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

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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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