Greater screen time is associated with adolescent obesity: A longitudinal study of the BMI distribution from Ages 14 to 18

Authors

  • Jonathan A. Mitchell,

    Corresponding author
    1. Department of Biostatistics and Epidemiology, University of Pennsylvania, 423 Guardian Drive, Blockley Hall, Philadelphia, PA 19104, USA
    • Department of Biostatistics and Epidemiology, University of Pennsylvania, 423 Guardian Drive, Blockley Hall, Philadelphia, PA 19104, USA

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  • Daniel Rodriguez,

    1. Department of Psychiatry, University of Pennsylvania, 3535 Market St, Suite 4100, Philadelphia, PA 19104, USA
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  • Kathryn H. Schmitz,

    1. Department of Biostatistics and Epidemiology, University of Pennsylvania, 423 Guardian Drive, Blockley Hall, Philadelphia, PA 19104, USA
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  • Janet Audrain-McGovern

    1. Department of Psychiatry, University of Pennsylvania, 3535 Market St, Suite 4100, Philadelphia, PA 19104, USA
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  • Disclosure: No conflicts of interest to declare.

  • Funding agencies: This study was supported by National Cancer Institute RO1 CA126958 (Audrain-McGovern).

Abstract

Objective:

Previous research has examined the association between screen time and average changes in adolescent body mass index (BMI). Until now, no study has evaluated the longitudinal relationship between screen time and changes in the BMI distribution across mid to late adolescence.

Design and Methods:

Participants (n = 1,336) were adolescents who were followed from age 14 to age 18 and surveyed every 6 months. Time spent watching television/videos and playing video games was self-reported (<1 h day−1, 1 h day−1, 2 h day−1, 3 h day−1, 4 h day−1, or 5+ h day−1). BMI (kg m−2) was calculated from self-reported height and weight. Longitudinal quantile regression was used to model the 10th, 25th, 50th, 75th, and 90th BMI percentiles as dependent variables. Study wave and screen time were the main predictors, and adjustment was made for gender, race, maternal education, hours of sleep, and physical activity.

Results:

Increases at all the BMI percentiles over time were observed, with the greatest increase observed at the 90th BMI percentile. Screen time was positively associated with changes in BMI at the 50th (0.17, 95% CI: 0.06, 0.27), 75th (0.31, 95% CI: 0.10, 0.52), and 90th BMI percentiles (0.56, 95% CI: 0.27, 0.82). No associations were observed between screen time and changes at the 10th and 25th BMI percentiles.

Conclusions:

Positive associations between screen time and changes in the BMI at the upper tail of the BMI distribution were observed. Therefore, lowering screen time, especially among overweight and obese adolescents, could contribute to reducing the prevalence of adolescent obesity.

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