PMCID: PMC12123996 DOI: 10.1186/s13148-025-01898-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Accepted: 05/10/2025] [Indexed: 06/02/2025] Open
Abstract
BACKGROUND Sleep is a biological necessity and fundamental to health. However, the associations of sleep patterns (integrating sleep determinants) with DNA methylation age acceleration (DNAm AA) remain unknown. We aimed to investigate the associations of sleep patterns with DNAm AA. METHODS This cross-sectional and prospective cohort study used data from the Dongfeng-Tongji cohort collected from 2013 to December 31, 2018. Sleep patterns were reflected by sleep scores (range 0-4, with higher scores indicating healthier sleep patterns) characterized by bedtime, sleep duration, sleep quality, and midday napping. DNAm AA was estimated by PhenoAge acceleration (PhenoAgeAccel), GrimAge acceleration (GrimAgeAccel), DunedinPACE, and DNAm mortality risk score (DNAm MS). Linear regression models were used to estimate β and 95% confidence intervals (CIs) for the cross-sectional associations between sleep patterns and DNAm AA. Mediation models were applied to assess the mediating role of DNAm AA in the associations between sleep patterns and all-cause mortality in a prospective cohort. RESULTS Among 3566 participants (mean age 65.5 years), 426 participants died during a mean 5.4-year follow-up. A higher sleep score was associated with lower DNAm AA in a dose-response manner. Each 1-point increase in sleep score was associated with significantly lower PhenoAgeAccel (β = - 0.208; 95% CI - 0.369 to - 0.047), GrimAgeAccel (β = - 0.107; 95% CI - 0.207 to - 0.007), DunedinPACE (β = - 0.008; 95% CI - 0.012 to - 0.004), and DNAm MS (β = - 0.019; 95% CI - 0.030 to - 0.008). Chronological age modified the associations between higher sleep scores and lower PhenoAgeAccel (p for interaction = 0.031) and DunedinPACE (p for interaction = 0.027), with stronger associations observed in older adults. Moreover, a slower DunedinPACE mediated 6.2% (95% CI 0.8% to 11.5%) of the association between a higher sleep score and a lower all-cause mortality risk. CONCLUSION In this cohort study, individuals with a higher sleep score had a slower DNAm AA, particularly in older adults. A slower DunedinPACE partially explained the association between higher sleep scores and lower all-cause mortality risk. These findings suggest that adopting healthy sleep patterns may promote healthy aging and further benefit premature mortality prevention, highlighting the value of sleep patterns as a potential tool for clinical management in aging.
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Affiliation(s)
- Tingyue Diao
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, China
| | - Kang Liu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, China
- School of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Lue Zhou
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, China
| | - Qiuhong Wang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, China
| | - Junrui Lyu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, China
| | - Ziwei Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fuchao Chen
- Hubei Clinical Research Center of Hypertension, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, China
| | - Wengang Qin
- Hubei Clinical Research Center of Hypertension, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, China
| | - Handong Yang
- Hubei Clinical Research Center of Hypertension, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, China
| | - Chaolong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, China.
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Ungvari Z, Fekete M, Varga P, Fekete JT, Lehoczki A, Buda A, Szappanos Á, Purebl G, Ungvari A, Győrffy B. Imbalanced sleep increases mortality risk by 14-34%: a meta-analysis. GeroScience 2025:10.1007/s11357-025-01592-y. [PMID: 40072785 DOI: 10.1007/s11357-025-01592-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2024] [Accepted: 02/28/2025] [Indexed: 03/14/2025] Open
Abstract
Sleep duration is a crucial factor influencing health outcomes, yet its relationship with mortality remains debated. In this meta-analysis, we aimed to investigate the association between short and long sleep duration and all-cause mortality in adults, including sex-specific differences. A systematic search was performed in multiple databases, including PubMed, Cochrane Central, and Web of Science, up to October 2024. Retrospective and prospective cohort studies involving adults with at least 1 year of follow-up and data on sleep duration and all-cause mortality were included. Hazard ratios were pooled using a random-effects model, with subgroup analyses performed based on sex and sleep duration categories. A total of 79 cohort studies were included, with data stratified by sex and categorized into short and long sleep durations. Short sleep duration (< 7 h per night) was associated with a 14% increase in mortality risk compared to the reference of 7-8 h, with a pooled hazard ratio of 1.14 (95% CI 1.10 to 1.18). Conversely, long sleep duration (≥ 9 h per night) was associated with a 34% higher risk of mortality, with a hazard ratio of 1.34 (95% CI 1.26 to 1.42). Sex-specific analyses indicated that both short and long sleep durations significantly elevated mortality risk in men and women, although the effect was more pronounced for long sleep duration in women. Both short and long sleep durations are associated with increased all-cause mortality, though the degree of risk varies by sex. These findings underscore the importance of considering optimal sleep duration in public health strategies aimed at enhancing longevity and highlight the need for sex-specific approaches in sleep health research.
