Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review
  • Published:

Correlates of Lifestyle and Obesity

Associations between sleep patterns and lifestyle behaviors in children: an international comparison

International Journal of Obesity Supplements volume 5, pages S59–S65 (2015)Cite this article

Subjects

Abstract

OBJECTIVES:

Although evidence is accumulating on the importance of a good night’s sleep for healthy eating and activity behaviors, existing research has mainly been conducted in high-income, developed countries with limited sociocultural variability. This study is the first to examine the associations between sleep patterns and lifestyle behaviors in children from 12 countries in five major geographic regions of the world.

METHODS:

This observational, multinational cross-sectional study included 5777 children aged 9–11 years from sites in Australia, Brazil, Canada, China, Colombia, Finland, India, Kenya, Portugal, South Africa, the United Kingdom and the United States. Nocturnal sleep duration (hours per night), sleep efficiency (%) and bedtime (h:min) were monitored over 7 consecutive days using an accelerometer. Lifestyle behaviors included moderate-to-vigorous physical activity (MVPA), total sedentary time (SED), self-reported screen time (ST) and healthy/unhealthy diet patterns (HDP/UDP). Multilevel modeling analyses were used to account for the hierarchical nature of the data.

RESULTS:

Overall, participants averaged 8.8 (s.d. 0.9) hours of sleep with 96.2% (s.d. 1.4) sleep efficiency and a mean bedtime of 2218 hours. After adjustment for age, sex, highest parental education and BMI z-score, results showed that (i) sleep duration was negatively associated with MVPA, SED and UDP score; (ii) sleep efficiency was negatively associated with MVPA and UDP score, and positively associated with SED; and (iii) later bedtime was positively associated with SED, ST and UDP score, and negatively associated with MVPA and HDP score. Results using categories of sleep patterns were consistent with the linear associations. Results also revealed that associations between sleep patterns and MVPA, SED and ST were significantly different between study sites, with stronger associations in high-income countries compared with low/middle-income countries.

CONCLUSIONS:

Sleep characteristics are important correlates of lifestyle behaviors in children. Differences between countries suggest that interventions aimed at improving sleep and lifestyle behaviors should be culturally adapted.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 3
Figure 2

Similar content being viewed by others

References

  1. Ohayon MM . Determining the level of sleepiness in the American population and its correlates. J Psychiatr Res 2012; 46: 422–427.

    Article  PubMed  Google Scholar 

  2. Akerstedt T, Nilsson PM . Sleep as restitution: an introduction. J Intern Med 2003; 254: 6–12.

    Article  CAS  PubMed  Google Scholar 

  3. Matricciani L, Olds T, Petkov J . In search of lost sleep: secular trends in the sleep time of school-aged children and adolescents. Sleep Med Rev 2012; 16: 203–211.

    Article  PubMed  Google Scholar 

  4. Keyes KM, Maslowsky J, Hamilton A, Schulenberg J . The Great Sleep Recession: changes in sleep duration among US adolescents, 1991-2012. Pediatrics 2015; 135: 460–468.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Gruber R, Carrey N, Weiss SK, Frappier JY, Rourke L, Brouillette RT et al. Position statement on pediatric sleep for psychiatrists. J Can Acad Child Adolesc Psychiatry 2014; 23: 174–195.

    PubMed  PubMed Central  Google Scholar 

  6. Schmid SM, Hallschmid M, Schultes B . The metabolic burden of sleep loss. Lancet Diabetes Endocrinol 2015; 3: 52–62.

    Article  CAS  PubMed  Google Scholar 

  7. Chaput JP, Tremblay A . Insufficient sleep as a contributor to weight gain: an update. Curr Obes Rep 2012; 1: 245–256.

    Article  Google Scholar 

  8. Cappuccio FP, Taggart FM, Kandala NB, Currie A, Peile E, Stranges S et al. Meta-analysis of short sleep duration and obesity in children and adults. Sleep 2008; 31: 619–626.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Chen X, Beydoun MA, Wang Y . Is sleep duration associated with childhood obesity? A systematic review and meta-analysis. Obesity (Silver Spring) 2008; 16: 265–274.

    Article  Google Scholar 

  10. Rüger M, Scheer FA . Effects of circadian disruption on the cardiometabolic system. Rev Endocr Metab Disord 2009; 10: 245–260.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Baron KG, Reid KJ, Kern AS, Zee PC . Role of sleep timing in caloric intake and BMI. Obesity (Silver Spring) 2011; 19: 1374–1381.

    Article  Google Scholar 

  12. Arora T, Taheri S . Associations among late chronotype, body mass index and dietary behaviors in young adolescents. Int J Obes 2015; 39: 39–44.

    Article  CAS  Google Scholar 

  13. Golley RK, Maher CA, Matricciani L, Olds TS . Sleep duration or bedtime? Exploring the association between sleep timing behaviour, diet and BMI in children and adolescents. Int J Obes 2013; 37: 546–551.

