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Pediatrics

Exploring the complex pathways among specific types of technology, self-reported sleep duration and body mass index in UK adolescents

International Journal of Obesity volume 37, pages 1254–1260 (2013)Cite this article

Subjects

Abstract

Objective:

To examine the independent associations between sleep duration, four technology types (computer use, mobile telephones, TV viewing and video gaming) and body mass index (BMI) z-score. We propose a theoretical path model showing direct effects of four technology types on BMI z-score and sleep duration as well as the indirect effects of each technology on BMI z-score while considering sleep duration as a mediator.

Methods:

Consenting adolescents (n=632; 63.9% girls, aged 11–18 years) were recruited to the Midlands Adolescent Schools sleep Education Study. The School Sleep Habits Survey (SSHS) and Technology Use Questionnaire (TUQ) were administered. Objective measures of height (cm) and weight (kg) were obtained for BMI z-score calculation.

Results:

Weekday use of all technology types was significantly associated with reduced weekday sleep duration after adjustment (β (computer use)=−0.38, P<0.01; β (mobile telephone)=−0.27, P<0.01; β (TV viewing)=−0.35, P<0.01; and β (video gaming)=−0.39, P<0.01). Use of all technology types, with the exception of mobile telephones, was significantly associated with increased BMI z-score after adjustment (β (computer use)=0.26, P<0.01; β (TV viewing)=0.31, P<0.01; and β (video gaming)=0.40, P<0.01). Our path model shows that weekday sleep duration was significantly and negatively associated with BMI z-score (β=−0.40, P<0.01).

Conclusion:

Weekday sleep duration potentially mediates the effects of some technologies on BMI z-score. If confirmed, improving sleep through better management of technology use could be an achievable intervention for attenuating obesity.

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References

  1. Foundation NS. Sleep in America Poll2006 19 June 2012. Available from: http://www.sleepfoundation.org/sites/default/files/2006_summary_of_findings.pdf.

  2. Foundation NS. Sleep in America Poll2011 19 June 2012. Available from: http://www.sleepfoundation.org/sites/default/files/sleepinamericapoll/SIAP_2011_Summary_of_Findings.pdf.

  3. Carskadon MA . Patterns of sleep and sleepiness in adolescents. Pediatrician 1990; 17: 5–12.

    CAS  PubMed  Google Scholar 

  4. Calamaro CJ, Yang K, Ratcliffe S, Chasens ER . Wired at a young age: the effect of caffeine and technology on sleep duration and body mass index in school-aged children. J Pediatr Health Care 2012; 26: 276–282.

    Article  Google Scholar 

  5. Tynjala J, Kannas L, Valimaa R . How young Europeans sleep. Health Educ Res 1993; 8: 69–80.

    Article  CAS  Google Scholar 

  6. Yen CF, Ko CH, Yen JY, Cheng CP . The multidimensional correlates associated with short nocturnal sleep duration and subjective insomnia among Taiwanese adolescents. Sleep 2008; 31: 1515–1525.

    Article  Google Scholar 

  7. Weaver E, Gradisar M, Dohnt H, Lovato N, Douglas P . The effect of presleep video-game playing on adolescent sleep. J Clin Sleep Med 2010; 6: 184–189.

    PubMed  PubMed Central  Google Scholar 

  8. Rehbein F, Kleimann M, Mossle T . Prevalence and risk factors of video game dependency in adolescence: results of a German nationwide survey. Cyberpsychol Behav Soc Netw 2010; 13: 269–277.

    Article  Google Scholar 

  9. Van den Bulck J . Adolescent use of mobile phones for calling and for sending text messages after lights out: results from a prospective cohort study with a one-year follow-up. Sleep 2007; 30: 1220–1223.

    Article  Google Scholar 

  10. Munezawa T, Kaneita Y, Osaki Y, Kanda H, Minowa M, Suzuki K et al. The association between use of mobile phones after lights out and sleep disturbances among Japanese adolescents: a nationwide cross-sectional survey. Sleep 2011; 34: 1013–1020.

    Article  Google Scholar 

  11. Wood B, Rea MS, Plitnick B, Figueiro MG . Light level and duration of exposure determine the impact of self-luminous tablets on melatonin suppression. Appl Ergon 2012; 44: 237–240.

    Article  Google Scholar 

  12. Achab S, Nicolier M, Mauny F, Monnin J, Trojak B, Vandel P et al. Massively multiplayer online role-playing games: comparing characteristics of addict vs non-addict online recruited gamers in a French adult population. BMC Psychiatry 2011; 11: 144.

