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Epidemiology

A double-edged sword: the association of daytime napping duration and metabolism related diseases in a Chinese population

European Journal of Clinical Nutrition volume 75, pages 291–298 (2021)Cite this article

Subjects

Abstract

Background

Some studies have suggested that daytime napping may increase the risk of type 2 diabetes. However, limited data have revealed the association between nap duration and other metabolic diseases. Data from the baseline survey of Lanxi Cohort Study, a population-based study of natural residents in Zhejiang Province, China, were used to investigate the relationship between nap duration and metabolic abnormalities.

Methods

A total of 3236 participants underwent a physical examination, laboratory tests, and face to face interview. They were categorized into four groups according to nap duration. Logistic regression models were used to examine the odds ratios (ORs) of napping duration with four metabolism-related diseases. Stratified analysis was further used to explore the interaction effects of gender and age on results.

Results

Compared to the no daytime napping group, people who napped during the daytime for more than 1 h were independently associated with a greater prevalence of diabetes (OR 1.56). Those who napped during the daytime within a half hour showed a lower prevalence of fatty liver, dyslipidemia, and central obesity. To be more specific, those who habitually napped during the daytime for more than 1 h exhibited an increasing prevalence of diabetes among female older than 50 years old. Those who habitually napped during the daytime within a half hour exhibited a decreasing prevalence of fatty liver and dyslipidemia among male <50 years old, and that of central obesity among female <50 years old.

Conclusions

Short daytime napping duration is associate with reduced rate of metabolism-related diseases and may protects people from negative health conditions, whereas long daytime napping duration is associate with higher prevalence of diabetes, which then can be harmful for health.

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Fig. 1: Prevalence of four obesity related diseases among people with different napping duation.

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References

  1. Fang W, Li Z, Wu L, Cao Z, Liang Y, Yang H, et al. Longer habitual afternoon napping is associated with a higher risk for impaired fasting plasma glucose and diabetes mellitus in older adults: results from the Dongfeng-Tongji cohort of retired workers. Sleep Med. 2013;14:950–4.

    Article  Google Scholar 

  2. Li J, Cacchione PZ, Hodgson N, Riegel B, Keenan BT, Scharf MT, et al. Afternoon napping and cognition in Chinese older adults: findings from the China Health and Retirement Longitudinal Study Baseline Assessment. J Am Geriatr Soc. 2017;65:373–80.

    Article  Google Scholar 

  3. Yamada T, Shojima N, Yamauchi T, Kadowaki T. J-curve relation between daytime nap duration and type 2 diabetes or metabolic syndrome: a dose-response meta-analysis. Sci Rep. 2016;6:38075.

    Article  CAS  Google Scholar 

  4. Dhand R, Sohal H. Good sleep, bad sleep! The role of daytime naps in healthy adults. Curr Opin Pulm Med. 2006;12:379–82.

    Article  Google Scholar 

  5. Shadyab AH, Kritz-Silverstein D, Laughlin GA, Wooten WJ, Barrett-Connor E, Araneta MR. Ethnic-specific associations of sleep duration and daytime napping with prevalent type 2 diabetes in postmenopausal women. Sleep Med. 2015;16:243–9.

    Article  Google Scholar 

  6. Liu R, Li Y, Mao Z, Liu X, Zhang H, Yang K, et al. Gender-specific independent and combined dose-response association of napping and night sleep duration with type 2 diabetes mellitus in rural Chinese adults: the RuralDiab study. Sleep Med. 2018;45:106–13.

    Article  Google Scholar 

  7. Wu J, Xu G, Shen L, Zhang Y, Song L, Yang S, et al. Daily sleep duration and risk of metabolic syndrome among middle-aged and older Chinese adults: cross-sectional evidence from the Dongfeng–Tongji cohort study. BMC Public Health. 2015;15:178.

    Article  CAS  Google Scholar 

  8. Fang W, Li Z, Wu L, Cao Z, Liang Y, Yang H, et al. Longer habitual afternoon napping is associated with a higher risk for impaired fasting plasma glucose and diabetes mellitus in older adults: results from the Dongfeng-Tongji cohort of retired workers. Sleep Med. 2013;14:950.