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Affiliation(s)
- Zoltan Ungvari
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- International Training Program in Geroscience, Doctoral College, Health Sciences Program/Institute of Preventive Medicine and Public Health, Semmelweis University, Budapest, Hungary
| | - Mónika Fekete
- Institute of Preventive Medicine and Public Health, Semmelweis University, Budapest, Hungary
| | - Péter Varga
- Institute of Preventive Medicine and Public Health, Semmelweis University, Budapest, Hungary
- Doctoral College, Health Sciences Program, Semmelweis University, Budapest, Hungary
| | - János Tibor Fekete
- Department of Bioinformatics, Semmelweis University, 1094, Budapest, Hungary
- Cancer Biomarker Research Group, Institute of Molecular Life Sciences, HUN-REN Research Centre for Natural Sciences, 1117, Budapest, Hungary
| | - Andrea Lehoczki
- Institute of Preventive Medicine and Public Health, Semmelweis University, Budapest, Hungary
- Doctoral College, Health Sciences Program, Semmelweis University, Budapest, Hungary
| | - Annamaria Buda
- Institute of Preventive Medicine and Public Health, Semmelweis University, Budapest, Hungary
- Doctoral College, Health Sciences Program, Semmelweis University, Budapest, Hungary
| | - Ágnes Szappanos
- Department of Vascular and Endovascular Surgery, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
- Department of Rheumatology and Clinical Immunology, Semmelweis University, Budapest, Hungary
| | - György Purebl
- Institute of Behavioural Sciences, Semmelweis University, Budapest, Hungary
| | - Anna Ungvari
- Institute of Preventive Medicine and Public Health, Semmelweis University, Budapest, Hungary.
| | - Balázs Győrffy
- Doctoral College, Health Sciences Program, Semmelweis University, Budapest, Hungary
- Department of Bioinformatics, Semmelweis University, 1094, Budapest, Hungary
- Department of Biophysics, Medical School, University of Pecs, 7624, Pecs, Hungary
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Wang M, Xiang X, Zhao Z, liu Y, Cao Y, Guo W, Hou L, Jiang Q. Association between self-reported napping and risk of cardiovascular disease and all-cause mortality: A meta-analysis of cohort studies. PLoS One 2024; 19:e0311266. [PMID: 39413101 PMCID: PMC11482734 DOI: 10.1371/journal.pone.0311266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Accepted: 09/16/2024] [Indexed: 10/18/2024] Open
Abstract
OBJECTIVES This meta-analysis aims to assess the association between adult nap duration and risk of all-cause mortality and cardiovascular diseases (CVD). METHODS PubMed, Cochrane Library, Embase and Web of Science databases were searched to identify eligible studies. The quality of observational studies was assessed using the Newcastle-Ottawa Scale. We performed all statistical analyses using Stata software version 14.0. For the meta-analysis, we calculated hazard ratio (HR) and their corresponding 95% confidence intervals (CIs). To assess publication bias, we used a funnel plot and Egger's test. RESULTS A total of 21 studies involving 371,306 participants revealed varying methodological quality, from moderate to high. Those who indulged in daytime naps faced a significantly higher mortality risk than non-nappers (HR: 1.28; 95% CI: 1.18-1.38; I2 = 38.8%; P<0.001). Napping for less than 1 hour showed no significant association with mortality (HR: 1.00; 95% CI: 0.90-1.11; I2 = 62.6%; P = 0.971). However, napping for 1 hour or more correlated with a 1.22-fold increased risk of mortality (HR: 1.22; 95% CI: 1.12-1.33; I2 = 40.0%; P<0.001). The risk of CVD associated with napping was 1.18 times higher than that of non-nappers (HR: 1.18; 95% CI: 1.02-1.38; I2 = 87.9%; P = 0.031). Napping for less than 1 hour did not significantly impact CVD risk (HR: 1.03; 95% CI: 0.87-1.12; I2 = 86.4%; P = 0.721). However, napping for 1 hour or more was linked to a 1.37-fold increased risk of CVD (HR: 1.37; 95% CI: 1.09-1.71; I2 = 68.3%; P = 0.007). CONCLUSIONS Our meta-analysis indicates that taking a nap increases the risk of overall mortality and CVD mortality. It highlights that the long duration time of the nap can serve as a risk factor for evaluating both overall mortality and cardiovascular mortality.