    Article  Google Scholar 

  13. 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 

  14. 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  Google Scholar 

  15. Taheri S, Lin L, Austin D, Young T, Mignot E . Short sleep duration is associated with reduced leptin, elevated ghrelin, and increased body mass index. PLoS Med 2004; 1: e62.

    Article  Google Scholar 

  16. Chaput JP, Despres JP, Bouchard C, Tremblay A . Short sleep duration is associated with reduced leptin levels and increased adiposity: results from the Quebec family study. Obesity (Silver Spring) 2007; 15: 253–261.

    Article  CAS  Google Scholar 

  17. Spiegel K, Tasali E, Penev P, Van Cauter E . Brief communication: sleep curtailment in healthy young men is associated with decreased leptin levels, elevated ghrelin levels, and increased hunger and appetite. Ann Intern Med 2004; 141: 846–850.

    Article  Google Scholar 

  18. Gupta NK, Mueller WH, Chan W, Meininger JC . Is obesity associated with poor sleep quality in adolescents? Am J Hum Biol 2002; 14: 762–768.

    Article  Google Scholar 

  19. Calamaro CJ, Park S, Mason TB, Marcus CL, Weaver TE, Pack A et al. Shortened sleep duration does not predict obesity in adolescents. J Sleep Res 2010; 19: 559–566.

    Article  Google Scholar 

  20. Knutson KL, Lauderdale DS . Sleep duration and overweight in adolescents: self-reported sleep hours versus time diaries. Pediatrics 2007; 119: e1056–e1062.

    Article  Google Scholar 

  21. de Jong E, Visscher TL, Hirasing RA, Heymans MW, Seidell JC, Renders CM . Association between TV viewing, computer use and overweight, determinants and competing activities of screen time in 4- to 13-year-old children. Int J Obes (Lond) 2011.

  22. Lazarou C, Soteriades ES . Children’s physical activity, TV watching and obesity in Cyprus: the CYKIDS study. Eur J Public Health 2010; 20: 70–77.

    Article  Google Scholar 

  23. Rey-Lopez JP, Ruiz JR, Vicente-Rodriguez G, Gracia-Marco L, Manios Y, Sjostrom M et al. Physical activity does not attenuate the obesity risk of TV viewing in youth. Pediatr Obes 2012; 7: 240–250.

    Article  CAS  Google Scholar 

  24. Berkey CS, Rockett HR, Field AE, Gillman MW, Frazier AL, Camargo CA et al. Activity, dietary intake, and weight changes in a longitudinal study of preadolescent and adolescent boys and girls. Pediatrics 2000; 105: E56.

    Article  CAS  Google Scholar 

  25. Maddison R, Foley L, Ni Mhurchu C, Jiang Y, Jull A, Prapavessis H et al. Effects of active video games on body composition: a randomized controlled trial. Am J Clin Nutr 2011; 94: 156–163.

    Article  CAS  Google Scholar 

  26. Piovesan C, Padua MC, Ardenghi TM, Mendes FM, Bonini GC . Can type of school be used as an alternative indicator of socioeconomic status in dental caries studies? A cross-sectional study. BMC Med Res Methodol 2011; 11: 37.

    Article  Google Scholar 

  27. Wolfson AR, Carskadon MA, Acebo C, Seifer R, Fallone G, Labyak SE et al. Evidence for the validity of a sleep habits survey for adolescents. Sleep 2003; 26: 213–216.

    Article  Google Scholar 

  28. Ness AR . The Avon Longitudinal Study of Parents and Children (ALSPAC)--a resource for the study of the environmental determinants of childhood obesity. Eur J Endocrinol 2004; 151 (Suppl 3): U141–U149.

    Article  CAS  Google Scholar 

  29. Wing YK, Li SX, Li AM, Zhang J, Kong AP . The effect of weekend and holiday sleep compensation on childhood overweight and obesity. Pediatrics 2009; 124: e994–e1000.

    Article  Google Scholar 

  30. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH . Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000; 320: 1240–1243.

    Article  CAS  Google Scholar 

  31. Dworak M, Schierl T, Bruns T, Struder HK . Impact of singular excessive computer game and television exposure on sleep patterns and memory performance of school-aged children. Pediatrics 2007; 120: 978–985.

    Article  Google Scholar 

  32. Ivarsson M, Anderson M, Akerstedt T, Lindblad F . Playing a violent television game does not affect saliva cortisol. Acta Paediatr 2009; 98: 1052–1053.

    Article  CAS  Google Scholar 

  33. Barf RP, Desprez T, Meerlo P, Scheurink AJ . Increased food intake and changes in metabolic hormones in response to chronic sleep restriction alternated with short periods of sleep allowance. Am J Physiol Regul Integr Comp Physiol 2012; 302: R112–R117.

