Greater screen time is associated with adolescent obesity: a longitudinal study of the BMI distribution from Ages 14 to 18
Mitchell JA, Rodriguez D, Schmitz KH, Audrain-McGovern J
Obesity (Silver Spring, Md.) · 92 citas
Cómo se estudió
- Diseño
- Estudio de cohortes (indexado por PubMed)
- Estudiado en
- Personas
- Resultado principal
- Marcadores de salud y funcionamiento
Quién lo pagó
- Financiación
- Financiación independiente
- Gobierno
- National Institutes of Health
- Gobierno
- National Cancer Institute
- Gobierno
- NCI NIH HHS
- Subvenciones
- National Cancer Institute (R01 CA126958); National Cancer Institute (F32 CA162847); National Cancer Institute (RO1 CA126958)
Según 3 financiadores declarados y la declaración de financiación del texto completo.
Publicación
- Publicado
- 2013-03-01 · Obesity (Silver Spring) · vol. 21 · número 3 · págs. 572–575
- Editorial
- Wiley
- Citado
- 158 citas · más que el 100% de estudios similares · 51.4× el promedio de su campo
- Impacto
- Entre el 10 % más citado de su campo
- Referencias
- 16 trabajos
- Acceso
- Lectura gratuita
- Áreas de investigación
- Child Development and Digital Technology · Impact of Technology on Adolescents · Obesity, Physical Activity, Diet
- Palabras clave
- screen time, adolescent obesity, body mass index, BMI distribution, television viewing, video game use, adolescent overweight
- MeSH
- humans, obesity, body weight, body mass index, prevalence, longitudinal studies, motor activity, sleep, video games, television, adolescent, child, female, male, self report, sedentary behavior
4 autores
- Jonathan A. Mitchell🇺🇸 · autor de correspondenciaUniversity of Pennsylvania
- Daniel Rodriguez🇺🇸University of Pennsylvania
- Kathryn H. Schmitz🇺🇸University of Pennsylvania
- Janet E. Audrain-McGovern🇺🇸University of Pennsylvania
Resumen
El texto original del estudio, en el idioma en que se publicó.
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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