    Article  Google Scholar 

  9. Leng Y, Cappuccio FP, Surtees PG, Luben R, Brayne C, Khaw KT. Daytime napping, sleep duration and increased 8-year risk of type 2 diabetes in a British population. Nutr Metab Cardiovasc. 2016;26:996.

    Article  CAS  Google Scholar 

  10. Qu H, Wang H, Deng M, Wei H, Deng H. Associations between longer habitual day napping and non-alcoholic fatty liver disease in an elderly Chinese population. PLos ONE. 2014;9:e105583.

    Article  Google Scholar 

  11. Peng K, Lin L, Wang Z, Lin D, Huang Y, Wang P, et al. Short sleep duration and longer daytime napping are associated with non-alcoholic fatty liver disease in Chinese adults. J Diabetes. 2017;9:827–36. https://doi.org/10.1111/1753-0407.12489.

  12. Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Targher G, et al. Prevalence of insulin resistance in metabolic disorders: the Bruneck Study. Diabetes 1998;47:1643.

    Article  CAS  Google Scholar 

  13. Shi S, Ansari T, Mcguinness OP, Wasserman DH, Johnson CH. Circadian disruption leads to insulin resistance and obesity. Curr Biol. 2013;23:372.

    Article  CAS  Google Scholar 

  14. Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28:193–213.

    Article  CAS  Google Scholar 

  15. Li L, Wang HM, Shen Y. Chinese SF-36 health survey: translation, cultural adaptation, validation, and normalisation. J Epidemiol Community Health. 2003;57:259–63.

    Article  CAS  Google Scholar 

  16. Guidelines for the data processing and analysis of the International Physical Activity Questionnaire (IPAQ)—short and long forms. 2005. https://www.ipaq.ki.se/scoring.

  17. Zhou B-F. Cooperative Meta-Analysis Group of the Working Group on Obesity in C. Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults-study on optimal cut-off points of body mass index and waist circumference in Chinese adults. Biomed Environ Sci. 2002;15:83–96.

    PubMed  Google Scholar 

  18. Chamberlain JJ, Rhinehart AS, Shaefer CF Jr, Neuman A. Diagnosis and management of diabetes: synopsis of the 2016 American Diabetes Association Standards of Medical Care in Diabetes. Ann Intern Med. 2016;164:542–52.

    Article  Google Scholar 

  19. Lee J-Y, Ryu S, Cheong E, Joint Committee for Developing Chinese guidelines on Prevention and Treatment of Dyslipidemia in Adults Sung K-C. Chinese guidelines on prevention and treatment of dyslipidemia in adults. Zhonghua Xin Xue Guan Bing Za Zhi. 2007;35:390–419.

    Google Scholar 

  20. Joint Committee for Guideline R. 2018 Chinese Guidelines for Prevention and Treatment of Hypertension—a report of the Revision Committee of Chinese Guidelines for Prevention and Treatment of Hypertension. J Geriatr Cardiol. 2019;16:182–241.

    Google Scholar 

  21. Khan AS, Isik M, Set T, Akturk Z, Avsar U. A 5-year trend of myocardial infarction, hypertension, stroke and diabetes mellitus in gender and different age groups in Erzurum, Turkey. J Taibah Univ Med Sci. 2014;9:198–205.

    Google Scholar 

  22. Kautzky-Willer A, Handisurya A. Metabolic diseases and associated complications: sex and gender matter! Eur J Clin Investig. 2009;39:631–48.

    Article  CAS  Google Scholar 

  23. Wu J, Xu G, Shen L, Zhang Y, Song L, Yang S, et al. Daily sleep duration and risk of metabolic syndrome among middle-aged and older Chinese adults: cross-sectional evidence from the Dongfeng-Tongji cohort study. BMC Public Health. 2015;15:178.

    Article  CAS  Google Scholar 

  24. Lucassen EA, Rother KI, Cizza G. Interacting epidemics? Sleep curtailment, insulin resistance, and obesity. Ann NY Acad Sci. 2012;1264:110–34.

    Article  CAS  Google Scholar 

  25. Van den Berg JF, Knvistingh Neven A, Tulen JHM, Hofman A, Witteman JCM, Miedema HME, et al. Actigraphic sleep duration and fragmentation are related to obesity in the elderly: the Rotterdam study. Int J Obes. 2008;32:1083–90.

