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Adolescent Physical Activity And The Built Environment: A Latent Class Analysis Approach, Kelsey Mcdonald, Mary Hearst, Kian Farbakhsh, Carrie Patnode, Ann Forsyth, John Sirard, Leslie Lytle
Adolescent Physical Activity And The Built Environment: A Latent Class Analysis Approach, Kelsey Mcdonald, Mary Hearst, Kian Farbakhsh, Carrie Patnode, Ann Forsyth, John Sirard, Leslie Lytle
John Sirard
This study used latent class analysis to classify adolescent home neighborhoods (n=344) according to built environment characteristics, and tested how adolescent physical activity, sedentary behavior, and screen time differ by neighborhood type/class. Four distinct neighborhood classes emerged: 1) low-density retail/transit, low walkability index (WI), further from recreation; 2) high-density retail/transit, high WI, closer to recreation; 3) moderate-high-density retail/transit, moderate WI, further from recreation; and 4) moderate-low-density retail/transit, low WI, closer to recreation. We found no difference in adolescent activity by neighborhood class. These results highlight the difficulty of disentangling the potential effects of the built environment on adolescent physical activity.
Comparison Of Three Measures Of Physical Activity And Associations With Blood Pressure, Hdl And Body Composition In A Sample Of Adolescents, Mo Hearst, John Sirard, La Lytle, Dr Dengel, D Berrigan
Comparison Of Three Measures Of Physical Activity And Associations With Blood Pressure, Hdl And Body Composition In A Sample Of Adolescents, Mo Hearst, John Sirard, La Lytle, Dr Dengel, D Berrigan
John Sirard
Background—The association of physical activity (PA), measured three ways, and biomarkers were compared in a sample of adolescents. Methods—PA data were collected on two cohorts of adolescents (N=700) in the Twin Cities, Minnesota, 2007–2008. PA was measured using two survey questions (Modified Activity Questionnaire (MAQ)), the 3-Day Physical Activity Recall (3DPAR), and accelerometers. Biomarkers included systolic (SBP) and diastolic blood pressure (DBP), lipids, percent body fat (%BF) and body mass index (BMI) percentile. Bivariate relationships among PA measures and biomarkers were examined followed by generalized estimating equations for multivariate analysis. Results—The three measures were significantly correlated with each other (r=0.22–0.36, …