Spatial Classification of Youth Physical Activity Patterns

Rainham, Daniel; Bates, Christopher J.; Blanchard, Chris M.; Dummer, Trevor J.B.; Kirk, Sara F. L.; Shearer, Cindy

doi:10.1016/j.amepre.2012.02.011

Cited by 150 publications

(155 citation statements)

References 49 publications

Supporting

Mentioning

140

Contrasting

Unclassified

Order By: Relevance

“…It is worth noting that this study included a large proportion of participants recruited in rural areas. In comparison, previous Canadian studies have found that the contribution of AST to daily PA levels is lower in rural areas compared to suburban and urban areas (Pabayo et al, 2012b;Rainham et al, 2012).…”

Section: Relationships Of Active School Transport With Physical Activcontrasting

confidence: 65%

“…Further, many studies have consistently found higher rates of AST in urban areas (Mitra et al, 2010;Panter et al, 2010a); moreover, a study in Halifax (Nova Scotia) found that the contribution of active travel to daily MVPA was greater in adolescents living in urban and suburban areas compared to rural areas (Rainham et al, 2012). However, within Canadian census metropolitan areas, Seliske et al (2012) observed that adolescents aged 12-15 years were more likely to accumulate at least 30 minutes of active transportation per day in areas with larger urban sprawl, while no differences were observed among older adolescents.…”

Section: Built Environmentmentioning

confidence: 99%

See 1 more Smart Citation

Assessing the health-related outcomes and correlates of active transportation in children and youth

Larouche

2014

Appl. Physiol. Nutr. Metab.

View full text Add to dashboard Cite

show abstract

Section: Relationships Of Active School Transport With Physical Activcontrasting

confidence: 65%

Section: Built Environmentmentioning

confidence: 99%

Assessing the health-related outcomes and correlates of active transportation in children and youth

Larouche

2014

Appl. Physiol. Nutr. Metab.

View full text Add to dashboard Cite

show abstract

“…Most recent studies of the locational context of PA focus on identifying PA locations relative to key participant addresses (e.g., within a distance of home, work, or school) [43], use GIS databases that, while useful and informative for single-city studies, have variable availability and comparability for multi-city studies [44,45], or rely on self-reported destinations [46,47]. Further, most current studies ultimately include an Bother^category to capture locations that fall outside of predefined location categories without regard to the proportion of PA that may occur in these alternative locations [43,44].…”

Section: Discussionmentioning

confidence: 99%

Where Are Adults Active? An Examination of Physical Activity Locations Using GPS in Five US Cities

Holliday¹,

Howard

Emch³

et al. 2017

J Urban Health

View full text Add to dashboard Cite

Increasing physical activity (PA) at the population level requires appropriately targeting intervention development. Identifying the locations in which participants with various sociodemographic, body weight, and geographic characteristics tend to engage in varying intensities of PA as well as locations these populations underutilize for PA may facilitate this process. A visual location-coding protocol was developed and implemented in Google Fusion Tables and Maps using data from participants (N = 223, age 18-85) in five states. Participants concurrently wore ActiGraph GT1M accelerometers and Qstarz BT-Q1000X GPS units for 3 weeks to identify locations of moderate-to-vigorous (MVPA) or vigorous (VPA) bouts. Cochran-Mantel-Haenzel general association tests examined usage differences by participant characteristics (sex, age, race/ethnicity, education, body mass index (BMI), and recruitment city). Homes and roads encompassed >40% of boutbased PA minutes regardless of PA intensity. Fitness facilities and schools were important for VPA (19 and 12% of bout minutes). Parks were used for 13% of MVPA bout minutes but only 4% of VPA bout minutes. Hispanics, those without a college degree, and overweight/obese participants frequently completed MVPA bouts at home. Older adults often used roads for MVPA bouts. Hispanics, those with ≤high school education, and healthy/overweight participants frequently had MVPA bouts in parks. Applying a new location-coding protocol in a diverse population showed that adult PA locations varied by PA intensity, sociodemographic characteristics, BMI, and geographic location. Although homes, roads, and parks remain important locations for demographically targeted PA interventions, observed usage patterns by participant characteristics may facilitate development of more appropriately targeted interventions.

show abstract

“…Previous research assessing land use type of physical activity locations in youth suggests that nonhome and nonschool physical activity is spread across multiple land use types, including green spaces, streets, retail locations, and other residential locations. [14][15][16] Although a small amount of overall physical activity occurred near home and near school (ie, the home and school neighborhoods), these locations may be the most promising for intervention. This is because the proportion of location time spent in physical activity for the near-home and near-school locations, ∼10%, was higher than for the other 3 locations assessed.…”

Section: Figurementioning

confidence: 99%

“…Most previous studies investigating physical activity locations in youth have used self-report methods and focused primarily on the home or school, 12,13 with the exception of 2 Global Positioning System (GPS)-based studies conducted in Europe and 1 in Canada that may not generalize to the United States. [14][15][16] It is possible that different amounts of physical activity in specific locations account for some of the demographic differences often observed in youth physical activity, so understanding how locations relate to demographic differences in youth physical activity could inform location-specific intervention strategies to reduce health disparities.…”

mentioning

confidence: 99%

Locations of Physical Activity as Assessed by GPS in Young Adolescents

et al. 2016

View full text Add to dashboard Cite

To compare adolescents' physical activity at home, near home, at school, near school, and at other locations.METHODS: Adolescents (N = 549) were ages 12 to 16 years (49.9% girls, 31.3% nonwhite or Hispanic) from 447 census block groups in 2 US regions. Accelerometers and Global Positioning System devices assessed minutes of and proportion of time spent in moderate to vigorous physical activity (MVPA) in each of the 5 locations. Mixed-effects regression compared MVPA across locations and demographic factors. RESULTS:Forty-two percent of adolescents' overall MVPA occurred at school, 18.7% at home, 18.3% in other (nonhome, nonschool) locations, and 20.6% near home or school. Youth had 10 more minutes (30% more) of overall MVPA on school days than on nonschool days. However, the percentage of location time spent in MVPA was lowest at school (4.8% on school days) and highest near home and near school (9.5%-10.4%). Girls had 2.6 to 5.5 fewer minutes per day of MVPA than boys in all locations except near school. CONCLUSIONS:Although a majority of adolescents' physical activity occurred at school, the low proportion of active time relative to the large amount of time spent at school suggests potential for increasing school-based activity. Increasing time spent in the neighborhood appears promising for increasing overall physical activity, because a high proportion of neighborhood time was active. Increasing youth physical activity to support metabolic health requires strategies for increasing use of physical activity-supportive locations (eg, neighborhoods) and environmental and program improvements in unsupportive locations (eg, schools, homes).

show abstract

Spatial Classification of Youth Physical Activity Patterns

Cited by 150 publications

References 49 publications

Assessing the health-related outcomes and correlates of active transportation in children and youth

Assessing the health-related outcomes and correlates of active transportation in children and youth

Where Are Adults Active? An Examination of Physical Activity Locations Using GPS in Five US Cities

Locations of Physical Activity as Assessed by GPS in Young Adolescents

Contact Info

Product

Resources

About