دورية أكاديمية

Sleep patterns and risk of chronic disease as measured by long-term monitoring with commercial wearable devices in the All of Us Research Program.

التفاصيل البيبلوغرافية
العنوان: Sleep patterns and risk of chronic disease as measured by long-term monitoring with commercial wearable devices in the All of Us Research Program.
المؤلفون: Zheng NS; Yale School of Medicine, Yale University, New Haven, CT, USA.; Brigham and Women's Hospital, Boston, MA, USA., Annis J; Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA.; Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.; Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, USA., Master H; Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA.; Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA., Han L; Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.; Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA., Gleichauf K; Google, Mountain View, CA, USA., Ching JH; Google, Mountain View, CA, USA., Nasser M; Nelson Connects, San Francisco, CA, USA., Coleman P; Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA., Desine S; Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA., Ruderfer DM; Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.; Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Hernandez J; Google, Mountain View, CA, USA., Schneider LD; Google, Mountain View, CA, USA.; Sleep Medicine Center, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Redwood City, CA, USA., Brittain EL; Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA. evan.brittain@vumc.org.; Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, USA. evan.brittain@vumc.org.
المصدر: Nature medicine [Nat Med] 2024 Sep; Vol. 30 (9), pp. 2648-2656. Date of Electronic Publication: 2024 Jul 19.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Nature Publishing Company Country of Publication: United States NLM ID: 9502015 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1546-170X (Electronic) Linking ISSN: 10788956 NLM ISO Abbreviation: Nat Med Subsets: MEDLINE
أسماء مطبوعة: Publication: New York Ny : Nature Publishing Company
Original Publication: New York, NY : Nature Pub. Co., [1995-
مواضيع طبية MeSH: Wearable Electronic Devices* , Sleep*/physiology, Humans ; Female ; Middle Aged ; Male ; Chronic Disease ; Adult ; United States/epidemiology ; Polysomnography ; Risk Factors ; Cross-Sectional Studies ; Aged
مستخلص: Poor sleep health is associated with increased all-cause mortality and incidence of many chronic conditions. Previous studies have relied on cross-sectional and self-reported survey data or polysomnograms, which have limitations with respect to data granularity, sample size and longitudinal information. Here, using objectively measured, longitudinal sleep data from commercial wearable devices linked to electronic health record data from the All of Us Research Program, we show that sleep patterns, including sleep stages, duration and regularity, are associated with chronic disease incidence. Of the 6,785 participants included in this study, 71% were female, 84% self-identified as white and 71% had a college degree; the median age was 50.2 years (interquartile range = 35.7, 61.5) and the median sleep monitoring period was 4.5 years (2.5, 6.5). We found that rapid eye movement sleep and deep sleep were inversely associated with the odds of incident atrial fibrillation and that increased sleep irregularity was associated with increased odds of incident obesity, hyperlipidemia, hypertension, major depressive disorder and generalized anxiety disorder. Moreover, J-shaped associations were observed between average daily sleep duration and hypertension, major depressive disorder and generalized anxiety disorder. These findings show that sleep stages, duration and regularity are all important factors associated with chronic disease development and may inform evidence-based recommendations on healthy sleeping habits.
(© 2024. The Author(s).)
