Inverted U-shaped relationship between sleep duration and phenotypic age in US adults: a population-based study.

Yanwei You, Yuquan Chen, Ruidong Liu, Yangchang Zhang, Meiqing Wang, Zihao Yang, Jianxiu Liu, Xindong Ma
Author Information
  1. Yanwei You: Division of Sports Science and Physical Education, Tsinghua University, Beijing, 100084, China.
  2. Yuquan Chen: School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing & Health Sciences, Monash University, Melbourne, VIC, 3004, Australia.
  3. Ruidong Liu: Division of Sports Science and Physical Education, Tsinghua University, Beijing, 100084, China.
  4. Yangchang Zhang: Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, 100169, China.
  5. Meiqing Wang: Division of Sports Science and Physical Education, Tsinghua University, Beijing, 100084, China.
  6. Zihao Yang: Division of Sports Science and Physical Education, Tsinghua University, Beijing, 100084, China.
  7. Jianxiu Liu: Division of Sports Science and Physical Education, Tsinghua University, Beijing, 100084, China. liujianxiu@mail.tsinghua.edu.cn.
  8. Xindong Ma: Division of Sports Science and Physical Education, Tsinghua University, Beijing, 100084, China. maxd@mail.tsinghua.edu.cn.

Abstract

Sleep is a modifiable behavior that can be targeted in interventions aimed at promoting healthy aging. This study aims to (i) identify the sleep duration trend in US adults; (ii) investigate the relationship between sleep duration and phenotypic age; and (iii) explore the role of exercise in this relationship. Phenotypic age as a novel index was calculated according to biomarkers collected from US adults based on the National Health and Nutrition Examination Survey (NHANES). Sleep information was self-reported by participants and discerned through individual interviews. The principal analytical method employed was weighted multivariable linear regression modeling, which accommodated for the complex multi-stage sampling design. The potential non-linear relationship was explored using a restricted cubic spline (RCS) model. Furthermore, subgroup analyses evaluated the potential effects of sociodemographic and lifestyle factors on the primary study outcomes. A total of 13,569 participants were finally included in, thereby resulting in a weighted population of 78,880,615. An examination of the temporal trends in sleep duration revealed a declining proportion of individuals with insufficient and markedly deficient sleep time since the 2015-2016 cycle. Taken normal sleep group as a reference, participants with extreme short sleep [β (95% CI) 0.582 (0.018, 1.146), p = 0.044] and long sleep [β (95% CI) 0.694 (0.186, 1.203), p = 0.010] were both positively associated with phenotypic age using the fully adjusted model. According to the dose-response relationship between sleep duration and phenotypic age, long sleep duration can benefit from regular exercise activity, whereas short sleep duration with more exercise tended to have higher phenotypic age. There is an inverted U-shaped relationship between short and long sleep durations and phenotypic age. This study represents an important step forward in our understanding of the complex relationship between sleep and healthy aging. By shedding light on this topic and providing practical exercise recommendations for promoting healthy sleep habits, researchers can help individuals live longer, healthier, and more fulfilling lives.

