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Examining the Association Between Screen Time, Beverage and Snack Consumption, and Weight Status Among Eastern North
Kristie Hicks1, Stephanie Jilcott Pitts2, Suzanne Lazorick3
1lifestyle coach, Minority Diabetes Prevention Program; nutrition graduate assistant, Brody School of Medicine, East Carolina University, Greenville, North Carolina.
Abstract:
BACKGROUND With the rise in technology use for the adolescent population, screen time may be related to unhealthy eating habits and contribute to adolescent obesity. Since 2007, an adolescent wellness program, Motivating Adolescents to Choose Health (MATCH), has been implemented in select North Carolina middle schools.METHODS Using MATCH study data from fall 2015 in 26 North Carolina middle schools, we examined the cross-sectional associations between screen time, unhealthy beverage and snack consumption, and BMI z-score with linear regression models controlling for physical activity, school, sex, weight category, and race.RESULTS Of the 2,763 youth surveyed, half were female, 48% were white, 33% were black, and 19% were other racial groups; 2% were underweight, 51% were healthy weight, 21% were overweight, and 26% were obese. Mean BMI percentile was the 72nd percentile and mean BMI z-score was 0.81. The average of self-reported behaviors included: 1,312 hours of screen time per year, sugary beverages consumed 2,073 times per year, and unhealthy snacks consumed 3,485 times per year. There were positive associations between screen time per year and both sugary beverage (B = 0.4699; 95% Confidence Interval [CI], 0.3689-0.5709; P < .001), and unhealthy snack consumption per year (B = 1.0085; 95% CI, 0.8413-1.1757; P < .001), after controlling for significant covariates. This suggests that an extra hour of screen time a day is associated with approximately 172 extra servings of sugary beverages per year (3.3 extra servings per week, or 0.5 extra servings per day) and 368 extra servings of unhealthy snacks per year (7.1 extra servings per week, or 1 extra per day). No association was found with BMI z-score (B = -0.00001; 95% CI, -0.00007-0.00005; P = .697).LIMITATIONS The baseline survey questions did not differentiate between types of screen time, and self-reported data may have impacted results.CONCLUSION In North Carolina adolescents, increased screen time is associated with increases in both unhealthy beverage and snack consumption. Future research is needed to further elucidate how these factors and others impact BMI. MATCH may increase effectiveness by including program components that address the relationship between screen time and unhealthy dietary consumption.
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