References: Ayas, N. T. et al. A prospective study of sleep duration and coronary heart disease in women. Arch. Intern. Med. 163, 205–209 (2003). (PMID: 1254661110.1001/archinte.163.2.205)
Cappuccio, F. P., D’Elia, L., Strazzullo, P. & Miller, M. A. Quantity and quality of sleep and incidence of type 2 diabetes: a systematic review and meta-analysis. Diabetes Care 33, 414–420 (2010). (PMID: 1991050310.2337/dc09-1124)
Gangwisch, J. E. et al. Short sleep duration as a risk factor for hypertension: analyses of the first National Health and Nutrition Examination Survey. Hypertension 47, 833–839 (2006). (PMID: 1658541010.1161/01.HYP.0000217362.34748.e0)
Gangwisch, J. E., Malaspina, D., Boden-Albala, B. & Heymsfield, S. B. Inadequate sleep as a risk factor for obesity: analyses of the NHANES I. Sleep 28, 1289–1296 (2005). (PMID: 1629521410.1093/sleep/28.10.1289)
von Ruesten, A., Weikert, C., Fietze, I. & Boeing, H. Association of sleep duration with chronic diseases in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study. PLoS ONE 7, e30972 (2012). (PMID: 10.1371/journal.pone.0030972)
Cappuccio, F. P., D’Elia, L., Strazzullo, P. & Miller, M. A. Sleep duration and all-cause mortality: a systematic review and meta-analysis of prospective studies. Sleep 33, 585–592 (2010). (PMID: 20469800286487310.1093/sleep/33.5.585)
Foley, D., Ancoli-Israel, S., Britz, P. & Walsh, J. Sleep disturbances and chronic disease in older adults: results of the 2003 National Sleep Foundation Sleep in America Survey. J. Psychosom. Res. 56, 497–502 (2004). (PMID: 1517220510.1016/j.jpsychores.2004.02.010)
Cribb, L. et al. Sleep regularity and mortality: a prospective analysis in the UK Biobank. eLife 12, RP88359 (2023). (PMID: 379951261066692810.7554/eLife.88359)
Watson, N. F. et al. Recommended amount of sleep for a healthy adult: a joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society. Sleep 38, 843–844 (2015). (PMID: 260399634434546)
Quan, S. F. et al. The Sleep Heart Health Study: design, rationale, and methods. Sleep 20, 1077–1085 (1997). (PMID: 9493915)
Moon, C., Hagen, E. W., Johnson, H. M., Brown, R. L. & Peppard, P. E. Longitudinal sleep characteristics and hypertension status: results from the Wisconsin Sleep Cohort Study. J. Hypertens. 39, 683–691 (2021). (PMID: 331863221077317210.1097/HJH.0000000000002692)
Full, K. M. et al. Sleep irregularity and subclinical markers of cardiovascular disease: the multi-ethnic study of atherosclerosis. J. Am. Heart Assoc. 12, e027361 (2023). (PMID: 367898691011147710.1161/JAHA.122.027361)
Arnal, P. J. et al. The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep staging. Sleep 43, zsaa097 (2020). (PMID: 32433768775117010.1093/sleep/zsaa097)
de Zambotti, M., Goldstone, A., Claudatos, S., Colrain, I. M. & Baker, F. C. A validation study of Fitbit Charge 2 compared with polysomnography in adults. Chronobiol. Int. 35, 465–476 (2018). (PMID: 2923590710.1080/07420528.2017.1413578)
Lee, X. K. et al. Validation of a consumer sleep wearable device with actigraphy and polysomnography in adolescents across sleep opportunity manipulations. J. Clin. Sleep. Med. 15, 1337–1346 (2019). (PMID: 31538605676039610.5664/jcsm.7932)
Stucky, B. et al. Validation of Fitbit Charge 2 sleep and heart rate estimates against polysomnographic measures in shift workers: naturalistic study. J. Med. Internet Res. 23, e26476 (2021). (PMID: 34609317852738510.2196/26476)
Eylon, G., Tikotzky, L. & Dinstein, I. Performance evaluation of Fitbit Charge 3 and actigraphy vs. polysomnography: sensitivity, specificity, and reliability across participants and nights. Sleep Health 9, 407–416 (2023). (PMID: 3727039710.1016/j.sleh.2023.04.001)
Chinnoy, E. D. et al. Performance of seven consumer sleep-tracking devices compared with polysomnography. Sleep 44, zsaa291 (2021). (PMID: 10.1093/sleep/zsaa291)
Chinoy, E. D., Cuellar, J. A., Jameson, J. T. & Markwald, R. R. Performance of four commercial wearable sleep-tracking devices tested under unrestricted conditions at home in healthy young adults. Nat. Sci. Sleep 14, 493–516 (2022). (PMID: 35345630895740010.2147/NSS.S348795)
Haghayegh, S., Khoshnevis, S., Smolensky, M. H., Diller, K. R. & Castriotta, R. J. Performance assessment of new-generation Fitbit technology in deriving sleep parameters and stages. Chronobiol. Int. 37, 47–59 (2020). (PMID: 3171830810.1080/07420528.2019.1682006)
Burkart, S. et al. Comparison of multichannel and single-channel wrist-based devices with polysomnography to measure sleep in children and adolescents. J. Clin. Sleep Med. 17, 645–652 (2021). (PMID: 33174529802071110.5664/jcsm.8980)
Master, H. et al. Association of step counts over time with the risk of chronic disease in the All of Us Research Program. Nat. Med. 28, 2301–2308 (2022). (PMID: 36216933967180410.1038/s41591-022-02012-w)
Perry, A. S. et al. Association of longitudinal activity measures and diabetes risk: an analysis from the National Institutes of Health All of Us Research Program. J. Clin. Endocrinol. Metab. 108, 1101–1109 (2023). (PMID: 3645888110.1210/clinem/dgac695)
Stamatakis, E. et al. Association of wearable device-measured vigorous intermittent lifestyle physical activity with mortality. Nat. Med. 28, 2521–2529 (2022). (PMID: 36482104980027410.1038/s41591-022-02100-x)
Fang, Y., Forger, D. B., Frank, E., Sen, S. & Goldstein, C. Day-to-day variability in sleep parameters and depression risk: a prospective cohort study of training physicians. npj Digit. Med. 4, 28 (2021). (PMID: 33603132789286210.1038/s41746-021-00400-z)
All of Us Research Program Investigators et al. The ‘All of Us’ Research Program. N. Engl. J. Med. 381, 668–676 (2019).