    Article  Google Scholar 

  26. Vgontzas AN, Liao D, Pejovic S, Calhoun S, Karataraki M, Bixler EO. Insomnia with objective short sleep duration is associated with type 2 diabetes: a population-based study. Diabetes Care. 2009;32:1980–5.

    Article  Google Scholar 

  27. Green CB, Takahashi JS, Bass J. The meter of metabolism. Cell. 2008;134:728–42.

    Article  CAS  Google Scholar 

  28. Marcheva B, Ramsey KM, Buhr ED, Kobayashi Y, Su H, Ko CH, et al. Disruption of the clock components CLOCK and BMAL1 leads to hypoinsulinaemia and diabetes. Nature. 2010;466:627–31.

    Article  CAS  Google Scholar 

  29. Patel SR, Hayes AL, Blackwell T, Evans DS, Ancoli-Israel S, Wing YK, et al. The association between sleep patterns and obesity in older adults. Int J Obes. 2014;38:1159–64.

    Article  CAS  Google Scholar 

  30. Who’s at risk?: US Centers for Disease Control and Prevention; 2017. https://www.cdc.gov/diabetes/basics/risk-factors.html.

  31. Wamsley EJ, Tucker MA, Payne JD, Stickgold R. A brief nap is beneficial for human route-learning: the role of navigation experience and EEG spectral power. Learn Mem. 2010;17:332–6.

    Article  Google Scholar 

  32. Shiryaev N, Jouroukhin Y, Giladi E, Polyzoidou E, Grigoriadis NC, Rosenmann H, et al. NAP protects memory, increases soluble tau and reduces tau hyperphosphorylation in a tauopathy model. Neurobiol Dis. 2009;34:381–8.

    Article  CAS  Google Scholar 

  33. Hayashi M, Motoyoshi N, Hori T. Recuperative power of a short daytime nap with or without stage 2 sleep. Sleep. 2005;28:829–36.

    PubMed  Google Scholar 

  34. Monk TH, Buysse DJ, Carrier J, Billy BD, Rose LR. Effects of afternoon “siesta” naps on sleep, alertness, performance, and circadian rhythms in the elderly. Sleep. 2001;24:680–7.

    Article  CAS  Google Scholar 

  35. Tanaka H, Taira K, Arakawa M, Toguti H, Urasaki C, Yamamoto Y, et al. Effects of short nap and exercise on elderly people having difficulty in sleeping. Psychiatry Clin Neurosci. 2001;55:173–4.

    Article  CAS  Google Scholar 

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Funding

This work was supported by Cyrus Tang Foundation (No. 419600-11102) and China Medical Board (CMB) Collaborating Program (No. 15-216 and 12-108).

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Authors and Affiliations

  1. Chronic Disease Research Institute, the Children’s Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China

    Xueyin Zhao, Shuyi Cen, Wenhui Lin, Min Yang, Fei Yang & Shankuan Zhu

  2. Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China

    Xueyin Zhao, Shuyi Cen, Wenhui Lin, Min Yang, Fei Yang & Shankuan Zhu

  3. Prince of Wales Clinical School, Faculty of Medicine, the University of New South Wales, Sydney, NSW, Australia

    Lin Cheng

  4. Hangzhou YITU Healthcare Technology Co. Ltd, Hangzhou, China

    Chaonan Zhu

  5. Red Cross Hospital of Lanxi City, Lanxi, Zhejiang, China

    Weifang Zheng

Authors
  1. Xueyin Zhao
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  7. Min Yang
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  9. Shankuan Zhu
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Contributions

XZ was responsible for designing the study questions, methods, participating the data collection, interpreting results, and writing the manuscript. LC was responsible for designing the study methods, conducting the literature research, and interpreting results. CZ was responsible for major data analysis, interpreting results, and providing feedbacks with each update. SC was responsible for organizing the manuscript, updating the reference list, and providing feedbacks with each update. WL, MY, FY, and WZ was responsible for collecting the data, interpreting results, and providing feedbacks with each update. SZ is the PI of Lanxi Cohort and was contributed to designing the study, managing data collection, and providing feedbacks with each update.

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Correspondence to Shankuan Zhu.

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Zhao, X., Cheng, L., Zhu, C. et al. A double-edged sword: the association of daytime napping duration and metabolism related diseases in a Chinese population. Eur J Clin Nutr 75, 291–298 (2021). https://doi.org/10.1038/s41430-020-00777-2

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