Background:
The use of digital technology such as mobile phones is ubiquitous in adolescents. However, excessive use may have adverse health effects, possibly partially mediated by disruptions to sleep.

Objective:
This study aims to assess the social predictors of digital technology use and their cross-sectional association with BMI z scores and being overweight in a large sample of adolescents.

Methods:
We used baseline data from a subset of a large adolescent cohort from 39 schools across Greater London who participated in the Study of Cognition, Adolescents and Mobile Phones (n=1473). Digital technology use included phone calls, internet use on mobile phones, and video gaming on any device. Multilevel regression was used to assess the associations between digital technology use and age-specific and sex-specific BMI z scores and being overweight (including obesity). Measurements were derived from height and weight, obtained by the Tanita BC-418 Body Composition Analyzer. We examined whether these associations were mediated by insufficient sleep.

Results:
Generally, participants with lower socioeconomic status reported more use of digital technology. Controlling for socioeconomic status, internet use on mobile phones for more than 3 hours per day was associated with higher BMI z scores (adjusted β=.30, 95% CI 0.11-0.48) and greater odds of being overweight (adjusted odds ratio 1.60, 95% CI 1.09-2.34), compared with low use (≤30 minutes). Similar associations were found between video gaming and BMI z scores and being overweight. The BMI z score was more strongly related to weekday digital technology use (internet use on mobile phones and video gaming) than weekend use. Insufficient sleep partly mediated the associations between digital technology use and BMI z scores (proportion of mediation from 8.6% to 17.8%) by an indirect effect.

Conclusions:
We found an association between digital technology use and BMI in adolescents, partly mediated by insufficient sleep, suggesting that the underlying mechanisms may be multifactorial. Further research with longitudinal data is essential to explore the direction of the relationships.