Original Article

International Journal of Obesity (2013) 37, 1254–1260; doi:10.1038/ijo.2012.209; published online 8 January 2013


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

T Arora1,2, S Hussain1, K-B Hubert Lam3, G Lily Yao1, G Neil Thomas4,5 and S Taheri1,2

  1. 1Birmingham and Black Country NIHR CLAHRC, University of Birmingham, Birmingham, UK
  2. 2School of Experimental Medicine, University of Birmingham, Birmingham, UK
  3. 3Occupational and Environmental Medicine, University of Birmingham, Birmingham, UK
  4. 4Unit of Public Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham, UK
  5. 5Institute of Public Health, Social and Preventive Medicine, Mannheim Medical Faculty, Heidelberg University, Heidelberg, Germany

Correspondence: Dr S Taheri, NIHR CLAHRC Theme 8, University of Birmingham, Room 109, Public Health Building, Edgbaston, Birmingham, B15 2TT, UK. E-mail: staheri@me.com

Received 13 July 2012; Revised 30 October 2012; Accepted 8 November 2012
Advance online publication 8 January 2013

Editor's Note:

This paper evaluated the correlation of sleep time and of obesity with the use of four different types of devices at bedtime in a large series of adolescents in the United Kingdom. Bedtime use of cellphones, TV viewing, computers, and video gaming all correlated with decreased sleep time. Use of all technology types, with the exception of cellphones, was associated with increased BMI z-score. This is a cross-sectional study and correlation does not prove causation, but these findings point out the need for controlled longitudinal trials. These findings should also serve as an alert to parents/carers to consider limitation of such devices at bedtime, since this is unlikely to do any harm and may confer benefit by decreasing the risk of weight gain in adolescents.





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.



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.



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).



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.


adolescence; sleep; technology use

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