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Affiliation(s)
- Meng Wang
- Department of Nursing, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Xin Xiang
- College of Acupuncture and Massage, Changchun University of Chinese Medicine, Changchun City, Jilin Province, China
| | - Zhengyan Zhao
- Department of Endocrinology, Zhengzhou Seventh People’s Hospital, Zhengzhou City, Henan Province, China
| | - Yu liu
- Emergency Medicine Department of the Second Mobile Contingent Hospital of the Chinese People’s Armed Police Forces, Wuxi City, Jiangsu Province, China
| | - Yang Cao
- Department of Nursing, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Weiwei Guo
- Department of Nursing, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Linlin Hou
- Henan Provincial People’s Hospital, Zhengzhou City, Henan Province, China
| | - Qiuhuan Jiang
- Henan Provincial People’s Hospital, Zhengzhou City, Henan Province, China
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Duan Y, Fu H, Gao J, Wang S, Chen C, Zhao Y, Jiang S, Wang C. Associations of prediabetes and sleep duration, and inflammation as a mediator in the China Health and Retirement Longitudinal Study. Sleep Health 2024; 10:470-477. [PMID: 38749824 DOI: 10.1016/j.sleh.2024.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 01/21/2024] [Accepted: 01/31/2024] [Indexed: 08/10/2024]
Abstract
OBJECTIVE The objective of this study was to examine the relationship between sleep duration and prediabetes, as well as to evaluate the influence of inflammation in mediating this association. METHODS A total of 4632 participants from the China Health and Retirement Longitudinal Study (CHARLS) were included in this study, comprising both baseline and 4-year follow-up data. The prospective relationship between sleep duration and the risk of prediabetes was examined using logistic regression models. We used multinomial logistic regression to evaluate the impact of prediabetes on sleep duration changes over follow-up, assessing the role of C-reactive protein in the association using mediation analysis. RESULTS Participants with short sleep duration (<5 hours) had a higher risk of prediabetes (odds ratios=1.381 [95% CI: 1.028-1.857]) compared to those with normal sleep durations (7-8 hours). However, excessive sleep durations (≥9 hours) did not show a statistically significant association with prediabetes risk. Moreover, individuals at least 60years old who experienced short sleep durations exhibited a higher risk of prediabetes. Individuals with prediabetes were more likely to have shorter sleep duration than excessive sleep duration (relative risk ratios=1.280 [95% CI: 1.059-1.547]). The mediation analysis revealed a mediating effect of C-reactive protein on the association between prediabetes and reduced sleep duration. CONCLUSIONS Short sleep duration was identified as a risk factor for the incidence of prediabetes. Conversely, prediabetes was found to contribute to shorter sleep duration rather than excessive sleep duration. Moreover, elevated levels of C-reactive protein may serve as a potential underlying mechanism that links prediabetes with shorter sleep.
