Background:
Lack of physical activity and more time spent in sedentary behavior are associated with obesity in youth. Moreover, reducing time spent in sedentary behaviors may actually reduce the risk for childhood obesity. Studies examining correlates of sedentary behavior in youth are much less common than those examining correlates of physical activity. In addition, studies of screen time typically examine factors associated with TV watching only or with total screen time (for example, combining TV watching and computer time). However, the correlates of TV watching may differ from those for computer use. Understanding these differences can inform the development of more effective interventions to reduce sedentary time.
Objectives:
This research used a population-based dataset to examine individual sociodemographic, family and environmental correlates of adolescent screen time. Time spent using the computer was examined separately from time spent watching TV and playing video games to determine whether the factors associated with each activity differ.
Methods:
Data were from the 2005 California Health Interview Survey (CHIS), a random-digit dial (RDD) telephone survey of 42,000 households drawn from every county in California. Analyses included responses from 4,029 adolescents ages 12-17. Adolescent responses to two questions were used to assess the amount of time spent watching TV/playing video games and using the computer for fun: 1) thinking about a typical Saturday or Sunday, about how many hours per day do you usually watch TV or play video games? and 2) about how many hours per day on a typical Saturday or Sunday do you use a computer for fun, not schoolwork? Multiple regression analyses were used to examine the association of individual sociodemographic, family and environmental characteristics with hours spent watching TV/playing video games and hours spent using a computer for fun. The following sociodemographic characteristics were included: age, gender, race/ethnicity (white, Latino, Asian, African American and American Indian) household income and adolescent work status. Family characteristics included parental education, parental nativity, parental work status, adult presence after school and parental knowledge of adolescent’s activities during free time. In addition, analyses included the number of days in the past week that adolescents were physically active for at least 60 minutes (0, 1-4, and 5 or more). Finally, neighborhood characteristics included urbanicity (urban, suburban and rural), parental perceptions of neighborhood safety, neighborhood income and neighborhood racial composition.
Results:
Adolescents spent an average of 2.9 hours watching TV or playing video games on a typical weekend day and spent an additional 1.6 hours using the computer for non-school activities. Adjusting for the sociodemographic, family and environmental characteristics mentioned above, the present analyses indicated several differences in the correlates of TV watching and computer use. Correlates of additional time spent watching television included male gender, American Indian and African American race, not participating in at least 60 minutes of physical activity on any of the previous seven days, not working in the previous year and parent educational attainment, with children of parents whose highest educational attainment was high school watching more TV than those whose parents were college graduates. Correlates of additional time spent using the computer for fun included older age, Asian race, higher household income, getting at least 60 minutes of physical activity on fewer than five of the previous seven days (compared to at lease five days), reporting that parents know little or nothing about free time activities, living in a predominantly non-white neighborhood and living in a higher-income neighborhood. Only the number of days that adolescents were physically active for at least 60 minutes was significantly associated with both hours spent watching TV and hours spent on the computer with fewer days of activity associated with more screen time. Presence of parent after school, parent nativity, parent work status, parent perceptions of neighborhood safety and urbanicity were not significantly associated with time spent in either sedentary behavior.
Conclusions:
The current results suggest that there are differences in the correlates of time spent watching TV and using the computer. Although sociodemographic and family factors were associated with both outcomes, the specific correlates of TV watching and computer use differed. In addition, some of the environmental characteristics examined in this study were associated with computer use, but none were associated with TV watching. Previous studies have not examined the correlates of different sedentary behaviors separately to determine differences in correlates. Reducing screen time is a potentially successful strategy in combating childhood obesity, and understanding differences in the correlates of different screen time behaviors can inform the development of more effective interventions to reduce sedentary time.
Support:
This work was supported by grants from the Robert Wood Johnson Foundation and The California Endowment.