    Article  CAS  Google Scholar 

  34. Brondel L, Romer MA, Nougues PM, Touyarou P, Davenne D . Acute partial sleep deprivation increases food intake in healthy men. Am J Clin Nutr 2010; 91: 1550–1559.

    Article  CAS  Google Scholar 

  35. Nedeltcheva AV, Kilkus JM, Imperial J, Kasza K, Schoeller DA, Penev PD . Sleep curtailment is accompanied by increased intake of calories from snacks. Am J Clin Nutr 2009; 89: 126–133.

    Article  CAS  Google Scholar 

  36. Al-Disi D, Al-Daghri N, Khanam L, Al-Othman A, Al-Saif M, Sabico S et al. Subjective sleep duration and quality influence diet composition and circulating adipocytokines and ghrelin levels in teen-age girls. Endocr J 2010; 57: 915–923.

    Article  CAS  Google Scholar 

  37. Hitze B, Bosy-Westphal A, Bielfeldt F, Settler U, Plachta-Danielzik S, Pfeuffer M et al. Determinants and impact of sleep duration in children and adolescents: data of the Kiel Obesity Prevention Study. Eur J Clin Nutr 2009; 63: 739–746.

    Article  CAS  Google Scholar 

  38. Chaput JP, Tremblay A . Acute effects of knowledge-based work on feeding behavior and energy intake. Physiol Behav 2007; 90: 66–72.

    Article  CAS  Google Scholar 

  39. Chaput JP, Drapeau V, Poirier P, Teasdale N, Tremblay A . Glycemic instability and spontaneous energy intake: association with knowledge-based work. Psychosom Med 2008; 70: 797–804.

    Article  Google Scholar 

  40. Chaput JP, Visby T, Nyby S, Klingenberg L, Gregersen NT, Tremblay A et al. Video game playing increases food intake in adolescents: a randomized crossover study. Am J Clin Nutr 2011; 93: 1196–1203.

    Article  CAS  Google Scholar 

  41. Bellisle F, Dalix AM, Slama G . Non food-related environmental stimuli induce increased meal intake in healthy women: comparison of television viewing versus listening to a recorded story in laboratory settings. Appetite 2004; 43: 175–180.

    Article  CAS  Google Scholar 

  42. Chen MY, Wang EK, Jeng YJ . Adequate sleep among adolescents is positively associated with health status and health-related behaviors. BMC Public Health 2006; 6: 59.

    Article  Google Scholar 

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Acknowledgements

We are grateful to all the participating adolescents. All authors are affiliated to the University of Birmingham. The study received funding from Action Medical Research, Aim Higher, the Heart of England Foundation Trust and the University of Birmingham. Drs Taheri, Yao and Hussain received funding from the National Institute for Health Research (NIHR) through the Collaborations for Leadership in Applied Health Research and Care for Birmingham and Black Country (CLAHRC-BBC) programme. The views expressed in this publication are not necessarily those of the NIHR, the Department of Health, NHS Partner Trusts, University of Birmingham or the CLAHRC-BBC Theme 8 Steering Group. We thank Mona Campbell at the Heart of England Foundation Trust for excellent management support for the project. Participating schools were Ashby School, Bishop Vesey’s Grammar School, Hamstead Hall, Highclare School, Repton School and Sutton Coldfield Grammar School for Girls. We thank all teaching staff for their support, in particular Jane Taylor, Trudi Young, William Potter, Claire Horne, Lawrence Sneary, Ken Morris, Suzanne Gray and Dr Dawn Edwards. We also thank all parents who agreed for their children to participate and students who assisted with the project. This was not an industry-supported study.

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Authors and Affiliations

  1. Birmingham and Black Country NIHR CLAHRC, University of Birmingham, Birmingham, UK

    T Arora, S Hussain, G Lily Yao & S Taheri

  2. School of Experimental Medicine, University of Birmingham, Birmingham, UK

    T Arora & S Taheri

  3. Occupational and Environmental Medicine, University of Birmingham, Birmingham, UK

    K-B Hubert Lam

  4. Unit of Public Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham, UK

    G Neil Thomas

  5. Institute of Public Health, Social and Preventive Medicine, Mannheim Medical Faculty, Heidelberg University, Heidelberg, Germany

    G Neil Thomas

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Correspondence to S Taheri.

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Arora, T., Hussain, S., Hubert Lam, KB. et al. Exploring the complex pathways among specific types of technology, self-reported sleep duration and body mass index in UK adolescents. Int J Obes 37, 1254–1260 (2013). https://doi.org/10.1038/ijo.2012.209

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