BACKGROUND: The objective of this study was to analyze associations of cardiorespiratory fitness (CRF) with physical activity, time spent watching television and using computer, mode of commuting to school (CS), and adiposity, by gender. METHODS: Participants were 1708 students (53.8% girls), aged 11 to 19 years. CRF was evaluated with a 20-meter shuttle-run test using VO2max by previously published equation. Maturation stages determined by Tanner's criteria, body mass index, and skinfolds were measured, and a questionnaire used to assess socioeconomic status, PA, television and computer time, and mode of CS. We conducted a regression analysis using CRF as the dependent variable. RESULTS: CRF was independent and positively associated with physical activity [β = 0.338 (95% CI = 0.119; 0.188); P < .001] and with maturation [β = -0.876 (95% CI = 0.666; 1.087); P < .001]; independent and negatively associated with television time [β = -0.003 (95% CI = -0.005; -0.002); P < .001] and adiposity [β = -0.068 (95% CI = -0.076; -0.060); P < .001]. CRF was positively associated with CS [β = 0.337; (95% CI = 0.014; 0.741); P = .014]. No associations were found for computer time. CONCLUSIONS: These findings suggest that increasing overall physical activity levels through interventions in different domains such as active CS, reducing sedentary activities, such as television time, might be effective strategies for improving CRF in youth.
BACKGROUND: The objective of this study was to analyze associations of cardiorespiratory fitness (CRF) with physical activity, time spent watching television and using computer, mode of commuting to school (CS), and adiposity, by gender. METHODS:Participants were 1708 students (53.8% girls), aged 11 to 19 years. CRF was evaluated with a 20-meter shuttle-run test using VO2max by previously published equation. Maturation stages determined by Tanner's criteria, body mass index, and skinfolds were measured, and a questionnaire used to assess socioeconomic status, PA, television and computer time, and mode of CS. We conducted a regression analysis using CRF as the dependent variable. RESULTS: CRF was independent and positively associated with physical activity [β = 0.338 (95% CI = 0.119; 0.188); P < .001] and with maturation [β = -0.876 (95% CI = 0.666; 1.087); P < .001]; independent and negatively associated with television time [β = -0.003 (95% CI = -0.005; -0.002); P < .001] and adiposity [β = -0.068 (95% CI = -0.076; -0.060); P < .001]. CRF was positively associated with CS [β = 0.337; (95% CI = 0.014; 0.741); P = .014]. No associations were found for computer time. CONCLUSIONS: These findings suggest that increasing overall physical activity levels through interventions in different domains such as active CS, reducing sedentary activities, such as television time, might be effective strategies for improving CRF in youth.