In this large, nationally representative, longitudinal cohort, weekly hours of screen time during adolescence independently and significantly predicted incident obesity in early adulthood. Fewer weekly hours of screen time during adolescence reduced the relative odds of incident obesity by over 40% among females and over 20% among males. Contrary to our hypothesis, longitudinal patterns of physical activity were less important predictors of incident obesity. Our results suggest that physical activity, if not maintained, may not be protective in the long-term and may not counteract the negative effects of screen time during adolescence and over time. Declines in screen time during the transition from adolescence to young adulthood were associated with lower obesity incidence, particularly for females, but not enough to overcome the obesity-promoting effects of screen time during adolescence. Our longitudinal results, including stronger results for females [35
], are consistent with other studies summarized in a recent literature review [16
] and in other recent studies showing a positive relationship between sedentary behavior and body weight [15
] and no longitudinal relationship between physical activity and obesity [36
], although existing literature is inconsistent.
In contrast, our cross sectional analysis suggests a strong protective association between physical activity and prevalent obesity for adolescent males, while both physical activity and screen time were important factors for adolescent females. This protective cross-sectional association between physical activity and obesity is not observed longitudinally, perhaps because such associations are diminished by other important lifestyle changes occurring during this lifecycle period [51
]. Gordon-Larsen et al. showed a positive relationship between physical activity and incident obesity among adolescents between Waves I and II of Add Health [52
], which is consistent with this explanation because it studied a one year follow-up period in contrast with the five year period assessed in the current study. Additionally, as noted in the Must and Tybor review [16
], cross-sectional associations may reflect causal effects of physical activity patterns on obesity, but they could also reflect limited capacity to engage in exercise or sports due to extreme obesity, lack of social support for overweight or obese adolescents, or weight loss efforts.
In females, the likelihood of obesity peaked at two to three MVPA bouts per week, perhaps reflecting reverse causality as described above or inaccurate reporting of MVPA. Those engaging in two or three bouts of MVPA may have been more likely to exercise for weight loss or maintenance and hence at greater risk of obesity. Alternatively, reporting two or three bouts may reflect over-reporting to a greater extent than those with high MVPA frequency; that is, due to social desirability, those with no MVPA may over-report within a reasonable range, resulting in high obesity prevalence and incidence in this MVPA range.
For females, reduced screen time was associated with a greater relative reduction of a larger absolute obesity incidence than for males (13% for males versus 16% for females), resulting in a greater potential impact of screen time on obesity incidence. Assuming no change in screen time, experimentally assigning low versus high screen time led to predicted obesity incidence of approximately 14% and 18%, respectively (a 3 to 4 percentage point difference) for females and 12% and 14% (a 1 to 2 percentage point difference) for males. These results underscore the potential public health impact of reducing screen time during adolescence on controlling obesity incidence in females in particular.
The association between screen time and incident obesity may differ by sex due to biologic differences in changes in energy expenditure in response to screen time, in the effects of other lifestyle factors, misclassification biases by sex, or, more likely, a combination of all three. Biologic differences such as differential reductions in metabolic rate while engaging in sedentary activity are not evident in clinical research, but these studies are often limited to young children or include only one sex [29
]. Other lifestyle factors such as changes in energy intake related to television viewing [27
] or concurrent activities while watching television or videos could also differ between males and females. Similarly, as hypothesized by Dunstan et al. [54
], screen time may be an indicator of sedentary behaviors in general, including activities such as computer use or reading, to a greater extent in females than males. Unfortunately, we are not able to quantify energy intake or overall energy expenditure in Add Health, so we were unable to investigate this issue. Recent studies in adult populations have demonstrated stronger associations between television viewing and metabolic risk factors in women than men [54
], suggesting that this difference is not spurious and reflects important sex differences in the influence of screen time on obesity and obesity-related conditions. In addition, findings point to questions regarding assessment of screen time.
Regardless of the mechanism or whether it is a direct relationship – increased "junk food" consumption in response to advertisements, deflated metabolic rate, or some other factor – these results suggest that adolescent females who watch less television and videos during adolescence and/or reduce their viewing time from adolescence to young adulthood are less likely to develop obesity as they become young adults, regardless of their physical activity level. Thus, reducing screen time during adolescence is likely an essential component of obesity prevention, particularly for females. Furthermore, the level of screen time at which obesity odds were reduced in this study are consistent with the American Academy of Pediatrics recommendation [57
] of 14 or fewer hours of television viewing per week in pediatric populations.
There are some limitations of the current study. As noted above, we could not assess energy intake, and activity data are subject to self-report bias. Misclassification is probably most dramatic among obese respondents reporting more socially desirable behavior, which would have attenuated the association between screen time and physical activity with obesity. For the same reason, those becoming obese between Waves II and III may have underreported screen time and/or over-reported physical activity to a greater extent at Wave III; this differential misclassification would have also attenuated the observed association between changes in these behaviors and Wave III incident obesity.
Second, the activity recall may not have captured all MVPA performed by respondents, and the "bouts" of activity classification is imprecise because each bout could be of any duration. Both of these factors would be expected to reduce precision and further dilute the apparent influence of physical activity. Furthermore, MVPA bouts may more accurately reflect physical activity level during adolescence, when more easily recalled organized sports practices and competitions are more common; this bias could potentially explain the lack of association between physical activity in young adulthood as well as stronger association with screen time, which may be more accurately reported, than physical activity. Finally, unmeasured factors related to both screen time and obesity such as an awareness of healthful behaviors could have contributed to these findings.