    Article  CAS  Google Scholar 

  14. Olds TS, Maher CA, Matricciani L . Sleep duration or bedtime? Exploring the relationship between sleep habits and weight status and activity patterns. Sleep 2011; 34: 1299–1307.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Chaput JP . Sleep patterns, diet quality and energy balance. Physiol Behav 2014; 134: 86–91.

    Article  CAS  PubMed  Google Scholar 

  16. Katzmarzyk PT, Barreira TV, Broyles ST, Champagne CM, Chaput JP, Fogelholm M et al. The International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE): design and methods. BMC Public Health 2013; 13: 900.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Barreira TV, Schuna JM Jr, Mire EF, Katzmarzyk PT, Chaput JP, Leduc G, Tudor-Locke C . Identifying children’s nocturnal sleep using a 24-h waist accelerometry. Med Sci Sports Exerc 2015; 47: 937–943.

    Article  PubMed  Google Scholar 

  18. Tudor-Locke C, Barreira TV, Schuna JM Jr, Mire EF, Katzmarzyk PT . Fully automated waist-worn accelerometer algorithm for detecting children’s sleep-period time separate from 24-h physical activity or sedentary behaviors. Appl Physiol Nutr Metab 2014; 39: 53–57.

    Article  PubMed  Google Scholar 

  19. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG . Calibration of two objective measures of physical activity for children. J Sports Sci 2008; 26: 1557–1565.

    Article  PubMed  Google Scholar 

  20. U.S. Centers for Disease Control and Prevention. Youth Risk Behavior Surveillance System (YRBSS, 2012. Available at www.cdc.gov/HealthyYouth/yrbs/.

  21. Lubans DR, Hesketh K, Cliff DP, Barnett LM, Salmon J, Dollman J et al. A systematic review of the validity and reliability of sedentary behaviour measures used with children and adolescents. Obes Rev 2011; 12: 781–799.

    Article  CAS  PubMed  Google Scholar 

  22. Schmitz KH, Harnack L, Fulton JE, Jacobs DR Jr, Gao S, Lytle LA et al. Reliability and validity of a brief questionnaire to assess television viewing and computer use by middle school children. J Sch Health 2004; 74: 370–377.

    Article  PubMed  Google Scholar 

  23. Currie C, Gabhainn SN, Godeau E, Roberts C, Smith R, Currie D et al (eds) Inequalities in Children’s Health: HBSC International Report from the 2005/2006 Survey. Health Policy for Children and Adolescents, No. 5. WHO Regional Office for Europe: Copenhagen, Denmark, 2008.

    Google Scholar 

  24. Vereecken CA, Maes L . A Belgian study on the reliability and relative validity of the Health Behaviour in School-Aged Children food-frequency questionnaire. Public Health Nutr 2003; 6: 581–588.

    Article  PubMed  Google Scholar 

  25. De Onis M, Onyyanga AW, Borghi E, Siyam A, Nishida C, Siekmann J . Development of a WHO growth reference for school-aged children and adolescents. Bull WHO 2007; 85: 660–667.

    PubMed  PubMed Central  Google Scholar 

  26. Kenward MG, Roger JH . Small sample inference for fixed effects from restricted maximum likelihood. Biometrics 1997; 53: 983–997.

    Article  CAS  PubMed  Google Scholar 

  27. Hirshkowitz M, Whiton K, Albert SM, Alessi C, Bruni O, DonCarlos L et al. National Sleep Foundation’s sleep time duration recommendations: methodology and results summary. Sleep Health 2015; 1: 40–43.

    Article  PubMed  Google Scholar 

  28. Schmid SM, Hallschmid M, Jauch-Chara K, Wilms B, Benedict C, Lehnert H et al. Short-term sleep loss decreases physical activity under free-living conditions but does not increase food intake under time-deprived laboratory conditions in healthy men. Am J Clin Nutr 2009; 90: 1476–1482.

    Article  CAS  PubMed  Google Scholar 

  29. Klingenberg L, Sjödin A, Holmbäck U, Astrup A, Chaput JP . Short sleep duration and its association with energy metabolism. Obes Rev 2012; 13: 565–577.

    Article  CAS  PubMed  Google Scholar 

  30. Williams SM, Farmer VL, Taylor BJ, Taylor RW . Do more active children sleep more? A repeated cross-sectional analysis using accelerometry. PLoS One 2014; 9: e93117.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Pesonen AK, Sjosten NM, Matthews KA, Heinonen K, Martikainen S, Kajantie E et al. Temporal associations between daytime physical activity and sleep in children. PLoS One 2011; 6: e22958.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Olds T, Ferrar KE, Gomersall SR, Maher C, Walters JL . The elasticity of time: associations between physical activity and use of time in adolescents. Health Educ Behav 2012; 39: 732–736.