Mayo, K. R. et al. The All of Us data and research center: creating a secure, scalable, and sustainable ecosystem for biomedical research. Annu. Rev. Biomed. Data Sci. 6, 443–464 (2023). (PMID: 375616001115747810.1146/annurev-biodatasci-122120-104825)
Mc Carthy, C. E. et al. Sleep patterns and the risk of acute stroke: results from the INTERSTROKE international case–control study. Neurology 100, e2191–e2203 (2023). (PMID: 10.1212/WNL.0000000000207249)
Al Lawati, N. M., Patel, S. R. & Ayas, N. T. Epidemiology, risk factors, and consequences of obstructive sleep apnea and short sleep duration. Prog. Cardiovasc. Dis. 51, 285–293 (2009). (PMID: 1911013010.1016/j.pcad.2008.08.001)
Linz, D. et al. Associations of obstructive sleep apnea with atrial fibrillation and continuous positive airway pressure treatment: a review. JAMA Cardiol. 3, 532–540 (2018). (PMID: 2954176310.1001/jamacardio.2018.0095)
Scott, H. et al. Sleep irregularity is associated with hypertension: findings from over 2 million nights with a large global population sample. Hypertension 80, 1117–1126 (2023). (PMID: 3697468210.1161/HYPERTENSIONAHA.122.20513)
Zhai, L., Zhang, H. & Zhang, D. Sleep duration and depression among adults: a meta-analysis of prospective studies. Depress. Anxiety 32, 664–670 (2015). (PMID: 2604749210.1002/da.22386)
Li, Y. et al. The brain structure and genetic mechanisms underlying the nonlinear association between sleep duration, cognition and mental health. Nat. Aging 2, 425–437 (2022). (PMID: 3711806510.1038/s43587-022-00210-2)
Ford, D. E. & Kamerow, D. B. Epidemiologic study of sleep disturbances and psychiatric disorders. An opportunity for prevention? JAMA 262, 1479–1484 (1989). (PMID: 276989810.1001/jama.1989.03430110069030)
Huang, T., Mariani, S. & Redline, S. Sleep irregularity and risk of cardiovascular events: the multi-ethnic study of atherosclerosis. J. Am. Coll. Cardiol. 75, 991–999 (2020). (PMID: 32138974723795510.1016/j.jacc.2019.12.054)
Irish, L. A., Kline, C. E., Gunn, H. E., Buysse, D. J. & Hall, M. H. The role of sleep hygiene in promoting public health: a review of empirical evidence. Sleep. Med. Rev. 22, 23–36 (2015). (PMID: 2545467410.1016/j.smrv.2014.10.001)
Zuraikat, F. M. et al. Sleep regularity and cardiometabolic heath: is variability in sleep patterns a risk factor for excess adiposity and glycemic dysregulation? Curr. Diab. Rep. 20, 38 (2020). (PMID: 32700156758434710.1007/s11892-020-01324-w)
Kwon, Y. et al. Association of sleep characteristics with atrial fibrillation: the Multi-Ethnic Study of Atherosclerosis. Thorax 70, 873–879 (2015). (PMID: 2598643610.1136/thoraxjnl-2014-206655)
Christensen, M. A. et al. Sleep characteristics that predict atrial fibrillation. Heart Rhythm 15, 1289–1295 (2018). (PMID: 29958805644838810.1016/j.hrthm.2018.05.008)
Chen, P. S., Chen, L. S., Fishbein, M. C., Lin, S. F. & Nattel, S. Role of the autonomic nervous system in atrial fibrillation: pathophysiology and therapy. Circ. Res. 114, 1500–1515 (2014). (PMID: 24763467404363310.1161/CIRCRESAHA.114.303772)
Somers, V. K., Dyken, M. E., Mark, A. L. & Abboud, F. M. Sympathetic-nerve activity during sleep in normal subjects. N. Engl. J. Med. 328, 303–307 (1993). (PMID: 841981510.1056/NEJM199302043280502)
Dhingra, L. S. et al. Use of wearable devices in individuals with or at risk for cardiovascular disease in the US, 2019 to 2020. JAMA Netw. Open 6, e2316634 (2023). (PMID: 372851571024874510.1001/jamanetworkopen.2023.16634)
