Purpose: To investigate potential time drift between devices when using Global Positioning Systems (GPS) and accelerometers in field-based research. Methods: Six Qstarz BT-Q1000XT GPS trackers, activPAL3 accelerometers, and ActiGraph GT3X+ and GT3X accelerometers were tested over 1–3 waves, each lasting 9–14 days. Once per day an event marker was created on each pair of devices concurrently. The difference in seconds between the time stamps for each event marker were calculated between each pair of GPS and activPAL devices and GPS and ActiGraph devices. Mixed-effects linear regression tested time drift across days and waves and between two rooms/locations (in an inner room vs. on a windowsill in an outer room). Results: The GPS trackers remained within one second of the computer clock across days and waves and between rooms. The activPAL devices drifted an average of 8.38 seconds behind the GPS devices over 14 days (p < .001). The ActiGraph GT3X+ devices drifted an average of 11.67 seconds ahead of the GPS devices over 14 days (p < .001). The ActiGraph GT3X devices drifted an average of 28.83 seconds behind the GPS devices over 9 days (p < .001). Time drift did not differ across waves but did differ between rooms and across devices. Conclusions: Time drift between the GPS and accelerometer models tested was minimal and is unlikely to be problematic when addressing many common research questions. However, studies that require high levels of precision when matching short (e.g., 1-second) time intervals may benefit from consideration of time drift and potential adjustments.
Chelsea Steel, Carolina Bejarano, and Jordan A. Carlson
Carolina M. Bejarano, Linda C. Gallo, Sheila F. Castañeda, Melawhy L. Garcia, Daniela Sotres-Alvarez, Krista M. Perreira, Carmen R. Isasi, Martha Daviglus, Linda Van Horn, Alan M. Delamater, Kimberly L. Savin, Jianwen Cai, and Jordan A. Carlson
Background: Total sedentary time and prolonged sedentary patterns can negatively impact health. This study investigated rates of various sedentary pattern variables in Hispanic/Latino youth. Methods: Participants were 956 youths (50.9% female) in the Hispanic Community Health Study/Study of Latinos Youth, a population-based cohort study of Hispanic/Latino 8- to 16-year-olds from 4 geographic regions in the United States (2012–2014). Total sedentary time and 10 sedentary pattern variables were measured through 1 week of accelerometer wear. Differences were examined by sociodemographic characteristics, geographic location, weekdays versus weekends, and season. Results: On average, youth were sedentary during 67.3% of their accelerometer wear time, spent 24.2% engaged in 10- to 29-minute sedentary bouts, and 7.2% in ≥60-minute bouts. 8- to 12-year-olds had more favorable sedentary patterns (less time in extended bouts and more breaks) than 13- to 16-year-olds across all sedentary variables. Sedentary patterns also differed by Hispanic/Latino background, with few differences across sex, household income, season, and place of birth, and none between weekdays versus weekends. Conclusions: Variables representing prolonged sedentary time were high among Hispanic/Latino youth. Adolescents in this group appear to be at especially high risk for unhealthy sedentary patterns. Population-based efforts are needed to prevent youth from engaging in increasingly prolonged sedentary patterns.