BACKGROUND AND PURPOSE: The main goal of this study was to address two questions: How is physical activity affected by sedentary behavior (computer, television, and commuting), and how are physical activity characteristics (intensity, frequency, type) different based on adolescents reports of physical activity? METHODS: The sample comprised 230 girls and 220 boys 14.6 years of age. Physical activity (PA) was assessed by questionnaire. Based on previously published standards, participants were grouped into the nonactive group, which included both sedentary and low active youth, and the active group, which included the moderately and vigorously active youth. Another questionnaire about leisure activities was applied to define the nature of PA. Sedentary behaviors, such as television viewing and computer use (weekday and weekend), and commuting to and from school (passive vs. active) were analyzed. RESULTS: Significantly more girls (p<or=.000) belonged to the inactive group (71.7%) than boys. The active participants reported being significantly more engaged in moderate intensity (49.1%; p<.000), moderate frequency (55.6%; p<.001), and team activities (62.0%; p<.005) than inactive participants. In addition, active participants reported significantly more participation in organized sports (21.6% vs. 5.2%) and in both activities (organized and individual activities; 45.5% vs. 3.9%) than nonactive counterparts. Our data show that active versus inactive groups did not differ on television watching on weekdays or on commuting. However, active participants were less likely to watch television on the weekends than inactive participants. Logistic regression showed that computer use during weekdays was a predictor of PA. An increase in computer use time (from 1 hr to 2-3 hr/day) was associated a higher PA. CONCLUSIONS: Sedentary behaviors such as television viewing or computer use might have different value in relation to PA for youth.
BACKGROUND AND PURPOSE: The main goal of this study was to address two questions: How is physical activity affected by sedentary behavior (computer, television, and commuting), and how are physical activity characteristics (intensity, frequency, type) different based on adolescents reports of physical activity? METHODS: The sample comprised 230 girls and 220 boys 14.6 years of age. Physical activity (PA) was assessed by questionnaire. Based on previously published standards, participants were grouped into the nonactive group, which included both sedentary and low active youth, and the active group, which included the moderately and vigorously active youth. Another questionnaire about leisure activities was applied to define the nature of PA. Sedentary behaviors, such as television viewing and computer use (weekday and weekend), and commuting to and from school (passive vs. active) were analyzed. RESULTS: Significantly more girls (p<or=.000) belonged to the inactive group (71.7%) than boys. The active participants reported being significantly more engaged in moderate intensity (49.1%; p<.000), moderate frequency (55.6%; p<.001), and team activities (62.0%; p<.005) than inactive participants. In addition, active participants reported significantly more participation in organized sports (21.6% vs. 5.2%) and in both activities (organized and individual activities; 45.5% vs. 3.9%) than nonactive counterparts. Our data show that active versus inactive groups did not differ on television watching on weekdays or on commuting. However, active participants were less likely to watch television on the weekends than inactive participants. Logistic regression showed that computer use during weekdays was a predictor of PA. An increase in computer use time (from 1 hr to 2-3 hr/day) was associated a higher PA. CONCLUSIONS: Sedentary behaviors such as television viewing or computer use might have different value in relation to PA for youth.
Authors: Jose A Serrano-Sanchez; Sara Martí-Trujillo; Angela Lera-Navarro; Cecilia Dorado-García; Juan J González-Henríquez; Joaquín Sanchís-Moysi Journal: PLoS One Date: 2011-09-01 Impact factor: 3.240