Keywords

References

  1. Front Genet. 2021 Jan 21;11:630186 [PMID: 33552142]
  2. Aging (Albany NY). 2018 Apr 18;10(4):573-591 [PMID: 29676998]
  3. J Affect Disord. 2022 Jan 1;296:183-188 [PMID: 34607059]
  4. Sleep Med. 2023 Oct;110:155-165 [PMID: 37595432]
  5. Brain Sci. 2023 Jan 19;13(2): [PMID: 36831714]
  6. Sleep Breath. 2022 Dec;26(4):2069-2075 [PMID: 34845630]
  7. Nat Hum Behav. 2021 Jan;5(1):113-122 [PMID: 33199855]
  8. Nat Rev Neurosci. 2008 Jan;9(1):58-65 [PMID: 18094706]
  9. Int J Cardiol. 2014 Oct 20;176(3):1187-9 [PMID: 25223816]
  10. Obesity (Silver Spring). 2022 Oct;30(10):1914-1916 [PMID: 36042009]
  11. Interface Focus. 2014 Oct 6;4(5):20140009 [PMID: 25285197]
  12. BMC Psychiatry. 2023 Sep 15;23(1):671 [PMID: 37715146]
  13. BMJ. 2016 Nov 1;355:i5210 [PMID: 27803010]
  14. Sleep. 2009 Mar;32(3):289-90 [PMID: 19294947]
  15. PLoS Med. 2018 Dec 31;15(12):e1002718 [PMID: 30596641]
  16. Lipids Health Dis. 2018 May 29;17(1):130 [PMID: 29843793]
  17. MMWR Morb Mortal Wkly Rep. 2016 Feb 19;65(6):137-41 [PMID: 26890214]
  18. Curr Diab Rep. 2014 Jul;14(7):507 [PMID: 24816752]
  19. Dev Cogn Neurosci. 2022 Aug;56:101130 [PMID: 35779333]
  20. Front Genet. 2021 Jun 15;12:663449 [PMID: 34211497]
  21. Commun Biol. 2021 Nov 18;4(1):1304 [PMID: 34795404]
  22. Sleep. 2006 Jul;29(7):881-9 [PMID: 16895254]
  23. EBioMedicine. 2017 Jul;21:29-36 [PMID: 28396265]
  24. PLoS One. 2017 Jul 24;12(7):e0181978 [PMID: 28738082]
  25. Heliyon. 2023 Aug 23;9(9):e19158 [PMID: 37810111]
  26. Rev Endocr Metab Disord. 2022 Dec;23(6):1323-1339 [PMID: 36152143]
  27. Sleep Med. 2015 May;16(5):559-63 [PMID: 25890781]
  28. Front Public Health. 2024 Jan 16;12:1197150 [PMID: 38292911]
  29. Sleep Med. 2023 Oct;110:7-16 [PMID: 37517285]
  30. Front Immunol. 2023 Jan 13;13:1080782 [PMID: 36713451]
  31. JAMA Neurol. 2021 Oct 1;78(10):1187-1196 [PMID: 34459862]
  32. BMC Public Health. 2023 Mar 14;23(1):489 [PMID: 36918831]
  33. Nutrients. 2024 Mar 08;16(6): [PMID: 38542688]
  34. J Pediatr. 2017 Aug;187:247-252.e1 [PMID: 28602380]
  35. Front Aging Neurosci. 2022 Dec 22;14:1042488 [PMID: 36620763]
  36. Sleep. 2013 Oct 01;36(10):1421-7 [PMID: 24082301]
  37. Front Aging Neurosci. 2023 Jun 22;15:1214748 [PMID: 37424629]
  38. Biochem Med (Zagreb). 2019 Oct 15;29(3):030501 [PMID: 31379458]
  39. PLoS One. 2011;6(8):e23462 [PMID: 21853136]
  40. Sleep. 2024 May 10;47(5): [PMID: 37943833]
  41. Sleep. 2015 Aug 01;38(8):1161-83 [PMID: 26194576]
  42. Minerva Pediatr. 2017 Aug;69(4):326-336 [PMID: 28211649]
  43. Biochem Pharmacol. 2021 Sep;191:114563 [PMID: 33857490]
  44. JAMA. 2018 Nov 20;320(19):2020-2028 [PMID: 30418471]
  45. BMC Med. 2022 Jun 17;20(1):207 [PMID: 35710548]
  46. Trends Neurosci. 2023 Apr;46(4):255-256 [PMID: 36764881]
  47. J Sleep Res. 2022 Oct;31(5):e13578 [PMID: 35253300]
  48. MMWR Morb Mortal Wkly Rep. 2009 Oct 30;58(42):1175-9 [PMID: 19875979]
  49. J Neurosci. 2023 Jul 12;43(28):5241-5250 [PMID: 37365003]
  50. Best Pract Res Clin Rheumatol. 2020 Apr;34(2):101504 [PMID: 32249021]
  51. Sleep Health. 2015 Mar;1(1):40-43 [PMID: 29073412]
  52. PeerJ. 2024 Feb 28;12:e17057 [PMID: 38436025]
  53. Aging Cell. 2022 May;21(5):e13610 [PMID: 35421261]
  54. J Sleep Res. 2009 Jun;18(2):148-58 [PMID: 19645960]
  55. J Gerontol A Biol Sci Med Sci. 2013 Jun;68(6):667-74 [PMID: 23213031]
  56. Am J Prev Med. 2016 Aug;51(2):206-215 [PMID: 27178884]
  57. Neuropsychopharmacology. 2017 Jan;42(1):129-155 [PMID: 27510422]
  58. Eur J Clin Invest. 2018 Feb;48(2): [PMID: 29231988]
  59. Aging (Albany NY). 2022 Jun 6;14(11):4622-4623 [PMID: 35666709]
  60. J Affect Disord. 2021 Dec 1;295:1377-1385 [PMID: 34565593]
  61. Sleep Med Clin. 2018 Mar;13(1):1-11 [PMID: 29412976]
  62. BMC Public Health. 2023 Jul 31;23(1):1465 [PMID: 37525176]
  63. Sleep. 2009 Mar;32(3):295-301 [PMID: 19294949]
  64. J Clin Endocrinol Metab. 2015 Sep;100(9):E1255-61 [PMID: 26168277]
  65. Sleep Med Rev. 2015 Apr;20:59-72 [PMID: 25127157]

MeSH Term

Adult
Humans
Nutrition Surveys
Sleep Duration
Cross-Sectional Studies
Sleep
Risk Factors
Sleep Wake Disorders

Word Cloud

Created with Highcharts 10.0.0sleepagedurationrelationshipphenotypicstudyUSexercise0SleepcanhealthyparticipantsshortlongpromotingagingadultsPhenotypicweightedcomplexpotentialusingmodelpopulationindividuals95%CI1p = 0U-shapedmodifiablebehaviortargetedinterventionsaimedaimsidentifytrendiiinvestigateiiiexplorerolenovelindexcalculatedaccordingbiomarkerscollectedbasedNationalHealthNutritionExaminationSurveyNHANESinformationself-reporteddiscernedindividualinterviewsprincipalanalyticalmethodemployedmultivariablelinearregressionmodelingaccommodatedmulti-stagesamplingdesignnon-linearexploredrestrictedcubicsplineRCSFurthermoresubgroupanalysesevaluatedeffectssociodemographiclifestylefactorsprimaryoutcomestotal13569finallyincludedtherebyresulting78880615examinationtemporaltrendsrevealeddecliningproportioninsufficientmarkedlydeficienttimesince2015-2016cycleTakennormalgroupreferenceextreme582018146044]694186203010]positivelyassociatedfullyadjustedAccordingdose-responsebenefitregularactivitywhereastendedhigherinverteddurationsrepresentsimportantstepforwardunderstandingsheddinglighttopicprovidingpracticalrecommendationshabitsresearchershelplivelongerhealthierfulfillinglivesInvertedadults:population-basedCross-sectionalExercise

Similar Articles

Cited By