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Background We examined the associations between screen time and adolescent obesity and the associations of reallocating screen time to other activities using isotemporal substitution models. Understanding the association between screen time and obesity may provide additional insights into effective obesity prevention strategies in adolescents. Methods We conducted a cross-sectional analysis of 5,180 adolescents (4th and 7th grade students) from the Korean Children and Youth Panel Survey 2018. Participants reported their height, weight, and average time spent watching television, using computer, using smartphone, and other after-school activities. Obesity was defined as BMI-for-age and -sex ≥ 95th percentile based on the 2017 Korean National Growth Charts. We performed multivariable logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between screen time and obesity prevalence, adjusting for potential confounders. Results Prolonged smartphone use (≥ 180 vs. <60 m/d: OR [95% CI] = 2.75 [2.06, 3.68]) was associated with a higher obesity prevalence. Television watching (≥ 120 vs. <60 min/d) was positively associated with obesity prevalence among 4th grade students (2.09 [1.51, 2.89]) but the association was not observed among 7th grade students (0.97 [0.63, 1.49]). One-hour increments of any non-screen time activities, with a simultaneous 1-hour decrease in combined screen time, were associated with a lower obesity prevalence (physical activity: 0.75 [0.65, 0.85]; sleeping: 0.69 [0.62, 0.78]; hanging out with friends: 0.80 [0.71, 0.89]; reading: 0.82 [0.69, 0.97]; studying: 0.84 [0.78, 0.90]; chatting with parents: 0.89 [0.88, 0.98]). Conclusions Our data suggest that public health strategies that reduce screen time and increase time for non-screen time activities, such as physical activity, may be effective in lowering adolescent obesity prevalence.
Background We examined the associations between screen time and adolescent obesity and the associations of reallocating screen time to other activities using isotemporal substitution models. Understanding the association between screen time and obesity may provide additional insights into effective obesity prevention strategies in adolescents. Methods We conducted a cross-sectional analysis of 5,180 adolescents (4th and 7th grade students) from the Korean Children and Youth Panel Survey 2018. Participants reported their height, weight, and average time spent watching television, using computer, using smartphone, and other after-school activities. Obesity was defined as BMI-for-age and -sex ≥ 95th percentile based on the 2017 Korean National Growth Charts. We performed multivariable logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between screen time and obesity prevalence, adjusting for potential confounders. Results Prolonged smartphone use (≥ 180 vs. <60 m/d: OR [95% CI] = 2.75 [2.06, 3.68]) was associated with a higher obesity prevalence. Television watching (≥ 120 vs. <60 min/d) was positively associated with obesity prevalence among 4th grade students (2.09 [1.51, 2.89]) but the association was not observed among 7th grade students (0.97 [0.63, 1.49]). One-hour increments of any non-screen time activities, with a simultaneous 1-hour decrease in combined screen time, were associated with a lower obesity prevalence (physical activity: 0.75 [0.65, 0.85]; sleeping: 0.69 [0.62, 0.78]; hanging out with friends: 0.80 [0.71, 0.89]; reading: 0.82 [0.69, 0.97]; studying: 0.84 [0.78, 0.90]; chatting with parents: 0.89 [0.88, 0.98]). Conclusions Our data suggest that public health strategies that reduce screen time and increase time for non-screen time activities, such as physical activity, may be effective in lowering adolescent obesity prevalence.
Background Studies have shown that prolonged television watching increases obesity risk among children. However, few studies examined the associations with other types of screen time, such as computer and smartphone use, using a prospective cohort study design. Further, little is known about the specific non-screen time activity that may yield the most benefits when reallocating screen time to other activities. Methods We conducted a prospective cohort analysis using 3-year follow-up data from the Korean Children and Youth Panel Survey 2018 (n = 2,023; 4th grade elementary students who were not obese at baseline). Average time spent watching television, using computer and smartphone, and other after-school activities were self-reported at baseline. Weight and height were also self-reported at baseline and follow-up surveys through 2021. We performed multivariable logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between screen time and obesity incidence, adjusting for potential confounders. We also performed isotemporal substitution models to examine the associations of reallocating screen time to other non-screen time activities (physical activity, sleeping, hanging out with friends, reading, studying, and chatting with parents) in an equal time-exchange manner. Results Longer combined screen time (≥ 240 vs. <120 m/d) was statistically significantly associated with an increased obesity risk (OR [95% CI] = 1.68 [1.03, 2.73]). The direction of associations with television watching (≥ 180 vs. <60 m/d: OR [95% CI] = 2.86 [1.58, 5.20]), computer use (≥ 120 vs. <60 m/d: 1.38 [0.52, 3.64]), and smartphone use (≥ 180 vs. <60 m/d: 1.42 [0.76, 2.65]) were all positive, although the association was most apparent and statistically significant for television watching only. The associations did not change after additional adjustment for other lifestyle factors, including physical activity, sleep, and breakfast skipping. In the isotemporal substitution models, reallocating 1-hour of screen time to reading (OR [95% CI] = 0.67 [0.48, 0.93]) was associated with a decreased obesity risk. Reallocating 1-hour of screen time to physical activity was only marginally significantly associated with obesity risk (0.79 [0.62, 1.01]). Conclusions Our data suggest that more efforts should focus on reducing screen time and increasing time for other non-screen time activities, particularly reading, for obesity prevention in children.
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