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Affiliation(s)
- Yanran Duan
- Hospital Management Departments, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Health Policy Research Center, Institute for Hospital Management of Henan Province, Zhengzhou, China
| | - Hang Fu
- Hospital Management Departments, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Health Policy Research Center, Institute for Hospital Management of Henan Province, Zhengzhou, China
| | - Jinghong Gao
- Hospital Management Departments, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Health Policy Research Center, Institute for Hospital Management of Henan Province, Zhengzhou, China
| | - Sufan Wang
- Hospital Management Departments, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Health Policy Research Center, Institute for Hospital Management of Henan Province, Zhengzhou, China
| | - Changying Chen
- Hospital Management Departments, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Health Policy Research Center, Institute for Hospital Management of Henan Province, Zhengzhou, China
| | - Yaojun Zhao
- Operation Management Department, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, China
| | - Shuai Jiang
- Hospital Management Departments, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Health Policy Research Center, Institute for Hospital Management of Henan Province, Zhengzhou, China.
| | - Chengzeng Wang
- Hospital Management Departments, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Health Policy Research Center, Institute for Hospital Management of Henan Province, Zhengzhou, China.
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Diao T, Liu K, Lyu J, Zhou L, Yuan Y, Yang H, Wu T, Zhang X. Changes in Sleep Patterns, Genetic Susceptibility, and Incident Cardiovascular Disease in China. JAMA Netw Open 2024; 7:e247974. [PMID: 38652473 PMCID: PMC11040405 DOI: 10.1001/jamanetworkopen.2024.7974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 02/21/2024] [Indexed: 04/25/2024] Open
Abstract
Importance The associations of changes in sleep patterns with incident cardiovascular disease (CVD) are not fully elucidated, and whether these associations are modified by genetic susceptibility remains unknown. Objectives To investigate the associations of 5-year changes in sleep patterns with incident CVD and whether genetic susceptibility modifies these associations. Design, Setting, and Participants This prospective cohort study of the Dongfeng-Tongji cohort was conducted from 2008 to 2018 in China. Eligible participants included those with complete sleep information at baseline survey (2008-2010) and the first follow-up survey (2013); participants who had no CVD or cancer in 2013 were prospectively assessed until 2018. Statistical analysis was performed in November 2023. Exposures Five-year changes in sleep patterns (determined by bedtime, sleep duration, sleep quality, and midday napping) between 2008 and 2013, and polygenic risk scores (PRS) for coronary heart disease (CHD) and stroke. Main Outcomes and Measures Incident CVD, CHD, and stroke were identified from 2013 to 2018. Cox proportional hazards regression models were applied to estimate hazard ratios (HRs) and 95% CIs. Results Among 15 306 individuals (mean [SD] age, 65.8 [7.4] years; 8858 [57.9%] female and 6448 male [42.1%]), 5474 (35.78%) had persistent unfavorable sleep patterns and 3946 (25.8%) had persistent favorable sleep patterns. A total of 3669 incident CVD cases were documented, including 2986 CHD cases and 683 stroke cases, over a mean (SD) follow-up of 4.9 (1.5) years. Compared with those with persistent unfavorable sleep patterns, individuals with persistent favorable sleep patterns over 5 years had lower risks of incident CVD (HR, 0.80; 95% CI, 0.73-0.87), CHD (HR, 0.84; 95% CI, 0.76-0.92), and stroke (HR, 0.66; 95% CI, 0.54-0.82) in the subsequent 5-year period. No significant effect modification by PRS was observed for sleep pattern change and CHD or stroke risk. However, sleep pattern changes and PRS were jointly associated with the CHD and stroke risk in a dose-dependent manner, with the lowest risk being among those with persistent favorable sleep patterns combined with low PRS (HR for CHD, 0.65; 95% CI, 0.52-0.82 and HR for stroke, 0.48; 95% CI, 0.29-0.79). Conclusions and Relevance In this cohort study of middle-aged and older Chinese adults, individuals with persistent favorable sleep patterns had a lower CVD risk, even among those with higher genetic risk. These findings highlight the importance of maintaining favorable sleep patterns for CVD prevention.
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Affiliation(s)
- Tingyue Diao
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kang Liu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- School of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Junrui Lyu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lue Zhou
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yu Yuan
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Handong Yang
- Department of Cardiovascular Diseases, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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