Beattie, Z. et al. Estimation of sleep stages in a healthy adult population from optical plethysmography and accelerometer signals. Physiol. Meas. 38, 1968–1979 (2017). (PMID: 2908796010.1088/1361-6579/aa9047)
Lim, S. E., Kim, H. S., Lee, S. W., Bae, K. H. & Baek, Y. H. Validation of Fitbit Inspire 2(TM) against polysomnography in adults considering adaptation for use. Nat. Sci. Sleep 15, 59–67 (2023). (PMID: 36879665998540310.2147/NSS.S391802)
Younes, M. et al. Reliability of the American Academy of Sleep Medicine rules for assessing sleep depth in clinical practice. J. Clin. Sleep Med. 14, 205–213 (2018). (PMID: 29351821578683910.5664/jcsm.6934)
Younes, M., Raneri, J. & Hanly, P. Staging sleep in polysomnograms: analysis of inter-scorer variability. J. Clin. Sleep Med. 12, 885–894 (2016). (PMID: 27070243487732210.5664/jcsm.5894)
Master, H. et al. How Fitbit data are being made available to registered researchers in All of Us Research Program. Pac. Symp. Biocomput. 28, 19–30 (2023). (PMID: 365409619811842)
McCauley, P. et al. A new mathematical model for the homeostatic effects of sleep loss on neurobehavioral performance. J. Theor. Biol. 256, 227–239 (2009). (PMID: 1893818110.1016/j.jtbi.2008.09.012)
Denny, J. C. et al. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations. Bioinformatics 26, 1205–1210 (2010). (PMID: 20335276285913210.1093/bioinformatics/btq126)
Wu, P. et al. Mapping ICD-10 and ICD-10-CM codes to phecodes: workflow development and initial evaluation. JMIR Med. Inform. 7, e14325 (2019). (PMID: 31553307691122710.2196/14325)
Zheng, N. S. et al. PheMap: a multi-resource knowledge base for high-throughput phenotyping within electronic health records. J. Am. Med. Inform. Assoc. 27, 1675–1687 (2020). (PMID: 32974638775114010.1093/jamia/ocaa104)
Friligkou, E. et al. Integrating genome-wide information and wearable device data to explore the link of anxiety and antidepressants with heart rate variability. Preprint at medRxiv https://doi.org/10.1101/2023.08.02.23293170 (2023).
معلومات مُعتمدة: U2C OD023196 United States OD NIH HHS; R21 HL172038 United States HL NHLBI NIH HHS; OT2 OD025315 United States OD NIH HHS; OT2 OD026551 United States OD NIH HHS; U24 OD023121 United States OD NIH HHS; OT2 OD026552 United States OD NIH HHS; OT2 OD025337 United States OD NIH HHS; OT2 OD025277 United States OD NIH HHS; OT2 OD026550 United States OD NIH HHS; R33 HL158941 United States HL NHLBI NIH HHS; OT2 OD026553 United States OD NIH HHS; OT2 OD025276 United States OD NIH HHS; OT2 OD026557 United States OD NIH HHS; OT2 OD026554 United States OD NIH HHS; U24 OD023163 United States OD NIH HHS; OT2 OD023206 United States OD NIH HHS; OT2 OD026556 United States OD NIH HHS; R01 FD007627 United States FD FDA HHS; HL158941 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI); U24 OD023176 United States OD NIH HHS; OT2 OD026548 United States OD NIH HHS; OT2 OD026549 United States OD NIH HHS; R61 HL158941 United States HL NHLBI NIH HHS; FD007627 U.S. Department of Health & Human Services | U.S. Food and Drug Administration (U.S. Food & Drug Administration); OT2 OD026555 United States OD NIH HHS; OT2 OD023205 United States OD NIH HHS; HL172038 U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
تواريخ الأحداث: Date Created: 20240719 Date Completed: 20240917 Latest Revision: 20240921
رمز التحديث: 20240921
مُعرف محوري في PubMed: PMC11405268
DOI: 10.1038/s41591-024-03155-8
PMID: 39030265
قاعدة البيانات: MEDLINE
الوصف
تدمد:1546-170X
DOI:10.1038/s41591-024-03155-8