IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i11p6154-d570265.html
   My bibliography  Save this article

Sleep Duration and Waking Activities in Relation to the National Sleep Foundation’s Recommendations: An Analysis of US Population Sleep Patterns from 2015 to 2017

Author

Listed:
  • Michael Osei Mireku

    (School of Psychology, University of Lincoln, Lincoln LN6 7TS, UK
    Lincoln Sleep Research (LiSReC), University of Lincoln, Lincoln LN6 7TS, UK
    Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK)

  • Alina Rodriguez

    (Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
    Centre for Psychiatry, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London EC1M 6BQ, UK)

Abstract

The objective was to investigate the association between time spent on waking activities and nonaligned sleep duration in a representative sample of the US population. We analysed time use data from the American Time Use Survey (ATUS), 2015–2017 ( N = 31,621). National Sleep Foundation (NSF) age-specific sleep recommendations were used to define recommended (aligned) sleep duration. The balanced, repeated, replicate variance estimation method was applied to the ATUS data to calculate weighted estimates. Less than half of the US population had a sleep duration that mapped onto the NSF recommendations, and alignment was higher on weekdays (45%) than at weekends (33%). The proportion sleeping longer than the recommended duration was higher than those sleeping shorter on both weekdays and weekends ( p < 0.001). Time spent on work, personal care, socialising, travel, TV watching, education, and total screen time was associated with nonalignment to the sleep recommendations. In comparison to the appropriate recommended sleep group, those with a too-short sleep duration spent more time on work, travel, socialising, relaxing, and leisure. By contrast, those who slept too long spent relatively less time on each of these activities. The findings indicate that sleep duration among the US population does not map onto the NSF sleep recommendations, mostly because of a higher proportion of long sleepers compared to short sleepers. More time spent on work, travel, and socialising and relaxing activities is strongly associated with an increased risk of nonalignment to NSF sleep duration recommendations.

Suggested Citation

  • Michael Osei Mireku & Alina Rodriguez, 2021. "Sleep Duration and Waking Activities in Relation to the National Sleep Foundation’s Recommendations: An Analysis of US Population Sleep Patterns from 2015 to 2017," IJERPH, MDPI, vol. 18(11), pages 1-15, June.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:11:p:6154-:d:570265
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/11/6154/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/11/6154/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Katharine G. Abraham & Aaron Maitland & Suzanne M. Bianchi, 2006. "Non-response in the American Time Use Survey: Who Is Missing from the Data and How Much Does It Matter?," NBER Technical Working Papers 0328, National Bureau of Economic Research, Inc.
    2. Tomislav Krističević & Lovro Štefan & Goran Sporiš, 2018. "The Associations between Sleep Duration and Sleep Quality with Body-Mass Index in a Large Sample of Young Adults," IJERPH, MDPI, vol. 15(4), pages 1-10, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jing-Yi Ai & Garry Kuan & Linda Ya-Ting Juang & Ching-Hsiu Lee & Yee-Cheng Kueh & I-Hua Chu & Xiao-Ling Geng & Yu-Kai Chang, 2022. "Effects of Multi-Component Exercise on Sleep Quality in Middle-Aged Adults," IJERPH, MDPI, vol. 19(23), pages 1-11, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Joshua Graff Zivin & Matthew Neidell, 2014. "Temperature and the Allocation of Time: Implications for Climate Change," Journal of Labor Economics, University of Chicago Press, vol. 32(1), pages 1-26.
    2. Daniel S. Hamermesh & Katie R. Genadek & Michael C. Burda, 2022. "Reply to “Racial Differences in Time at Work Not Working†by William A. Darity Jr. et al," ILR Review, Cornell University, ILR School, vol. 75(3), pages 573-577, May.
    3. Jens Bonke & Mette Deding & Mette Lausten & Leslie S. Stratton, 2008. "Intra‐Household Specialization in Housework in the United States and Denmark," Social Science Quarterly, Southwestern Social Science Association, vol. 89(4), pages 1023-1043, December.
    4. Arenas-Arroyo, Esther & Schmidpeter, Bernhard, 2022. "Spillover effects of immigration policies on children's human capital," Ruhr Economic Papers 974, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. Borgschulte, Mark & Cho, Heepyung & Lubotsky, Darren, 2022. "Partisanship and survey refusal," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 332-357.
    6. Charlene Kalenkoski & Karen Hamrick & Margaret Andrews, 2011. "Time Poverty Thresholds and Rates for the US Population," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 104(1), pages 129-155, October.
    7. Han, Jeehoon & Meyer, Bruce D. & Sullivan, James X., 2020. "Inequality in the joint distribution of consumption and time use," Journal of Public Economics, Elsevier, vol. 191(C).
    8. te Braak Petrus & Minnen Joeri & Glorieux Ignace, 2020. "The Representativeness of Online Time Use Surveys. Effects of Individual Time Use Patterns and Survey Design on the Timing of Survey Dropout," Journal of Official Statistics, Sciendo, vol. 36(4), pages 887-906, December.
    9. McCarthy, Jaki S. & Jacob, Thomas & McCraken, Amanda, 2010. "Modeling Non-response in National Agricultural Statistics Service (NASS) Surveys Using Classification Trees," NASS Research Reports 235029, United States Department of Agriculture, National Agricultural Statistics Service.
    10. Stella Chatzitheochari & Sara Arber, 2011. "Identifying the Third Agers: An Analysis of British Retirees' Leisure Pursuits," Sociological Research Online, , vol. 16(4), pages 44-55, December.
    11. Laura Fumagalli & Heather Laurie & Peter Lynn, 2013. "Experiments with methods to reduce attrition in longitudinal surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 499-519, February.
    12. Jay Stewart & Harley Frazis, 2019. "The importance and challenges of measuring work hours," IZA World of Labor, Institute of Labor Economics (IZA), pages 1-95, July.
    13. Lovro Štefan & Maja Horvatin & Mario Baić, 2019. "Are Sedentary Behaviors Associated with Sleep Duration? A Cross-Sectional Case from Croatia," IJERPH, MDPI, vol. 16(2), pages 1-8, January.
    14. Switek, Maggie, 2012. "Internal Migration and Life Satisfaction: Well-Being Effects of Moving as a Young Adult," IZA Discussion Papers 7016, Institute of Labor Economics (IZA).
    15. Burns, Christopher & Prager, Daniel & Ghosh, Sujit & Goodwin, Barry, 2015. "Imputing for Missing Data in the ARMS Household Section: A Multivariate Imputation Approach," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205291, Agricultural and Applied Economics Association.
    16. Malgorzata Switek, 2016. "Internal Migration and Life Satisfaction: Well-Being Paths of Young Adult Migrants," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 125(1), pages 191-241, January.
    17. Felderer Barbara & Kirchner Antje & Kreuter Frauke, 2019. "The Effect of Survey Mode on Data Quality: Disentangling Nonresponse and Measurement Error Bias," Journal of Official Statistics, Sciendo, vol. 35(1), pages 93-115, March.
    18. Hamermesh, Daniel S., 2010. "Incentives, time use and BMI: The roles of eating, grazing and goods," Economics & Human Biology, Elsevier, vol. 8(1), pages 2-15, March.
    19. Julie L. Hotchkiss, 2019. "US Decennial Census return rates: the role of social capital," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 46(5), pages 648-668, January.
    20. Malgorzata Switek & Richard A. Easterlin, 2018. "Life Transitions and Life Satisfaction During Young Adulthood," Journal of Happiness Studies, Springer, vol. 19(1), pages 297-314, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:11:p:6154-:d:570265. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.