• Katelyn M Holliday, Annie Green Howard, Michael Emch, Daniel A Rodríguez, Wayne D Rosamond, and Kelly R Evenson.
• Department of Epidemiology, University of North Carolina, 137 E. Franklin Street, Suite 306, Chapel Hill, NC, 27514, USA. khausman@email.unc.edu.
• J Urban Health. 2017 Aug 1; 94 (4): 459469459-469.

AbstractIncreasing 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 bout-based 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.

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