    Article  PubMed  Google Scholar 

  33. Ekstedt M, Nyberg G, Ingre M, Ekblom Ö, Marcus C . Sleep, physical activity and BMI in six to ten-year-old children measured by accelerometry: a cross-sectional study. Int J Behav Nutr Phys Act 2013; 10: 82.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Shechter A, St-Onge MP . Delayed sleep timing is associated with low levels of free-living physical activity in normal sleeping adults. Sleep Med 2014; 15: 1586–1589.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Adamo KB, Wilson S, Belanger K, Chaput JP . Later bedtime is associated with greater daily energy intake and screen time in obese adolescents independent of sleep duration. J Sleep Disord Ther 2013; 2: 126.

    Article  Google Scholar 

  36. Burt J, Dube L, Thibault L, Gruber R . Sleep and eating in childhood: a potential behavioral mechanism underlying the relationship between poor sleep and obesity. Sleep Med 2014; 15: 71–75.

    Article  PubMed  Google Scholar 

  37. Kjeldsen JS, Hjorth MF, Andersen R, Michaelsen KF, Tetens I, Astrup A et al. Short sleep duration and large variability in sleep duration are independently associated with dietary risk factors for obesity in Danish school children. Int J Obes 2014; 38: 32–39.

    Article  CAS  Google Scholar 

  38. Hjorth MF, Chaput JP, Damsgaard CT, Dalskov SM, Michaelsen KF, Tetens I et al. Measure of sleep and physical activity by a single accelerometer: can a waist-worn Actigraph adequately measure sleep in children? Sleep Biol Rythms 2012; 10: 328–335.

    Article  Google Scholar 

Download references

Acknowledgements

We thank the ISCOLE External Advisory Board and the ISCOLE participants and their families who made this study possible. A membership list of the ISCOLE Research Group and External Advisory Board is included in Katzmarzyk et al. (this issue). ISCOLE was funded by The Coca-Cola Company.

Author information

Authors and Affiliations

  1. Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada

    J-P Chaput, A G LeBlanc & M S Tremblay

  2. Pennington Biomedical Research Center, Baton Rouge, LA, USA

    P T Katzmarzyk, T V Barreira, S T Broyles, G Hu & C Tudor-Locke

  3. University of Ottawa, Ottawa, Ontario, Canada

    A G LeBlanc

  4. Department of Exercise Science, University of Syracuse, Syracuse, NY, USA

    T V Barreira

  5. Department of Food and Environmental Sciences, University of Helsinki, Helsinki, Finland

    M Fogelholm

  6. St. Johns Research Institute, Bangalore, India

    R Kuriyan & A Kurpad

  7. Division of Exercise Science and Sports Medicine, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa

    E V Lambert & D E Rae

  8. Alliance for Research in Exercise Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia

    C Maher & T Olds

  9. CIFI2D, Faculdade de Desporto, University of Porto, Porto, Portugal

    J Maia

  10. Centro de Estudos do Laboratório de Aptidão Física de São Caetano do Sul (CELAFISCS), Sao Paulo, Brazil

    V Matsudo

  11. Department of Recreation Management and Exercise Science, Kenyatta University, Nairobi, Kenya

    V Onywera

  12. School of Medicine Universidad de los Andes, Bogota, Colombia

    O L Sarmiento

  13. Department for Health, University of Bath, Bath, UK

    M Standage

  14. Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA

    C Tudor-Locke

  15. Tianjin Women’s and Children’s Health Center, Tianjin, China

    P Zhao

Authors
  1. J-P Chaput
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P T Katzmarzyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A G LeBlanc
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M S Tremblay
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. T V Barreira
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. S T Broyles
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. M Fogelholm
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. G Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. R Kuriyan
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. A Kurpad
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. E V Lambert
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. D E Rae
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. C Maher
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. J Maia
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. V Matsudo
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. V Onywera
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. O L Sarmiento
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. M Standage
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. C Tudor-Locke
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. P Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. T Olds
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

for the ISCOLE Research Group

Corresponding author

Correspondence to J-P Chaput.

Ethics declarations

Competing interests

MF has received a research grant from Fazer Finland and has received an honorarium for speaking for Merck. AK has been a member of the Advisory Boards of Dupont and McCain Foods. RK has received a research grant from Abbott Nutrition Research and Development. VM is a member of the Scientific Advisory Board of Actigraph and has received an honorarium for speaking for The Coca-Cola Company. TO has received an honorarium for speaking for The Coca-Cola Company. The remaining authors declare no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chaput, JP., Katzmarzyk, P., LeBlanc, A. et al. Associations between sleep patterns and lifestyle behaviors in children: an international comparison. Int J Obes Supp 5 (Suppl 2), S59–S65 (2015). https://doi.org/10.1038/ijosup.2015.21

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ijosup.2015.21

This article is cited by

Search

Advanced search

Quick links