BACKGROUND: Physical activity is an essential element in reducing the prevalence of obesity, but much is unknown about the intensity and location of physical activity among youth-this is important because adolescent health behaviors are predictive of behaviors in adults. PURPOSE: This study aims to identify the locations where youth moderate-to-vigorous physical activity (MVPA) occurs, and to examine how MVPA varies according to urbanicity (urban, suburban, rural). METHODS: Participants included adolescent students (N=380, aged 12-16 years) from Halifax, Nova Scotia. Locations of MVPA were measured using accelerometers and GPS data loggers for up to 7 days. Specialized software was developed to integrate and process the data. Frequencies of MVPA by location were determined, and differences in MVPA were assessed for association with urbanicity. RESULTS: Active commuting accounted for the largest proportion of time in MVPA among urban and suburban students. Rural students achieved most MVPA at school. Other residential locations, shopping centers, and green spaces accounted for a majority of the remaining MVPA. Minutes in MVPA varied significantly overall (196.6 ± 163.8, 84.9 ± 103.2, 81.7 ± 98.2); at school (45.7 ± 45.2, 18.6 ± 28.0, 29.8 ± 39.7); while commuting (110.3 ± 107.1, 31.5 ± 55.2, 19.5 ± 39.7); and at other activity locations (19.7 ± 27.1, 14.8 ± 26.8, 12.0 ± 22.1) and by urbanicity. CONCLUSIONS: Findings reveal that the journeys between locations are as important as home and school settings in contributing to greater MVPA in adolescent youth. The relative importance of context as a contributor to MVPA varies with urbanicity. Combining actimetry and GPS data provides a precise link between physical activity measurements and contexts of the built environment.
BACKGROUND: Physical activity is an essential element in reducing the prevalence of obesity, but much is unknown about the intensity and location of physical activity among youth-this is important because adolescent health behaviors are predictive of behaviors in adults. PURPOSE: This study aims to identify the locations where youth moderate-to-vigorous physical activity (MVPA) occurs, and to examine how MVPA varies according to urbanicity (urban, suburban, rural). METHODS:Participants included adolescent students (N=380, aged 12-16 years) from Halifax, Nova Scotia. Locations of MVPA were measured using accelerometers and GPS data loggers for up to 7 days. Specialized software was developed to integrate and process the data. Frequencies of MVPA by location were determined, and differences in MVPA were assessed for association with urbanicity. RESULTS: Active commuting accounted for the largest proportion of time in MVPA among urban and suburban students. Rural students achieved most MVPA at school. Other residential locations, shopping centers, and green spaces accounted for a majority of the remaining MVPA. Minutes in MVPA varied significantly overall (196.6 ± 163.8, 84.9 ± 103.2, 81.7 ± 98.2); at school (45.7 ± 45.2, 18.6 ± 28.0, 29.8 ± 39.7); while commuting (110.3 ± 107.1, 31.5 ± 55.2, 19.5 ± 39.7); and at other activity locations (19.7 ± 27.1, 14.8 ± 26.8, 12.0 ± 22.1) and by urbanicity. CONCLUSIONS: Findings reveal that the journeys between locations are as important as home and school settings in contributing to greater MVPA in adolescent youth. The relative importance of context as a contributor to MVPA varies with urbanicity. Combining actimetry and GPS data provides a precise link between physical activity measurements and contexts of the built environment.
Authors: Andrea Chircop; Cindy Shearer; Robert Pitter; Meaghan Sim; Laurene Rehman; Meredith Flannery; Sara Kirk Journal: Health Promot Int Date: 2013-08-14 Impact factor: 2.483
Authors: Donna Spruijt-Metz; Cheng K Fred Wen; Brooke M Bell; Stephen Intille; Jeannie S Huang; Tom Baranowski Journal: Am J Prev Med Date: 2018-08-19 Impact factor: 5.043
Authors: Thomas R Kirchner; Jennifer Cantrell; Andrew Anesetti-Rothermel; Ollie Ganz; Donna M Vallone; David B Abrams Journal: Am J Prev Med Date: 2013-10 Impact factor: 5.043
Authors: Natalie Colabianchi; Claudia J Coulton; James D Hibbert; Stephanie M McClure; Carolyn E Ievers-Landis; Esa M Davis Journal: Health Place Date: 2014-01-24 Impact factor: 4.078
Authors: Christopher Johansen; Kim D Reynolds; Jennifer Wolch; Jason Byrne; Chih-Ping Chou; Sarah Boyle; Donna Spruijt-Metz; Brianna A Lienemann; Susan Weaver; Michael Jerrett Journal: J Phys Act Health Date: 2020-05-27
Authors: Sandy J Slater; Lisa Nicholson; Jamie Chriqui; Dianne C Barker; Frank J Chaloupka; Lloyd D Johnston Journal: Am J Prev Med Date: 2013-02 Impact factor: 5.043